Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm

An algorithm is developed for footstep, vehicle, and rain detection using seismic sensors operating in a wireless sensor network. Each standalone seismic sensor is coupled with a wireless node, and alarm conditions were evaluated at the sensor rather than at the gateway. The algorithm utilizes slow...

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Main Authors: Gökhan Koç, Korkut Yegin
Format: Article
Language:English
Published: Wiley 2013-10-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2013/783604
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author Gökhan Koç
Korkut Yegin
author_facet Gökhan Koç
Korkut Yegin
author_sort Gökhan Koç
collection DOAJ
description An algorithm is developed for footstep, vehicle, and rain detection using seismic sensors operating in a wireless sensor network. Each standalone seismic sensor is coupled with a wireless node, and alarm conditions were evaluated at the sensor rather than at the gateway. The algorithm utilizes slow and quick adaptive thresholds to eliminate static and dynamic noise to check for any disturbance. Duration calculation and filters were used to identify the correct alarm condition. The algorithm was performed on preliminary field tests, and detection performance was verified. Footstep alarm condition up to 8 meters and vehicle presence alarm condition up to 50 meters were observed. Presence of rain did not create any alarm condition. Detection based on kurtosis was also performed and shortcomings of kurtosis especially for vehicle detection were discussed, proposed algorithm has minimal load on the sensor board and its data processing unit; thus, it is energy efficient and suitable for wireless sensor alarm networks.
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id doaj-art-44db080b003748ab907da249a8a82db7
institution Kabale University
issn 1550-1477
language English
publishDate 2013-10-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-44db080b003748ab907da249a8a82db72025-02-03T05:48:32ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-10-01910.1155/2013/783604Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds AlgorithmGökhan Koç0Korkut Yegin1 Department of Electrical and Electronics Engineering, Yeditepe University, 34755 Istanbul, Turkey Department of Electrical and Electronics Engineering, Yeditepe University, 34755 Istanbul, TurkeyAn algorithm is developed for footstep, vehicle, and rain detection using seismic sensors operating in a wireless sensor network. Each standalone seismic sensor is coupled with a wireless node, and alarm conditions were evaluated at the sensor rather than at the gateway. The algorithm utilizes slow and quick adaptive thresholds to eliminate static and dynamic noise to check for any disturbance. Duration calculation and filters were used to identify the correct alarm condition. The algorithm was performed on preliminary field tests, and detection performance was verified. Footstep alarm condition up to 8 meters and vehicle presence alarm condition up to 50 meters were observed. Presence of rain did not create any alarm condition. Detection based on kurtosis was also performed and shortcomings of kurtosis especially for vehicle detection were discussed, proposed algorithm has minimal load on the sensor board and its data processing unit; thus, it is energy efficient and suitable for wireless sensor alarm networks.https://doi.org/10.1155/2013/783604
spellingShingle Gökhan Koç
Korkut Yegin
Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
International Journal of Distributed Sensor Networks
title Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
title_full Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
title_fullStr Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
title_full_unstemmed Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
title_short Footstep and Vehicle Detection Using Slow and Quick Adaptive Thresholds Algorithm
title_sort footstep and vehicle detection using slow and quick adaptive thresholds algorithm
url https://doi.org/10.1155/2013/783604
work_keys_str_mv AT gokhankoc footstepandvehicledetectionusingslowandquickadaptivethresholdsalgorithm
AT korkutyegin footstepandvehicledetectionusingslowandquickadaptivethresholdsalgorithm