Cargando…
Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing
Modern home automation systems include features that enhance security, such as cameras and radars. This paper proposes an innovative home security system that can detect burglars by analyzing acoustic signals and instantly notifying the authorized person(s). The system architecture incorporates the...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346312/ https://www.ncbi.nlm.nih.gov/pubmed/37447640 http://dx.doi.org/10.3390/s23135792 |
_version_ | 1785073285646516224 |
---|---|
author | Al-Khalli, Najeeb Alateeq, Saud Almansour, Mohammed Alhassoun, Yousef Ibrahim, Ahmed B. Alshebeili, Saleh A. |
author_facet | Al-Khalli, Najeeb Alateeq, Saud Almansour, Mohammed Alhassoun, Yousef Ibrahim, Ahmed B. Alshebeili, Saleh A. |
author_sort | Al-Khalli, Najeeb |
collection | PubMed |
description | Modern home automation systems include features that enhance security, such as cameras and radars. This paper proposes an innovative home security system that can detect burglars by analyzing acoustic signals and instantly notifying the authorized person(s). The system architecture incorporates the concept of the Internet of Things (IoT), resulting in a network and a user-friendly system. The proposed system uses an adaptive detection algorithm, namely the “short-time-average through long-time-average” algorithm. The proposed algorithm is implemented by an IoT device (Arduino Duo) to detect people’s acoustical activities for the purpose of home/office security. The performance of the proposed system is evaluated using 10 acoustic signals representing actual events and background noise. The acoustic signals were generated by the sounds of keys shaking, the falling of a small object, the shrinking of a plastic bag, speaking, footsteps, etc. The effects of different algorithms’ parameters on the performance of the proposed system have been thoroughly investigated. |
format | Online Article Text |
id | pubmed-10346312 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103463122023-07-15 Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing Al-Khalli, Najeeb Alateeq, Saud Almansour, Mohammed Alhassoun, Yousef Ibrahim, Ahmed B. Alshebeili, Saleh A. Sensors (Basel) Article Modern home automation systems include features that enhance security, such as cameras and radars. This paper proposes an innovative home security system that can detect burglars by analyzing acoustic signals and instantly notifying the authorized person(s). The system architecture incorporates the concept of the Internet of Things (IoT), resulting in a network and a user-friendly system. The proposed system uses an adaptive detection algorithm, namely the “short-time-average through long-time-average” algorithm. The proposed algorithm is implemented by an IoT device (Arduino Duo) to detect people’s acoustical activities for the purpose of home/office security. The performance of the proposed system is evaluated using 10 acoustic signals representing actual events and background noise. The acoustic signals were generated by the sounds of keys shaking, the falling of a small object, the shrinking of a plastic bag, speaking, footsteps, etc. The effects of different algorithms’ parameters on the performance of the proposed system have been thoroughly investigated. MDPI 2023-06-21 /pmc/articles/PMC10346312/ /pubmed/37447640 http://dx.doi.org/10.3390/s23135792 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Al-Khalli, Najeeb Alateeq, Saud Almansour, Mohammed Alhassoun, Yousef Ibrahim, Ahmed B. Alshebeili, Saleh A. Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title | Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title_full | Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title_fullStr | Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title_full_unstemmed | Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title_short | Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing |
title_sort | real-time detection of intruders using an acoustic sensor and internet-of-things computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346312/ https://www.ncbi.nlm.nih.gov/pubmed/37447640 http://dx.doi.org/10.3390/s23135792 |
work_keys_str_mv | AT alkhallinajeeb realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing AT alateeqsaud realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing AT almansourmohammed realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing AT alhassounyousef realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing AT ibrahimahmedb realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing AT alshebeilisaleha realtimedetectionofintrudersusinganacousticsensorandinternetofthingscomputing |