Design and Development of Efficient Energy Systems (Artificial Intelligence and Soft Computing for Industrial Transformation) - Hardcover

Tripathi, Suman Lata

Hardcover

ISBN 10: 1119761638 ISBN 13: 9781119761631

Publisher: Wiley-Scrivener, 2021

Synopsis

There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.

This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.

The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications.  Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library. 

About this title

About the Author

Suman Lata Tripathi, PhD, is a professor at Lovely Professional with more than seventeen years of experience in academics. She has published more than 45 research papers in refereed journals and conferences. She has organized several workshops, summer internships, and expert lectures for students, and she has worked as a session chair, conference steering committee member, editorial board member, and reviewer for IEEE journals and conferences. She has published one edited book and currently has multiple volumes scheduled for publication, including volumes available from Wiley-Scrivener.

Dushyant Kumar Singh, is an assistant professor and Head of Embedded Systems Domain at Lovely Professional University. With a masters degree from Punjab Engineering College, University of Technology, Chandigarh, he has several years of industrial experience and more than ten years of teaching experience.

Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has almost ten years of teaching, research and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching.

P. Raja is currently working as an assistant professor at Lovely Professional University. His expertise is in VLSI and embedded systems. He has more than 14 years of experience with 5 years in embedded industry. He has 14 publications in UGC-approved and other reputable journals. He also has 10 patents to his credit.

From the Back Cover

Covering the concepts and fundamentals of efficient energy systems, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple industries, for both the engineer and the student.

There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.

This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.

The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.

This outstanding new volume:

• Handles the fundamentals of system design including the concept of energy saving aspects at different levels
• Is useful for all engineering students for learning the fundamentals of system design and automation with machine learning and IoT
• Will be helpful for researchers and designers to find out key parameters for future projects and current applications

Audience:

Engineers and scientists across many fields, including petroleum and process engineers, chemical engineers, electrical engineers working with power systems, and students at the university and post-graduate level studying energy topics

From the Inside Flap

Covering the concepts and fundamentals of efficient energy systems, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple industries, for both the engineer and the student.

There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.

This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.

The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.

This outstanding new volume:

• Handles the fundamentals of system design including the concept of energy saving aspects at different levels
• Is useful for all engineering students for learning the fundamentals of system design and automation with machine learning and IoT
• Will be helpful for researchers and designers to find out key parameters for future projects and current applications

Audience:

Engineers and scientists across many fields, including petroleum and process engineers, chemical engineers, electrical engineers working with power systems, and students at the university and post-graduate level studying energy topics

Edition details

• Publisher: Wiley-Scrivener
• Publication date: 2021
• Language: English
• ISBN 10: 1119761638
• ISBN 13: 9781119761631
• Binding: Hardcover
• Edition number: 1
• Number of pages: 384