I/UCRC Phase II: ASU Research Site of the NSF Net-Centric and Cloud Software and Systems I/UCRC

有了这个奖项，亚利桑那州立大学IUCRC网站的网络中心和云软件和系统（NCSS）I/UCRC将过渡到第二阶段的网站。NCSS涉及北德克萨斯大学（牵头单位）、南卫理公会大学、德克萨斯大学达拉斯分校、密苏里州科技大学和亚利桑那州州立大学。该网站已经建立了必要的知识基础和营销基础设施，以吸引和留住第二阶段的行业合作伙伴，并在NCSS内拥有良好的行业成员和参与记录。网络传感系统在国土安全、网络中心防御系统、工业应用、健康监测等领域具有重要意义。第二阶段的中心将能够创造传感器信号处理的新能力，并将弥合传感器开发和大规模传感器部署之间的差距。该中心具有独特的地位，以创新的方式促进基础研究，教育，奖学金和行业活动，并将继续与现有的网络中心伞整合。通过NCSS，该网站专注于数字信号和图像处理，传感器网络，信息技术和算法以及无线通信云软件开发等研究领域。 计划的研究进展和贡献的具体领域包括：a）使用虚拟传感器阵列的雷达到达方向估计的进展，B）网络传感器监测算法和云软件的开发，预测过程故障，c）监测网络PV阵列的传感器的故障检测，d）用于活动检测的网络成像传感器，以及e）用于图像理解的摄像机阵列的网络中心方法。

With this award, the Arizona State University IUCRC site of the Net-centric and Cloud Software and Systems (NCSS) I/UCRC will transition to a Phase 2 Site. The NCSS involves University of North Texas (Lead Site), Southern Methodist University, University of Texas at Dallas, Missouri University of S&T and Arizona State University. The site has already established the necessary intellectual base and marketing infrastructure to attract and retain industry partners for Phase 2, and has an excellent track record of industry membership and engagement within the NCSS. Networked sensing systems are important in homeland security, Net Centric defense systems, industry applications, health monitoring and other areas. The Phase 2 center will enable the creation of new capabilities in sensor signal processing and will bridge the gap between sensor development and large scale sensor deployment. The center is uniquely positioned to promote fundamental research, education, scholarship, and industry activities in an innovative manner that will continue integrating well in the existing Net-Centric umbrella. With the NCSS, this Site focuses on research areas such as digital signal and image processing, sensor networks, information technologies and algorithm and cloud software development for wireless communications. Specific areas of planned research advances and contributions include: a) Advances in radar direction of arrival estimation using virtual sensor arrays, b) development of networked sensor monitoring algorithms and cloud software which predict process failures, c) fault detection in sensors monitoring networked PV arrays, d) networked imaging sensors for activity detection, and e) net centric approaches with camera arrays for image understanding.