SCC-PG: Community Based Approach to Address Heavy Metal Contamination in Drinking Water using Cloud-Connected Smart Electrochemical Sensors

SCC-PG：使用云连接的智能电化学传感器解决饮用水中重金属污染的基于社区的方法

• 批准号: 1952147
• 负责人: Pradeep Kurup
• 金额: $ 15万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952147&HistoricalAwards=false
• 关键词: SCC; PG; Community; Based; Approach

Millions of people In the US use drinking water with potentially unsafe levels of heavy metals. Heavy metal contamination of water can be due to leaching of lead and copper from plumbing, anthropogenic activities including mining, industrial and agricultural, among others. In this planning grant engineers, computer scientists, and social scientists will work closely with community stakeholders (residents, community leaders, regulators, utility managers) from the socioeconomically diverse communities of Lowell, Lawrence, Dracut, Westford, and Chelmsford, in Massachusetts, to explore the feasibility of a smart, community-engaged water-quality monitoring and warning system based on user-friendly handheld Electronic Tongue (E-Tongue) devices capable of detecting drinking water contamination. These devices will provide reliable water quality data, and empower citizens to test their own water, aggregate data from their community, and act when a problem is apparent. Cloud-based machine learning algorithms will take the responses from the individual E-Tongue devices and produce predictions about how widespread the problem is, whether the problem is local or systemic, and what other locations may have been contaminated. Further, these predictions would be valuable, for example, in helping to determine which residents in the surrounding area should receive alert notifications to test their own water quality. It could also help notify the local government of the potential need to take action. Through a series of workshops, the project will incorporate and be informed by the perspective of residents in areas such as the effective presentation of the water quality data, privacy concerns community members may have about sharing their water quality data, and the factors that affect the adoption of the technology by the community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在美国，数以百万计的人使用重金属含量可能不安全的饮用水。水中的重金属污染可归因于从管道中浸出铅和铜，以及包括采矿、工业和农业在内的人为活动等。在这项规划拨款中，工程师、计算机科学家和社会科学家将与来自马萨诸塞州洛厄尔、劳伦斯、德拉库特、韦斯特福德和切姆斯福德等社会经济多元化社区的社区利益相关者(居民、社区领袖、监管者、公用事业经理)密切合作，探索基于用户友好的手持电子舌头(E-TUMP)设备能够检测饮用水污染的智能、社区参与的水质监测和预警系统的可行性。这些设备将提供可靠的水质数据，并使公民能够测试自己的水，收集来自社区的数据，并在问题明显时采取行动。基于云的机器学习算法将从单个电子舌头设备获取响应，并生成关于问题有多普遍、问题是局部的还是系统性的，以及其他哪些地点可能受到污染的预测。此外，这些预测将是有价值的，例如，有助于确定周围地区的哪些居民应该收到警报通知，以检测自己的水质。它还可以帮助通知当地政府可能需要采取行动。通过一系列研讨会，该项目将纳入并了解居民的观点，如水质数据的有效呈现、社区成员对共享他们的水质数据可能存在的隐私担忧，以及影响社区采用该技术的因素。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。