PREDICTIVE POLICING: A Machine Learning Approach to Predict and Control Crimes in Metropolitan Cities

  • Jibran R. Khan
  • Farhan A. Siddiqui
  • Nadeem Mahmood
  • Muhammad Saeed
  • Qamar ul Arifeen
Keywords: Predictive Policing, Machine Learning, Crime Prediction, K-Means, Naïve Bayesian

Abstract

Security is the one of the basic need of human’s life and biggest challenge of history that cannot be diminished at least in metropolitan cities like Karachi. It can only be controlled by efficient resources allocation and effective strategies with forthcoming insight of criminal moves. Big data analytics with the support of machine learning algorithms makes it possible to deals with huge amount of data, extract hidden inter-connection, pattern and meaningful information. This paper, proposed the model for the predictive policing system and built test model using k-means and naïve Bayes methodologies for street crime in Karachi region. The model is then run under R and WEKA environment which produced accuracy around 70%.

PREDICTIVE POLICING: A Machine Learning Approach to Predict and Control Crimes in Metropolitan Cities
Published
2019-01-30
How to Cite
Jibran R. Khan, Farhan A. Siddiqui, Nadeem Mahmood, Muhammad Saeed, & Qamar ul Arifeen. (2019). PREDICTIVE POLICING: A Machine Learning Approach to Predict and Control Crimes in Metropolitan Cities. University of Sindh Journal of Information and Communication Technology , 3(1), 17-26. Retrieved from https://sujo.usindh.edu.pk/index.php/USJICT/article/view/567

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