Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Localisation of Room Occupants in Home Environments using Unobtrusive Sensing Solutions

Version 1 : Received: 14 August 2021 / Approved: 16 August 2021 / Online: 16 August 2021 (12:13:28 CEST)

How to cite: Ekerete, I.; Nugent, C.; McLaughlin, J. Localisation of Room Occupants in Home Environments using Unobtrusive Sensing Solutions. Preprints 2021, 2021080333 (doi: 10.20944/preprints202108.0333.v1). Ekerete, I.; Nugent, C.; McLaughlin, J. Localisation of Room Occupants in Home Environments using Unobtrusive Sensing Solutions. Preprints 2021, 2021080333 (doi: 10.20944/preprints202108.0333.v1).

Abstract

This paper proposes the localisation of room occupants in home environments using Unobtrusive Sensing Solutions (USSs). The ability to localise room occupants in home environments can help in the objective monitoring of sedentary behaviour. While wearable sensors can provide tangible information on health and wellness, they have battery life issues and the inability to perform prolonged monitoring. This work uses heterogeneous USSs in the form of an Infrared Thermopile Array (ITA-64) thermal sensor and a Multi-Chirp Frequency Modulated Continuous Wave Mono-pulse (MC-FMCW-M) Radar sensor to monitor room occupants. Digital filters and background subtraction algorithms were used to process the thermal images gleaned from the ITA-64 thermal sensors. The MC-FMCW-M Radar sensor used multi-chirp and Doppler shift principles to estimate the exact location of the targeted room occupants. The estimated distances from the Radar Sensor were compared with ground truth values. Experimental results demonstrated the ability to identify thermal blobs of occupants present in the room at any particular time. Data analyses indicated no significant difference (p = 0.975) and a very strong positive correlation (r = 0.998) between the ground truth distance values and those obtained from the Radar Sensor.

Keywords

Unobtrusive Sensing; Radar sensor; Thermal Sensor; Localisation; Home Environment.

Subject

MATHEMATICS & COMPUTER SCIENCE, Information Technology & Data Management

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