This book presents high-quality research papers presented at Congress on Smart Computing Technologies (CSCT 2024) organized by Soft Computing Research Society (SCRS), held at National Institute of Technology Sikkim from 14 to 15 December 2024. The book extensively covers recent research in algorithms for smart computing, AI and machine learning in smart computing, edge computing algorithms, adversarial networks and autoencoders, data visualization, data mining, data analytics, machine learning, game theory, high-performance computing, mobile and ubiquitous platforms for smart environments, cloud/edge/fog computing technologies for smart systems, Internet of Things (IoT) and industrial IoT technologies for smart systems, smart device and hardware, security, privacy, and economics in smart environments, big data, healthcare informatics, smart precision agriculture, smart transportation, social network analysis, and humancomputer interaction. The book is presented in two volumes

Presents research works in the field of smart computing technologies Provides original works presented at CSCT 2024 held in Ravangla, India Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Prof. Mukesh Saraswat's profile: Prof. Mukesh Saraswat is a Professor and Associate Dean (Innovation) at Jaypee Institute of Information Technology (JIIT), Noida, India. Prof. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 20 years of teaching and research experience. He has guided 04 Ph.D. students and presently guiding 04 Ph.D. students. He has published more than 80 journal and conference papers in the areas of image processing, pattern recognition, and soft computing. He was part of a successfully completed project funded by SERB, New Delhi on image analysis. He has been an active member of many organizing committees for various conferences and workshops. He is also a Faculty In-charge of the Jaypee Youth Club at JIIT, Noida. He is also a guest editor of the Array, Journal of Swarm Intelligence, SN Computer Science, and Journal of Intelligent Engineering Informatics. He is one of the General Chairs of the International Conference on Data Science and Applications. He is also an Advisory Board Member of the Journal MethodsX. He is an active member of CSI and SCRS Professional Bodies.

Dr. Abhishek Rajan received B.Tech. degree in electrical and electronics engineering from Biju Patnaik University of Technology Odisha in 2008 and M.Tech. degree in power and energy systems from National Institute of Technology Silchar, Assam-India in 2013. In 2018 he received his Ph.D. in electrical engineering from National Institute of Technology Silchar, Assam, India. From 2008 to 2009 he works as Lecturer in IACR Engineering College Rayagada, Odisha, in the Department of EEE. From 2009 to 2011 he works as Lecturer in Gandhi Engineering College Bhubaneswar, Odisha, in the Department of EEE. From 2013 to 2014 he served as Assistant Professor at Royal Group of Institution Guwahati, Assam. Since 2018, he is serving as Assistant Professor at NIT Sikkim, in the Department of EEE. He as published number of research article in various state-of-the-art literatures. His area of interest includes optima power flow, reactive power management, RE integration.

Dr. Antorweep Chakravorty is Associate Professor at the University of Stavanger. His current research and development work is in the field of applied blockchains, big data, large-scale machine learning, and data privacy. He has an interest in real-world problems, especially development of privacy-enabled data-driven services in smart energy, healthcare, and smart city domains. Antorweep completed his Ph.D. in 2015 with a thesis on Privacy Preserving Big Data Analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching, and supervision.

Inhalt

Plant Disease Detection using Deep Learning: A Focus on Pathogen-Based Classification.- NR2-A Novel Graph Based Encryption Algorithm.- Smart Computing Approaches to Adaptive Ensemble Learning for Detecting APT Threats through Network Behavior Anomalies.- Building a model of Physical Activity Recognition using Hierarchical AutoML.- Intelligent post-operative room Systems: A Cost-Effective Design for Enhanced Patient Care in Resource-Limited Settings.- United Against Hate: A Deep Learning Ensemble Approach for Robust Hate Speech and Offensive Language Detection.- Harnessing Grey Wolf Optimization for Enhanced Deep Learning CNN in Rheumatoid Arthritis X-ray Analysis.- Enhancing Anomaly Detection in IoT Systems with an Ensemble of Machine Learning Algorithms.- Harnessing Machine Learning for Accurate Water Quality Monitoring and Prediction.- Anomaly Detection in DC Distribution Systems: A Wavelet and Autoencoder-based Method.-Etc.