CRI: Infrastructure for Networked Sensor Information Technology

该项目在新墨西哥州开发了一系列传感器网络测试平台，重点关注无线传感器网络在以下应用中的使用：-牧场牲畜的跟踪、控制和行为监测，-生态研究地点天气和气候的微监测，-保护分布式传感任务的上下文隐私，-为嵌入式传感器节点和网关开发基于组件的中间件工程，-创建集成传感器网络设计环境和测试平台；-开发用于智能办公设计和远程学习的实时协作虚拟环境。该项目建立了无线传感器网络（WSN）和分布式传感器信息技术的基础设施、核心能力和专业知识，服务于三个具体的研究项目：分布式传感中的隐私保护问题、基于组件的WSN中间件工程和集成传感器网络设计环境和测试平台。所要求的设备包括不同类型的嵌入式处理器-无线电模块（mote）、兼容传感器数据采集模块、串行和以太网编程和接口板以及嵌入式专用网关计算机。更广泛的影响：新开设的传感器网络课程为学生提供了多层次的服务，加强了这所少数民族大学的教育。此外，研究项目为社会提供了直接和间接的利益。改进远程教育与主校区教育相结合的方式，吸引和参与更多的学生接受高等教育；提高对牧场利用和牲畜行为的了解有助于改善土地利用和社会粮食生产；提高对传感器网络隐私安全问题和传感器软件工程的理解有助于进一步部署关键任务领域的可部署性。

This project, developing a series of sensor networking testbeds in New Mexico, focuses on the use of wireless sensor networks in the following applications:-Tracking, controlling, and behavioral monitoring of livestock on rangeland, -Micro-monitoring of weather and climate on an ecological research site, -Protecting contextual privacy of distributed sensing tasks, -Developing component-based middleware engineering for embedded sensor nodes and gateways, -Creating an integrated sensor net design environment and testbed, and -Developing a real-time collaborative virtual environment for smart office design and distance learning.Establishing infrastructure, core capabilities, and expertise in Wireless Sensor Networks (WSN) and Distributed Sensor Information Technology, the project services three specific research projects:-Privacy protection issues in distributed sensing,-Component-based middleware engineering for WSN, and-Integrated sensor net design environment and testbed.The equipment requested includes different types of embedded processor-radio modules (motes), compatible sensor data acquisition modules, serial and Ethernet programming and interface boards, and embedded specialized gateway computers. Broader Impact: Newly developed courses on sensor networks service students at many levels, strengthening the education at this minority serving university. Furthermore, the research projects offer benefit to society directly and indirectly. Improved methods for integrating distance learning with main-campus learning attracts and engages more students in higher education; improved understanding of rangeland usage and livestock behavior helps improve land utilization and food production for society; and improved understanding of sensor network privacy security issues and of software engineering for sensors helps further the deployability mission-critical areas.