GSC-GeoSentinelCrime

• 

  Landing page

• 

• 

• 

Geo Sentinel Crime(GSC):Redefining Public Safety Through Advanced Crime Mapping

Inspiration Crime Thriller Movies and Serial Killer documentaries.

What it does We built a comprehensive Crime Mapping System integrating FIR data to pinpoint crime hotspots based on various parameters like type, date, and location. Our platform employs advanced analytics and machine learning to predict crime patterns, optimize patrol routes, and enhance public safety. With a user-friendly interface and real-time insights, we empower law enforcement agencies to proactively prevent crime and ensure swift response. Additionally, we facilitate women's security through strategic patrol unit location studies. Together, we've developed a cutting-edge solution to revolutionize public safety and foster safer communities. ** How we built it** We compiled a dataset leveraging FIR data, incorporating factors like population density, crime type, latitude, longitude, and date. Our model predicts prevalent crimes within a 10 km radius, facilitating visual mapping for law enforcement. Utilizing Flask, we trained the model and employed the Haversine formula to determine police proximity to crime spots. Leaflet.js visualizes the map, while React.js handles frontend development. Although dataset availability affects accuracy, we generated one and stored it in Firestore. Additionally, we offer an open-source API for dataset augmentation, encouraging contributor involvement. ** Challenges we ran into** 1.Lack of proper dataset.

** Accomplishments that we're proud of** 1.We created a new dataset and provided it as Open source. 2.Created a model using limited factors. 3.Visualized the data where most crimes can be occured in a range of 10km from point of cops location. 4.Police can add new crime occured at a specific location.

What we learned 1.Creation of dataset. 2.Working with GIS data. 3.Integrating map functionalities and other geospatial features.

** What's next for GSC-GeoSentinelCrime** 1.If more factors are included in the dataset accuracy in predicting the hotspots increases. 2.Using a vector database for the efficient working of the model when new data is added. 3.Route optimization -generating efficient patrol routes for police forces.

Built With

• firebase
• flask
• leaflet.js
• machine-learning
• openstreetmap
• react