Abstract:

【Objective】 To understand the key technologies and applications of smart agriculture, including the Internet of Things, sensor technology, remote sensing technology, artificial intelligence and machine learning, big data technology and large-scale modeling technology, as well as the precision, automation and intelligence at the agricultural management level. Analyze the practical experience and enlightenment of smart agriculture. 【Methods】 Literature data were collected, summarized and sorted out. The key technologies and application cases of smart agriculture were analyzed by statistical methods. 【Results】 The Internet of Things technology is the cornerstone of smart agriculture, and users can remotely monitor crop growth conditions and environmental changes, and timely make corresponding management. Sensor technology is used to monitor the crop growing environment and biological information in real time, and agricultural sensor is the source technology of modern agricultural development mode such as digital agriculture, information agriculture, and smart agriculture. Remote sensing technology provides macroscopic monitoring means for agricultural production. 【Conclusion】 Artificial intelligence and machine learning technology bring intelligent decision support to smart agriculture, and big data technology plays the role of analysis and decision support in smart agriculture.

Key words: literature review; smart agriculture; experience; practice

摘要：

【目的】了解智慧农业的关键技术和应用,包括物联网、传感器技术、遥感技术、人工智能与机器学习、大数据技术以及大规模技术,以及在农业管理水平的精准化、自动化和智能化。分析智慧农业的实践经验和启示。【方法】文献资料收集、汇总与整理。运用统计学方法分析智慧农业的关键技术及应用案例。【结果】物联网技术是智慧农业的基石,用户可以远程监控作物生长状况和环境变化,及时做出相应的管理。传感器技术用于实时监测作物生长环境和生物信息,农业传感器是数字农业、信息农业、智慧农业等现代农业发展模式的源头技术。遥感技术为农业生产提供了宏观的监测手段。【结论】人工智能和机器学习技术为智慧农业带来智能化的决策支持,大数据技术在智慧农业中扮演着分析和决策支持的角色。

关键词: 文献综述, 智慧农业, 经验, 实践