2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City

2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City
Author: Mohammed Atiquzzaman
Publisher: Springer Nature
Total Pages: 1314
Release: 2021-12-09
Genre: Technology & Engineering
ISBN: 9811674663

This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City

2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City
Author: Mohammed Atiquzzaman
Publisher: Springer Nature
Total Pages: 1157
Release: 2022-01-01
Genre: Technology & Engineering
ISBN: 9811674698

This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Smart Grids as Cyber Physical Systems, 2 Volume Set

Smart Grids as Cyber Physical Systems, 2 Volume Set
Author: O. V. Gnana Swathika
Publisher: John Wiley & Sons
Total Pages: 791
Release: 2024-04-29
Genre: Technology & Engineering
ISBN: 1394261705

Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security of supervisory control and data acquisition (SCADA) systems, offering clarity on specific operating and security issues that may arise that deteriorate the overall operation and efficiency of smart grid systems. It also provides techniques to monitor and protect systems, as well as aids for designing a threat-free system. This title discusses how artificial intelligence (AI) may be extensively deployed in the prediction of energy generation, electric grid-related line loss prediction, load forecasting, and for predicting equipment failure prevention. It also discusses power generation systems, building service systems, and explores advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms. Additionally, we will explore research contribution of experts in CPS infrastructure systems, incorporating sustainability by embedding computing and communication in day-to-day smart grid applications. This book will be of immense use to practitioners in industries focusing on adaptive configuration and optimization in smart grid systems. Through case studies, it offers a rigorous introduction to the theoretical foundations, techniques, and practical solutions CPS offers. Building CPS with effective communication, control, intelligence, and security is discussed from societal and research perspectives and a forum for researchers and practitioners to exchange ideas and achieve progress in CPS is provided by highlighting applications, advances, and research challenges. This book offers a comprehensive look at ICS cyber threats, attacks, metrics, risk, situational awareness, intrusion detection, and security testing, providing a valuable reference set for current system owners who wish to configure and operate their ICSs securely.

Big Data Analytics in Intelligent IoT and Cyber-Physical Systems

Big Data Analytics in Intelligent IoT and Cyber-Physical Systems
Author: Nonita Sharma
Publisher: Springer Nature
Total Pages: 312
Release: 2023-11-04
Genre: Technology & Engineering
ISBN: 9819945186

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 IoT 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.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
Author: John Macintyre
Publisher: Springer Nature
Total Pages: 999
Release: 2021-11-02
Genre: Computers
ISBN: 3030895114

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Proceedings of the International Conference on Big Data, IoT, and Machine Learning

Proceedings of the International Conference on Big Data, IoT, and Machine Learning
Author: Mohammad Shamsul Arefin
Publisher: Springer Nature
Total Pages: 784
Release: 2021-12-03
Genre: Technology & Engineering
ISBN: 9811666369

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Big Data Analytics for Internet of Things

Big Data Analytics for Internet of Things
Author: Tausifa Jan Saleem
Publisher: John Wiley & Sons
Total Pages: 402
Release: 2021-04-20
Genre: Mathematics
ISBN: 1119740754

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.

Social Sensing

Social Sensing
Author: Dong Wang
Publisher: Morgan Kaufmann
Total Pages: 232
Release: 2015-04-17
Genre: Computers
ISBN: 0128011319

Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book

Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)

Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)
Author: Rajiv Misra
Publisher: Springer Nature
Total Pages: 362
Release: 2021-09-29
Genre: Computers
ISBN: 3030824691

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.