What is it about?
This paper presents a new approach to crime hotspot detection and monitoring. The approach consists of three phases’ namely: video analysis, crime prediction and crime mapping. In video analysis, crime indicator events are modelled using statistical distribution of semantic concepts. In crime prediction, a neuro-fuzzy method is used to model indicator events. In crime mapping, kernel density estimation is used to detect crime hotspots.
Featured Image
Why is it important?
Identifying crime hotspots and analyzing crime patterns is sometimes exploited by law enforcement agencies for predictive policing.This often helps in providing the necessary insights to responding or investigating crimes, prioritizing policing resources and evaluating policing tactics.
Perspectives
Besides that, the issue of crime hotspot analysis and crime prediction is still an open research problem given the global surge in terrorism, gang violence and mass shootings.It is our conviction that using crime indicator events from real time video is a more realistic way of identifying and monitoring crimes hotspots for effective crime prevention.
Nurudeen Mohammed
Central South University
Read the Original
This page is a summary of: Crime Hotspot Detection and Monitoring Using Video Based Event Modeling and Mapping Techniques, International Journal of Computational Intelligence Systems, January 2017, Atlantis Press,
DOI: 10.2991/ijcis.2017.10.1.64.
You can read the full text:
Contributors
The following have contributed to this page
