Efficient allocation of law enforcement resources using predictive police patrolling

TL;DR

This paper implements a self-exciting point process model to predict crime hotspots in Bogotá, aiming to optimize police resource allocation and improve crime prevention strategies.

Contribution

It fully implements and deploys the Mohler et.al (2011) model for crime prediction in Bogotá, demonstrating its practical application for law enforcement resource allocation.

Findings

Model outperforms standard hotspot methods in predicting crime

Technological deployment facilitates efficient police resource distribution

Improves crime prevention effectiveness

Abstract

Efficient allocation of scarce law enforcement resources is a hard problem to tackle. In a previous study (forthcoming Barreras et.al (2019)) it has been shown that a simplified version of the self-exciting point process explained in Mohler et.al (2011), performs better predicting crime in the city of Bogot\'{a} - Colombia, than other standard hotspot models such as plain KDE or ellipses models. This paper fully implements the Mohler et.al (2011) model in the city of Bogot\'{a} and explains its technological deployment for the city as a tool for the efficient allocation of police resources.