AI and machine learning are becoming powerful tools in helping us predict extreme weather and rising sea levels, challenges that deeply affect coastal farming communities. By analyzing huge amounts of data from satellites, weather stations, and ocean sensors, these technologies can spot early warning signs of storms, floods, droughts, or creeping sea-level rise. This means farmers in coastal areas can get timely alerts and plan ahead whether it's adjusting planting schedules, protecting crops, managing irrigation, or moving livestock to safer ground. AI can even help predict things like soil salinity or saltwater intrusion, and suggest more climate-resilient crop options. In simple terms, AI turns complex climate data into practical, easy-to-understand advice that helps people on the ground make smarter, faster decisions, protecting their land, their harvests, and their futures.

AI and ML play a critical role in forecasting extreme weather events and rising sea levels by analyzing vast climate datasets, identifying anomaly patterns, and enabling early warnings. These insights support timely agricultural interventions in coastal regions, such as switching crops, adjusting planting schedules, or reinforcing infrastructure. Predictive models can help optimize resource allocation and mitigate climate-related losses in vulnerable agri-ecosystems.

In this context, my paper "Advanced Crop Recommendation System: Leveraging Deep Learning and Fuzzy Logic for Precision Farming" (IJAESR, 2022) presents a hybrid AI system using deep learning and fuzzy logic to recommend crops based on yield forecasts, climate data, and market dynamics. While focused on precision farming, the approach directly supports climate-aware agricultural decision-making, which is essential for coastal resilience and adaptation.

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Article ADVANCED CROP RECOMMENDATION SYSTEM: LEVERAGING DEEP LEARNIN...