| 项目编号: | 1637251
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| 项目名称: | EAGER: Smart Water Sensing for Sustainable and Connected Communities Using Citizen Science |
| 作者: | Dong Wang
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| 承担单位: | University of Notre Dame
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| 批准年: | 2016
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| 开始日期: | 2016-09-01
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| 结束日期: | 2018-08-31
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| 资助金额: | 251976
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | project
; citizen science
; local community
; new smart water
; transformative drinking water monitoring system
; water contamination level
; drinking water quality
; water quality datum
; water safety
; connected community
; system
; computer science
; water quality
; drinking water contamination
; household drinking water quality monitoring process
; sustainable community
; smart water
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| 英文摘要: | 1637251
Wang, Dong
The overall goal of this project is to develop a citizen science based smart water sensing system that accurately and efficiently detects drinking water contamination by using crowdsensing water quality data measured at the consumers' end. Monitoring drinking water quality at the point of use is vitally important to inform consumers about the water safety and to facilitate the decision-making process to minimize public health threats for a sustainable community. This project targets to: i) provide a brand new and transformative drinking water monitoring system by leveraging the collective power of crowdsensing in a community; ii) address fundamental challenges in crowdsensing and enable humans to be both sensors and users of the system; iii) integrate education and research through citizen science to enhance knowledge of common people on water quality and public health; and iv) engage government officials and residents (end users) throughout the process to address a real-world problem in a local community, and generate outcomes that will be broadly applicable in other places to enable more sustainable and connected communities.
In this project, the PIs plan to develop a new Smart Water Sensing (SWS) system to reliably monitor the water contamination levels in a local community (Granger, IN) and a novel Crowdsensing Data Analysis Engine (CDAE) to address the data reliability and data sparsity challenges of using crowdsensing data. The research is a novel combination of two distinct disciplines: computer science and environmental engineering. The development of the proposed SWS system is exploratory given little prior work, but the success of this project would help to make crowdsensing a reliable alternative that transforms the household drinking water quality monitoring process. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/91195
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Dong Wang. EAGER: Smart Water Sensing for Sustainable and Connected Communities Using Citizen Science. 2016-01-01.
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