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The systematic method of detecting crime, evaluating crime patterns, and anticipating crime trends is known as crime analysis and prediction. Crime is inherently unexpected and causes societal disruption. As Bangladesh’s population grows, so does the prevalence of crime, which is wreaking havoc on our society in various ways. As a result, analyzing crime data has become crucial for a better understanding of future crime patterns. Machine learning and data mining techniques can be quite useful in predicting future crime trends and patterns in this situation. Various machine learning algorithms are utilized in this study to predict future crime patterns in Bangladesh. The crime statistics are gathered from the Bangladesh Police website to analyse and predict dacoity, robbery, murder, women and child repression, kidnapping, burglary, theft, and other crimes in Bangladesh’s various regions. Another dataset from ACLED has been used to predict different kinds of events such as battles, explosions, protests, riots, strategic developments, violence against civilians with geolocations of the events. This research might assist Bangladesh police and law enforcement authorities to predict, prevent, and solve future crimes. The performance and success rate of the project are highly satisfactory. All resources of the project can be found at https://tinyurl.com/297yykmu |
