Proceedings of the 5th International Conference on Big Data Analytics for Cyber-Physical System in Smart City—Volume 1
BDCPS 2023, December 28–29, Fuyang, China
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Beschreibung
This book gathers a selection of peer-reviewed papers presented at the 5th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2023) conference, held in Fuyang, China, on December 28–29. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of 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.
This book gathers a selection of peer-reviewed papers presented at the 5th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2023) conference, held in Fuyang, China, on December 28–29. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of 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.
Includes papers presented at the BDCPS 2023 conference Covers the latest advances made in the field of machine learning and big data analytics methods Offers a valuable resource for all researchers and professionals interested in big data
Autor*in
Mohammed Atiquzzaman
Themen in »Proceedings of the 5th International Conference on Big Data Analytics for Cyber-Physical System in Smart City—Volume 1«
Big Data Analytics Cyber-Physical System Smart City Machine Learning BDCPS 2023 Internet of Things (IoT) Network Intelligence Intelligent Sensor Placement Object-Linked Information Integration Multidimensional Complex System