When Deep Learning Meets Cyber-physical Systems

Abstract:

Cyber-Physical Systems have a broad range of application scenarios such as smart grids, intelligent transportation systems, smart manufacturing, supply chain management and healthcare systems. Various sensors are deployed in CPS to collect ambient data, which can be used to detect malicious behaviors, identify possible bugs and adjust policies to improve the system efficiency. In this talk, I will introduce recent advances in applying deep learning schemes in electricity-theft detection in smart grids and traffic flow prediction in transportation systems. Regarding to electricity-theft detection, we propose a novel electricity-theft detection method based on Wide & Deep Convolutional Neural Networks (CNN) model to detect electricity-theft. In particular, Wide & Deep CNN model consists of two components: 1) the Wide component that can capture the global features of 1-D electricity consumption data and 2) the Deep CNN component that can accurately identify the non-periodicity of electricity-theft and the periodicity of normal electricity usage based on two dimensional (2-D) electricity consumption data. Extensive experiments based on realistic dataset show that Wide & Deep CNN model outperforms other existing methods. Regarding to traffic flow prediction, we propose a Deep and Embedding Learning Approach (DELA) to analyze the traffic flow in terms of travel time. Our DELA can analyze the traffic flow in a fine-grained manner. Realistic experimental results show that DELA outperforms existing approaches in terms of prediction accuracy. This talk will also discuss the future directions in this promising area.

Biography:

Hong-Ning Dai is currently with Faculty of Information Technology at Macau University of Science and Technology as an associate professor. He obtained the Ph.D. degree in Computer Science and Engineering from Department of Computer Science and Engineering at the Chinese University of Hong Kong. He also holds visiting positions at Department of Computer Science and Engineering of the Hong Kong University of Science and Technology, School of Electrical Engineering and Telecommunications of the University of New South Wales, respectively. His research interests include cyber-physical systems, wireless networks and Big Data Analytics. He is the winner of Bank of China (BOC) Excellent Research Award of Macau University of Science and Technology in 2015. He has published more than 70 peer-reviewed papers in refereed journals and conferences. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE).