IoT-Based Automatic Dynamic Flow Visualization and Monitoring for Hydrological Stations

Due to geographical dispersion and dynamic water conditions, traditional manual methods are confronted with challenges such as heavy workload, delayed flood reporting, and low data processing efficiency. This study proposes a real-time flow monitoring system for water gate stations in a certain tidal river section based on Internet of Things technology. The system adopts a hierarchical architecture, integrating the water level sensor, flowmeter and positioning module into the gate acquisition unit. By using TCP-based data transmission, reliable remote communication and cloud-based dynamic flow calculation are guaranteed. Methods such as hydraulic factors and single-tide push flow are adopted to improve the monitoring accuracy of tidal river sections. At the data application level, the visual interface dynamically displays real-time water levels, flow curves and flood alerts, meeting industry standards for data accuracy and compliance. The system achieves efficient hydrological data sharing and spatio-temporal analysis through the cloud platform and multi-terminal collaboration, forming a comprehensive monitoring chain from on-site perception to cloud processing and decision support. This provides a scientific basis for intelligent water resource management and flood control decision-making.