Do Advances in Smart City Technology Provide a Plausible Route of Crime Fighting and if so, Which Areas Would Affect the Most Progress Given Concerns in Facial Recognition and Drone Technology?

Davies, C, Simpson, G and Cox, C (2025) Do Advances in Smart City Technology Provide a Plausible Route of Crime Fighting and if so, Which Areas Would Affect the Most Progress Given Concerns in Facial Recognition and Drone Technology? International Journal of Criminology and Policing Education, 1 (1). pp. 1-33. ISSN 1466-5026

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Abstract

Abstract
This research aims to investigate the possibilities of utilising increasingly complex technology in crime fighting by the police. The research will cover the increasing use of facial recognition technology (FRT) and drones as these subjects are highly relevant in pursuing technological smart cities (Appio, Lima and Paroutis, 2019). An evidence based, systematic literature review was utilised to gather and critique data of these topics.

The research has identified that there is a significant lack of public knowledge surrounding FRT and drones, and a rise in concerns regarding their use. The author concludes that FRT does not provide a plausible route of crime fighting presently due to technological issues and public resistance, resulting from its misuse and illegitimate application. On the other hand, drone use should be further explored and expanded upon due to favourable public perception and innovative uses in policing.

To the authors’ knowledge, there is little research available which discusses the use of FRT and drones. E-vehicle use especially can be proactively targeted through such technologies as discussed and therefore this research is highly relevant in informing national police objectives.

The authors recommend that FRT technology use is restricted until further research improves its capabilities and thus public perception. Police drone use on the other hand should be expanded quickly to reduce the burden on the public from technological driven criminality.

Limitations of evidence-based research projects should be noted, primarily in this case of selection bias.

Item Type:	Article
Uncontrolled Keywords:	0603 Evolutionary Biology; 0605 Microbiology; 1108 Medical Microbiology; Microbiology; 3104 Evolutionary biology; 3107 Microbiology
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare. Criminology K Law > K Law (General)
Divisions:	Law and Justice Studies
Publisher:	PKP Publishing Services Network
Related URLs:	https://journals.leedstrinity.ac.uk/index.php/ijpcj/index
Date of acceptance:	12 September 2025
Date of first compliant Open Access:	16 September 2025
Date Deposited:	16 Sep 2025 10:52
Last Modified:	16 Sep 2025 11:00
DOI or ID number:	10.70386/ijcpe.v1i1.9
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27162

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