Big Data Analytics for Cyber-Physical Systems
Machine Learning for the Internet of Things

Surveys novel use cases of data analytics methods for cyber-physical systems and Internet of Things (IoT) applications in smart cities

Guido Dartmann (Edited by), Houbing Song (Edited by), Anke Schmeink (Edited by)

9780128166376

Paperback, published 16 July 2019

396 pages
22.9 x 15.1 x 2.5 cm, 0.66 kg

Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT 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 IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science.

1. Data analytics and processing platforms in CPS2. Fundamentals of data analysis and statistics3. Density-based clustering techniques for object detection and peak segmentation in expanding data fields4. Security for a regional network platform in IoT5. Inference techniques for ultrasonic parking lot occupancy sensing based on smart city infrastructure6. Portable implementations for heterogeneous hardware platforms in autonomous driving systems7. AI-based sensor platforms for the IoT in smart cities8. Predicting energy consumption using machine learning9. Reinforcement learning and deep neural network for autonomous driving10. On the use of evolutionary algorithms for localization and mapping: Infrastructure monitoring in smart cities via miniaturized autonomous11. Machine learning-based artificial nose on a low-cost IoT-hardware12. Machine Learning in future intensive care—Classification of stochastic Petri Nets via continuous-time Markov chains13. Privacy issues in smart cities: Insights into citizens’ perspectives toward safe mobility in urban environments14. Utility privacy trade-off in communication systems15. IoT-workshop: Blueprint for pupils education in IoT16. IoT-workshop: Application examples for adult education

Subject Areas: Transport law [LNKT]