Wireless water quality monitoring for improved drinking water system management
Wireless water quality monitoring for improved drinking water system management
批准号:
570897-2021
负责人:
Peleato, NicolasNM
金额:
$21.9万
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
信息和通信技术的进步使城市能够更智能地管理基础设施和服务。智慧城市发展的一个有前途的领域是提高饮用水基础设施的监测和控制能力。提供安全优质的饮用水是一项基本的公共服务。然而,对供水管网边缘或客户水质的实时监测有限,最终是在哪里用水,而水质是最重要的。供水系统的水质一直是供水系统管理的普遍挑战,监测不足导致未能及时发现短期污染事件和水质恶化或污染。该项目旨在通过开发无线水质传感器在服务连接(即连接到家庭或客户的使用点)进行监测,来解决在分配系统中保持水质方面的挑战。这项技术将使公用事业公司能够更快地对水质问题做出反应,并提供更多的空间信息。此外,在客户使用点监测数据将提高客户对供水质量的保证。该项目还希望利用大量监测数据来开发人工智能模型,以帮助更严格地控制水处理过程。开发的模型将侧重于减少氯的用量,以限制潜在有害副产品的形成,同时确保有足够的氯存在,以保护公众健康。
英文摘要
Advancements in information and communication technologies are enabling cities to manage infrastructure and services more intelligently. A promising area of smart city development is improving the capabilities of monitoring and controlling drinking water infrastructure. Delivery of safe and high-quality drinking water is an essential public service. However, there is limited real-time monitoring of the water distribution networks' edges or customer water quality, ultimately where the water is used, and quality matters the most. Water quality in distribution systems has been a pervasive challenge for water systems management, with inadequate monitoring leading to untimely detection of short-term contamination events and water quality deterioration or contamination. This project aims to address challenges with maintaining water quality in distribution systems by developing wireless water quality sensors for monitoring at service connections (i.e. connection to a home or at the customer's point of use). This technology will enable utilities to respond to water quality issues faster and with greater spatial information. Furthermore, monitoring data at customer use points will increase customer assurance in the delivered water quality. The project also looks to leverage large amounts of monitored data to develop AI models that would aid in tighter control of the water treatment processes. The developed models will focus on reducing chlorine dosing to limit the formation of potentially harmful byproducts while ensuring that sufficient chlorine is present to protect public health.
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