Table of Contents
Advances in Artificial Intelligence
Volume 2014, Article ID 740358, 9 pages
Research Article

Physical Violence Detection for Preventing School Bullying

1The Communication Research Center, Harbin Institute of Technology, Harbin, China
2Department of Electrical Engineering, University of Oulu, Oulu, Finland
3Department of Electrical Engineering, Petra Christian University, Surabaya, Indonesia
4Department of Computer Science and Engineering, University of Oulu, Oulu, Finland

Received 4 May 2014; Revised 24 July 2014; Accepted 7 August 2014; Published 24 August 2014

Academic Editor: António Dourado Pereira Correia

Copyright © 2014 Liang Ye et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


School bullying is a serious problem among teenagers, causing depression, dropping out of school, or even suicide. It is thus important to develop antibullying methods. This paper proposes a physical bullying detection method based on activity recognition. The architecture of the physical violence detection system is described, and a Fuzzy Multithreshold classifier is developed to detect physical bullying behaviour, including pushing, hitting, and shaking. Importantly, the application has the capability of distinguishing these types of behaviour from such everyday activities as running, walking, falling, or doing push-ups. To accomplish this, the method uses acceleration and gyro signals. Experimental data were gathered by role playing school bullying scenarios and by doing daily-life activities. The simulations achieved an average classification accuracy of 92%, which is a promising result for smartphone-based detection of physical bullying.