[charlimit] CRAC(K)IN Crime

Inspiration

With law enforcement agencies facing a decreasing supply of manpower, optimizing police patrols has become essential. Ensuring effective coverage and rapid response times in the face of limited resources is a critical challenge that demands innovative solutions. Thus, we proposed CRACIN (Crime Activity Index), a solution to this challenge, aiming to resolve the issue by enhancing patrol efficiency and effectiveness, through the use of crime data analysis and patrol route optimization.

What it does

Our team has developed the CRACIN (Crime Activity Index), which incorporates data on the severity, frequency, location, and timing of recent crimes. Using our CRACIN data as the base, our solution optimizes routes for patrolling policemen to be able to respond to emergencies by being as close as possible to various crime hotspots.

How we built it

Our team opted to develop a website accessible via both computers and mobile devices, providing flexibility for law enforcement personnel on the move. We used HTML/CSS/JS on the front-end, leveraging the Leaflet library to construct the Singapore Map and display optimized routes for the law enforcement personnel. Subsequently, Python was employed at the back-end to sift through and handle data from our crafted sample database, creating the Crime Activity Index (CRACIN). Since real-time crime data is not accessible, we populated the database with sample data representing four regions of Singapore. We then integrated the open-source ORSM API to compute optimal routes. Utilizing CRACIN, we also generated a heatmap depicting crime activity density across localized regions, thereby highlighting areas prone to criminal incidents.

Challenges we ran into

We were unable to obtain accurate data on recent crimes in Singapore, finding a balanced formula for CRACIN was difficult as the severity of each crime was subjective.

Accomplishments that we're proud of

CRACIN is proud of the ease-of-use of its website and its versatility, as new routes can be easily added to the application via CSV files.

What we learned

We have learnt about the usage of map providers API (Leaflet) and routing APIs (OSRM), and solutions to route optimization problems (Travelling Salesman Problem etc.). We have also gained a deeper insight into the existing issues of patrol routes planning.

What's next for CRAC(K)IN Crime

We hope to enhance the application further by adding support for different travel modes, such as walking and biking. This would largely increase the versatility of the application. We also hope to include an easy to use GUI that allows patrolling officers to easily drag-and-drop markers and plan the most effective route. We also hope to include a login system, to enhance the security of the application such that only authorized personnel are able to view the routes.