Fuzzy Geographical Model for Visualizing Crimes Hot Spots

Abstract

Crimes Hot spots are areas that have a greater than average number of criminal or disorder events. Recently, many researchers pay more attentions for detecting crime hot spots to allow police personnel to plan effectively for emergency response, determine mitigation priorities, analyze historical events, and predict future events. This paper introduces a fuzzy geographical model for detecting crimes hot spots. The proposed model has three main phases which are: (1) Pre-processing, (2) Fuzzification, and (3) Visualization. In pre-processing phase, the model uses statistical methods and cleansing techniques to clean the raw dataset. In Fuzzification phase, the number of crimes converts into linguistic value according to the hybrid (triangular and trapezoidal) membership function. In visualization phase, the results are visualized on GIS map with different colors based on the density of crime hot spot. This paper aims to rank the hotspot crime places in the country, so the decision-makers can be knowing accurately. Our dataset collected from Cairo crimes at year 2016 and the results of our approach suitable and has a good manner for the decision maker with high accuracy.