RunCao_Portfolio

PORTFOLIO. Run Cao B.Arch. South China University of Technology Selected Works 2019-2023 caorun847374504@gmail.com

CONTENT Main Projects

01

VENDOR INSIGHT | Mobile Vendor & Big Data

02

MIND FOCUS | ADHD & Open Space Office

03

COOPERATIVE BEAT | Nonverbal Communication

04

CITY ROAM | AR & Citywalk

[Urban Data Analysis] Personal Research | Guangzhou | 2023

[User Data Measurement] Personal Research | Guangzhou | 2023

[User Behavior] Academic Studio | Guangzhou | 2023

[User Experience] Academic Studio | Hong Kong | 2023

Other Works

05

Architecture Heritage Scanning & Mapping

06

Scale of Time — Poetry Space Art Installation

07

Gaze Upon Dacheng Hall

08

WATERFOWL

[3D Scanning & Field Measurement] Academic Research | Guangzhou | 2022

[Installation Construction] Internship Project | Guangzhou | 2020

[Historical Site Renovation] Graduation Project | Nanyang | 2023

[Bamboo Construction] Competition Project | Guangzhou | 2019

[Urban Data Analysis] VENDOR INSIGHT | Mobile Vendor & Big Data NLP Analysis & Object Detection & GIS Analysis

[TOOL] Weiciyun, Gephi, ArcGIS, Rhino, YOLOv4 [LOCATION] Guangzhou, Guangdong, China [DATE] Sep. - Nov. 2023 [INSTRUCTOR] Han Tu [INDIVIDUAL PROJECT]

Mobile Vendor Social Problem

Data Base

Analysis

Weibo Entries

NLP Analysis(Weiciyun)

Baidu Street View

Object Detection(YOLOv4)

Urban Data

ArcGIS Analysis

Design Guideline

Social issues arising from mobile vendors in Guangzhou have been escalating both in spatial and non-spatial dimensions.

However, the majority of solutions to mobile vendor issues are formulated in a top-down manner, with very few bottom-up approaches. This research aimed to collect evaluations of the mobile vendor issue from numerous individuals through big data methods. I employ machine learning to study the spatial and non-spatial dimensions of the location of vendors. During the initial investigation into the social issues caused by mobile vendors, I scraped 41,849 Weibo entries from 2015 to 2023 related to Guangzhou and mobile vendors. I conducted Natural Language Processing (NLP) analysis, identifying the perspectives and needs of various social members on the issue. To explore the contradiction between the city's built environment and the distribution of mobile vendors, I trained a YOLOv4 model with 500 photos of mobile vendors, predicting their locations in a total of 493,220 street view images from 2014 to 2023. After combining the predicted results with Points of Interest (POI), house prices, population density, and other data for analysis, I visualized the spatial distribution contradiction of mobile vendors. Based on the results of NLP and visualization analysis, urban design guidelines were formulated to allow mobile vendors in the city to sell more effectively while reducing their negative impact on urban appearance.

Problems of Mobile Vendor Space Occupation and Urban Development

Survival Pressure and Social Injustice

An increasing number of urban spaces are becoming formalized, leading to a continuous exclusion of street vendors. The presence of mobile vendors also brings about disorder and noise, impacting the living environment of residents.

In Guangzhou, mobile vendors, as a low-income group, face significant challenges in supporting their entire families, leading to high survival pressure.

spatial conflict among the government, mobile vendors, and residents.

Government

Vendor Exclude Discipline

City Developemnt

Use Gray Space

non-spatial conflict among the government, mobile vendors, and merchants.

Resident

Government

Purchant Complaint

Sales Space

Mess Noise

Vendor Normalization

Comfortable Environment

Social Governance

Security Problem

Merchant Compete Complaint

Survival Pressure

Take Away Business

Make Profit

Accessible Data

Research Methodology

Based on the issues related to mobile vendors, both spatial and non-spatial aspects were considered, and four districts in the central areas of Tianhe, Yuexiu, Haizhu, and Liwan in Guangzhou were selected. Within this scope, relevant data about mobile vendors were collected.

01 PROBLEMS

Weibo Entries

POI Data

Population Density

Housing Price

360° Street View

Spacial problems

Non-spacial problems

city appearance

city construction

economic problem

social problem

informal space

living density

regulation

security problem

02 DATABASE Social Media Posts

Urban Data Point of Interest(POI)

OpenStreetMap

metro station market bus station city management

guangzhou.osm

Weibo Scraper

Route of vendor Route of city inspector Scope of influence

Street View Images (SVI)

road network.shp

From Baidu POI API key

GIS: Points along Gemoetory Housing Price(HP)

Keyword Mobile Vendor & Guangzhou

Guangzhou_SVI.csv

house price and rent price plot ratio

TXT 41849 texts in total

From Anjuke APP

4 direction

0° 270°

Publish time From 2014-2023

Population Density(PD)

90°

API key

180°

Guangzhou_SVI.csv

100m accuracy 1000m mesh

Publisher certification personal and official

historical streetview

123305x4=493220 From 2014 to 2023

From WorldPop.org

03 ANALYSIS Natural Language Processing Data Cleaning removing irrelevant and duplicate texts

Pedestrian

Data Intergration POI

HP

PDM GIS

Classification Sort data by time and publisher Keyword Arrangement people, place,abstract word,criteria, object

Object Detection(ML) L

Training Dataset Divide vendors into four classes Table

Car

TricycleG

round

500 streetview images in total YOLOv4 Training 1306 times iteration Average IoU = 64.67% mAP@0.50 = 95.27 %

Collocation Analysis

YOLOv4-vendor.weight Historical streetview prediction Data Intergration and Visualization

Data_Intergration.csv

predicted Pt.csv

04 DESIGN SUGGESTION DATA Analysis

Emotion Analysis Positive

SPSS

optimisml

ove serenity

interest

contempt

correlationr

egression

admiration terror

rage

Street management

Vendor

Road occupation

fear

apprehension

Individual

Square openness

amazement surprise

disgust

Government

submission

ecstasy

loathing

Negative

exploratoty

trust

vigilance annoyance anger

descriptive statistics acceptance

joy

anticipation aggressiveness

Spatial Solution

awe

Neutral

sadness

Non-spatial Solution

POI

pensiveness remorse

disapproval

ROAD

Government

Regulation

Vendor

Normalization

Individual

Cooperation

Emotional Model

Evaluation of Texts proportion of emotions

City Inspector Mobile Vendor

Evaluation of Keywords Count the number of times keywords appear in different emotions

HP PD ML POI

ROAD HP PDM L

NLP analysis Spatial Problem

Association Analysis

High-frequency nouns related to spatial location are associated with "inspector," "vendor," and "regulation." This indicates that these locations are frequent sites for regulation and inspection.

Non-spatial Problem

The scraped Weibo entries were categorized into two groups: official and individual accounts. The majority of the entries were identified as official accounts.

Frequency analysis reveals that the most common nouns are "vendor," "city inspector," "street," "market," "regulation," and "city appearance." In terms of adjectives, there is a scarcityv of positive and neutral adjectives, with a predominance of negative adjectives. The most frequently occurring adjective is "messy."

Account

Noun

"Vendor" and "inspector" often co-occur and are frequently associated with "regulation." regulation" has a close relationship with "city appearance," suggesting that the purpose of regulation is for beautifying the cityscape.

Adjective

fine healthy vendor

convenient

city inspector

steady simple cheap

Positivie

unobstructed official 2020-2023

board street

citizen

fresh flexible

vendor

clinical case

extensive

arbitrary official 2017-2019

street

important fixed

market market

city

formal complex busy

school

normal

Neutual

Official

community

city inspector

free stall road square crossing

regulation

individual 2020-2023

messy epidemic

individual 2017-2019

Negative

school

Individual

official 2014-2016

food individual 2014-2016

traffic economy price

People Place

regulation

city appearance serious

Abstract noun

order

uncivil

Weight

civilization

congested

0

smell of cooking noise disturbance

disordered

Criteria

square

2000 4000 6000 8000 10000

violent narrow

city appearance

Emotion Analysis

citizen Negative posts proportion was increasing for both sides. This was attributed to the increasing restrictions on mobile vendors operating on the streets due to urban development and issues related to the pandemic.

community clinical case

Tianhe Park

Huacheng Avenue

city inspector

Ersha Island

Shamian

vendor

Yide Road

Urban Data Collection

Official

Individual

Point of Interest According to literature, mobile vendors typically choose locations near markets and transportation hubs because of the high foot traffic, and they tend to avoid areas near urban management bureau offices to prevent potential penalties from the city inspectors.

traveller customer Market_POI Density

street low

market

High

city school stall

City Manager_POI Density There was often a large gathering of mobile vendors near schools. However, due to concerns about food safety and management issues, most parents and authorities did not want vendors to appear around schools.

road square crossing

low

High

walking street bridge

Transportation_POI Density

urban village low

subway station

High

park train station regulation epidemic food Population Density

traffic

To maximize profits, mobile vendors typically choose to set up stalls in places with high foot traffic and dense population, aiming to attract a larger customer base.

economic When mobile vendors operated on the road, it affects traffic and lead to congestion. As the incidence of occupying roads increased, negative evaluations also rose.

price

Greasy dirt can affect the cleanliness of city streets and the living environment of residents.

city appearance

Therefore, both individuals and officials did not want vendors to generate greasy dirt.

order

low

High

civilization greasy dirt noise disturbance car tricycle

Housing Price

fruit barbeque vegitable waste 5.0

4.5

4.0

3.5

43.02%

47.67%

56.41%

3.0

2.5

2.0

1.5

19.27%

1.0

0.5

0.0

37.71%

20.25%

17.21%

32.08%

26.38%

Individuals generally hold a negative attitude towards street vendors than the government, and from 2014 to 2023, negative opinions have increased.

negative

positive

0.0

0.5

1.0

1.5

2.5

2.0

2014-2016

28.39%

23.34%

2017-2019

28.65%

21.61%

2020-2023 people place abstract word criteria object

38.09%

17.76%

3.0

3.5

4.0

4.5

5.0

48.27%

49.74%

44.15%

Government reports on street vendors are mostly positive; however, the proportion of negative evaluations has been consistently increasing from 2014 to 2023.

Due to their lower income and the inability to move long distances, mobile vendors often reside in close proximity to their homes. They complete the entire process, from preparing materials to selling, near their residences. Consequently, they tend to choose areas with lower housing prices. low

High

Object Detection and Data Analysis Machine Learning

2014 - 2016

2017 - 2019

2020 - 2023

Correlaiton Analysis

Conclusion

Number of table vendor

Class 0 Table Mobile Vendors

Distribution of table vendor 2014-2016

Distribution of table vendor 2017-2019

Distribution of table vendor 2020-2023

The number of table vendors has continuously decreased from 2014 to 2023, but their distribution locations have not changed significantly.

Number of ground vendor

Class 1 Ground Mobile Vendors

Distribution of ground vendor 2014-2016

Distribution of ground vendor 2017-2019

Distribution of ground vendor 2020-2023

The number of ground vendors has decreased dramatically after 2020, and their distribution locations have changed over 10 year period.

Number of car vendor The number of car vendors has continuously decreased from 2014 to 2023, and their distribution locations are quite uniform.

Class 2 Car Mobile Vendors

Distribution of car vendor 2014-2016

Distribution of car vendor 2017-2019

Distribution of car vendor 2020-2023

Number of tricycle vendor

Class 3 Tricycle Mobile Vendors

Distribution of tricycle vendor 2014-2016

Distribution of tricycle vendor 2017-2019

Distribution of tricycle vendor 2020-2023

The number of tricycle vendors was several times higher in the period 2017-2019 compared to the other two years, and their distribution is relatively uniform.

Jianye Avenue

Huacheng Avenue

Dongfeng East Road

Baoye Road

Duobao Road

Zengnan Road

Design Guideline

High

Low

Heat map of combination of all the vendor from 2020 to 2023

Find out where the vendors are most densely populated and have the most serious problems based on the machine learning results, and use the NLP analysis results and correlation analysis results to implement urban design for the problem of mobile vendors.

Spatial Solution

Non-Spatial Solution

Government

Street management

School management

Time management

Set criteria

Street hygiene

Reduce noise

Get a license

Flea market for vendor

Cooperation

Complaint in time

Mobile Vendor

Low road occupation Individual

Open up the market

[User Data Measurement] MIND FOCUS | ADHD & Open Space Office VR Experiment Based on CPT and EEG Data [TOOL] Unity, Rhino, Muse2, Oculus Quest 2,Python [LOCATION] Guangzhou, Guangdong, China [DATE] Jul. - Aug. 2023 [INSTRUCTOR] Han Tu [MY ROLE] 90% UNITY Scene Design 45% User Test 70% Data Cleaning and Analysing 100% Application Design and Drawing this Pofolio [GROUP MEMBER] Yuhao Huang, Kaitong Guan, Hanyu Xue Improve Concentration Survey People with ADHD lack of concentration in open office

Questionnaires Interviews

VR Experiment

Factors Selection

Unity Modelling

Experiment Scenes

EEG test

Quantitative Analysis

APP Design

CPT test

Problems Qualitative Analysis

As open offices become increasingly common, more and more patients with Attention Deficit Hyperactivity Disorder (ADHD) find it challenging to concentrate in such environments. However, there hasn't been a systematic study on which factors of open offices affect the concentration of individuals with ADHD. This research aimed to investigate the factors influencing the concentration of individuals with ADHD in open office environments, with the goal of enhancing their focus. We conducted phone interviews with 25 ADHD patients, comprehending their assessments and various needs in an open office setting, categorizing the factors influencing ADHD concentration into three classes: spatial orientation, noise, and spatial segmentation. Subsequently, we utilized VR devices to simulate open office environments, measured users’ EEG data, and collected behavioral data through the Continuous Performance Test (CPT) to quantify the influence of these factors. We analysed the data and calculated the weight of the distraction of each factors. Based on our calculations, we designed a seat selection application to effectively address the distraction issues faced by individuals with ADHD in open office environments.

Our study systematically measured the factors affecting ADHD concentration and determined their respective weights. This seat selection application proves to be a solution for improving the concentration of individuals with ADHD in open office settings.

Preliminary Research

JourneyMap & Main Factors

Background

DURING WORK

Concentration

RUN-UP TIME

I don't want to eat medicines everyday to let me concentrate.

fetch water

clear the desk

chatting

other passing by

being watched

foof smell

outside view

noise

Elements

make plans

By breaking the traditional cubicle structure and promoting communication and cooperation among employees, open office is considered to improve work efficiency. However, more and more cases showed that the open office environment may face many challenges for some employees' adult ADHD patients in their daily lives, especially in the workplace. Besides drug control, is there any other possibility to help ADHD stay focused at work?

Factors Evaluation

Main Factors

Too much distraction, I cannot stay focus!

Orientation The seats in different positions affevct the concealment of the space, that is,

Sound Different sound types can affect ADHD’s concentration, such as white noise (the

Spatial type Different space types will affect ADHD’s concentration, such as whether the view

the degree of surveillance,which will affect the concentration of ADHD.

sound of keyboard, paper and pen) and seductive sounds (people talking).

outside the window can be seen, indoor work areas and rest areas

ADHD Uers Persona Needs

Behavior High Distraction

Spatial chaos

Outside scenery Being watched

People walking

Schedule planning

Dam-board

Noise

Stare at screen for a long time

Work in a relaxed sitting position

Independent work station

Get rid of ADHD medicine

Listen to people talk instead of working

Chat with multiple people

High interactive work

Relaxed working atmosphere

Talking with others Water dispenser

People talking Rest place High Universality

Low Universality

Traits

Pain points

Number of people Suffer from ADHD

Work in open space office

Take medicine regularly

Light Music Easily influenced by surrounding

Severe procrastination

Make plans without finish

Long run-up time

Desk size Exercise habit Virtual office Scent

Temperature

Space atmosphere

Low Distraction We conducted telephone interviews with 25 ADHD patients to learn about the factors that affect ADHD patients' concentration in an open office environment.We divided the factors into four categories according to the degree of distraction and university. High distraction and high university influencing factors were used as research variables in this study.

Experiment Methods

Experiment Procedure Selected Factors from Interviews

Pritential Challange and Strategies ？

Orientation of open space will affect ADHD's concentration

√

Noise in the open office will affect ADHD' s concentration

Spatial type will affect ADHD' s concentration

Causes Line of Sight (Be Watched)

Testing in real venues Use VR to simulate the is too expensive real environment

unable to measure concentration level

Use EEG equipment to measure brain wave

unable to measure work performance

Vision or Perception

Sound

Auditory Sense

Field of View

Vision or Perception

Use CPT to analyasis ADHD's performance

Variables Technologies Tech 1 — VR Simulation

Space Orientation Tech 2 — EEG Test

Tech 3 — CPT Test

Supervisor A position that can be easily seen by the supervisor

Other colleagues A positon easily seen by walking colleagues

Sound Seductive sound(S) Sound of talking and Eating

The level of being watched

Space Segmentation

White sound(W) The sound of things being carried, keyboards, drafts

The ratio of two types of sounds

Indoors(I) Outdoors(O) See space Have views out outside the office the window area The visibility of tow types of space

1 Low monitoring level

2 Middle 3 High

THETA

Procedure The level of being watched

Seductive sound(S)

White sound(W)

Indoors(I)

Outdoors(O)

High S High W Low Monitoring

Low S High W 1

High I High O

2

Low I High O

3

High I Low O

4

Low I Low O

Middle Monitoring High S Low W

Use Unity to model the VR scene, and record different office environment audios to simulate a real open office environment, and display the VR scene in Oculus Quest 2.

Scenarios

Use the Muse2 device to measure the brain wave data of experimenters. Beta waves and Theta waves can reflect the concentration level of the experimenters.

In the CPT test, the experimenters will see random letters appearing one after another and have to respond to the correct letter within a short time by clicking a button.

Scene Design

High Monitoring

Low S Low W

6 min Test and 1min Rest Each Experiment

6 min Test and 1min Rest Each Experiment

The sequence of experiments was arranged randomly

Perform scene design in unity according to experimental variables and process

6 min Test and 1min Rest Each Experiment

Experiment Scenes Based on the experimental variables and with reference to the typical open office floor plan, the scene was modeled in Unity, and people walking and talking were added to the scene to simulate the open office environment as realistically as possible.

Different seat positions and different audios correspond to different variables.Different experimental scenarios are changed by the different combinations of seats and audio.Different scenes have changed the level of

Scene 4

Scene 4

Scene 2

Scene 1

Scene 4

Scene 3

Scene 4

Scene 4

Scene 7 Scene 2

Scene 5

concentration for ADHD patients.

Scene 1

Scene 4

Scene 6

Scene 3 Scene1

Scene2

Scene6

Scene3

Scene 4

Scene4

Scene7

Scene5

Scene 5

Scene 6

Scene 7

Low monitoring

Middle monitoring

High monitoring

Human voice

Environmental voice

None sound

City view

Entertainment area view

Office staff flow line

EEG Data Processing

CPT Data Processing

We tested 10 people with ADHD who took medication, and who didn't take medication, and 10 people without ADHD. Obtained their EEG data through experiments, and perform data cleaning and analysis. And the characteristics of the EEG data of the three groups were compared.

While conducting VR & EEG testing, the experimenter was asked to perform CPT testing to simulate working in an open office environment. They were faced with repetitive boring tasks and had to maintain concentration for a period of time. We recorded the timing of their behavior of clicking the botton to analysis their work performance.

β and θ brainwaves are associated with the concentration level

Collected the data of 10 testers with ADHD and 10 without ADHD

Count the average value of each group and get average brainwave

Perform moving average and linear trend analysis

ADHD without Medicine

Record the timings of tester clicking the button during the CPT test.

Compare the recorded timing to key timing of each scenarios

Correct Detection

The concentration levels of people with ADHD who don't take medication decreased over time and remained at a low level.

ADHD with Medicine

This indicates the number of times the subject responded to the target stimulus. Higher rates of correct detections indicate better attentional capacity.

Collected and analysed the data to get different test scorings

Omission Error

This indicates the number of times the target was presented, but the subject did not click the button. High rates indicate that the subject is either not paying attention to stimuli or has a sluggish response.

Correct Detection of Space Orientation

Omission Error of Space Orientation

Correct Detection of Noise

Omission Error of Noise

The concentration levels of people with ADHD who take medication increased over time but remained at a low level.

People without ADHD

The concentration levels of people without ADHD increased over time and remained at a consistently high level.

Count the Average value of the test scorings in each scenarios

Data Analysis

EEG

people walk by

people disappear

CPT Correct Detection

CPT Omission Error

Location

Sound_Mute

Testers with ADHD had low correction rate and low omission rate.

Sound_Mute

Sound_human voice decreased

Tester with ADHD had Moderate correction rate and low omisison rate.

Sound_human voice decreased

Low correction and high omission

Sound_environment voice decreased

Tester with ADHD had low correction rate and high omisison rate.

Sound_environment voice decreased

highest

Sound_both voice decreased

Sound_both voice decreased

Tester with ADHD had high correction rate and high omisison rate. people talk loud

Slience

lowest

Orientation_low monitor

Tester with ADHD had low correction rate and high omisison rate.

Orientation_low monitor

Loud white sound

lowest omission

Orientation_medium monitor

Tester with ADHD had high correction rate and lowest omisison rate.

Orientation_medium monitor

Orientation_High monitor

Tester with ADHD had high correction rate and high omisison rate.

Orientation_High monitor

Subjects with ADHD BETA_Average

THETA_Average

BETA_Trend

THETA_Trend

The correction rate of experimenters with ADHD is significantly lower than that of experimenters without ADHD, and the corrction rate of people with ADHD is more affected by changes in environmental factors.

The omission rate of experimenters with ADHD is significantly higher than that of experimenters without ADHD, and the omission rate of people with ADHD is more affected by changes in environmental factors.

Ave rate with ADHD Subjects without ADHD Ave rate without ADHD

Design Solution Concentration Factors Analysis Method Based on the analysis of the aforementioned EEG and CPT data, the arithmetic mean of all data points for Beta waves, Theta waves, as well as the average values of Correct Detection, show a negative correlation with the degree of attention dispersion in ADHD. Omission Error exhibits a positive correlation. Using these relationships, calculate the weight of attention dispersion for each factor.

Seat Evaluation

Seat Selection Application

distraction level low

high

ADHD patients can use this APP to analyze existing open office environments. Based on the analysis results, the app can suggest improvements to enhance focus and recommend products that can help improve concentration.

Home Page

AR Scanning

Seat Selection Result

Set the basic information and needs that meet their situation about the open office

If users haven't chosen the seat.

Scan the office overall plan to get the spatial information of the office

Evaluate the whole office and choose the most suitable seat for ADHD patients to focus.

360° Scanning

Seat Evaluation Result

Shopping Page

If users already had a seat, used the panorama to scan the view upon the seat

If users have a seat, they can get the evaluation of their seat and the advice

Users can buy more equipment and items to improve their concentration based on advice.

The higher the weight, the greater the impact of the factor on ADHD concentration.

Conclusion on Each Factor

Weight_Space Orientation

Whether high or low monitor will lead to distraction, it is easier to concentrate when at an intermediate value.

Weight_Noise

Both human voices and white noise will have an impact on concentration, with human voices having a greater impact.

Weight_Space Segmentation

Both indoor and outdoor views have an impact on concentration, and indoor views have a greater impact.

[User Behavior] COOPERATIVE BEAT | Nonverbal Communication Cooperative Installation Test & Education [TOOL] Arduino IDE, Arduino Mega, Rhino, 3D Printer [LOCATION] Guangzhou, Guangdong, China [DATE] Jun. - Aug. 2023 [INSTRUCTOR] Yiqing Wang [MY ROLE] 70% Conceptual Design 100% Fabrication, User Test, Drawing this Pofolio [GROUP MEMBER] Ruirui Ren

Theory Nonverbal Communication Efficiency Test

Conduit Metaphor

Inspiration Heart Beat Process

Expression Body Language

Installation Fabrication Communication Education Tutorial Cooperation Training

Michael Ready proposed the Conduit Metaphor Theory in 1979, suggesting that language is like a conduit, transferring one's thoughts from one end to another. However, non-verbal communication often constitutes a significant portion of face-to-face interaction, and there has been a lack of quantifiable means to study non-verbal communication. We aim to explore the relationship between body language, expressions, and the efficiency of information transmission in non-verbal communication through the design of a collaborative installation. Simultaneously, this collaborative installation can serve as an educational tool to help children develop cooperative awareness and understand non-verbal communication. We utilized Arduino distance sensors and air pumps to detect people's positions and simulate the process of heartbeats. In user testing, participants collaborated to simulate the heartbeat process non-verbally, and their motion data were recorded to evaluate the effectiveness of their collaborative efforts. We successfully completed the simulation of the heartbeat process in user testing, analyzing the efficiency of information transmission through expressions and body movements in non-verbal communication. Additionally, we involved children in our installaition game, allowing them to experience the process of nonverbal cooperation.

Importance of Nonverbal Communication

Spoken words Eye contact Loudness Facial expressions Voice Tone Gesture Appearance Touch Body movement

People get the basic meaning of what others say from what words they say.

Space/distance

Nonverbal behaviors may constitute a universal language system. Smiling, crying, pointing, caressing, and glaring are examples understood across nationalities, offering a fundamental means of communication when verbal interaction is hindered by language barriers.

People judge other people's attitudes and emotions from the tone, intonation, and loudness of their voices.

Verbal 7%

Percentatge of Communication Albert Mehrabian's research has suggested that when people talking to other, 7% of meaning is communicated through spoken word, 38% through tone of voice, and 55% through body language.

Spoken words

Voice 38% Voice

Loudness

Body Language 55% Tone

Body movement

Conduit Metaphor

The Toolmakers Paradigm

Thought is a container

Mutual understanding needs iterations

Facial expressions

Space distance

Touch

Gestures

Eye contact

Apperaance

Noise

Eject

Thoughts

Extract

Idea Space

Speakers eject thoughts into idea space

Idea space contains thoughts

Listeners extract thoughts from idea space

Rather than words, an "idea space" between individuals' minds can serve as the container for mental content. The conduit is not a sealed pipeline but an open channel, enabling mental content to flow into or out of this shared space.

Meaning is created by individuals as messages are exchanged. Receivers independently interpret messages, using their personal context and past experiences to assimilate new information. Achieving shared understanding requires ongoing, dialogical communication, as listeners make sense of the presenter's perceptions without knowing their exact thoughts.

Different people in different environments and backgrounds, when faced with the same information, will interpret it based on their own knowledge and may end up with completely different interpretations.

water direction gas direction

Interaction Process

Inspiration

We found inspiration in the beating and circulation of the heart

state 1

state 2

state 3

Venous flow returns to the right atrium and arrives in the right ventricle

Venous blood is then sent in the lung via the pilmonary artery

state 4

After oxygenation in the lung, the blood returns to the left atrium

Red blood arrives in the left ventricle and then is sent in the arteries to the tissues

Metaphor installation

state 1 In the initial state, the blue side is full of water and the red side is half filled.

state 2

state 3

state 4

The balloon in the blue side starts to inflate and water flows to the red side.

The balloon on the blue side begins to deflate and the water is sucked back.

red side ballon begins to At the end of the interaction, inflate, the water flows to the the volume of outflowing bottom container. water is recorded.

Process Explanation Non-verbal communication medium 1 Not familiar with device operation mode 2 Low level of education 3 Certain communication barriers

1 Understand the operating mode of the device 2 High level of education 3 No language communication barriers

state 5

position information

position information

Sensor 2

Distance △ 2

△2=△3

Balloon 1 Inflation

△2≠△3

Static

△1=△3 △2=△4

Both ballons Deflation

Air Pump 1 Blue Side Sensor 3

Distance △ 3

Both Pumps installation reaction

installation reaction

Sensor 1

People only communicate with each other through the metaphor installation, without using language.

Installation Detail

Installation This installation will provide interactive feedback on the location information of both communicators.

Both users move within a range of 2 meters from the installation and engage in nonverbal communication.

Static

△1=△4

Static

△1≠△4

Balloon 2 Inflation

Final Mixed Liquid

Air Pump 2

User 2 people can explore the effectiveness of conveying information in different forms of nonverbal communication through the installation.

△1≠△3 △2≠△4 Distance △ 1

Red Side User 1

Liquid 1 Out flow

Sensor 4

Distance △ 4

Liquid 2 Out flow

Situation

Δ2 ≠ Δ3 static

Δ2 = Δ3 A balloon inflation

Δ1 ≠ Δ3 static

Δ1 = Δ3 both balloons inflation

Δ1 ≠ Δ4 static

Δ1 = Δ4 B balloon inflation

Δ2 ≠ Δ4 static

Δ2 = Δ4 both balloons inflation

The installation consists of three layers: interaction layer, circuit layer, and output layer. Components 1-9 are for the interaction layer, 10-14 are for the circuit layer, and 15-18 are for the output layer.

Installation Components

5

6

7

8

Installation Test

1 State 1: at the beginning of the interaction, both ballons are static 2 State 2: blue ballon inflates, water flows from blue bottle to red bottle 3 State 4: red ballon inflates,water flows form red bottle to the bottom 4 State 5: In the end, water was pumped into the bottom container

1

2

3

4

3

1

2

4

10

17

15

16

18

9

11

13

12

14

1 5000mL container 2 2000mL container 3 glass tube

10 Arduino Mega 11 HC-SR04 12 air pump

4 steel hoop 5 union elbow 6 glass stopper 7 ballon 8 plastic joint

13 12V battery 14 breadboard 15 three-neck flask 16 angle iron 17 connect plate

9 rubber band

18 screw and nut

Installation Structure

Circuit Design 5 6

3

3

5

3

8

4 9

8 4 9

-S R C H

04

1

R -S

7

The installation consists of three layer

C

04

H

7

2 Pump

11

Pump

11

14

13

10

12

12

11

10

11 Arduino Mega

13

12

14 11

11

H

H

04

C

R

-S

-S

C

12V Battery

Plan of the Circuit Layer 15

1 5000mL container 2 2000mL container 3 glass tube 4 steel hoop 5 union elbow 6 glass stopper 7 balloon 8 three-neck bottle cap 9 rubber band

10 Arduino Mega 11 HC-SR04 12 air pump 13 12V battery 14 breadboard 15 three-neck flask 16 angle iron 17 connect plate 18 screw and nut

Record Data in Excel

16 17 18

04

11

R

12 11

The user's position was detected by an ultrasonic sensor and the air pump was driven to inflate the ballon to let the liquid flow out. At the same time, the installation transmitted the location data to the computer excel document through Arduino Mega.

User Test Scenes

Experimental Procedure Each test was conducted for 3 minutes, recording position data during the process and the final volume of water flowing out.

Testers

Both testers know the rule of installation

Only one tester know the rule of installation

Both testers don't know the rule of installaion

Variations

expression

expression

body movement

Nonverbal Cooperation

no expression

no body movement

Expression Cooperation

Both testers can see each other's expressions and body movements.

body movement

Body Movement Cooperation

Both testers can only see each other's expressions, but not their body movements.

Both testers can only see each other's body movements, but not their expressions.

Expression Cooperation

Body Movement Cooperation

Location Recording

Nonverbal Cooperation

tester who don't know the rule Location Analysis tester who don't know the rule

tester who know the rule

area 1

area 2

tester who know the rule area 3

area 4

Location data recorded by sensors (only one tester know the rule, Nonverbal Cooperation) Both balloons deflation

200 Blue balloon inflation 150

Blue balloon inflation

100 Red balloon inflation 50 Red balloon inflation 60

0

Static

Blue balloon inflation

Red balloon inflation

120

Both deflation

Static

Blue balloon inflation

180s

Red balloon inflation

Tutorial Scenes

Non-verbal Communication Education

Cooperation Training & Playing

This installation can train non-verbal communication and help children understand the importance of non-verbal communication.

At the same time, explain the way the heart moves in a vivid way

This installation can cultivate children's sense of cooperation and allow children with language communication difficulties to participate and communicate with other children through body language.

[User Expericence] CITY ROAM | AR & Citywalk User Research and Application Development [TOOL] Figma, Rhino, Bezel, Unity [LOCATION] HongKong, China [DATE] Sep. - Nov. 2023 [INSTRUCTOR] Chengyu Chen, Han Tu [MY ROLE] Group Conceptual Design 45% User Interview 50% App Design and Drawing this Pofolio [GROUP MEMBER] Yiling Jiang, Jialu Li Iteration

User Research

Questionaires Bad Citywalk Experience

AR Prototype

User Test

Hifi Prototype

Interviews

Improve

Citywalk, as a new form of urban micro-tourism, is becoming increasingly popular among young people who enjoy exploring urban scenery and understanding city culture through this activity. However, although there are many travel apps on the market, there are few specifically designed for citywalks. We aimed to enhance the citywalk experience through augmented reality (AR) by customizing journeys for users and enriching their experience with AR landscapes. Through online surveys and phone interviews, we researched ten users who regularly participate in citywalks. We categorized them into two user personas: those primarily interested in understanding city culture and those focused on exploring and checking in at trendy spots. We identified user pain points related to their desire for more points of interest along the route and more interesting landscapes. Using Bezel, we created an AR prototype and developed low-fi wireframes. We tested our prototype with users, collected feedback, and iterated our product. Subsequently, we designed a hi-fi prototype. By combining citywalk route recommendations with navigation and AR landscapes, we created a unique citywalk experience. This not only facilitates route planning for citywalk users but also enhances the variety of landscapes they encounter during their citywalks.

ARCHITECTURE HERITAGE SCANNING & MAPPING Tomb's Details

Point Cloud in VR Scene

Location: Guangzhou, Guangdong, China Date: Sep. - Dec. 2022 Instructor: Jiang Feng Member: Shunjie Chan, Yixing Luo, Jianling Teng, Jiang Zhu, Yu Xin

Pavilion's Details

Stone pillar plinth 1

Wooden pillar plinth

Window pattern

Stone pillar plinth 2

Plaque 1

Eaves tiles

Plaque 2

Dougong

Surveying and mapping of ancient tombs of Muslim sages (Tang Dynasty, 629AC, 2370 sqm).

Installation Construction Project Name: The Scale of Time — Poetry Space Art Installation Project design & completion year: 2020 Chief Designer: Zhenjiang Guo Installation design team: Jiayu Zeng, Meijun Li, Run Cao, Minghao Zhu, Wenyu Wang Project address: Guangdong Times Museum, Guangzhou, China Building area: 15 square meters Poetry creation: Lihai Huang Interaction Design: Chuan Liu

Gaze Upon Dacheng Hall | Nanyang Wangfu Hotel Renovation Design Elevation construction

Pillar construction

Stone brick Waterproof layer Reinforced concrete

Wooden beams

Wooden pillars

Cross steel connecting

Connect steel plate

Weld steel plate

Bolted connection

Tiebeam reinforcement

Diagonal beam laying

Purlin laying

Grille laying

Glass laying Reinforced concrete pillars and beams

Graduation Project Location: Nanyang, Henan, China Area: 11000 ㎡ Instructor: Jiang Feng, Haohao Xu Date: Feb. - Jun. 2023 Individual work Wancheng Center in Nanyang: Confucian temple used to transform into Nanyang Wangfu Hotel. Plan preserves hotel functions, enhances cultural attributes, fortifies temple's essence, creates commemorative public space, exhibition, and Chinese studies areas for elevated cultural vibrancy.

Bamboo Construction PROJECT NAME: Waterfowl LOCATION: Guangzhou, Guangdong, China AREA: 18 sqm DATE : Oct. - Dec. 2019 INSTRUCTOR: Lu Xiong, Guanqiu Zhong MY ROLE: Group Design, Prototype Modelling 50%, Group Constuction GROUP MEMBER: Yi Gong, Chenlong Su, Mingqi Xiao, Xiang Xiong, Hao Huang, Xingyue Gu, Yongxi Du, Haoming Huang, Zhaoming Lv, Hankai Chen

Modelling

Selecting bamboo

Curving bamboo

Fixing bamboo frame

Making steel cable net

Tightening the cable surface

Weaving bamboo

Cutting the edge