In discussion with one of our prospective clients, who wanted to create a novel method for reducing certain aspects of crime in a particular location, based on multiple variables and applied research techniques, we were engaged to build a Geo.AI based predictive model. With the success of the initial developments and the accuracy of the models, we were requested to further enhance the platform to provide a deeper planning, management and governance platform which could help the prospect with different decision-making actionable insights.
Reducing crime in a more digitally connected, aware and adapting environment with criminals improving their methods continuously was one of the biggest challenges. The easy availability of resources for criminals and their “target audience” being vast, needed a huge amount of coordination with the law enforcement agencies. Collection of Micro level Data sets, high resolution spatial imagery, reverse geocoding of crime locations, high volume of different sets of crimes and their inter-correlation required the understanding and approval of the prospective client. The applied research methods used required approvals and indepth understanding by the respective authorities.
How We Intend To Make An Impact
Deepspatial’s Platform helped understand the crime patterns with respect to geodemographic analysis, gap analysis and hotspot analysis. It provided an environmental context-based policing plan where conditions are conducive for crimes. A problem-oriented risk value map with higher & lower risk areas at micro levels according to spatial influence of criminogenic features are available in the platform. The platform also allows for predicting hotspots for different types of crimes while identifying the time related environmental conditions near the crime scenes which favor the occurrence of crime in an area. It also provides for an exit route analysis based on type of crime, traffic conditions, police outposts, police stations, time of day and multiple other parameters.
Expected Visible Results
The major goal is to reduce the overall crime incidents across locations. Using the Deepspatial platform’s multi-variable correlated data-driven approach, identification of gaps, planning and faster decision making would be provided to the client. The ability to forecast impacts based on the decisions implemented with respect to different types of crime could also be simulated to check for the effectiveness of the models and continuous enhancements in the platform would be based on the different actual implementations. The platform would provide the ability to predict types of crime & their hotspots, exit routes and also recommend the changes needed to enable proactive policing.