HARaaS: HAR as a service using wifi signal in IoT-enabled edge computing: Poster abstract

2Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Zhang, J., Wei, B., & Cheng, J. (2020). HARaaS: HAR as a service using wifi signal in IoT-enabled edge computing: Poster abstract. In SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (pp. 681–682). Association for Computing Machinery, Inc. https://doi.org/10.1145/3384419.3430469

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free