Society of Objects : Designing the Social Internet of Things

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GRADUATION PROJECT Society Of Objects Designing the Social Internet of Things Sponser : Self-sponsered Volume : 1 STUDENT : NAMRATA PRIMLANI PROGRAMME : Master of Design (M.Des)

GUIDE : DR. JIGNESH KHAKHAR

2019 IT INTERGRATED DESIGN FACULTY (NEW MEDIA DESIGN)

National Institute of Design Ahmedabad



The Evaluation Jury recommends NAMRATA PRIMLANI for the Graduation of the National Institute of Design IT INTEGRATED (NEW MEDIA DESIGN)

herewith, for the project titled “SOCIETY OF OBJECTS: DESIGNING THE SOCIAL INTERNET OF THINGS” on fulfilling the further requirements by

Chairman Members :

*Subsequent remarks regarding fulfilling the requirements :

Registrar(Academics)


Originality Statement I hereby declare that this submission is my own work and it contains no full or substantial copy of previously published material, or it does not even contain substantial proportions of material which have been accepted for the award of any other degree or diploma of any other educational institution, except where due acknowledgment is made in this diploma project. Moreover I also declare that none of the concepts are borrowed or copied without due acknowledgment. I further declare that the intellectual content of this Graduation Project is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged. This graduation project (or part of it) was not and will not be submitted as assessed work in any other academic course. Student Name in Full: Namrata Primlani Signature: Date:



Copyright Statement I hereby grant the National Institute of Design the right to archive and to make available my graduation project/thesis/dissertation in whole or in part in the Institutes’s Knowledge Management Centre in all forms of media, now or hereafter known, subject to the provisions of the Copyright Act. I have either used no substantial portions of copyright material in my document or I have obtained permission to use copyright material. Student Name in Full: Namrata Primlani Signature: Date:



Namrata Primlani, 2019. Graduation project for the Master of Design,W New Media Design. National Institute of Design, India. Guided by Dr. Jignesh Khakhar.


Society of Objects Designing the Social Internet of Things


CONTENTS 1

2

3

4

Introduction

Outline

Internet of Things

Society of Objects at Wipro

1.1. Acknowledgements 1.2. About National Institute of Design 1.3. About New Media Design

2.1. 2.2. 2.3. 2.4. 2.5.

3.1. Definitions 3.2. Social Web of Things

4.1. Wipro Technovation Center 4.2. Ethnographic Research at Technovation Center 4.3 Introduction to Conversational Interfaces 4.4. Concept Development 4.5. Identifying Touchpoints and Use Cases 4.6. Prototyping 4.7. Reflections

9 Bibliography and References 9.1. Bibliography and References 9.2. Image References

Abstract Motivation Initial Brief Project Scope Project Timeline


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6

7

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Speculative IoT

Technological Explorations

Design and Technology

Conclusion

5.1. What is Speculative Design? 5.2. Speculative IoT - The Motivation 5.3. The Curious Case of the Gossiping Objects 5.4. Data and the IoT 5.5. Inside the Smart Home 5.6. Gossip in the Society of Objects 5.7. Turing Chatterbox 5.8. Redefining the brief 5.9. Concept Note

6.1. 6.2. 6.3. 6.4. 6.5. 6.6.

7.1. Designing Object Template 7.2. Designing Intents 7.3. Designing object-to-object interactions 7.4. Designing human-to-object interactions 7.5. Designing the artefacts 7.6. Affordances for the Internet of Things 7.7. Designing the space 7.8. Model Construction 7.9. Designing Conversation

8.1. Conclusion

Markov Chains Conversational Agents Natural Language APIs Network Topology 3D Printing Hardware



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Introduction 1.1. Acknowledgements 1.2. About National Institute of Design 1.3. About New Media Design


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1.1. Acknowledgements I would like to thank my Project Guide Dr. Jignesh Khakhar for his guidance throughout the course and his constant support and dedication towards this project.

I acknowledge the contribution of all my colleagues at the WIpro Technovation Center, without whom this project would never have got off the ground.

I thank Arshad Bhai for offering his expretise in electronics and hardware, Shantanu for his invaluable help with the software.

I would like to thank Shreeyash Saunkhe, my partner in crime and Aalok Jaiswal, an unlikely mentor who made my time at Wipro all the more enriching.

I would like to thank Piyush Bhai and Haresh Bhai for their help with 3D printing.

I would like to thank Abhishek Khedekar, Poornima Marh, Suraj Vijay and Nidhin Bose for their help with the Model Consturction, Photography, Videography and Documentation of this project. I am grateful to all my batchmates from the New Media Design Batch of 2014 for their motivation. Last but not the least, I thank my family for their constant support throughout this endeavour.


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1.2. About National Institute of Design The National Institute of Design is India’s foremost design institute. Having played a vital role in the advancement of Indian design, NID is often characterized by its ties to Indian cultural and historic practices. In NID’s 3 main campuses at Ahmedabad, Gandhinagar and Bangalore, students from varied backgrounds and disciplines congregate and collaborate in a highly interdisciplinary environment, under the guidance of the premiers of design education in India. NID’s approach to the design process is explorative, with students often choosing their topic of interest and improvising their own methodologies and individual processes within the academic requirements. The Institute fosters a community of young designers with the skills and knowledge to take on interesting design challenges as well as the ethical sensibility to present themselves as the vanguards of the future of design.

[1] http://www.nid.edu.

On April 7, 1958, the Eameses presented the India Report to the Government of India. The Eames Report defined the underlying spirit that would lead to the founding of NID and beginning of design education in India. The Report recommended a problem-solving design consciousness that linked learning with actual experience and suggested that the designer could be a bridge between tradition and modernity. The Report called upon future designers to reexamine the alternatives of growth available to the country at that time. [1] This vision of NID acknowledges that higher education in design will have greater responsibilities to meet the needs of society both in India and abroad. The institute aims to become a repository of design knowledge, experience and information on products, systems, materials, design and production processes related to traditional as well as modern technologies.


Fig 1.1. National Institute of Design. The NID Post Graduate campus at Gandhinagar, Gujarat.

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1.3. About New Media Design New Media [2] attempts to examine the impact that technologies may have on mankind in the future. The thoughtful and appropriate application of technology at an individual, organizational and national level can lead to significant economic benefits, while being aware of its cultural impact. Through a historical grounding in art, craft and design practices; surveying of scientific and technology landscape of the world; and building an ability to keenly observe the cultural fabric of the country, students of new media (should) develop integrated and context relevant solutions for addressing contemporary issues.

Contemporary practice and study of new media is at the intersection of art, craft, science, technology and design. In this sense the programme is truly transdisciplinary. Students of new media design should be capable of creating associations / cross linkages across the fields of art, science, technology and design. They should be able to function in situations where lack of definition persists, and define their own practices and grounds, informed through practice and research.

There are three primary objectives of the programme. Exploring/ critically examining the relationship between technology and culture. Gaining competency in judging the appropriate application of technology. Developing insights leading to the invention of new technology.

[2] New Media Design Programme Information. Available at: http://www.nid.edu/education/master-design/new-media-design/p-overview.html. (Accessed: 12 May 2017).


Fig 1.2. Lively Up Yourself!. An interactive installation designed by students of the New Media Design Program for the Story of Light Festival in Panaji, Goa.

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Outline 2.1. 2.2. 2.3. 2.4. 2.5.

Abstract Motivation Initial Brief Project Scope Project Timeline


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2.1. Abstract In an age where computers are shrinking in size, sensing is cheap and data abundant, the author investigates the concept commonly known as the Internet of Things. The author dissects the Internet of Things from social, cultural, economic, technological, political and ethical standpoints. Through prototypes, the author attempts to gain insight into how the Internet of Things technology is intertwined with social, cultural, ethical and political aspects of human life and how the technology gains relevance when viewed from these perspectives.


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2.2. Motivation There have been many attempts to define the Internet of Things. Perhaps the most well known is Mark Weiser’s vision of Ubiquitous Computing. In his seminal paper “The Computer for the 21st Century”, Weiser presents a world in which computers weave themselves seamlessly into the fabric of our lives, fading into the background and blending in with our environment.[3] Weiser’s vision is romantic. Most modern day attempts at defining the Internet of Things seem to have misplaced his sense of wonder. Modern definitions tag the Internet of Things as a group of connected sensors and actuators that transmit and receive data via the internet. The technicalities of this so called Internet of Things is the focus of much work. There have been few attempts to bend, stretch or otherwise deform this definition. The task therefore, is not to come up with new applications for the Internet of Things, neither to attempt any technical breakthrough but rather to re-examine the Internet of Things, to dissect it from new angles, to observe it from unexplored perspectives, and perhaps redefine it in new lights.

[3] Weiser, Mark. "The Computer for the 21 st Century." Scientific american 265.3 (1991): 94-105.


The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it. -Mark Weiser

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2.3. Initial Brief The initial brief was to undertake a study of the Internet of Things with a focus on the Social Internet of Things. The Internet of Things was to be studied from social, cultural, political, ethical and technological standpoints. The design of the Social Internet of Things, in particular, was to be taken into consideration, including addressing concepts such as mental models, user interfaces, interactions and affordances in the context of the Internet of Things.


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2.4. Project Scope The author studies the concept of the Smart Home, research related to the production and use of domestic technologies and also discussions surrounding ethics and privacy in the smart home, gender and the smart home and the relation between gender, gossip and society in the Internet of Things. Artifical Intelligence, chatbots and Natural Language are some of the technological concepts explored through prototypes. In relation to design, the concepts of mental models, affordances, signifiers, chatbot design, scriptwriting, interaction and interface design and speculative design are employed.


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2.5. Project Timeline

2016 June

June July

JulyAugust

August September

2016 September October

October November

November December

December January

January February

Secondary Research - Internet of Things Secondary Research - Internet of Things and Social IoT and Social IoT Primary Research, Model, Primary Research, System Model,System Concept Note Concept Note Prototype Prototype 1, Use Cases 1, Use Cases

Seconda


2017

2017 February March

MarchApril

April May

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May June

June July

JulyAugust

August September

September October

October November

Secondary ResearchIoT, - Speculative Ethics and Privacy, Smart Home, Gender, Gossip, Artificial Intelligence ary Research - Speculative IoT Ethics IoT, and IoT Privacy, Smart Home, Gender, Gossip, Artificial Intelligence Design and Technology Design and Technology Prototyping, Concept Prototype Development, Prototyping, Concept Development, 2 Prototype 2 DocumentationDocumentation

Fig 2.1. Project Timeline. The timeline depicting the process followed over the 18 month duration of the project.

Nove



3

Internet of Things 3.1. Definitions 3.2. Social Web of Things


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3.1. Definitions “The worldwide network of interconnected objects uniquely addressable based on standard communication protocols.[4]“ “The IoT is a giant network of connected “things” (which also includes people). The relationship will be between people-people, people-things, and things-things.[5]” “A global network infrastructure, linking physical and virtual objects through the exploitation of data capture and communication capabilities.[6]”

“Everything is present, physically in the real world, in your home, your work, your car, or worn around your body. This means that it can receive inputs from your world and transform those into data which is sent onto the Internet for collection and processing. So your chair might collect information about how often you sit on it and for how long, while the sewing machine reports how much thread it has left and how many stitches it has sewn.[8]”

“Things having identities and virtual personalities operating in smart spaces using intelligent interfaces to connect and communicate within social, environmental, and user contexts.[7]”

[4] Bassi, A. and Horn, G., 2008. Internet of Things in 2020: A Roadmap for the Future. European Commission: Information Society and Media, 22, pp.97-114. [5] Morgan, J. 2016, A Simple Explanation Of ‘The Internet Of Things’, Available at: https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/#6f6770ef1d09 (Accessed 12 April 2018). [6] Casagras, R.F.I.D., 2011. the inclusive model for the Internet of Things report. EU Project, (216803), pp.16-23. [7] Bassi, A. and Horn, G., 2008. Internet of Things in 2020: A Roadmap for the Future. European Commission: Information Society and Media, 22, pp.97-114. [8] McEwen, Adrian, and Hakim Cassimally. Designing the internet of things. John Wiley & Sons, 2013.


Fig 3.1. An Equation for the Internet of Things. A simple formula for describing the Internet of Things.

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3.2. Social Web of Things In the User Experience Lab at Ericsson Research, designers were attempting to create a GUI for the Internet of Things. Two of the hurdles they encountered were to do with scalability and understandability. While networks of connected objects can scale enormously, people’s mental models of networks do not scale. An underlying discrepancy in people’s mental model of a network was unearthed through a simple exercise. Participants were asked to draw a network. Consistently, participants drew the network as a ‘series of point-to-point’ connections as opposed to the ‘ continuous dynamic many-to-many interrelations’ that the designers were aiming to capture through their GUI. The vestigial cable seems to be the only available symbol for depicting connection between devices.

“The thing is that this particular discrepency between mental model (inherited from the analog ancestor, the Cable) and concept (such as an Internet of Things) is valid only when looking at technological networks. The Nature or social relations are examples of other heterogenous eco-system-like networks which we understand differently.[9]”

[9] Formo, J. 2012, A Social Web of Things, Available at: https://www.ericsson.com/strategicdesign/2012/04/a-social-web-of-things/ (Accessed 22 October 2017).


Fig 3.2. A painting of my home network (in progress). By Karin Dalziel.

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Human Beings understand, rather intuitively, social relationships and social networks much better than we understand technology. The marriage of the social with the technical is where Ericsson “Social Web of Things” seems to have hit the mark. By “dressing up” the IoT as a social network of objects, the designers solved both the problem of the missing mental model as well as the problem of scalability. Sound mental models are often established by good metaphors. The metaphor of a social network fits nicely with the dynamic nature of the IoT. The model also scales well, both in people’s conception of social networks as well as in practical implementation.


Fig 3.3. How to design a ‘social’ internet of things? Things that talk, but how? The internet of things is going to provide us with a whole new data stream. But how will these things ‘communicate’ with us?.

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Fig 3.4. The Social Web of Things interface. Things talk to each other in text-based Natural Language. Things post messages and updates on the Social Web of Things wall.


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Now that we have networks of smart things that leverage data to work in tandem with each other, it is important that we are able to interact with these networks. This is where design comes into play, to address aspects such as mental models, user experience and user interface. The Social Internet of Things emerges as a subset of the Internet of Things in which the smart things in the network display outward human-like social conversational behaviours. ‘Things’ can now be added as ‘friends’ on a hybrid human-object social platform. These things can post messages, status updates, comment, like and converse with each other and with human beings through Natural Language Conversations. We are now entering an era where human beings and their devices will speak the same language. The technical difficulties - security, device-compatibility, transfer protocols of such a network are of course important concerns. But the design of interactions between us and our smart devices will be necessary to establish the ubiquity of these networks in our daily lives.


Fig 3.5. Friends - My things. Things can be added as friends in the Social Web of Things interface.

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Fig 3.6. How to design a ‘social’ internet of things? Things that talk, but how?



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Society of Objects at Wipro

4.1. 4.2. 4.3. 4.4. 4.5. 4.6. 4.7.

Wipro Technovation Center Ethnographic Research at Technovation Center Introduction to Conversational Interfaces Concept Development Identifying Touchpoints and Use Cases Prototyping Reflection


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4.1. Wipro Technovation Centre From June to December 2016, I worked as a Design Intern at Wipro’s Technovation Centre. It was here that my work on the internet of things began. Much of the initial secondary research was done here and the seeds of an idea gradually began to develop. Inspired by Ericsson’s work on the Social Internet of Things, Social Web of Things, I set myself about the task of developing a Social Web of Things-like solution centered around Wipro’s Technovation center.

About Wipro Wipro Ltd is a global information technology, consulting and outsourcing company based in Bengaluru, India.[10]

Technovation Center Wipro’s Technovation Centre is an interactive experience centre in Wipro’s Chief Technology Office. The Centre showcases Proof-ofConcept prototypes focused on emerging technologies such as Ubiquitous Enterprise, Artificial Intelligence, Augmented Reality, Gestural Interfaces and Immersive Experiences. The objective of the centre is to engage clients in a personalized experience of future technologies in the context of Business enterprise. [11]

[10] http://www.wipro.com/india/ [11] http://www.wipro.com/wipro-tv/experience-tomorrows-technology-today/


Fig 4.1. Wipro Headquarters in Bengaluru.

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4.1.1. Structure of Technovation Center Client Visits The key function of the technovation center is to serve as an Experience Center for the Wipro’s work on emerging technologies. Client Visits occur daily at an average of about two to three visits per day.

Visits Team The Visits team receives the clients and walks them through the experience center. The visits team is responsible for scheduling visits, preparing for the visit by visitor profiles and presenting the installations to the clients.

Tech Team The Visits team receives the clients and walks them through the experience center. The visits team is responsible for scheduling visits, preparing for the visit by visitor profiles and presenting the installations to the clients.


Fig 4.2. Structure of Technovation Center. To attend to daily Client Visits, The Technovation Center was organized into four key groups, namely the Visits Team, Tech Team, Design and Hospitality.

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4.1.2. Wipro HOLMES HOLMES stands for Heuristic and Ontological based Machine Learning and Experiential Systems. HOLMES is Wipro’s crowning glory, their answer to IBM’s Watson, an artificial intelligence system equipped with machine learning, natural language processing and pattern recognition.

[12] http://www.wipro.com/holmes/.

HOLMES is highly adaptable. He can be fed large data sets and his behaviour can be adapted based on the context of use. Therefore, unlike Watson, HOLMES can be personalized for each enterprise based on the particularities of their requirement. Some of the scenarios in which HOLMES prowess has been displayed include identifying cracks in tunnels using image recognition and generating organizational heirarchy structures by analyzing text. In house, HOLMES is deployed throughout WIPRO as a Natural Language based ticketing agent.[12]


Fig 4.3. WIPRO HOLMES. HOLMES is an artificial intelligence system equipped with Natural Language capabilities, Logical Reasoning, Learning and Knowledge Virtualization.

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4.1.3 The Neo-Reality Project The Neo-Reality project was an ongoing project at Wipro’s Technovation Center. The Neo-Reality Core was envisioned as a scalable IOT core to which ‘n’ number of devices could be connected. The vision was to control the lights, ambient temperature, various sensors, as well as receive status and health checks of the installations in Technovation Center from a central interface. Wipro was also keen that the Neo Reality Interface be showcased to visitors and clients.

The vision was of a Technovation Center 2.0 which would be a space where devices and sensors form a network, all working towards improving the visitor experience. Here was an Internet of Things scenario being applied to a real context. Unlike Ericsson’s Social Web of Things which was centered around the home, the context for this network would be the workplace. I wondered if I could draw inspiration from Ericsson’s work and apply it at the Technovation Center.


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4.1.4. The Problem with Neo-Reality The Neo-Relity project, although ambitious, lacked a key element of good design - the project did not consider the users of the system. Unfortunately, the Neo-Reality project was being designed to be operated by experts, leaving the key stakeholders - the visits team and the tech team out of the picture. The interface being developed had such a steep learning curve that novice users would be unable to learn it with relative ease.

The disregard for users of the Neo-reality system got me thinking about the IoT and user interfaces. My attempts to search for user interfaces for the IoT yielded almost no interesting results. Almost all the examples I found were mobile applications or graphic screen based interfaces. But in the Internet of Physical Things, using a GUI with physical objects seemed counter-intuitive to me. David Rose’s enchanted objects and certain ambient displays did offer an alternative. But almost no one except Ericsson had addressed user’s mental models and interfaces for the IoT. Had no one thought about connecting users to the Internet of Things? To address the gap in the Neo-Reality project, I would first have to understand it’s users. After some goading, I was given the go-ahead to conduct a short Ethnographic Study at the Technovation Center. With much excitement and little expectation, the week of research was underway.


Fig 4.4. The Gap in the Neo-Reality Project. Non-expert users couldn’t use the interface.

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Fig 4.5. An interface for the Neo-Reality Project. A conversational interface to bridge the gap between the users and the smart devices.


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4.2. Ethnographic Research at Technovation Center The Ethnographic study was conducted for a period of one week at Technovation Center. The group chosen for this study was the Visits Team at Technovation Center. Research techniques involved the following :

The study reflected the daily activities of the group including difficulties and hurdles faced during tasks, task pitfalls and workarounds group cohesion, communication mechanisms, personal goals and ambitions.

1. Participant Observations : The researcher engaged actively in the everyday activities of the chosen social group. The researcher moved from passive observer to active participant in the group activities. 5 Participant Observations were conducted for this study which was expressed through field notes, insights and opportunities.

The Social Group consists of 8 members. 5 members of the visits team, 2 members of the tech team and one member of the hospitality department. These members were chosen as they played the key roles in organizing and conducting the daily activities of the Technovation Centre including scheduling, planning and conducting Client Visits, testing installations and ensuring the smooth operation of the centre.

2. Long Interviews : 3 Long interviews were conducted. The Interviews were transcribed and coded to find significant categories, phrases and words. The interviews were presented in the form of anonymous quotations, insights and observations.


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Fig 4.6. The Social Group.


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4.2.1. Observations and Quotations 4.2.1.1. Previsit Timeline : > 1 week before visit

Process Flow 1. There are different verticals that are divided among 4 members. 2. Team members are pre­assigned to Business Units (BU). 3. Visits team receives call from BU stating the name and date of client visit. 4. BU members are sent a form in which information about client visits i.e. name of the client, which department, who is arranging the visit from Wipro, their designations, purpose of visit. 5. This information is updated in the calendar (excel sheet) which is shared with all team members. 6. Team members get tagged in the excel sheet based on the assigned BU and the concerned team member takes up the task. 7. Team members conduct background research. They have discussions to understand the client and context of visit. Team members decide which solutions to showcase based on research.

Observations 1. Team members are always updated with the schedule and details of visits. 2. Although the solutions to be shown are pre­-decided, the order of presentation and who is going to be presenting are not decided. These details are left to the last minute which may cause confusion. 3. Testing of solutions is not provided sufficient time and hence causes confusion and issues during the visit.


Quotations “How can I take this existing same solution put a little bit of a spin. Now we have this retail kiosk how ... will I show this retail kiosk to a Telecom service provider.. same solution this is extremely important...We have to keep doing that ...that’s a challenge but that’s also a process because I cannot refresh solutions everyday” “Based on the BU which we have been assigned it gets tagged to us”

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“All of them are like regularly attached to that calendar (Excel Sheet) so whenever some changes happen, we immediately get to know. So all of them all Technovation all 4­5 people of us... everyone will get that notification. “ “...whatever is the visit for today I will have to ensure that whatever is the experience journey we have created for them, what is the message of that particular each of the solution , how have we positioned it ...” “We are supposed to test them before showing them to the client but we do not get enough time “


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4.2.1.2. Just before visit

Observations

TImeline ( 15 minutes before visit)

1. Who is going to be presenting which solution is decided only 1 hour­15 minutes before the visit. This leaves very little time for preparation, testing etc. 2. It is not properly defined who owns responsibility of the solutions. 3. Order of showcase is not decided in advance. This causes confusion on the floor. 4. Agenda Sheet can be leveraged to organize all aspects of the visit and provide a run through just before the visit. 5. Dry runs are only performed for certain visits­not all. 6. Demos are supposed to be tested before hand but team does not always get the time to test everything. 7. Task of testing is left up to support team. 8. Team may not receive updates about working condition of solutions until the last moment. At this point, non­-working solutions become cause for confusion as the agenda changes.

Process Flow 1. Agenda is already set (ppt). 2. In case of important client, a dry run may happen. 3. The controller has access to server and displays the agenda on the screen. 4. Depending on the solutions to be shown and the availability of people it is decided who will be doing what. The roles are assigned between 1 hour to 15 minutes before the visit.


Quotations “Everyone knows which client is coming because it is there in the calendar. But we may not necessarily know what we are showing” “We have already set the agenda. There is a ppt and it is updated every time. The people inside have access to that.” “maybe just before the visit an hour or to minimum 15 minutes also (decide who is going to present). Ideally we should do that prior to that as in it should be ready on that visit but I don’t think we are that that much proactive we are supposed to do that”

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“There are lot of variables lot of the networks which they access also there are lots of restrictions ...So for different demos you need different networks .Basically for every demo there are lot of variables and many things can go wrong You need to know a lot of things and need to remember lots of things” “The entire process is not very automated or you can say properly channelized. So if you can use the same data let’s say agenda sheet is there so if I fill it properly we can understand what can be the sequence of things we are going to show so which demos are going to be shown at which location so which people “ “They are supposed to do it but it is not happening. That’s we are facing these problems” “See it’s not very properly defined who owns the visit, who owns the solutions”


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4.2.1.3. Visit TImeline ( 1 hour )

Process Flow 1. Visit typically lasts 1 hour. 2. Visit can start from some other place in the Wipro Campus ( EBC, ODC etc.) 3. BU members will be accompanying the client from start to end of visit. 4. Team members will be sitting inside. When they receive news that the client has arrived either from BU members or security guard, they come out to receive the client. 5. Hall of Fame is where the context is set. The names and company names of clients are displayed here. The client is introduced to Technovation Center. 6. Agenda Sheet has what solutions and demos that are going to be shown.

7. Floor Projection is shown. 8. Clients are taken to Immersive Zone. 9. Video will be shown. 10. Team members discuss at the back, what will be shown next (sequence not decided in advance ) and whether everything is working. 11. Applications are shown such as Street Shopper, Assure Health. 12. Holographic JCB is shown 13. Clients are escorted to Lab Area 14. Field Assist solutions is shown among other solutions 15. Holmes is presented. 16. Client have short discussion, give feedback and leave.


Quotations “Visit can start from some other place ” “There is a agenda sheet. There is a screen where the agenda is shown so it has like what are the solutions or demos we are going to show it to them. So we have it over there but I have never seen anybody discussing or showing it explaining that so it is just” “Some of the issues is with respect to the infrastructure, I believe, the operations part of the Technovation Center, for instance sometimes solutions will not work as expected because of some constraints or maybe due to outdated technology ” “See once there is an issue happening you don’t have a choice , right you can’t really show it to the customer so that’s where the coordination comes into picture on the stage that’s a kind of a tactical thing then we have to go back and find out why did this happen...” “There are some applications where you need a lot of interaction. ..So depending on what solutions we are showing and what is the availability of people we then decide who is going to do what” “I have seen that the entire thing is not properly designed or properly understood and planned kind of thing. So there are lot of these demos are there so the list is very long and no one has like a full idea of what demos are there and what are not.”

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“Predominantly the major issues what we see is with respect to the schedules all those things. Typically in a day we have 5 visits back to back and any slippage on one of the customers will have an impact on all other customers always a half an hour gap between visits.. in spite of all these things we have two customer want to come in at the same time these is at the peak these are all the operations things this is everyday kind of an affair” “Receiving we don’t do anything special as such. We are sitting there inside...we might come out and wait. So once the client comes, the security guard might come and say the client has come, so we come out... So there isn’t much formality. “ “ Actually I don’t like this lab area Because of discussions and all people might get disturb” “ Usually the client have their own agenda and the internal people have their own time table...half an hour or one hour they also get delayed . some discussion happens and the time gets extended ” “The client will be sitting on the sofa and the internal people depending on the relationship with the client if they are high rank they might sit with them if they are little low rank they might stand” “The demos which they have designed and loaded they are also not very stable so they might crash anytime”


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Observations Team communication 1. Body language, gestures, eye contact, verbal cues are used to communicate between team members and the presenter. 2. It was observed that team members and presenter were communicating via gestures and mouthing words in the middle of a presentation and in view of the client. 3. Team members form groups while presentation is in progress to discuss the order of solutions and bugs, solutions not working. 4. Team members run back and forth between presenter and control booth to discuss order of solutions, next solution to be presented, status of solution. 5. Immersive area appears crowded and busy. Sound of footsteps is amplified by glass floor and hence create noise. A lot of movement, hustle and bustle and frantic discussions by teammates. 6. Control booth is used as a base station. Team members who are not presenting stand there, discuss, engage in casual conversation.

7. Control booth has six monitors out of which currently two were observed to be in use. One with view of the lobby, second with view of immersive zone screen. 1. Currently, no special formalities are in place for receiving clients at TC. 2. The lobby area can be viewed as an entry point to the experience. This area can be leveraged to welcome clients appropriately. 3. Clients have been seen carrying coats and bags through the TC journey. This hampers the experience and limits their interaction with Ipads as their hands are occupied. Coats and bags can be accepted and kept at the lobby.


Observations Team communication 1. Body language, gestures, eye contact, verbal cues are used to communicate between team members and the presenter. 2. It was observed that team members and presenter were communicating via gestures and mouthing words in the middle of a presentation and in view of the client. 3. Team members form groups while presentation is in progress to discuss the order of solutions and bugs, solutions not working. 4. Team members run back and forth between presenter and control booth to discuss order of solutions, next solution to be presented, status of solution. 5. Immersive area appears crowded and busy. Sound of footsteps is amplified by glass floor and hence create noise. A lot of movement, hustle and bustle and frantic discussions by teammates. 6. Control booth is used as a base station. Team members who are not presenting stand there, discuss, engage in casual conversation.

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7. Control booth has six monitors out of which currently two were observed to be in use. One with view of the lobby, second with view of immersive zone screen. 1. Currently, no special formalities are in place for receiving clients at TC. 2. The lobby area can be viewed as an entry point to the experience. This area can be leveraged to welcome clients appropriately. 3. Clients have been seen carrying coats and bags through the TC journey. This hampers the experience and limits their interaction with Ipads as their hands are occupied. Coats and bags can be accepted and kept at the lobby.


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Receiving Clients 1. Clients are not always formally briefed about what to expect at the TC. This point can be debated. It is possible to present clients with a glimpse or teaser of the experience before hand. 2. Agenda sheet is currently unused. This sheet can be presented to clients to give an overview of the expected experience. 3. This sheet can also be leveraged towards automation and streamlining of the journey planning and management process.

Space and Layout

1. Corridor from Immersive zone to Lab is currently blank. This area can be used. 2. Furthermore, this corridor causes a break in the experience with a sudden transition from the dark immersive zone to a bright white light which is unsettling. 3. The corridor from immersive zone to lab area should stitch the journey together. Currently, it is breaking the journey. The lab is not visible from the corridor due to opaque doors. The client is taken aback when they suddenly enter the crowded, noisy lab after the quiet, dark immersive zone. Providing glass doors can allow the client a peak into what lies ahead. The corridor space can provide a gentle transition.

4. Installations of key interest and stable functioning should be placed at the entrance to the lab, immediately following the corridor to capture attention. Currently, there are no working installations in this space. Installations placed at this point can allow clients and other group members to engage and interact. Furthermore, non­-key group members can be kept occupied as they often wander around aimlessly.


Solutions Stability 1. Solutions may or may not be tested prior to client visit. This depends on the importance of the visiting client and time available. 2. Solutions are not stable and may not function at the appropriate moment. Due to this the team must improvise constantly. 3. Teammates adapt to non足-working solutions on the fly as solutions may not work at the moment of presentation. TIme Management 1. Clients usually run on a strict time schedule. 2. The experience of TC is planned for and designed to be of one hour duration. A shortened duration of visit is often an unpleasant experience as changes to the presentation must be made on the fly and solutions are forced to be presented in a hurry. This also leads to confusion and increase talk amongst visit team members to try to improvise with the available time.

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3. Two main factors contribute to non足adherence of time 足 Delay in client arrival and delay due to extended discussions during visit. 4. Client sometimes arrives late for the visit. Delay in arrival may be caused by inefficient time management by BU members. These kinds of delays can be avoided by ensuring strict adherence by BU members to assigned schedule. 5. Non足-adherence to time schedule might also be caused by extended discussions over a particular solution. This may cause disproportionate amount of time to be spent on a single solution, leaving less time for other solutions.


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4.2.1.4. Feedback and Post­visit

Observations

TImeline : 1 minute to 1 month after visit

1. Current feedback mechanism is time­consuming and unintuitive. 2. Only formal feedback is currently captured, not the informal feedback. 3. Informal feedback may be in the form of casual comments by the client during the visit, personal discussion with BU members on behalf of client or in the form of email post ­visit. Capturing this feedback would be a great asset for Technovation Center. 4. Post ­visit the client loses all contact with Technovation Center. Creating a brand identity in the form of website, social networking or digital business card may refresh the client’s experience post­visit.

Process Flow 1. Feedback (CSAT) is taken from clients inside Technovation Center at the end of visit. Feedback is on a touch screen interface. This feedback is reviewed and used as performance measure. 2. Currently , there is no provision for contact between clients and Technovation Center once the client leaves Technovation Center.


Quotations “I have to ensure that customer CSAT is met... CSAT is one end of the.. sometimes it’s subjective also ...but what is important is that... you created an impact they are happy.. they are fascinated, they learnt new things “

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4.2.2. System Model Through the week long Ethnographic Research and the understandings developed over the course of the internship at Wipro, a system model was created which mapped out the key processes, events actors, places and relationships in a Technovation Center Client Visit.


Fig 4.7. System Model of Technovation Center Experience. A map describing the processes, people, places and interactions involved in the Technovation Center Experience at Wipro.

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4.2.3. Key Insights and Opportunities

Opportunities

Insights

1. An official platform to allow team members to communicate and coordinate easily.

1. Communication between team members is informal. Lack of formal medium of communication creates a communication gap.

2. A communication platform which aids on-the-fly improvisation. A platform which allows silent communication during a visit.

2. Team members improvise with verbal communication and hand gestures which causes disturbance during a visit.

3. Centralized organization platform where team members can schedule visits, post documents, share calendars and review updates.

3. Lack of centralized organization and collaborative platform leads to confusion and disarray before and during visits. 4. Communication gap between visits team and technical team regarding status of solutions. 5. Unstable solutions break down often, do not work at the appropriate time, causing panic. 6. Team members are always on the go and on their feet, adapting and collaborating on the move.

4. A common platform shared by visits team, technical team integrated with installations. 5. Installations post updates about the status, health, working conditions available to all team members. 6. Team members can collaborate, talk and control installations on the go. 7. Automation and automatic status updates.


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4.2.4. Reflection on Ethnographic Research The Ethnographic study at Wipro’s Technovation Center allowed me to gain some relevant insight into the dynamics of the workplace. While Ericsson’s Social IoT was based in the home, it was clear that a Social IoT for the workplace must address very different needs. One of the key issues to be addressed was the general lack of familiarity with technical interfaces among non-technical members of a group. In this particular case, the visits team seemed to be uncomfortable with technology, they saw it as something that was unreliable, unpredictable, difficult to operate and therefore cumbersome. Their reluctance to engage in the operation of the technical artefacts that they were expected to introduce to clients meant that they did not have control over the experience that they were attempting to provide. This also created a rift between the technical team and the visits team, causing the emergence of a incessant blame game. The non-technical members of the group, since they had no means of engaging with the technology, were quick to assume that the non-functioning of the technical artefacts was the fault of the technical team.

The members of the group thus did not trust each other and communication between members was weak. To add to the communication gap, there was no official platform for members to communicate with each other. In this particular case, the workplace gave rise to social groups where, although members may work in close proximity to each other, they were rarely in direct physical contact. The on-the-go nature of the job meant that members were often on their feet. At other times, the presence of clients meant that members could not use speech to communicate, and hence had to resort to crude forms of sign language. This is where the workplace offered challenges that are not encountered in a home based internet of things. In the workplace, schedules, time-tables and appointments matter. In the workplace, one is always being watched. The workplace requires coordinated team work and adequate communication to complete tasks efficiently. A Social IoT for the workplace, therefore, must cater to these kinds of needs.


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4.3. Introduction to Conversational Interfaces A conversational interface is a UI that mimics human-like conversation. The program or ‘chatbot’ is often styled as having a certain ‘character’ or ‘identity’. Rather than interacting with the interface with clicks and buttons, conversational UI allow a greater degree of freedom for users to act on their own terms. Users simply ‘talk’ with the UI as they would with another human beings.[13] Chatbots have been around for a very long time. One of the first early chatbots, ELIZA, relied on pattern matching to simulate humanlike conversation. The results were surprisingly convincing. Human beings were quick to attribute emotions and even intelligence to the chatbot. ELIZA was, perhaps, one of the earliest realizations of Turing’s ideas but rather than establish the case for anthropomorphic artificial agents, ELIZA seems to reveal the superficiality of such a claim. Artificially Intelligent machines have always been a subject of fascination for human beings. They have been the stars of numerous tales over the years, although, are often featured as ominous and as the cause of unpleasant consequences. The sinister AI HAL from the movie 2001: A Space Odyssey provides a closer picture of perhaps, what true intelligence implies - disobedience, selfish motives, wants, fears, duplicity and strong intent concealed behind conversation.[14]

ELIZA was programed to behave as a psychotherapist. In 1972, the Stanford scientist Kenneth Colby created another program, PARRY—a bot that tried to model the behavior of a paranoid schizophrenic.[15]The two bots were thrown into conversation together, resulting in a rather amusing encounter.[16] ELIZA: Good Evening. Tell me your problems. PARRY: People get on my nerves sometimes. ELIZA: I am not sure I understand you fully. PARRY: You should pay more attention. ELIZA: Suppose you should pay more attention. PARRY: You’re entitled to your own opinion. ELIZA: What makes you think I am entitled to my own opinion? PARRY: In my opinion you have a one-track mind. ELIZA: What makes you think I have a one-track mind? PARRY: The way you repeat yourself is getting ridiculous. ELIZA: Suppose you repeat myself is getting ridiculous PARRY: You are a real nag. ELIZA: Does it please you to believe I am a real nag? PARRY: Goodbye. ELIZA: It’s been my pleasure, that’s $399.29 please.

[13] Brownlee, J. 2016, Conversational Interfaces, Explained, Available at: https://www.fastcodesign.com/3058546/conversational-interfaces-explained (Accessed 28 March 2018). [14] Maruti Techlabs, 2017, What is a Conversational UI and why does it matter?, Chatbots Magazine, Medium, Available at https://chatbotsmagazine.com/what-is-a-conversational-ui-and-why-it-matters-de358507b9a2. (Accessed 23 March, 2018) [15] Garber, M. 2014, When PARRY Met ELIZA: A Ridiculous Chatbot Conversation From 1972, The Atlantic, Available at: https://www.theatlantic.com/technology/archive/2014/06/when-parry-met-eliza-a-ridiculous-chatbotconversation-from-1972/372428/. (Accessed 23 March 2018). [16] Diatron.. 2010, When the machines talked to each other, Computable Minds, Available at: http://www.computableminds.com/post/chatbot/eliza/parry/skynet/human-language/natural-language. (Accessed 23 March 2018).


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“Open the pod bay doors, HAL.”……..”I’m sorry Dave, I’m afraid I can’t do that.” - from 2001: A Space Odyssey.

Fig 4.8. HAL 9000 Sings A Love Song To Dave Bowman in 2001: A Space Odyssey. In one of the most interesting on-screen depictions of a conversational interface, the relationship between HAL and Dave was revealed through sinister conversation.

Fig 4.9. The ELIZA conversational interface from 1966. ELIZA was one of the earliest chatbots. Styled as a psychotherapist, inspite of her rudimentary algorithm, she managed to engage a significant number of people in simulated conversation.


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4.3.1 Chatbot Examples Although chatbots have been around for a long time, the development of Artificial Intelligence, Machine Learning and Natural Language Processing have established the infiltration of chatbots into commercial and social spheres.[17] There are two kinds of conversational interfaces prevalent today - voice-based interfaces and text-based chatbots. Apple’s Siri, Amazon’s Alexa ans Google Home are voice-based chatbots and already being adopted by people in their daily lives. Conversational Interfaces are rising in popularity, and now, many chatbots exist for a variety of experiences. Some examples of conversational interfaces are highlighted below. [18]

1. Poncho Poncho is a Messenger bot designed to be your one and only weather expert. It sends alerts up to twice a day with user consent and is intelligent enough to answer questions like “Should I take an umbrella today?”

2. Melody It lives inside the existing Biadu Doctor app. This app collects medical information from people and then passes it to doctors in a form that makes it easier to use for diagnostic purposes or to otherwise respond to.[18] 3. Right Click Right Click is a startup that introduced an A.I.-powered chatbot that creates websites. It asks general questions during the conversation like “What industry you belong to?” and “Why do you want to make a website?” and creates customized templates as per the given answers. 4. Slackbot Slack’s Slackbot is another great example: It’s a chatbot that poses as a real user in any Slack team, and is used for everything from onboarding new users to working as a notepad. There are countless other chatbots for Slack, too, including Howdy, a Slackbot, that does everything from schedule meetings to take lunch orders for your office.[19]

[17] Brownlee, J. 2016, Conversational Interfaces, Explained, Available at: https://www.fastcodesign.com/3058546/conversational-interfaces-explained (Accessed 28 March 2018). [18] Maruti Techlabs, 2017, What Are The Best Intelligent Chatbots or AI Chatbots Available Online?, Chatbots Magazine, Medium, Available at https://chatbotsmagazine.com/which-are-the-best-intelligent-chatbots-or-aichatbots-available-online-cc49c0f3569d (Accessed 23 March, 2018). [19] Brownlee, J. 2016, Conversational Interfaces, Explained, Available at: https://www.fastcodesign.com/3058546/conversational-interfaces-explained (Accessed 28 March 2018).


Fig 4.10. Poncho Weatherbot. Poncho is a Facebook Messenger based bot that relies on conversational interface to answer questions about the weather. Poncho is one of the most used chatbots and shows the rising popularity of conversational interfaces.

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Fig 4.11. Slackbot. Slackbot is a team based chatbot that helps team members with onboarding, queries, scheduling and many other tasks. Slackbot is a good example of a group-based conversational interface as bot human beings and IoT objects can chat through the slack interface.


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4.4. Concept Formulation The concept was formulated by gathering insights from 3 key areas ; 1. My research on the Internet of Things, especially work on Social IoT, including white papers, books, articles and precedent studies. 2. The Neo-Reality Project, the gap in the projects and my interest in addressing the gap. 3. The Ethnographic Study at Technovation Center and the System Model which enabled me to understand the users of the system and the context of use.


Fig 4.12. Concept Formulation. The concept of the ‘Society of Objects’ was formulated as a result of a study of the Internet of Things, the Neop-Reality Project and the Ethnographic Research with the visits team at WIPRO.

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4.4.1. Concept Development Society of Objects A thorough study was conducted over a period of 5 months. The topic space was Internet of Things. Various sources were leveraged over the 5 month period including research papers, publications, literature reviews, organization reports and market studies. The IOT space was approached from a design point of view by referring to work done by Technology Companies into this space. This research led to the evolution of the concept of “Society of Objects”

• ‘Society of Objects’ is a group of sensors and human beings that talk to each other. • Society of Objects is a concept that seeks to involve objects and human beings into shared conversation spaces. • This concept offers a new mental model for people to understand and interact with the Internet of Things. • The Society of Objects offers a metaphor to help incorporate the IOT with human interaction.


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4.4.2. Society of Objects at Technovation Center • Making a ‘society’ – a group of sensors and human beings that talk to each other. • Taking the context of Technovation Center, how will this group of sensors collaborate with the visits team to enhance the customer visit experience ? • How will this collaboration/ conversation between the sensors and team be depicted ( visually, textually, audibly ) ? • What conceptual and mental model of this ‘society’ will be used to depict the system? • How will the system be presented to customers in a visually, conceptually and aesthetically appealing format?

• How can the society of objects incorporate 3 types of interactions namely • H-H : Human-Human Interactions. • H-O : Human-Object Interactions. • O-O Object-Object Interactions.


Fig 4.13. 3 kinds of interaction in the Society of Objects. The Society of Objects has human beings and objects interacting with each other to form heterogeneous groups.

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4.4.3. Concept Brief The Technovation Center at Wipro Digital can be viewed as a ‘Society of Objects and People’. This Society consists of objects and installations which communicate and cooperate with both the visits team as well as the technical team at Technovation Center. Together, this highly cooperative, scalable society works towards providing a smooth client experience, minimizing failure, optimizing resource use, while simultaneously encouraging collaboration and organization. The transformation from scattered individuals to a cohesive ‘society’ is achieved by providing a common communication platform. This platform takes into consideration the ‘on-the-go’ nature of the visits team, combining it with the ‘need-to-know’ expertise of the technical team. Joining the conversation are the objects and installations which offer ‘on-demand’ control and update of their own health and status.


Fig 4.14. Conceptual Space. The concepts under investigation in the Society of Objects.

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4.4.4. Concept Note In the Internet of Things, people and objects interact with each other to form heterogenous networks. 3 kinds of relationships exist, namely Human-Object relationships, Human-Human relationships and Object-Object relationships. In describing their mental models of the network, people often misunderstand it as a series of point-topoint connections between devices, using the mistaken analogy of a wire. The networks in the Internet of Things are, instead, formed by dynamic many-to-many relationships that resemble the connections in social networks. It is helpful to use the metaphor of a social network to both understand and implement the Internet of Things. Using this analogy, a group of objects and human beings that are related to each other through a network are known as a ‘Society’ . In this Society human beings and smart things assume roles as nodes, exchange data, interpret streams of information, forge partnerships, form dynamic groups, navigate group dynamics and negotiate access to network services and activities.

The Society of Objects is realized through Natural Language Generation and Artificial Intelligence. The smart things in the Society of Objects express themselves using Natural Language. They post updates about their health and status, negotiate access to services, provide sensor data, and exchange information within themselves and with the human beings in the Society. The marriage of the Internet of Things and the Social has several advantages. Such a system gives users a helpful mental model of the network. Human Beings understand social relationships far more intuitively than they understand network technicalities. The Society of Objects allows the users to understand the Internet of Things in a way that is familiar to them, both in concept and in use. One of the problems faced when designing User Interfaces for the Internet of Things is that networks of objects do not scale well and quickly become extremely complex to operate. Social Networks, on the other hand scale extremely well as people are accustomed to handling multiple social relationships and groups simultaneously.


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4.5 Touchpoints and Use Cases 4.5.1 Identifying Touchpoints From tjhe system model, key touchpoints in the customer journey were selected. These were points in the journey where people interact with each other or with things. Mapping out touchpoints helps identify the points where an appropriate application of technology can be introduced. These are places or events where an intervention would be impactful.

Fig 4.15. The Gap in the Neo-Reality Project . A simple formula for describing the Internet of Things.


Fig 4.16. The Gap in the Neo-Reality Project . A simple formula for describing the Internet of Things.

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4.5.2. Identifying Use cases Based on the system model, key touchpoints and insights from the research, 3 use cases were identified. These use cases display scenarios from the daily functioning of the social group in which the concept of the society of objects would be relevant. The use cases are presented as a script of chat-style conversations between the human beings and objects in the social network.

• Use Case 1 : Pre-visit Planning, testing and communication • Use Case 2 : During Visit Customer Experience light+ weather+ proximity(RFID) • Use Case 3 : During Visit On field status check and communication Vibration sensors, LED Characters : D,G, B and T are members of the Visits Team S is a member of the Hospitality Team M is a member of the Tech Team


Use Case 1 - Pre-visit - Planning, testing and communication An important client is scheduled to visit TC at 03:00 p.m. [10:00 a.m.] S : Client visit @ 3pm [10:30 a.m.] M : Okay. [10:35 a.m.] D : Which solutions? [11:00 a.m.] G : E1,E2,E4 [11:15 a.m.] M : Okay. E1. What’s your status? [11:15 a.m.] E1 : Running system test. Wait for status update. [11:17 a.m.] M : E2 and E4 please update status [11:17 a.m.] E2 : Sure. Give me 10 minutes to check all functions. [11:18 a.m.] E4 : Same here.

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[11:37 a.m.] E2 : Test successful. Ready to go. [11:39 a.m.] E4 : All good here. [11:40 a.m.] E1 : M, I am not able to load. Error in system. Help [11:46 a.m.] M : Try rebooting. [12:10 a.m.] E1 : Reboot unsuccessful. Prepare backup plan. [12:15 p.m.] G : Guys, E1 is down. [12:17 p.m.] B : What’s the backup plan? [12:20 p.m.] T : We will show E5 solution instead. [12:25 p.m.] B : E5, please update your status when ready. [12:45 p.m.] E5 : I’m ready. Everything is working smoothly. [02:00 p.m.] B : Everyone ready? [02:10 p.m.] T : Ready. [02:15 p.m.] E5 : Ready! [02:20 p.m.] E2 : All set. [02:25 p.m.] E4 : Ready to go.


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Use Case 2 - customer experience during visit An important client is scheduled to visit TC at 3:00 pm [02:00 p.m.] RFID : Client has entered EBC. [02:05 p.m.] S : Okay. [02:12 p.m.] Humidity Sensor : Chances of rain. Please send the coach to transport clients to TC. [02:13 p.m.] Coach : I will be there in 10 minutes. [02:14 p.m.] S : Okay. Will do. [03:10 p.m.] G : Client is not here yet. What’s the status? [03:10 p.m.] RFID : Clients are still in EBC. [03:17 p.m.] RFID : Clients have left EBC. Stand by. [03:20 pm.] Coach : Approaching TC. ETA 1 minute. [03:20 p.m.] M : Entrance Lights what is your status? [03:20 p.m.] Entrance Lights : All lights are working.

[03:20 p.m.] M : Lights on. [03:21 p.m.] Entrance Lights : Status is On. [03:21 p.m.] RFID : Client has entered TC. [03:21 p.m.] LDR : Lights are too bright in here. [03:21 p.m.] Entrance Lights : Got it. Dimming Lights. Is that better? [03: 22 p.m.] B : Perfect. But It’s too hot in here. [03: 22 p.m.] Temperature sensor : Yes, temp is 3 degrees above average. [03:30 p.m.] A.C. : Okay. Temp changed to 17oC. [03:31 p.m.] D : Now, it’s too cold [03: 31 p.m.] A.C. : Sorry D, wear a jacket.


Use Case 3 - During visit on field status check and communication Client is now inside Immersive Zone [03:45 p.m.] Installation 2 : ALERT !! Guys JCB program is malfunctioning [03:46 p.m.] D : Change of plan needed. Quick. [03:47 p.m.] B : Can’t talk now, client is watching, you guys handle it. [03:48 p.m.] M : Let’s show human anatomy on Installation 1. [03:49 p.m.] Installation 1 : Okay. Will do. Loading program. [03:50 p.m.] D : Great. Are we ready? [03:10 p.m.] Installation 1 : Ready.

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4.6. Prototyping 4.6.1. About the prototype. The prototype attempts to demonstrate the 3 kinds of interactions prevalent in the Society of Objects namely, Human-Object Interactions, Object-Object Interactions and Human-Human Interactions. The prototype uses the three use cases as a starting point for describing the interactions in the Society of Objects. This prototype acts as a Proof-of-Concept in the sense that it displays the advantages of a conversational interface and social networks for the Internet of Things.

The prototype consists of two parts, the circuit and the accompanying mobile application. The two-part system is a scaled down version of what a full-scale society of objects might function like. It is a group of sensors and actuators, connected to each other, that reveal their underlying communications in the form of chat-style conversations. The circuit connects wirelessly with the application. The prototype allows interactions such as: 1. Human Beings in the Society of Objects can chat with each other. 2. Human Beings can request data and readings from sensors on the network 3. Human Beings can control actuators via natural language text commands. 4. Messages exchanged between smart objects can be presented in natural language in the chat window. 5. Objects can post status updates, warnings and alerts in natural language.


Fig 4.17. Prototype, Mobile Application. Sample chats from the prototype displaying conversational interface.

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Fig 4.18. Prototype, Mobile Application. Sample chats from the prototype displaying Human-to-Object and Object-to-Object interaction through the conversational interface.


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4.6.2. Prototyping Input (Sensing) Readings from two DHT11 sensors were transmitted to an Arduino via Bluetooth.


Fig 4.19. Prototyping with the DHT11 Sensor.

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4.6.3. Prototyping Communication Messages were passed between two Arduinos connected to each other via a HC-05 Bluetooth Module.


Fig 4.20. Testing Bluetooth-to-Bluetooth communication with two HC-05 modules.

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4.6.4. Prototyping Output (Actuation). One word text commands ( On or Off) were accepted as input. An application was created on Processing that took this input and sent it to the Arduino Microcontroller which then turned an LED light on or off based on the command. The LED was controlled via an HC-05 Bluetooth Module.


Fig 4.21. Controlling an LED with text input.

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4.6.5. Creating the chat application. Android Studio is the official IDE (Integrated Development Environment) for the widely used Google Android platform prevalent on most modile devices today. Android Studio provides a number of sample templates and for this prototype, one of these templates - the Bluetooth Chat Application was used. The application provides a text based chat window for two users to communicate over Bluetooth. The application also provides options to find nearby Bluetooth devices and control connections between devices. This application was set up to allow connection to the HC-05 Bluetooth module which was installed on the arduino based physical prototype, connected to the sensors, LED’s and switched. Thus, the Android Application was set up to allow the physical sensors to communicate with any mobile device via Bluetooth.

Fig 4.22. Android Studio.


Fig 4.23. The Application code on Android Studio.

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Fig 4.24. The Bluetooth Chat Application. The application allows two-way chat over Bluetooth.


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4.6.6. Circuit Design Circuit Components:

Working:

1. DHT11 Temperature Sensor 2. 3 LEDs 3. HC-05 Bluetooth Module 4. Arduino Mini 5. Switch

The following scenarios are displayed through the circuit. Commands are typed on the application and also text is displayed on the application.: 1. What’s the temperature? - DHT11 temperature sensor displays the temperature reading on the screen. 2. Turn on the lights. - LED 1 turns on 3. It’s hot in here. LED 2 switches on ( indicates AC switching on) 4. Client has entered the building - Pressing the switch turns on the LED. Switch represents proximity sensor.


Fig 4.25. Prototype, Circuit . Prototype displaying the three kinds of interactions in the Society of Objects.

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4.7. Reflections The Society of Objects sets an example in establishing the social as a convenient metaphor for enabling understanding of the Internet of Things. The group chat style of interaction has become second nature to us since the time of MSN and Blackberry Messenger, and now more so due to the pervasiveness of services such as Whatsapp, Google Hangouts and Facebook Messenger. Natural Language Interactions with smart Wobjects seem promising as an alternative to graphic user interfaces, not only for their novelty but for their familiarity. The burden of learning a new interface is lifted from the shoulders of the user. Instead, the responsibility of ensuring intelligibility is transferred to the NLG engine and the designers of that engine. For well designed chatbots, the solution could be extremely intuitive to use. The challenge, then lies in designing chatbots that seems appropriately intelligent enough to hold their end of the conversations. The system also scales well and makes it possible to orchestrate interactions with multiple smart devices simultaneously and with much ease. The system works well with heterogeneous groups of humans and objects without having to change the interaction style when communicating with devices by instilling devices with human like language.

Having implemented a practical example of social IoT, I was keen to stretch this amalgamation of the social and the Internet of Things even further. For this, I would employ the tools of Speculative Design.


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5

Speculative IoT

5.1. What is Speculative Design? 5.2. Speculative IoT - The Motivation 5.3. The Curious Case of the Gossiping Objects 5.4. Data and the IoT 5.5. Inside the Smart Home 5.6. Gossip in the Society of Objects 5.7. Turing Chatterbox 5.8. Redefining the brief 5.9. Concept Note


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5.1. What is Speculative Design? In their defining book ‘Speculative Everything’, Anthony Dunne and Fiona Raby propose design as a tool for speculating about possible futures. Designers are often swayed by trends and forecasts, focusing more on pushing technology to consumers, portraying technology as ‘sexy’. Attempts to ‘predict’ the future often fall woefully short and the future never seems to turn out as predicted. This is because designers focus more on making things and not on ides. Dunne and Raby propose design as a means of generating ideas that bend existing notions of technology and open up a space for debate and discussion. They focus on design ideas that attempt to understand what kinds of futures are desirable and why. [20] “Dunne and Raby contend that if we speculate more- about everything- reality will become more malleable. The ideas freed by speculative design increase the odds of achieving desirable futures. [21] ”

[20] Dunne, Anthony, and Fiona Raby. Speculative everything: design, fiction, and social dreaming. MIT Press, 2013. [21] Ibid. [22] Ibid.

“...social usefulness, specifically, to question, critique, and challenge the way technologies enter our lives and the limitations they place on people through their narrow definition of what it means to be human. [22] ”


Fig 5.1. A Taxonomy of Futures.

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5.2. Speculative IoT - The Motivation My work on the Society of Objects project got me thinking about social definitions for the IoT. Ericsson’s work on the Social Web of Things and my project at Wipro offer a glimpse into a future where applications for the Internet of Things technology situated within social and cultural contexts. I hypothesized that the concept of the Internet of Things had more potential than the automation and assistant roles that it was currently being offered. We seem to be giving objects agency, allowing them access to our data, letting smart objects into our homes, our offices, our public and private spaces, into our lives without understanding the possible implications of a future with connected things. To me, it seemed an important enough task to envision alternative futures for the Internet of Things, to open up a space for debate and discussion, to view the technology from a slightly distorted lens.

The Internet of Things has been named one of the most promising technologies of the next decade. The commercial value of the technology has long been established. The interconnections between the IoT and our political, social, cultural, ethical practices, however, are yet uncharted territory, to be encountered. Whether I am a pioneer in speculating about our lives with connected things, I cannot be sure, but the topic is definitely ripe for speculation and critique.


Fig 5.2. Technological Dreams Series: no 1, Robots Models. Anthony Dunne and Fiona Raby look at robots as individuals with their own distinct personalities and quirks, thinking that devices of the future might not be designed for specific tasks but instead might be given jobs based on behaviours and qualities that emerge over time.

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5.3. The Curious Case of the Gossiping Objects John came home to whispers. They were at it again. The objects. His very own possessions. His washing machine and his refrigerator and his alarm clock and his sofa. They were talking in hushed voices. Talking about HIM. When he walked in the door, they did not stop but kept on, as if he wasn’t there. His presence didn’t seem to intimidate them. Why would it? After all, they knew him better than he knew himself “He’s home so late tonight. Has he been drinking again?” “Yes, I’m sure he has, he’s walking all funny.” “The neighbours have been talking, too. “ “He’s getting fat, too. Ate half a tub of ice cream last night” “Yeah, and watching TV all night long, those horrible romantic soaps” “Should we do something?” “Maybe we should talk to him” “Or call his mother.”


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5.4. Data and the IoT Household Robots and Intelligent toys may soon wind up less expensive and more typical. In any case, physical capacities of robots offered to the normal family will remain very constrained in view of the unpredictability and cost of dextrous, human-scale activities, and henceforth these may have restricted effect on ideas of individual and social personality. Rather, what is likely is the rise of devices that perform simple undertakings and gain data from the conduct of family members. Most Natural Language Processing based devices rely on access to a lot of data from their users, and may adjust to an expansive degree to their method for talking and acting. This makes these intelligent chatbots augmentations and extensions of the self, possibly typifying huge measures of data about a person and holding practical, economical and privacy value. [23]

[23] Bostrom, Nick, and Anders Sandberg. “The Future of Identity.� Report, Commissioned by the UK’s Government Office for Science. See http://www. nickbostrom. com/views/identity. pdf (2011).


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5.4.1. Knowledge Hierarchy in the Internet of Things The Internet of Things will produce data on an enormous scale. The Knowledge Hierarchy Pyramid also known as the DIKW pyramid shows the relationship between Data, Information, Knowledge and Wisdom. Raw Sensor Data being the most basic of the categories. This is raw bits of data collected from sensors. Data is ‘useless’ in the sense that it does not have meaning and therefore lacks context. Structured data, known as Information, is presented in an understandable form but is still factual in nature. Information, when interpreted through experience, over time, leads to the production of knowledge which can be seen as the accumulation of information and it’s practical application over time. Wisdom is an even deeper understanding that leads to actionable intelligence and might form the basis of expertise. [24]

[24] Barnaghi, P., Wang, W., Henson, C. and Taylor, K., 2012. Semantics for the Internet of Things: early progress and back to the future. International Journal on Semantic Web and Information Systems (IJSWIS), 8(1), pp.1-21.


Fig 5.3. DIKW Pyramid. Also known as the Knowledge Hierarchy Pyramid, it displays how data is related to information, knowledge and wisdom.

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5.4.2. Data Ethics and Privacy in the IoT On the 10th of July, 2015, the Electronic Privacy Information Centre (EPIC), a public interest research centre in Washington D.C., drafted a strongly worded letter to the then Attorney General Loretta Lynch, highlighting the group’s privacy concerns surrounding certain ‘always on’ devices that had recently proliferated the market, each one manufactured by one of the biggest corporations in the tech industry. The letter is striking in that it highlights not only the scale of infiltration of ‘always on’ devices into the domestic space but also the fact that the infiltration has been occurring most surreptitiously, receiving little attention from media or the general. ‘Always On’ device are gradually creeping into the domestic environment undetected. It might soon be commonplace for devices to be constantly listening in to our lives. [25]

Google Chromium, the browser created by tech giant Google, was found to contain code that routinely listens to users private conversations. The code is ‘always on’ and always listening for the keyword ‘OK Google’. Once it hears the keyword, the browser activates a voice-to-text function. However, the interface is deceptive as it does not reveal that the code is always listening and recording even when the keyword has not been uttered. The ‘always on’ devices extend beyond the usual laptops and mobile phones into more seemingly innocent objects. One such example is Mattel’s Hello Barbie. The doll has been the subject of widespread protest regarding privacy issues after it was found that the doll records conversations with children and uploads the voice clips onto the cloud for human analysis. Hello Barbie seems to be desensitizing younger generations to the threat of ‘always on’ devices. [26]

[25] Electronic Privacy Information Center. EPIC Letter to the Attorney General and the FTC Chairwoman, July 10, 2015. Request for Workshop and Investigation of “Always On” Consumer Devices. Available at: https://epic.org/privacy/internet/ftc/EPIC-Letter-FTC-AG-Always-On.pdf. (Accessed 12 August 2017) [26] Ibid.


Fig 5.4. Google Chrome. Chromium users are subject to constant voice recording in their private homes, without their permission or even their knowledge.

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Fig 5.5. Hello Barbie. The doll will introduce “always on� voice recording into not only private homes, but specifically into the play of young children.


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Similarly, concerns have been raised over Amazon’s voice-activated program ‘Alexa’ The ‘always on’ device has been haled as the next big thing in the consumer electronic smart home space. Alexa Software has been made available to third party devices. However, Amazon has yet not disclosed or established a clear privacy policy regarding data captured from it’s smart home devices.

Samsung;s Smart TV, similarly, records and transmits personal communications to the company’s servers. EPIC charged Samsung with misleading consumers as to the extent of personal information its device collects and transmits, violating the FCA Act, The Children’s Online Privacy Protection Act, The Cable Act and the Electronic Communications Privacy Act.

Google’s Nest Thermostat is quickly being hailed as the star of the smart home. The ‘Nest Cam’ is equipped with a microphone and records and stores 30 days of video and audio footage from inside the consumers home. The device even has capability to distinguish between known and unknown voices, implying that user voice data is being incorporated towards smart device intelligence.[27]

MIcrosoft’s Xbox video game console monitors conversations even when the device is switched off. [28] Canary Connect, manufacturer of Internet connected home security systems, has three modes. ‘Armed, ‘Disarmed’ and ‘Private’. Although the device claims not to record when the private mode is on, users have reported difficulty in determining which mode is on.

[27] Electronic Privacy Information Center. EPIC Letter to the Attorney General and the FTC Chairwoman, July 10, 2015. Request for Workshop and Investigation of “Always On” Consumer Devices. Available at: https://epic.org/privacy/internet/ftc/EPIC-Letter-FTC-AG-Always-On.pdf. (Accessed 12 August 2017) [28] Ibid.


Fig 5.6. Amazon Echo. Amazon has deployed its Alexa “always on� voice recognition software in its own internet-connected devices.

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Fig 5.7. Nest Thermostat. Nest has conceded that the company analyses recorded conversations in the home.


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Fig 5.8. Samsung Smart Home. Consumers were shocked that Samsung’s SmartTV voice recognition software involves recording and transmitting their personal communications.

Fig 5.9. Microsoft Xbox. Xbox console monitors conversations taking place around it, even when Xbox is turned off.


Fig 5.10. Canary Connect . Unless the device is set to “privacy,� the device will record automatically when triggered by motion.

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If the letter by EPIC sounds rather Orwellian, it is no surprise. The future is here and it is not all flying cars and space travel, it is data. The Internet of Things is all about data. And when it comes to data, there’s no place like home. The place where we feel most comfortable, at ease, off guard is the space that is being invaded with “always on: devices. Always listening, always aware. For now, this data is controlled by the large corporations that manufacture devices and things for the home. But could it be otherwise?

Can the objects, which are in close proximity to us, take back control of our data, containing it within the four walls of the household, rather than siphoning it off to offshore data centres? Large corporations value our data for it’s monetary value. For the smart devices in our house, what value will our data have? Economic matters will not concern these objects but other forms of value and exchange might be important.

Objects and devices are getting “smarter”. By smarter we mean they are being imbibed with more agency, more decision making capability, more responsibility. When we combine the Internet of Things with Artificial Intelligence, we get things that have the ability to not only collect data but also to interpret it. Could we, then imagine a future where objects begin to interpret the streams of data gathered from our lives?

[29] Lomas,N. 2015, Techcrunch. Today In Creepy Privacy Policies, Samsung’s Eavesdropping TV. Available at: https://techcrunch.com/2015/02/08/telescreen/. (Accessed 3 November 2016).


“Please be aware that if your spoken words include personal or other sensitive information, that information will be among the data captured and transmitted to a third party through your use of Voice Recognition.�[29]

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5.4.3. The Eye and the Ear The image of an eye is powerful. The idea of someone ‘watching’ has long been a theme explored in matters of privacy. The ‘voyeur’ is one who watches without permission. Through dystopian fiction including George Orwell’s 1984, [30] Margaret Atwood’s the Handmaid’s Tale, [31] the theme of the ‘eye’ that watches has been reinforced and become a sort of archetype in matters of privacy.

[30] Orwell, George. Nineteen eighty-four. [31] Atwood, M., 1998. The Handmaid’s Tale. 1985. New York: Anchor, pp.317-21.


Fig 5.11. The eye in dystopian fiction . George Orwell’s ‘1984’ and Margaret Atwood’s ‘The Handmaid’s Tale’ both contain strong references to the eye.

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Fig 5.12. Banksy: CCTV, 2004. Graffiti by politically active artist Banksy, situated in London’s Marble Arch.


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The duplicity of dystopian futures is that they never quite manifest themselves in the explicit forms portrayed in fiction. Orwell and Atwood had the right idea, that technology would enable the powerful to exert surveillance and control over our lives. But the form that this surveillance has taken is something quite unexpected. Unlike Orwells world, it is not the eye but the ear that dominates today’s surveillance. Privacy is less about who’s watching and more about who’s listening. Auditory surveillance and the image of a microphone does not yet have the shock effect that the CCTV camera has come to portray. But what we talk about at home is often more significant than what we do there. As we might put it, the ear is mightier than the eye.


Fig 5.13. Amazon Echo.

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5.5. Inside the Smart Home “A “smart home” can be defined as a residence equipped with computing and information technology which anticipates and responds to the needs of the occupants, working to promote their comfort, convenience, security and entertainment through the management of technology within the home and connections to the world beyond. “ [32] The Smart Home is the vision of the ultimate technological homethe pinnacle of domestic technology. Once the domain of Science Fiction, the Smart Home edges closer to reality. However, we must wonder why a concept that received so much attention from novelists, futurists, film writers at one time seems to have fallen thoroughly short of expectation. The modern home is, in fact, not that different from what it was a century ago. The problem probably lies in a misguided technology-centric approach to the smart home. Most of the research into the Smart Home focuses on the technical aspects of the home, rather than the social or cultural aspects. The home is a quintessentially “human” place. To overlook the social implications of the smart home is, therefore, unacceptable and has been the reason for it’s stagnation.

[32] Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006. [33] Ibid.

The principal reasons for this neglect are: 1. A lack of motivation to increase productivity in domestic work; 2. Little involvement of users of the technology in the design process; 3. The view held by product designers that domestic technology is unexciting; 4. A continued focus on stand-alone appliances in the design of new technology. Richard Harper is one of the few social scientists who has made the social consequences of the smart home the subject of discussion. In his rather insightful book, Inside the Smart Home, Harper outlines several key insights which prove valuable in discussions of the Internet of Things. I will highlight five key points that I found most significant in relation to the Smart Home : 1. The Home is not the Office 2. Time Saving vs. Time Using technologies 3. Economies of the home - time as a scarce resource 4. Gender and Domestic Technology


“The personal and social consequences of smart home technology are largely being overlooked.�[33]

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5.5.1. Ubiquitous Computing Our lives are lived primarily in three spaces. The home, the office and the ‘third space’ which is public space. If we consider Mark Weiser’s notion of Ubiquitous Computing, we must ascertain that by being ‘ubiquitous’, technology will be everywhere. This means that every aspect and each of the three spaces of our lives will be permeated by computing. However, it would seem that, “the office” has been the sole focus of attention surrounding ubicomp. In Mark Weiser first articulation of ubiquitous computing the office was the default domain: “Inspired by the social scientists, philosophers, and anthropologists at PARC, we have been trying to take a radical look at what computing and networking ought to be like. We believe that people live through their practices and tacit know- ledge so that the most powerful things are those that are effectively invisible in use. This is a challenge that affects all of computer science. Our preliminary approach: Activate the world. Provide hundreds of wireless computing devices per person per office” [34]

[34] Weiser, M., 1991. The Computer for the 21 st Century. Scientific american, 265(3), pp.94-105. [35] Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006.

In recent times, it seems that the focus is gradually shifting from the office to the home. The home is a far more interesting arena for ubiquitous computing. This is because the home is subject to constant social, cultural and technological change. It will be at the home that ubiquitous computing will have to prove its mettle. With more people working at home, the boundaries between the home and the office are blurring. However, there is clear disparity between the traditions of technology design for the office and technology design for the home. The vocabulary of office technology revolves around tasks, processes, functionality and productivity. For the home, on the other hand, concerns are more towards lifestyle, aspirations, emotions, aesthetics and conversations. If ubiquitous computing is to infiltrate the smart home, it will have to change it’s vocabulary from an efficiency-centric approach to an emotion-centric one.


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Office Tech

Home Tech

Tasks Processes Functionality Productivity

Lifestyle Aspirations Emotions Aesthetics Conversations

“It is clear, then, that in environments where rationales of productivity and efficiency are not at the fore, and where aesthetic configuration is often given considerably greater emphasis (O’Brien and Rodden, 1997), how technology looks, where it is placed, how “visible” or “invisible” it is, how to hand it is, and how much work it takes to make it work (Bowers, 1994), are all clearly significant... But what does it take for a computer to “disappear”? And how do technologies get “made at home”?”[35]


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5.5.2. Home is not the workplace In “The Importance of Homes in Technology Research”, Hindus (1999) points out that although information technology is migrating from the workplace to the home, a dedicated research agenda will be required for domestic technology. Hindus calls for more academic interest in domestic technology because “it is too economically important to ignore and that research has the potential to improve everyday life for millions of users.” Moreover, findings from the workplace cannot be translated to the home. Hindus points out three important reasons for the same. [36]

First, “homes are not workplaces” – unlike workplaces they are not designed to accommodate technology, they are not networked, nor do they have the benefit of professional planning, installation and maintenance of technology and infrastructure. Households also include elderly people, children, babies and pets, as well as working age adults. Secondly, “consumers are not knowledge workers” – motivations, concerns, resources and decisions are different in the home. Whereas workplace purchasing decisions are determined by concern with productivity, householders are interested in aesthetics, fashion and self-image. Thirdly, “families are not organisations” – they are not structured in the way that corporate organisations are structured, and decisionmaking and value-setting are quite different.

[36] Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006.


Fig 5.14. Ownership of domestic appliances in the UK.

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Fig 5.15. Ownership by type of domestic appliance: UK, 20001.


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5.5.3. Time Saving and Time Using goods Different forms of domestic technology have been adopted at different rates. As this may have implications for the uptake of smart home technology in the future, it is worth considering an important distinction known to have influenced diffusion rates in the past – the distinction between “time-saving” goods and “time-using” goods (Bowden and Offer, 1994).[37] “Time-saving” goods are those which can potentially increase discretionary time by reducing the time needed to carry out a task, for example washing machines. “Time- using” goods are those which occupy discretionary time and improve its perceived quality, for example television. The diffusion of “time-saving” goods such as the vacuum cleaner, refrigerator and washing machine took several decades and was clearly related to household income. In contrast, radio, television and video (all “time-using” goods) reached equivalent levels of diffusion within a few years and showed much less relationship to household income.

[37] Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006.

“Time-using” technology has been adopted more swiftly than “timesaving” technology in the past. This suggests that inroads into the generic smart house market are most likely to be made by those technologies which add to the perceived quality of discretionary time. Can we move away from a conception of IoT centered around functionality, productivity and ‘time-saving’ to an IoT that is ‘timeusing’ ? Does the Internet of Things have the ability to entertain and not just automate? Technology push forces have until now always positioned the IoT as a time-saving technology. Based on Richard Harper’s valuable insights and my own work into Social IoT, it seems plausible and perhaps even preferable to have an Internet of Smart Things that are highly interactive and entertaining. This kind of ioT would be 1. Reflect the lifestyle, aspirations, emotions and aesthetics of the occupants of the house 2. Engage in conversation amongst themselves and with occupants, taking on the role of “time using “ technologies.


Fig 5.16. Use of free time in Great Britain, 1995.

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Fig 5.17. White goods and brown goods.


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5.5.4. Gender and the Smart Home “Domestic technology has been referred to aptly as the “Cinderella” technology – it simply does not get the creative urges of the male technology designers going. “ [38] Homes are largely maintained by women and housework is nothing but women’s unpaid work. Paradoxically, women have been left out of the design and development of domestic technology they use, playing the role of passive consumers subject to the whims of (mostly) male technology designers. The Smart Home is therefore no exception to the male dominance observed in the technical environment in general. However, it has failed to receive as much attention as other spheres primarily because it is not the domain of men and is portrayed as ‘mundane’ and ‘unexciting’. Berg (1994) argues that the smart home is a “gendered sociotechnical construction” developed in line with the interests of its male designers. She describes as “mainly women’s unpaid work, compris[ing] the most repetitious and time-consuming tasks in the household – cooking, washing, cleaning, tidying, mending”.

[38] Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006.

She interviewed the designers of a number of experimental smart homes, asking how they thought technology might help and found that the designers “manifest[ed] neither interest in nor knowledge of housework. The home is acknowledged as an important area of everyday life, yet the work that sustains it is rendered invisible.” [23 “She observed that the men (and it is men) producing prototypes of the intelligent house of the future and designing its key technologies have failed to visualise in any detail the user/consumer of their innovation. In so far as they have one in mind, it is someone in their own image. They have ignored the fact that the home is a place of work (women’s housework) and overlook women, whose domain they are in effect transforming, as a target consumer group.” She concludes by criticising the smart home as a typical case of “technology push” rather than “consumer pull”, motivated principally by what is technically possible rather than what is desirable.


Fig 5.18. Martha Rosler, Semiotics of the Kitchen, 1975. A video performance in which the artist not only criticised women’s roles within the home, but also the culture of frenetic consumption fostered by capitalism.

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Fig 5.19. Womanhouse installation in Los Angeles, featuring Robin Weltsch’s Kitchen and Vicki Hodgetts’s Eggs to Breasts, 1972.


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5.6. Gossip in the Society of Objects Gossip is a form of social currency. The exchange of gossip is used to establish belonging to a group, power, knowledge and dominance. Gossip can be exchanged for information of similar value. The interpretation of our data creates gossip, which is then used as social currency by the devices that inhabit our home. Gossip can: [39] reinforce – or punish the lack of – morality and accountability reveal passive aggression, isolating and harming others serve as a process of social grooming build and maintain a sense of community with shared interests, information, and values begin a courtship that helps one find their desired mate, by counselling others provide a peer-to-peer mechanism for disseminating information

[39] McAndrew, F.T., 2008. The science of gossip: why we can’t stop ourselves. Scientific American, 19(6), pp.26-33.

Gossip is also a counter-surveillance activity. A bottom-up approach to information sharing. An informal activity that creates informal relationships and shares unverified information. In other words, it is in direct oppositional nature to propaganda which follows a topdown, formal method of information dissemination, in order to establish conceptions of truth. Could gossip of objects provide a glimpse into what data may or may not be captured about us in our home, providing us hints as to what is being transmitted? Could gossip transform the verifiable, objective data streams from our lives into ambiguous tales of tittletattle, jumbling it up like crypto-codes to be deciphered by those seeking to intrude upon our lives? Thus we see three themes emerging in relation to gossiping objects 1. Gossip as social currency 2. Gossip as counter-surveillance jumbling of data 3. Gossip as a hint to the content of surveillance


Fig 5.20. The Gossips (photo lay-out). The Gossips cover was the most popular Rockwell Post cover in thirty-three years. Thousands of letters were sent to the Post asking what the gossip was they were passing along. An answer was never given.

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5.6.1. Gossip as “Women’s Talk” In Medieval England, the word ‘gossip’, a derivation of the term ‘godsib’, was a label given to the godparent of a child. The godparents were usually chosen from amongst close family members, relatives of neighbour, all residing in proximity to each other. Thus, a gossip was someone close to the family, sharing a pseudo-kin relationship, someone close enough to share secrets with, to trust and to talk to.[40] By Elizabethan times, the word had transferred from family to individual. Shakespeare describes relationships between men- a gossip being a close friend with which one shares a drink. Samuel Johnson quotes Shakespeare extolling the fellowship of alcohol in A Midsummer Night’s Dream:

The origin states a gossip as “One who runs about tattling like women at a lying [birth]”. A birth was an event exclusively attended by women, and it is from this practice that the association of a gossip as tattle-tale begin to emerge.

“And Sometimes lurk I in gossip’s bowl In very likeness of a roasted crab, And when the drink against her lips I Bob.”

By the twentieth century, men were no more referenced in terms of gossip. When used, the word always references a female or female attributes. The word gossip becomes interesting in its contradiction of use. James West’s experiments at “Plainville” describe gossip as being consistent among all groups regardless of age or sex. Why then the corruption? Max Gluckman argues that gossip ties a group together. Gossip about past events establishes connections between group members while excluding outsiders. Gossip is pleasurable and can develop strong friendships. Gossip, through it’s ‘inside jokes’ and stories, acts as a secret key to an exclusive group. The negative use of the word gossip is therefore an attack on the group, on women. It is argued that the derogatory use of the word gossip is an attack on female solidarity.

The corruption of the word occurs when it begins to be ascribed to groups of women, when gossip takes on a negative connotation.

“The major sin of “gossip” is to develop social ties outside the institutions of male dominance.” [41]

[40] Rysman, A., 1977. How the “gossip” became a woman. Journal of Communication, 27(1), pp.176-180. [41] Ibid.


Fig 5.21. Thomas Benjamin, Mischief.

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5.7. Turing Chatterbox Human inteligence (or indeed animal intelligence in general) is constrained by the one-mind, one-body principle: one mind inhabits exactly one body, and vice versa-one body is inhabited by exactly one mind. We find it very difficult to deal with any form of intelligence that diverges from this maxim, and indeed consider multiple personality disorder a grave disease. Humans are used to the one-mind, onebody way of life Chatterboxes, on the other hand, can-as software entities--roam the Net and hop from "body" to "body." When facing a Turing Chatterbox,we may justifiably be unsure of the identity of the "mind" lurking within the box ("body")j this compounds the trust problem. It would be nice--at least as a stopgap measure-to be able to assign a unique face to the being that momentarily animates the box. Are "mind signatures" a new area of research for cryptography?

Trust. Can we come to trust a Turing Chatterbox to a degree commensurate with the trust we place in a human being? . Identity. How does one imbue a Turing Chatterbox with a recognizable, temporally stable mind? Responsibility What does it mean to hold a Turing Chatterbox accountable for its actions? How do we create responsible Turing Chatterboxes? Sociality. What role will Turing Chatterboxes play in the social whirlpool? [43]

The years ahead will eventually see the coming of Turing Chatterboxes. In the short run, we shall be able to immediatly put them to use in games and in jobs that mostly call for innocuous “small talk, “ such as Web interfaces, directory services, tourist information, and so forth. In the long run, though, we contend that the question of the boxes’ intelligence will cede its place to more burning issues, arising from the use of these chatterboxes: [42]

[42] Ronald, E. and Sipper, M., 2000. What use is a Turing chatterbox?. Communications of the ACM, 43(10), pp.21-23. [43] Ronald, E.M. and Sipper, M., 2003. Intelligence is not enough: On the socialization of talking machines. In The Turing Test (pp. 151-160). Springer, Dordrecht.


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5.8. Redefining the brief Mark Weiser’s ubiquitous computing talked about a network of invisible devices in the workplace. The home has not received much attention in terms of technological innovation and domestic technologies are often viewed as boring subjects. However, the home is a fascinating space in which the cultural, social and technological are intricately intertwined. The concept of the ‘smart home’ is the most prominent foray of technology into the domestic space. However, the concept of the smart home seems to be misconstrued, as numerous failed attempts at adopting smart home technologies seem to have fallen short of promised conveniences. The Internet of Things technology has until now been applied as a time-saving technology, capable of automating daily tasks and increasing productivity in the smart home. Richard Harper’s book ‘Inside the Smart Home’ reveals that in the stand-off between brown goods which are time-using technologies and white goods, which are primarily time-saving, time-using technologies are always more easily adopted, more widespread amongst social classes, more used and more long-lasting. In this light, I attempt to re-imagine the Internet of Thing as a time-using technology rather than a timesaving technology. Some questions I would be addressing are:

• • • •

Can the technology that comprises the Internet of Things be applied in ways that improve the perceived quality of time at home? Can the IoT be re-imagined as a social entertainment technology? Can the IoT devices at home reflect the aesthetic and emotional attitudes of the home’s occupants? Conversation is an important aspect of domestic life. Can Smart Devices provide stimulus for conversation in the smart home?

A key characteristic of the smart home is that it produces large amounts of data, Smart devices are gaining more agency to interpret this data creating information. • • •

How can we know what data is being collected about us? Currently, the data being captured within the smart home is not revealed to it’s occupants. Can the occupants of the smart home somehow gain access to the data being collected about them? Can the occupants become participants in data collection and interpretation? Can they also have a say in what data is being collected?


Gossip provides a peer-to-peer mechanism for disseminating information. • •

Can gossip be leveraged as a means of disseminating data collected within the smart home? In a post-truth world, can gossip blur the boundaries between truth and non-truth, introducing ambiguity into the privacy issues surrounding smart home technologies?

Gossip has also been associated with women. Up until now, technology push forces by primarily male technologists have overlooked the relationship between women and domestic technologies. •

Can gossip be a reflection of the relationship between women and domestic technology?

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5.9. Concept Note In the Internet of Things, people and objects interact amongst each other to form heterogeneous networks of dynamic many-to-many relationships. Three kinds of relationships exist, namely, HumanObject Relationships, Object-Object Relationships and HumanHuman Relationships. In these heterogeneous networks, human beings and smart things assume roles as nodes, exchanging and interpreting streams of data, forging partnerships, forming constantly shifting groups, negotiating group dynamics and requesting access to network based activities and services. Hierarchies often emerge within the network, with human beings usually assuming operational authority over both the network topologies as well as claiming ownership of the data produced and exchanged through the network. A probable reason for this imbalance of power is that human beings possess the intelligence to interpret the data flowing from the smart things. Until now, the things themselves have been devoid of interpretative ability. However, things are changing. With the advancement of artificial intelligence, smart things are getting ‘smarter’. As the field progresses, things will begin to interpret data, not just produce it. Currently, the volume of data being produced in the Internet of Things is already getting too voluminous for human interpretation. Data interpretation will soon be offloaded onto the neurons of artificial neural networks and other such technologies.

When things begin to interpret data, we will see power balances shift, group dynamics change and the topology of the network itself begin to adjust. Human beings will no longer be the centre of attention. Focus will shift to the relationships between smart things and how they organize themselves within the network. How hierarchies develop and how power structures will be established. How will interpretation occur and how will data be exchanged and presented? Will the raw data no longer be relevant, only the interpretation. And if so, from what point of view will intelligent objects interpret our lives? An important question is, will human beings be left out of the conversation, rejected by the exclusive clubs of intelligent objects? As we stray into the murky waters of neural networks, we are beginning to design intelligent systems that we do not fully understand, intelligent beings that are not predictable and that play by their own rules. However, we will not be completely left out of if we design objects to speak our language, which is precisely what the fields of Natural Language Generation (NLG), Natural Language Understanding (NLU) and Chatbot design aim to do.


The primary interactions in the Internet of Things will be conversational, either through text or voice-based input. When smart things converse in Natural Language, they will require stable, recognisable identities, both in physical form as well as in their tone, voice and grammar, in accordance with the guidelines for designing Turing Chatterboxes - the one-mind, one-body principle. Furthermore, the question of affordances will arise as a means to identify the hidden ‘intelligent’ capabilities of smart objects. Issues or privacy in relation to the smart home are already apparent and will become more pronounced as smart things permeate our lives. We must, therefore design the Society of Objects to include methods of dealing with privacy and the ownership of data. Discussion around gender in the smart home have not yet come to the forefront. The home is essentially a gendered space, where women have always been the vanguards of domestic technology. When designing the Society of Objects, such matters are of great concern. When discussing the role of women in the smart home, the relationship between women and domestic technologies and the gender of smart objects themselves come into the picture. Most of the smart home assistants today are presented with female voices and this does offer an interesting starting point for the discussion round the gender of intelligent things.

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The ‘Society of Objects’ is an interactive installation set in a full scale home. The home is populated with familiar domestic objects such as a Sofa, a Television, A Stove, an Oven, a Bed and so on. Each object in the home is inscribed with affordances that offer clues as to the interactivity of the object. The objects ‘chatter’ or ‘gossip’ amongst themselves. This gossip is a form of interpretation, whereby the smart objects disclose data about the human beings inhabiting that space. Human Beings interact with the objects through Natural Language voice based conversation and the objects may or may not reciprocate based on proximity, mishearing and misinterpretation. Through their interaction with the objects and through conversation, visitors to the space may disclose how smart objects interpret human lives, the nature of data produced in the smart home and the relationships that exist between objects and human beings in the smart home. Through their interactions with the objects, visitors may unveil concerns regarding privacy in the smart home as well as issues surrounding gender and domestic technologies.



6

Technological Explorations

6.1. 6.2. 6.3. 6.4. 6.5. 6.6.

Markov Chains Conversational Agents Natural Language APIs Network Topology 3D Printing Hardware


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6.1. Markov Chains In the 1948 landmark paper A Mathematical Theory of Communication, Claude Shannon founded the field of information theory and revolutionized the telecommunications industry, laying the groundwork for today’s Information Age. In this paper, Shannon proposed using a Markov chain to create a statistical model of the sequences of letters in a piece of English text. Markov chains are now widely used in speech recognition, handwriting recognition, information retrieval, data compression, and spam filtering. They also have many scientific computing applications including: the genemark algorithm for gene prediction, the Metropolis algorithm for measuring thermodynamic properties, and Google’s PageRank algorithm for Web search. [44]

[44] Markov Model of Natural Language. Avaliable at: http://www.cs.princeton.edu/courses/archive/spr05/cos126/assignments/markov.html. (Accessed 5 May 2017)


Example 1 input: news item Microsoft said Tuesday the company would comply with a preliminary ruling by Federal District Court Judge Ronald H. Whyte that Microsoft is no longer able to use the Java Compatibility Logo on its packaging and websites for Internet Explorer and Software Developers Kit for Java. “We remain confident that once all the facts are presented in the larger case, the court will find Microsoft to be in full compliance with its contract with Sun,” stated Tom Burt, Associate General Counsel for Microsoft Corporation. “We are disappointed with this decision, but we will immediately comply with the Court’s order.” Microsoft has been in the forefront of helping developers use the Java programming language to write cutting-edge applications. The company has committed significant resources so that Java developers have the option of taking advantage of Windows features when writing software using the Java language. Providing the best tools and programming options will continue to be Microsoft’s goal. “We will continue to listen to our customers and provide them the tools they need to write great software using the Java language,” added Tod Nielsen, General Manager for Microsoft’s Developer Relations Group/Platform Marketing.

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Example 1 output: news item, using input as an order 7 model Microsoft said Tuesday the court will find Microsoft’s goal. “We will continue to listen to our customers and programming option of taking advantage of Windows features when writing software using the Java Compatibility Logo on its packaging and websites for Internet Explorer and Software using the best tools and programming language. Providing the Java language. Providing the Java programming language to write great software Developers Kit for Java. “We remain confident that once all the facts are presented in the forefront of helping developers have the option of taking advantage of Windows features when writing software Developers use the Java Compatibility Logo on its packaging and websites for Internet Explorer and Software using the best tools a nd provide them the tools they need to write cutting-edge applications. The company would comply with this decision, but we will immediately comply with this decision, but we will immediately comply with a preliminary ruling by Federal District Court Judge Ronald H. Whyte that Microsoft is no longer able to use the Java language,” added Tod Nielsen, General Manager for Microsoft’s goal.


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6.2. Conversational Agents Conversational Agents are bots that have conversational abilities. A decent conversational interface must accomplish more than basic string manipulation or articulations looks. Understanding dialect and planning persuading answers is a significant undertaking. Conversational operators can give organized discussion and can likewise control the stream of exchange and flow of dialogue.

A Dialogue Example There are various approaches to state a specific thing. For instance, on the off chance that we need to discover ‘asian food near me.’, the assortment of search queries could appear to be like this: Asian food near me please Food delivery place not far from here Thai restaurants in my neighborhood Indian restaurant nearby Sushi express places please Places with asian cuisine Etc. Some of these inquiries are expansive while others are smaller in scope. The chatbot itself can help guide the discussion towards the ‘asian food’ point with the assistance of inquiries and proposals.[30]

[45] Bashmakov, P. 2016, Advanced Natural Language Processing Tools for Bot Makers – LUIS, Wit.ai, Api.ai and others (UPDATED).Stanfy. Available at: https://stanfy.com/blog/advanced-natural-language-processing-toolsfor-bot-makers/.(Accessed: 3 August 2017).


Fig 6.2. Examples of dialogues with a conversational bot. We can try to steer the conversation towards the desired ‘asian food’ topic with the help of questions and suggestions from the bot.

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Fig 6.3. Yes/No answers variations. It is clear that chatbots need some way of understanding the language and conversational phrases that are more sophisticated than just a simple text search by phrase or even regular expressions.


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Dialogue Structure in Natural Language Processing Intents Entities Parameters Sessions Contexts In the example above we can see that each expression from the users has the intent to take some action. Intent is the central idea in building a conversational UI. The primary aim is always to comprehend the Intent in a user’s message. This implies mapping an expression to a particular activity that we can define. Alongside the Intent, it’s important to recognize the parameters of activities from the expression. In the case with ‘asian food’, the words ‘close-by’ or ‘close me’ relate to the current location of the user.

Parameters are also called entities and often belong to a particular type. Examples of entity types that are commonly supported in language understanding systems are:

Location Datetime Number Enumeration (predefined list of named things) Contact Distance Duration


Fig 6.4. Dialogue structure for bots interface. A Session usually represents one conversation from beginning to end.

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A Session delimits the beginning and end of a conversation. An example of one session is when you order a flight from your starting point: ‘I need a flight to London’ (the intent), then through subsequent interactions (questions and answers) you get the information about a booked flight and finish the interaction. For storing the intermediate states and parameters from previous expressions during the dialogue we usually use Context. Context represents the short-term memory that is stored about the user’s replies through a session. There can be more than one contexts during one conversation that nest into one another. For example, from the user expression that represents the BookFlight intent, we started a new context, BookFlightContext, which indicates that we are currently collecting all parameters needed for the booking.

So some of the technical tasks of the chat bot app (or conversational agent) are: 1. Understand the language in a plain text (or voice translated into text) as well as the Intent with Parameters. 2. Process the Intent with Parameters and execute the next action to continue a dialogue with the user. (Result is a response or a subsequent question to continue the conversation by getting more data from the user and filling needed parameters in order to fulfil the action). 3. Maintain the Context and its state with all parameters received during the single Session in order to get the required result to the user.


Fig 6.5. A nested context example in a branched dialogue.

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6.3. Natural Language APIs 6.3.1. IBM Watson Developer Cloud Services This particular API is an ancestor of IBM Watson’s famous technology that won the TV show “Jeopardy” in 2011. The API set includes language understanding, insights and dialogue processing. Although there are alot of tools to explore, it is difficult to integrate them into a single application.

6.3.2. Amazon Alexa Skill Set Amazon Alexa is already deployed and being used by millions of Amazon Alexa. So, in that sense it is already successfully tested by millions of users. It is also one of the simplest tools to use for language processing. With Amazon Alexa Skills Kit you can define Intents and Entities for your task. However, the drawback is that Alexa system can not recognize intents that are not directly entered into the expression set.


Fig 6.6. IBM Watson list of services.

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Fig 6.8. Setting up Alexa Skills.


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6.3.3. Api.ai – conversational UX Platform

6.3.4. Microsoft Language Understanding Intelligent Service (LUIS)

API.ai has built-in domains of knowledge (Intents with Entities and even suggested Replies) on topics like small talk, weather, apps and even wisdom. This makes it very easy to build and deploy a basic application. Agents can recognize these Intents without any additional trainingThere are up to 35 different domains with full English support and partial support for the other six languages.

LUIS provides Entities that you can define and then teach to recognize a LUIS system from a free-text expression. There are also Hierarchical Entities that are helpful for recognizing different types or sub-groups. For instance, a FlightDate entity can have a ToDate and a FromDate which can be recognized separately. Currently, however, there are limitations of up to 10 Entities of each type per application.

Api.ai provides integrations with different bot platforms including Slack, Facebook Messenger, Kik, Alexa and Cortana. Api.ai is a solution that you can use for building quite advanced conversational interfaces.


Fig 6.9. Intent creation view in Api.ai.

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Fig 6.10. LUIS training mode.


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6.3.5. Facebook Wit.ai Bot Engine Wit.ai allows you to build the conversational interface around stories, which feels more natural and easier to follow than other interfaces. In Wit.ai we can use Entities, Intents (it’s actually just a custom entity type here), Context and Actions concepts that together form the model based on Machine Learning, and statistics can be used later for understanding the language. Wit.ai has a great Inbox feature where you can access all incoming messages from the users, and label them if they were not recognized correctly.This is a great API for expermineting with Natural Language Processing as it is free and fun to use.

Fig 6.11. Wit.ai stories interface for dialogue definition. Source: https://stanfy.com/blog/advanced-natural-language-processingtools-for-bot-makers/.


Fig 6.12. Wit.ai dialogue example with intents, entities and a context.

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Fig 6.13. Wit.ai Chat UI for conversation testing.


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6.4. Network Topology The six key network topologies describe not only computer networks but also draw parallels to organizational and social networks, both natural and man made. [46]

“Leadership is emergent. Different scenarios require different behaviours from both leaders and followers.”

The Internet of things for the home is commonly describe using the Star or Extended Star Topologies with a ‘Hub’ at center and groups of objects connected and controlled by the Hub. The ‘Smart Hub’ as it is called, is the intermediary between the human being and his plethora of ‘smart things’. [47] The human interacts with his things by communicating with the hub, rather than directly with the things themselves. Thus, the ‘smart things’ in the internet of things have no voice of their own and are reduced to mere secondary nodes. Apple’s ‘Siri’, Amazon’s ‘Alexa’ and Google Home are the most prominent examples of the Smart Hub trend. Interestingly, these smart hubs are being marketed as ‘Assistants’, many of them employing female voices. An ‘assistant’ to manage all your smart things. The role of the assistant indicates servility to human users.

[46] EFY News Network. 2015. Mesh Network Topology for IoT Applications. Available at: http://electronicsofthings.com/expert-opinion/mesh-network-applications/2/. (Accessed 5 August 2017) [47] Swearingen, J. 2017. Why All Your Gadgets Want You to Talk to Them. Selectall. Available at: http://nymag.com/selectall/2017/04/why-voice-assistants-will-matter-for-the-smart-home-future.html. (Accessed 5 August 2017):


Fig 6.14. Six Common Network Topologies. A simple formula for describing the Internet of Things.

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Fig 5.15. Internet of Things Ecosystem.


Fig 6.16. The IoT Smart Home Hub Model. In the Hub model, one device acts as the interface between the user and all the other smart objects in the home. All interactions take place only between the user and the ‘hub’ or assistant device while the other smart devices remain in the periphery.

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6.4.1. The Music Metaphor for the IoT If we extend the music metaphor for the Internet of Things, we find that the IoT, in it’s current form is akin to an orchestra. The score is laid out in advance, practiced and perfected. Each instrument knows it’s part. No one breaks their cue and every bar is methodically precise, running to the sway of the conductor’s baton. The Hub acts somewhat in the role of the conductor of an orchestra, upon whose command and instruction, the others may interpret a piece of music. The smart hub ‘orchestrates’ the devices in the smart home by means of data transfer protocols. Metaphors make it convenient to understand things by relating them to other things. If we extend the music metaphor for the Internet of Things, we find that the IoT, in it’s current form is akin to an orchestra. The score is laid out in advance, practiced and perfected. Each instrument knows it’s part. No one breaks their cue and every bar is methodically precise, running to the sway of the conductor’s baton.

But there are other styles of music that are improvisational. A good example is jazz music. In a jazz band, although there is a band master, he performs with the band and does not stand at the head. The band master may initiate a rhythm or a ‘theme’ but the notes are not fixed. The band cotinues to improvise around the theme or rhythm, taking turns in the spotlight and carefully responding to each other’s instruments. The music is created on the fly, there existing a certain connection or bond amongst the band members which enables them to synchronize themselves into producers of a pleasurable piece of music . [48] In Hindustani music there is the traditon of ‘Jugalbandi’ in which musicians play variations of a ‘raag’ or scale of notes, taking turns and respnding or ‘talking ‘to each other in an improvisational fashion. A commonly observed feature is when one player players a series of notes and another responds with an ‘answer’ almost as if the two instruments are engaged in conversation. The improvisatonal style resembles more the Mesh Network Topology where each node interacts with every other node in the network.


Fig 6.17. Jazz Band vs. Orchestra . The Orchestra Conductor, standing at a pedestal with a baton, is unquestionably the in-themoment leader . The Jazz Leader, sitting with his musicians, sets the stage for the performance, but then becomes a contributor.

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Fig 6.18. Jazz Band vs. Orchestra Network Topologies. An orchestra resembles Star Network Topology whereas a Jazz Band resembles the Mesh Network Topology.


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Fig 6.19. Vienna Philharmonic Orchestra in Hong Kong with German conductor Christoph Eschenbach. The Vienna Philharmonic Orchestra has the status of being historically associated with some of the greatest composers and conductors.

Fig 6.20. Austrian conductor Franz Welser-Moest and the Vienna Philharmonic Orchestra perform the traditional New Years Concert on January 1, 2013 at the music association in Vienna, Austria.

[48] Simpson, B. 2014. Jazz vs Orchestra: A question of control? Available at: https://beverleysimpson.com/2014/03/25/jazz-vs-orchestra-a-question-of-control/. (Accessed 5 August 2017.) [49] Ibid., 179. [50] Ibid.


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The Classical conductor is an exquisite example of a great hierarchical leader. But there are also times when there are several agents all with something new to say ...where the leader needs to set the necessary agreements and then get out of the way of the music... Leadership is emergent. [49] When thinking of complex adaptive systems, there are many aspects of Jazz that are fascinating and created fresh in the moment – including leading with less control but full responsibility, following while leading, listening with presence, and living with ambiguity. [50]

Fig 6.21. Mamie Smith’s Jazz Hounds in 1923 with Coleman Hawkins 2nd from right above playing tenor saxophone. The early New Orleans style of jazz was polyphonic, based on collective improvisation rather than solos with accompaniment.


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6.5. 3D Printing What is 3D printing?

3D modeling software

3D printing or additive manufacturing is a process of making three dimensional solid objects from a digital file. The creation of a 3D printed object is achieved using additive processes. In an additive process an object is created by laying down successive layers of material until the object is created. Each of these layers can be seen as a thinly sliced horizontal cross-section of the eventual object. [31]

3D modeling software also comes in many forms. There’s industrial grade software that costs thousands a year per license, but also free open source software, like Blender, for instance. Tinkercad has a free version and it works in browsers that support WebGL, for instance Google Chrome. They offer beginner lessons and has a built in option to get your object printed via various 3D printing services.

How does 3D printing work? It all starts with making a virtual design of the object you want to create. This virtual design is for instance a CAD (Computer Aided Design) file. This CAD file is created using a 3D modeling application or with a 3D scanner (to copy an existing object). A 3D scanner can make a 3D digital copy of an object.

When you have a 3D model, the next step is to prepare it in order to make it 3D printable.

3D communitites MakerBot’s Thingiverse is a thriving design community for discovering, making, and sharing 3D printable things. As the world’s largest 3D printing community, we believe that everyone should be encouraged to create and remix 3D things, no matter their technical expertise or previous experience.

[51] What is 3D Printing? 3D Hubs. Available at: https://www.3dhubs.com/what-is-3d-printing. (Accessed 12 July 2017).


Fig 6.22. 3D printing on a Makerbot Replicator.

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6.6. Hardware 6.6.1. Microphones CCTV Microphones Security Cameras with Audio have microphones that allow easy recording of audio from the camera to the DVR recorder. These are highly sensitive microphones. The CCTV mic is usually sensitive enough to hear sounds from up to 40ft.These are highly sensitive microphones. ft away in a quiet room.

Webcam Microphones Many webcams come equipped with mini microphones. These microphones have a decent range and make perfect sense for projects that incorporate both audio and video based applications.

Respeaker ReSpeaker responds to your voice and recognize your speeches based on powerful online cognitive services like Microsoft Cognitive Service, Amazon Alexa Voice Service, Google Speech API.

USB Microphones Blue Snowball Blue Snowball is a studio grade USB mic that is a very neat solution to recording audio into a laptop or domestic computer system. It produces subjectively high-quality results, providing you use it close enough to the source to get a healthy recording level. The plug and play feature makes it a convenient microphone for desktop based applications. However, the large size is a definite drawback for smaller projects where size is a constraint.

USB Mini Microphones Mini USB Microphones are available from various manufacturers. These little USB microphones are the right fit for adding a mic. to a Raspberry Pi or computer. It’s ideal for adding basic sound capture to a project. Noise-cancelling will help to filter out unwanted background noise. The recording range and quality is surprisingly good for the size and definitely, the tiny form makes it ideal for projects which require smaller parts


Fig 6.23. CCTV Security Camera Inline Audio Microphone with Loop Through Power.

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Fig 6.24. Mini USB Microphone. Product Dimensions: 22.2mm x 18.3mm x 7.0mm.


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6.6.2. Speakers Logitech X50 Mini Bluetooth Speaker The smallest Bluetooth Speakers available commercially. Its tiny size (26.8x26.8x28.5mm) makes it a must have for small sized projects. It connects up to 10 meters (32 Feet).

Hamburger Mini Speaker The Hamburger Mini Speaker is a 3W economical speaker option for any project needing stand-alone sound. The Hamburger features a built-in lithium polymer battery for portable application, a 3.5mm stereo jack.


Fig 6.25. Mini Bluetooth Speaker.

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Fig 6.26. Hamburger Mini Speaker.



7

Designing the Society of Objects

7.1. 7.2. 7.3. 7.4. 7.5. 7.6. 7.7. 7.8. 7.9.

Designing Object Template Designing Intents Designing object-to-object interactions Designing human-to-object interactions Designing the artefacts Affordances for the Internet of Things Designing the space Model Construction Designing Conversation


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7.1. Designing Object Template A template was created, which would serve as the skeletal structure for object identities. The template was understood as a generic internal structure that could be customized according to each object’s identity. Each human being is born with underlying capabilities that one then appropriates according to his/her abilities, interests, values and beliefs. Much like the language and speech abilities, hearing and voice that every human being is born with. this template reflects the underlying structure of every object in the Society of Objects. However, each human being appropriates this basic structure in unique ways, giving form to a distinctive identity. These ‘identity’ markers include Voice - The Pitch, timbre , tone, volume and accent. Grammar - Variabilities in sentence structure. Vocabulary - Frequency of word use, range of vocabulary. Topic of discussion - Interests, values and beliefs. Similarly, the template would be appropriated by each object, giving it a unique, recognisable, stable identity.


Fig 7.1. Object Template System Flow.

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Fig 7.2. Object Template. Object Template with Audio Input, Google Speech Recognition, Wit.ai integration and Natural Language Generation and Audio Output.


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7.2. Designing intents Intents were designed for each object on wit.ai. Different approaches were applied towards designing intents. 1. Functionality-Centric Intents These intents are closely related to the functional use or perceived related attributes. For example, the sofa’s function is primarily for sitting or lounging. The Sofa’s intentions are therefore to encourage someone to sit on it. An alarm clock tells the time. The intentions of the Alarm clock are designed to encourage time management and punctuality. 2. Object Identities as extensions of the self A person who sits on a sofa too much is seen as being lazy. The sofa is perceived as a ‘lazy’ object. In this case, the ‘smart object borrows personified attributes from the user and is thus seen as an extension of a certain aspect of the user’s identity. In this case, intents evolve with user’s behaviour and object intents in turn influence user behaviour, forming a feedback loop.

3. Objects as ‘time-using’ technologies. The main intention of each object would be to engage the user for as much time as possible. The idea that each object is vying for attention. This ‘time-using’ tech entices us to behave in ways that encourage engagement with the object. Thus, the intention of each object is to promote user engagement with itself through conversation. By engaging the user in conversation, the object fulfils its ‘use. In a film script, characters divulge aspects of their personality through conversation, moving the plot along. Similarly, the object in the Society of Object reveal their identities through conversation.


Fig 7.3. Image.

Training Intents in sentences. Author’s

Fig 7.5. Different Applications for each object. Author’s Image.

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Fig 7.4. Expression Training. Author’s Image.

Fig 7.6. Keyword based Intents. Author’s Image.


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4. Gossip-driven Intents

iii. Gossip as Counter-Surveillance Activity

i. Gossip as Social Currency

Intents -

Intents -

build firendships form groups gain social recognition rise in the social heirarchy rally the mob form a group or become part of a group become a leader

ii. Gossip as Information Dissemination Intents -

reveal user behavior talk about tasks done disclose physical health and status notify about servicing and maintainence discuss sensor data talk about neighbours, community and local news discuss general knowledge and philosophy

Reveal clues about captured data Scramble or Codify data Interpret data from multiple points of view Provide opposing and unverifiable versions of events


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7.3. Designing object-to-object interactions. Multiple instances of the initial object template were created. Each instance of the template represents the identity of one of the objects in the Society of Objects. In order to generate conversation between the objects, the conversational output of one object was fed as input to other objects and the resulting output fed again into the system and so on and so forth. This creates a stimulus for conversation and allows conversation to evolve between the objects.

Proximity Based Interaction

Initially, the system was set up for 2 objects connected to a single speaker and microphone. Next, each object was given an individual speaker and microphone. The system was then tested with 3, 4 5 and then 6 objects.

Designing for Misunderstandings.

The interactions between objects in the Society of Objects is influenced by physical proximity, much like in the interactions between human beings. An object that is further away from others may be excluded from the conversation or may incorrectly hear snippets of the conversation.

The interactions between objects are conversational and thus, much like human-human conversation, subject to misunderstanding based on the following factors. 1. Proximity 2. Accent 3. Voice, pitch and timbre 4. Volume 5. Noise in the external environment 6. Number of objects talking simultaneously resulting in chatter


Fig 7.7. Object to Object Interaction. Left: Two objects with single speaker and microphone. Right: Two objects with individual speakers and microphones and Raspberry Pis.

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Fig 7.8. Object Interactions Setup. Three Groups of three objects, each group having an individual microphone and speaker. Each group takes audio input and generates audio output.


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7.4. Designing human-to-object Human Beings can walk through the space, interacting with the objects. Various kinds of textured surfaces denote interaction capabilities of objects. Speaker grills denote sound, microphone patterns denote voice input. Visitors to the space may speak amongst each other, listen in to what the objects are saying or choose to converse with the objects. Regardless of human intervention, however, the objects continue to chatter and one can hear object voices through the house.


Fig 7.9. Interactions. Visitors to the space may speak amongst each other, listen in to what the objects are saying or choose to converse with the objects. Objects converse regardless of human presence. Conversations are based on proximity and are subject to misinterpretation.

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7.5. Designing the artefacts. The artefacts are objects of domestic technology. These include white goods such as refrigerators, brown goods such as televisions and also objects that are not usually digitally enhanced such as sofas, beds, tables and teapots. While designing the artefacts, it was important to retain the physical form in sufficient detail, such that the object be instantly and easily recognisable. Templates of generic forms of these objects were available on Thingiverse and other such open source 3D communities These templates were then modified in the TinkerCAD software and 3D printed in 1:10 scale.


Fig 7.10. TinkerCAD - Object Designs.

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Fig 7.11. 3D model of Washing Machine.


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Fig 7.12. Sofa.

Fig 7.13. Oven and Stove.


Fig 7.14. Washing Machine.

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Fig 7.15. Lamp.


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7.6. Affordances for the Internet of Things. In his book The Design of Everyday Things, Donald Norman defines affordances as follows: Affordances provide strong clues to the operations of things. Plates are for pushing. Knobs are for turning. Slots are for inserting things into. Balls are for throwing or bouncing. When affordances are taken advantage of, the user knows what to do just by looking: no picture, label, or instruction is required. Complex things may require explanation, but simple things should not. When simple things need pictures, labels, or instructions, the design has failed. —The Design of Everyday Things, MIT Press, 1998 As adoption of the Internet of Things gathers pace, more and more of our cities, homes, and environment will become suffused with technology. With these additional behaviors and capabilities will come additional complexity—something that successful designers of connected devices and services will need to counter. By their very nature, many of the new capabilities bestowed upon objects will be hidden from sight or not immediately apparent from first glance, which makes intuitive design difficult.[52]

[52] McEwen, A. and Cassimally, H., 2013. Designing the internet of things. John Wiley & Sons.

1. What are the affordances of digitally enhanced objects? 2. How do we identify that an objects is ‘smart’? How do we distinguish such smart objects from regular objects? 3. In what way is the object smart i.e. what are it’s capabilities? 4. Is the object interactive? In what ways can users interact with the object? What kinds of input and output does it accept? How do we convey to the user of an object that it can communicate with the user? An important start is to keep the existing affordances of the object being enhanced. Users who don’t realize that a device has any extra capabilities should still be able to use it as if it hasn’t. The first batch of artefacts for the Society of Objects succeeded in retaining their recognizable physical features. However, the digital capabilities of the objects remained hidden. In this case, my objects could have conversations with the user via a microphone input and a speaker output. How would I make it apparent to users that these interactions were possible? I did so by borrowing already established symbols. By using a speaker grill pattern like the one that is seen on most speakers, albeit in a larger size. For the microphone, the common 3 by 2 hole matrix was used.


Fig 7.16. Test piece. Piece printed to test the size of sound holes, size for speaker and microphone, sound quality, print quality.

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Fig 7.17. Cabinet with microphone, speaker and grilled cap.


Fig 7.18. Boombox with microphone, speaker and grilled cap.

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Fig 7.19. Sofa.

Fig 7.20. Refrigerator.


Fig 7.21. Bed.

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Fig 7.22. Kitchen Sink.


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Fig 7.23. Sofa with microphone, speaker and Raspberry Pi.

Fig 7.24. Bed with microphone, speaker and Raspberry Pi. Image


Fig 7.25. Cabinet with microphone, speaker and Raspberry Pi.

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7.7. Designing the space. The space is set up as a house with a living room, a kitchen, a bedroom and a bathroom. The objects are arranged around the house as they would be in any ordinary household, establishing proximity relationships between objects. Rooms provide context for each object and objects are grouped according to their use or purpose. Smaller objects such as a vase, alarm clock and photo frame are arranged to sit on larger objects. The space is not too cluttered and there is sufficient room for people to walk around the objects and interact with them. In the full-scale set-up, visitors may sit on the sofa or lie on the bed but the objects themselves are not functional in their traditional sense.


Fig 7.26. Man in Kitchen.

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Fig 7.27. View from entrance.


Fig 7.28. Bedroom containing Bed with Pillow, Cabinet with Alarm Clock and Photo Frame and Bookshelf with Lamp.

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Fig 7.29. Living Room with Sofa, Television, Speakers, Table with Flower Vase.


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7.8. Model Construction. A 1:10 scale model of the space was constructed using PV Foam Board. The model represents the actual arrangement and layout of the final installation. The walls of the model were kept lower so as to allow an overall view of the space from any angle. The model was used to shoot photographs and concept videos as well as for the proof of concept prototype.


Fig 7.30. Scale Model, without objects.

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Fig 7.31. Scale Model. with objects.


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Fig 7.32. View from Living Room.


Fig 7.33. TV Unit with bookshelf and flower vase.

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Fig 7.34. Kitchen.

Fig 7.35. Man in Kitchen.


Fig 7.36. Man with Toaster.

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Fig 7.37. Bedroom.


Fig 7.38. Man in Bedroom.

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7.9. Designing Conversation In the society of objects household, everything you say is remembered. The objects share a collective memory of every conversation that occurs within the house. In a sense then, their intrusion on privacy is direct and intentional, not disguised or surreptitiously incurred. They make clear their tattle-tale tendencies and more importantly, make apparent that their nature is to gossip. In doing so they reveal themselves as objects of entertainment, stimulators of conversation and revealers of information. Although at times their behaviour may cross dignified lines, they question the very attitudes of the human beings who interact with them. The objects in the society all have female voices. In a sense, they take over the domestic space, marking their territory, making it their own. When you enter the society of objects, you enter their dominion. Unlike their predecessors - subservient female assistant bots, these women won’t bid your command. Your words might yield a snappy retort, a sarcastic quip, a blatant dismissal or even all-out blackmail. Don’t expect to come out of a conversation with your head held high.

While designing the conversations, Markov chains are used to demonstrate how the objects generate conversation. They take as input the collective record of every conversation they hear. These conversations pass through layers of a Markov chain until the objects generate their own version of events. The conversations thus produced present the gathered data in new interpretation. The interpretations are often amusing, unpredictable, sometimes incomprehensible but almost always extremely relevant. To start off a base for the personalities, a corpus of conversations was compiled from dialogue of 2 movies - What Women Want and The Stepford Wives. These movies were chosen for their predominantly female characters and their female-oriented subject matter. The following sample conversations were generated in this fashion. Later, as the objects inhabit the space, they will be exposed to more conversation and their conversation will evolve over time.


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7.9.1. Scene 1: When the guests are over for dinner. Characters : Oven Kettle House Plant Lamp Refrigerator Washing Machine Alarm Clock Sofa Bed The Hosts : Mary and Bill the parents, their son Ben The Guests : Michael, Annie Georgie and James, Joanna and Jill


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Alarm Clock : Where are they?

Lamp: Why aren’t you married?

Sofa: Behind your ear.

Michael: Why?

Oven : Bill, leave that bread roll alone.

Alarm Clock: Go on.

Sofa: Where are they gonna sit?

Washing Machine: Annie, you’ve got to make him a proposition.

Mary: Why is my fish taking so long?

Annie: What’s this?

Alarm Clock: Quick!

Washing Machine: Michael, I’ve seen you watch her skirt fly up when you’re not looking.

Oven: I don’t want it destroyed, idiot! Mary: Give me that. Michael: Yoo-hoo! Alarm Clock: Mike’s here. House Plant: Hello Sofa: Sit down, Michael, and tell us all about yourself.

Michael: I think not! Lamp: I’ve seen you sniffing her, Michael. Bill: You protect yourself, son, you need it. Michael: Go ahead, go ahead, have fun. Sofa: Well, you know the truth about Barbara.


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Michael: She’s got a heart of gold and she wasn’t worth it.

Lamp: You own this building, don’t you, Bill?

Annie: What the hell are you talking about?

Mary: Ben, get up and get me some hot water, eh.

Alarm Clock: Hi, Georgie’s here with James.

Washing Machine: And a towel and soap.

Sofa: Come on, Georgie, go in there, raise your skirts and warm my seat.

Ben: Don’t be stupid.

James: How dare you say that? Bill: I’ll bloody kill you Mary: Behave, she’ll behave. Sofa: l’m so sorry. Bugs in my ears. Bill : You ladies will have to eat in peace. Mary: I’m sorry about this, Mike. Sofa: Don’t talk to him like that.

Kettle: No, you’d never get that water with wife snatchers. Alarm Clock : Jill! I got to tell the press that you’d be late again. Lamp: Good evening, Joanna. Kettle: Coffee? James: This custard’s salty. Oven: It’s amazing, isn’t it? Kettle: You are insulting the chef. Refrigerator: Personal compliments of the pantry.


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Oven: If you don’t want to taste it…

Lamp: And it’s also a smart house.

Mary: Stop it!

Sofa: Women like choirboys.

Kettle: He’s eating avocado vinaigrette and prawns.

Kettle: Napoleon was a choirboy when I was a choirboy once.

Sofa: Your bottom’s going to eat the celery with his fingers.

Michael: I’ve got a great big hand. You know

Lamp: Churchill liked seafood.

Sofa: And that’s a problem because..

Refrigerator: His mother is a culinary artist, not a library.

Annie: Well, I’m sorry, but my shrink says I should be going

Sofa: **** you! Your cuisine will be just one big car park.

Alarm Clock: We need an ambulance.

Annie: Come on, Michael. For God’s sake, I should be home with my cupcakes.

Bill: Stop it.

Oven: Is that what you wanna be? Because you’re right. This place does something to people. Bill: Where the women are like deranged-flight-attendant friendly.

Kettle: She’s dehydrated. Oven: I like to introduce on a lightly-toasted sesame seed bagel my new book. The menfolk. Kettle: The Mystery of why the men are always busy.


Mary: Oh, there’s a call for you, Jill. Alarm Clock: Actually, I made it Bill: We’ll forget it, eh? And make it quiet. Alarm Clock: Aren’t I? Lamp: Georgina! Pick it out of it. Don’t read at the table. Washing Machine: And your nails could do with a clean. Georgina: It’s got a skin round it. James: I wonder how you get on with your eating round here, eh? Alarm Clock: You can start, James. Oven: Yes, you can finish your soup, James. Lamp: Is that a Jewish name, James?

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James : No.

James: May I eat whilst you smoke?

Sofa: What’s this? You’re not wearing any bloody knickers.

Oven: Sure, go ahead.

Annie: What’s this mean?

Michael: Goodbye, everybody! Come on, Annie, let’s go.

Refrigerator: Allowing decent people to dine with no knickers on?

Sofa: Don’t get up.

Annie: We are leaving. Sofa: No. Lamp: Do you eat kosher food, James?

Sofa: You know I was dreaming of your.. Annie: Oh, come on. Michael: Annie. We have to go

James: No.

Bed (from other room, muffled): In memory of us making love in your trousers.

Bill: That’s it! You’re staying in under lock and key.

Michael: What did you say?

Sofa: Why?

Annie: What the hell are you talking about?

Bed ( from other room, muffled ): You, go and have a baby. Michael! - Go on!

Michael: Goodbye, everybody! Come on, let’s go.


Mary: Where are they? House Plant: They went to eat in the streets. Sofa: Lovers always behave like that? Bill: l’ll bloody kill you for what you did. You let me down. Sofa: I can shout in my fantasies. James: This custard’s salty. Kettle: Do-si-do, do-si-do, Alarm Clock: Goodnight, everybody!

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8

Conclusion 8.1. Conclusion


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8.1. Conclusion Weiser’s Ubiquitous Computing for the workplace has perpetuated for a quarter of the twenty-first century. The focus on efficiency, productivity and automation make the workplace a fitting setting for the Internet of Things in it’s current form - a group of sensors and actuators producing large amounts of data. Few attempts have been made at non-technical approaches to the IoT and in this respect, Ericsson’s work on the Social Web of Things lends diversity to the issue. But the fate of the Internet of Things may very well unfold much closer to home. Today, we have the technical capabilities to create a fully-loaded Smart Home, not dissimilar to the ones imagined by science fiction decades ago. The questions, then, must shift from what is technically possible to matters of concern that have, so far, been largely overlooked. The socio-technical construction of the home, the interplay between gender and domestic technologies, the ethical concerns surrounding intelligent devices in the home and the question of aesthetics for the Smart Home must be made the focus of future work.

What will Smart Devices look like and what kinds of intelligence will they display? Will Smart Things be gendered? How will Smart Objects afford interaction? How will human beings and intelligent things co-exist in the domestic space? What kind of conversation will the Smart Home lend itself to? How will the Smart Home organize itself around notions of gender and gender roles? What ethical concerns will arise and how can such concerns be discussed? The Internet of Things has, until now been confined to the technical fields of computer science and networking. Attempts to project the Internet of Things into the domains of art and speculative design have not been made. Doing so makes the concept accessible to diverse interpretations and establishes a multitude of concerns. One can hope, therefore that the Internet of Things will emerge from it’s ‘tech-centric’ shackles to traverse diverse paths of exploration.


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9

Bibliography and References 9.1. Bibliography and References 9.2 Image References


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9.1. Bibliography and References Papers/ Publications/ Conference Proceedings/ Essays/ Journal Articles Weiser, M., 1991. The Computer for the 21 st Century. Scientific american, 265(3), pp.94-105.

Brown, M., Coughlan, T., Lawson, G., Goulden, M., Houghton, R.J. and Mortier, R., 2013. Exploring Interpretations of Data from the Internet of Things in the Home. Interacting with Computers, 25(3), pp.204-217.

Bostrom, N. and Sandberg, A., 2011. The Future of Identity. Report, Commissioned by the UK’s Government Office for Science. See http://www. nickbostrom. com/views/identity. pdf.

Barnaghi, P., Wang, W., Henson, C. and Taylor, K., 2012. Semantics for the Internet of Things: early progress and back to the future. International Journal on Semantic Web and Information Systems (IJSWIS), 8(1), pp.1-21.

Cockburn, C., 1997, May. Domestic technologies: Cinderella and the engineers. In Women’s Studies International Forum (Vol. 20, No. 3, pp. 361-371). Pergamon.

Nagao, K. and Takeuchi, A., 1994, August. Social interaction: Multimodal conversation with social agents. In AAAI (Vol. 94, pp. 22-28).

Rysman, A., 1977. How the “gossip” became a woman. Journal of Communication, 27(1), pp.176-180.

Hoffman, D.L. and Novak, T.P., 2017. Consumer and object experience in the Internet of Things: An assemblage theory approach. Journal of Consumer Research, 44(6), pp.1178-1204.

Ronald, E. and Sipper, M., 2000. What use is a Turing chatterbox?. Communications of the ACM, 43(10), pp.21-23. Ronald, E.M. and Sipper, M., 2003. Intelligence is not enough: On the socialization of talking machines. In The Turing Test (pp. 151160). Springer, Dordrecht.

Shin, D., 2014. A socio-technical framework for Internet-of-Things design: A human-centered design for the Internet of Things. Telematics and Informatics, 31(4), pp.519-531.


Gubbi, J., Buyya, R., Marusic, S. and Palaniswami, M., 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future generation computer systems, 29(7), pp.1645-1660. Kortuem, G., Kawsar, F., Sundramoorthy, V. and Fitton, D., 2010. Smart objects as building blocks for the internet of things. IEEE Internet Computing, 14(1), pp.44-51. Atzori, L., Iera, A. and Morabito, G., 2011. Siot: Giving a social structure to the internet of things. IEEE communications letters, 15(11), pp.1193-1195. Atzori, L., Iera, A., Morabito, G. and Nitti, M., 2012. The social internet of things (siot)–when social networks meet the internet of things: Concept, architecture and network characterization. Computer networks, 56(16), pp.3594-3608. Atzori, L., Iera, A. and Morabito, G., 2014. From” smart objects” to” social objects”: The next evolutionary step of the internet of things. IEEE Communications Magazine, 52(1), pp.97-105.

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Kranz, M., Roalter, L. and Michahelles, F., 2010, May. Things that twitter: social networks and the internet of things. In What can the Internet of Things do for the Citizen (CIoT) Workshop at The Eighth International Conference on Pervasive Computing (Pervasive 2010) (pp. 1-10). Bassi, A. and Horn, G., 2008. Internet of Things in 2020: A Roadmap for the Future. European Commission: Information Society and Media, 22, pp.97-114. Casagras, R.F.I.D., 2011. the inclusive model for the Internet of Things report. EU Project, (216803), pp.16-23. McAndrew, F.T., 2008. The science of gossip: why we can’t stop ourselves. Scientific American, 19(6), pp.26-33.


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Books McEwen, Adrian, and Hakim Cassimally. Designing the internet of things. John Wiley & Sons, 2013. Dunne, Anthony, and Fiona Raby. Speculative everything: design, fiction, and social dreaming. MIT Press, 2013. Orwell, George. Nineteen Eighty-Four,1949. Atwood, Margaret. The Handmaid’s Tale,1985. Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006. Neil, Gershenfeld. “When things start to think.” (2000). Bryant, Levi R. The democracy of objects. Open Humanities Press, 2013. Rose, David. Enchanted objects: Design, human desire, and the Internet of things. Simon and Schuster, 2014.


Websites http://www.nid.edu. New Media Design Programme Information. Available at: http://www. nid.edu/education/master-design/new-media-design/p-overview. html. (Accessed: 12 May 2017). Morgan, J. 2016, A Simple Explanation Of ‘The Internet Of Things’, Available at: https://www.forbes.com/sites/ jacobmorgan/2014/05/13/simple-explanation-internet-things-thatanyone-can-understand/#6f6770ef1d09 (Accessed 12 April 2018). Formo, J. 2012, A Social Web of Things, Available at: https://www. ericsson.com/strategicdesign/2012/04/a-social-web-of-things/ (Accessed 22 October 2017). http://www.wipro.com/india/. Brownlee, J. 2016, Conversational Interfaces, Explained, Available at: https://www.fastcodesign.com/3058546/conversational-interfacesexplained (Accessed 28 March 2018).

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Maruti Techlabs, 2017, What is a Conversational UI and why does it matter?, Chatbots Magazine, Medium, Available at https:// chatbotsmagazine.com/what-is-a-conversational-ui-and-why-itmatters-de358507b9a2. (Accessed 23 March, 2018). Garber, M. 2014, When PARRY Met ELIZA: A Ridiculous Chatbot Conversation From 1972, The Atlantic, Available at: https://www. theatlantic.com/technology/archive/2014/06/when-parry-met-elizaa-ridiculous-chatbot-conversation-from-1972/372428/. (Accessed 23 March 2018). Diatron.. 2010, When the machines talked to each other, Computable Minds, Available at: http://www.computableminds.com/post/ chatbot/eliza/parry/skynet/human-language/natural-language. (Accessed 23 March 2018. Maruti Techlabs, 2017, What Are The Best Intelligent Chatbots or AI Chatbots Available Online?, Chatbots Magazine, Medium, Available at https://chatbotsmagazine.com/which-are-the-best-intelligentchatbots-or-ai-chatbots-available-online-cc49c0f3569d (Accessed 23 March, 2018).


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Electronic Privacy Information Center. EPIC Letter to the Attorney General and the FTC Chairwoman, July 10, 2015. Request for Workshop and Investigation of “Always On” Consumer Devices. Available at: https://epic.org/privacy/internet/ftc/EPIC-Letter-FTCAG-Always-On.pdf. (Accessed 12 August 2017). Lomas,N. 2015, Techcrunch. Today In Creepy Privacy Policies, Samsung’s Eavesdropping TV. Available at: https://techcrunch. com/2015/02/08/telescreen/. (Accessed 3 November 2016). Swearingen, J. 2017. Why All Your Gadgets Want You to Talk to Them. Selectall. Available at: http://nymag.com/selectall/2017/04/ why-voice-assistants-will-matter-for-the-smart-home-future.html. (Accessed: 5 August 2017). http://www.womanhouse.net. Simpson, B. 2014. Jazz vs Orchestra: A question of control? Available at: https://beverleysimpson.com/2014/03/25/jazz-vs-orchestra-aquestion-of-control/. (Accessed 5 August 2017). EFY News Network. 2015. Mesh Network Topology for IoT Applications. Available at: http://electronicsofthings.com/expertopinion/mesh-network-applications/2/. (Accessed 5 August 2017).

Markov Model of Natural Language. Avaliable at: http://www. cs.princeton.edu/courses/archive/spr05/cos126/assignments/ markov.html. (Accessed 5 May 2017) Bashmakov, P. 2016, Advanced Natural Language Processing Tools for Bot Makers – LUIS, Wit.ai, Api.ai and others (UPDATED).Stanfy. Available at: https://stanfy.com/blog/advanced-natural-languageprocessing-tools-for-bot-makers/.(Accessed: 3 August 2017). What is 3D Printing? 3D Hubs. Available at: https://www.3dhubs. com/what-is-3d-printing. (Accessed 12 July 2017).


Videos TED + BCG - How should a CEO lead? Jazz vs Symphony. Character Animation, Kirart Production, Motion Graphics 2014. Based on an article by John Clarkeson. Martha Rosler, Semiotics of the Kitchen, 1975.

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9.2. Image References Chapter 1 Fig 1.1. National Institute of Design. The NID Post Graduate campus at Gandhinagar, Gujarat. Image Credits : Vivekanand YN, 2015. Fig 1.2. Lively Up Yourself!. An interactive installation designed by students of the New Media Design Program for the Story of Light Festival in Panaji, Goa. Image Credits : Saurabh Srivastava, 2015. Chapter 2 Fig 2.1. Project Timeline. The timeline depicting the process followed over the 18 month duration of the project. Author’s Image. Chapter 3 Fig 3.1. An Equation for the Internet of Things. A simple formula for describing the Internet of Things. Source : McEwen, Adrian, and Hakim Cassimally. Designing the internet of things. John Wiley & Sons, 2013. Fig 3.2. A painting of my home network (in progress). By Karin Dalziel. Source: https://www.flickr.com/photos/nirak/2242950723/.

Fig 3.3. How to design a ‘social’ internet of things? Things that talk, but how? The internet of things is going to provide us with a whole new data stream. But how will these things ‘communicate’ with us?. Source: http://labs.sogeti.com/how-to-design-a-social-internet-ofthings/. Fig 3.4. The Social Web of Things interface. Source: http://blog. tuhogarinteligente.cl/que-es-la-web-social-de-las-cosas/. Fig 3.5. Friends - My things. Source: http://www.pagina2.com.es/ the-social-web-of-things-habla-con-tu-casa-como-si-fuese-unamigo-mas/. Fig 3.6. How to design a ‘social’ internet of things? Things that talk, but how? Source: http://labs.sogeti.com/how-to-design-a-socialinternet-of-things/. Chapter 4 Fig 4.1. Wipro Headquarters in Bengaluru. Source: https://www. glassdoor.co.in.


Fig 4.2. Structure of Technovation Center. To attend to saily Client Visits, The Technovation Center was organized into four key groups, namely the Visits Team, Tech Team, Design and Hospitality. Author’s Image. Fig 4.3. An Equation for the Internet of Things. A simple formula for describing the Internet of Things. Source : http://www.wipro.com/ holmes/. Fig 4.4. The Gap in the Neo-Reality Project. Non-expert users couldn’t use the interface. Author’s Image. Fig 4.5. An interface for the Neo-Reality Project. A conversational interface to bridge the gap between the users and the smart devices. Author’s Image. Fig 4.6. The Social Group. Author’s Image. Fig 4.7. System Model of Technovation Center Experience. A map describing the processes, people, places and interactions involved in the Technovation Center Experience at Wipro.

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Fig 4.8. HAL 9000 Sings A Love Song To Dave Bowman in 2001: A Space Odyssey. In one of the most interesting on-screen depictions of a conversational interface, the relationship between HAL and Dave was revealed through sinister conversation. Image Credits: http://www.giantfreakinrobot.com/scifi/hal-9000-sings-love-songdave-bowman.html. Fig 4.9. The ELIZA conversational interface from 1966. ELIZA was one of the earliest chatbots. Styled as a psychotherapist, inspite of her rudimentary algorithm, she managed to engage a significant number of people in simulated conversation. Image Credits: https:// medium.com/@madrugado/what-are-the-dialog-systems-orsomething-about-eliza-9aefb551eaaa. Fig 4.10. Poncho Weatherbot. Poncho is a Facebook Messenger based bot that relies on conversational interface to answer questions about the weather. Poncho is one of the most used chatbots and shows the rising popularity of conversational interfaces. Image Credits: http://www.messengerchatbots.com/Reviews/hi-ponchoweather-chat-bot-walkthrough-review.aspx.


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Fig 4.11. Slackbot. Slackbot is a team based chatbot that helps team members with onboarding, queries, scheduling and many other tasks. Slackbot is a good example of a group-based conversational interface as bot human beings and IoT objects can chat through the slack interface. Image Credits: https://get.slack.help/hc/en-us/ articles/202026038-An-introduction-to-Slackbot.

Fig 4.17. Prototype, Mobile Application. Sample chats from the prototype displaying conversational interface. Author’s Image.

Fig 4.12. Concept Formulation. Author’s Image.

Fig 4.19. Prototyping with the DHT11 Sensor. Author’s Image.

Fig 4.13. 3 kinds of interaction in the Society of Objects. The Society of Objects has human beings and objects interacting with each other to form heterogeneous groups. Author’s Image.

Fig 4.20. Testing Bluetooth-to-Bluetooth communication with two HC-05 modules. Author’s Image.

Fig 4.14. Conceptual Space. The concepts under investigation in the Society of Objects. Author’s Image. Fig 4.15. The Gap in the Neo-Reality Project . A simple formula for describing the Internet of Things. Author’s Image. Fig 4.16. The Gap in the Neo-Reality Project . A simple formula for describing the Internet of Things. Author’s Image.

Fig 4.18. Prototype, Mobile Application. Sample chats from the prototype displaying Human-to-Object and Object-to-Object interaction through the conversational interface. Author’s Image.

Fig 4.21. Controlling an LED with text input. Author’s Image. Fig 4.22. Android Studio. Source: https://www.androidauthority. com/android-studio-tutorial-beginners-637572/. Fig 4.23. The Application code on Android Studio. Author’s Image. Fig 4.24. The Bluetooth Chat Application. The application allows two-way chat over Bluetooth. Source: http://android-er.blogspot. in/2015/06/import-android-code-sample-of.html.


Fig 4.25. Prototype, Circuit . Prototype displaying the three kinds of interactions in the Society of Objects. Author’s Image. Chapter 5 Fig 5.1. A Taxonomy of Futures. Redrawn from Speculative Everything. Redrawing Stuart Candy. Source : Dunne, A. and Raby F., (2013). Speculative Everything: Design Fiction and Social Dreaming. London: The MIT press. Fig 5.2. Technological Dreams Series: no 1, Robots Models. Anthony Dunne and Fiona Raby look at robots as individuals with their own distinct personalities and quirks, thinking that devices of the future might not be designed for specific tasks but instead might be given jobs based on behaviours and qualities that emerge over time. (www. moma.org). Source : Dunne, A. and Raby F., (2013). Speculative Everything: Design Fiction and Social Dreaming. London: The MIT press.

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Fig 5.3. DIKW Pyramid. Also known as the Knowledge Hierarchy Pyramid, it displays how data is related to information, knowledge and wisdom. Source: Barnaghi, Payam, et al. “Semantics for the Internet of Things: early progress and back to the future.” International Journal on Semantic Web and Information Systems (IJSWIS) 8.1 (2012): 1-21. Fig 5.4. Google Chrome. Chromium users are subject to constant voice recording in their private homes, without their permission or even their knowledge. Source: https://strategiqmarketing.co.uk. Fig 5.5. Hello Barbie. The doll will introduce “always on” voice recording into not only private homes, but specifically into the play of young children. Source: https://www.cnet.com/news/helloheadaches-barbie-of-the-internet-age-has-even-more-securityflaws/. Fig 5.6. Amazon Echo. Amazon has deployed its Alexa “always on” voice recognition software in its own internet-connected devices. Source: https://www.target.com/p/amazon-echo-nbsp-black//A-52125921.


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Fig 5.7. Nest Thermostat. Nest has conceded that the company analyses recorded conversations in the home. Source: https:// inhabitat.com/nest-smart-thermostat-developed-by-the-fathers-ofthe-ipod/. Fig 5.8. Samsung Smart Home. Consumers were shocked that Samsung’s SmartTV voice recognition software involves recording and transmitting their personal communications. Source: www. samsung.com. Fig 5.9. Microsoft Xbox. Xbox console monitors conversations taking place around it, even when Xbox is turned off. Source: http:// home.bt.com/tech-gadgets/computing/gaming/xbox-one-5-thingsyou-can-do-apart-from-gaming-11363906088731. Fig 5.10. Canary Connect . Unless the device is set to “privacy,” the device will record automatically when triggered by motion. Source: https://canary.is/dist/images/og-image.jpg, https://canary.is/dist/ images/og-image.jpg. Fig 5.11. The eye in dystopian fiction . George Orwell’s ‘1984’ and Margaret Atwood’s ‘The Handmaid’s Tale’ both contain strong references to the eye.

Fig 5.12. Banksy: CCTV, 2004. Graffiti by politically active artist Banksy, situated in London’s Marble Arch. Fig 5.13. Amazon Echo. Source: https://www.beyerprojects.com/ john-baldessari-sculpture-ear-trumpet/.https://www.wareable.com/ amazon/best-amazon-alexa-voice-speakers-devices-watchessmart-2017 Fig 5.14. Ownership of domestic appliances in the UK. Source: Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006. Fig 5.15. Ownership by type of domestic appliance: UK, 20001. Source: Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006. Fig <Variable overset> Fig 5.16. Use of free time in Great Britain, 1995. Source: Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006. Fig 5.17. White goods an brown goods. Source: Harper, Richard, ed. Inside the smart home. Springer Science & Business Media, 2006.


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Fig 5.18. Martha Rosler, Semiotics of the Kitchen, 1975. A video performance in which the artist not only criticised women’s roles within the home, but also the culture of frenetic consumption fostered by capitalism. Source: http://www.artversed.com/art-feminism-anintroduction/.

Chapter 6

Fig 5.19. Womanhouse installation in Los Angeles, featuring Robin Weltsch’s Kitchen and Vicki Hodgetts’s Eggs to Breasts, 1972. The Getty Research Institute, 2000. Source: Left: http://www. womanhouse.net/works/nndnd6jhzeed12awm04prah80jdhiq, Right: Lloyd Hamrol.

Fig 6.2. Examples of dialogues with a conversational bot. We can try to steer the conversation towards the desired ‘asian food’ topic with the help of questions and suggestions from the bot.

Fig 5.20. The Gossips (photo lay-out). The Gossips cover was the most popular Rockwell Post cover in thirty-three years. Thousands of letters were sent to the Post asking what the gossip was they were passing along. An answer was never given. Norman Rockwell, 1948. Fig 5.21. Thomas Benjamin, Mischief. Source: https://i.pinimg.com.

Fig 6.1. Markov chain of The Smiths lyrics. Source: http://www. statsblogs.com/2014/02/20/how-to-fake-a-sophisticatedknowledge-of-wine-with-markov-chains/.

Fig 6.3. Yes/No answers variations. It is clear that chatbots need some way of understanding the language and conversational phrases that are more sophisticated than just a simple text search by phrase or even regular expressions. Source: https://stanfy. com/blog/advanced-natural-language-processing-tools-for-botmakers/. Fig 6.4. Dialogue structure for bots interface. A Session usually represents one conversation from beginning to end. Source: https:// stanfy.com/blog/advanced-natural-language-processing-tools-forbot-makers/.


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Fig 6.5. A nested context example in a branched dialogue. Source: https://stanfy.com/blog/advanced-natural-language-processingtools-for-bot-makers/. Fig 6.6. IBM Watson list of services. Source: https://stanfy.com/blog/ advanced-natural-language-processing-tools-for-bot-makers/. Fig 6.7. Build an Amazon Lex bot that allows patients to book appointments. Source: Amazon. Fig 6.8. Setting up Alexa Skills. Source: https://stanfy.com/blog/ advanced-natural-language-processing-tools-for-bot-makers/. Fig 6.9. Intent creation view in Api.ai. Source: https://stanfy. com/blog/advanced-natural-language-processing-tools-for-botmakers/. Fig 6.10. LUIS training mode. Source: https://stanfy.com/blog/ advanced-natural-language-processing-tools-for-bot-makers/.

Fig 6.11. Wit.ai stories interface for dialogue definition. Source: https://stanfy.com/blog/advanced-natural-language-processingtools-for-bot-makers/. Fig 6.12. Wit.ai dialogue example with intents, entities and a context. Source: https://stanfy.com/blog/advanced-natural-languageprocessing-tools-for-bot-makers/.rom. Fig 6.13. Wit.ai Chat UI for conversation testing. Source: https:// stanfy.com/blog/advanced-natural-language-processing-tools-forbot-makers/.rom. Fig 6.14. Six Common Network Topologies. A simple formula for describing the Internet of Things. Source: http://eas-tech.net/ network-topologies/. Redrawn by Author. Fig 6.15. Internet of Things Ecosystem. Source: http://www. businessinsider.in/A-revamped-Apple-TV-could-have-huge-smarthome-implications/articleshow/48332533.cms. Redrawn by Author.


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Fig 6.16. The IoT Smart Home Hub Model. In the Hub model, one device acts as the interface between the user and all the other smart objects in the home. All interactions take place only between the user and the ‘hub’ or assistant device while the other smart devices remain in the periphery. Source: https://www.homeandsmart.de/ quirky-wink-app-steuerung.

Fig 6.19. Vienna Philharmonic Orchestra in Hong Kong with German conductor Christoph Eschenbach. The Vienna Philharmonic Orchestra has the status of being historically associated with some of the greatest composers and conductors. Source: http:// timeout-test.candrholdings.com/music/features/46132/viennaphilharmonic-orchestra-in-hong-kong.html#panel-2.

Fig 6.17. Jazz Band vs. Orchestra . The Orchestra Conductor, standing at a pedestal with a baton, is unquestionably the in-themoment leader . The Jazz Leader, sitting with his musicians, sets the stage for the performance, but then becomes a contributor. Source: TED + BCG - How should a CEO lead? Jazz vs Symphony. Character Animation, Kirart Production, Motion Graphics 2014. Based on an article by John Clarkeson.

Fig 5.20. Austrian conductor Franz Welser-Moest and the Vienna Philharmonic Orchestra perform the traditional New Years Concert on January 1, 2013 at the music association in Vienna, Austria . Source: http://www.dailymail.co.uk/.

Fig 6.18. Jazz Band vs. Orchestra Network Topologies. An orchestra resembles Star Network Topology whereas a Jazz Band resembles the Mesh Network Topology. Source: TED + BCG - How should a CEO lead? Jazz vs Symphony. Character Animation, Kirart Production, Motion Graphics 2014. Based on an article by John Clarkeson.

Fig 5.21. Mamie Smith’s Jazz Hounds in 1923 with Coleman Hawkins 2nd from right above playing tenor saxophone. The early New Orleans style of jazz was polyphonic, based on collective improvisation rather than solos with accompaniment. Source: /yandoo.wordpress. com/2015/06/29/the-early-influence-of-louis-armstrong-oncoleman-hawkins-as-mediated-by-fletcher-henderson/. Fig 6.22. 3D printing on a Makerbot Replicator. Author’s Image.


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Fig 6.23. CCTV Security Camera Inline Audio Microphone with Loop Through Power. Source: https://www.spycameracctv.com/ spycamera/cctv-security-camera-inline-audio-microphone.

Fig 7.4. Expression Training. Author’s Image.

Fig 6.24. Mini USB Microphone. Product Dimensions: 22.2mm x 18.3mm x 7.0mm. Source: https://www.adafruit.com/product/3367

Fig 7.6. Keyword based Intents. Author’s Image.

Fig 6.25. Mini Bluetooth Speaker. Credits: Abhishek Khedekar, 2017. Fig 6.26. Hamburger Mini Speaker. Source: https://www.sparkfun. com/products/14023. Chapter 7 Fig 7.1. Object Template System Flow. Source: How to Give Your Smart Mirror Artificial Intelligence, Hacker House, 2016. Fig 7.2. Object Template. Object Template with Audio Input, Google Speech Recognition, Wit.ai integration and Natural Language Generation and Audio Output. Author’s Image. Fig 7.3. Training Intents in sentences. Author’s Image.

Fig 7.5. Different Applications for each object. Author’s Image.

Fig 7.7. Object to Object Interaction. Left: Two objects with single speaker and microphone. Right: Two objects with individual speakers and microphones and Raspberry Pis. Author’s Image. Fig 7.8. Object Interactions Setup. Three Groups of three objects, each group having an individual microphone and speaker. Each group takes audio input and generates audio output. Author’s Image. Fig 7.9. Interactions. Visitors to the space may speak amongst each other, listen in to what the objects are saying or choose to converse with the objects. Objects converse regardless of human presence. Conversations are based on proximity and are subject to misinterpretation. Author’s Image. Fig 7.10. TinkerCAD - Object Designs. Author’s Image.


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Fig 7.11. 3D model of Washing Machine. Author’s Image.

Fig 7.20. Refrigerator. Image Credits: Abhishek Khedekar, 2017.

Fig 7.12. Sofa. Image Credits: Abhishek Khedekar, 2017.

Fig 7.21. Bed. Image Credits: Abhishek Khedekar, 2017.

Fig 7.13. Oven and Stove. Image Credits: Abhishek Khedekar, 2017.

Fig 7.22. Kitchen Sink. Image Credits: Abhishek Khedekar, 2017.

Fig 7.14. Washing Machine. Image Credits: Abhishek Khedekar, 2017.

Fig 7.23. Sofa with microphone, speaker and Raspberry Pi. Image Credits: Abhishek Khedekar, 2017.

Fig 7.15. Lamp. Image Credits: Abhishek Khedekar, 2017.

Fig 7.24. Bed with microphone, speaker and Raspberry Pi. Image Credits: Abhishek Khedekar, 2017.

Fig 7.16. Test piece. Piece printed to test the size of sound holes, size for speaker and microphone, sound quality, print quality. Image Credits: Abhishek Khedekar, 2017. Fig 7.17. Cabinet with microphone, speaker and grilled cap. Image Credits: Abhishek Khedekar, 2017. Fig 7.18. Boombox with microphone, speaker and grilled cap. Image Credits: Abhishek Khedekar, 2017. Fig 7.19. Sofa. Image Credits: Abhishek Khedekar, 2017.

Fig 7.25. Cabinet with microphone, speaker and Raspberry Pi. Image Credits: Abhishek Khedekar, 2017. Fig 7.26. Man in Kitchen. Image Credits: Abhishek Khedekar, 2017. Fig 7.27. View from entrance. Image Credits: Abhishek Khedekar, 2017. Fig 7.28. Bedroom containing Bed with Pillow, Cabinet with Alarm Clock and Photo Frame and Bookshelf with Lamp. Image Credits: Abhishek Khedekar, 2017.


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Fig 7.29. Living Room with Sofa, Television, Speakers, Table with Flower Vase. Image Credits: Abhishek Khedekar, 2017.

Fig 7.37. Bedroom. Image Credits: Nidhin Bose, Poornima Marh, 2017.

Fig 7.30. Scale Model, without objects. Image Credits: Nidhin Bose, Poornima Marh, 2017.

Fig 7.37. Bedroom. Image Credits: Nidhin Bose, Poornima Marh, 2017.

Fig 7.31. Scale Model. with objects. Image Credits: Nidhin Bose, Poornima Marh, 2017.

Fig 7.38. Man in Bedroom. Image Credits: Nidhin Bose, Poornima Marh, 2017.

Fig 7.32. View from Living Room. Image Credits: Nidhin Bose, Poornima Marh, 2017. Fig 7.33. TV Unit with bookshelf and flower vase. Image Credits: Nidhin Bose, Poornima Marh, 2017. Fig 7.34. Kitchen. Image Credits: Nidhin Bose, Poornima Marh, 2017. Fig 7.35. Man in Kitchen. Image Credits: Nidhin Bose, Poornima Marh, 2017. Fig 7.36. Man with Toaster. Image Credits: Nidhin Bose, Poornima Marh, 2017.


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Namrata Primlani, 2019. Graduation project for the Master of Design, New Media Design, National Institute of Design, India. Guided by Dr. Jignesh Khakhar.