Intelligent Systems for Sustainable Industrial Infrastructure

This book presents the select proceedings of the 4th International Conference on Intelligent Systems and Applications 2025. The theme of this conference is 'Intelligent Systems for Sustainable Industrial Infrastructure'. It covers the topics of intelligent systems in waste detection and environmental sustainability, underwater trash detection, wastewater management, crop and irrigation management, time series models, price forecasting and regression models, safety and wellbeing, smart and resilient construction, wireless sensor network and crack detection in concrete structures. The book is useful for researchers and professionals interested in the broad field of artificial intelligence and machine learning with applications to sustainable industrialization.

Comprises peer-reviewed proceedings of the conference ICISA 2025 Covers the latest research in intelligent systems for industrial infrastructure Enriches understanding by including contributions from leading experts in the field

Autorentext

Anand J Kulkarni holds a PhD in Artificial Intelligence (AI) based Distributed Optimization from Nanyang Technological University, Singapore, MS in AI from University of Regina, Canada. He worked as Postdoctoral Research Fellow at Odette School of Business, University of Windsor, Canada. Since 2021, he is working as Research Professor and Associate Director of the Institute of Artificial Intelligence at the MITWPU, Pune, India. His research interests include AI based Nature Inspired optimization algorithms, and self-organizing systems. Anand pioneered optimization methodologies such as cohort intelligence, ideology algorithm, expectation algorithm, socio evolution & learning optimization algorithm leader-advocate-believer based algorithm and snail homing & mating search algorithm. Dr. Anand has published over 120 research papers in peer-reviewed reputed journals, chapters and conferences along with 7 authored and 15 edited books. He has guided 6 doctoral, 10 master’s and over 60 UG students. Dr. Anand is the lead series editor for several reputed publishers. He is the recipient of the best paper award in IEEE ICNSC, Chicago, USA and 'Swatantryveer Savarakar Award' 2023 by ‘Pune Marathi Granthalay’, Pune for his Marathi book entitled 'Artificial Intelligencechya Watewar'.

Apoorva S Shastri holds a PhD in Optimization Algorithms and Applications from Symbiosis International (Deemed University), Master of Technology (M.Tech) in VLSI Design and Bachelor of Engineering in Electronics & Product Design Technology from R.T.M.N.U, Nagpur. She has also done a Diploma from the Govt. Polytechnic, Nagpur. She worked as a guest faculty at Centre for Development of Advanced Computing (C-DAC), Pune. Currently, she is a Research Assistant Professor at Institute of Artificial Intelligence at the MITWPU, Pune, India. Her research interests include optimization algorithms, VLSI design, multi-objective optimization, continuous, discrete, and combinatorial optimization, complex systems, manufacturing, and self-organizing systems. Dr. Apoorva developed socio-inspired optimization methodologies such as multi-cohort intelligence algorithm, expectation algorithm and LAB algorithm, and snail homing and mating search algorithm. Dr. Apoorva has published several research papers in peer reviewed journals, chapters, and conferences along with 1 authored and 5 edited books.

Hossein Bonakdari is an Associate Professor of Civil Engineering at the University of Ottawa, specializing in AI-driven hydrology, hydraulics, wildfire/flood modeling, and climate resilience. He has published over 310 papers and authored four books. Dr. Bonakdari develops advanced algorithms to extract insights from big datasets. His innovative work addresses pressing environmental challenges, including floods, droughts, and wildfires, while making significant contributions to both national and international research communities.

Inhalt

Encord YOLOV8 integration Solid Waste Detection for Environmental Sustainability.- Design and Analysis of Bladeless Wind Turbine at Low Wind Speed at Low Wind Speed.- Comparative Analysis of Deep Learning Models for Underwater Trash Detection: A Study of R-CNN, YOLO, SSD, and DeepLabv3+.- Artificial Intelligence in Wastewater Management: Opportunities, Challenges, and Emerging Trends.- Prediction of H2S Solubility in Ionic Liquids Using Ensemble Machine Learning Models.- Optimizing Agriculture: Integrating Advanced Algorithms for Crop and Irrigation Management.- Etc.