The identification of patterns amongst crime incidents has been the subject of various studies, and an important challenge in criminology is the prediction of crime occurrences with a high level of accuracy. Currently, the technique of statistical crime hot spotting, alongside empirical knowledge of the law enforcement agencies; is applied. In this paper, we provide a fresh and minimally explored approach at solving this problem, by using an artificial neural network-based model, for the purpose of area-based crime prediction. Our model can predict where crime will be most prevalent, being of obvious benefit to a city and its citizens. In order to create actionable insights, the model that we created is able to predict crime within a small-time frame and a small geographic region. In addition, our experimental results on the Boston Police Department’s open data set consisting of crimes across a span of 10 years yielded an accuracy of 81%, which is a marked improvement over recent models proposed in literature.
CITATION STYLE
Patil, A. P., Nawal, D. J., & Jain, D. (2020). Crime Prediction Application Using Artificial Intelligence. In Lecture Notes in Electrical Engineering (Vol. 605, pp. 238–245). Springer. https://doi.org/10.1007/978-3-030-30577-2_20
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