Synchronous Head Movement as a Crowd-Behavior-Based Security System

Individuals react in response to internal or external stimuli, whether visual, auditory, gustatory, olfactory, cutaneous, kinesthetic, or vestibular. This behavior is not fully utilized to infer possible security incidents taking place or about to take place in a defined geographical area outside of...

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Main Author: Abdulaziz Almehmadi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9348891/
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spelling doaj-8a8203b95ac94ca3bd7f3e520ac0d6332021-03-30T14:56:08ZengIEEEIEEE Access2169-35362021-01-019242632427210.1109/ACCESS.2021.30574349348891Synchronous Head Movement as a Crowd-Behavior-Based Security SystemAbdulaziz Almehmadi0https://orcid.org/0000-0002-2833-6900Faculty of Computing and Information Technology (FCIT), University of Tabuk, Tabuk, Saudi ArabiaIndividuals react in response to internal or external stimuli, whether visual, auditory, gustatory, olfactory, cutaneous, kinesthetic, or vestibular. This behavior is not fully utilized to infer possible security incidents taking place or about to take place in a defined geographical area outside of the range or field-of-view of security systems. Sensors are in place in the form of human senses. If these natural sensors are utilized together with advances in deep learning technology, researchers will be equipped to build advanced security solutions. In this paper, we propose a security system based on the crowd behavior of synchronous head movement (SHMOV). The system provides an alert of a possible security incident if synchronous head movement occurs among a crowd in a specific area by analyzing the video stream from a camera. We assessed the proposed SHMOV system using an experiment on 20 participants in auditory, visual, and olfactory settings. This experiment demonstrated the technology's potential, with 100%, 100%, and 80% incident detection accuracy and alerts issued 9, 24, and 47 seconds after the start of each incident, respectively.https://ieeexplore.ieee.org/document/9348891/Crowd behaviorsecurity incidentsecurity systemhuman sensesbehavioral movement
collection DOAJ
language English
format Article
sources DOAJ
author Abdulaziz Almehmadi
spellingShingle Abdulaziz Almehmadi
Synchronous Head Movement as a Crowd-Behavior-Based Security System
IEEE Access
Crowd behavior
security incident
security system
human senses
behavioral movement
author_facet Abdulaziz Almehmadi
author_sort Abdulaziz Almehmadi
title Synchronous Head Movement as a Crowd-Behavior-Based Security System
title_short Synchronous Head Movement as a Crowd-Behavior-Based Security System
title_full Synchronous Head Movement as a Crowd-Behavior-Based Security System
title_fullStr Synchronous Head Movement as a Crowd-Behavior-Based Security System
title_full_unstemmed Synchronous Head Movement as a Crowd-Behavior-Based Security System
title_sort synchronous head movement as a crowd-behavior-based security system
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Individuals react in response to internal or external stimuli, whether visual, auditory, gustatory, olfactory, cutaneous, kinesthetic, or vestibular. This behavior is not fully utilized to infer possible security incidents taking place or about to take place in a defined geographical area outside of the range or field-of-view of security systems. Sensors are in place in the form of human senses. If these natural sensors are utilized together with advances in deep learning technology, researchers will be equipped to build advanced security solutions. In this paper, we propose a security system based on the crowd behavior of synchronous head movement (SHMOV). The system provides an alert of a possible security incident if synchronous head movement occurs among a crowd in a specific area by analyzing the video stream from a camera. We assessed the proposed SHMOV system using an experiment on 20 participants in auditory, visual, and olfactory settings. This experiment demonstrated the technology's potential, with 100%, 100%, and 80% incident detection accuracy and alerts issued 9, 24, and 47 seconds after the start of each incident, respectively.
topic Crowd behavior
security incident
security system
human senses
behavioral movement
url https://ieeexplore.ieee.org/document/9348891/
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