Application of Multi-node Intelligent Monitoring System in Concrete Construction

This article first designs a new type of intelligent monitoring node, which is suitable for concrete construction applications in remote areas. Intelligent nodes have advantages such as battery power supply, low-power design, no need for external connections, and convenient networking. Intelligent nodes have advantages such as battery power supply, low power consumption design, no need for external connections, and convenient networking, as well as monitor the core temperature, external temperature, and internal strength information of concrete in real-time during construction and upload data wirelessly. Subsequently, a detailed discussion was conducted on the multi-node and multi-sensor information fusion algorithm based on Kalman filtering for the intelligent node. The algorithm first performs outlier removal on the collected data, then the algorithm considers the core temperature, external temperature, and intensity information as a whole and parallelly calculates the fusion information of multiple nodes and sensors. The experimental results show that under the information fusion of 10-100 sensors, the average measurement accuracy of core temperature is improved by 70.80%, the average measurement accuracy of external temperature is improved by 67.45%, and the average measurement accuracy of internal strength information is improved by 68.87%. Moreover, as the number of sensors increases, the measurement accuracy will further improve. The new intelligent monitoring node designed in the paper meets the needs of the vast majority of concrete construction scenarios. The sensor information fusion algorithm designed based on the intelligent node has low computational complexity, simple parameter adjustment, and significant improvement in measurement accuracy, whichs can not only accelerate construction progress, reduce construction costs, and ensure construction quality, but also provide strong support for intelligent analysis and judgment of subsequent multi node concrete monitoring networks.