Smart Cyber Physical Systems
Description
This book discusses the outcome of the ICSCPS 2024 conference proceedings which provide a comprehensive exploration of Smart Cyber-Physical Systems (CPS), delivering deep into the intersection of the physical and digital worlds. The book is a must-read for researchers, engineers, students, and professionals seeking to understand and harness the power of CPS in today's technology-driven landscape. This conference's main topics encompass CPS's foundational principles, from mathematical modeling and control theory to real-time systems and cyber-security. It unravels the intricacies of sensors and actuators, shedding light on their design and applications in various domains. With a focus on communication and networks, readers will gain insights into the critical aspects of data exchange and connectivity in CPS, including wireless communication, IoT integration, and network security.
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Persons
Dr. Ramesh Chandra Poonia is a professor at the Department of Computer Science, CHRIST (Deemed to be University), India. He holds a double Postdoctoral Fellowship, first from the Cyber-Physical Systems Laboratory Lab, Department of ICT and Natural Sciences, Norwegian University of Science and Technology - NTNU, Norway, and second fellowship on the Collaborative Project of Oakland University USA, and Imam University, Saudi Arabia. He obtained his Ph.D. in Computer Science from Banasthali University, Banasthali, India, in July 2013. He received his M.Tech. in DSE from Birla Institute of Technology and Science, Pilani, India. He has authored over 126 journal and conference articles and edited 11 books/conference proceedings. He is the main guest editor of more than 30 special issues of journals including Springer, Taylor and Francis, Inderscience, IGI Global, and Elsevier. He is an associate editor of the Journal of Sustainable Computing: Informatics and Systems, Elsevier.
Dr. Sugam Sharma is a senior data scientist and currently working as CSSM Principal Systems Architect for Center for Survey Statistics and Methodology, Iowa State University. His research interests include big data, cloud computing, multidimensional databases, GIS technology, sensor network, and smart home technology. Previously, he also has served as an assistant professor, software consultant for NAVTEQ Inc., and JAVA developer at Ames Laboratory, USA. Dr. Sharma also holds M.S. in Computer Science from Jackson State University, Mississippi, USA, and B.E. in Computer Science from Roorkee, India.
Prof. Ibrahim A. Hameed is a Professor and Head of Applied Robotics Research Group at the Department of Mechanical Engineering and Technology Management, Faculty of Science and Technology, Norwegian University of Life Sciences (NMBU), Norway. He is a Senior Member of the IEEE, serves as Secretary of the IEEE Norway Section, and is the former elected Chair of the IEEE Computational Intelligence Society (CIS) Norway Chapter. He holds two Ph.D. degrees: one in Industrial Systems and Information Engineering from Korea University, South Korea, and another in Mechanical Engineering from Aarhus University, Denmark. He has authored more than 120 peer-reviewed journal and conference papers. His current research interests focus on Artificial Intelligence, Machine Learning, Optimization, and Robotics.
Dr. Kamal Upreti is currently working as an associate professor in Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India. He completed his B.Tech. (Hons) Degree from UPTU, M. Tech. (Gold Medalist) from Galgotias University, PGDM (Executive) from IMT Ghaziabad, and Ph.D. from OPJ University in Department of Computer Science & Engineering. Now, he is doing Postdoc from National Taipei University of Business, TAIWAN funded by MHRD. He has published 50+ Patents, 40+ Books, 32+Magazine issues, and70+ Research papers in in various international conferences and reputed journals. His areas of interest are cyber-security, machine learning, health care, wireless networking, embedded system, and cloud computing.
Content
A Comprehensive Review of Machine Learning and Deep Learning Techniques for Cyberbullying Detection.- Integration of Software-Defined Vehicles and Automated Network Slicing for Advancing Sustainable Transportation.- Developing an Advanced Cybersecurity Framework and Blueprint: A Contemporary Approach to Counter Hacking through Reverse Engineering Techniques.- AI-Driven Radiomics for Early Detection of Gynaecological Cancers: A Multimodal Approach.- Assessing the Accuracy, Correlation, and Efficacy of Artificial Intelligence Generated Synthetic Data for Privacy Protection in Training Large AI Models.