Perception of human beings has evolved from natural biosensor to powerful sensors and sensor networks. In sensor networks, trillions of devices are interconnected and sense a broad spectrum of contexts for human beings, laying the foundation of Internet of Things (Io T). However, sensor technologies have several limitations relating to deployment cost and usability, which render them unacceptable for practical use. Consequently, the pursuit of convenience in human perception necessitates a wireless, sensorless and contactless sensing paradigm.
Recent decades have witnessed rapid developments in wireless sensing technologies, in which sensors detect wireless signals (such as acoustic, light, and radio frequency) originally designed for data transmission or lighting. By analyzing the signal measurements on the receiver end, channel characteristics can be obtained to convey the sensing results. Currently, significant effort is being devoted to employing the ambient Wi-Fi, RFID, Bluetooth, Zig Bee, and television signals for smart wireless sensing, eliminating the need for dedicated sensors and promoting the prospect of the Artificial Intelligence of Things (AIo T).
This book provides a comprehensive and in-depth discussion of wireless sensing technologies. Specifically, with a particular focus on Wi-Fi-based sensing for understanding human behavior, it adopts a top-down approach to introduce three key topics: human detection, localization, and activity recognition. Presenting the latest advances in smart wireless sensing based on an extensive review of state-of-the-art research, it promotes the further development of this area and also contributes to interdisciplinary research.
Inhoudsopgave
Chapter 1. Wireless Sensing Overview.- Chapter 2. Understanding of Channel State Information.- Chapter 3. Passive Human Detection with Wi-Fi.- Chapter 4. Passive Detection of Moving Targets with Dynamic Speed using Wi-Fi.- Chapter 5.’Passive Detection of Moving and Stationary Human with Wi-Fi’.- Chapter 6.’Decimeter-Level Passive Human Tracking with Multiple Wi-Fi Links’.- Chapter 7.’Decimeter-Level Passive Human Tracking with a Single Wi-Fi Link’.- Chapter 8. Inferring Motion Direction with Wi-Fi.- Chapter 9. Human Gesture Recognition with Wi-Fi.- Chapter 10. Human Gait Recognition with Wi-Fi.- Chapter 11. Research Summary and Future Directions.
Over de auteur
Zheng Yang is an associate professor at the School of Software and BNRist, Tsinghua University. He holds a BE degree from Tsinghua University, and a Ph D degree from Hong Kong University of Science and Technology. His research interests include Internet of Things, mobile computing, pervasive computing, industrial internet, smart city, etc. He is the author and co-author of 3 books and over 100 papers published in leading journals and conferences. Zheng received the China National Natural Science Award (2011). He is a senior member of IEEE and a member of ACM.
Kun Qian is a post-doctoral researcher in the Department of Electrical and Computer Engineering, University of California San Diego. He received his Ph.D in 2019 at the School of Software, Tsinghua University. He received his B.E. in 2014 in Software Engineering from School of Software, Tsinghua University. His research interests include mobile computing and wireless sensing, etc. He has published over 20 papers in competitive conferences and journals.
Chenshu Wu is an assistant professor at the University of Hong Kong. He is also the Chief Scientist at Origin Wireless Inc. His research focuses on wireless AIo T systems at the intersection of wireless sensing, ubiquitous computing, and the Internet of Things. He has published two books, over 60 papers in prestigious conferences and journals, and over 40 patents. His research has been commercialized as products, including Link Sys Aware that won the CES 2020 Innovation Award, HEX Home that won CES 2021 Innovation Award, and Origin Health Remote Patient Monitoring that won CES 2021 Best of Innovation Award. He holds BS and Ph D degrees in Computer Science both from Tsinghua University.
Yi Zhang is currently working toward his Ph D degree at the School of Software in Tsinghua University. Prior to that, he received his BE degree from the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, in 2017. His research interests include wireless sensing, mobile computing, and machine learning. He is the author and co-author of over 6 papers published in leading journals and conferences.
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