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Case Study

Multi-Hazard Early Warning System

Client

National Agency for Disaster Countermeasure - BNPB

Published Date

Sep 30, 2025

Topic

Disaster Management

Service

Custom Software Development; Geospatial Data Integration & Visualization; Sensor Installation & Integration;

GeoDashboard for MHEWS represents a leap forward in disaster management innovation, delivering real-time predictions, actionable insights, and seamless communication to ensure timely and effective responses. With its robust features and alignment to national policies like 'Satu Data' and 'Satu Peta,' GeoDashboard is more than a solution—it's a strategic asset for saving lives and protecting communities across Indonesia.

Product Highlight
Predictive Modeling
and Risk Analysis

Conducts exposure and impact analysis to estimate affected population, infrastructure, and economic assets, supporting disaster preparedness and response planning.

Data Integration and Management

Integrates seamlessly with existing GIS servers, big data platforms, and data lakes, supporting real-time data ingestion from various sources such as hazard models, sensor networks, and historical datasets.

Interactive Risk Monitoring Dashboard

Displays real-time disaster data (e.g., water levels, weather forecasts) with interactive layers for flood, tsunami hazard zones, and evacuation routes.

Real-Time Communication and Dissemination

Sends automated notifications and disseminates early warnings to relevant stakeholders via various communication channels, following the Common Alerting Protocol (CAP).

User Management and Role-Based Access Control

Uses Role-Based Access Control (RBAC) for secure user management, allowing access control over modules and features based on user roles.

Tech Highlights
TypeScript

Strongly-typed front-end codebase for reliability and maintainability.

Python

Scalable API layer for authentication, business logic, and integrations.

Node.js

Data processing, validation routines, and geospatial utilities.

PostgreSQL + PostGIS

Authoritative spatial database for parcels, boundaries, and price layers.

Dramatiq Worker

Asynchronous task queue for background jobs (validation, geoprocessing, report generation).

Kubernetes Cluster

Container orchestration for high availability, scaling, and rolling updates.

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