Smart AI Water Leakage Detection System

I&T Wish Smart AI Water Leakage Detection System
(REF: W-0478)
Matched I&T Solution
Trial Project
Summary and Challenges
  • The aging of hospital piping can lead to a variety of issues, including water leaking and low water pressure. This can compromise patient safety and the hospital's facility's overall efficiency and functioning. Water leakage is a significant problem resulting in extensive property damage, increased utility bills, and even health hazards.
  • However, in most of cases, it is too late to find out the potential water leakage location which finally causes severe damage in pipe bursting. Moreover, the piping system is complicated in hospitals across different zones and infected areas which may not be allowed to install water straps everywhere for detection.
Expected Outcome
  • We aim to develop a Smart AI Water Leakage Detection System with water leakage sensors except for traditional water strap methodology. Those sensors will collect related data throughout the building's main and branch pipes to detect changes in the water flow volume/ water pressure.
  • The data will be transmitted to a centralized system where it will be analyzed using machine learning and big data analysis from the historical data. The analysis will identify the patterns and anomalies in the data to find out the potential leaks and provide early warning in a centralized dashboard.
  • To ensure the system's accuracy, machine learning algorithms can be employed to identify normal water flow / pressure patterns and detect deviations from those patterns. This approach will enable the system to detect even small unnoticed leaks. In case of pipe bursting, the system can remotely turn off the valve automatically to reduce property damage.
Expected Trial Duration 6-month
Contact Information
I&T Wish Proposer:Electrical and Mechanical Services Department (EMSD)
Contact Person:TANG Lok Yiu
Position:Engineer/Health Sector/Hong Kong East/4
Tel:2505 0076
Email: tangly@emsd.gov.hk
Initiating Department Department of Health (DH)
Upload Date 2023-06-29
Closing Date 2023-07-13