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iProtect: Detecting Physical Assault Using Smartphone

  • Zehao Sun
  • Shaojie Tang
  • He HuangEmail author
  • Liusheng Huang
  • Zhenyu Zhu
  • Hansong Guo
  • Yu-e Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9204)

Abstract

Motivated by the reports about assaults on women, especially college girls, in China, we take the first step to explore possibility of using off-the-shelf smartphone for physical assault detection. The most difficult one among challenges in our design is the extraordinary complexity and diversity of various assault instances, which lead to an extremely hard, if not impossible, to perform fine-grained recognition. To this end, we decide to focus on the characteristics of intensity and irregularity, based on which several features are extracted. Moreover, we proposed a combinatorial classification scheme considering individuality of user’s ADLs(Activities of Daily Living) and universality of differences between ADLs and assaults to most people. The data we used for evaluation are collected from simulated assaults which are performed by our volunteers in controlled settings. Our experiment results showed that physical assaults could be distinguished with the majority of ADLs in our proposed feature space, and our proposed system could correctly detect most instances of aggravated assault with low false alarm rate and short delay.

Keywords

Assault detection Smartphone sensing Activity recognition Machine learning 

Notes

Acknowledgement

This paper is supported by the National Science and Technology Major Project under No. 2012ZX03005-009, National Science Foundation of China under No. U1301256, 61170058, Special Project on IoT of China NDRC (2012-2766), Research Fund for the Doctoral Program of Higher Education of China No. 20123402110019, and joint innovation fund of Jiangsu Provision No. BY2012127.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Zehao Sun
    • 1
  • Shaojie Tang
    • 3
  • He Huang
    • 2
    Email author
  • Liusheng Huang
    • 1
  • Zhenyu Zhu
    • 1
  • Hansong Guo
    • 1
  • Yu-e Sun
    • 2
  1. 1.University of Science and Technology of ChinaHefeiChina
  2. 2.Soochow UniversitySuzhouChina
  3. 3.University of Texas at DallasDallasUSA

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