AIN-Based MEMS (Micro-Electro-Mechanical System) Hydrophone Sensors for IoT Water Leakage Detection System

• Main Authors: Wee Kee Phua, Sarbudeen Mohamed Rabeek, Beibei Han, Edwin Njihof, Tyler Tianlu Huang, Kevin Tshun Chuan Chai, Jason Hock Huat Yeo, Soon Thor Lim
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Water
• Subjects: IoT; hydrophone; water leakage; analytics; process flow; detection
• Online Access: https://www.mdpi.com/2073-4441/12/11/2966

There is an urgent need for industrial Internet of things (IoT) solutions to deploy a smart hydrophone sensor grid to monitor pipeline health and to provide an accurate prediction in the event of any leakage. One solution is to develop an IoT water leakage detection system consisting of an interface to capture acoustic signals from aluminum nitride (AlN)-based micro-machined infrasonic hydrophone sensors that are fed as inputs and predict an approximate leak location as a form of output. Micro-electro-mechanical systems (MEMS) are particularly useful for IoT applications with low power consumption and small device footprint. Data analytics including characterization, pre/post processing are applied to determine the leaks. In this work, we have developed the process flow and algorithm to detect pipe leakage occurrence and pinpoint the location accurately. Our approach can be implemented to detect leaks for different pipe lengths, diameters and materials.