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.

中文翻译：

---

用于物联网漏水检测系统的基于 AIN 的 MEMS（微机电系统）水听器传感器

迫切需要工业物联网 (IoT) 解决方案来部署智能水听器传感器网格，以监测管道健康状况并在发生任何泄漏时提供准确预测。一种解决方案是开发一个物联网漏水检测系统，该系统由一个接口组成，用于捕获来自基于氮化铝 (AlN) 的微机械次声水听器传感器的声学信号，这些传感器作为输入提供，并以输出形式预测近似泄漏位置。微机电系统 (MEMS) 对于具有低功耗和小设备占用空间的物联网应用特别有用。应用包括表征、预处理/后处理在内的数据分析来确定泄漏。在这项工作中，我们开发了流程和算法来检测管道泄漏的发生并准确定位位置。我们的方法可用于检测不同管道长度、直径和材料的泄漏。