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Robust Occupancy Inference with Commodity WiFi

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 occupan...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/WiMOB.2016.7763228

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Institution:
University of Oxford
Oxford college:
Keble College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
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Grant:
NRF2013EWT-EIRP04-012
SinBerBEST Program
NRF2011NRF-CRP001-090
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
WiMob 2016: 12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications Journal website
Host title:
WiMob 2016: 12th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
Publication date:
2016-12-01
Acceptance date:
2016-08-01
DOI:
Source identifiers:
638857
Pubs id:
pubs:638857
UUID:
uuid:41a2f067-b4a4-4cab-b621-f0e044e52d14
Local pid:
pubs:638857
Deposit date:
2016-08-17

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