A Framework for Visual Representation of Crime Information

Objectives: This paper proposes a framework that transforms the structural crime related data into effective visual reports to strengthen the pro-active activities of law enforcement agencies. Methods/Statistical Analysis: The information visualization depends on the input data. The visualization engine, as proposed in this research work, processes all the data to produce crime information instrumental for the law-enforcing agencies and present it in three different formats: 1) Statistically summarized reports in graphical formats, 2) Heat-maps of crimes and 3) Clusters of crime patterns based on geo-locations. Findings: The visual crime analysis information may also help the policy-makers to gain depth knowledge about crime types, their timings at certain regions. This insight knowledge may improve the performance of law enforcement agencies in reducing crime rate and utilizing resources efficiently. Especially, it performs comprehensive processing of crime information to detecting heat-maps of crimes, clustering crime patterns and presenting it by means of information visualization techniques. Application/Improvements: Law enforcement agencies can use the system to have comprehensive, consolidated and chronologically view of all types of reported criminal activities.