Artificial Intelligence for Sustainable Applications (Artificial Intelligence and Soft Computing for Industrial Transformation) - Hardcover

Über die Autorin bzw. den Autor

K. Umamaheswari, PhD, is a professor and head with 27 years of experience in the Department of Information Technology at PSG College of Technology, Coimbatore, India.

B. Vinoth Kumar, PhD, is an associate professor with 19 years of experience in the Department of Information Technology at PSG College of Technology, Coimbatore, India.

S. K. Somasundaram, PhD, is an assistant professor in the Department of Information Technology, PSG College of Technology, Coimbatore, India.

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The objective of this book is to leverage the significance of artificial intelligence in achieving sustainable solutions using interdisciplinary research through innovative ideas.

With the advent of recent technologies, the demand for Information and Communication Technology (ICT)-based applications such as artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), health care, data analytics, augmented reality/virtual reality, cyber-physical systems, and future generation networks, has increased drastically. In recent years, artificial intelligence has played a more significant role in everyday activities. While AI creates opportunities, it also presents greater challenges in the sustainable development of engineering applications. Therefore, the association between AI and sustainable applications is an essential field of research. Moreover, the applications of sustainable products have come a long way in the past few decades, driven by social and environmental awareness, and abundant modernization in the pertinent field. New research efforts are inevitable in the ongoing design of sustainable applications, which makes the study of communication between them a promising field to explore.

This book highlights the recent advances in AI and its allied technologies with a special focus on sustainable applications. It covers theoretical background, a hands-on approach, and real-time use cases with experimental and analytical results.

Audience

AI researchers as well as engineers in information technology and computer science.