Research on AI decision support system for agricultural intelligentization and industrial upgrading under the background of rural revitalization

With the development of science and technology, traditional agriculture faces many challenges, such as low production efficiency and uneven quality of agricultural products, and agricultural intelligent technology has become the key to solve these problems. Firstly, this paper analyzes the demand of agricultural intelligence and industrial upgrading under the background of rural revitalization, and points out the urgency of improving agricultural production efficiency, agricultural product quality and optimizing agricultural industrial structure. Then, the architecture of agricultural AI decision support system (DSS) based on "cloud-edge-end" collaboration is proposed, which includes data perception layer, edge computing layer, cloud intelligence layer and application service layer. By integrating many advanced technologies, real-time monitoring and data collection of the whole agricultural production process are realized. In the key technology and implementation part, the core algorithm models are introduced in detail, such as LSTM combined with Attention mechanism for crop growth prediction, YOLOv7 and migration learning for pest identification, and other key technologies, such as multi-source data fusion, spatio-temporal modeling, lightweight deployment and blockchain traceability. In the aspect of data engineering system construction, the data acquisition specification, data processing flow and data storage flow are expounded. Finally, through the verification in three typical agricultural demonstration areas, the results show that the system has significantly improved the key indicators such as the accuracy of pest identification, the response time of edge calculation, the effect of fertilization decision-making and the traceability efficiency of blockchain compared with the traditional methods, effectively improving the intelligent level and management efficiency of agricultural production, and providing strong support for agricultural intelligence and industrial upgrading under the background of rural revitalization.