Published Paper Details:

The accelerating threat of climate change demands innovative and data-driven solutions. Artificial Intelligence (AI), powered by machine learning and deep learning, has emerged as a transformative tool to address both climate change mitigation and adaptation. This research paper explores how AI-enabled "smart models" can analyze massive and complex datasets, enhance predictive capabilities, and optimize resource utilization for sustainable development. Applications range from renewable energy forecasting and precision agriculture to disaster prediction and carbon monitoring. The paper highlights both existing work and future opportunities, while also addressing key challenges such as energy costs, algorithmic bias, and data inequities. By proposing an integrated framework that emphasizes inclusivity, energy efficiency, and explainability, this work contributes toward shaping a sustainable and equitable AI-driven climate future.