Crime Rate Prediction in Tamil Nadu Using Machine Learning

Prevention is preferable to treatment. It is preferable to prevent crimes from happening rather than look into how or why they were committed. With today’s rising crime rate, it has become essential to establish a vaccine system that stops crimes from happening, just as vaccinations are provided to children to prevent disease. Predicting crime incidents has mostly relied on past crime statistics as well as various geospatial and demographic data. For the prediction of future crimes, a Random Forest Regression model has been proposed. This approach is applied to train our model, which has the highest accuracy amongst other methods. K-means clustering is also used to find patterns in our dataset. Using the data kept in repositories can be very helpful in evaluating and forecasting crimes. The crime rate in India is rising daily, posing a serious threat to the country. In this study, numerous significant crime trends are thoroughly examined, and crime data are statistically analyzed. Law enforcement organizations can use this study to help them develop plans and techniques to deal with the crimes. In order to do this, clustering of the districts having low crime or high crime is done using K-Means clustering. In order to build a web application for deployment, the Flask framework and the frontend languages of HTML, CSS, and JavaScript are used. PowerBI is also used for the EDA part.