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@article{210234,
        author = {Samuel Dhinakar R and Sabari S and Sanmaya Shree S and Santhiya T and Santhosh BB},
        title = {ReliefMatcher.AI: An AI-Assisted Resource Matching Framework for Disaster Relief Coordination},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {6},
        pages = {146-150},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=210234},
        abstract = {Natural disasters such as floods, cyclones, earthquakes, and landslides create urgent demand for food, drinking water, medicines, shelter, transport, and other essential supplies. Relief operations can be slowed by fragmented communication, limited visibility of available resources, duplicated requests, and difficulty identifying the most urgent needs. This paper presents ReliefMatcher.AI, a web-based disaster relief resource matching platform developed to support coordination between people requesting assistance, donors, volunteers, rescue teams, and relief organizations. The system records available resources and relief requests, then uses a scoring-based matching workflow to compare relevant factors including resource category, quantity, location, availability, and urgency. Requests can be assigned priority levels—Critical, High, Medium, and Low—to help users identify cases that may need earlier attention. The implementation described in the project report uses a React and Vite frontend, a Flask backend, and SQLite for data persistence, with map-based visualization and dashboard-oriented components. The deployed project is available at the project website. Functional checks described in the report cover user access, resource entry, request submission, matching, prioritization, and request tracking. The available documentation does not provide a reproducible benchmark dataset or measured accuracy, latency, or field-outcome results; therefore, the system is presented as a decision-support prototype rather than a validated emergency dispatch service. Future work includes stronger field validation, offline-friendly operation, multilingual access, secure verification, and integration with authorized disaster-management data.},
        keywords = {Disaster Relief, Resource Allocation, Humanitarian Logistics, Artificial Intelligence, Decision Support, Priority-Based Matching, Web Application},
        month = {November},
        }