Smart Policing: Using Geospatial Crime Data to Plan Patrol Routes

Effective planning of police patrol routes is crucial for law enforcement agencies to ensure efficient deterrence and detection of crime, enforcement of laws, and provision of community assistance. An effective patrolling strategy helps in making communities feel more secure and safe. With limited resources, optimizing patrol routes is crucial to cover crime hotspots effectively and reduce response times during emergencies. This study proposes a novel approach to utilize spatial crime data for police patrol route planning. The road network is modeled as an edge-weighted graph, and a custom weight function is used to assign weights to the graph, determining the hotspots. Clustering techniques are then applied to filter hotspots, and an ant colony optimization algorithm is used to plan the routes. The proposed algorithm can be applied to any jurisdiction provided that historical spatial crime data is available. By utilizing the proposed method, law enforcement agencies can enhance their patrolling strategies, resulting in targeted and more efficient approaches to maintaining community safety and security.