Smart Leakage Management System for China's Water Supply: Leading Suppliers & Factory Solutions
Working Principle:
AI flow measurement algorithm based on "cloud collaboration"
- Simulated working conditions based on simulation test bench and real working conditions of multiple water companies
- Collect data on different pipe diameters, pressures, temperatures, and branch pipes to establish an AI flow measurement algorithm model
- The cloud-based AI flow measurement algorithm continuously optimizes and learns, making flow measurement accuracy more precise
Frequently Asked Questions
What is the core working principle of this AI flow measurement?
It utilizes an AI flow measurement algorithm based on "cloud collaboration" that continuously learns and optimizes flow data.
How is the AI flow measurement model established?
The model is built by collecting data under various simulated and real working conditions from multiple water companies, focusing on different pipe diameters, pressures, temperatures, and branch pipe configurations.
What variables does the algorithm consider for flow measurement?
The algorithm processes data points including pipe diameters, system pressures, fluid temperatures, and branch pipe characteristics to ensure high precision.
How does cloud collaboration improve measurement accuracy?
The cloud-based AI system continuously receives new operational data, allowing the algorithm to learn, optimize, and refine its measurement parameters over time.
Are real-world water company conditions used in the testing process?
Yes, the system is calibrated using both simulation test benches and the actual, real-world working conditions of multiple water utility companies.