Abstract
Crime is an ever-increasing entity. This research work aims at leveraging existing data to prevent crime in better ways than existing structures. Crime mapping technique is developed first, to provide a way of identifying and labelling crime hotspots. An algorithm for predicting crime is developed, under the domain of predictive policing. This is done with an underlying foundation of criminology theories. Finally, possible approaches to retrofit these techniques to smart cities are suggested, to provide a holistic solution to the problem of crime solving.
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Kawthalkar, I., Jadhav, S., Jain, D., Nimkar, A.V. (2021). Predictive Crime Mapping for Smart City. In: Tripathy, A., Sarkar, M., Sahoo, J., Li, KC., Chinara, S. (eds) Advances in Distributed Computing and Machine Learning. Lecture Notes in Networks and Systems, vol 127. Springer, Singapore. https://doi.org/10.1007/978-981-15-4218-3_35
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DOI: https://doi.org/10.1007/978-981-15-4218-3_35
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