Flash Flood Analytics Dashboard - IIOC Smart City Initiative
Real-time disaster management dashboard with geospatial analytics and IoT sensor integration for flood monitoring in Ipoh City.
Project Overview
Proof-of-concept smart city dashboard developed for Ipoh City Council's disaster management operations. Features real-time flood data visualization, predictive analytics, interactive heat maps, and emergency response coordination. Built with Vue.js frontend and Laravel backend, integrating IoT sensor data with geospatial mapping to provide actionable insights for city authorities during flash flood events.
- Designed and implemented responsive Vue.js dashboard with real-time data updates
- Integrated Leaflet maps with custom layers for flood visualization and heat mapping
- Built interactive data filters for sensor selection, time-range analysis, and severity levels
- Optimized map performance with marker clustering for hundreds of sensor points
- Developed API integration with Laravel backend for real-time sensor data streaming
- Ensured cross-browser compatibility and mobile responsiveness for field operations
- Created exportable reports and analytics for post-flood analysis
Project Journey
Processing and visualizing complex real-time geospatial flood data from multiple IoT sensors across the city. Needed to create an intuitive interface for emergency response teams to quickly assess flood severity, identify affected areas, and coordinate relief efforts. Required optimizing performance for large datasets while maintaining real-time updates during critical flood events.
Developed a map-centric dashboard using Vue.js for reactive UI components and Leaflet for advanced geospatial visualization. Implemented layered mapping with flood depth heat maps, sensor location markers, and historical flood zone overlays. Connected to Laravel backend APIs for real-time sensor data streaming and PostgreSQL/PostGIS for spatial queries. Optimized rendering with data clustering and progressive loading techniques.
Delivered a functional POC that reduced flood situational awareness time from 30+ minutes to under 2 minutes. Enabled data-driven decision-making with visual analytics showing flood progression and severity. System successfully demonstrated during pilot testing, identifying 15 critical flood-prone areas and enabling proactive evacuation planning. Foundation laid for city-wide smart flood management expansion.
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