Hundreds of millions of youths suffer from various violence each year. The negative impacts motivate much research and numerous studies on violence. However, those attempts went their own way, making the achieved results, especially from engineering, not so useful. Based on the Sensor and Social Web (SEWEB) concept, Violence Detection (VITEC) was proposed as a possible framework to facilitate multi-disciplinary researchers in their fight against violence. At its core, it consists of a primary agent, which is violence detection using physiological signals and activity recognition, and a secondary agent, which is violence detection using surveillance video. The second layer of the proposed framework contains a cloud computing service with a Personal Safety Network (PSN) database. The cloud computing service manages all data, notifications, and some more thorough processing. The upper layer is for both observed young persons and members of the PSN. The proposed framework offers business opportunities. The existing school violence/bullying intervention programs can take advantage of VITEC by providing almost instant notifications of violent events, enabling the victims to get immediate help and intensifying coordination among different sectors to fight against violence. In the long run, VITEC may provide an answer related to the vision of having a world free from violence in 2030, as addressed by the UN Special Representative of Secretary-General on violence against children.
Ferdinando Hany, Huuki Tuija, Ye Liang, Han Tian, Zhang Zhu, Sun Guobing, Seppänen Tapio, Alasaarela Esko
A4 Article in conference proceedings
Place of publication:
First EAI International Conference, AICON 2019, Harbin, China, May 25–26, 2019, Proceedings, Part II
Ferdinando H. et al. (2019) VITEC: A Violence Detection Framework. In: Han S., Ye L., Meng W. (eds) Artificial Intelligence for Communications and Networks. AICON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 287. Springer, Cham, https://doi.org/10.1007/978-3-030-22971-9_1
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