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REACH Banner

REACH

Real-time Emergency Alert Collection Hub

An AI-powered warning system to bridge official disaster forecasts and the community in Pakistan.

Status Stack License

The Problem

Pakistan faces a critical disconnect in its disaster management infrastructure. While agencies like NDMA and PMD generate vital data, the "last mile" of communication is broken.

Fragmentation

Critical alerts are scattered across isolated agencies, or locked inside static PDF bulletins.

Latency & Jargon

Reports are often verbose, technical, and require manual parsing, leading to dangerous delays in dissemination.

Zero Targeting

Warnings are broadcast at the national level, causing alert fatigue. Faulty systems to deliver geofenced alerts.


The Solution

REACH is an automated pipeline that ingests raw government data and transforms it into precision-targeted, actionable alerts. We treat disaster alerts as spatial data problems, not just text problems.

How it works

Architecture Diagram

  1. Ingestion: Scrapers check bulletins (NDMA, NEOC, PMD) every 10 minutes for updates.
  2. Normalization: AI processes fetched documents in under 30 seconds to extract severity, timeline, description, etc. and convert it to a CAP (Common Alerting Protocol)-inspired schema.
  3. Geocoding: A custom service resolves location names to polygons. It handles complex directional variants (e.g., "North Khyber Pakhtunkhwa") using grid intersection logic over administrative boundaries.
  4. Distribution: Normalized data is stored in our database and served via web app for visualization and filtering.

Tech Stack

Our architecture is built for speed, resilience, and geospatial accuracy.

Component Technology Description
Frontend React, TypeScript, and Mapbox for web app.
Services Python microservices handling business logic and scraping.
Backend and Database Supabase for storing alerts, geometries, cron jobs and message queues.
AI Engine Gemini-3-Flash for high-speed inference for document parsing and entity extraction.

Visuals

Alert Polygon and Centroid Visualization Searching Historical Alerts
Filtering By Location User Guide

Roadmap

  • Scrapers: Automated bots hitting NDMA, NEOC, and PMD public sources on a 10-minute cron
  • AI Pipeline: Document processing pipeline achieving latency of under 1 minute per report using Gemini 3 Flash
  • Spatial Engine: Heuristic geocoder capable of parsing admin regions and directional descriptors into polygons
  • Web Dashboard: A responsive React application for searching alerts, filtering by severity/date, and visualizing risk zones on an interactive map
  • Performance: Optimizing database and backend for better performance
  • Deduplication: Logic to merge overlapping reports from different agencies into a single "Source of Truth" event
  • UX Polish: Refining the dashboard based on early user feedback
  • Alerts: Notifications for user apps based on their GPS location
  • Mobile Apps: Apps for Android and iOS to get information to all users conveniently
  • Advanced Geocoding: Improving the heuristic engine to resolve roadways, hydrology (rivers/dams), and bridges
  • Data Expansion: Integrating social media firehose (validated) and international weather APIs

Acknowledgements

  • NDMA, NEOC, and PMD for their tireless work in disaster monitoring
  • The open-source community for incredible tools and libraries
  • Render, Modal, Supabase and Netlify for allowing us to host our app's services for free
  • Communities affected by the 2025 floods - this is for you

And the Featured on Awesome README project for featuring us.


  Built with for a safer Pakistan.

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AI-powered disaster alert system for Pakistan that automatically processes official emergency warning documents.

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