计算机科学 ›› 2015, Vol. 42 ›› Issue (3): 47-50.doi: 10.11896/j.issn.1002-137X.2015.03.010

• 网络与通信 • 上一篇    下一篇

基于无线体域网的囚犯异常行为实时分析

杨璐璐,陈建新,周 亮,魏 昕   

  1. 南京邮电大学无线宽带通信与传感网技术教育部重点实验室 南京210003,南京邮电大学无线宽带通信与传感网技术教育部重点实验室 南京210003,南京邮电大学无线宽带通信与传感网技术教育部重点实验室 南京210003,南京邮电大学无线宽带通信与传感网技术教育部重点实验室 南京210003
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受中国国家自然科学基金(61201165),泛在无线通信和无线传感器网络教育部重点实验室开放课题项目(NYKL201306),江苏省高校自然科学基金(13KJB510026),同济大学嵌入式系统与服务计算教育部重点实验室项目(ESSCKF201305)资助

Real-time Analysis of Prisoner’s Abnormal Behavior Based on Wireless Body Area Network

YANG Lu-lu, CHEN Jian-xin, ZHOU Liang and WEI Xin   

  • Online:2018-11-14 Published:2018-11-14

摘要: 随着无线传感技术的快速发展,无线体域网在远程医疗、智能家居等方面的应用日渐成为研究热点。监狱作为一个特殊场所,对囚犯的日常行为监控是必不可少的。准确而有效的监控系统能够在囚犯有异常行为发生时及时告警,这有助于监狱的管理,并阻止危险事故的发生。在监狱环境下,提出一种基于无线体域网的囚犯异常行为识别方法,即通过一个腕带式加速度传感器获取囚犯活动时的三轴加速度数据,采用分类算法判断是否有打架斗殴等异常行为发生。实验结果表明,该方法对异常行为的识别准确率能够达到95%。

关键词: 无线体域网,异常行为识别,加速度传感器,特征提取,分类算法

Abstract: With the rapid development of wireless sensor technology,the application of wireless body area network in telemedicine and smart home gradually becomes the research hotspot.Prison is a special place,and the prisoner’s daily behavior monitoring is essential.Accurate and effective monitoring system can alarm in time when abnormal behavior occurs,and it contributes to the management of prison and prevent dangerous accidents.In the prison environment,a method for prisoner’s abnormal behavior recognition based on wireless body area network was presented. The three axis acceleration data are collected during the prisoner’s movement through a wrist-worn acceleration sensor,and then the classification algorithms are used to recognize the activities to assess whether there are abnormal behaviors.The experimental results show that the recognition accuracy of the abnormal behaviors can reach 95%.

Key words: Wireless body area network,Abnormal activity recognition,Accelerometer,Feature selection,Classification algorithms

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