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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1136-1145 |
| Number of pages | 10 |
| Journal | Proceedings of the International Conference on Industrial Engineering and Operations Management |
| Volume | 2018 |
| Issue number | SEP |
| State | Published - 2018 |
| Event | 3rd North American IEOM Conference. IEOM 2018 - Duration: Sep 27 2018 → Sep 29 2018 |
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
