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Article

Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

by 1,*,†, 1,†, 2 and 1
1
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
2
School of Informatics and Digital Engineering, Aston University, Birmingham B4 7ET, UK
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2021, 21(3), 988; https://doi.org/10.3390/s21030988
Received: 28 November 2020 / Revised: 9 January 2021 / Accepted: 21 January 2021 / Published: 2 February 2021
(This article belongs to the Section Internet of Things)
In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces. View Full-Text
Keywords: thermal images; activity recognition; 3D scene reconstruction; 3D thermal model; Internet of Things (IoT) thermal images; activity recognition; 3D scene reconstruction; 3D thermal model; Internet of Things (IoT)
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MDPI and ACS Style

Naik, K.; Pandit, T.; Naik, N.; Shah, P. Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging. Sensors 2021, 21, 988. https://doi.org/10.3390/s21030988

AMA Style

Naik K, Pandit T, Naik N, Shah P. Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging. Sensors. 2021; 21(3):988. https://doi.org/10.3390/s21030988

Chicago/Turabian Style

Naik, Kshirasagar, Tejas Pandit, Nitin Naik, and Parth Shah. 2021. "Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging" Sensors 21, no. 3: 988. https://doi.org/10.3390/s21030988

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