This volume presents select proceedings of the International Conference on Sustainable Advanced Computing (ICSAC 2021). It covers the latest research on a wide range of topics spanning theory, systems, applications, and case studies in advanced computing. Topics covered are machine intelligence, expert systems, robotics, natural language processing, cognitive science, quantum computing, deep learning, pattern recognition, human-computer interface, biometrics, graph theory, etc. The volume focuses on the novel research findings and innovations of various researchers. In addition, the book will be a promising solution for new generation-based sustainable, intelligent systems that are machine and human-centered with modern models and appropriate amalgamations of collaborative practices with a general objective of better research in all aspects of sustainable advanced computing.

Includes select papers from the International Conference on Sustainable Advanced Computing ICSAC 2021 Focuses on the novel research findings and innovations of various researchers Includes a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects

Autorentext
Sagaya Aurelia is currently associated with the department of computer science at CHRIST-deemed to be University. She completed her B.E. in the year 2000, M.Tech. in the year 2002, and Ph.D. in the year 2019. She published several research papers in journals and conferences of national and international repute. She was awarded the Peace Leader and Peace Educator award by the global mission of the UN Global Compact. Her research interest areas are human-computer interaction, augmented reality, and virtual reality.

Somashekhar S. Hiremath is an Associate Professor in the Department of Mechanical Engineering, Indian Institute of Technology Madras. He has over two decades of teaching and research experience. He worked as a visiting professor at the Ecole Centrale de Nantes, France, and Warsaw University of Technology, Poland. He also worked as a Director of Tamil Nadu Small Industries Corporation Limited, popularly known as TANSI, Chennai. Dr. Somashekhar has guided 11 doctoral students, 5 M.S. (by research) students, and 43 master students. He has 02 patents, 56 journal papers, 130 conference papers, 03 edited books, 03 monographs, 04 book chapters to his credits. His research areas include mechatronic system design, robotics, micro-machining, fluid power systems, system simulation, and modeling, finite element modeling, and precision engineering.

Karthikeyan Subramanian is currently heading the Department of Information Technology at the University of Technology & Applied Sciences, Oman. He completed his B.Sc. and M.Sc. from Bharathidasan University. He completed his Ph.D. in computer science and engineering from Alagappa University. Dr. Subramanian served as an Editor-in-Chief of the International Journal of Computer Science and System Analysis. He has guided 13 Ph.D. Students. His interests are cryptography and network security, key management and encryption techniques, sensor network security.

Saroj Kr. Biswas is currently associated with the National Institute of Technology (NIT) Silchar and has over ten years of experience. He did his B.Tech from Jalpaiguri Government Engineering College, M.Tech. from National Institute of Technical Teachers' Training and Research, Kolkata, and Ph. D from NIT Silchar. Dr. Biswas has supervised 2 Ph.D. students and presently guiding 6 Ph.D. students, published 36 research papers in peer-reviewed journals of national and international repute. His research interest areas are artificial intelligence, sentiment analysis, and image processing.

Inhalt
Predictive Analytics for real time Agriculture Supply Chain Management: A novel pilot study.- Analysis and Prediction of Crop Infestation Using Machine Learning.- ECG based Personal Identification System.- Explorations in Graph-based Ranking Algorithms for Automatic Text Summarization on Konkani Texts.- Demography Based Hybrid Recommender System for Movie Recommendations.- Holistic Recommendation System Framework For Health Care Programs.- A synthetic data generation approach using correlation coefficient and neural networks.- Cepstral Coefficient based Gender Classification using Audio signals.