Reservoir
Scene Introduction Demand Analysis Program Highlights Core Products
Scene Introduction

The Ruhr IoT Reservoir Safety Monitoring and Early Warning System is based on technologies such as IoT, wireless communication, big data, and high-precision satellite positioning.

The monitoring system focuses on the safety of small and medium-sized reservoir, and establishes an automated safety monitoring and sensing network.

The monitoring system conducts comprehensive dynamic monitoring of environmental factors, deformation, seepage, stress, and strain, and provides reliable foundational data for evaluating the safety status of dams/levees.

The monitoring system design complies with relevant standards: Specification For Earth-Rockfill Technical Dam Safety Monitoring, Technical Specification For Concrete Damsafety Monitoring, Technical Code For Levee Project Safety Monitoring etc.

Demand Analysis
  • Dam-breaking Risk
    The main causes that can lead to Dam-breaking include: structural issues with earth-rock dams, seepage problems in the dam, and metal structure problems; termite infestations; operational and management issues of the reservoir.
  • Insufficient IoT Monitoring Devices
    Data monitoring issues in small and medium-sized reservoirs include: most small and medium-sized reservoirs only have manual observation facilities, and some reservoirs lack observation facilities entirelyl; the majority of data comes from manual observations; insufficient automated monitoring systems
  • Insufficient Data Governance Capability
    The reasons for insufficient data governance capabilities include: lack of unified standards in data governance; insufficient availability of real-time and dynamic monitoring data; lack of tools for analyzing real-time data; absence of a collaborative platform for cross-departmental data sharing.
Program Highlights
  • Sensing: Integrated Monitoring Framework
    The Monitoring Framework consists of the following components: Structural Safety Monitoring System; Hydrological and Rainfall Monitoring System; Video Surveillance Systems.
  • Model: Simulation and Projection
    Leveraging AI-powered predictive algorithms, the system enables simulation, prediction, and analysis of structural deformation, crack propagation, and other critical factors, providing decision-making support for managers.
  • Surveillance: Real-Time System
    Establish a multi-scenario, multi-dimensional IoT sensing network to enable real-time, automated online monitoring and data collection for the safety and operational status of hydraulic engineering facilities.
  • Analysis: Risk Assessment
    Risk assessment involves the timely evaluation and hierarchical early warning based on the extent of structural damage, development trends, and potential severity of hazards. It enables threshold-based warnings, trigger alarms, model-based alerts, and the management of warning records.
  • Enhancement: Closed-loop Management
    The enhancement of the monitoring system for management includes: Real-Time Feedback on Abnormal Status; Guides the daily operation and maintenance; Assists in rapid emergency response decision-making.
Core Products
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