Robust occupancy inference with commodity WiFi

Xiaoxuan Lu, Hongkai Wen, Han Zou, Hao Jiang, Lihua Xie, Niki Trigoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate occupancy information of indoor environments is one of the key prerequisites for many pervasive and context-aware services, e.g. smart building/home systems. Some of the existing occupancy inference systems can achieve impressive accuracy, but they either require labour-intensive calibration phases, or need to install bespoke hardware such as CCTV cameras, which are privacy-intrusive by default. In this paper, we present the design and implementation of a practical end-to-end occupancy inference system, which requires minimum user effort, and is able to infer room-level occupancy accurately with commodity WiFi infrastructure. Depending on the needs of different occupancy information subscribers, our system is flexible enough to switch between snapshot estimation mode and continuous inference mode, to trade estimation accuracy for delay and communication cost. We evaluate the system on a hardware testbed deployed in a 600m2 workspace with 25 occupants for 6 weeks. Experimental results show that the proposed system significantly outperforms competing systems in both inference accuracy and robustness.
Original languageEnglish
Title of host publication2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-8
Number of pages8
ISBN (Electronic)978-1-5090-0724-0
ISBN (Print)978-1-5090-0725-7
DOIs
Publication statusPublished - 5 Dec 2016
Event12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications - New York, United States
Duration: 17 Oct 201619 Oct 2016
https://conferences.computer.org/wimob2016/

Conference

Conference12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
Abbreviated titleWiMob 2016
CountryUnited States
CityNew York
Period17/10/1619/10/16
Internet address

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