Abstract: Agricultural non-point source pollution not only causes the deterioration of surface water environment, but also seriously restricts the green and sustainable development of agriculture. In recent years, with the increasing emphasis on non-point source pollution control in China, relevant monitoring plans and management systems have gradually been established. However, there are still problems with low effectiveness in non-point source pollution control. We summarised the current status of monitoring targets, spatiotemporal resolution, source identification methods and management measures for non-point pollution monitoring at different scales. It pointed out the problems of discontinuous monitoring of non-point source pollution, insufficient spatiotemporal refinement and estimation accuracy of non-point source pollution load, lack of dynamic identification of pollution sources, and insufficient matching between pollution sources and management measures, which directly or indirectly lead to the imperfect monitoring system, insufficient intelligence, low level of refinement, and low efficiency of pollution control for non-point source pollution. With development of informatization and digitization, the Internet of Things platform has become a key lever for intelligent supervision by integrating sky and ground integrated monitoring equipment and algorithms, providing technical support for fine monitoring of non-point source pollution. It is proposed to construct an intelligent observation system for agricultural non-point source pollutant Internet of Things to improve the observation accuracy of key parameters, use the “non-point source model + fingerprint tracing” technology system for identifying and tracking multiple sources of non-point source pollutants sources area, and consider the effectiveness evaluation and scheme optimization of multi-source and multi governance models to solve the problem of precise and differentiated governance. Improve the systematic, integrated, and intelligent level of non-point source control, bridging the key breakthrough path from “monitoring” to “treatment”. During the "14th Five-Year Plan" period, the National Key Research and Development Plan launched and implemented the key special project of "Agricultural Non-Point Source, Heavy Metal Pollution Prevention and Control and Green Input Product Research and Development", which focused on the relevant research of "Intelligent Monitoring, Risk Identification and Regulation Technology of Non-Point Source Pollutants in Typical Basins". Among them, the application and demonstration of the Internet of Things intelligent monitoring platform was carried out in the Taihu Basin, which has both plain and hilly complex terrain, dense population, and active agricultural activities. This typical case has integrated monitoring instruments, non-point source pollution simulation model, pollution source identification and other parts, providing an important reference for intelligent supervision of agricultural non-point source pollution.