AgriAidBlock – AI-Powered Agricultural Resources and Subsidy Allocation for Farmers with Blockchain Transparency
1M.JEEVAROSHINI,2S.NESIKA,3J.POONGUZHALI,4MRS.N.DHAMAYANDHI
1,2,3Student, 4 Assistant Professor ,Department of Computer Science and Engineering Kings College of Engineering, Punalkulam, Pudukotai.
jeeveroshini55@gmail.com nesika180@gmail.com poonguzhalik04@gmail.com
Abstract:
Agricultural subsidy distribution systems in developing economies face persistent challenges including inefficient beneficiary prioritization, manual verification delays, duplicate claims, and lack of transparency. Conventional rule-based allocation frameworks fail to dynamically assess farmer-specific risk factors such as landholding size, crop profile, financial vulnerability, and historical subsidy utilization. These limitations reduce fairness, accountability, and operational efficiency in subsidy disbursement.This paper presents AgriAidBlock, an integrated AI–Blockchain framework designed to enhance accuracy, transparency, and security in agricultural subsidy allocation. The proposed system employs a supervised machine learning model, specifically XGBoost, to predict and prioritize eligible beneficiaries based on multi-dimensional farmer data. To address concerns of data integrity and trust, a blockchain- based smart contract mechanism is implemented to ensure immutable recording, transparent validation, and tamper-resistant fund disbursement.The integration of predictive analytics with decentralized ledger technology enables automated decision-making, minimizes fraudulent claims, reduces administrative delays, and improves traceability of subsidy transactions. The proposed framework demonstrates how AI-driven prioritization combined with blockchain-enabled governance can significantly enhance the reliability and accountability of agricultural welfare programs
Key words: Agricultural Subsidy Allocation, XGBoost, Artificial Intelligence, Blockchain Technology, Smart Contracts, Fraud Detection, Decentralized Governance.
