Optimizing crime hotspots and cold spots using Hidden Markov Model

Abstract

Public security is a key concern around the world. Efficient patrol strategy can help to increase the effectiveness of police patrolling and improve public security.  In this paper, patrol pocess is formulated as Markov process, By taking the all the nearest locations and probability of types of crimes happened in each location as Hidden Markov Model. Using Viterbi algorithm we can find most likely sequence of hidden states here hidden states are the areas need to concentrate. After finding the path for patrolling we can find the crime hotspots and cold spots in the current area for better surveillance.