Artificial intelligence for leak monitoring in water distribution networks

用于供水管网泄漏监测的人工智能

• 批准号: 560711-2020
• 负责人: Cascante, Giovanni
• 金额: $ 2.19万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=707018
• 关键词: Artificial; intelligence; leak; monitoring; water

Nearly 25-30% of drinking water is estimated to be lost between treatment and delivery. This is not only a loss of revenue and wasted energy from storage to delivery, but also a loss of valuable resource when nearly 1 in 10 people on our planet lack access to clean drinking water. Conventional leak detection technologies rely on inspection methods which involve cumbersome processes and expert interpretation of data to determine the presence of leaks and their location. Our industrial partner has invested in a patented monitoring system which can be installed on fire hydrants to detect and locate leaks, year-round even in cold climates. However, the decision-support tools are basic and have significant room for advancement using artificial intelligence (AI) and latest developments in communication technologies, including 5G. This project aims to bring latest developments in AI to bear on the problem of leak detection and localization in water distribution systems. Most importantly, through this partnership, new algorithms and processes which have been developed and validated by the academic team in controlled laboratory and field environments will be further developed and translated to real-world complex operational environments. It is anticipated that such advancements will increase detection rates and robustness, while also reducing or eliminating the need for expert user intervention. Through this collaboration, trainees will also gain skills in machine learning and signal processing which are in high demand in Canada and worldwide.

据估计，在治疗和分娩之间损失了近25-30%的饮用水。这不仅损失了收入，浪费了从储存到运送的能源，而且还损失了宝贵的资源，因为地球上有近十分之一的人无法获得清洁的饮用水。传统的泄漏检测技术依赖于检测方法，这些方法涉及繁琐的过程和专家对数据的解释，以确定泄漏的存在及其位置。我们的工业合作伙伴投资了一套专利监控系统，该系统可以安装在消防栓上，即使在寒冷的气候下也可以全年检测和定位泄漏。然而，决策支持工具是基本的，利用人工智能（AI）和包括5G在内的通信技术的最新发展，有很大的进步空间。该项目旨在将人工智能的最新发展应用于供水系统的泄漏检测和定位问题。最重要的是，通过这种伙伴关系，学术团队在受控实验室和现场环境中开发和验证的新算法和流程将进一步开发并转化为现实世界复杂的操作环境。预计这些进步将提高检测率和鲁棒性，同时减少或消除对专家用户干预的需求。通过此次合作，学员还将获得机器学习和信号处理方面的技能，这些技能在加拿大和全球都有很高的需求。