Artificial Intelligence Driven Weather Forecasting Framework for Sustainable Agriculture

B, Jeevan; Heeraman, Jatoth; Vinod, Ratod; Tejaswi, S Padma

Volume 2, Issue 2 (11-2026) AISEE 2026, 2(2): 131-139 | Back to browse issues page

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B J, Heeraman J, Vinod R, Tejaswi S P. Artificial Intelligence Driven Weather Forecasting Framework for Sustainable Agriculture. , AISEE. 2026; 2 (2) :131-139
URL: http://aisesjournal.com/article-1-48-en.html

Artificial Intelligence Driven Weather Forecasting Framework for Sustainable Agriculture

Jeevan B

, Jatoth Heeraman ^*

, Ratod Vinod

, S Padma Tejaswi

Department of Mechanical Engineering, Malla Reddy (MR) Deemed to be University, Hyderabad, Telangana, 500100, India.

Abstract: (14 Views)

This research presents an intelligent weather prediction system designed to enhance decision-making in agriculture through accurate, location-specific forecasting. The proposed framework integrates Internet-connected weather stations, Earth-observation datasets, and artificial intelligence algorithms to generate reliable short- and medium-term predictions. By analyzing historical temperature records, soil conditions, humidity patterns, and climate variables, the system provides farmers with actionable insights tailored to crop growth requirements. In addition, an integrated alert mechanism notifies users of potential weather-related hazards, enabling timely preventive measures to protect crops, livestock, and farm infrastructure. The model delivers real-time agricultural information through an accessible interface, ensuring usability even for farmers with minimal technical proficiency. Overall, the system aims to improve agricultural sustainability and productivity by mitigating the risks associated with increasingly unpredictable climatic conditions.