Smart Computing Techniques in Industrial IoT (eBook, PDF)

Redaktion: Chowdhary, Chiranji Lal; Wu, Yulei; Tripathy, Asis Kumar

• Format: PDF

Produktbeschreibung

The book provides a conceptual framework and roadmap for applications and research trends in Smart Computing Techniques in Industrial IoT. This volume aims to provide information on emerging fields of intelligent computing techniques with a particular emphasis on industrial IoT development and applications of artificial intelligence, deep learning techniques, computational intelligence methods, the Internet of Medical Things (IoMT), optimization techniques, blockchain, and cloud computing. It will be a useful guide for undergraduate and postgraduate students studying artificial intelligence, deep learning, industry 4.0, industry 5.0, smart cities, machine learning, deep learning computational intelligence, and edge/cloud computing.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 218
• Erscheinungstermin: 19. Oktober 2024
• Englisch
• ISBN-13: 9789819774944
• Artikelnr.: 72244985

Autorenporträt

Chiranji Lal Chowdhary is an Associate Professor in the School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, where he has been since 2010. He received a B.E. (CSE) from MBM Engineering College in Jodhpur, and M. Tech. (CSE) from the M.S. Ramaiah Institute of Technology, Bangalore. He received his Ph.D. VIT University, Vellore. His research interests span both computer vision and image processing, mainly through the application of image processing, computer vision, machine learning and computational intelligence. Prof. Chowdhary is the editor/co-editor of 10 books and has authored over 80 articles on computer science. He has also filed three patents based on his research. Asis Kumar Tripathy is a professor at the School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. He completed his Ph.D. from the National Institute of Technology, Rourkela, and MTech from IIIT Bhubaneswar, India. His research interests include wireless sensor networks, cloud computing, the Internet of Things, and advanced network technologies. He has several publications in refereed journals, reputed conferences, and book chapters. He is the associate editor of the International Journal of Computational Science and Engineering. Also, he is the reviewer of many IEEE Transactions, ACM journals, Elsevier, and Springer journals. Further, he also serves as the reviewer of international funding agencies such as the Swiss National Science Foundation. He has served as a program committee member in several international conferences of repute. He has also been involved in many professional and editorial activities. He is a senior member of IEEE and a member of ACM. Yulei Wu is an Associate Professor working across the Faculty of Engineering and the Bristol Digital Futures Institute, University of Bristol, UK. He received his Ph.D. degree in Computing and Mathematics and B.Sc. (1st Class Hons.) degree in Computer Science from the University of Bradford, UK, in 2010 and 2006, respectively. His research interests focus on digital twins and ethics-responsible decision making and their applications on future networks, connected systems, edge computing, and digital infrastructure. He has published 10 authored/edited monograph books and over 150 research papers in prestigious international journals and conferences. He is a Senior Member of the IEEE and the ACM.

Inhaltsangabe

CIRSH: Building Critical Infrastructure model and Real-Time applications towards sustainable goals in Smart and Secured Healthcare systems using IIoT.- Blockchain And IOT Integration For Financial Sector Revolution.- Neural Networks for Cloud-Based Industrial Internet of Things.- Deep Learning approach towards Green IIOT.- Deep Learning Approach towards Green IIOT.- Introduction to Industrial IoT and Smart Computing Techniques.- Optimization of IIoT Wireless Communications using Interference Analysis.- Green Industrial Internet of Things: An Extensive Survey on Recycling Strategies for Greener Future of Industrial Operations.- AI-based Cybersecurity opportunities & issues on IIoT.- Sustainable and smart healthcare based IIoT tools.- Contribution of Python to Improving Efficiency in Artificial Intelligence and Advancing Automation Capabilities.- Industry 4.0: The Role of Industrial IoT, Big Data, AR/VR, and Blockchain in the Digital Transformation.