Data-driven predictive policing and crime analysis

Thesis Abstract

This project focuses on the application of data-driven techniques in predictive policing and crime analysis. Traditional policing methods often rely on reactive responses to criminal activities. Data-driven approaches leverage historical crime data, demographic information, and environmental factors to predict and prevent criminal incidents. This project will explore the use of machine learning algorithms, geospatial analysis, and predictive modeling to develop a predictive policing system. The goal is to improve resource allocation, crime prevention, and community safety.