Track: Data Analytics

Abstract

Crimes are rampant across cities and towns throughout the world. Using crime analytics allows law enforcement agencies to pinpoint areas with high crime rates and determine methods to reduce them. Analytical models can be used to predict and visualize crimes so that they can be prevented, before they happen. This paper presents a case study on crime analysis and visualization in Erie City, Pennsylvania, USA. Crime data was obtained by the Erie Police Department. Data was pre-processed to remove the outliers, fix invalid addresses, and calculate the longitudes and latitudes. Descriptive analytics was developed to analyze the crimes per crime type and region and develop heat maps for the crime distribution. Two specific areas that have high crime rates were further investigated. The results provide decision makers with valuable insights into crime prediction and prevention. Cameras were installed in the areas with high crimes rate.