AI-Based Crime Prediction and Real-Time Alert System Using Machine Learning Techniques

• Author(s): Uday Tukadiya; Dr. Balamurugan S.
• Paper ID: 1717915
• Page: 2466-2474
• Published Date: 19-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

Crime rates are increasing in many cities and towns, which is becoming a serious problem for public safety. People are facing risks like theft, assault, and other crimes in their daily lives, especially in crowded urban areas. One of the biggest issues is that most systems only react after a crime has already happened. There are very few systems that can warn people in advance about possible danger in a particular area. Because of this, it becomes difficult to prevent crimes and protect individuals on time. With the growth of technology and availability of data, it is now possible to use computer-based methods to study past crime records and find patterns. Machine learning is very useful in this field because it can handle large amounts of data and find hidden relationships between factors like location, time, and type of crime. Different algorithms such as logistic regression, random forest, support vector machine, and deep learning models like LSTM have been used in earlier studies for crime prediction. However, most of these studies only focus on predicting crime and do not connect the results with real-time applications that can help users directly. Also, many studies do not compare multiple algorithms properly, so it is not clear which model works best. To solve these problems, this project proposes a system that compares different machine learning and deep learning models for predicting crime. It also includes a mobile application that gives real-time alerts to users based on their location. The process involves collecting crime data, cleaning it, selecting important features, training different models, and testing their performance using measures like accuracy, precision, recall, and F1-score. The system will show risk levels for different areas and notify users if they are entering a high-risk zone. The main goal of this study is to find the best prediction model and create a useful system that can help people stay safe and support better decision-making for public safety.

Keywords

Crime Prediction, Machine Learning, Hotspot Detection, Real-Time Alert System, Spatio-Temporal Analysis, Smart City Safety

Citations

IRE Journals:
Uday Tukadiya, Dr. Balamurugan S. "AI-Based Crime Prediction and Real-Time Alert System Using Machine Learning Techniques" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 2466-2474 https://doi.org/10.64388/IREV9I11-1717915

IEEE:
Uday Tukadiya, Dr. Balamurugan S. "AI-Based Crime Prediction and Real-Time Alert System Using Machine Learning Techniques" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717915