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Application of AI-driven cloud services in intelligent agriculture pest and disease prediction
- 1 Computer Science and Engineering, Santa Clara University, CA,USA
- 2 Information Studies, Trine University, AZ, USA
- 3 Business Analytics, University College Dublin, Dublin,lreland
- 4 Computer Science, Fudan University, ShangHai,China
- 5 Electrical Engineering,University of Washington,Seattle,WA,USA
* Author to whom correspondence should be addressed.
Abstract
Cloud computing technology helps agricultural operators collect the most valuable information by providing information push platforms, supply and demand information platforms, and expert interaction platforms for agricultural operators. Agricultural operators use cloud computing technology to monitor the growth of diseases, pests and grasses in farms, soil changes and weather conditions in real time, and use the data information analyzed by the cloud computing center to accurately judge the growth status of crops at any time and understand the growth laws of crops, which is conducive to improving crop yields. The article discusses the extensive application of cloud computing technology in advancing agricultural informatization in China. It outlines how cloud computing facilitates data collection, analysis, and decision-making in various agricultural sectors, leading to improved efficiency and productivity. Specific applications include monitoring crop growth, managing livestock health, facilitating agricultural e-commerce, ensuring product quality and safety, and predicting diseases and pests. The article also presents a methodology for developing an improved model for tea disease detection, leveraging techniques such as self-attention mechanisms, feature fusion networks, and transfer learning. Overall, cloud-based solutions play a crucial role in modernizing agriculture, enhancing sustainability, and increasing profitability in the sector.
Keywords
Cloud computing, Crops, Disease and pest prediction, Intelligent drive, forecast
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Cite this article
Lin,Y.;Li,H.;Li,A.;Shi,Y.;Zhuang,S. (2024). Application of AI-driven cloud services in intelligent agriculture pest and disease prediction. Applied and Computational Engineering,77,231-237.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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