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.