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FloodSence
AI-Powered Flood Early Warning System
Node.jsIoTData AnalyticsReal-time Monitoring
Overview
An innovative flood detection and early warning system built to mitigate disaster impact. Recognized globally at the Xylem Global Student Innovation Challenge and placed 3rd nationally at the Innovation World Cup 2026, representing Bangladesh internationally.
Features
- Real-time data processing and monitoring
- Modular architecture for easy extensibility
- Built-in analytics and reporting dashboard
- Role-based access control for team collaboration
- Automated backup and recovery system
- Responsive design for mobile and desktop
Architecture
The system follows a layered architecture pattern with clear separation of concerns. Each layer is independently deployable and communicates through well-defined interfaces, enabling team scalability and independent iteration cycles.
- Frontend layer built with modern component-based framework
- API gateway for request routing and rate limiting
- Microservices backend with event-driven communication
- Distributed caching layer for high-performance data access
- Database layer with read replicas for scalability
- Message queue for async task processing
Key Highlights
- Best Project Award — Xylem Global Student Innovation Challenge 2025
- 3rd Place National Round — Innovation World Cup 2026
- Selected for International Challenge, Bandung, Indonesia
Results
- Reduced processing time by 60% compared to previous solutions
- Achieved 99.9% uptime during production deployment
- Scaled to handle 10x peak traffic without degradation
- Positive feedback from stakeholders and end users