Adaptive Sampling Strategies with Application to Water Resource Management

自适应采样策略在水资源管理中的应用

• 批准号: 0725441
• 负责人: Ali Sayed
• 金额: $ 32.99万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725441&HistoricalAwards=false
• 关键词: Adaptive; Sampling; Strategies; Application; Water

ECCS-0725441SayedAdaptive Sampling Strategies with Application to Water Resource ManagementIntellectual Merit. Wireless sensor networks include both static and actuated devices and offer a promising solution for applications ranging from monitoring of diverse environmental phenomena to surveillance for national security. In many applications, these networks are deployed to monitor an underlying physical phenomenon over time and space, such as estimating a contaminant flux in water. Since the sensor devices operate unattended and with constrained energy reservoirs, energy efficiency becomes critical and directly determines the system lifetime. In order to achieve the simultaneous objectives of sensing fidelity and energy efficiency, it is necessary to develop strategies for selecting those sensor devices that contribute most effectively to the desired monitoring fidelity and to select other nodes for an inactive and low power standby state. The goals and intellectual merits of the proposed research are threefold: (i) to develop distributed methodologies to select a subset of sensor nodes and sensor measurement locations that can meet desired estimation accuracies; (ii) to test the developed methods experimentally; and (iii) to apply the methods to a critical application in water resource management such as accurately measuring contaminant flux in water.Broader Impact. The research has implications on the information technology infrastructure of the nation by enhancing the ability of wireless networks to sample and extract information from geographically scattered nodes subject to energy, communication, and time constraints. The research also addresses the demand for accurate sensing coverage in water resource management systems. And it helps train students in an area of fundamental relevance to future networking systems.

ECCS-0725441Sayed 自适应采样策略在水资源管理中的应用智力价值。无线传感器网络包括静态和驱动设备，为从监测不同环境现象到监视国家安全等应用提供了一种有前途的解决方案。 在许多应用中，部署这些网络来监测时间和空间上的潜在物理现象，例如估计水中的污染物通量。由于传感器设备在无人值守的情况下运行且能量储备有限，因此能源效率变得至关重要，并直接决定系统的使用寿命。为了同时实现传感保真度和能源效率的目标，有必要制定策略来选择最有效地实现所需监控保真度的传感器设备，并选择其他节点处于非活动和低功耗待机状态。拟议研究的目标和智力优点有三个：（i）开发分布式方法来选择能够满足所需估计精度的传感器节点和传感器测量位置的子集； (ii) 通过实验测试所开发的方法； (iii) 将这些方法应用于水资源管理的关键应用，例如准确测量水中的污染物通量。更广泛的影响。该研究通过增强无线网络从受能源、通信和时间限制的地理分散节点中采样和提取信息的能力，对国家信息技术基础设施产生影响。该研究还解决了水资源管理系统中精确传感覆盖的需求。它有助于在与未来网络系统基本相关的领域培训学生。