IoT-based occupancy detection system in indoor residential environments

IoT-based occupancy detection system in indoor residential environments We propose an Internet of Things (IoT)-based occupancy detection system using change patterns of dust concentrations such as particulate matter. Previous research studies have used other features such as visual, chemical, or acoustic data. In this paper, the point extraction algorithm is proposed to construct triangular shapes, and their properties are used to detect occupancy in an indoor environment. For the verification of the proposed method, an IoT-based system is implemented for the occupancy detection in real residential environments. Finally, we analyze the experimental results, and compare them with those of other conventional approaches from a qualitative point of view. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Building and Environment Elsevier

IoT-based occupancy detection system in indoor residential environments

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0360-1323
D.O.I.
10.1016/j.buildenv.2018.01.043
Publisher site
See Article on Publisher Site

Abstract

We propose an Internet of Things (IoT)-based occupancy detection system using change patterns of dust concentrations such as particulate matter. Previous research studies have used other features such as visual, chemical, or acoustic data. In this paper, the point extraction algorithm is proposed to construct triangular shapes, and their properties are used to detect occupancy in an indoor environment. For the verification of the proposed method, an IoT-based system is implemented for the occupancy detection in real residential environments. Finally, we analyze the experimental results, and compare them with those of other conventional approaches from a qualitative point of view.

Journal

Building and EnvironmentElsevier

Published: Mar 15, 2018

References

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