Revolutionizing Ngo Workflow Optimization: An Ai-Based Approach for Automated Volunteer Deployment and Impact Reporting Using K-Nearest Neighbors

Workflow optimization in NGOs involves streamlining processes to improve efficiency, reduce costs, and enhance impact. In existing system, NGO system operates without a centralized platform, making difficult for collaboration and resource sharing Volunteer deployment is manual. It is leading to slow response times. It lacks intelligent algorithms for matching nearby volunteers, resulting in uncoordinated and inefficient relief efforts. In proposed system,this paper is focused on the Volunteer Disaster Management System(VDMS), a web-based application designed to support collaboration among multiple non-governmental organizations during disaster situations. It automates the coordination and assignment of volunteers using the K-Nearest Neighbors algorithm to match individuals based on their geographical location. The system includes realtime notification features to alert volunteers during emergencies and task deployments. Additionally, it offers tools for tracking volunteer activities, task status, and overall impact, ensuring transparency and accountability. The platform streamlines disaster response efforts, improves resource utilization, and connects organizations with nearby volunteers and affected communities effectively.