Smart Disaster Platform: A Web-Based System for NGO Verification and Skill-Aware Volunteer Allocation in Disaster Response

Abstract

During a disaster, relief agencies must quickly decide which volunteers to send where, while also ensuring that the organisations asking for help are genuine. Informal channels such as phone calls and messaging groups make both tasks slow and error-prone. This paper presents the Smart Disaster Platform, a role-based web application that connects volunteers, non-governmental organisations (NGOs) and an administrator on one system. NGOs register using their NGO-DARPAN identifier and are admitted only after administrator approval; volunteers follow the same approve-before-activate workflow. Approved users can raise disaster requests that state the disaster type, location, severity, number of volunteers needed and the food, water and medicine required. For each request the platform ranks available volunteers with a transparent weighted score built from skill relevance (40%), location match (30%), availability (20%) and fit with the request’s resource needs (10%), and records each allocation so a volunteer cannot be assigned twice to the same event. The system is built with React, Node.js/Express and MySQL. We describe the architecture, database design, REST interface and scoring algorithm, and demonstrate the ranking with a worked example. Limitations and the planned extensions are discussed.

Introduction

The Smart Disaster Platform is a web-based application designed to improve disaster relief coordination in India by connecting disaster requests with suitable, available volunteers and verified NGOs. During floods, cyclones, earthquakes, landslides and fires, coordination is often delayed by manual communication, difficulty identifying skilled volunteers and challenges in verifying organisations. The proposed platform addresses these issues through approval-based registration and transparent, score-based volunteer allocation.

The system uses a three-tier architecture comprising a React front end, an Express and Node.js back end, and a MySQL database. It supports three user roles: volunteers, NGOs and administrators. NGOs register using their NGO-DARPAN identification details, while volunteers provide their skills, contact information and location. Both must receive administrator approval before logging in. Approved users can submit disaster requests specifying the disaster type, location, severity, required volunteers and essential resources such as food, water and medicine.

The platform's main feature is a smart volunteer allocation algorithm that ranks available, approved volunteers using four weighted factors:

• Skill relevance (40%) – how closely a volunteer's skills match the disaster and its requirements.

• Location match (30%) – how closely the volunteer's location matches the disaster location.

• Availability (20%) – whether the volunteer is available for deployment.

• Requirement fit (10%) – whether the volunteer's skills support specific needs, such as medical assistance, food distribution or emergency rescue.

The resulting score ranges from 0 to 100. Volunteers are ranked from highest to lowest, with explanations showing the component scores and reasons for each recommendation. Coordinators can review the suggestions and confirm allocations. The system also prevents duplicate assignments of the same volunteer to the same disaster.

The application includes registration and login pages, an administrator dashboard, disaster request management, volunteer listings, allocation recommendations and assignment tracking. Its REST API connects the interface with the server and database, while role-based access controls restrict users to permitted functions.

A hypothetical high-severity flood scenario in Chennai illustrates the algorithm. A medical volunteer located in Chennai receives the highest score of 100, followed by a logistics volunteer in Chennai Central with 94, a rescue volunteer in Madurai with 85, and a cooking volunteer in Madurai with 52. This example demonstrates how the system balances skills, location, availability and disaster-specific requirements; it is illustrative rather than a real-world performance evaluation.

Despite its potential, the current prototype has several limitations. Location matching relies on text comparisons rather than geographical distance, and skill matching uses basic keyword rules. NGO verification is performed manually, and the scoring weights have not been validated against real disaster-response data. Further improvements should include stronger authentication and security, geolocation-based matching, standardised skill categories, automated NGO verification where possible, notifications, live resource tracking and mobile support. The algorithm should also be evaluated with disaster-management professionals and real or simulated incidents.

Conclusion

We presented the Smart Disaster Platform, a role-based web system that combines approval-gated onboarding of NGOs and volunteers, structured disaster requests and an explainable weighted ranking of volunteers. The implementation uses common open-source technologies, which makes it easy to deploy and extend. The worked example shows how the ranking behaves, and the discussion identifies the security, matching and evaluation work needed to move from prototype to field use.

References

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Copyright

Copyright © 2026 Deepa G, Dhivya K, Hemavathi R. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.