Physical Violence Detection for Preventing School Bullying. (21st August 2014)

• Record Type: Journal Article
• Authors: Ye, Liang; Ferdinando, Hany; Seppänen, Tapio; Alasaarela, Esko
• Other Names: Correia António Dourado Pereira Academic Editor.
• Is Part Of: Advances in artificial intelligence. Volume 2014(2014)
• Publication Date: 2014-08-21
• Subjects: Artificial intelligence -- Periodicals; Artificial intelligence; Periodicals; Electronic journals; 006.3
• DOI: 10.1155/2014/740358
• Languages: English
• ISSNs: 1687-7470

Abstract

Abstract : 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.