Nonita Sharma & Monika Mangla 
Big Data Analytics in Intelligent IoT and Cyber-Physical Systems [PDF ebook] 

Stöd


This book explores the complete system perspective, underlying theories, modeling, and applications of cyber-physical systems (CPS). Considering the interest of researchers and academicians, the editors present this book in a multidimensional perspective covering CPS at breadth. It covers topics ranging from discussion of rudiments of the system and efficient management to recent research challenges and issues. 


This book is divided into four sections discussing the fundamentals of CPS, engineering-based solutions, its applications, and advanced research challenges. The contents highlight the concept map of CPS including the latest technological interventions, issues, challenges, and the integration of CPS with Io T and big data analytics, modeling solutions, distributed management, efficient energy management, cyber-physical systems research, and education with applications in industrial, agriculture, and medical domains. This book is of immense interest to those in academia and industry. 

€160.49
Betalningsmetoder

Innehållsförteckning

An outline of Cyber-Physical System: Issues and Security Risks.- Classification of Vulnerabilities in Cyber Physical Systems: Approach, Security and Challenges.- Sensing and Communication Mechanisms for Advanced Robotics and Complex Cyber-Physical Systems.- Deep Learning-Based Anomaly Detection in Cyber-Physical System.- Security Issues and Privacy Challenges of Cyber-Physical System in Smart Healthcare Applications

Om författaren

Dr. Nonita Sharma is working as Associate Professor at Indira Gandhi Delhi Technical University for Women, New Delhi. She has more than 15 years of teaching experience. Her major area of interest includes data mining, bioinformatics, time series forecasting, and wireless sensor networks She has published several papers in the International/National Journals/Conferences and book chapters. She received several best paper awards for her research work at renowned international conferences. She has been awarded the Best Teacher Award in view of recognition of her contributions, achievements, and excellence in Computer Science & Engineering at NIT Jalandhar. She has been awarded Best Content Guru Award by Infosys twice. She is a member of IEEE and has been shortlisted in the Top 5 for IEEE Women Achiever Award. She is the reviewer of many peer-reviewed journals and contributed to academic research in terms of projects, papers, and patents.
Dr. Monika Mangla received her Ph.D. from the Thapar Institute of Engineering and Technology, India, in 2019. She is working as an Associate Professor in the Department of Information Technology at Dwarkadas J. Sanghvi College of Engineering, Mumbai. Her interest areas include Io T, cloud computing, algorithms and optimization, location modeling, and machine learning. She has published several research papers and book chapters (SCI and Scopus Indexed) with reputed publishers. She has also been associated with several journals of national and international repute as a reviewer. She has two patents applied to her credit. She is a life member of CSI and IETE. 
Dr. Subhash K Shinde has earned his Ph.D. in Computer Science and Engineering from Shri Guru Gobind Singhji Institute of Engineering and Technology, India. He has over 24 years of academic and research experience. His research areas include machine learning, computer networks, network security, data warehousing, and mining. He has also been guiding research scholars at the University of Mumbai, India. Currently, he is working as a Professor and vice-principal at Lokmanya Tilak College of Engineering (LTCo E), India. He has published numerous research papers at various reputed national/international conferences and journals (SCI and Scopus Indexed).

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Språk Engelska ● Formatera PDF ● Sidor 314 ● ISBN 9789819945184 ● Filstorlek 9.5 MB ● Redaktör Nonita Sharma & Monika Mangla ● Utgivare Springer Nature Singapore ● Stad Singapore ● Land SG ● Publicerad 2023 ● Nedladdningsbara 24 månader ● Valuta EUR ● ID 9230219 ● Kopieringsskydd Social DRM

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