AgriCarbonChain: A Blockchain and Cloud-Based Framework for AI-Assisted Verification of Agricultural Carbon Credits
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Updated time：2026-07-25 21:35:20
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Abstract
Agricultural carbon-credit programs require transparent and reliable verification mechanisms to ensure the authenticity of carbon sequestration claims. Current methods, however, tend to suffer from the lack of stakeholder confidence due to fragmented data management, centralized verification and limited auditability, which can lead to inaccurate carbon-credit distribution. AgriCarbonChain (Agricultural Carbon Credit Blockchain Framework) is a blockchain- and cloud-based framework proposed in this paper to verify agricultural carbon credits using AI. The framework brings together cloud-based data management, AI systems for carbon-sequestration assessment and fraud detection, blockchain secured verification and reporting of the carbon-credit lifecycle together in one architecture. The mathematical verification model is further developed in order to assess the carbon-sequestration, verification confidence, carbon-credit eligibility and fraud risk. It was tested with integrated agricultural and environmental data for various scenarios of carbon-credit verification. The results of the experiments show that AgriCarbonChain can accurately verify 98.2% of the samples, detect fraud 96.3% of the time, and provide a level of confidence in the verification process of 97.1%. Moreover, the AI-assisted verification model achieved an AUC value of 0.986, and an average precision of 0.981, demonstrating strong and reliable verification accuracy. The proposed framework is scalable, transparent and trustworthy for agricultural carbon-credit verification and enables secure evidence-based carbon-credit management.
Keywords
Agricultural carbon credits, Artificial intelligence, Blockchain, Cloud computing, Carbon sequestration, Carbon-credit verification, Fraud detection, Sustainable agriculture.
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