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March 17, 20260 citationsOpen Access

A Real Time Disaster Response Platform for Local Community Coordination Using Geospatial Insights

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MAMohd Arham ArhamMNMaheen NajamSHSriramula Sri Harshini

Key Points

  • The research aims to design a platform that enhances disaster response coordination using geospatial insights.
  • Developed a real-time disaster response platform integrating official alerts and community coordination.
  • Used a weighted keyword-based classification engine for disaster type identification.
  • Implemented geospatial visualization and navigation features for evacuation planning.
  • Created a QR-based financial assistance module utilizing UPI technology.
  • Demonstrated low synchronization latency in response coordination.
  • Achieved high classification accuracy in identifying disaster types and severity.
  • Showed effectiveness in linking official alerts to community-level response.
  • Provided a scalable framework integrating government data and community participation.

Abstract

This research presents the design and implementation of a real-time disaster response platform aimed at improving community coordination during emergency situations using geospatial technologies. The proposed system integrates official disaster alerts from the National Disaster Management Authority (NDMA) through the Common Alerting Protocol with a peer-to-peer coordination network that enables affected individuals, volunteers, and responders to communicate and organize relief efforts efficiently. A weighted keyword-based classification engine processes unstructured alert descriptions to automatically identify disaster types and severity levels, enabling faster situational awareness. The platform incorporates real-time geospatial visualization, nearby shelter discovery, and navigation assistance to support evacuation planning. In addition, a decentralized QR-based financial assistance module using Unified Payments Interface (UPI) technology allows direct monetary support to victims without intermediary transaction fees. Experimental evaluation demonstrates low synchronization latency and high classification accuracy, highlighting the system’s effectiveness in bridging the gap between official disaster alerts and community-level response. The platform provides a scalable framework for integrating government data, geospatial analytics, and community participation to enhance disaster preparedness and response.

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Cite This Study

Arham et al. (2026) studied this question.

synapsesocial.com/papers/69b8f13ddeb47d591b8c63c3https://doi.org/10.5281/zenodo.19032857
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