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物联网与人工智能技术在智慧农业中的应用研究OA

Research on Integrated Application of Internet of Things and AI Technologies in Smart Agriculture

中文摘要英文摘要

探讨物联网与人工智能技术如何推动现代农业的智能化转型,以期为智慧农业发展提供理论依据.本研究采用文献综述法,系统梳理大数据时代背景下,物联网、大数据和人工智能等关键技术在现代智慧农业中的具体应用现状.结果表明,物联网技术实现了农业环境的实时监测,大数据技术为农业生产决策提供了数据支持,而人工智能则在智能育种、产量预测、病虫害识别等领域展现出巨大潜力.物联网、大数据与人工智能的深度融合是提升生产智能化水平的关键.本文剖析了当前在数据、成本、标准与人才方面面临的挑战,并展望了跨模态数据融合、轻量化AI、迁移学习、区块链安全及人机协同等未来方向,以期为相关研究提供借鉴,推动该领域的理论创新与实践落地.

This study aims to explore how the Internet of Things(IoT)and artificial intelligence(AI)technologies can drive the intelligent transformation of modern agriculture,with the intention of providing a theoretical basis for the development of smart agriculture.This study employs the literature review method to systematically sort out the current application status of key technologies,including IoT,big data,and AI,in modern smart agriculture against the backdrop of the big data era.The findings indicate that IoT technology enables real-time monitoring of agricultural environments,big data technology provides data support for agricultural production decision-making,and AI demonstrates immense potential in areas such as intelligent breeding,yield prediction,and pest and disease identification.The deep integration of IoT,big data,and AI is the key for improving the level of intelligent production.At the same time,this paper analyzes the current challenges in data,cost,standards and talents,and looks forward to the future directions of cross-modal data fusion,lightweight AI,transfer learning,blockchain security and human-machine collaboration,in order to provide reference for related research and promote theoretical innovation and practice in this field.

俞静;许士芳;韩小双

上海市松江区农业技术推广中心蔬菜推广科,上海 201600上海市松江区农业技术推广中心蔬菜推广科,上海 201600上海市松江区农业技术推广中心蔬菜推广科,上海 201600

农业科技

物联网大数据人工智能深度学习云计算智慧农业

Internet of Thingsbig dataartificial intelligencedeep learningcloud computingsmart agriculture

《中国农学通报》 2026 (1)

211-218,8

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