Real-time intelligence dashboard for monitoring crime related activity using aggregated data from news and social media sources.
- Frontend: https://your-vercel-link.vercel.app
- Backend API: https://your-render-link.onrender.com
CrimeIntel AI is a fullstack intelligence platform that collects and visualizes crime related data from multiple sources including:
- News scraping
- Reddit discussions
- Twitter posts
- Social media content
The system processes this data and presents it through an interactive dashboard with real-time updates and geospatial visualization.
- Real time alerts using Socket.IO
- Crime heatmaps with Leaflet
- Interactive analytics dashboard
- Multi source data aggregation
- Role-based authentication (Admin / Officer)
- Modular full-stack architecture
- React + Vite
- Tailwind CSS
- Framer Motion
- Leaflet
- Node.js
- Express.js
- MongoDB
- Socket.IO
crimeintel-ai/
├── backend/
├── frontend/
├── eda/
# Clone repository
git clone https://github.com/vipultechstack/crimeintel-ai.git
# Backend
cd backend
npm install
npm run dev
# Frontend
cd ../frontend
npm install
npm run devCrimeIntel AI follows a modular full-stack architecture with real-time data flow.
Data Sources (News, Reddit, Twitter, Social Media)
↓
Ingestion Layer (Scrapers / Workers)
↓
Processing Layer (Services)
↓
MongoDB Database
↓
REST APIs + Socket.IO Events
↓
Frontend Dashboard (React)
- Modular structure (auth, crime, post, social)
- Service layer for business logic
- Worker-based ingestion for social platforms
- REST APIs for data access
- Socket.IO for real-time updates
- Feature-based structure (auth, dashboard, intelligence)
- Shared UI component system
- Centralized API handling
- Real-time updates via WebSockets
Most dashboards only visualize static data.
CrimeIntel AI focuses on:
- Aggregating real-time data from multiple sources
- Monitoring social signals for crime-related activity
- Visualizing insights with geospatial context
- Delivering live updates through real-time communication
This project is designed to reflect how modern intelligence systems aggregate, process, and visualize real-time data streams.
- Challenge: Integrating data from news, Reddit, Twitter, and social feeds
- Solution: Created modular ingestion services and workers for each source
- Challenge: Keeping dashboard data updated without refresh
- Solution: Implemented Socket.IO for live event updates
- Challenge: Managing different data formats from multiple sources
- Solution: Standardized processing layer before storing in MongoDB
- Challenge: Avoiding tightly coupled code
- Solution: Used modular architecture with service-based separation
The project includes exploratory analysis of crime-related datasets to understand patterns and trends.
- Data cleaning and preprocessing
- Pattern identification
- Insight generation for dashboard design
- Law enforcement monitoring and analysis
- Social media intelligence tracking
- Crime trend analysis and visualization
- Real-time alert systems for critical events
- Event-driven architecture using message queues (Redis, BullMQ)
- NLP-based classification of crime-related content
- Geo-clustering for hotspot detection
- Advanced filtering and search capabilities
- Notification center with priority alerts
If you're interested in collaboration, freelance work, or discussing opportunities:
- GitHub: https://github.com/vipultechstack
- Email: vipulpaighan.1988@gmail.com
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