A framework for the optimal deployment of police drones based on street-level crime risk
A framework for the optimal deployment of police drones based on street-level crime risk
Drones are increasingly adopted for policing in many countries, as they can aid police officers to detect hazards and respond to incidents with timely and low-cost services. However, the planning and deployment of police drones are subject to several challenges, including the proper distance metric for drone flying and the risk-based location optimisation of drone base stations. This study proposes a new framework that enables the optimal deployment of police drones to address crime risk issues on urban street networks. This risk-based decision framework takes into account three potential distance metrics that regulate and shape the flying routes of drones, which in turn affects the optimal location of drone base stations. In addition, this framework takes into account the major risk constraints of flying drones in urban areas, including domestic privacy and elevation. The proposed risk-based decision framework is validated using the real case study of Liverpool with historical crime data and street network layouts. The findings contribute to the operations and management of police drones in urban areas and shift the paradigm of policing drones towards a risk-based regime.
Chen, Huanfa
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Gao, Xiaowei
c9321bf6-bb53-4bc7-82f9-d123aaa637a5
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d
18 December 2023
Chen, Huanfa
09830c4f-5f98-4aa4-889d-b28070bb6c83
Gao, Xiaowei
c9321bf6-bb53-4bc7-82f9-d123aaa637a5
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d
Chen, Huanfa, Gao, Xiaowei, Li, Huanhuan and Yang, Zaili
(2023)
A framework for the optimal deployment of police drones based on street-level crime risk.
Applied Geography, 162, [103178].
(doi:10.1016/j.apgeog.2023.103178).
Abstract
Drones are increasingly adopted for policing in many countries, as they can aid police officers to detect hazards and respond to incidents with timely and low-cost services. However, the planning and deployment of police drones are subject to several challenges, including the proper distance metric for drone flying and the risk-based location optimisation of drone base stations. This study proposes a new framework that enables the optimal deployment of police drones to address crime risk issues on urban street networks. This risk-based decision framework takes into account three potential distance metrics that regulate and shape the flying routes of drones, which in turn affects the optimal location of drone base stations. In addition, this framework takes into account the major risk constraints of flying drones in urban areas, including domestic privacy and elevation. The proposed risk-based decision framework is validated using the real case study of Liverpool with historical crime data and street network layouts. The findings contribute to the operations and management of police drones in urban areas and shift the paradigm of policing drones towards a risk-based regime.
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Accepted/In Press date: 8 December 2023
e-pub ahead of print date: 18 December 2023
Published date: 18 December 2023
Identifiers
Local EPrints ID: 503669
URI: http://eprints.soton.ac.uk/id/eprint/503669
ISSN: 0143-6228
PURE UUID: 89d0c82d-8123-4275-b1ad-5eb8db6a0c64
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Date deposited: 08 Aug 2025 16:41
Last modified: 22 Aug 2025 02:49
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Contributors
Author:
Huanfa Chen
Author:
Xiaowei Gao
Author:
Huanhuan Li
Author:
Zaili Yang
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