Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, Io T gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between Io T technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple Io T applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for Io T in schools, new courses and concepts for universities and adult education on Io T and data science. – Bridges the gap between Io T, CPS, and mathematical modelling- Features numerous use cases that discuss how concepts are applied in different domains and applications- Provides "best practices", "winning stories" and "real-world examples" to complement innovation- Includes highlights of mathematical foundations of signal processing and machine learning in CPS and Io T
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