Optimizing resource allocation in remote healthcare via blockchain-enabled decentralized networks and spectral clustering - A. Kanimozhi; K. Vidya (Automatika)
Healthcare accessibility in remote regions is hindered not by a lack of resources but by delayed and inefficient delivery mechanisms. This study addresses the critical issue of healthcare resource misallocation through a blockchain-enabled, decentralized communication framework integrated with advanced clustering techniques. The proposed system utilizes the InterPlanetary File System (IPFS) to handle resource requests transparently and securely, while spectral and agglomerative clustering algorithms are employed to optimize delivery routes. A variant of the Travelling Salesman Problem is adapted to minimize travel time and resource expenditure. The methodology includes real-time request broadcasting, secure node authentication using cryptographic keys, and dynamic route planning. Performance was evaluated using clustering metrics such as Silhouette Coefficient (up to 0.013), Davies-Bouldin Index (as low as 1.45), and Calinski–Harabasz Index (above 1.1), with the Agglomerative-Spectral combination yielding the most efficient clusters. Comparative analysis confirms significant improvements over existing methods in cluster compactness, path variability, and system scalability. The proposed framework shows strong potential for transforming telemedicine and emergency healthcare logistics in underserved regions.