Artificial Intelligence for Sustainability A Human-Centric Approach to Global Challenges

1. Human-Centered Artificial Intelligence: Evolution, Challenges and Trends

J. Gokulakrishnan, G. Prethija, Viswa Danuskka

2. Framework for Green and Sustainable Human Centered AI: Challenges and Research Directions

R. Thejal, Prithi Samuel, Reshmy A.K., Sudha Rajesh, Vikneswaran Vijean, Fizza Ghulam Nabi

3. Human centered Artificial Intelligence and the education sector: A statistical Analysis

S. Nagendra Prabhu, G. Siva Shankar, M. Kiruthika, K. Moorthi

4. Artificial Intelligence for Sustainable Value Creation and Goal Development

Ponmani S, Vinothini S

5. Digital Twin and Human Centred AI for Sustainable Growth Development

Karthi. S, Kalaiyarasi. M, Selvapriya. M and Ragavi. C

6. Trustworthy and Sustainable Edge AI: Human Centric Approach and Research Directions

Rajaram P, Rajasekar Rangasamy, Ramachandran V, Divyapushpalakshmi M, Balaji V

7. Augmented Agile: Human-Centered AI-Assisted Software Management for Sustainable Development

A. Pandian, K. Sreekumar, M. Anand, K. Pradeep Mohankumar, S. Padmini

8. Smart Logistics: Using Artificial Intelligence and Blockchain in Supply Chain Management

M. Valliammal, S. K. Manivannan

9. Business value through human-centric AI: Case studies and Research Directions

Gopirajan PV, Harsh Bhayana, Joyal Dave, S Naveen

10. Towards an AI-Centric Requirements Engineering Framework for Trustworthy AI
Deepika Roselind J, R Srivats, Kalyanasundaram V, Saimirra R, Keerthi AJ

11. Human-centricity in AI governance: Use Cases, Challenges and Research Directions

Vijay K, Ujjain S, Dhanush Ishwar D, Thilak Kumar V

12. An impact of business value through human centric AI

Rufia Thaseen. I, S. Shahar Banu

Biography

Prithi Samuel is currently working as an Associate Professor in the Department of Computational Intelligence at SRM Institute of Science and Technology, Kattankulathur Campus, Chennai. She has completed her Ph.D. in Information and Communication Engineering from Anna University, Chennai. She has got over 19+ years of teaching experience in reputed engineering colleges in Coimbatore and Chennai. She is a pioneer researcher in the areas of Automata Theory, Deep learning, Machine Learning, Computational Intelligence Techniques, and Natural Language Processing. She has published papers in leading International Journals and International Conferences and published books and book chapters in international publications.

A.K. Reshmy is working as an Associate Professor in the Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Chennai, TamilNadu, India. She has more than 20 years of experience in teaching and research. She has received her Master of Engineering in Systems Engineering and Operations Research from College of Engineering, Guindy, Anna University, Chennai, India. She is a recipient of gold medal for securing first rank in Master of Engineering. She received Professor T.R. Natesan Endowment Award (Gold Medal-Instituted by Operational Research Society of India-Chennai Chapter). She has completed her doctorate (Ph.D in Information and Communication Engineering) from Anna University in the field of Big Data. Her current research focus is on Data Science, Machine Learning. To her credit she has published papers in Scopus Indexed Journal, presented papers in International Conferences and has filed patent. She has served as resource person and chaired conference session. She is Life member of Indian Society of Technical Education (ISTE) and a fellow of Institution of Engineering and Technology (IET).

Sudha Rajesh received her bachelor’s degree in computer science and engineering from Shri Angalamman College of Engineering and Technology affiliated to Anna University, Tamil Nadu, India and Master’s degree in Computer Science and Engineering from Pavendhar Bharathidasan College of Engineering and Technology affiliated to Anna University, Tamil Nadu, India. She received her Doctor of Philosophy in Faculty of Computer Science and Engineering from Sathyabama Institute of Science and Technology, Tamil Nadu, India. She is currently working as Associate Professor in the Department of Computational Intelligence in SRM Institute of Science and Technology, Chennai. She has 17+ years of experience in teaching and research. Her area of interest includes Python, Machine Learning, Data Science, Software Engineering, Software Quality Attributes and Estimation of Design Patterns and Data Mining. She published 50+ research papers in various International Journals and Conferences. She published 9 Indian Patent. She holds the position of a reviewer and an editorial board member in reputed International Journals. She is a Lifetime Member in ISTE, ACM.

Vikneswaran Vijean is an accomplished Senior Lecturer with a robust background in the research industry, specializing in bio-signal processing. He earned his PhD in Biomedical Electronic Engineering from Universiti Malaysia Perlis, complemented by a Bachelor's Degree in Mechatronic Engineering from the same institution. Driven by a passion for education, he has contributed significantly to the academic landscape, imparting knowledge in subjects such as Medical Robotics, Design Projects, Analogue Electronics, Electronic Engineering skills, and Computer Aided Design. With a research focus encompassing Evoked responses, phonocardiogram analysis, bio-signal processing, speech analysis, artificial intelligence, expert systems, and Machine Learning, Dr. Vikneswaran has left an indelible mark on the field. His extensive scholarly contributions include 23 academic journals, 41 conference proceedings, 4 book chapters, and 3 copyrights. As of 2023, his H-index stands at 11, accompanied by 415 citations, attesting to the impact of his work. As a mentor, Dr. Vikneswaran has guided and supervised 4 Ph.D and 3 M.Sc students to successful graduations, demonstrating his commitment to fostering the next generation of researchers. Currently, he is actively mentoring 2 PhD candidates, showcasing his dedication to academic mentorship. Beyond the classroom, Dr. Vikneswaran is a sought-after speaker, having delivered numerous international talks, lectures, and workshops on biomedical signal processing applications. His expertise is further recognized through his role as an active reviewer for various ISI indexed journals and as an Engineering Technology Accreditation Council (ETAC) Panel registered with the Board of Engineers Malaysia. Dr. Vikneswaran's professional affiliations include being a chartered engineer registered with the Engineering Council, UK, a Graduate Engineer with the Board of Engineers Malaysia, and a member of the Institution of Engineering and Technology, UK. Dr. Vikneswaran was appointed as a visiting fellow in Intel Microelectronics (M) Sdn. Bhd in early 2023. His leadership skills were showcased through the successful organization of a series of activities involving collaborations between industries and academia. Furthermore, Dr. Vikneswaran and his research team were able to accumulate research funding amounting to RM 490,540.00 from various governmental agencies and industries. In summary, Dr. Vikneswaran Vijean is a dedicated educator, prolific researcher, and influential figure in the field of bio-signal processing. His multifaceted contributions to academia, research, and industry underscore his commitment to advancing knowledge and fostering meaningful collaborations.

Fizza Ghulam Nabi graduated from Department of Mechatronics Engineering at Universiti Malaysia Perlis 2019 and currently, she is working as Assistant Professor in the Department of Industrial Engineering & Management, University of Punjab, since September 2020. She has published 26 articles published in various national and international reputed journals. Her google h-index is 6 and her i10 index is 4. Her current research interests are Signal Processing, Digital Signal Processing, Signal Analysis, Discrete Signal Processing, FFT Time-Frequency Analysis, Discrete-Time Signal Processing, Coding, Adaptive Filtering, Filter Theory Spectrum Analysis, Power Spectrum Density, Detection Theory.