International Journal of Science, Engineering and TechnologyAuthors: Abinaya M, Kanchana B, Santhiya D, Gayathri M
Abstract: Agriculture is a key area of focus, as it is important for the global food supply, and millions of farmers around the world live off their agricultural products. Rainfall has become increasingly unpredictable. Temperature patterns have become increasingly variable. Climate patterns have shifted. Also, farmers often lacked access to modern climate prediction and advisory services. Erratic rainfall, temperature variations, and seasonality have caused climatic risk, a major source of uncertainty for all farmers, especially smallholders. Existing models have relied on static patterns of historical climatic data and failed to account for events over time. In addition to low productivity, revenue loss also occurred. In contrast to previous models that suggested strict recommendations based on past data and crop conditions, the proposed model provided data-driven and optimal recommendations, such as the best sowing time and the best crop for precision agriculture. Additionally, it was a scalable and reliable crop failure risk model and could improve productivity and sustainable climate-resilient agricultural practices.
DOI: http://doi.org/10.5281/zenodo.21701812
