Implementation of SEPP for Space, Time & Frequency based 3-dimensional crime analysis

Varinderjit Kaur, Avani Chopra


The urban areas are observed under the higher crime influence than the rural areas in the continuous studies for several years. Hence, the crime prediction is an important task to analyze the possibility of the future crimes on particular locations in the urban areas. The crime prediction practices are performed to help the police department to efficiently deploy the force, which eventually alleviates the hiring of more employees. This helps to reduce the crime as well as the cost of security implementation in the police department. In this paper, the SEPP (self extracting point process) based time, space and intensity based model is proposed, which can combine the multiple features of the crime records to accurately and vastly predict the high dimensional data. This may be used to prepare the security policies, police force deployment, installation of the surveillance devices, etc for the police department. The proposed model is intended to improve the accuracy and detail of prediction of crime data, which enables its use up to a higher extent than the previous models.

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