Abstract

This paper examines how crime patterns affect predictive policing in Denver, Colorado. Modern crimes like cybercrime and identity theft have challenged traditional crime research methods, necessitating data-driven ones. In this context, the study examines how machine learning and AI can identify and forecast crime trends across neighborhoods, timeframes, and other aspects. The research sought to understand crime's dynamics and socioeconomic effects. The study collected data using a mixed-method approach based on questions about crime kinds, rates, and sociodemographic characteristics. A large chunk of the data came from public databases and targeted neighborhood surveys. Regression analysis, decision trees, and neural network methods were used to create predictive models from a large crime data sample. These models were tested for accuracy and generalizability and found crime trends and hotspots that affect law enforcement resource allocation. This study shows that AI can transform crime analysis and prevention. The predictive models accurately predicted crime, enabling proactive enforcement and resource management. The paper emphasizes ethical AI deployment, arguing for privacy and prejudice prevention. Law enforcement should adopt dynamic resource allocation tactics, increase community policing, and create AI-supportive policies, according to the dissertation. For practitioners, the paper recommends ethical data use and collaborative frameworks to improve crime analysis models. The findings suggests that future multidisciplinary studies may reveal the social processes behind crime patterns. To stay up with crime and technology, methodological advances are needed. This paper shows how AI may be used in criminal investigation and sets a precedent for ethical technology use in public safety. It launches future research into data science and criminology's symbiotic partnership to make communities safer.

Publication Date

9-23-2024

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Sanjay Modak

Advisor/Committee Member

Hammou Messatfa

Campus

RIT Dubai

Download

Share

COinS