School Violence Detection Based on Multi-sensor Fusion and Improved Relief-F Algorithms

School bullying is a common social problem around the world, and school violence is considered to be the most harmful form of school bullying. This paper proposes a school violence detecting method based on multi-sensor fusion and improved Relief-F algorithms. Data are gathered with two movement sensors by role playing of school violence and daily-life activities. Altogether 9 kinds of activities are recorded. Time domain features and frequency domain features are extracted and filtered by an improved Relief-F algorithm. Then the authors build a two-level classifier. The first level is a Decision Tree classifier which separates the activity of jump from the others, and the second level is a Radial Basis Function neural network which classifies the remainder 8 kinds of activities. Finally a decision layer fusion algorithm combines the recognition results of the two sensors together. The average recognition accuracy of school violence reaches 84.4%, and that of daily-life reaches 97.3%.

[1]  Hany Ferdinando,et al.  Violence Detection From ECG Signals: A Preliminary Study , 2017 .

[2]  Xin Liu,et al.  Collaborative Energy and Information Transfer in Green Wireless Sensor Networks for Smart Cities , 2018, IEEE Transactions on Industrial Informatics.

[3]  Hany Ferdinando,et al.  Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook , 2014 .

[4]  Tapio Seppänen,et al.  Physical Violence Detection for Preventing School Bullying , 2014, Adv. Artif. Intell..

[5]  Yu'e Lin,et al.  Enhanced Parameter-Free Diversity Discriminant Preserving Projections for Face Recognition , 2018, Int. J. Pattern Recognit. Artif. Intell..

[6]  Andrea Mannini,et al.  Activity recognition using a single accelerometer placed at the wrist or ankle. , 2013, Medicine and science in sports and exercise.

[7]  Vinod Chandran,et al.  Physical Activity Recognition Using Posterior-Adapted Class-Based Fusion of Multiaccelerometer Data , 2017, IEEE Journal of Biomedical and Health Informatics.

[8]  Peng Wang,et al.  A Combined Motion-Audio School Bullying Detection Algorithm , 2018, Int. J. Pattern Recognit. Artif. Intell..

[9]  Doruk Coskun,et al.  Phone position/placement detection using accelerometer: Impact on activity recognition , 2015, 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

[10]  Tapio Seppänen,et al.  Enhancing Emotion Recognition from ECG Signals using Supervised Dimensionality Reduction , 2017, ICPRAM.

[11]  Tapio Seppänen,et al.  An instance-based physical violence detection algorithm for school bullying prevention , 2015, 2015 International Wireless Communications and Mobile Computing Conference (IWCMC).

[12]  Tapio Seppänen,et al.  Emotion Recognition by Heart Rate Variability , 2014 .

[13]  Yeh-Liang Hsu,et al.  A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring , 2010, Sensors.