Multiple thermal sensor array fusion towards enabling privacy-preserving human monitoring applications

Naser, A. ORCID: 0000-0001-5969-1756, Lotfi, A. ORCID: 0000-0002-5139-6565 and Zhong, J., 2022. Multiple thermal sensor array fusion towards enabling privacy-preserving human monitoring applications. IEEE Internet of Things Journal. ISSN 2327-4662

1518024_Lotfi.pdf - Post-print

Download (5MB) | Preview


Human-centric applications of a single Thermal Sensor Array (TSA) have performed extremely well in many areas. However, most of these works have not yet reached the real applicability stage of the Internet of Things (IoT) applications. The main limitation of deploying such systems on a large scale is the challenge of fusing multiple TSAs to cover a wide inspection area, e.g. smart homes, hospitals and many other domestic environments. On the other hand, objects that appear in the low-resolution thermal images acquired from TSA have low intra-class variations and high inter-class similarities, making the identification of the overlapping regions through matching a comparable template image in multiple images very difficult. This paper proposes a motion-based approach to fuse multiple TSAs and learn the domestic environment layout to enable further human-centred IoT applications to run in the cloud. Besides, a privacy-improvement on utilising these sensors in IoT applications is proposed. The proposed approach is evaluated with comprehensive experiments on different sensor placements and domestic environment conditions. This paper shows an average performance of 92.5% accuracy using various machine learning techniques and use case scenarios.

Item Type: Journal article
Publication Title: IEEE Internet of Things Journal
Creators: Naser, A., Lotfi, A. and Zhong, J.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10 February 2022
ISSN: 2327-4662
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions: Schools > School of Science and Technology
Record created by: Jeremy Silvester
Date Added: 17 Feb 2022 13:13
Last Modified: 02 Sep 2022 08:28

Actions (login required)

Edit View Edit View


Views per month over past year


Downloads per month over past year