Cooperative Networked PIR Detection System for Indoor Human Localization
Pyroelectric Infrared (PIR) sensors are low-cost, low-power, and highly reliable sensors that have been widely used in smart environments. Indoor localization systems can be categorized as wearable and non-wearable systems, where the latter are also known as device-free localization systems. Since t...
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doaj-cfce2f8bfea54627a98452e9e2c7f1612021-09-26T01:23:21ZengMDPI AGSensors1424-82202021-09-01216180618010.3390/s21186180Cooperative Networked PIR Detection System for Indoor Human LocalizationChia-Ming Wu0Xuan-Ying Chen1Chih-Yu Wen2William A. Sethares3Department of Electrical Engineering, National Chung Hsing University, Taichung 402, TaiwanDepartment of Electrical Engineering, National Chung Hsing University, Taichung 402, TaiwanDepartment of Electrical Engineering, Bachelor Program of Electrical Engineering and Computer Science, Innovation and Development Center of Sustainable Agriculture (IDCSA), National Chung Hsing University, Taichung 402, TaiwanDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USAPyroelectric Infrared (PIR) sensors are low-cost, low-power, and highly reliable sensors that have been widely used in smart environments. Indoor localization systems can be categorized as wearable and non-wearable systems, where the latter are also known as device-free localization systems. Since the binary PIR sensor detects only the presence of a human motion in its field of view (FOV) without any other information about the actual location, utilizing the information of overlapping FOV of multiple sensors can be useful for localization. In this study, a PIR detector and sensing signal processing algorithms were designed based on the characteristics of the PIR sensor. We applied the designed PIR detector as a sensor node to create a non-wearable cooperative indoor human localization system. To improve the system performance, signal processing algorithms and refinement schemes (i.e., the Kalman filter, a Transferable Belief Model, and a TBM-based hybrid approach (TBM + Kalman filter)) were applied and compared. Experimental results indicated system stability and improved positioning accuracy, thus providing an indoor cooperative localization framework for PIR sensor networks.https://www.mdpi.com/1424-8220/21/18/6180pyroelectric infrared sensor networksnon-wearable systemcooperative indoor localizationsignal processing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chia-Ming Wu Xuan-Ying Chen Chih-Yu Wen William A. Sethares |
spellingShingle |
Chia-Ming Wu Xuan-Ying Chen Chih-Yu Wen William A. Sethares Cooperative Networked PIR Detection System for Indoor Human Localization Sensors pyroelectric infrared sensor networks non-wearable system cooperative indoor localization signal processing |
author_facet |
Chia-Ming Wu Xuan-Ying Chen Chih-Yu Wen William A. Sethares |
author_sort |
Chia-Ming Wu |
title |
Cooperative Networked PIR Detection System for Indoor Human Localization |
title_short |
Cooperative Networked PIR Detection System for Indoor Human Localization |
title_full |
Cooperative Networked PIR Detection System for Indoor Human Localization |
title_fullStr |
Cooperative Networked PIR Detection System for Indoor Human Localization |
title_full_unstemmed |
Cooperative Networked PIR Detection System for Indoor Human Localization |
title_sort |
cooperative networked pir detection system for indoor human localization |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-09-01 |
description |
Pyroelectric Infrared (PIR) sensors are low-cost, low-power, and highly reliable sensors that have been widely used in smart environments. Indoor localization systems can be categorized as wearable and non-wearable systems, where the latter are also known as device-free localization systems. Since the binary PIR sensor detects only the presence of a human motion in its field of view (FOV) without any other information about the actual location, utilizing the information of overlapping FOV of multiple sensors can be useful for localization. In this study, a PIR detector and sensing signal processing algorithms were designed based on the characteristics of the PIR sensor. We applied the designed PIR detector as a sensor node to create a non-wearable cooperative indoor human localization system. To improve the system performance, signal processing algorithms and refinement schemes (i.e., the Kalman filter, a Transferable Belief Model, and a TBM-based hybrid approach (TBM + Kalman filter)) were applied and compared. Experimental results indicated system stability and improved positioning accuracy, thus providing an indoor cooperative localization framework for PIR sensor networks. |
topic |
pyroelectric infrared sensor networks non-wearable system cooperative indoor localization signal processing |
url |
https://www.mdpi.com/1424-8220/21/18/6180 |
work_keys_str_mv |
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1716869102690107392 |