Violence Detection Using Wi-Fi and 5G/6G Sensing Technologies: A Review

Author:

Kannan Aieswarya1,Kouzani Abbas Z.1ORCID

Affiliation:

1. School of Engineering, Deakin University, Geelong, VIC 3216, Australia

Abstract

Violence, a pervasive societal concern, demands innovative approaches for its early detection and prevention. This review paper explores the intersection of violence detection and wireless fidelity (Wi-Fi), alongside fifth-generation (5G) and sixth-generation (6G) mobile technologies. Wi-Fi sensing, initially employed for human activity detection, has also demonstrated versatility across a number of other important applications. The significance of leveraging Wi-Fi sensing for violence detection is investigated, underscoring its ability to enhance security protocols and minimise response time. Moreover, through the development and use of machine learning algorithms to analyse and interpret intricate channel state information (CSI) features, the accuracy of violence detection can be improved. Furthermore, this investigation delves into the rapidly developing domain of mobile sensing, examining its contribution to the advancement of violence detection functionalities. The potential convergence of 5G and forthcoming 6G sensing technologies increases the effectiveness of violence detection. Through an analysis of Wi-Fi and mobile sensing technologies, this review paper highlights the transformative capacity that their integration may have on approaches to violence prevention and response.

Publisher

MDPI AG

Reference35 articles.

1. (2024, April 02). Australian Institute of Health and Welfare, Available online: https://www.aihw.gov.au/family-domestic-and-sexual-violence/resources/fdsv-summary#:~:text=It%20is%20estimated%20that%20of,family%20member%20(ABS%202023c.

2. Technological Innovations for Tackling Domestic Violence;Kouzani;IEEE Access,2023

3. (2024, April 02). The University of St Andrews. Available online: https://reportandsupport.st-andrews.ac.uk/support/what-is-physical-violence.

4. MoWLD: A robust motion image descriptor for violence detection;Zhang;Multimed. Tools Appl.,2017

5. Vijeikis, R., Raudonis, V., and Dervinis, G. (2022). Efficient Violence Detection in Surveillance. Sensors, 22.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3