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农学学报 ›› 2025, Vol. 15 ›› Issue (7): 57-64.doi: 10.11923/j.issn.2095-4050.cjas2024-0095

• 农业工程 农业机械 生物技术 食品科学 • 上一篇    下一篇

基于AIoT的智慧农业无土栽培系统设计与应用

林海(), 黄杜辉, 李景国   

  1. 湛江幼儿师范专科学校信息科学系人工智能大师工作室,广东湛江 524084
  • 收稿日期:2024-05-08 修回日期:2024-09-05 出版日期:2025-07-20 发布日期:2025-07-18
  • 作者简介:

    林海,男,1976年出生,广东湛江人,副教授,本科,研究方向:人工智能物联网方向。通信地址:524300 广东省湛江市遂溪县遂城镇运河东路5横一巷10号,E-mail:

  • 基金资助:
    广东省科技创新战略专项资金重点项目“基于边缘计算的智慧公路管理系统设计”(pdjh2023a1047); 湛江幼儿师范专科学校大学生创新创业训练计划项目“智创生活—做Al水培蔬菜领班者”(2023ZYDC01)

Design and Application of Soilless Cultivation System in Smart Agriculture Based on AIoT

LIN Hai(), HUANG Duhui, LI Jingguo   

  1. AI Master Studio of Department of Information Science, Zhanjiang Preschool Education College, Zhanjiang Guangdong 524084
  • Received:2024-05-08 Revised:2024-09-05 Online:2025-07-20 Published:2025-07-18

摘要:

针对土地资源匮乏、气候变化和环境污染等严峻现实,本研究通过设计一种基于AIoT技术的无土栽培智慧系统,将无土栽培与现代信息技术相融合,旨在突破传统农业的瓶颈,推动农业自动化、智能化和精细化管理的发展。该系统融合了物联网感知、视觉识别、大数据分析和机器学习等技术,采用多源异构数据融合分析作物生长状况,利用人工智能算法对温室环境智能调控,并通过Web/移动端实现远程可视化监控。整个系统在Jetson nano平台上实现软硬件高度集成,具备优良的并行计算能力和扩展性。实验结果表明,相较于人工管理组,该系统智能调控下的蔬菜生长周期缩短了15.4%,植株高度增加了17.0%,叶片数量增加了26.7%,株重提高了27.4%,且远程操控界面便利高效,验证了系统在促进无土栽培农业现代化方面的卓越性能。该系统为精准农业发展提供有力技术支撑,有望推动现代农业实现可持续高效绿色发展。

关键词: 无土栽培, 智慧农业, 物联网, 人工智能, 大数据分析, AIoT

Abstract:

In response to the pressing challenges of land resource scarcity, climate change, and environmental pollution, this study designs an AIoT-based smart soilless cultivation system that integrates soilless cultivation with modern information technology. The system aims to overcome the limitations of traditional agriculture and promote the development of agricultural automation, intelligence, and precision management. This system incorporates Internet of Things (IoT) sensing, computer vision, big data analytics, and machine learning technologies. It employs multi-source heterogeneous data fusion to analyze crop growth conditions, utilizes artificial intelligence algorithms for intelligent greenhouse environment regulation, and enables remote visual monitoring through web and mobile interfaces. The entire system is highly integrated in terms of hardware and software on the Jetson nano platform, offering excellent parallel computing capabilities and scalability. Experimental results demonstrate that, compared to the manually managed control group, vegetables under the intelligent regulation exhibited a 15.4% shorter growth cycle, a 17.0% increase in plant height, a 26.7% increase in leaf count, and a 27.4% improvement in plant weight. Additionally, the remote control interface proved to be convenient and efficient, validating the system's outstanding performance in promoting the modernization of soilless agricultural cultivation. This system provides robust technical support for the development of precision agriculture and has the potential to drive modern agriculture towards sustainable, efficient, and environmentally friendly development.

Key words: soilless cultivation, smart agriculture, Internet of Things, artificial intelligence, big data analysis, AIoT