AI-Enhanced Blockchain Networks for Climate Change Monitoring and Carbon Credit Verification

Abstract

Climate change is the most pressing global problem, which warrants technological innovation in accurate monitoring and efficient market-based solutions. In this paper, we propose a framework to combine staking with artificial intelligence and blockchain to provide a transparent, secure, and efficient way of monitoring a variety of carbon credits related to carbon footprint. This uses machine learning algorithms to combine satellite imagery, IoT (wearable) data, and immutable blockchain ledgers to create tamper-proof environmental monitoring systems. It suggests brilliant contract architecture that can generate carbon credits through AI to validate the process, federated learning applications to track cross-border emission activity, and neural networks to validate carbon sequestration projects. Using these systems, we achieved orders of magnitude improvement in verification accuracy, transaction transparency, and market efficiency over traditional systems. By employing this integrated approach, some of the most pressing carbon market dilemmas, including narrowing carbon market data integrity issues, delays in verification, and deficits of trust among carbon market participants, can be resolved, and it is a strong foundation for climate action globally.