IIT Tech Ambit October-November Issue by IIT Tech Ambit

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The Ather Trinity Part 3 - The Mastermind

“If a professor says, ‘Leave your job and come back; we will take care of everything,’ I think that is a great morale boost,..” - In the third and final article of this series, we get in touch with Tarun Mehta, CEO, Co-Founder and one of the brains behind Ather Energy. Written by ARCHI BANERJEE, PIYUSH KUMAR Designed by RENU SREE PINNINTI

lectric Vehicles will be the go-to mode of transport in the near future - it’s efficient, clean - and thanks to Ather Energy, now it‘s smart and fast as well (Read the first and second articles in the series to convince yourself about this). After starting off with a small idea of swappable battery packs, Ather Energy has now become a front runner in producing smart electric scooters in India. As a tech startup, the journey of Ather Energy was not facile at all. Tarun Mehta and Swapnil Jain’s startup was in one of the earlier batches incubated at the Research Park of IIT Madras. Mehta recalls the support of R. Krishna Kumar, a professor at the Dept. of Engineering Design at IIT-Madras.

“If a professor says, ‘Leave your job and come back; we will take care of everything,’ I think that is a great morale boost,” says the Ather CEO, “For the first fivesix months, we literally camped out of the department. We were just hanging around in his labs and other department labs before we sort of reached a conclusion that ‘This seems interesting and we should actually start a company and build a product.’ It was a very important phase and he was super supportive then.” The idea (now a reality) of an indigenous top notch electric scooter with the best of parameters is more than just the ultimate fancy of the atma nirbhar Indian consumer - Ather Energy’s rise is that of an engineering startup that dared to rethink the traditional rules of the automobile industry and started out with fresh ideas - a lesson truly pertinent to those who find themselves at the place where Swapnil and Tarun were in their first year at IIT Madras. Here we have Tarun Mehta, CEO and Co-Founder of Ather Energy who will walk us through the early-stage development of his startup. 7

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How is the startup scenario at IIT Madras? Do you see more such engineering startups coming up from IIT Madras’s Research Park?

IIT Madras & Ather’s beginnings: How has the company benefited from the middle ground between industry and academia that the incubation period at IIT Madras provided?

Tarun: We were one of the earlier batches to have taken incubation at the Research Park. But since then, now, the Research Park and the campus at large have been living up to the reputation of producing a lot of tech, hardware, and deep tech startups. IIT Madras probably has the best reputation in the country. Most of the startups that have come out are still early stage so we don’t hear as much about them. But honestly, for any early-stage VC or investor looking for the fountain of deep tech or hardware startups, it has got to be the starting point today. I will give a lot of credit to the foresight of the Institute and several departments (engineering design, biotech, etc.) and several initiatives like the CSI Center for Innovation and Entrepreneurship Cell, which I believe led to a lot of startups coming out of IIT. There is also an increase in the participation from professors directly as cofounders of more and more startups. That’s an extremely healthy trend, one that I hope will continue and accelerate.

Tarun: I think the biggest benefit of starting from the campus was the cocoon that it provided. Being amidst a lot of startups and being amidst enterprises has values, but there is an unsaid value of being in a place like the campus. The Research Park gives you time to develop your idea. It gives you time to iterate and form a long-term vision without getting too distracted. One of the biggest problems of being close to other startups or industries is that you tend to pivot a lot. Starting up at a place like the IIT-M campus allows you the space to form enough opinions so you don’t pivot a lot. And actually, that’s pretty much what I would say was the benefit of being at IIT when at the beginning. We were not exactly in the middle of industry and academia as much as we were in a really nice sheltered place for the first year.

Source: decoratingideas9.blogspot.com

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Source: blog.atherenergy.com

Ather Energy is a brilliant example of how engineering along with innovative ideas can provide solutions to major problems. As alumni of IIT Madras, how far do you think IIT Madras and the Department of Engineering Design in particular, try to inculcate that spirit? Are the courses designed in such a manner that it also engages and builds a student’s ability to think out of the box? Tarun: I think we were in a very interesting time on the campus when Swapnil and I joined in 2007. And it was a fantastic time because the Center for Innovation, Entrepreneurship Cell, and FSAE Project was just about starting up. A lot of the startups that came out in the 2011-13 period were by people who were extremely active in these initiatives. It was also an interesting time in that the Department of Engineering Design was just getting started. We felt that we were actually involved in the building of the department, we were the third batch. I do think that the department of engine design does have more openness and opens up more opportunities for people to think of starting up. At least back in our time, there was a lot of conversation not just on the theory but on physical projects. And not just physical prototypes, there was a lot of

conversation around understanding the entire journey of taking an idea to a product. So we had courses from the Management Studies Department, by Prof. L S Ganesh. We had courses within the department, where we ended up pitching the complete project, right from the cost of the prototype, to the development cost, to the multiple stages required to convert into a product. Obviously, the real industry and an actual startup are very different. But just the fact that courses are designed to make us think about all of this was extremely helpful. I also give a lot of credit to the professors. Even when we started up, we were literally camping out of the department. Professors like Sandipan Bandopadhyay, our Professor RKK (Professor R Krishna Kumar), and many others were extremely supportive. I remember when we wanted to start up, we just went and told Prof RKK that we want to leave our jobs because we want to start building electric vehicles. And his response was, “First leave your job”. And I think that’s amazing to hear from a professor. That it will be great if you just leave your job first. And because you want to build something, come back to the campus and come back to the department. And obviously the department was very supportive. So it’s a lot of small things that added up. Whether the courses are designed to encourage the students’ ability to think out-of-the-box, I’m not sure. But yes, some sections of it are. I do see a constant journey at the department level to try and get better at it. So I’m hopeful that we could have an ideal course structure in the coming few years.

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When you were at IIT Madras, how and what made you realise that it’s time for switching to the production stage (as a company) from the incubation and R&D stage? Tarun: It was the funding. The first money came from an alumnus who was delivering a talk on the campus. And because we were around the campus, we happened to bump into him. We pitched the idea. And we ended up raising 25 lakhs from him. That was enough for us to take real office space in the Research Park. But the journey from there to actually thinking of building a real company and not just a small lab, and actually hiring people at any significant scale happened when we raised the first million dollars from Sachin and Binny Bansal. Back in 2014, this was a phenomenal capital to raise for us. We had no plan of what to do with the million dollars back then. So that was the first time and we realized that it’s time to move out of thinking like a lab or a small incubated company and actually start thinking as a real company and hire people.

Vehicle Development & Vertical Integration: Ather is not alone in its bet on electric mobility. There are at least a dozen others in India working day and night to launch electric vehicles on Indian roads. But a key ingredient of what makes them, them, is Ather’s unique vehicle development processes. Unlike other electric vehicle companies, the company itself owns and controls its process, the suppliers, distributions, the whole supply chain - or in industry jargon, their production line is vertically integrated. They brought all of the technology in house and built everything from scratch (apart from the very basic ingredients - like the Li ion battery cell, which has to be imported) and in the process, reduced initial acquisition cost, created better prototypes and products, and also allowed themselves to bring unorthodox features to their product for example: a Battery Management System (AKA the brain of the vehicle) built entirely by

the people at Ather, that helps monitor all the cells, voltage, current, load, and temperature. It helps track the performance of the battery pack on a daily basis, and it has inbuilt algorithms that learn continuously about the usage and performance of its battery packs. We asked them to put up some light on the processes that they have adopted to make Ather scooters happen.

How do people at Ather come up with the initial idea of an electric scooter? What are the motivations at play when the team comes up with a new model ? Tarun: The driving belief for us is that the product has been built for us. Right from the first product that we started building, the S340, the belief has been that we should build something that we ourselves can use. And if we really can use this product, we might find 100 more such people like us. And eventually, this can be the start of a good company. Obviously, now that we’re scaling up, we are thinking beyond just our own selves. But that has been one of the starting ideas, to think of product development. Just build something that you yourself can be a customer to and then build your way from there.

Does Ather being vertically integrated and being dependent on itself for some of its technology induce delays in product development? How does Ather tackle that?t Tarun: On the contrary, the biggest benefit of being vertically integrated is that it makes product development extremely fast because it reduces external dependencies. And if you’re trying to build a well-designed product, typically external dependencies slow you down, because there’s no way that you will find all your vendors will have the exact specs that you need.

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And if all of them have to create a spec in line with what you want as a product, it’s a very long journey: communication is a nightmare, they may not have the right competency, their timelines will be wildly different, stitching them all up together and then negotiating with them is an incredibly long process. That’s part of the reason why nobody built an exciting electric scooter before S340 and 450 rolled out. It was just not considered viable. So being vertically integrated actually gives you a faster timeline if, and only if, you’re trying to build a fantastic product. If you’re just trying to build a product being vertically integrated is a slower route, and you’re better off taking a lot of things off the shelf and quickly integrating them in the best possible way. It may or may not give you the best spec. And it will certainly make the competition’s job very easy because once you demonstrate the integration, it’s easy for others to take out the same components and integrate them in a similar way. But it’ll give you a much faster timeline. But so it really boils down to what you’re trying to do.

How has the data collected from MESSI and other such systems helped Ather in developing, debugging and improving their vehicles? What exactly does Ather Energy do with all of the driving data that it collects? Tarun: So data helps in multiple ways. Firstly, data helps in better product development. As more and more data pours in, you’re essentially running a pretty large scale testing of your product, which is impossible to do internally. Today, for example, any automotive company does not have more than a few million kilometres worth of data, on even their old legacy products. Even with a product selling for the last 10-15 years it is very unlikely that any company will have more than a few million kilometres of data on it. On the other hand, in less than two years and barely a few thousand vehicles on the road, we already have 12 million kilometres of data on our own products. And the data quality is extremely high. Information on everything from acceleration, braking, motor performance, battery performance, battery degradation, thermal performance, performance, pack cycling, mechanical response, vibrations, to more software-related ones like when components need servicing, pour back in. And it’s extremely, extremely valuable for product design. In the last two years, we’ve been able to reduce the cost of the vehicle down to half of where we started. And a significant part of it can be attributed to the fact that we just had better data from the field, allowing us to make changes quicker than was otherwise viable.

MESSI - Making Every Scooter Smart and Intelligent - is a datacollecting device developed by the Ather team to gather more data than what they gather from prototypes and testing teams. MESSI can be plugged and used comfortably with almost all types of existing scooters. With MESSI, essentially a Data Acquisition System, several data types on the scooters are collected in real time from the end user’s experience - throttle, RPM, brake, horn, accelerations, orientations, and location

VERSION 1 AND 2 OF MESSI Source: blog.atherenergy.com

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Source: autox.com

And another way data becomes helpful is it allows us to give people more insights into their own riding patterns, which is extremely interesting, especially for early adopters. And it opens up the opportunity for developers to build new use cases on the back of the data that is already available, increasing the stickiness of the product and its ecosystem.

What are the current problems faced by Ather in their vehicle development process? Tarun: I’ll say the biggest thing that we’ve been with the building right now is an organization, an engine of an organization that can do product development recurrently and produce a very similar high-quality output every single time. It’s one thing to build a product, it’s another thing to build a company as a product. So I would say the biggest challenge faced is, converting the product development into an actual process that still continues to produce the same quality every single day.

The Market and the Policies: India has currently the fourth largest automotive industry in the world which contributes over 45% to the manufacturing sector of the GDP. India has one of the cheapest skilled labour forces in the world, and that could make India a global provider for clean mobility solutions and induce a much-needed spurt in exports. In terms of Government EV policy, while the

overall outlook of the Government towards the adoption of electric vehicles has been positive and even ambitious at times, their policy has at times been shaky. Peek here to get an insight into how government policies and rules are affecting the electric vehicle’s industry in India. Read ahead to figure out what people at Ather thinks about the government policies and how they have been affected by COVID-19.

How has the market and EV supply chain logistics been affected by Covid-19? How soon does Ather and the EV industry at large expect to be back on track (both in terms of market demand and supply chain logistics)? Has Covid-19 really delayed the Indian electric vehicle transformation for at least the medium term, or will the industry bounce back quick enough? Tarun: The lockdown had disrupted the local supply chains and manufacturing, and had also impacted demand in the short term. This disruption will definitely have a strong impact over the next 2-3 quarters, post which we should begin to see the industry starting to get back to pre-COVID levels. In the immediate future, there is an opportunity to experiment with new ownership and finance models, given the squeeze in people’s disposable incomes.

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Since a bulk of EV components (most notably, the Li-ion batteries) are sourced from outside India, how far is the government helping with localisation of supply chains and production of raw materials inside the country; and with indigenous R&D related to electric vehicles? Tarun: The government needs to step in with supply-side incentive. The conditions have been extremely right for the 12-18 months, with most global suppliers setting up manufacturing in India – like making motor controllers, electronics etc. they are all looking at the sector very strategically. Outside of China, Asia will be a massive market for manufacturing of 2 wheelers and India will become a natural possible choice for a hub in south Asian manufacturing. There is a massive interest from suppliers to set up large capacity in India.

Source: autox.com

The fundamental need for mobility hasn’t gone away. If anything, people for whom public transport, ride-share etc was their primary mode of transport, will now be open to personal mobility. That is great for the automobile industry. The impact on EVs will probably be lower than it will be on ICE vehicles.

At this point, if the government can step up and provide some supply-side incentive, not what they offer the OEMs like land subsidy, discounts, labour subsidies if these can be extended to EV component manufacturing companies too, will be really good. For example lithium-ion cells manufacturing, that’s the one thing that affects the entire EV industry in India, I know many companies are seriously looking at it but some support from the government will be very useful because the timing is right, everyone is excited and the industry seems to be growing.

How has the EV industry and Ather Energy in particular been hit by the boycott of Chinese goods, considering China was a major source of Lithium-Ion batteries for the Indian EV industry? Tarun: For a lot of OEMs the supply was severely affected for a few months, especially those that are dependent on international partners. Ather has a strong local supplier base for nearly 90% of the product being indigenously built and sourced from past one and half years.

What does Ather Energy think of the FAME-II (Faster Adoption and Manufacturing of Hybrid and Electric Vehicles - II) scheme?

Taiwan is a much larger manufacturer, so the direct dependency for anything on China is no longer there. I feel there is heightened awareness and reduced dependency on vendors from China because brands are aware of the changing geopolitical situation. Companies are looking for and experimenting with vendors from across the globe.

Tarun: We at Ather believe FAME 2’s intent was to incentivize the EV industry to build high-quality vehicles that consumers would buy. It incentivized better technology - lithium

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-ion batteries and incentivized OEMs to build vehicles that would be comparable to ICE vehicles so consumers could make the shift to EVs. FAME 2 has been a boon to the market that is building electric vehicles and this can be seen in consumersâ€™ reactions and brands like ours have been able to sell their products at a more affordable price. Most importantly it promoted Make In India and disincentivized importing kits and components. The Government of India has announced an outlay of 10,000 crores under phase 2 of (Faster Adoption and Manufacturing of Hybrid and Electric Vehicles - II) FAME scheme on April 1, 2109. For consecutively three years, the government will offer incentives for electric buses, three-wheelers and four-wheelers to be used for commercial purposes. Plug-in hybrid vehicles and those with a sizeable lithium-ion battery and electric motor will also be included in the scheme and fiscal support offered depending on the size of the battery.

and monthly expenses of an electric vehicle will always be far more affordable than ICE vehicles.

Future plans: Ather Energy develops all of their technology in house, and to add more to their unorthodox business model, Ather has also come up with their own charging network, and a facilitating app for the same. As a part of this project, Ather has already established several charging stations in Bangalore and Chennai. These DC-fast-charging stations dubbed as Ather Grid use Atherâ€™s proprietary charging method and connector to charge the Ather scooters. Unlike most auto manufacturers in India, Ather Energy owns and operates its own Experience Centers - Ather Spaces which aim primarily at providing customers with the insights of the Ather bikes developed by them. We wanted to know from Tarun what is next for Ather Energy:

What is the market price and operational cost of owning an Ather Energy scooter as compared to an ICE (Internal Combustion Engine) Vehicle? Tarun: Ather 450 retails at around 1.13 lacs while the 450X is for 1.49 lacs and 1.59 lacs. Although the TCO is slightly higher compared to a ICE model (Aprilia costs around 1 lac). There are 2 key segments in EVs today - one that is looking at EVs purely from a TCO perspective, and the other that sees EVs as the future of automobiles, and technologically superior. For the first, the tough economic environment makes the case stronger to go for EVs. The second segment is skewed towards the premium end of the market, and relatively less vulnerable to the economic environment. Oil and gas prices fluctuating, the maintenance FOUNDERS SWAPNIL JAIN AND TARUN MEHTA Source: cantemtemizlik.com 15

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How far are we as a country from achieving electric mobility on our roads, and where does Ather Energy see itself in India’s electric future?

Are there any plans for producing new and unorthodox products that further improve the rider’s experience (for example, smart helmets) anytime soon?

Tarun: One of the best things to happen with the pandemic is people have now realised the importance of a clean and green environment, and have witnessed the quick results that can be seen with reduced air pollution. The transport industry can only reduce air pollution by making a systematic shift to electric mobility, this will drive the transition in India.

Tarun: We plan to roll out a Tyre Pressure Monitoring System (TPMS) soon and offer a smart helmet option by the end of March 2021. These features are designed to exploit the scooter’s connected tech features.

Ather Energy started off with Tarun Mehta and Swapnil Jain developing Battery packs. Did you (at least initially) have any plans of expanding into the energy sector, and do you still have any such future plans?

The year 2019 was one of the worst years for the traditional automobile industry with falling sales and piling inventory. Passenger vehicle sales declined by 17.98 per cent in April-November 2019 over the same period last year, according to the Society of Indian Automobile Manufacturers (SIAM). In a way, the industry was struggling even before the pandemic unlike the EV industry, which saw a 20% increase in sales. With new and existing brands launching more efficient and powerful electric two-wheelers that are nearequal or better in performance than their ICE counterparts, electric vehicles will definitely be the future of mobility in India.The pandemic may have disrupted our timelines for the national launch of the 450X, but not our spirit. We will be starting deliveries of the 450X starting next month in a phased manner across all the 10 cities we announced early this year. By Q1 of 2021 Ather 450 will be on roads in Mumbai, Delhi, Chennai, Bengaluru, Hyderabad, Coimbatore, Kochi. Ahmedabad, Pune, and Nagpur.

Tarun: Currently, all our energies are into launching the 450X nationally. As I’m finishing this article, I can only think of one way to wrap up this series on Ather Energy - how it has taught me what true engineering and entrepreneurial virtues are. In just a couple of months time, engineering campuses all over India and IITs specifically will again be teeming with enthusiastic first year students (at least in online classrooms, if not physically) ready to take on the world with their ideas. And if there is one message that they need to imbibe, is that the road to success today is not the oft quoted ‘stable’ engineering career - but rather, it starts from daring to explore new possibilities, and goes forward with vision, hard work and astute knowledge of one’s field of expertise. And what better example of that than Ather Energy itself!

Does Ather Energy have any plans of coming up with other products (Electric Cars, or electric motorbikes) than the electric scooters currently being made? Tarun: Not at the moment

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Innovation to aid reopening amidst plummeting GDP:

AI based social distancing An idea turned innovation - turned Start-Up - Yantrakaar AI, founded by the students of IIT Kharagpur with the motivation of providing simplified Tech solutions to help fight the virus.

Written by NITHISH KANNEN Designed by SHALMALI SRIRAM

ith the raging global pandemic beating its own record each day, causing potentially irrecoverable economic fallout and accounting for over 100 million jobs globally, normalcy seems a distant dream. The global economy is reeling from a monster, one that can make even the 2008 recession look like a mere dry run. Of course, the invisible virus is one thing. But let‘s not forget the elephant in the room: the risk of a financial heart attack. It is too early to predict the economy‘s course after the pandemic confidently, but a recession is clearly inevitable. The global market was already shaky in 2019 and now deliberately shutting down the world‘s major economies sure doesn‘t help the cause. What started with the breakdown of oil talks and Saudi Arabia‘s announcement of a price war is now a global economic fallout. No one alive has seen a crisis of this nature and magnitude before. The perfect policy and ideology to deal with such a conundrum is still an active debating point among epidemiologists. It is not right to expect the government to come up with a solution magically. The fact is that bureaucracies themselves have little to no experience dealing with low-probability, high-stakes biomedical risks like pandemics. They sit awkwardly between the conventional silos of modern governance and mathematical models of risk assessment. South Korea, a nation that experienced one of the most significant initial outbreaks after China, has managed to defeat the virus without even imposing a nationwide lockdown. The East Asian country has used a big data approach to contact tracing, using credit card history and location data from cell phones. Surveys confirm that most Koreans were ready to concede digital privacy to prevent an outbreak. Authorities also imposed strict social distancing campaigns, leaving most bars, restaurants, and movie theaters free to operate.

Source: news-medical.net 19

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obviously bleak. But one feat is common to all success stories: ‘effective enforcement of social distancing.’ The effectiveness of social distancing in containing the spread of the virus is established. By now, all of us have come across numerous news articles and medical research highlighting social distancing as the single most potent weapon against the disease spread.

WE DON’T EVEN NEED A VACCINE IF SOCIAL DISTANCING IS ENFORCED EFFECTIVELY Source: Statistica

The recent Wuhan pool party might have managed to lift a few sunken spirits — given that Wuhan is claimed to be the origin of the virus. China imposed one of the strictest lockdowns the world has ever seen. Beijing embarked on one of the most extensive mass mobilization efforts in history, closing all schools, forcing millions of people inside. Drones hovered above streets, forcing people to get inside their homes. Chinese facial recognition software (which was discussed in detail in ‘The Dating Paradigm’’) linked to a mandatory phone app, color coded people based on their contagion risk. Spain, Germany, Italy, the United Kingdom, and other European nations have had their own models to combat the deadly virus. While there is no correct way of doing this — the chance of a model from one region succeeding in totally a different geography is

While most countries that have the spread in check have figured out an efficient and elaborate way to enforce social distancing. But the situation in India is, as always, unique: India is a country with more than 1.3 billion people and a population density of 464 per sq. km - in China, the world’s most populous country, it is 153, in the US, it is 36, and in Russia, it’s just 9. An average Indian family has five members, and 40% of all homes - that is, 100 million households - have only one room. In a country like India, social distancing is a mere oxymoron. You might wonder how South Korea, with a higher population density (527 per sq. km) than India managed to enforce social distancing — apparently, their style of tunneled, semi-basement homes come handy (inserts PARASITE theme). On a serious note, it’s not just the homes; most of our workplaces aren’t designed for a pandemic - like situation. Most of the Indian workspaces are cramped and poorly ventilated. It seems nearly impossible to enforce human distancing in a factory with over a thousand laborers cramped over a few acres of land. Given how many of us we are, the Indian

JUST A REGULAR INDIAN STREET ON A COMPLETE LOCKDOWN Source: Alamy Stock Photos

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THE PROTOTYPE Source: Yantrakaar AI Website

markets, places of worship, eateries, and literally every other place we go to is designed to accommodate maximum number of people in a given area. Is it even possible to keep people 2 feet apart in public places, let alone 6 feet? The reason why an external Social distancing monitor is crucial for a country like India becomes apparent in just a visit to a market in your neighborhood; a simple ‘device,’ per se, one that probably notifies people or ensures that ‘ Social Distancing’ is something that runs in the back of people’s mind while they go about doing their everyday activities. This device can essentially alleviate all the problems discussed above: can get people to their workplaces safely and back, can ensure safety in workplaces, can initiate reopening of public places such as malls and markets, and eventually help us take a giant step towards the revival of our plummeting economy. Obviously, a technology intervention is called for. Enter AGV (Autonomous Ground Vehicle), a student research group in IIT KGP that works on multi-disciplinary projects ranging from Deep Learning to Self-Driving. Realizing the necessity of futuristic innovation and a technology intervention to actualize what looks like a promising idea on paper, they have developed a cyber-physical system based on Artificial Intelligence for monitoring social distancing in public places. Yes, they brought together the two buzz words of 2020:

Artificial intelligence and Social distancing. Under the leadership of Professor Debashish Chakravarty and professor Aditya Bandopadhyay, the team has engineered a low-cost device for monitoring social distancing in public places using a Plug and Play Hardware(P2H) Solution. In a nutshell, this device can ring an alarm or notify the concerned authority about any violation of social distancing norms. The Plug and Play hardware has been bestowed with additional features such as one-click calibration, auto pose correction, and a web-based user interface to customize it for different locations and monitor feed. What followed was an ingenious Hybrid Cloud Computing based Smart Surveillance [HC2] solution that is compatible with pre-installed CCTV networks. Since most companies have a CCTV network in place, this HC2 can just be integrated with the existing cameras. The computations are performed on the cloud; hence, a fast, efficient solution is not limited by the user’s computational capabilities. The Graphical user interface can be installed on the user’s desktop supported by Windows, Linux, or macOS. The interface has a user-friendly dashboard that allows visualization of instances of violation of norms. The dashboard tracks

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INTERFACE Source: Yantrakaar AI Website

the number of such occurrences in a given time and records images of breaches that can be viewed in a slideshow mode. The HC2 uses various parallelism levels to enhance computational speed by allocating 50 parallel servers to each user, allowing them to integrate 150 CCTVs on a single network. This systemâ€™s efficiency is further reduced by using motion-triggered object detection and computation: the users are not charged for instances of inactivity, such as instances of an empty room or a single stationary person. The HC2 solution comes with an added feature of Masked Face Detection. Companies can now penalize their employees for reasons that would have been considered crazy half a year back! Tailor-made to suit places like India, this remarkable effort was acknowledged by popular media networks and the Minister of Education.

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Realizing the potential in the scalability of the project in domains such as Traffic Surveillance, Industries, Workplaces, and Automation, the team leader Rishabh Singh (a 4th-year undergraduate student at IITKGP), along with a few of his teammates has founded Yantrakaar AI, a start-up aimed at commercializing this product and providing other AIbased solutions primarily for industries. The start-up has already been contacted by the energy giant, ONGC and a few Diamond and Textile industries in Surat.The startup envisions a futuristic society that leverages AI and Cloud Computing to solve its problems. Here are excerpts from an interview with Rishabh Singh, Founder of Yantrakaar AI: Nithish: What was the inspiration behind the project? Rishabh: An important factor was the convenience of development with the initial prototype because the development team was proficient in Computer Vision. Definitely some similar projects have been made before, but none have been made which is so user- friendly that is affordable and can be scaled easily. The optimizations methods used both at local and cloud computation level are novel, and the code is robust and can handle errors, which becomes an essential point for a commercial product. Nithish: Briefly mention some of the roadblocks and challenges faced? Rishabh: The major challenges that we faced were making the product affordable for use, as we involve cloud computing in our HC2 model, and we used AWS for that, which itself is too costly, so we optimized our pipeline accordingly to reduce cost as much as we can and was able to narrow down it to just Rs 9 per camera per hour. Another challenge was to make the processing in real-time and to reduce the latency as much as we can, due to the lowspeed internet connection of the customer, latency tends to increase exponentially, so to control that we tried to allot multiple servers while maintaining the low cost. Lastly, to make the software understandable to use and

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to bring transparency in processing was one of our major challenges so to overcome that we designed a GUI compatible with all major OS types which provide the user step by step instruction to install the software with the help of GIFs and also act as a control panel to set-up cameras and to visualize results. Nithish: Where will this device be positioned and what is its range/effectiveness? Rishabh: Our solution comes with dual model support (model A and model B), which are trained for different use cases. Model A supports close range cameras, which can generally be used for Indoor monitoring, located at a height up to 12m, and Model B supports long-range cameras, which are generally used for outdoor monitoring and located at a height above 12m. Previous attempts have been made to support these kinds of models according to the specific use-cases, but we are not aware of a DualModel Hybrid solution like ours, that optimizes computation and offers flexibility based on usecases for every individual camera in the network. Nithish: What is the scope of expansion? Rishabh: The product has a foundational architecture of smart surveillance and can be scaled to similar applications within days. For example, it took us only three days to add the Masked Face detection feature to our software, as we just need to change the detection pipeline without changing anything else. The solution is highly scalable in Traffic Surveillance, Industrial Automation, etc. Necessity is the mother of invention.The damage to health, wealth and well-being has already been enormous. This has been more like a world war, one where all of us are on the same side. Developing vaccine prototypes, which used to take decades at the least before, is being developed and tested within months. The world is working in tandem to defeat the invisible enemy, and global innovation is key to limiting the damage. We still have a long way to go.

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Prediction on drug-drug interaction : A life-saving deed

A research team of the Computer Science and Engineering department of IIT Kharagpur has developed a noble algorithm for effective detection of drug blending and producing better characteristic understandability of interrelated drugs. Written by RAJDEEP SARKAR Designed by SHARVARI SRIRAM

volving technologies in all fields have demanded autonomous features over time. As visible to us, there are numbers to render right now- cars, self-navigating drones, military robots, underwater vehicles, and getting quite optimistic in enlisting all those names that ease up our technical chores and put a significant impact in increasing the productivity too. Based on recent breakthroughs in the domains of deep learning and artificial intelligence, extensive and prompt regulatory developments are needed to specify the requirements from them and manage their deployment. And they all need unprecedented levels of safety and security, to overcome concerns about the potential negative impact of the new technology. Such is the case in the identification of an indefectible drug or admixture of drugs while referring to a patient. Reasonably, we search for a reliable algorithm in providing us with the pieces of information on drugs that can counter the affiliated health issues. Interactions between drugs can lead to serious unwanted effects or a reduction in the therapeutic effects of some drug compositions. As we see, in elderly patients, there is a regular prescription of concurrent use of multiple medications, which the medical practitioners call Polypharmacy. It is not something to be necessarily considered as an illrecommendation, about more than 40% of the older adults are relying on polypharmacy. But also it is a severe matter of concern since, in many instances, it can lead to adverse outcomes or reduced treatment effectiveness and sometimes even being more harmful than helpful or presenting too much risk for petty benefit.

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Here we enlist the underlying causes of unwanted drug effects and interactions:-

On choosing the practical pathway Before we move in-depth, it is necessary to know that prediction of drug-drug interaction is an important aspect in the domain of drug development or more specifically for producing a chemical combination since the concurrent administration of one or more drug is a common phenomenon in the field of pharmacotherapy and the effect of one drug might alter the influence of another and result in an interaction between them. In recent years, newly formulated drugs are getting commercialized and thus are smoothly available in the markets, therefore, making it a distinct job for the professionals to characterize the drug-drug interactions.

Wrong choice of drug Failing to take account of renal function Wrong dosage Wrong route of administration Transmission errors Errors in taking the drug

A research team lead by Prof. Sudeshna Sarkar and Prof. Pawan Goyal comes up with the idea of predictions on drug-drug interactions which can be much beneficial to save lives.

However, this process of drug-drug interaction is way time-consuming, expensive, and too laborious. A compelling force thus influenced the computer scientists to give rise to a tenable software that characterizes an effective computational method to identify and categorize different drugs based on the protein structures, chemical similarities, and successful interactivity, which can account for better management and reduce the chances of chronic diseases to happen. Till now, over the planet, the progress on the

VISUALIZING THE CASES THAT REQUIRES DRUG-DRUG INTERACTION AND THEIR POSSIBLE EFFECTS. Source:- Department of Health and Human Sciences, US

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Source:- Nature

routeway of drug-drug interaction’s prediction was adhered to thorough retrospection of similarities in protein structures and dealt with the experimentation with drug pairs to identify the side-effects and the physiological factors. But, what new are we getting this time which can improve the effectiveness in a broad sense?

in its behavior or function. This additional information will do a great help in predicting the binding capability of drugs with the targets, which in turn can tell us the unknown interactions among drugs and the possibilities of their use in medications and treatments. That would be quite less time consuming for future medical prescriptions.

Tzhis time our researchers came with the deep learning methods that will not only take care of the above-mentioned chemical factors but also aims at providing the information regarding drugs and the biological targets as well. Here, by the term “biological-target” we simply mean any protein or nucleic acid to which a specific biological entity binds, resulting in a change

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How they got this formulated?

experience, or instruction, to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly.

It becomes our primary responsibility to point out the need for the existence of machine learning principles; we grow up and learn things and even acquire some habits over time, but machines are not gifted with brains. They only follow those instructions that are put forward by the user, thus it became the need of the hour to train the machines priorly by passing some specific set of pieces of information which will vary according to the specified cases.

Here, along with these algorithmic features our researchers also came to add another factor that will for sure increase the predictability, which is basically a “graph” and its purpose is to represent a collection of interlinked descriptions of entities – real-world objects, events, situations or abstract concepts. And professionals prefer to call it “Knowledge-graph” where entity descriptions contribute to one another, forming a network, where each entity represents part of the description of the entities, related to it.

Machine learning is a subset of the larger field of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. The process of learning begins with observations or data, such as examples, direct

Similarly, here the main entities are drugs, and their complete available pieces of information are taken down from bioinformatics databases namely DrugBank and UniProt, as this time we have moved ahead with the gene-sequences

ALGORITHM RELATES PHYSICO-CHEMICAL AND BIOLOGICAL FEATURES TO STUDY THE ACTIONS OF CERTAIN DRUGS. Source:- Amazon Science

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and protein structures, a lot of input data will for sure provide us results with a better probability. Furthermore, the â€œTargetsâ€? which can be proteins or nucleic acids, and lastly the disease from which one is suffering. And finally, algorithms helped to establish the relations between these entities which in turn tells us the probability of those drugs interacting and countering a disease successfully and also for those which are not.

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running the codes. Secondly, it will become less time-consuming in a majority of the cases when we have a greater surety in medication by the drug interactions since prior produced drugs can be studied more proficiently. Their unknown effects can also be laid down, which in turn will not solely rely on the production of new drugs with new protein structures for the medication of the adult patients.

And how are we benefited? On the verge of the formulation of this sublime algorithm, we are left with two essential advantages, which can be briefly explained; firstly, we see an opening up of the door to reduce the labor charges on a visible margin and making it profitable for the pharmaceutical and medicine manufacturing industries as from now onwards no hand-on activities are required to study the effectiveness of drug interaction, as the database can be explored by

ILLUSTRATION PRESENTING THE FUNCTIONING OF ALGORITHM BY CLASSIFYING THE DATA AND MAKING PREDICTIONS ON INTERACTION. Source: Nature

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Cars and Carbon Nanotubes: What does IIT Madras say?

A group of researchers in IIT Madras discovered that carbon nanotubes can be used to reduce vibrations in automobiles, which may prove to be a groundbreaking discovery in the future

Written by GARGI DAS Designed by SHALMALI SRIRAM

“W

hile it may seem small, the ripple effect of small things is extraordinary.”

For centuries, it was small things that had a much humongous effect on mankind as compared to the bigger things. For instance, a small depreciation in a country’s currency can result in a big economic setback, a small virus can cause a pandemic and so on. However, small things can also bring about significant positive changes. It has been discovered that a small element called “nanofibre” can have a great impact on our lifestyle. But how? Let us take a look at the latest innovation by a team from IIT Madras. Dr. Prathap Haridoss, Dr. Anand Joy, Dr. Susy Varughese, Dr. Anand K. Kanjarla, Dr. S. Sankaran along with the research students from the Metallurgy and Materials Department of IIT Madras has come up with Carbon Nanotube Composites that can reduce vibrations in automobiles. Their paper has been published in the peer reviewed international journal Nanoscale Advances. They have together developed an interesting polymer based composite. It shows how carbon nanotube fibres can help reduce vibrations.

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About The Experts

Carbon Nanotubes A carbon nanotube is a cylindrical tube of hexagonal carbon atoms with a diameter of nearly one nanometer. Carbon nanotubes can be single walled (SWCNT) or multi walled (MWCNT). MWCNTs are two or more nested single wall nanotubes joined by weak molecular forces. These are expected to be of various uses in different spheres such as electronics, optics, composites, nanotechnology, material science. Letâ€™s get a sneak peek at their properties which would make it a bit clearer for us to understand exactly why these tiny volunteers were chosen.

Mechanical Properties:

Dr. Prathap Haridoss graduated from IIT Madras in 1992 with a B.Tech degree in Metallurgical and Materials Engineering. He then went on to earn a Ph.D in Materials Science from the University of Wisconsin Madison, USA in 1999. He has worked as a senior scientist in Power Plug Inc., Latham, NY, USA and is presently a faculty in IIT Madras in the department of Metallurgy and Materials Engineering.

They are the stiffest material yet discovered in terms of tensile strength and elastic modulus. Strength of individual CNT shells is very high. A multiwall nanotube was tested to have 63 gigapascals of tensile strength while an individual CNT has a strength of approximately 100 gigapascals. Because carbon nanotubes have a low density for a solid its specific strength is high, it is the best of known materials.

Electrical Properties: They are known to be metallic or semi conductive. They have a high electric current density and are explored to be used as interconnect and conductivity enhancing components in composites. Intrinsic superconductivity has also been reported, however, no concrete evidence is found yet.

Optical Properties: They have important absorption, photoluminescence and Raman Spectroscopy properties. Numerous parameters of the nanotube manufacturing process can be changed to alter nanotube quality. Photodetectors and LEDs based on single nanotubes have been made in the lab. Crystallographic tubes have also affected the tubeâ€™s working.

Dr. Anand Joy is a research student in the Department of Metallurgy and Materials Engineering in IIT Madras. He worked in the lab under Dr. Prathap Haridoss. Earlier he had also worked for a project funded by the Naval Research Board. Presently he works as a senior Mechanical Engineer at Applied Materials.

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Thermal Properties: All nanotubes are considered to be good conductors along the tube but good insulators lateral to the tube axis, known as Ballistic Conductors. Their thermal properties are also affected strongly by crystallographic defects.

What do we mean when we say Polymer Nanocomposites? They are polymers or copolymers having nanoparticles or nanofillers dispersed in a polymer matrix. They belong to the category of multi phase system and consume nearly 95% of plastic production. They have a greater ratio of surface area to volume which implies a greater dominance of atoms on the surface than the interior of the particle. This increases their strength, and the particle becomes more heat resistant. They also have a broad range of applications including homogeneous and heterogeneous catalysis, sensorics, filter applications and optoelectronics. Polymer nanocomposites are thousand times smaller than the thickness of the sheet of paper. Thus, these extraordinary properties are what the team looked forward to exploiting. Carbon nanotube reinforced polymers are extremely long and light fiber-reinforced plastic which contains carbon fiber nanotubes. They have ultra-high Youngâ€™s modulus and tensile strength which are promising, which means they wonâ€™t break easily under load. They also have good electrical and thermal properties which make them a good candidate for a wide range of applications such as nano-sensors and atomic transportation.Dr. Prathap Haridoss graduated from IIT Madras in 1992 with a B.Tech degree in Metallurgical and Materials Engineering. He then went on to earn a Ph.D in Materials Science from the University of Wisconsin Madison, USA in 1999. He has worked as a senior scientist in Power Plug Inc., Latham, NY, USA and is presently a faculty in IIT Madras in the department of Metallurgy and Materials Engineering.

Source: greenfuture.io

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What is Viscoelastic property and why can it be sought after? It is the property that depicts both viscous and elastic characteristics of matter when they undergo deformation. The viscosity of the matter gives it a time dependent rate of strain. These substances dissipate energy as opposed to elastic materials and this property helps in absorbing shock by dissipating a part of the mechanical shock into heat energy. The viscoelastic properties of polymers are combined with the inter-facial properties of CNT to dampen vibrations. The team used MWCNTs synthesized by different methods and loaded in epoxy. Their damping effects are visualized by studying computational simulations.

The team has focused much on how much difference the structure and morphology of a material makes in the damping properties of polymer composites. The paper also stresses on how the origin of vibrations is not the intertube frictional loss but between the atoms of the inner tube and the outer tube. The atomic interactions between the end caps of the tube were simulated. It is also found that the mean diameter of the spherical particles increases with the CNT and adduct particles. The damping mechanism is probably due to the relative sliding of spherical particles during dynamic load which dissipates energy. The reduction in the distance between spherical particles as well as the reduction in the elastic modulus of the continuous phase facilitate relative sliding.

CN EXPECTED TO REDUCE VEHICLE VIBRATIONS Source: IIT Madras Facebook Page 34

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CN EXPECTED TO REDUCE VEHICLE VIBRATIONS Source: vernacular.ai

“Our simulation studies have shown beyond doubt that the vibration damping properties of MNCWTs arise from interaction between the atoms that consist of the inner and outer tubes rather than the intertube frictional energy loss”, states Professor Haridoss. Source: Futuristech Info

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Paper to Pulp to Paper : The Hydrapulper

There is a debate about the enormous usage of paper.Whether it comes to printing books or taking notes,many still prefer paper over digital devices.Naturally,the question arises;why not just keep recycling the large amounts of used paper instead of making paper by cutting down trees? Written by SHREYA M P Designed by NIDAMANURI CHANIKYA GUPTA

ccording to Shred-it UK, a company that provides paper shredding services, it takes up to 70% less energy to recycle paper than to produce new paper from trees. However, paper recycling is being done in large industries and it is expensive to do it on a small scale. Paper is made of cellulose fibres from various sources. In order to recycle paper, the fibres must be separated and made into a pulp. The properties of the pulp can be tweaked by adding chemicals according to the product that needs to be produced using the pulp. This is exactly what a group of students did at IIT Palakkad but on a smaller scale by building a device to recycle paper. Under the supervision of Dr Dinesh Jagadeesan, an Assistant Professor in the Department of Chemistry at IIT Palakkad, a student team made the ‘Hydrapulper’. The team members are N. Poojitha (BTech Mechanical Engineering), MVS Bala Narasimha (BTech Electrical Engineering), K. Sai Deekshith (BTech Computer Science Engineering) and R. Rohith Reddy(BTech Electrical Engineering) who are now final year students.

The motivation behind the project As part of the Csquare innovation programme (Csquare or Creation square is the innovation lab at IIT Palakkad), the group was given the problem statement: Converting waste paper into Papier-mâché. They came up with the Hydrapulper to solve this problem.

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What is the Hydrapulper and how does it work?

The trial run Using the chemicals alum and rosin (the team pointed out that similar chemicals can also be used) and the pulp made using the device, they were able to make a thick but brittle piece of paper. They werenâ€™t able to figure out the exact composition of the chemicals needed to produce paper with better quality. The pulp can also be used like clay to make crafts by adding adhesives.

It is a device where shredded paper soaked in water can be fed in and turned into pulp. With the addition of chemicals, the pulp can be used to make a number of products. The device consists of a container made of stainless steel in which a spiral blade is placed inside. A motor is used to transmit power and the shafts of the motor and the spiral blade are connected to a belt and pulley arrangement. Anti-Vibration pads were used and thus the wear and tear of the parts was reduced.

Improvements that can be made

The spiral blade (which has an increasing radius) generates friction between adjacent layers which turns the shredded paper into the basic fibres which form the pulp. The pulp produced can be used to make paper or any products that are made using paper. About 1 kg of shredded paper can be recycled using 20L of water.

Challenges The team had a budget of 10,000 INR to finish this project. They also had a strict deadline and had to complete the project in 45 days. According to the team, procuring the motor and fabricating the spiral blade were the hardest parts. Apart from these obstacles, they encountered several technical difficulties. There was wobbling and heavy vibrations when the device was running. This was due to the type of collar used in the shaft and the mass imbalance caused because the spiral blade was asymmetric.

THE HYDRAPULPER MADE BY THE TEAM Source: MuSE IIT Palakkad

Although the hydrapulper built was able to produce pulp, many improvements can be made to the design to keep improving the efficiency. For instance, instead of using the pulley and belt mechanism, a gearbox can be used. This would make the device more efficient. But due to budget constraints, the team wasnâ€™t able to procure a gear box. Secondly, the device does take a long time to convert paper into pulp. It is possible that after optimizing the design of the hydrapulper, the process can be made less time consuming. If the hydrapulper can be marketed at a lower price, many paper products can be made which will serve as a source of income especially for the rural population.

The experience gained As we all know, working on a project is not only about sharpening our technical skills, it teaches us a lot of soft skills;The team worked on this project during their summer break after their second semester.

THE PAPER MADE USING THE PULP PRODUCED BY THE HYDRAPULPER Source: MuSE IIT Palakkad 38

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So, it was not a surprise that they were quite inexperienced when it came to managing time and funds while working on relatively large projects compared to what they might have done previously during their school days. When asked about the experience gained while working on the project, Poojitha, one of the team members said, â€œWorking on this project helped us learn the skill of time management and also problem solving. The first prototype we built was not up to the mark and we had only 45 days to build the hydrapulper. So with improvisation and a lot of brainstorming, our team was finally able to build itâ€?. The team won the Csquare Innovation program in 2018 participating among 13 other teams who worked on other innovative projects. They showcased the hydrapulper by representing IIT Palakkad at the Unnat Bharat Abhiyan (Tech4Seva) conducted at IIT Delhi. As of now, the team members have not planned to make any improvements to the device and market it. But they would like to work on it sometime and hopefully, make the hydrapulper available at an affordable cost in the market.

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OCT: Optical Coherence Tomography OCT is an Emerging Technology for Biomedical Imaging and Optical Biopsy giving us the ability to dive deeper within into the layers of the retina and understand the complexities with ease using state-of-theart Machine Learning techniques.

Edited by MOHIT SHARMA Designed by AVANTI HARGUDE

ith age and time, our Eyes and the retina starts to lose its integrity and the ability to interpret signals from the visual cortex of the brain thus pacifying and fading into oblivion. A big reason is being unaware of what happens within. The vitreous humor that holds all the layers in place by applying force on them, starts to lose its viscosity. Subsequently, the retinal layers that were tightly bonded and communicating at a phenomenal rate are suddenly put into a jolt. A jolt that makes them loose from each other and breaking of micro neurons. But this is not where the problem begins. Our body knows how to tackle this by adjusting the cornea and the lens. The real danger lies in the formation of a tumor in the choroid layers with prolonging inattention to the eyes. This tumor is capable of hampering your eyesight forever.

We all know about this complex engineered visual receptor organ known as â€˜The Eyeâ€™. With what ease it distinguishes & classifies different objects contrasting to a state of the art deep neural network algorithm or computer vision software. But do you know sensory intellect comes at a cost? A cost where you can lose this visual prowess forever! And you might not be even aware of it.

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A STATE OF THE ART OCT MACHINE AT DIVYADRISHTI IMAGING LABORATORY, IIT ROORKEE. Source: Divyadrishti Imaging Laboratory at IIT Roorkee.

ABSTRACT DEPICTION OF THE COLOR SPECTRUM INTERPRETED BY THE EYE Source: Shutter-Stock

I’ve told you about where the problem lies but I haven’t told you about why we can’t rectify this problem with the ease we solve other problems. Firstly, it’s very arduous and impossible to predict the tumor size and location by seeing the external eye. We need to dig even deeper and this is where Optical Coherence Tomography kicks in. Optical Coherence Tomography or OCT is the technique that uses a laser projection to map the internal surface of the eye. The laser enters the eye and hits the retina causing a spike in the frequency of the laser. This spike is recorded on a graph and using the correlation to the thickness of retinal layers, the geometry is plotted. To understand more on this complex subject we go to Divyadrishti Imaging Laboratory at IIT Roorkee. The main theme of the research

Lab is creating hardware and post-processing soft tools, mainly, related to Direct and NonInvasive Imaging for Industrial and Medical Applications. Non-Destructive Evaluation is also one similar field. The Major objective of research is to pose challenges so as to improve the understanding of Radiation Propagation and its measurement, in general.

The team from Divyadrishti Imaging Laboratory, IIT Roorkee tells us, “There are only 3-4 OCT machines on the Earth! With one of them being at IIT Roorkee. Our mission is to provide better healthcare facilities in the domain of optometry.”

OCT A vs OCT B vs OCT C SCANS Source: Functional Connectivity Of The Rodent Brain Using Optical Imaging by Edgar Guevara 42

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The team also tells us that there are three types of OCT scans namely — OCT-A, OCT-B & OCT-C. The major differentiation factor among the three is the dimension of the scan. In OCT many one-dimensional scans (A-scans) are performed at several depths to create a twodimensional image (B-scan). Those B-scans, if acquired closely and rapidly, can be translated into a volumetric image (C-scan) of a retina, So we do have a possible solution to take a glimpse into the internal framework of the eye. So why can’t we rectify this tumor? Our modern-day techniques only allow us to take an image of the internal working of the eye but don’t classify whether it has a tumor or not. This is where doctors scratch their heads as they cannot tell if the retina has a tumor or not with exact assurance. There might be a lot of falsepositives that may lead to unnecessary treatment or a lot of false-negatives leading to failure of treatment. So what is the one true solution? Deep Learning! This is where the solution lies. I may have said in the beginning that The Eye surpasses every possible deep learning model. So how can it detect the tumor? The secret lies in the capability of a model learning the same

OCT SCAN SHOWING DIFFERENT RETINA LAYERS Credits: Divyadrishti Lab, IIT Roorkee

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thing for a billion years without complaining. It’s not a human that grows weary of doing the same task for more than a day. That’s what truly makes it a machine, right? A neural network has the capability to see several images of an OCT scan and learn how a healthy eye differs from an infected one. It becomes so capable that it can differentiate a tumor from a normal eye on a single pixel basis! A doctor might improperly classify a fluid pocket in the retina or loose retinal layers as a tumor but a neural network will not.

Preprocessing: The process begins by taking an OCT-B scan as shown above and breaking it into several layers namely, photoreceptors, neurons, and choroid. This is a challenging task as there is a lot of noise in the data and manual annotation of data is tiresome. A few attempts are being made to make this process automated.

One such attempt is being done by Divyadrishti Lab at IIT Roorkee. The team has used several convolution neural networks to self annotate the image and extract all features and artifacts from it.

OCT IMAGE AFTER PREPROCESSING SHOWINGDIFFERENT LABELLED LAYERS Credits: Divyadrishti Lab, IIT Roorkee

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The automation of this process will lead to a revolutionary change in the learning process by decreasing the time taken 100 folds. After the data is annotated, it is converted into the desired format as the training model demands. It can in the form of pixel values or greyscale values.

Training Phase: The real task of making your model learn begins! The data is labeled as healthy and infected and fed to the model. The model like a naïve child starts learning the true difference at single-pixel levels. It is made to learn the data repeatedly and then used to predict unseen OCT scans. The process is truly magical if looked through the perspective of the network. The whole process is done using various libraries as Scikit-Learn and Tensor Flow which are toolkits to work on machine learning projects. We don’t need to worry about the internal working about the model right now. What we really want is our model to predict with maximum true positives.

“It doesn’t matter what algorithm or toolkit you use. The most important task is to structure your learning towards detecting the retinal layers, even though the accuracy is low.” - Team at Divyadrishti Lab, IIT Roorkee

Deployment Phase: After the desired accuracy is attained the model is directly implemented into an OCT graphing machine.The machine automatically tells whether the scan has a tumor or not with a definite quantifiable assurance. This leads to a better-secured approach to this difficult task of identifying the tumor. The Big-AI dream has always been about automating everything. But its heart truly lies at the intensive problems as identifying a tumor. What may seem simple at first has several layers of complexities attached to it. Solving such a problem truly enlightens us about this complex structure of healthcare. The aim of mankind has always been to be better at what it does. And AI is nothing but an ally to us at what we do! 44

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Vernacular.ai :

AI-based voice automation platform A Series-A funded startup founded by IIT Roorkee Alumni, an AI-First SaaS business that is driven with a mission to become the leading voice automation/AI platform in the world.

Written by AYISHIK DAS Designed by KEERTI CHARANTIMATH

e live in a post-COVID-19 world where physical distancing, work from home, and contactless interactions have become the new norm. Thus, there have been many innovations and focus on voice automation. One company working in voice AI solutions is Vernacular.ai, founded by IIT Roorkee alumnus. The co-founders are Akshay Deshraj, Prateek Gupta, Manoj Sarda, and Sourabh Gupta. Vernacular.ai is an AI-First SaaS business aimed to enhance customer experience through intelligent voice conversations. Their vision is to build a unique voice AI platform, which would enable a multi-lingual audience to engage with interfaces online. They have picked call centers as the first vertical to go after. This is due to the fact call centers are traditionally places where there are high costs, high attrition rates, and for the end-users IVRs are frustrating, and wait times are irritating.

“Large enterprises in India will be spending $30 million – $50 million per year on call centers. But I would say getting a cab in five minutes is much higher than getting connected to a call center in five minutes, and this is where our product VIVA comes in and solves not just costs but also customer satisfaction.” Co-founder Sourabh Gupta said this in an interview with Telegraph. They have developed two major products: Virtual Intelligent Voice Assistant (VIVA) and Vernacular Automated Speech Recognition (VASR).

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VIVA VIVA helps accelerate engagement strategy and utilizes cutting edge speech recognition and Natural Language Understanding (NLU) technology. It is an intelligent and multilingual platform that can help automate 80% of call centre operations. VIVA has been trained by 1,00,00+ hours of speech data, and it keeps learning as its being used. It has been deployed to help enterprises boost customer stickiness and loyalty through a deep understanding of the customer’s context and intent.

recognizes 10 Indian languages to support the enterprise user base. VASR builds the foundations of our conversational AI platform. “Vernacular Automated Speech Recognition that truly listens and analyses.” It raises flags in our conversation in addition to spot keywords and generating insights. VASR also supports context and sentiment analysis. Many of the features are the same as VIVA, like streaming and synchronous cognition, content and intent identification, and speech characteristics.

Technology behind Vernacular.ai

VIVA support 10 Indian languages and has features like streaming and synchronous cognition and content and intent identification. Streaming and synchronous cognition analyses conversations for both online and offline cases. Content and intent identification allow VIVA to identify the user’s speech input’s real meaning as per the domain. Hyperpersonalization of calls is possible by its speech characteristic feature, which understands users.

We have seen the features and customizations possible by VIVA and VARS, but it is possible because of the technology. The three significant challenges in making VIVA and VARS incorporate the style factor in conversation, answering tough but essential questions, and smooth interaction even with external problems. To solve these problems, Vernacular. ai has developed technology, namely - Idiolect layer, Contextual conversation clustering (C3), and Conversation Monitoring.

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Idiolect layer :

VASR enables enterprises to convert audio to text by applying powerful neural network models in an easy-to-use Application Programming Interface (API). The API

Successful human conversations go beyond context. Both understanding and articulation are essential and must be incorporated. The idiolect layer plays a role in this.

TEAM VERNACULAR.AI Source: yourstory.com

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Idiolect is formally explained as ‘speech habits peculiar to a particular person.’ While communicating, they use the understanding of these habits and patterns to derive an appropriate style along with content, which then goes out as a response.

Conversation Monitoring :

While communicating, they use the understanding of these habits and patterns VIVA’s engine understands various aspects of a caller’s idiolect in real-time, including many named factors like age, gender, etc. and latent factors and the standard lexical components needed for regular Spoken Language Understanding (SLU). This understanding, along with the semantics collected from SLU, helps in generating a response.

Customer interactions aren’t always smooth because of multiple factors such as background noise, insufficient knowledge of the conversational agent, a hard to understand the accent, etc. Thus, it is important to monitor to keep an eye on these conversational agents. Monitoring is usually done manually in call centres by auditing/quality teams. To automate this process, conversation monitoring comes in handy.

Contextual conversation clustering (C3) :

The technology works by continuously monitoring an ongoing call and classifying it as a good or bad conversation based on over 70 conversation-level features. It generates a score for a call where a score of 0 means the call went pretty bad, and a score of 100 means the call went pretty well.

A variety of challenging but essential questions are asked in call centres. The response is usually compared manually by auditing/quality teams. This problem is solved using C3. It scans through unlimited calls and makes groups of requests based on over 40 parameters. These groups help identify hidden conversational patterns in a user-bot session. The identified patterns are then used to generate situational reports of why a particular pattern is happening, provide an actionable suggestion to

a human-agent in case of a transfer, and power the conversation monitoring technology. Even after transferring, C3 learns from the human agent’s interactions.

Identifying bad conversations is crucial since disappointing customer service may hamper customer loyalty and impact the brand image. This technology helps to catch these instances early on before it can make a significant impact and helps to ensure that customers have the best experience and the voice-bot is getting the maximum possible satisfaction score.

VASR AND VIVA THE PRODUCTS OF VERNACULAR.AI Source: vernacular.ai

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Which industry is Vernacular.ai functioning? Vernacular.ai has shown its presence in many industries, namely banking and insurance, food and beverage, travel and hospitality, DTH, internet service providers, and even online gaming. They create industry-specific customized solutions with their integrated voice & conversational intelligence into products through an independent platform that is always learning. Their technology provides numerous benefits in these industries by increasing workers’ productivity and preventing the loss of customers due to the long wait for customer service. It reduces the number of calls received in call centres, thus reduces operating costs. It stops interested customers from going to other providers by reducing delays in their calls. Vernacular.ai’s self-efficient, 24x7 service increases return on investment by freeing up agents focusing on converting high-quality leads. Customer experience is improved by proactively guiding them throughout the call and helping improve operations through customer feedback. The demo of their service can be heard on their website: https://vernacular.ai. With their recent Series A funding, Vernacular. ai is planning to expand to newer markets in the US and Southeast Asia and develop their R&D. They are also planning to double their team to help drive their goal of becoming the leading voice automation/AI platform in the world. “Voice automation has taken center stage for customer enagement for enterprises. This is also a time when voiceprocessing technologies need to evolve and communicate better than ever before. COVID-19 has accelerated this shift from touch to talk.” Words said by the co-founder in an interview with Telegraph.

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An Assistive Communication Device for the Differently Abled

An inexpensive communication system designed by IIT Palakkad students uses electrooculography to convert eye movements into text! .

Written by NAREN LOGANATHAN Designed by KEERTI CHARANTIMATH

Introduction

ith the help of the technological advancements we have made over the last couple of decades, the quality of life for people battling disabilities and impairments has increased substantially. There are a plethora of assistive devices and software available to the differently abled. However, a majority of these tools are only available at a steep price, and this acts as a deterrent for would-be users from economically weak sections. This is especially the case for assistive communication systems, which are designed to enable (or in milder cases, enhance) a userâ€™s ability to communicate with other people. Such systems are often provided to individuals with speech impairments, or extreme mobility issues (as a consequence of motor neurone disease, paralysis, stroke, etc.). They are expensive, and at the same time, very necessary. Without assistive communication systems, disabled persons incapable of speech and conventional forms of communication would find it nearly impossible to relay their needs and thoughts to their caregivers or others. There are multiple efforts being made towards reducing the costs of these devices. One such endeavour undertaken by IIT Palakkad students Vishal Choudhari and Anjali Agarwal has shown some promise. Under the guidance and mentorship of Professor Vinod A. Prasad, they developed an innovative, low-cost assistive communication device targeted at people suffering from paralysis and speech impairments.

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How does this device work?

The EOG technique : There is a resting electrostatic potential between the cornea (the clear, front part of the eye) and the foveal sclera (which is a layer of blood vessels lining the back of the eye). Simply put, you can think of the eye as a small battery of sorts, with a positive terminal at the front (cornea) and a negative terminal at the back.

Overview : The core functioning of the device revolves around electrooculography (EOG). This technology — as the name probably suggests — is used to capture eye movements in the form of electrical signals, which can then be modified and further analysed using software. Anjali and Vishal used the captured eye movements of the user to operate a virtual keyboard displayed to the user on a monitor.

Electrooculography specifically deals with measuring this potential difference, which is formally termed as corneal-retinal standing potential. Repeated measurements of this potential generate an analog signal, called an electrooculogram. This potential can be used as a measure of the position of the eye at a particular instant.

The device particularly looks out for saccadic movement of the user’s eyes, which refers to the rapid and simultaneous movements of both eyes. Saccadic movements also involve two or more changes of the individual’s visual gaze in the same general direction.

These potentials are measured with the help of multiple electrodes. The team used two pairs of electrodes, and one extra electrode was grounded to zero for reference. One pair of electrodes was used to measure vertical eye movement. The two electrodes were placed above and below an eye (on the skin). The other pair was used to track horizontal eye movement. In this case, the electrodes were placed on the left and right. This collection of electrodes acquired signals from muscles surrounding the eyes to generate an electrooculogram.

THE DEVICE IN ACTION Source: youtube.com/VishalChoudhari

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Further processing and additional steps : The resulting electrooculogram had to be amplified, shifted and filtered. This was accomplished by passing the output of the electrodes through a signal conditioning circuit. Further, the modified signal needed to be digitised and sampled, and this was done using the analog to digital converters (ADCs) of an Arduino board. The information from the signal was then classified in real time using MATLAB. Based on the result, a particular key would be ‘pressed’ on the virtual keyboard — ideally the key which the user wanted to select. Vishal and Anjali found out that tweaking the signal processing algorithm on a case-by-case basis improved the accuracy of this classifier.

Case Study The team demonstrated the functionality of the device on a 63-year-old patient affected by a combination of progressive supranuclear palsy and multiple system atrophy. The paralysed and speech-impaired patient was only capable of blinking, feeble eye movements and minute motions of her right forefinger. The team initially tried to use EOG techniques to capture the eye movements of the patient, but due to weak muscular activity, the signals acquired were not sufficiently strong. Eventually, they managed to translate the motion of the patient’s finger into signals for selecting letters on the virtual keyboard. Text-to-speech functionality was also implemented afterwards. This indigenous assistive technology device developed by the IIT Palakkad students costed approximately 1,500 rupees in total, which is a minuscule amount in comparison to the prices of assistive communication devices currently in the market (which are often imported). Efforts like these indicate that it is possible to manufacture assistive devices at a low cost. This will significantly relieve the financial burdens on the differently abled arising due to their special needs. The future definitely appears to be brighter for them. Source: unsplash 55