The Public Distribution System (PDS) plays a vital role in ensuring food security by distributing subsidized food commodities to economically weaker sections of society. However, the traditional distribution model faces several operational challenges including long queues at ration shops, lack of transparency, manual record keeping, and leakage of commodities during distribution. These limitations reduce the efficiency and reliability of the system. This paper proposes an AI-Powered Trusted Community Delivery Model designed to modernize the Public Distribution System using intelligent monitoring and digital verification mechanisms. The proposed system integrates artificial intelligence techniques such as route optimization algorithms, GPS-based tracking, OTP-based delivery authentication, and centralized administrative dashboards. The model introduces verified community delivery personnel who distribute ration commodities directly to beneficiaries at their homes. The system ensures transparency and accountability through real-time monitoring and automated delivery confirmation. The proposed framework has been validated through a prototype implementation and simulation-based analysis to demonstrate its feasibility and effectiveness. The results indicate that the model can serve as a practical and scalable solution for enhancing public welfare distribution systems.
A/P et al. (Thu,) studied this question.
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