Aknex-CrowdIQ
Inspiration
Large pilgrimage events often experience overcrowding, long queues, delayed emergency response, and inefficient resource distribution. We wanted to build an AI-powered platform that helps organizers predict these issues before they become critical, making events safer and more efficient.
What it does
Aknex-CrowdIQ is an AI crowd intelligence platform that analyzes CCTV feeds and live event data to:
- Predict crowd congestion
- Estimate queue waiting times
- Detect potential medical emergencies
- Forecast food and water demand
- Optimize security and staff deployment
- Provide a real-time dashboard with alerts and analytics
How we built it
The platform combines computer vision, machine learning, and a modern web dashboard.
Frontend
- React
- TypeScript
- Tailwind CSS
Backend
- Node.js
- Express.js
AI & Analytics
- Python
- YOLO
- Scikit-learn
- Pandas
- NumPy
Database & Cloud
- PostgreSQL
- AWS
Communication
- REST APIs
- WebSockets
Challenges we ran into
The biggest challenge was combining real-time AI predictions, live analytics, and dashboard visualization into one scalable platform while maintaining fast response times and accurate predictions.
Accomplishments that we're proud of
- Built an end-to-end AI crowd management platform.
- Designed an intuitive real-time monitoring dashboard.
- Integrated AI-based prediction for congestion and resource planning.
- Created a scalable architecture suitable for large public events.
What we learned
This project improved our understanding of computer vision, machine learning, real-time data processing, scalable web development, and AI deployment for public safety.
What's next for Aknex-CrowdIQ
- Live drone integration
- Mobile application for field staff
- Edge AI for faster CCTV processing
- Multi-language support
- Digital twin simulation for event planning
- Integration with emergency response systems
Log in or sign up for Devpost to join the conversation.