Rakshekanetra: Smart Crime Analytics Dashboard

Rakshekanetra is a real-time crime analytics and prediction dashboard designed to empower law enforcement with data-driven insights. Built during a hackathon for the Karnataka Police, this project leverages machine learning, interactive visualizations, and real-time mapping to support smart policing and proactive crime prevention.

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Features

• Crime Trend Analysis Analyze historical crime data to uncover emerging patterns using ML models.

• Predictive Analytics Identify future crime hotspots based on time, location, and past incident trends.

• Real-time Mapping Visualize incidents spatially using the Google Maps API for better decision-making.

• Smart Dashboard Interface Designed for both field officers and command staff, the dashboard is responsive and user-friendly.

• Interactive UI with Streamlit Dynamic filtering, visualization toggles, and user-driven data exploration.

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Tech Stack

Layer	Technology Used
Frontend	Streamlit
Backend	Python
Mapping	Google Maps API
ML & Data	scikit-learn, pandas, numpy
Visualization	Plotly, Streamlit Charts

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Screenshot

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Getting Started

To run this project locally:

1. Clone the Repository

   git clone https://github.com/shreyas27092004/crime-rate-prediction.git
   cd crime-rate-prediction

2. Install Dependencies

   Create a virtual environment and install required packages:

   python -m venv venv
   source venv/bin/activate        # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

3. Add API Key

   Create a .env file (or use secrets.toml if using Streamlit secrets):

   GOOGLE_MAPS_API_KEY=your_api_key_here
   

4. Run the App

   streamlit run app.py

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License

This project is open-source and available under the MIT License.

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Contact

• Email: shreyasshreyu405@gmail.com
• GitHub: shreyas27092004
• College: Presidency University, Bangalore

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