INFEWS N/P/H2O: Optimizing Spatio-temporal Sensor Placement for Nutrient Monitoring

INFEWS N/P/H2O：优化营养物监测的时空传感器放置

• 批准号: 1619523
• 负责人: Urmila Diwekar
• 金额: $ 14.63万
• 依托单位: Vishwamitra Research Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1619523&HistoricalAwards=false
• 关键词: INFEWS; H2O; Optimizing; Spatio; temporal

1619523 Diwekar, Urmila M.The food production system generates waste streams that are characterized by high concentrations of organic matter, nitrogen- and phosphorus-containing species in water. Therefore, monitoring nitrogen and phosphorous species is important for water quality requirements for agricultural as well as energy recovery from waste streams. Currently these species are monitored via stationary monitoring stations. However nitrogen and phosphorous species move via agricultural run-off to other water systems, so portable sensors are needed that can change positionsin real time. This type of dynamic sensing requires suitable algorithms that can calculate appropriate sensor locations in real time in the face of inherent uncertainties in the fate and transport of the relevant species. To develop such an algorithmic framework to solve the problem of sensor placement in real time is the objective of this research.This research is targeted to develop a fundamental understanding of the relationships involved in sensor placement and interaction with nutrient fate and transport of relevant species, with the goal of identifying the number and spatio-temporal positions of sensors for maximum effectiveness. Given that uncertainty is inherent, the problem of sensor placement will be formulated as a dynamic stochastic programming problem, the solution of which will be the dynamic optimal sensor deployment policy for nutrient monitoring in the face of uncertainties. Dynamic sensing with portable low cost sensors is a new area for nutrient monitoring which shows promise for food-water-energy nexus. This research will provide a theoretical basis for such an endeavor. This real time sensor placement problem will allow for the study of the spatial-temporal aspect of pollution which a constant monitoring station does not provide.

1619523 Diwekar，Urmila M.食品生产系统产生的废物流的特征是水中有机物、含氮和含磷物质的浓度高。因此，监测氮和磷的种类对于农业用水的质量要求以及从废物流中回收能源非常重要。目前，这些物种通过固定监测站进行监测。然而，氮和磷物种通过农业径流转移到其他水系统，因此需要能够真实的实时改变位置的便携式传感器。这种类型的动态感测需要适当的算法，可以在相关物种的命运和运输存在固有不确定性的情况下真实的计算适当的传感器位置。本研究的目标是建立一个真实的时间传感器布置的算法框架，以确定传感器的数量和时空位置，从而最大限度地发挥传感器的作用。由于不确定性是固有的，传感器的部署问题将被制定为一个动态随机规划问题，其解决方案将是动态最优的传感器部署策略，养分监测在面对的不确定性。使用便携式低成本传感器进行动态感测是营养监测的一个新领域，其显示出食物-水-能量关系的前景。本研究将为这一奋进提供理论基础。这个真实的时间传感器的放置问题将允许研究污染的时空方面，这是一个恒定的监测站所不能提供的。