Crime Rate Prediction and Spot Detection System Using Machine Learning and Data Mining

Abstract

Analysis of crime is a methodological approach to the identification and assessment of criminal patterns and trends. In a number of respects cost our community profoundly. We have to go to many places every day for our daily purposes and many times in our everyday lives we face numerous safety problems such as hijack, kidnapping, harassment, etc. In general, we see that when we need to go anywhere at first, we are searching for google maps, google maps show that one, two, or more ways to get to the destination, but we always choose the shortcut route, but we don't understand the path situation correctly. Is it really secure or not that's why we face many unpleasant circumstances, in this job we use different clustering approaches of data mining to analyzing the crime rate of Bangladesh and us also used K-Nearest Neighbor(KNN) algorithm to train our dataset, For our job, we are using main and secondary data, By, analyzing the data, we find out for many places the prediction rate of different crime and use the algorithm to determine the prediction rate of the path. Finally, to find out our save route, we use the forecast rate. This job will assist individuals become aware of the crime area and discover their secure way to the destination.