Applications of Artificial Intelligence in Weather Prediction and Agricultural Risk Management in India - Zargari Benjamin; Topacio Najmeh; Mashhadi Shariati (Techno Agriculturae Studium of Research, 2024)
Accurate weather prediction and effective agricultural risk management are essential to improve the productivity and sustainability of the farm sector in India. However, extreme climate fluctuations and weather uncertainty pose significant challenges for farmers and policymakers. Artificial Intelligence (AI) offers a potential solution to this problem with its ability to analyze complex data and identify patterns. This study aims to explore the application of Artificial Intelligence in weather prediction and agricultural risk management in India. Specifically, the study seeks to develop AI models that accurately predict weather and recommend appropriate agrarian risk management strategies. In this study, historical weather data, climate data, and agricultural data were collected from various sources. Various AI techniques, such as machine learning, deep learning, and natural language processing, are used to analyze data and develop weather prediction and agricultural risk management models. The model is then validated and optimized using test data. The results showed that the developed AI model can predict the weather more accurately than conventional methods. The model can also provide specific recommendations for agricultural risk management, such as proper crop selection, optimal planting timing, and other risk mitigation strategies. This research shows the vast potential of Artificial Intelligence in improving weather prediction and agricultural risk management in India. By adopting AI technology, farmers and policymakers can make better decisions and improve the productivity and sustainability of the agricultural sector.