鲁尔物联-物联网数字底座

Scene Introduction

The urban water supply industry, a vital part of national infrastructure, is crucial for urbanization planning and balancing the interplay of life, production, and ecology.

Enabled by advanced technologies such as the Internet of Things (IoT), cloud computing, and hydrodynamic analysis, the Ruhr IoT Water Delivery Network Sensing System integrates a water quality monitoring system, a water delivery network monitoring system, and an early warning platform to ensure safety of the water supply.

Demand Analysis

Burst of Water Supply Pipe

Burst of Water Supply Pipe can lead to the following issues: disruption of water supply, accumulation of water on roads and traffic disruptions, collapse and sinkholes of road.

Water Quality Non-Compliance

Water Quality Non-Compliance could severely endanger residents' lives and safety, and may lead to widespread social issues if not addressed promptly.

Insufficient water supply pressure

Many residents in high-rise urban buildings face frequent water pressure issues caused by inadequate secondary water supply systems, resulting in significant disruptions to their daily routines.

Program Highlights

Comprehensive Water Quality Monitoring System

The Comprehensive Water Quality Monitoring System covers the entire water production process, including water sources, water treatment plants, distribution networks, and water tanks. The system real-timely uploads water quality data and alerts.
Intelligent Water Pressure Regulation System

based on water pressure monitoring data and water usage conditions within the pipeline, the system automatically analyses water usage during peak and off-peak periods to realize pipeline pressure intelligent adjustment and guarantee normal water usage of residents.
Risk Assessment of Water Delivery Network

Static Risk Assessment Model： focuses on historical data and fixed attributes (e.g., pipeline material, age, and past failure records); provides a baseline understanding of potential risks; dynamic Risk Assessment Model; incorporates real-time data (e.g., pressure, flow rates, and temperature) and environmental factors (e.g., weather, soil conditions); provides Offers a more adaptive and responsive risk evaluation.