Intelligent sensor network deployment and data analysis in nuclear chemical engineering

In order to improve the efficiency and reliability of intelligent monitoring and data analysis in nuclear and chemical engineering, a design scheme of intelligent sensor network system based on microservice architecture is proposed. The system adopts a layered architecture and combines edge computing and cloud computing technologies to achieve efficient collection, processing and analysis of multi-source data. By optimising the sensor selection and deployment strategy, the accuracy of radiation monitoring, temperature and pressure parameter detection and chemical composition analysis is improved. The application of data fusion and deep learning algorithm effectively enhances the fault diagnosis and prediction ability under complex working conditions. The experimental results show that the system performs well in monitoring coverage, data transmission reliability and anomaly warning capability, especially in the radiation monitoring scenario, which significantly improves the nuclide identification accuracy and warning advance, and verifies the applicability and efficiency of the scheme.