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Using RF Transmissions from IoT Devices for Occupancy Detection and Activity Recognition

Chetty, K; Li, W; Vishwakarma, S; Tang, C; Woodbridge, K; Piechocki, R; (2021) Using RF Transmissions from IoT Devices for Occupancy Detection and Activity Recognition. IEEE Sensors Journal 10.1109/JSEN.2021.3134895. (In press). Green open access

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Abstract

IoT ecosystems consist of a range of smart devices that generated a plethora of Radio Frequency (RF) transmissions. This provides an attractive opportunity to exploit already-existing signals for various sensing applications such as e-Healthcare, security and smart home. In this paper, we present Passive IoT Radar (PIoTR), a system that passively uses RF transmissions from IoT devices for human monitoring. PIoTR is designed based on passive radar technology, with a generic architecture to utilize various signal sources including the WiFi signal and wireless energy at the Industrial, Scientific and Medical (ISM) band. PIoTR calculates the phase shifts caused by human motions and generates Doppler spectrogram as the representative. To verify the proposed concepts and test in a more realistic environment, we evaluate PIoTR with four commercial IoT devices for home use. Depending on the effective signal and power strength, PIoTR performs two modes: coarse sensing and fine-grained sensing. Experimental results show that PIoTR can achieve an average of 91% in occupancy detection (coarse sensing) and 91.3% in activity recognition (fine-grained sensing).

Type: Article
Title: Using RF Transmissions from IoT Devices for Occupancy Detection and Activity Recognition
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/JSEN.2021.3134895
Publisher version: https://doi.org/10.1109/JSEN.2021.3134895
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Wireless Sensing Sensor, IoT devices, Gesture Recognition, Occupancy Detection
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10140360
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