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一种用于人员行为跟踪的非侵入式信息物理社会感知解决方案:机制、原型及现场实验

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments.

作者信息

Jia Yunjian, Zhou Zhenyu, Chen Fei, Duan Peng, Guo Zhen, Mumtaz Shahid

机构信息

College of Communication Engineering, Chongqing University, Chongqing 400044, China.

School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China.

出版信息

Sensors (Basel). 2017 Jan 13;17(1):143. doi: 10.3390/s17010143.

Abstract

Tracking people's behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people's access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people's access behaviors can be correctly tracked within a one-second delay.

摘要

跟踪人们的行为是与网络物理社会感知(CPSS)相关的以人为主的应用的一个主要类别。大多数跟踪方法利用摄像头网络或诸如全球定位系统(GPS)和蓝牙等内置在移动设备中的传感器。在本文中,我们提出一种基于非侵入式无线保真(Wi-Fi)的跟踪方法。为了证明其可行性,我们旨在跟踪人们在Wi-Fi网络中的访问行为,这一行为最近引起了学术界和业界的广泛关注。用于获取访问踪迹的现有方法要么对媒体访问控制(MAC)级别的传输动态提供的可见性非常有限,要么有时不够灵活且成本高昂。在本文中,我们提出一种以非侵入式、灵活且简化的方式运行的被动CPSS系统,以克服上述限制。我们已经在现成的个人计算机上实现了该原型,并进行了实际部署实验。实验结果表明该方法是可行的,并且可以在一秒延迟内正确跟踪人们的访问行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/270a/5298716/4522b2018175/sensors-17-00143-g001.jpg

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