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(Nehru Institute of Engineering and Technology, India)
Dr. S. ARUNKUMAR currently working as Associate Professor in the Department of Electrical and Electronics Engineering, Nehru Institute of Engineering and Technology, Coimbatore. Graduated his B.E. degree in Electrical and Electronics Engineering from Sri Ramakrishna Institute of Technology in the year 2007. Completed his Masters in Embedded and Real Time Systems from Coimbatore Institute of Technology, Coimbatore in the year 2011. He holds a Ph.D. in Electrical Engineering, Anna University, Chennai in the year 2022. He has total 15 years of teaching experience. He has published 15 research papers in reputed national and international journals. He is an author of 7 books in the field of Mobile Computing, Distributed Computing architectures, Multimedia Communication, Artificial Intelligence, Machine Learning, Electronic Devices and Circuits Manual, Circuit Theory.
Artificial Intelligence and IoT for Intelligent Prediction and Decision Support in Real-World Application presents a comprehensive exploration of how Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming predictive analytics and intelligent decision-making across diverse application domains. The book covers fundamental concepts, machine learning and deep learning techniques, cloud and edge computing frameworks, explainable AI, and real-time data analytics for building intelligent prediction systems. Through twenty chapters, the book highlights practical applications in healthcare, transportation, electric vehicles, environmental monitoring, smart cities, agriculture, industrial automation, finance, energy management, and higher education. It demonstrates how AI-driven predictive models leverage historical and real-time data to improve forecasting accuracy, optimize resource utilization, automate decision-making, and enhance operational efficiency. The volume also discusses emerging technologies, implementation challenges, ethical considerations, and future research directions, making it a valuable reference for researchers, academicians, students, engineers, industry professionals, and policymakers interested in intelligent predictive systems and data-driven decision support.