Swarm Intelligence Response Methods Based on Urban Crime Event Prediction
-
Published:2023-11-11
Issue:22
Volume:12
Page:4610
-
ISSN:2079-9292
-
Container-title:Electronics
-
language:en
-
Short-container-title:Electronics
Author:
Wang Changhao1,
Tian Feng1,
Pan Yan2
Affiliation:
1. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021, China
2. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China
Abstract
Cities attract a large number of inhabitants due to their more advanced industrial and commercial sectors and more abundant and convenient living conditions. According to statistics, more than half of the world’s population resides in urban areas, contributing to the prosperity of cities. However, it also brings more crime risks to the city. Crime prediction based on spatiotemporal data, along with the implementation of multiple unmanned drone patrols and responses, can effectively reduce a city’s crime rate. This paper utilizes machine learning and data mining techniques, predicts crime incidents in small geographic areas with short timeframes, and proposes a random forest algorithm based on oversampling, which outperforms other prediction algorithms in terms of performance. The research results indicate that the random forest algorithm based on oversampling can effectively predict crimes with an accuracy rate of up to 95%, and an AUC value close to 0.99. Based on the crime prediction results, this paper proposes a multi-drone patrol response strategy to patrol and respond to predicted high-crime areas, which is based on target clustering and combined genetic algorithms. This strategy may help with the pre-warning patrol planning within an hourly range. This paper aims to combine crime event predictions with crowd-sourced cruise responses to proactively identify potential crimes, providing an effective solution to reduce urban crime rates.
Funder
National Natural Science Foundation of China
National University of Defense Technology
Science and Technology on Information Systems Engineering Laboratory
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference40 articles.
1. Citaristi, I. (2022). The Europa Directory of International Organizations 2022, Routledge.
2. (2023, November 05). Statistics on Major Violations and Crimes for the Third Quarter of 2021. The Police Association of Chaina. Policing Stud. 2022, 93–96. Available online: http://www.tpaoc.org.cn/html/wenzhangxuandeng/2022/04/1663.html.
3. Lu, J.Q. (2021). Crime Statistics and Optimizing Crime Governance. Chin. Soc. Sci., 105–207.
4. (2018, September 25). China Emergency Service Network. Available online: http://www.52safety.com/yjfxbg/index.jhtml.
5. Machine Learning in Crime Prediction;Jenga;J. Ambient. Intell. Humaniz. Comput.,2023