Crime Anatomization Using QGIS

With a population of approximately more than hundred lakh, the Mumbai city is witnessing an alarming increase in the rate of cognisable crimes year after year. It is the need of the hour, for the police in their role to catch criminals that they remain convincingly ahead in the race between lawbreakers and law enforcers. One of the paramount concerns of the police is how to enhance investigative effectiveness and to analyse the increasing number of crimes. The proposed research work creates a user-friendly interface to map crime using QGIS, visualize and analyze and predict crime incident patterns and trends using clustering algorithms such as K-Means, Agglomerative and predictive algorithm such as SVM and Random Forest.