Integrating Ai-Driven Forecasting With Agricultural Practices To Combat Food Insecurity In Climate-Vulnerable Regions

Abstract

Since people in climate-change risk areas experience food shortages often, experts are now using technology to strengthen crop production. This investigation investigates how farmers can use AI forestry tools to deal with weather conditions, lower their expenses and understand the yields from their crops. The study uses environmental science, machine learning and agronomy together to explore if AI can solve problems related to hunger and environmental agriculture. They also looked into merging climate data, forecasting what to grow, designing easing warning systems and executing precision farming. For our study, we use existing data, try out models to simulate different situations and question individuals working in farming areas mostly hit by droughts and floods. According to the reports, AI helps decrease problems caused by climate change in agriculture because it can give farmers guidance immediately. Yet, there are still problems with infrastructure, not knowing enough about digital technology and concerns over bias in AI. Finally, the paper recommends ways to make AI valuable for farmers, support their development and foster teamwork among different parts of the agricultural community.