Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

A decision support system for predictive police patrolling

Camacho-Collados, M. and Liberatore, F. ORCID: https://orcid.org/0000-0001-9900-5108 2015. A decision support system for predictive police patrolling. Decision Support Systems 75 , pp. 25-37. 10.1016/j.dss.2015.04.012

Full text not available from this repository.

Abstract

In the current economic climate, many police agencies have reduced resources, especially personnel, with a consequential increase in workload and deterioration in public safety. A Decision Support System (DSS) can help to optimize effective use of the scarce human resources available. In this paper we present a DSS that merges predictive policing capabilities with a patrolling districting model, for the design of predictive patrolling areas. The proposed DSS, developed in close collaboration with the Spanish National Police Corps (SNPC), defines partitions of the territory under the jurisdiction of a district that are efficient and balanced at the same time, according to the preferences of a decision maker. To analyze the crime records provided by the SNPC, a methodology for the description of spatially and temporally indeterminate crime events has been developed. The DSS has been tested with a case study in the Central District of Madrid. The results of the experiments show that the proposed DSS clearly outperforms the patrolling area definitions currently in use by the SNPC. To compare the solutions in terms of efficiency loss, we discuss how to build an operational envelope for the problem considered, which can be used to identify the range of performances associated with different patrolling strategies.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Elsevier
ISSN: 0167-9236
Date of Acceptance: 24 April 2015
Last Modified: 26 Oct 2022 08:25
URI: https://orca.cardiff.ac.uk/id/eprint/127423

Citation Data

Cited 62 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item