Pre-emptive Policing: Can Technology be the Answer to Solving London’s Knife updates Crime Epidemic?

Sandra Smart-Akande*, Joel Pinney, Chaminda Hewage, Imtiaz Khan, Thanuja Mallikarachchi

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddPennodadolygiad gan gymheiriaid

Crynodeb

As knife-related crimes continue to increase it has become an evergrowing area of concern in the UK. The highest rates were recorded in the London Metropolitan area with a rate of 168 offences involving a knife per 100, 000 people in 2017/2018. This is an increase of 26 offences per 100, 000 people since the previous year’s statistics (2016/2017). With knife-related incidents continuing to climb on an upwards trend, the Metropolitan Police continues to explore innovative methods to address these worrying statistics. This chapter provides an in-depth analysis on the research of knife-enabled crimes, causes and motivating factors with the focus on the 33 boroughs of London. This chapter reviews the contemporary literature to answer many of the important questions including what are the main causes and who are perpetrators of knife crimes? how are the London Metropolitan Police dealing with knife crime? and how does the London Metropolitan Police force employ big data and predictive analysis for pre-emptive policing? The findings of this chapter uncover not only an analysis of the recent knife crime statistics in London but also a review of the motivations causing individuals to carry a bladed article. The chapter also addresses how technological innovations can be utilised to address the knife crime epidemic. Through investigating pre-emptive policing using big data and innovative technology, the chapter provides a critical review on how technology can help the London Metropolitan Police address knife crime.

Iaith wreiddiolSaesneg
TeitlArtificial Intelligence and National Security
CyhoeddwrSpringer International Publishing
Tudalennau204-230
Nifer y tudalennau27
ISBN (Electronig)9783031067099
ISBN (Argraffiad)9783031067082
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 5 Mai 2022

Dyfynnu hyn