Intelligent Techniques for Cyber-Physical Systems covers challenges, opportunities, and open research directions for cyber-physical systems (CPS). It focuses on the design and development of machine learning and metaheuristics-enabled methods as well as blockchain for various challenges like security, resource management, computation offloading, trust management, and others in edge, fog, and cloud computing, Internet of Things (IoT), Internet of Everything (IoE) and smart cities. It also includes the design and analysis of deep learning-based models, sensing technologies, metaheuristics, and blockchain for complex real-life systems for CPS.
- Offers perspectives on the research directions in cyber-physical systems (CPS)
- Provides state-of-the-art reviews on intelligent techniques, machine learning, deep learning, and reinforcement learning-based models for cloud-enabled IoT environment
- Discusses intelligent techniques for complex real-life problems in different CPS scenarios
- Reviews advancements in blockchain technology and smart cities
- Explores machine learning-based intelligent models for combinatorial optimization problems
The book is aimed at researchers and graduate students in computer science and engineering and electrical and electronics engineering.
About the Author: Dr. Mohammad Sajid is a committed academician with several years of extensive experience in teaching and administration at a leading academic institution. Currently, he is working as an Assistant Professor in the Department of Computer Science at Aligarh Muslim University, India. He has completed his Ph.D., M. Tech., and MCA degrees from the School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi. His research interests include Parallel and Distributed Computing, Cloud Computing, Bio-Inspired Computation, and combinatorial optimization problems. He has published numerous research papers in international conferences and journals of repute (including IEEE, Elsevier, Springer, Interscience, Wiley, Taylor & Francis, IGI Global, etc.). He published one patent and was awarded a research startup grant in 2017 from University Grants Commission (UGC), India.
Dr. Anil Kumar Sagar is currently working as a Professor in the Department of Computer Science and Engineering at Sharda University Greater Noida, India. He did his B. E. and M. Tech, Ph.D. in Computer Science. Before joining Sharda University, he worked as a Professor at the School of Computing Science and Engineering, Galgotias University, India. His research interests include Mobile Ad hoc Networks and Vehicular Ad hoc Networks, IoT, and Artificial Intelligence. He has published numerous papers in international journals and conferences, including IEEE and Springer. He has received a Young Scientist Award for the year 2018-19 from the Computer Society of India and the Best Faculty Award for the years 2006 and 2007 from SGI, Agra.
Dr. Jagendra Singh is a committed academician with extensive experience in teaching and research positions at leading academic institutions. He received his Ph.D. in Computer science from Jawaharlal Nehru University, New Delhi. Currently, he works as an Associate professor in the School of Computer Science, Engineering and Technology, Bennett University, Greater Noida. He had worked with the National Institute of Technology (NIT), Calicut, Kerala. He has published several research articles in reputed journals and conferences and published many patents. He is an active reviewer of many reputed journals. His area of interest is Natural Language Processing (Information Retrieval System, Recommendation System, Sentiment Analysis) and Machine Learning (Deep Learning, Neural Network, and Data Analytics).
Dr. Osamah Ibrahim Khalaf is a Senior Engineering and Telecommunications Assistant Professor at Al-Nahrain University/College of Information Engineering. He holds ten years of university-level teaching experience in computer science and network technology and has a strong CV for research activities in computer science and information technology projects. Dr. Osamah has had many published articles indexed in (ISI/Thomson Reuters /SCI) and participated in and presented at numerous international conferences. He holds patents and has received several medals and awards due to his innovative work and research activities. He has good skills in software engineering, including experience with .Net, SQL development, database management, mobile applications design, mobile techniques, Java development, android development, IOS mobile development, Cloud system and computations, and website design. His brilliant personal strengths are in a Highly self-motivated team player who can work independently with minimum supervision, having strong leadership skills, and an outgoing personality. In 2004, he got his B.Sc. in software engineering from Al-Rafidain University College in Iraq. Then in 2007, he got his M. Sc. in computer engineering from Belarussian National Technical University. After that, in 2017, he earned his Ph.D. in computer networks from the faculty of computer systems and software engineering University Malaysia, Pahang. He has overseas work experience at Binary University in Malaysia and University Malaysia Pahang.
Dr. Mukesh Prasad is a Senior Lecturer at the School of Computer Science in the Faculty of Engineering and IT at the University of Technology Sydney who has made substantial contributions to machine learning, artificial intelligence, and the Internet of things. His research interests include big data, computer vision, brain-computer interface, and evolutionary computation. He is also working in the evolving and increasingly important field of image processing, data analytics, and edge computing, which promise to pave the way for new applications and services in Healthcare, biomedical, agriculture, smart cities, education, marketing, and finance. His research has appeared in numerous prestigious journals, including IEEE/ACM Transactions, and at conferences, and he has written more than 120 research papers. He started his academic career as a lecturer with UTS in 2017. He became a core member of the University's world-leading Australian Artificial Intelligence Institute (AAII), which has the vision to develop theoretical foundations and advanced technologies for AI and to drive progress in related areas. His research is backed by industry experience, specifically in Taiwan, where he was the principal engineer (2016-17) at the Taiwan Semiconductor Manufacturing Company (TSMC). He developed new algorithms for image processing and pattern recognition using machine learning techniques. He was also a postdoctoral researcher leading a Big Data and computer vision team at National Chiao Tung University, Taiwan (2015). He received an MCA degree from the School of Computer and Systems Sciences at the Jawaharlal Nehru University in New Delhi, India (2009), and a Ph.D. from the Department of Computer Science at the National Chiao Tung University in Taiwan (2015).
