AI BASED CARBON CREDIT AUTHENTICATION, FOOTPRINT CALCULATION AND TRANSACTION VERIFICATION SYSTEM

Abstract: The increasing need for transparent and efficient carbon credit markets has led to the exploration of Artificial Intelligence (AI) to address fraud, double-counting, and inefficiency in traditional carbon credit trading systems. This paper proposes an AI-based carbon credit trading system that leverages machine learning and predictive analytics to provide a transparent, secure, and automated marketplace for buying and selling carbon credits. Through the use of AI-driven smart algorithms, the system automates the issuance, verification, and trading of carbon credits, reducing transaction costs and eliminating intermediaries. The system ensures that each carbon credit represents a verified and actual reduction in emissions by employing AI-powered data validation and anomaly detection, offering real-time tracking and traceability. Furthermore, the advanced analytical capabilities of AI promote inclusivity, enabling a broader range of participants to engage in emission reduction efforts. This system not only fosters environmental accountability but also drives global sustainability by providing an accessible, cost-effective, and scalable solution to meet emission reduction targets and combat climate change.

Keywords: Artificial Intelligence, Carbon Credit Trading, Smart Contracts, Transparency, Machine Learning.