Case study

Predictive policing system for forecasting crimes created for the Polish Police.

Challenge

Creation of an IT system for the Polish Police supporting the short-term prediction of events, including crimes and offenses, suggesting to officers the place and time of a possible event.

Organization profile

The Polish Police is a centralized, armed and uniformed formation. Nearly 100,000 policemen supported by almost 25,000 civilian workers are expected to watch over the safety of Poland’s inhabitants and the maintenance of public order. The contemporary Polish Police consist of officers employed in the criminal, preventive and support services of the police in the organizational, logistic and technical areas.

Well-armed and trained anti-terrorist police are involved in detaining the most-dangerous criminals. Police officers of the Central Bureau of Investigation (CBŚP) unit break up organized crime groups, fight against criminal terror and drug trafficking.

Project budget: 1,75 mln Euro, duration: 36 months

Solution

ML learning methods are very effective in predicting criminal events. They can be used, among others to predict the place and time where such events may occur and to find spacetime relationships.

Assumptions: The MIM Solutions solution is based on the assumptions similar to the successfully used PredPol system. The PredPol system is the first crime prediction system that achieved significant success in crime prevention. It operates in 11 major cities in the US and the UK. The main advantage of this system is the very small amount of data needed to make forecasts and thus the speed and flexibility of implementation in various centers. The basic version of the system uses solely the information on the place, time and type of event. The aim of the MIM Solutions system is to support police officers in suggesting the place and time of possible future events. The system extracts various crime patterns from historical data (e.g. on Fridays in the evening there are more robberies in this district, on working days break-ins happen most often in this area, etc.) that a human may not notice.

Data used to create the model: The predictive system was based on police data from the decision support system (DSS, in Polish: SWD), which includes the place, time and type of event. The data was processed to obtain the exact coordinates of the place based on the textual description.

Creating of the system: The MIM Solutions model uses a spatial-temporal regression model based on gradient boosted decision trees (GBDT). It predicts the probability of another event based on previously observed events in the area. It allows the simple integration of external data sources such as weather, cultural and sports events. It supports predictions for any period of time, e.g., hour, day, or month. When preparing a crime forecast for a given region (e.g. city, commune, county), we divide the region into small square areas called locations. The default and recommended square size is 200 by 200 meters. The development of the right features for the algorithm to use was the key challenge. We made sure that the features capture spatio-temporal information about past crimes and allow robust predictions for the forecast.

Results are based on the example of Białystok, a city in eastern Poland. With 20 police patrols at our disposal, we can place a patrol at the scene of a crime in over 30 percent of cases. As the number of policemen increases, so does the number of successfully predicted sites of crimes.

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