Efficient allocation of law enforcement resources using predictive police patrolling
Applications
2018-12-03 v1
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.
Cite
@article{arxiv.1811.12880,
title = {Efficient allocation of law enforcement resources using predictive police patrolling},
author = {Mateo Dulce and Simón Ramírez-Amaya and Álvaro Riascos},
journal= {arXiv preprint arXiv:1811.12880},
year = {2018}
}
Comments
Presented at NIPS 2018 Workshop on Machine Learning for the Developing World