Integration of Artificial Intelligence (AI) to generate personalized weather and crop advisories: A case study of Meghdoot app in India

Accurate and timely agricultural weather information is crucial, given the evolving environmental dynamics and increased climatic variability. The report emphasizes the significance of tailored weather and climate-based advisories for farmers and highlights the dispersed nature of essential information across various organizations and formats. Despite advancements in meteorological analysis capabilities, there are still gaps in effectively translating data into tangible actionable advisories. To address this issue, the report delves into the impact of Meghdoot, a mobile application designed in India to provide tailored crop management recommendations alongside district-level meteorological data. To further improve the provisioning of crop management advisories, Artificial Intelligence (AI) techniques were used in a pilot project as an alternative to the existing labor-intensive manual process. The suggested approach involves a comprehensive integration of observed meteorological data, anticipated data, and past crop advisories. It utilizes an OpenAI quick architecture for natural language processing and a Random Forest regressor for predictions.