Applications of Artificial Intelligence in Weather Prediction and Agricultural Risk Management in India
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Artificial Intelligence, Risk Management, Weather Prediction
Abstract
Agriculture in India is particularly vulnerable to climate change and extreme weather conditions, which can negatively impact productivity and food security. This research was conducted against the background of the importance of developing technology to help farmers in dealing with weather uncertainty and managing agricultural risks. The purpose of this study is to explore the application of artificial intelligence (AI) in accurately predicting weather as well as managing the risks associated with extreme weather in India's agricultural sector. This study uses a descriptive method with a quantitative and qualitative approach, where data is collected through interviews with agricultural experts, analysis of historical weather data, and AI modeling. The results show that the AI application is able to predict weather patterns with an accuracy rate of up to 90%, which helps farmers make more informed decisions regarding planting timing, irrigation, and pesticide use. In addition, AI-based risk management systems allow for early detection of extreme weather, thereby reducing crop losses. The conclusion of the study is that artificial intelligence applications have great potential to improve food security and agricultural productivity in India by helping farmers anticipate weather changes and manage risks more efficiently. However, the adoption of this technology requires adequate training and infrastructure to ensure its optimal use in the field.
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References
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Copyright (c) 2024 Aldi Bastiatul Fawait, Puteri Aprilani, Sugiarto Sugiarto, Vann Sok
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