MRI: Acquisition of Equipment to Develop an Ubiquitous Wireless Sensor Network for Measurement, Modeling, and Prediction in Water Resource Management

MRI：采购设备以开发无处不在的无线传感器网络，用于水资源管理的测量、建模和预测

• 批准号: 1427838
• 负责人: Bo Sun
• 金额: $ 20万
• 依托单位: Lamar University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1427838&HistoricalAwards=false
• 关键词: MRI; Acquisition; Equipment; Develop; Ubiquitous

This project, acquiring equipment to advance real-time in situ monitoring of data related to water quantity and quality, aims to develop Wireless Sensor Networks (WSNs) to - Obtain measurements of temperature, water dissolved oxygen, water depth, flow rate, and pH value spatially and temporally with high resolution and accuracy;- Apply WSN-collected real-time, large-scale heterogeneous data to develop, calibrate, and validate water quantity and quality models, to characterize interactions among water resources, climate changes, and human impact to provide more accurate prediction for water sustainability management under different scenarios; and- Compile and distribute regional and national measurements and design a database/online repository.Hydrologists, water resource scientists, and water resource engineers will utilize the WSN-framework with the expectation of- Deriving understanding of complex interactions among water resource, global climate change, and human impacts from data inference;- Utilizing the research results to provide effective and economic solutions for sustainable water resource management;- Providing a current water quantity and quality database and online repository for others to increase collaboration.The instrumentation enables the collaborative application of technologies to water resource management research advancing understanding of complex problems to optimize consumption of limited water under different climate conditions. It also contributes to establish an appropriate environment to broaden students' knowledge and research experience, and encourages participation of underrepresented minorities/women, Furthermore, research results will be integrated into the curricula in CS and water resource education, as well as introduced to a large number of low-income and minority students within their communities in grades 6-12.

该项目旨在获取设备，以推进与水量和水质相关的数据的实时现场监测，目的是开发无线传感器网络（WSNs），以获得高分辨率和准确度的温度，水溶解氧，水深，流速和pH值的时空测量值;- 应用无线传感器网络收集的实时，大规模的异构数据来开发，校准和验证水量和水质模型，以表征水资源，气候变化，和人类影响，为不同情景下的水资源可持续性管理提供更准确的预测;汇编和分发区域和国家测量数据，并设计数据库/在线储存库。和水资源工程师将利用无线传感器网络框架的期望-推导水资源，全球气候变化，- 利用研究成果为可持续水资源管理提供有效和经济的解决方案;- 为其他人提供当前水量和水质数据库和在线储存库，以加强合作。该仪器使技术能够协同应用于水资源管理研究，促进对复杂问题的理解，以优化有限水的消耗在不同的气候条件下。此外，研究成果将被纳入CS和水资源教育课程，并介绍给社区内大量低收入和少数民族学生的6-12年级。