This book features high-quality research papers presented at the International Conference on Intelligent Electrical Systems & Industrial Automation (IESIA 2025), organized by Department of Electrical Engineering, Electrical and Electronics Engineering, Institute of Engineering & Management, Kolkata, India during June 25 27, 2025. The volume presents diverse range of topics, including smart sensors, automation control algorithms, energy-efficient solutions, and real-time data analytics.

Presents recent research in intelligent electrical systems Discusses the outcomes of IESIA 2025, held in Kolkata, India during June 2025 Serves as a reference resource for researchers and practitioners in academia and industry

Autorentext

Sanjoy Mondal obtained his B.Tech. and M.Tech. degrees from the National Institute of Technology Durgapur in 2004 and 2006, respectively. In 2013, he completed his Ph.D. at the Indian Institute of Technology Guwahati, specializing in Intelligent Control, Autonomous Systems, Sliding Mode Control, Unmanned Aerial Vehicles, Coordination Control of Multi-Agent Systems, Air Traffic Control, and Power Electronics. Dr. Mondal furthered his research through post-doctoral stints at École de Technologie Supérieure in Montreal and Nanyang Technological University in Singapore. Presently, he serves as an Associate Professor at the Institute of Engineering and Management in Kolkata, India. Dr. Sanjoy Mondal has contributed significantly to his field. His research prowess is evident in his 50+ publications in reputable journals and conferences. His main research areas include intelligent network control, modern transportation system, electrical and power network and new product development.

 Vincenzo Piuri obtained his Ph.D. from the Polytechnic of Milan, Italy, in 1989 and has been a Full Professor at the University of Milan since 2000. Formerly, he held positions in Polytechnic of Milan, Italy, and at the University of Texas at Austin, USA. Dr. Piuri's research focuses on artificial and computational intelligence, spanning areas such as machine learning, image processing, and industrial applications. With an impressive publication history of over 400 papers in international journals, conference proceedings, books, and book chapters, he holds esteemed titles including Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. Currently serving as the IEEE Region 8 Director (2023-24), Dr. Piuri has held past leadership roles, including IEEE Vice President for Technical Activities (2015). His editorial contributions, including serving as Editor-in-Chief of the IEEE Systems Journal from 2013 to 2019, underscore his dedication to advancing the field of computer engineering.

João Manuel R. S. Tavares graduated from the Universidade do Porto, Portugal in 1992, holds M.Sc. and Ph.D. degrees from the same university. Having achieved his Habilitation in Mechanical Engineering in 2015, he is a Full Professor at the Department of Mechanical Engineering (DEMec) of the Faculdade de Engenharia da Universidade do Porto (FEUP) and serves as the Head of DEMec since June 2023. As a senior researcher at INEGI, he has co-edited over 80 books, authored 50 book chapters, and contributed to 650 articles in international and national journals and conferences. João Tavares has a significant editorial role in various journals and is a co-founder of the book series Lecture Notes in Computational Vision and Biomechanics by Springer. His extensive involvement in international conferences includes being the co-founder and co-chair of several conferences, emphasizing his influence in computational vision, medical imaging, biomechanics, and biomedical engineering.

Inhalt

Advancing the Performance of Deep Learning Models Using Bayesian Optimization.- Edge AI-Powered Real-Time Arrhythmia Detection.- Anomaly Detection in Intrusion Detection Systems.- Real Time Depression Prediction Using Machine Learning.- An Affordable Automated Greenhouse Management System for Accurate Farming in Resource-Limited Settings.- Optimizing Healthcare Solutions: Exploratory Data Analysis and Feature Engineering for Early Detection of Alzheimer's Disease using Machine Learning.- Leveraging Benefit Through Real Time Status Monitoring of TDBFP Lube Oil System.- IoT-Driven Smart Tourism Technologies and its Impact on Tourist Experiences.- Smart Learning Environments.- IOT for Smart Health Monitoring System.- Advancements in Li-Fi and Visible Light Communication for High-Speed Data Transmission.- Porous PDMS based Triboelectric Nanogenerator as a new energy technology and animal sound detection.- Connectivity Module for PV-IV Plotting Devices.- SolveIt.- Next-Generation Intrusion Detection System Using Advanced AI Techniques and Federated Learning.- Integrating Secure Multi-Party Computation with Blockchain Networks for Advanced Privacy Protection.- Analyzing the Impact of Cyclone Amphan on Mangrove Ecosystems Using Spectral Indices in Henry Island, Sundarbans.- AI-Driven Smart Water Resource Management.- Real-Time AI-driven IoT System for Sustainable Wildlife Monitoring.- Poaching Detection.- IoT Botnet Detection Using Random Forest and Behavioral Analysis.- Mitigating Noise in Big Data for Social Media.- Neurological Disease Severity Classification Using Keystrokes Dynamics.- AI-Driven Smart Traffic Management System: Dynamic Timing of Traffic Lights.- DeepGEx.- Development and Validation of a New Contingency Analysis Methodology Considering Tripping of Transmission Line.- Optimization of Energy Efficiency in Residential Buildings and Offices using Artificial Intelligence Methods.- Electric Vehicle Charging Systems.- A Novel Optimized Energy Detection for Cognitive Radio-Based IOT: A Throughput-Centric Approach.- Performance Analysis of Naïve Bayes, SVM, and Decision Tree for Disease Risk Prediction.- Mangrove Health Evaluation using Type-2 Fuzzy System in Henry Island, India.- Metaheuristic-Driven CNN-LSTM Model for Improved Cryptocurrency Closing Price Forecasting.- Customer segmentation using unsupervised machine learning.- Frequency Control of Microgrid using Simultaneous G2V-V2G mode of EV Fleet.- Cost Optimization Through Fuel Management in Coal-Fired Thermal Power Plants.