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

[1619523] Diwekar, Urmila m .粮食生产系统产生的废水以水中高浓度的有机物、含氮和含磷物质为特征。因此，监测氮和磷物种对农业水质要求以及从废物流中回收能源非常重要。目前，这些物种是通过固定监测站监测的。然而，氮和磷通过农业径流转移到其他水系统，因此需要能够实时改变位置的便携式传感器。这种类型的动态感知需要合适的算法，在面对相关物种命运和运输的固有不确定性时，可以实时计算出合适的传感器位置。开发这样一个算法框架来实时解决传感器的放置问题是本研究的目的。本研究的目的是对传感器的放置和相互作用与相关物种的营养命运和运输的关系有一个基本的了解，目的是确定传感器的数量和时空位置，以获得最大的效果。考虑到不确定性是固有的，传感器的放置问题将被表述为一个动态随机规划问题，其解决方案将是面对不确定性的养分监测的动态最优传感器部署策略。利用便携式低成本传感器进行动态传感是营养监测的一个新领域，在食物-水-能关系方面具有广阔的应用前景。本研究将为这一努力提供理论依据。这种实时传感器放置问题将允许对污染的时空方面进行研究，这是一个恒定监测站无法提供的。

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.