Crime Prediction Using Advanced Deep Learning Techniques: A Systematic Review

Rizwan Hameed; Saman Aziz; Faisal Rehman; Shanza Gul; Areej Ahmed; Bushra

doi:10.54692/ijeci.2024.0804214

Rizwan Hameed Department of Computer Science & Information Technology, Superior College Mandi Bahauddin, Pakistan
Saman Aziz Department of Statistics & Data Science, University of Mianwali, Mianwali, Pakistan
Faisal Rehman Department of Information Technology, Lahore Leads University, Pakistan
Shanza Gul Department of Statistics & Data Science, University of Mianwali, Mianwali, Pakistan
Areej Ahmed Department of Statistics & Data Science, University of Mianwali, Mianwali, Pakistan
Bushra Department of Statistics & Data Science, University of Mianwali, Mianwali, Pakistan

DOI: https://doi.org/10.54692/ijeci.2024.0804214

Keywords: Deep Learning, crime prediction, crime detection, crime datasets.

Abstract

Over the last couple of decades, researchers have searched for patterns in the occurrence of crimes to predict crimes using intelligent methods based on Deep Learning accurately. To find out the variety of Deep Learning algorithms applied to the tasks of anticipating crime, this current review paper analyzes more than 150 studies. Researchers are given access to datasets that they use to predict crime; the paper discusses the techniques often implemented in algorithms as well as various patterns and components related to criminality that employ Deep Learning. The review also outlines strategies and potential challenges that must be addressed to improve the efficiency of crime prediction. To finish, the detailed literature review on the application of Deep Learning for crime prediction presented in this paper should be useful to scholars interested in this field. Crime estimation strategies can be raised among authorities to deter and prevent criminal actions even more effectively.