适合大规模组网部署的水质传感器原理设计实现方法及分布式功能算法研究

项目名称： 适合大规模组网部署的水质传感器原理设计实现方法及分布式功能算法研究

项目编号： No.61303246

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 黄希

作者单位： 中国科学院计算技术研究所

项目金额： 27万元

中文摘要： 无线传感器网络通过对于湖泊、海洋的多点区域监测，可以迅速探测出污染源，并对污染程度和扩散趋势作出预测。然而目前水参数传感器大都昂贵并且功耗较高，造成单个传感器节点成本过高，不适合大规模部署。而单点或者稀疏的节点布置方式无法提供水质参数的空间分布数据，阻碍了相关的污染定位预测方法的研究与实现。本项目将针对传感器网络在功耗和成本方面的要求，以水参数中最基础也最重要的温度以及电导率为切入点，进行相关传感器的设计研究。以此为载体，采集区域水参数数据并建模，进行相关的功能计算技术研究.最终实现对污染源的快速定位以及扩散情况的预测。同时将部分计算分布式化，通过小区域内节点间数据比对，实现传感器的自校准以及网络的自唤醒等功能。该项目的研究成果不但可为无线传感器网络在水环境监测方面的大规模部署提供系统原型以及关键技术支持，其所研制的温度和电导率传感器也为将来集成各类离子分子类传感器打下重要基础。

中文关键词： 传感器网络；水质传感器；分布式计算；低成本；低功耗

英文摘要： The source of water pollution can be quickly located and diffusion of pollution can be predicted by applying Wireless Sensor Network (WSN) to lake or ocean for large scale multi-point monitoring. However, most of the water quality sensors are expensive and power hungry, making them not suitable for large scale deployment. Deployment with single or a few WSN nodes cannot provide the area distribution data of water quality parameters, which prohibit the development of pollution locating and predicting technology. In this project, we firstly focus on the requirements of WSN in cost and power, choose temperature and conductivity, which are two of the most basic and most important water quality parameters, to be the penetration point for sensor design. Basing on the achievement, we then collect area data of water quality parameters for modeling and developing the related computing technology. Finally we realize the functions of pollution source locating and pollution diffusion predicting. We also convert a part of the algorithm for distributed computing, so that the system can support functions that sensor node self calibration, and network self wake up, by sharing data between nearby sensor nodes. The achievements of this project will provide prototype system and key technology support for large scale deployment of

英文关键词： Wireless Sensor Network；Water Environment；Distributed Information Computing；Low Cost ；Low Power