Predictive Methods in Next-Generation Computing: An Approach Toward Sustainability - Tapa dura

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R. Sathiyaraj, PhD is an assistant professor in the Department of Computer Science and Engineering at GITAM University. He has authored two books, served as lead editor for two books, and published five patents and over 20 articles in refereed journals and international conferences. His research interests include machine learning, big data analytics, and intelligent systems.

Rajesh Kumar Dhanaraj, PhD is a professor at Symbiosis International University. He has contributed over 45 books on various technologies, 21 patents, and over 90 articles in various refereed journals and international conferences. His research interests include machine learning, cyber-physical systems, and wireless Sensor networks.

K. Arun Kumar, PhD is an assistant professor in the Department of Computer Science and Engineering at GITAM University. He has contributed over 15 articles to various reputed journals. His research focuses on wireless networks, data mining, deep learning, and big data.

Rutvij H. Jhaveri, PhD is an Associate Professor in the Department of Computer Science and Engineering at Pandit Deendayal Energy University. He has published more than 200 papers in a wide variety of areas in computer scienceand coedited four books. His research interests include software-defined networking, cybersecurity, and smart ecosystems.

A. Mohamed Abbas, PhD works in the IT Department at the University of Technology and Applied Sciences, Sultanate of Oman. He has published 23 research articles in reputed international journals and presented 16 papers in international Conferences. Additionally, he has registered four patents, one of which was granted. His research is focused on artificial intelligence, big data, Internet of Things, and machine learning.

De la contraportada

Predictive Methods in Next-Generation Computing is essential for anyone looking to understand how next-generation computing technologies are driving predictive models to create smarter, safer, and more sustainable solutions across diverse fields.

Computing technologies are significantly evolving in all sectors, aiming to provide an automated, energy-efficient solution for various real-world problems with an advanced predictive model. This book explores computing technologies in various domains and provides novel strategies and designs for a smart, secure, and sustained environment for the future. Predictive Methods in Next-Generation Computing provides a realistic overview of various computer technologies that have made drastic advances in the field of smart applications, resulting in smart agriculture, healthcare, traffic management, and sustainability. The book comprehensively covers predictive models using artificial intelligence, machine learning, and Internet of Things and considers these applications for various smart applications to create a safe, smart environment for everyone. The chapters include real-world case studies, giving readers a glimpse into the benefits of integrating technology into predictive analytics to make the practice more automated, energy-efficient, safe, and profitable.