Zhang, Jin, Wei, Bo and Cheng, Jun (2020) HARaaS: HAR as a service using wifi signal in IoT-enabled edge computing: poster abstract. In: SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems. ACM, New York, pp. 681-682. ISBN 9781450375900
Full text not available from this repository. (Request a copy)Abstract
Human activity recognition (HAR) is an important component in context awareness IoT applications such smart home, smart building etc. With the proliferation of WiFi-integrated devices, researchers exploit WiFi signals to recognize various human activities. In this work, we introduce a HAR as a Service (HARaaS) model for activity recognition services applied in IoT areas. HARaaS proposes a novel edge computing model in the concept of the Sensing as a Service (S2aaS) architecture to offer accurate and real-time activities recognition services with good energy efficiency. HARaaS distributes the resource-hungry computing workload i.e. training recognition model to edge terminals, and exploits the built-in intelligence of IoT devices. A WiFi-based activity recognition service is designed following the HARaaS architecture, and the lightweight machine learning and deep learning model are incorporated in the service for accurate activity recognition. Experiments are conducted and demonstrate the service achieves an activity recognition accuracy of 95% with extremely low latency and high energy efficiency.
Item Type: | Book Section |
---|---|
Uncontrolled Keywords: | WiFi, CSI, human activity recognition, IoT, edge computing |
Subjects: | G400 Computer Science |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | John Coen |
Date Deposited: | 09 Dec 2020 12:19 |
Last Modified: | 09 Dec 2020 12:19 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/44953 |
Downloads
Downloads per month over past year