TY - CHAP
T1 - Pre-emptive Policing
T2 - Can Technology be the Answer to Solving London’s Knife updates Crime Epidemic?
AU - Smart-Akande, Sandra
AU - Pinney, Joel
AU - Hewage, Chaminda
AU - Khan, Imtiaz
AU - Mallikarachchi, Thanuja
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
PY - 2022/5/5
Y1 - 2022/5/5
N2 - 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.
AB - 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.
KW - Big data
KW - Knife crime
KW - Pre-emptive policing
KW - Predictive analysis
UR - http://www.scopus.com/inward/record.url?scp=85160115992&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-06709-9_11
DO - 10.1007/978-3-031-06709-9_11
M3 - Chapter
AN - SCOPUS:85160115992
SN - 9783031067082
SP - 204
EP - 230
BT - Artificial Intelligence and National Security
PB - Springer International Publishing
ER -