Invention and Innovation: Changing Dynamics of the S&T Initiatives

Professor Santanu Chaudhury

Director's Column

---

 

1.0 Introduction 

Science and technology initiatives over the years have been projected as national drivers for economic growth. In India major investments in the Science and technology sector have come through public funding. The proposed STI policy 2021 also emphatically states, “Science, technology and innovation (STI) are the key drivers for economic growth and human development.”.

If we look at the past, the decade of 2010 to 2020 was declared as the ‘Decade of Innovation’. It was expected that this would lead to creation of innovative institutions and mindsets for national progress. In 2013, government formulated Science, Technology, and Innovation Policy 2013 (not just S&T policy which was the past practice.) The key features of this policy were to build S&T -based innovation ecosystem in the country. In addition, it was expected that private sectors will increase investments in R&D. In contrast to the past scenario, the proposed STI policy 2021 has emerged through a challenging scenario of COVID pandemic which brought S&T and researchers to the national focus. The pandemic challenge has highlighted the need for long term fundamental research, mission mode outcome-oriented projects and a powerful mechanism for delivery of research outputs for benefit of all. These initiatives cannot operate in isolation. Appropriate political will and financial commitments are essential for such ecosystems to emerge. We, academicians and researchers have critical role. At times we need to make difficult decisive choices, which may not be obvious, but necessary to contribute meaningfully and remain relevant. Science and innovation can only ensure sustainability of the humanity against known and unknown global threats.

2.0 Science and Invention 

Science is pursuit and application of knowledge for understanding nature and social world through systematic unbiased observations, experimentations and evidence based reasoning. (This is how Science Council of UK defines science which provides a comprehensive way of looking at both social and natural sciences). Science represents the spirit of inquiry and discovery. Questioning is the basis for evolution of science. Science tells not to believe anything no matter what be its source until and unless it is consistent with evidences and reason. This essence of science gets epitomised in the motto of “The Royal Society” - 'Nullius in verba' meaning 'take nobody's word for it'. It expresses the determination of the scientific community to withstand attempts of unscientific domination and to “verify all statements by an appeal to facts determined by experiments”[2]. Science fundamentally leads humanity to new knowledge which are basic principles of natural and social world until and unless those are proven wrong and replaced by new knowledge.

Engineers make use of scientific knowledge to design processes, structures and equipment meeting a variety of human needs. Each engineering discipline is founded upon a set of theories derived from core science. Basic or fundamental research in engineering is the development of such theories through attempts to establish a basis for empirical observations and develop new methods for engineering analysis. Research aims to advance state of the art by framing newer techniques and causal basis for design of engineering systems. Using these principles and methodologies solutions ranging from tangible artefacts to complex socio-technical systems are delivered by engineers.

Fundamental research leads to discovery of new principles which helps us to understand natural and social world. To discover is to bring something into existence that was not known. Discovery may be accidental and need not be an outcome of a structure process. A discovery is illumination of a pre-existing thing, such as the discovery of a natural law. Thus, discoveries in that sense are limited to what is already here or to the world of the possible. Discovery adds to the body of human knowledge and explains some unresolved problems. Creativity in problem solving leads to discovery. Quest for solving problems to make human life better, to satisfy human aspirations, leads to inventions. Inventions, such as transistors or cellular communication, have uniqueness - they are new to the world. Inventions emerge through a process of exploitation of natural phenomenon/laws discovered by scientists to synthesize something new and unique.

Ever since the prehistoric stone tools were invented, humans have lived in a world shaped by inventions. Paleolithic stone weapons made hunting possible. The printing press, introduced in the 15th century, once and for all democratized the process of the expression of thoughts. The typewriter, which came to market in 1870s, was instrumental in freeing women from housework in the western world and changing their social status for good. Internet and cellular phones have completely changed the way we interact with each other. From ideation to experimental validation to conversion into a product for general/popular use is, however, a long cycle.

There is a continuous spectrum of scientific activity linked with the process of discovery, invention and productization. At one end of the spectrum is basic scientific research; at the other end, engineering development. Moving from the pure-science end of the spectrum to the engineering end, the goals become more closely defined and more closely tied to the demand of the solution of a specific practical problem or the creation of a practical product. Inventions, in this context, can be divided into two broad classes: fundamental inventions and incremental improvements on existing technologies. It is clear that discovery and basic inventions generate fundamental knowledge and know-how to solve problems. Investments in this invention life cycle are not expected to yield products but generate knowledge to make a product. An engineering researcher is more likely to be involved in invention rather than scientific discovery. Discovery and invention life cycles effectively convert investment to intangible knowledge for humanity.

3.0 Moonshots  

Throughout the course of history a number of disruptive scientific or technological changes have happened only when people have ventured into projects with wildly ambitious goals, may be fraught with possibilities of failure. A moonshot project typically has ambitious, exploratory goals expected to produce ground breaking results. Normally there are no expectations of near term achievements. These projects also have a very high risk of failure.

The idea of moonshot projects has an interesting genesis. In 1962, the then US president, John F. Kennedy in his speech at Rice University, disclosed his dream to put a person on the moon by the end of the decade. Audacity of this challenge not only inspired motivation and passion of the scientific community but also public imagination. Public support and political will to take the project forward despite setbacks were exceptional. A project with a smaller goal possibly could have never triggered this level of commitment.

Today, Japan has well organised Moonshot Research and Development programmes that aims to create disruptive interventions to solve issues facing future society by supporting projects which are much more than just extensions of conventional technologies. We can look at some examples:

1.	Realization of sustainable medical and nursing care systems to prevent and overcome major diseases by 2040, for everyone to enjoy life without health anxiety until 100 years old. This has a number of moonshot goals
	(i).	Realization of a society where everyone can prevent diseases spontaneously in daily life
	(ii).	Realization of a medical network accessible for anyone from anywhere in the world.
	(iii).	Realization of drastic improvement of QoL without feeling load (realization of an inclusive society without health disparity)

2.	Realization of a society in which human beings can be free from limitations of body, brain, space, and time by 2050.Moonshot goals of this project are
	(i).	The Realization of an Avatar-Symbiotic Society where Everyone can Perform Active Roles without Constraint
	(ii).	Liberation from Biological Limitations via Physical, Cognitive and Perceptual Augmentation
	(iii).	Cybernetic Avatar Technology and Social System Design for Harmonious Co-experience and Collective Ability

Outside Japan, the European Union, the United States, and China aim to introduce disruptive innovation by announcing their ambitious moonshots and setting their goals for resolving difficult issues in a manner that was unthinkable in the past. Research institutions and universities have also initiated moonshot projects. MIT launched Intelligence Quest in January 2018. It has two parts – Core and Bridge. The key output of the “Core” will be machine-learning algorithms which can advance understanding of human intelligence with insights from computer science. The second entity – “the Bridge” is positioned to explore application of MIT discoveries in natural and artificial intelligence to all disciplines. Key questions being pursued in this initiative, in words of MIT president – ““How does human intelligence work, in engineering terms? And how can we use that deep grasp of human intelligence to build wiser and more useful machines, to the benefit of society?”. An active industry player pursuing moonshots is X - formerly Google X, now a separate subsidiary of its parent company Alphabet.

The dream of the moonshot to put human being on moon was a one-time engineering feat. Today’s Moonshots would require a new set of technologies to be invented and then integrated for the benefit of humanity. Present challenges, like medical care for all or transporting billions of people, are also fundamentally different as scales involved here are different. It is not just more challenging but qualitatively different. Engineering devices or systems, that are both effective and affordable at a global scale for billions, will be difficult and will be a problem of different kind.

Moonshot thinking is pursuing things that appear impossible, but if achieved has potential to redefine the future of humanity. Moonshots have multi-dimensional implications - it can be in any field, not necessarily only in science and technology. These are initiatives which would appear today impossible science fiction like but if successful will affect million or billions of people. Getting into moonshot thinking requires an spirit of adventure, ability to imagine with audacity, love failures as opportunity to learn, willingness to work in multi-disciplinary teams. Even there are games to get initiated into moonshot thinking (https://x.company/moonshots-game/setup). However, all moonshots are big budget items – risk investments with potential of huge return or huge loss.

 4.0 Innovation 

Encyclopedia Britannica defines innovation in the following way: “Innovation, the creation of a new way of doing something, whether the enterprise is concrete (e.g., the development of a new product) or abstract (e.g., the development of a new philosophy or theoretical approach to a problem).” While invention requires the creation of new ideas and processes, innovation requires implementation of the invention. Innovation targets to derive a positive outcome from the invention.

Transformation from invention to innovation is not straight forward. There are questions, challenges, trade-offs and financial implications. Key issues are:

(i).	Solution Readiness: How can one generate a solution from an invention? what problem is the solution ready to solve? When is a solution really ready for the market?
(ii).	Production Readiness: How can one build/manufacture a single instance of a new solution? 10? 10,000? What sort of facility is required for production? And how can one fund this?
(iii).	Team Readiness: What type and size of team is needed? How can one build, prepare, and manage that team? And what sort of characteristics is expected of the team?
(iv).	Stakeholder Readiness: Which stakeholders are most important (e.g. regulators, investors) and how can you best manage them? How does one engage them in the solution readiness activities to ensure that they too are ready?

An invention may be feasible and novel in an experimental set-up. However, utility of the invention can only be established if it addresses economic and operational constraints of the target application in the context of a market. Creating a market value for an invention requires design of appropriate techniques and technologies to transform the invention to a marketable solution. This productization process requires a precise understanding of the intended market and the requirements of the customers. In many cases, artistic creativity in design of the solution enhances the value of innovation. Following is interesting excerpt: “We’re all searching for the next iMac or VW Beetle—any worthwhile innovation that captures the public’s imagination and strengthens the company’s brand (Excerpt From: Tom Kelley. “The Art of Innovation”).

5.0 Changing Dynamics

Innovation requires knowledge and strategies which go beyond the realm of traditional academic research. Discovery and invention consumes financial resources to generate knowledge. Innovation transforms knowledge to financial assets. Innovation ecosystem is critical and requires careful nurturing in the academic system. Start-ups provide the pathway for academic knowledge production system to get engaged actively with the innovation ecosystem and financially exploit discovery and inventions. Consequently, we find globally, a strong support system for start-ups and technology parks in the academic institutions. Incubators nurture start-ups for generating tangible financial value for institutional discoveries and inventions. On the other hand technology parks are expected to house matured industries to provide inputs for use inspired research to the academic ecosystem. The application scenarios and problems faced in delivery of solutions for practical problems can lead to generation of knowledge by the academic ecosystem which has value for industry.

Presence of these essential enablers for taking research to the field are expected to offer academia new benchmarks to evaluate their research. Not just citations or high impact publications but patents of commercial value, start-ups promoted, consultancy for use inspired research and finally marketable outcome of research have become indicators of contributions by a faculty. Obviously, in today’s academic ecosystem a faculty is not just knowledge producer but also knowledge consumer for value generation along with imparting education to the students. Even education for the students are not just acquisition of analytical skills to solve problems but also to acquire the ability to identify problems to create knowledge and consume knowledge for creation of value through start-ups’s or similar ventures.

Start-up’s from a practical perspective begin their journey typically somewhere in the invention life cycle and not typically in the discovery phase. An academic research provides in many cases the core inspirational input for innovation. However, its journey to become a solution requires a variety of investigations for putting in place auxiliary components required for creating value out of the solution. In many cases, start-ups engage themselves in those aspects of inventions in collaboration with faculty mentors. However, the most important contribution of start-ups are their effort in transforming knowledge into a marketable prototype through a process of refining the output so that performance parameters are adapted to meet market demands, so that the solution has repeatable, reliable and consistent performance in different operational situations and designing an unencumbered process for manufacturing the solution. Subsequent scaling up and productization including refinement of usability aspects are another stage in the process of innovation. Typically start-up’s by this stage attracts commercial funding which then are clear indicators of commercial value of the innovation. Whether, this will be a successful product or not depends number of other factors including market dynamics.

Dynamics of research ecosystem today expects a close synergy between academic research and innovation process. Policy for funding research, in many cases, is getting oriented towards estimating return of the investment in terms of tangible value creation along with intangible knowledge outcome. Academicians are therefore, expected to pursue research projects, may be in association with start-up’s so that there is a linkage with innovation ecosystem for possible value creation. We need to position basic and fundamental research and use driven research in a new way.

Solutions of critical problems we are facing today in Climate Change, Energy, Food, Water, Health and others require long term fundamental moonshot efforts. For example an Energy moonshot can be: To find a energy source that is cheaper than today’s hydrocarbon energy, that has zero (carbon dioxide) emissions, and that is as reliable as today’s overall energy system. These Moonshots require miraculous discoveries. These discoveries frequently do not come from extensions of known science and technology but from foundational conceptual revolutions. These also do not emerge from vacuum. There is a dynamic interaction between scientific insights and the technologies, financing, engineering, as well as the standards, regulations, and policies that complement, enable, and develop them. They can form the nucleus for a dedicated knowledge and value producing ecosystem with a long term possibility. But they are not goal directed research.

However, the ability to perceive moonshots requires intellectual attributes of a different kind. Thinking about moonshots is an exercise in logical imagination – generating novel problems which can have long term attention of research groups. Some of the sub-problems emerging out of this exercise can be pursued with limited funding but can have substantial impact if they can navigate the discovery-invention-innovation life cycle to reach end-users.

Basic disruptive research is neither divorced from all technological and practical concerns, nor just concerned with mere practical necessity, characterised by rather unpredictability. There has to be dynamic interaction between domains of science and technology, between foundational research and commercial research. We can imagine a 2D space. One of the two dimensions will represent utility - utility in terms of the degree to which the pursuit is curiosity driven and the other dimension can represent the degree to which it is necessity-driven and viable. In this representation the search for extra-terrestrial life belongs to the extreme corner of purely “I’m curious” and have “no idea” how useful the answer is. Any scientific discovery and invention can be placed around in this space as all effort to create something disruptive today is a combination of discovery and invention and not just discovery followed by invention along a linear path.

6.0 Conclusions 

All these are clear indicators of changing times and changing expectations. It is always a challenge to get transformed with new demands. However, success visits an institution when it can transform itself with time and evolve with changes and more importantly can define the changes.

 

---

Editorial

Shankar Manoharan

Editorial

---

The futurologist Alvin Toffler said “Yesterday violence was power, today wealth is power and tomorrow knowledge will be power”. Dr. R. Chidambaram, the Chairman, Board of Governors of IIT Jodhpur frequently paraphrases Toffler’s words to say “Those who have the ability to transform knowledge into technology have power”. Today, as the world continues to battle an invisible enemy, it is scientific knowledge, translated into technology that has given us power over this virus. Right from identifying new diagnostic / treatment modalities, the development of vaccines, to the genome sequencing of new variants to mitigate their spread, science and technology have been central to our advance against COVID-19. Our advances against COVID-19 have not been without losses. The world has lost innumerable frontline warriors and medical professionals to this onslaught. Along with these immeasurable losses, we also remember Dr. Vandana Sharma, a young, dynamic faculty member from the IIT Jodhpur family, who championed IIT Jodhpur’s cause of effective online education and Mr. Pawan Meena, an Alumnus, from the Class of 2014 of B.Tech. (CSE). Their loss is irreplaceable to the Institute community. Despite the challenging times, IIT Jodhpur remains committed to grow in leaps and bounds to meet the technology needs of India.

As you will recall, the 6th Convocation of IIT Jodhpur was held on December 6, 2020 in an immersive 360-degree mixed-reality environment. Professor Geoffrey Hinton, Turing Award Winner and Emeritus Distinguished Professor at the Department of Computer Science, University of Toronto, Canada graced the occasion and delivered the Convocation address. The full transcript of his address is included in this issue. I am sure that you will find it illuminating. IIT Jodhpur remains committed to strengthening its relationship with industry stakeholders. To this effect, the annual Industry Day 2021 was organized virtually on March 12-13, 2021. The main themes of Industry Day 2021 were green technology, smart infrastructure, medical technology and drug discovery.

In the In Focus section of this issue, is an article by Dr. Heena Rathore, an Alumnus of IIT Jodhpur (Class of 2016 of Ph.D. in Information & Communication Technologies), currently serving as an Assistant Professor at the University of Texas, San Antonio, on neuroscience-inspired approaches for machine learning. Also in this section, Dr. Alok Ranjan shares his perspectives on how the current situation is a wakeup call for strengthening the health system in India. You will also find several other interesting snippets of ongoing research at IIT Jodhpur in this issue of TechScape. These interdisciplinary innovations can have several applications and create a profound social impact. Just to give a flavour for the diversity of research areas covered in this issue, Dr. Prasenjit Sarkar takes us through the process for development of human tissue in laboratory bioreactors, while Dr. Preeti Tiwari explores more fundamental questions on how social entrepreneurial intentions are formed. Dr. Rima Bhattacharya introduces us to Asian American literature and Dr. Jayant Kumar Mohanta discusses the design of spatial robots for lower-limb rehabilitation. Such diversity is and will always be our strength as TechScape strives to make knowledge available across disciplines. We are confident that you will enjoy reading this issue and we thank the contributing authors for making every issue of TechScape an experience in itself for you, the reader.

---

How did people perceive novel coronavirus threat during early stages of pandemic? An analysis of data from Google Trends and Johns Hopkins Coronavirus Resource Centre.

Siddarth Srivastava

News & Views

---

World health organization (WHO) declared the outbreak of novel coronavirus (SARS-CoV-2) as a public health emergency of international concern (PHEIC) on 30th Jan 2020. This led to a worldwide increase in Google search of the term “coronavirus” (Fig Siddharth_1). This analysis focussed on five countries, India, United States, Germany, Italy and South Korea for their Google search behaviour during the initial stages of COVID19 pandemic. These five countries were selected based on their differences in demography, infection and mortality rates and strategies utilized to combat COVID 19 pandemic.

Google Trends data suggested that in each of the five countries, an increase in coronavirus patient numbers did not lead to proportionate increase in “coronavirus” word Google search (Fig Siddharth_2.1-Siddharth_2.5). Interestingly, in these five countries, “coronavirus” Google search rapidly increased only when the governments (GOVTs) announced “lockdown” or equivalent. Thus, the perception of novel coronavirus as a threat seemed to be linked to GOVTs announcement of lockdown rather than to increasing numbers of coronavirus patients. Various forms of “lockdown” resulted in a combination of following conditions (1) confinement of people within their homes (2) closure of schools and day care (3) ban on meetings of more than 50 people (4) closing of international or inter-state borders. In each of the five countries, increased “coronavirus” Google search lasted for a few days after the announcement of lockdown. However, subsequently the “coronavirus” search dipped, even when numbers of coronavirus patients steadily rose (Fig Siddharth_2.1-Siddharth_2.5). Thus, the behaviour of increased “coronavirus” Google search did not correlate with the rate of increase of coronavirus patients.

Interestingly, on the day and on a few subsequent days after the lockdown announcement, while “coronavirus” Google search significantly increased, Google search for terms such as “grocery”, “transport”, “YouTube” and “lockdown” did not show corresponding rise (Fig Siddharth_3).

Thus, announcement of lockdown (or equivalent) and not increasing numbers of coronavirus patients acted as a trigger for people to google search “coronavirus”. Coronavirus posed a threat yet “unknown” to common people hence instead of fear, it elicited a response of “anxiety”. While fear is human response to specific, observable danger, anxiety is seen as diffused, unfocused, objectless, future-oriented fear which is elicited by an unknown danger.The data showed that rather than perceiving rising numbers of coronavirus infected patients as a threat, a GOVT announcement of lockdown or equivalent seemed to make people more aware of the magnitude of the threat and they tried to gather more information on coronavirus over the internet. The day lockdown was announced in the five countries of interest, “coronavirus” Google search was significantly more than “grocery” and “transport”. This was puzzling as during a lockdown restricted availability of grocery and transport posed an immediate threat. This could be because coronavirus posed a novel threat compared to the restrictions on grocery and transport. Thus, during a pandemic, the day a GOVT announces lockdown or equivalent, it would also be the ideal time to provide citizens with the best information and resources about the threat. Also, GOVTs can be transparent with the information on numbers of infected patients as it does not seem to trigger anxiety which was evident from “coronavirus” google search pattern.

Methodology:
1. Google Trends (https://trends.google.com/trends/?geo=US) was used to analyse Google searches of terms "coronavirus", “grocery”, “transport”, “YouTube” and “lockdown” in various countries listed here. Google search numbers represent search interest relative to the highest point on the chart for the given region and time. A value of 100 is the peak popularity for the term. A value of 50 means that the term is half as popular. A score of 0 means there was not enough data for this term.
2. Johns Hopkins coronavirus resource centre (https://coronavirus.jhu.edu/map.html) was used to count confirmed coronavirus infected people on a given date, in countries studied here.

Reinventing Ayurveda for the 21st Century

Bala Pesala and Mitali Mukerji

News & Views

---

Context
Human life span has been continuously increasing over the past 100 years with the innovations in modern medicine and better availability of health care services. The disease burden has been shifting slowly from infectious diseases to non-communicable diseases. In spite of the increased life span, the disease-free life, quantified using Years Lived with Disability (YLDs), has been reducing over the years. Non-communicable diseases such as diabetes, cancer, cardiovascular diseases have high YLD scores thus causing significant health care burden. While modern medicine has seen success in treating the diseases, it has largely been a “one size fits all” approach and reactive care. A paradigm shift is occurring from a reactive healthcare model to Predictive, Preventive, Personalized, and Participatory (P4) medicine for a holistic and proactive management of health across the entire lifespan in the 21st Century. In this future medicine, health and diseases are seen as a continuous spectrum rather than two distinct points.

Potential of Ayurveda in Future Integrative Medicine
Ayurveda science, an ancient Indian approach of holistic medicine, has evolved over the last two thousand years, that is still contemporary and encompasses all aspects of P4 medicine, has great potential for promoting a healthy lifestyle and curing of diseases with reduced side effects [1,2]. Highly personalized nature of treatment is inbuilt into Ayurveda where the baseline homeostatic state of the patient, “Prakriti”, is understood first before diagnosis of the disease and subsequent therapeutic recommendations. Prakriti also determines the genetic predisposition of a patient to various diseases and hence Ayurveda based preventive diet, lifestyle, medicines, panchakarma can be followed to maintain a healthy lifestyle. There have been several peer reviewed studies which clearly show the biochemical [3], genomic [4], metagenomic [5,6] basis of Ayurveda in the last 10 years and its potential in stratified medicine. Interestingly, the highly personalized nature of Ayurveda treatment is also evident from the multiple subtypes described for each modern disease. For example, diabetes in broadly classified as “Type 1” and “Type 2” diabetes in the modern medicine while Ayurveda describes >15 sub-types of diabetes depending on the expression of clinical symptoms and the treatment is tailored as per the patient’s prakriti and the disease sub-type. Further, the pharmacopeia of traditional Ayurveda medicines is vast and has significant potential to compliment the modern medicine to achieve “Integrative and personalized medicine” which also gives multiple treatment options to the patients especially suffering from various chronic metabolic, autoimmune and gastric disorders.

Path forward for Mainstreaming and Globalizing Ayurveda
Ayurveda has great potential to realize the next generation of P5 medicine: Personalized, Preventive, Predictive, Participatory and Promotive. However, for Ayurveda to transform from an alternative medicine to mainstream medicine, rigorous evidence-based approach in both diagnostics and therapeutics is the need of the hour. To start objectivizing and quantifying the beneficial aspects of Ayurveda for its integration with mainstream medicine, one needs to start collecting, structuring, and organizing Ayurveda knowledge both from the classical texts and clinical studies over the past century, without compromising the key aspects of personalization and heterogeneity in disease management. Recently, there has been a big data analytics study analysing >350,000 subjects data undergoing Ayurveda treatment which provide key insights into the target population, diseases for which it could be a preferred choice and treatment efficacy [7]. Ontological frameworks routinely used in modern medicine also need to be developed both for structuring Ayurveda clinical knowledge as well as understanding the molecular pathways and scientific basis of multi-drug Ayurveda medicine.

Ayurveda diagnostics can greatly benefit from data driven “Phenomics” approaches where in the personalized “Prakriti” is quantified using a combination of computer vision, IoT sensors and machine learning for capturing key anatomic, physical, physiological and psychological parameters (see fig. 1). Further, “Vikriti” or disease including its sub-type can be diagnosed using a conversational AI based differential diagnosis combined with “digital pulse diagnosis”.

In addition, explainable AI will play a key role in providing trusted assist to Ayurveda doctors and clinicians. Companies such as Babylon, DemDx, have built AI driven differential diagnosis engines for modern medicine which have the potential to reduce the health care costs, unnecessary hospital visits and remote teleconsultations at the comfort of the home. Similar initiatives in Ayurveda and other traditional systems are the need of the hour.

Currently, the Ayurveda industry is valued at more than 10 billion USD, growing at a Compound Annual Growth Rate (CAGR) of >16%. For the industry to grow exponentially and reach a >100 billion market value in the next 20 years, more rigorous evidence-based approaches in Ayurveda therapeutics are needed. Due to the highly personalized nature of Ayurveda, compared to randomized control trials, patient specific longitudinal tracking of clinical, biochemical and multi-omics parameters would be more suitable to evaluate the drug efficacy. In addition, standards for Ayurveda drug efficacy evaluation and potential toxicity, side effects need to be clearly established. Another area that is ripe for innovation is discovery of bio-actives in Ayurveda drugs and repurposing of Ayurveda drugs to the emerging infectious and non-communicable diseases. Recently, a landmark study has been published, which employed transcriptomics and connectome analysis for deeper understanding of the genetic and molecular pathways of Cissampelos pareira, a herbal drug used for the treatment of female hormone disorders and fever [6]. This approach revealed a novel pathway which could be a potential target in dengue viral infection. More such rigorous multi-omic studies are needed to understand the multiple disease curing potential of Ayurveda drugs.

IIT Jodhpur with its excellent track record of designing multi-disciplinary and transdisciplinary programs, has recently initiated the formation of a Transdisciplinary Centre of Excellence in Integrative Precision Health. As a part of this, an AyurTech Centre of Excellence in collaboration with the Dr. Sarvepalli Radhakrishnan Rajasthan Ayurved University, Jodhpur, is planned with the goal of “Establishment of AI driven integrative framework for population and individual risk stratification and early actionable precision health interventions with a special focus on arid regions”. This scientific and data driven approach to Ayurveda diagnostics and therapeutics can achieve evidence based Ayurveda, which will greatly help in globalizing Ayurveda similar to traditional Chinese medicine which has seen higher acceptance and adoption internationally.

References:-

1.	Prasher B, Gibson G, Mukerji M Genomic insights into ayurvedic and western approaches to personalized medicine (2016). J Genet. 2016 Mar;95(1):209-28.
2.	Wallace, Robert Keith. "Ayurgenomics and Modern Medicine." Medicina 56.12 (2020): 661.
3.	Prasher, B., Negi, S., Aggarwal, S., Mandal, A. K., Sethi, T. P., Deshmukh, S. R., ... & Mukerji, M. (2008). Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda. Journal of translational medicine, 6(1), 1-12.
4.	Govindaraj, P., Nizamuddin, S., Sharath, A., Jyothi, V., Rotti, H., Raval, R., ... & Thangaraj, K. (2015). Genome-wide analysis correlates Ayurveda Prakriti. Scientific reports, 5(1), 1-12.
5.	Chauhan NS, Pandey R… Mukerji M, Dash D (2018) Western Indian Rural Gut Microbial Diversity in Extreme Prakriti Endo-Phenotypes Reveals Signature Microbes. Front Microbiol. 2018 Feb 13;9:118.
6.	Jnana, Apoorva, et al. "Prakriti phenotypes as a stratifier of gut microbiome: A new frontier in personalized medicine?." Journal of Ayurveda and Integrative Medicine 11.3 (2020): 360-365.
7.	Singh, Harpreet, et al. "Big data analysis of traditional knowledge-based Ayurveda medicine." Progress in Preventive Medicine 3.5 (2018): e0020.
8.	Haider, M., Dholakia, D., Panwar, A., Garg, P., Gheware, A., Singh, D., ... & Mukerji, M. (2021). Transcriptome analysis and connectivity mapping of Cissampelos pareira L. provides molecular links of ESR1 modulation to viral inhibition. Scientific reports, 11(1), 1-9.

Building a collaborative mindset - an essential ingredient for success in research

Mitali Mukerji

News & Views

---

“In the long history of humankind (and animal kind, too) those who learned to collaborate and improvise most effectively have prevailed.”
― Charles Darwin

I started off as a basic science researcher in the 90s at the Indian Institute of Science, when research was an individual's initiative: a “solo” project. Even if we would develop or deliberate our ideas with fellow colleagues from other laboratories, which in my case did happen extensively, this dialogue was always a conversation, not a formal collaboration. Most laboratories were open to sharing resources or unpublished methods for technical issues. This help generally merited an acknowledgment but seldom authorship, in the ensuing publication. From this basic conditioning, I moved on to genomics sciences which in those days was fast evolving into a research enterprise that involved global collaborations across laboratories. Consequently, this culture became embedded in my own research career and a majority of my projects run in the “collaborative” mode. Having done all my research in India, spanning more than 25 years, in this essay I would like to share my perspective on the key ingredients for sustained collaborations.

Why collaborate?
Broadly, the impact of any research, whether for academic interest, societal benefit, commercial or translational, can be increased manifold via collaborations. However, there are trade-offs in solo vs. collaborative efforts. In solo mode, there is high personal satisfaction and sense of ownership. When the work is in the proof-of-concept stage or fundamental biology space, where the potential is not apparent or quantifiable, it is ideal to initially pursue it in solo mode. If the projects in “solo” mode however are not aligned with the institutional mandate, they are challenging to sustain.

The foremost advantage of collaborations is timing: the ability to go from idea to implementation, without losing out on the prime mover advantage. Since expertise, resources and infrastructures are shared, the projects also become more affordable. A drawback of collaborations carried out to build resources, databases or registries is the lack of immediate academic appeal and their perception as intellectually sterile exercises. Long-term collaborations also generate assets that are useful after the project tenure is complete. I illustrate these points with examples from my career.

I was part of the Indian Genome Variation Consortium which built a comprehensive resource of variations from diverse Indian populations. The first years of the project involved extensive sample collection and genotyping. This baseline catalogue unexpectedly became seminal in many later interesting discoveries, such as the linkage of geoclimatic adaptation (high altitude, salinity, humidity) with human phenotypes and disease, founder mutations and population histories, to name a few from our group. In another instance, we have been studying a group of neuro-degenerative disorders called ataxia with AIIMS New Delhi. Here, over the past 20 years we have built a genetic registry of more than 5000 patient families. A bulk of the time in the initial 10 years (a long time in a student or PIs career) went in genetic diagnosis of ataxia and creating visibility. In those times, it was a challenge to appreciate the potential for future research and equally challenging for researchers to participate in such projects. Fast forward 20 years: this clinical cohort has been crucial to investigate the genetic basis of rare diseases in India, which was not the initial goal of this project. Along with these projects, I still pursued one project in “solo” mode: understanding the role of Alu repeats in genome organisation and function, which has been deeply fulfilling.

How to collaborate?
First, the need for collaboration depends on the domain of the problem that needs to be addressed. For instance, most biological fundamental research can be done solo or with limited collaboration. If the needs are applied, then it might require an expertise of a different discipline for implementation as well as more people of the same discipline for scaling up. If the area of research is translational then one cannot move ahead without collaborations. For instance, our projects in the areas of ataxia disease genomics and Ayurgenomics would have been incomplete without the participation of modern and Ayurveda clinicians, data scientists and public health professionals. The kind of collaboration also depends upon the degree of innovation. For radical innovations there might be a greater need for functional diversity, than for incremental innovations.

A second aspect, which needs consideration during planning of collaborative projects, is the type of setting and infrastructure needs for collaboration. Studies which can be conducted in academic institutions or involve clinical settings/field-work have different requirements for infrastructure, resource and manpower.

A third important consideration is whether the collaboration is anticipated to be long or short term. It is very important to have an open discussion on resource sharing, terms of collaborations and IPR sharing policy at inception. Many times we think it’s too premature to deliberate on these issues but this is important for pre-empting future conflicts.

Fourth, a successful collaboration requires stakeholders, each with well-defined ownership as well as accountability. It is also important to respect the motivations for individual stakeholders. Drivers could be personal incentives such as: more acceptability by peers, awards or monetary benefits. It could also be driven by an organization’s need either for revenue or national as well as global recognition and visibility. Many times a need for societal relevance also could be a key driver. Stakeholders should not have conflict of interests and not get into a competitive position at each other’s expense. The diversity in expertise amongst stakeholders ensures this as it can provide a scope for independent visibility and recognition amongst peers. For example, in the Indian Genome Variation Consortium project which involved 200 participants, all the major stakeholders were from the same domain. The cohesiveness could not be sustained amongst stakeholders as once the dataset and platform were ready, everyone could independently take off to do solo projects.

Who leads in a collaboration?
A major aspect of the collaboration is the criteria for choosing the leader and also defining the leadership hierarchy in terms of reporting structure. An essential attribute in a leader besides a demonstrable competence is interpersonal communication skills, emotional intelligence and empathy. Also, the manner in which the leader handles conflicts, by consensus or autocratic methods, determines the cohesiveness within the team and his/her acceptance as a leader. Depending on the kind of collaboration, there might be requirements of multiple leaders from different domains. The roles of these leaders should be clearly defined. There is also a key role for mentorship and monitoring needs in major collaborative efforts. Choosing the appropriate mentors should be one of the critical aspects in such initiatives. The mentors should not have biased or personal interests or stakes in the project. It is important to distinguish between mentor, leader and manager (discussed more separately). Oftentimes the lead PI is assumed to be all three.

Solo leaders directing a multi-disciplinary team where the subordinates are from diverse backgrounds can hamper progress especially if they comprise a major percent. In long-term collaborative projects another aspect to consider is the growth dynamics of the team players and also the mentor-mentee dynamics. A person who ideates the project needs to relinquish leadership at some point of time with the evolution of the project and growing experience of team members.

In the ataxia project there has been a succession of leadership: from a biophysicist to geneticist and now a clinician leading the project. It started with how repetitive sequences are involved in pathogenesis of ataxia by looking at natural variations associated with disease status in multi-generation families. As the registry built up, the question evolved to using the variations to trace founders and identify new variations linked to diseases. Further, induction of clinicians in the backdrop of a registry enabled linking genotypes to phenotypic trajectories and resolving unknown cases through next generation sequencing approaches. This project is now poised for a iPSC approach, and expanding to include stem cell biologists. A glue that held the work together was the involvement of a single clinical investigator throughout the research period, who now heads a specialised ataxia clinic in AIIMS New Delhi. The sustenance of this program was due to successive leadership who had the expertise and interest in the project as it evolved organically.

What about team members?
The composition of the team could go a long way towards determining the success of the collaboration. As mentioned earlier, it should ensure adequate diversity so that contributions of the team players are evident. If all the team members have similar participation, then the collaborative members could become competitors eventually. Some key characteristics that determine team success include experience and expertise of team players, the alignment of individuals’ aspirations as well as their initial conditioning. Understanding of temperament, mindsets as well as value systems amongst the team members can minimise inter-individual conflicts. It is also very important that each of the team members are clear about their expertise and have their growth trajectories aligned to the collaboration for them to effectively contribute to the team efforts.

The Ayurgenomics project has had a diverse set of people with expertise from very contrasting domains. It has been the most challenging and the most engaging project personally for me. However, since it required a major cross-talk between genomics, Ayurveda, modern medicine and computational sciences, a major effort was devoted to developing an effective dialogue for communications amongst the researchers. The language, conditioning and approaches in each of these disciplines is very different and there are limited avenues where cross-talks between these disciplines are possible. This is compounded by the lack of funding organisations that provide a level playing field for researchers who are from different philosophies. The incentive framework and appraisal mechanisms are benchmarked to whatever is mainstream. This cannot create a sustainable framework for innovative research.

How do you share credits?
In large collaborative projects the credit sharing and attributions should be discussed right at the inception of the project else it becomes very ticklish at a later point and sometimes, professional relations get affected. In collaborative projects involving radical innovations success can take a longer time compared to one that involves incremental innovation. Some aspects of collaborative work cannot be completed unless initial frameworks are set. How do you credit the people who had been key during inception where the outcomes are not apparent? In these kinds of projects, it is important to keep a trail of contributions from inception to completion. There could be a few team members who play critical roles during inception and some during closures. If the gaps from inception to closure are very wide, the contributions of the initial players do not get adequately recognized or credited and the individuals who participate during closure of the projects share most of the limelight. There should also be attempts to define outcomes in definitive milestones to keep the team together. This also ensures that the contribution of maximum team members is visible. If independence and ownership for the sub-projects at all levels of functional hierarchy is provided, more people can be incentivized in collaborative projects. However, a balance of quality and quantity needs to be explicit.

One of the interesting things we initiated in the Indian Genome Variation Project was to have a review paper written up about the project with the attributions clearly mentioned. Subsequently any manuscript which solely used the resources had the consortium as one of the authors. To this date, Indian Genome Variation consortium is credited with an authorship in nearly 40 manuscripts and the same has been continued for TRISUTRA Ayurgenomics consortium and, also adopted in the PANASIAN SNP consortium.

Do we need managers?
An important cultural aspect, unfortunately prevalent in Indian science, is a poor respect for timelines and time of collaborative partners. A collaborative project would have complex dependencies at the organizational level, between team members and between organizations. This is where the role of managers is very crucial and we have to give due consideration to this critical manpower in major collaborative projects. Clearly defined milestones and definitive outcomes at each milestone are crucial to sustaining a team throughout collaboration and it is the role of the manager to ensure this. Anything managerial is anathema for a free-thinking scientist in an academic research, but this mindset needs to change.

There will always be many different ways in which we can pursue a fulfilling science career. Framing solo vs. collaborative research, merely in intellectual terms, has been counterproductive for Indian science. I hope that early career researchers find examples in this essay to encourage them to adopt a strategy that best fits with their research goals. Ultimately, it is “peers”, who create a scientific culture and the next generation may wish to do things differently.

Acknowledgements
The author is grateful to L S Shashidhara (IISER Pune, Ashoka University) and Megha (TDU) for providing critical comments and editorial support for this article.

Institute Vision and Strategy 2021-25

Deepak Fulwani

News and Views

---

Institute Vision and Strategy 2021-25

The institute has completed more than a decade in its journey in nurturing talent and achieving excellence. The institute has experienced a significant growth in recent times and by 2025 the student strength will reach to close to 5000 from the current strength of 2564. It is important for a technology institute to assess the changing landscape of the technology and other relevant factors to shape and tune its strategy to contribute significantly and meaningfully. There were several factors including but not limited to New Education Policy, exponential change in technology, changing nature of work and job, financial constraints, expectations from the society, and, the need for virtual mode of education with the traditional brick and mortar model necessitate the need to expand the current Vision and Mission of the institute. Furthermore, high-quality education acquires unprecedented importance in improving the lives and future of the people/planet. The arena and scope of technological education also have to expand far beyond the 20th-century concepts. Technology institutes have to increasingly become more and more multi-disciplinary, and also contribute more directly to the application of emerging technologies for responding effectively to ever-changing challenges/opportunities. They have to become significant contributors to the national development, including in the areas of sustainability, economic growth, and societal problem-solving. The shift in nature of work/ jobs move towards the use of immersive media for blended teaching and the new virtual educational institutions, and growing societal expectations are all calling for a total rethink.

With this backdrop, an institute level committee deliberated on various aspects of the institute and proposed a draft version of the vision document. The committee reimagined the core constituents of the institute i.e., all academic units, administrative offices, and other activities following four steps namely “Reimagine, Redefine Disrupt, Innovate,”. Furthermore, drafting vision document was also inspired by principles of Foresight− a field which predicts most probable futures. This document was debated in series of meetings with different stakeholders and subsequently feedback received through various discussion sessions was incorporated.

Vision statement reflects the proposed nature of the institute; it is envisaged as a future driven knowledge institute, with emphasis on the use of Transformational Technologies/ Interventions with a multidisciplinary approach. The Vision has been translated into a Mission with a five-point Mandate, and a Strategic Architecture to create a holistic institute for knowledge creation and dissemination of all traditional and emerging technologies and their fusion, and its application for national/societal purposes.

The Mission will be achieved through ten Goals. These Goals relate to Curriculum, Pedagogy, Research, Outreach, Institutional Collaboration, Industry Connect, Infrastructure, Student Life Cycle, Financial Plan, and Agile Organisation. The main objectives relate to offering a flexible curriculum, enhancing translational research ecosystem, inculcating professional internal culture, efficient collaboration with industries and institutions, fostering humanitarian values and passion for learning, and to develop socially responsible faculty, students, and future leaders, committed to creating a sustainable society. Every goal is also divided into several sub-goals and the institute Vision and Strategy Document documents strategy for each of the sub-goals and respective Key Performance Indicators (KPIs). In what follows, the institute vision statement, Mission and Goals are presented.

Vision

"A future-driven institute for nurturing excellence of thought; creating, preserving, and imparting knowledge; and using transformational technologies/interventions with a multidisciplinary approach for responding to societal challenges and aspirations. "

Mission

1. Foster humanitarian values, passion for learning, and creativity in faculty and students
2. Move towards high quality, futuristic educational, and research ecosystem
3. Develop socially responsible faculty, students, and future leaders, committed to creating a self-reliant India
4. Catalyze a professional internal culture along with enabling infrastructure and ancillary services
5. Forge effective national as well as international collaboration and partnership with industry and academia for diverse purposes and activities.

Goals

Curriculum

To assimilate balanced, broad-based as well as specialized education in all curricula with opportunities for different kinds of students and their interests.

Pedagogy

To establish systems for dynamic development, implementation, and evaluation of futuristic pedagogy including blended-hybrid teaching and experiential learning.

Research

Have a globally engaged research ecosystem with state-of-the-art facilities in place, for attaining leadership in research on academic, social, national, and industrial fronts while capitalizing on emerging and in-demand opportunities.

Outreach

To be the Institute of Choice for a lifelong learning journey of working professionals, alumni, and the community.

Institutional Collaboration

Have an efficient platform in place for forging impactful partnerships with academia, research institutes, business organizations, civil society, governments, and other agencies across the world for contributing to larger goals for humanity.

Campus Sustainability Project (CSP)

Anand Krishnan Plappally

News and Views

---

IIT Jodhpur is situated at eastern edges of great Thar Desert in India. IIT Jodhpur was born in 2008 and moved to present main campus in 2017. Campus plan was conceived supposing the campus as a living laboratory. The institute is in its teens with its second phase of physical infrastructure development in its last mile. The ecosystem of the campus pertaining to land-use and land cover has transitioned to completely different one during last decade. Campus needs to be sustainable in all fronts and as per the vision of our Director. The Campus Sustainability Project (CSP) is being developed as part of IIT Jodhpur’s commitment to embed sustainable practices across education, administration, finances, student well-being, landscape, ecosystems, natural resources, global social responsibility of the institute and extremely feeble environment prevailing in the region. IIT Jodhpur’ s ability to achieve desired outcomes in the said areas and maintain the ability to continue programs, processes and activities over next decade will provide definition to sustainability

Energy: In order to enable the campus in such a manner, practices to reduce our dependency on fossil fuels needs to be introduced in a phased manner. New renewable energy sources, rechargeable batteries, energy storages can be opted for use in area of transport and energy production. Our new vendors and collaborators should be following UN (sustainability development goals) SDG norms and should have awareness to upkeep their processes and working within environmental conservation edicts. Student projects related to carbon capture data, carbon sequestration and footprint are proposed for the next two years with the long term plan to make IITJ campus carbon neutral.

Waste: Practice of circular causation is to be enabled through strategies to stop waste by concepts of refusing to create waste, reduce its evolution, reuse it, refurbishing products, redesign to fit, rethink about a process, recycle it, recover valuables from it as well produce energy through processes to rot waste. The construction, biomedical, kitchen, paper, sewage and gardening waste need to segregate at source and properly processed to ensure cleanliness around the campus through small projects envisaging a waste free campus in the long run. Setting SDG targets for individual units or buildings which are achievable with effective use of science and technology products and processes are the main aim

Out-Reach: Water and energy are bound to be audited through competitions between occupants of a different physical infrastructure. Students, staff and faculty will test the sustainability indices of processes, devices, and frameworks which they design, create and implement within the campus during the next two years of this project. These projects will be showcased live to the outside world to disseminate concepts which are aligned to UN SDGs and also to churn the public opinion how to practice sustainability in their surroundings. This culture will build a competitive thought to conserve campus amenities and its limited natural resources.

Education: Education for sustainability at IITJ will motivate pupil to produce technology and services that uses renewable resources and does not damage their ecological habitats. This focuses on process, design and product appropriateness, natural resource conservation and creating ecologically and socially aware engineers and professionals who understand interdependence of environmental, social, cultural, data and economic systems. In this regard, talks on sustainability has already started with thought process on initiating management development programs (MDPs), certificate programs and doctoral programs at IIT Jodhpur. Dissemination of knowledge on SDGs and for attainment of SDGs will be also demonstrated periodically to the nearby districts, communities, schools and neighbors through physical as well as online mode.

External Linkage: During the CSP, global linkages with sustainability accreditation organizations, memberships with higher education organization related to UN, regional institutional collaborations and on-campus initiatives is also necessitated. Projects will be also aiming to position IITJ towards promulgating emission mitigation pathways, initiating newer technologies, studies, standards and policies for achieving net zero (emissions need to fall to zero) in alignment to guidelines proposed in the Paris Agreement on 12 December 2015 (by the 196 Parties to the UN Framework Convention on Climate Change (UNFCCC)).

Support: The institute, through its Office of infrastructure and CETSD will support and enable the project initiation in terms of small financial as well as administrative supports. All stakeholders irrespective of student, faculty, staff, family members and other stakeholder are requested to join hands to take forward this movement towards a vibrant future for the region as well as the campus by proposing projects towards SDGs.

Scope: Projects can be from diverse areas, but not limited to, conservation and carbon capture and fixation, data sensing and collection, water management, digitization, AI based interventions, education -based projects, SDG awareness-survey, framework, management, behavioral, awareness, social outreach, neighborhood village partnerships, environmental aspects, student projects, student SDG awareness projects, waste management, transport, renewable energy use, and flora-fauna sustenance.

Impact Analysis of Renewable Variabilities on Coherency Change Patterns in Power System

Ravi Yadav

Research Snippets

---

The dynamic response of a multi-machine interconnected power system to a disturbance introduces multiple electromechanical oscillatory modes within a frequency range of 0.1–2 Hz. A subset of these modes constitutes the inter-area oscillatory modes (0.1-0.7 Hz) produced by synchronous generators oscillating in unison with respect to other areas or systems [1]. These groups of generators exhibit similar dynamic behavior for a disturbance i.e., their frequency and phase-angle signals have homogeneous oscillations. Such units are referred to as “coherent” generators [2]. Identification of coherent generator groups is required for: 1) Controlled-Islanding: That limits the spread of cascading outages by partitioning the system into multiple controllable and self-sustainable islands, 2) Wide-Area damping Control: where critical inter-area oscillatory modes in a system are identified and attenuated using control strategy based on wide area measurement system data (WAMS), and 3) Dynamic equivalencing and system aggregation for dynamic vulnerability analysis.

Most of the available literature analyzes coherency patterns for only conventional synchronous generation in the power system [3]. However, high penetration of intermittent renewable energy sources can influence existing inter-area modes or introduce weakly damped modes in a system, which alters the coherency grouping of a system [4]. Depending upon the source characteristics, control topology, and location of renewable generation the coherent grouping in a power system can vary. Renewable alterations like non-uniform inertia distribution and source intermittency need to be included in the coherency pattern study for modern power systems [5]. In this work, an in-depth analysis of coherency changes patterns due to variabilities in renewable generation is presented. It raises pertinent points regarding the impact of new renewable integration, and outage of renewable sources on low-frequency power system oscillations, and the effect of dynamic renewable intermittencies on small signal stability.

Power system coherency study under different penetration levels can provide limited insight into system dynamics under renewable integration. Intermittent renewable generation can influence system dynamics in a variety of ways like non-uniform changes in inertia distribution due to: (i) a new renewable source integration at varied locations in the grid, (ii) scheduled or unscheduled outages of existing renewable plants, (iii) dynamic power flow pattern changes, and (iii) source intermittency (change in wind speed or solar insolation profiles). Each type of these variability influences the system coherency in a unique way and their effect needs to be studied for planning, wide area control, and controlled islanding applications.

Case 1: Effect of Non-uniform Inertia Distribution with Renewables
Any new large-scale renewable integration in a system could influence the existing inter-area oscillatory modes or may introduce newer oscillatory modes in the system, which can affect the system coherency. New integration can influence coherency in two ways:
(1) Spatial location of new integration or power sharing changes of participating generators.
(2) Type of renewable source or control topology.
Case 1.1: Effect new integration and power flow patterns with renewables
The location of renewable energy power plants (REPPs) and their interconnection point in a system are mostly governed by the geographical abundance of renewable sources within a geographical zone. However, depending on the interconnection nodes, the coherency grouping of an area or system can vary distinctly.

To illustrate this, two different scenarios are considered, 1) an offshore wind farm (OWF) (with back-to back voltage source converter- high voltage direct current (VSC-HVDC) link of capacity 500 MVA) is integrated while keeping the power sharing similar among the neighboring generators and 2) changing the power sharing ratio.

To simulate the first scenario, an OWF is integrated at bus-23 near generator G-07 of the IEEE-39 bus system [6]. For a trip disturbance at Line 6-11, the speed signals under base case (i.e., without OWF) and with OWF are shown in Fig. 1 (a) and (b). The disturbance excites two local oscillatory modes -0.682±8.473j (with damped frequency 1.348 Hz), and-0.5±7.100 j (with damped frequency 1.13 Hz). For both the local modes, all four generators G-04, 05, 06, and 07 participate under the base case, which changes with integration of OWF as G-07 no longer participate in these modes (refer mode shape plot of Fig. 2 (a)). A similar trend is observed for a critical inter-area mode -0.32±5.99j (damped frequency 0.955 Hz), where participation of G-07 changes with integration of OWF at bus-23 as shown in Fig. 2 (b). This shows that the participation of generator G-07 in the oscillations within the coherent area changes with the integration of OWF at bus-23 and it starts oscillating as a disassociated generator.

In the second scenario, a new OWF is integrated at bus-21, which changes the dispatched power from generators G-06 and G-07 based on their effective droop. This excites a new local oscillatory mode-1.062±10.6j (damped frequency 1.69 Hz), where only G-06 and 07 are participating, whereas an opposite trend is observed for the inter-area mode -0.346 + 6.344j (damped frequency 1.009), where G-06 and G-07 lose participation. This can be visualized from the speed signals and mode phasor plot of Fig. 3 (a) and Fig. 4. In another scenario, an OWF is integrated at bus-19 which changes the scheduled powers from G-04 and 05 in accordance with their effective droop. This excites a new local oscillatory mode -0.995+10.890j (damped frequency 1.733) with the participation of G-04 and G-05 only, whereas the same generators lose their participation in the critical inter-area mode -0.360+6.315j (refer to the speed signal and mode phasor plot in Fig. 3 (b) and Fig. 4 (b)).

The scenarios discussed above, indicate that the location of newly integrated REPP and corresponding power flow change in existing generators excite new modes within the power system and change the coherent participation of these generators in critical low-frequency inter-area modes.

For automated segregation of coherent groups, an un-supervised spectrum similarity approach method is used, which is proposed in our previous work [1]. For the case of OWF integration at bus-23, the coherency method indicates the separation of the generator G-07 from the previously coherent area (CA)-02 and forming a new coherent area CA-3 as shown in Fig. 5 (a). Whereas, in the case of OWF integration at bus-21 the coherency method indicates the separation of generators G-06 and 07 forming a new coherent area CA-2 as shown in Fig. 5 (b).

Case 1.2: Effect of Outages of Existing Renewable Sources
Planned or unplanned outages of a renewable power plant can affect system coherency depending upon the type of renewable source and location of the outage. In addition to switching outages, any reduction in dispatched power from renewable can cause a varying effect on system oscillations and therefore coherency. The outage of renewable sources can affect coherency in the following ways:
(1) Location of renewable outage/reduced dispatch
(2) Magnitude of outage/dispatch changes in the renewable source.
(2) Type of renewable source facing outage.

To illustrate this, the IEEE-39 bus system is modified to include OWF and DFIG integrations at different locations in the network as shown in Fig. 6. The wind power plants are distributed in a way that generators in all three areas have a uniform distribution of non-synchronous generation. The penetration level is 25 %, which is measured as:

As the spatial distribution of renewables is considered unform across the base case, so no apparent impact is observed on system coherency grouping. This dynamically un-changed IEEE-39 bus system with 20% renewable penetration level is subjected to renewable outages/dispatch changes to analyze their impact on system coherency. For this, two scenarios are considered. In first scenario the OWF at bus-6 suffers an outage, creating a new dynamic state of the system. For this perturbed system a line trip event at line 6-11 is simulated at 5s and oscillation trends are analyzed. The generator speed signals under base case and after outage of OWF at bus-06 for a line trip event at 6-11 are shown in Fig. 7 (a) and (b).

The outage of OWF at bus-06 increases the dispatched power from G-03, which in turn enhances the effective inertia of G-03 and changes the coherency trends for adjoining generators. For example, after an outage the participation of generator G-04 in the inter-area mode -0.345+6.045j (damped frequency 0.962 Hz) changes in a way that it starts oscillating with G-03 forming a single coherent group as shown in the mode shape plot of Fig. 8 (a). The reason for this is the increased effective inertia of G-03, which forces G-04 to oscillate in unison. It became coherent to gen-03 and formed a new coherent group leaving the existing coherency with area-02. In another scenario, an outage of the onshore wind plant (DFIG type) at bus-21 causes a change in oscillation participation of G-03, G-04, G-05, and G-07. In a way that G-04, G-05 start oscillating distinctly from the G-06, G-07 (under base case all four generators oscillate in unison for most inter-area modes). In addition, G-03 also start oscillating in unison with G-06, which was dissociated during the base case without any outage. The Speed signals and mode shape plots for this scenario are shown in Fig. 7 (c) and 8 (b). The reason for these changes is the increased effective inertia of G-06 that disturbs a delicate inertial balance in the system.

These observations are confirmed with the automated un-supervised spectrum similarity method [1]. For outage OWF at bus-06 the method correctly detects the formation of new coherent group CA-02 with G-03, G-04, G-05, G-06, and G-07 oscillating in unison as shown in Fig. 8 (a). On the other hand, for the outage of DFIG from bus-21, the generators G-07, 06, and 03 form a separate coherent group CA-2, whereas generators G-04 and 05 form another coherent group CA-3.

From these results it can be understood that outage/reduced dispatch of any renewable power plant and associated inertia change in the area, not only affects the coherency within the group but also of the adjoining coherent groups.

Case. 2: Effect of Source Intermittency Renewable energy sources like photovoltaics and wind are inherently intermittent and are non-dispatchable generations. Therefore, intermittencies associated with renewables make the effective inertia of a power system time-varying. Due to the time variation of inertia, the coherent grouping of generators becomes dynamic (the effect will be more prominent for high renewable penetration levels), which makes coherency detection a frame-to-frame operation rather than static segregation. In the work, the intermittency scenario is simulated by inducing a sudden fast ramp reduction of 20% in the detached power from DFIG at bus-19 at 7 s.

Under this scenario, the speed signals for different generators are shown in Fig. 9 (a), where due to the sudden reduction in DFIG output at bus-19, the existing generators G-04 and 05 start swinging distinctly from the generator G-06 and 07. This is confirmed from the mode participation trends, where generators G-04, 05 participate as a distinct group with respect to generators G-06 and 07 in a new inter-area mode -0.458±5.975j (damped frequency 0.975) as shown in Fig. 9 (b). This implies that fast ramp intermittency in DFIG at bus-19 caused segregation of area-02 into two coherent groups: one group with G-04 & G-05 and other groups with G-06 & G-07 generators.

The coherency results with the unsupervised clustering method for wind intermittency shown in Fig. 10, also show that the generator G-04, 05, 06, and 07 which were oscillating as a single coherent group pre-intermittency, started oscillating as two coherent groups of (G-04 & 05) and (G-06 & 07) post-intermittency.

The above analysis clearly indicates that the fast intermittencies in solar and wind power sources cause dynamic variations in system inertial patterns causing dynamic variation in the system’s oscillatory patterns and thus time-variation in coherency trends.

Conclusion
This work analyzes the impact of renewable variabilities on power system oscillation patterns and coherency trends. The work provides the following observations regarding the influence of power system coherency with renewable variabilities:
1) Renewable distribution changes at high penetration levels cause non-uniform variations in system inertia distribution resulting in the segregation of large coherent areas into small coherent groups.
2) The spatial location of renewable variability and magnitude of change in renewable power dispatched influences the mode participation trends in a power system uniquely.
3) The dynamic changes in system coherency with high renewable penetration levels make islanding, wide-area damping control, and dynamic system grouping also dynamic.
4) Distribution changes at different locations activate new and distinct inter-area modes in the system complicating the area control and islanding.
5) Fast ramp intermittencies in renewables cause dynamic variation in system coherency status for pre- and post-intermittency time periods for the same set of disturbances.

References:-

1.	R. Yadav, A. K. Pradhan and I. Kamwa, "A Spectrum Similarity Approach for Identifying Coherency Change Patterns in Power System Due to Variability in Renewable Generation," in IEEE Transactions on Power Systems, vol. 34, no. 5, pp. 3769-3779, Sept. 2019.
2.	H. You, V. Vittal, and X. Wang, “Slow coherency-based islanding,” IEEE Transactions on Power Systems, vol. 19, no. 1, pp. 483–491, Feb 2004.
3.	I. Kamwa, A. K. Pradhan, G. Joos, and S. R. Samantaray, “Fuzzy partitioning of a real power system for dynamic vulnerability assessment,” IEEE Transactions on Power Systems, vol. 24, no. 3, pp. 1356–1365, Aug 2009.
4.	M. A. M. Ariff and B. C. Pal, “Coherency identification in interconnected power system - an independent component analysis approach,” in 2013 IEEE Power Energy Society General Meeting, July 2013, pp. 1–1.
5.	R. Christie, Power systems test case archives, 1993. [Online]. Available: https://www.ee.washington.edu/research/pstca.

Electrochemical Energy Storage Devices: State of the Art and Future Directions

Prashant Kumar Gupta, Praveen Kumar Sappidi

Research Snippets

---

To address the future energy demands, it is essential to develop scalable energy storage systems from abundant materials that can be integrated with renewable energy. For centuries, batteries have been known for their excellent chemical energy conversion and storage. Most portable energy storage technology is currently dominated by lithium-ion while stationary energy storage with lead acid-based technology. The intercalation-based lithium-ion technology has high energy density but is still expensive to scale up. Less abundance of lithium and the safety due to the use of liquid organic electrolytes are primary concerns. While on the other hand, conversion reaction-based lead acid batteries cause significant environmental problems with low energy density and limited cycle life require exploring an alternate energy storage technology.

The current state of the art for lithium-based technology has a positive electrode of LiCoO2 or its derivatives or spinel compound like LiMn2O4 or polyanionic compound like LiFePO4. The present research can be divided into two categories: the first one focuses on the cost and safety with the expense of energy density, while the other is to improve the energy density, whereas the demand for optimum performance lies in both. Recently, partial replacement of transition metal sites with the lithium known as lithium-rich compound showed very high capacity ~300 mAh/g but suffered from a poor cycle life [1]. Apart from lithium, other cations like K+, Na+, Zn+2, Mg+2, Al+3, etc. have been explored for energy storage. However, none were found suitable. Similar mono-valent Na and K-based ions show poor cycle life due to the bigger size of the intercalating ions. The multivalent ions, though they have an ion size close to the Li+ but high electric density due to greater charge, will result in strong electrostatic interaction with the host material, resulting in a polarization effect that sluggish the diffusion process.

The search for better technology for the future based on earth-abundant materials like Na+ and Zn+2 requires much scientific exploration to make these technologies feasible on the device level. As seawater is an infinite source of sodium elements and is an abundant material. The concentration of Na+ ions in seawater is approximately 0.47 M. It can possibly act as a Na+ ion source during the direct use of sea water in batteries. But the suitable electrode material requires more scientific examination for the commercialization of these technologies. Similarly, India lies in 7th place in terms of zinc reservoirs and 3rd place in the production of the world’s 5.3% zinc, which attracts researchers for zinc-based technology. Zinc metal has a theoretical specific capacity of 820 mAh/g. A capacity density of more than two times that of lithium, equal to 5855 mAh/cm3 makes it a potential material for energy storage application and needs to be explored [2].

With the advancement of computer’s power will help design and analyze experiments via computations to better understand the underlying physicochemical factors, which will result in the development of next-generation energy storage devices, electrode materials and solid and liquid electrolytes. The rate of charging and discharging, stability, and overall efficiency of any battery is highly dependent on the structural and transport properties of the electrolytes. The atomistic and molecular level simulations would help understand the Ion hopping (Li+, Na+, Mg2+, Zn2+, and Al3+, etc.), ion dynamics, ionic conductivity, transference number, and solvation thermodynamic properties in different electrolytes and electrode materials. On the other hand, it is known that solvated ions in the liquid electrolytes influence the overall reaction rate and selectivity. Thus, fundamental gaps such as accurate understanding of the reaction kinetics in different electrolyte materials and their effects due to different perturbations are challenging, which need to be understood in more detail. A combination of atomic-level simulations such as Density Functional Theory (DFT), Molecular dynamics (MD) simulations, and Coarse-grained (CG) simulations along with the experimental benchmarks, will help in developing the next-generation batteries. Figure 1 presents research directions towards the combined computational and experimental approach toward this multi-dimensional battery material development problem.

Figure 1. Combined computational and experimental approach towards the development of battery materials.

Further, to enhance the battery performance, different electrolytes are being considered such as water-in-salt electrolytes [3], polymer electrolytes [4], etc. However, there are challenges such as developing enhanced sampling techniques for the electrochemical reactions in the solid-liquid interfaces, implementing Machine Learning (ML) approaches to understand the physicochemical properties of liquid electrolytes [5], and estimating the lifetime of both electrolyte and electrode materials. Considering modern computing resources such as GPUs and web-based cloud technologies, this combination of approaches would enable the researchers to solve this complex problem.

References:-

1.	P. Roziera, and J. M. Tarascon. Li-Rich Layered Oxide Cathodes for Next-Generation Li-Ion Batteries: Chances and Challenges. Journal of The Electrochemical Society, 162 (14) A2490-A2499, 2015
2.	A. Konarov, N. Voronina, J. H. Jo, Z. Bakenov, Y. K. Sun, and S. T. Myung. Present and Future Perspective on Electrode Materials for Rechargeable Zinc-Ion Batteries. ACS Energy Letter, 3, 2620−2640, 2018
3.	T. Liang, R. Hou, Q. Dou, H. Zhang, X. Yan. The Applications of Water‐in‐Salt Electrolytes in Electrochemical Energy Storage Devices. Advanced Functional Materials, 31(3), pp. 2006749, 2021.
4.	K. D. Fong, J. Self, B. D. McCloskey, and K. A. Persson. Ion Correlations and Their Impact on Transport in Polymer-Based Electrolytes. Macromolecules, 54(6), pp. 2575-2591, 2021
5.	Y. Shao, L. Knijff, F. M. Dietrich, K. Hermansson, C. Zhang. Modelling Bulk Electrolytes and Electrolyte Interfaces with Atomistic Machine Learning. Batteries & Supercaps, 4(4), pp. 585-595, 2021.

Design of Mechanically Tunable Wide Phononic Band Gaps in Soft Laminates by Means of Topology Optimization

Atul Kumar Sharma

Research Snippets

---

The propagation of elastodynamic waves in periodic composite materials, also known as phononic crystals (PnCs), has gained increasing attention in the recent past [1,2]. PnCs possess the promising characteristic of exhibiting band gaps within which the propagation of acoustic/elastic waves in certain frequency ranges is prohibited. Due to this characteristic, PnCs have been implemented in a wide range of engineering applications such as frequency filters, vibration isolators, acoustic diodes, noise suppressors, and among many others [3,4].

Soft active materials, such as tissues, dielectric elastomers, and magnetorheological elastomers, etc. have been of particular interest due to their characteristic of undergoing large deformation when actuated by mechanical, electrical, magnetic, thermal fields [5]. The constitutive behavior of such materials is nonlinear and material properties are a function of mechanical, electrical, or magnetic loading. These features made them attractive for tunable band gap structures. In this regard, a significant effort has been made to investigate the wave propagation and band gaps in the periodic composite structures or PnCs made up of soft active materials [3,6,7]. However, in several of these applications, the position and width of the band gaps of PnCs play a crucial role. Thus, it is necessary to design a periodic structure that possesses the desired position and width of the band gap. The design of PnCs with tunable band gaps has been the topic of continued interest and investigation [1]. A large volume of literature expounds on designing the topologies of PnCs made up of hard materials such as Aluminium/Epoxy, for widening the band gap width [1,2]. In contrast, not much work has been done on topology optimization of PnCs made up of soft materials [8]. To this end, this paper reports a gradient-based topology optimization framework for designing wide and mechanically tunable soft band gap structures.

Consider an infinite periodic laminated composite composed of perfectly boded two different soft compressible phases denoted by a and b as shown in Fig. 1. In the undeformed configuration, the thickness of the unit cell is . For tuning the band gaps, laminate is subjected to fixed equi-biaxial prestretch in the lateral directions and the pre-stress in the longitudinal direction. In the deformed configuration, the thickness of the unit cell becomes and is related to undeformed thickness as with p=(a,b) and being the stretch ratio in the longitudinal direction for pth phase. Considering that the phases are made up of compressible neo-Hookean materials, the nonlinear constitutive relation relating the applied prestress and longitudinal prestretch is given as

Figure 1: Schematic of an infinite two-phase soft phononic crystal subjected to prestress in the longitudinal direction and the corresponding undeformed unit cell.

This paper is restricted to investigate the longitudinal waves propagating in the x3 direction of the deformed phononic crystal. The finite deformation field theory presented in Ref. [9] is used for studying the incremental elastic longitudinal wave propagation superimposed on the static deformation induced by the applied prestress . The incremental equation governing the longitudinal waves propagating in the x3 is obtained as

Next, the standard finite element method with Bloch periodic boundary conditions [10] is adopted to find the band diagrams of the infinite periodic soft laminate. Considering time-harmonic excitation, the resulting finite element equations for modeling the infinite periodic soft laminate is given as

where denotes the spatially dependent nodal incremental displacement vector, K and M are the stiffness and mass matrices, respectively, and k is the wave vector. The eigenvalue problem (Eq. 2) along with the Bloch periodic boundary condition is solved for extracting the longitudinal band diagram.

This paper aims to find the optimal distribution of soft compressible phases a and b in the unit cell that maximizes the band gap width in the pre-stressed configuration. The mathematical formulation of the topology optimization problem for maximizing the band gap width in the pre-stressed configuration is defined as

The finite element eigenvalue problem and the topology optimization problem presented in this paper are implemented by developing an in-house MATLAB code. The unit cell is assumed to be made up of two compressible neo-Hookean hyperelastic phases a and b whose material properties are listed in Table 1. In the undeformed configuration, the size of the unit cell is taken to be 1mm and discretized into 200 linear bar elements. The longitudinal band structures are obtained by sweeping the wave vector in the irreducible first Brillouin zone . For convenience, the frequency is normalized as and the wave vector is normalized as kh.

In conclusion, a gradient-based topology optimization framework is presented for maximizing the longitudinal band gap width in soft compressible laminated phononic crystals. The topology optimization and finite element framework presented for extracting band gap diagrams is implemented using an in-house MATLAB code. The higher compression prestress is found to have a favourable impact on the optimized band gap characteristics. The present gradient-based framework can be extended for designing wide tunable band gaps for anti-plane and in-plane waves of general propagation direction in two-dimensional and three-dimensional soft composites.

References:-

1.	G. Yi, Y. C. Shin, H. Yoon, S.-H. Jo, B. D. Youn, Topology optimization for phononic band gap maximization considering a target driving frequency, JMST Advances 1 (1) (2019) 153-159.
2.	W. Li, F. Meng, Y. Chen, Y. f. Li, X. Huang, Topology optimization of photonic and phononic crystals and metamaterials: a review, Advanced Theory and Simulations 2 (7) (2019) 1900017.
3.	Y. Chen, B. Wu, Y. Su, W. Chen, Tunable two-way unidirectional acoustic diodes: Design and simulation, Journal of Applied Mechanics 86 (3) (2019)
4.	Z.-G. Chen, J. Zhao, J. Mei, Y. Wu, Acoustic frequency filter based on anisotropic topological phononic crystals, Scientific reports 7 (1) (2017) 1-6.
5.	J. Kim, J. W. Kim, H. C. Kim, L. Zhai, H.-U. Ko, R. M. Muthoka, Review of soft actuator materials, International Journal of Precision Engineering and Manufacturing 20 (12) (2019) 2221-2241.
6.	R. Getz, D. M. Kochmann, G. Shmuel, Voltage-controlled complete stopbands in two-dimensional soft dielectrics, International Journal of Solids and Structures 113 (2017) 24-36.
7.	A. Bayat, F. Gordaninejad, Band-gap of a soft magnetorheological phononic crystal, Journal of vibration and acoustics 137 (1) (2015).
8.	E. Bortot, O. Amir, G. Shmuel, Topology optimization of dielectric elastomers for wide tunable band gaps, International Journal of Solids and Structures 143 (2018) 262-273.
9.	A. Dorfmann, R. W. Ogden, Electroelastic waves in a finitely deformed electroactive material, IMA Journal of Applied Mathematics 75 (4) (2010) 603-636.
10.	C. Kittel, Introduction to solid state physics, John Wiley & Sons, Inc., New York (2005).
11.	K. Svanberg, The method of moving asymptotes—a new method for structural optimization, International journal for numerical methods in engineering 24 (2) (1987) 359-373.

IITJ’s CODE Device useful for Better Indoor Air Quality and COVID-19 Pandemic

Ram Prakash

Innovation Gallery

---

In the current era, airborne transmitted pathogen infection is causing diseases of significant morbidity and mortality. Almost every year we are seeing a new bacteria or virus of influenza nature appearing and creating epidemic/pandemic of diseases. Besides human-to-human transmission, in the highly crowded and indoor enclosed environments such as healthcare facilities, schools, colleges, universities, large shopping malls, commercial buildings, and public buildings, indoor pathogens shed from humans may further transmit and disperse through HVAC systems, and may lead to cross-infections. This fear has created a lockdown across the world and the infection due to COVID-19 has affected work productivity hugely. Human safety is very important but this is causing substantial economic impacts. People are scared to work in public places. To reduce the risks of infection from such transmission in the indoor environment, engineering control strategies is the need of hour. Accordingly, IIT Jodhpur has developed a novel Cold-plasma Detergent in Environment (CODE) Device under an industry-sponsored project to reduce the risks of infection from airborne pathogens in the indoor environment, by using DBD plasma in combination with nanotechnology.

What is technological innovation?
The IITJ’s CODE device is based on a cold plasma discharge for the generation of plasma detergent ions in the environment. The device comprises a novel geometry plasma source with specially designed electrodes and a filter coated with metal oxide nanoparticles catalysts. It is an environment friendly technique and uses low-cost electrode materials. The need for feed gas, pallets and/or differential pressure has been eliminated from the plasma discharge for air purification by virtue of new design and process. It is a well-known fact that one finds the highest negative ion concentration in natural clean air, and the high negative ion concentration dramatically improves indoor air quality and health. There is a range of methodologies tested to generate negative ions, particularly for hydroxyl radicals (‘natural detergent’) using UV-light and/or plasmas. On one hand UV-light has constraint because of energy of the e-h pair is limited and the generated hydroxyl radical’s quenches well before (i.e., ~0.1 sec). On the other hand, the presently used plasma discharges are either costlier or consumes high power or are created with much more complexities.

What are the key features?
The IITJ’s CODE device is able to generate efficient plasma detergent ions with a larger sustenance time that also at atmospheric pressure (without any additional gas or vacuum system). The developed device has been characterized electrically and this new type of discharge plasma generation requires low average power to operate and simultaneously provides high efficiency for plasma detergent generation that has been tested in an 8’’ device. It is able to produce plasma detergent ions in lakhs and with an average ion sustenance time more than 25 sec. The device is easily scalable and is free from UV-light and Ozone.

What can it do?
The working performance of the device has been tested for disinfection of total microbial counts, reduction of total fungal counts, dust and pollens in the indoor environments of sizes more than 1,72,80,000 cm3 and the obtained results are highly encouraging which showed that the pristine natural environment is quite realizable from the CODE device in the indoor environments. It is a low-cost and easily scalable device and will require less maintenance. The tests are underway and the device can also degrade Volatile Organic Compounds (VOCs) because the hydroxyl radicals created in the environment will freely react with organic molecules to partially ionize or fully oxidize them to CO2 and H2O.

The scope of the invention is not limited only in elimination of total microbial counts, total fungal counts and dust/pollen, but it can also deactivate the most lethal range of other airborne viruses including COVID-19, SARS CoV, Influenza, etc. because the virus is not a living organism, but a protein molecule covered by a protective layer of lipid (Fat) and the produced active plasma detergent ions for more than 20 seconds with optimum concentration will effectively kill the viruses (i.e., already established that detergent foam cuts the fat −only one needs to rub hands so much for 20 seconds or more).

To whom it will be useful?
The developed technology is attractive for individuals in offices, houses, public places (such as healthcare facilities, schools, colleges, universities, large shopping malls, commercial buildings, taxis, trains, cinema halls, conference halls, marriage halls, etc.) and can provide a pristine natural indoor environment. Systems based on this technology can eventually be deployed at all public and health care facilities as standalone system or can be integrated with the ducts, AC, Coolers, etc. The proposed device can also be easily tailored in the form of CODE Jets to clean the environment, personal protective equipment, dresses, Facemasks, etc. for safe handling the patients by the Doctors and hence can be a useful technique to fight with the pandemic of disease such as COVID-19, SARS CoV, Influenza, etc.

Who developed the technology? Faculties and Ph. D. students of the Department of Physics, IIT Jodhpur (Dr. Ram Prakash, Associate Professor, Project Leader, Dr. Ambesh Dixit, Associate Professor, Mr. Ramavtar, Ph. D. Scholar, Ms. Kiran, Ph.D. Scholar) under an industry-sponsored project supported by M/s Porte Automations Private Ltd., Noida and IIT Jodhpur Seed Grant Scheme.