CAREER: Synergistic Cross-IoT N-Way Sensing using Wireless Traffic in the Edge

物联网设备已越来越多地应用于人们的日常生活中，如个人健康监测、全球定位、电网管理、供应链控制、智能家居自动化等。这些物联网设备预计将广泛部署在从住宅到高度动态的城市环境等环境中。随着物联网设备数量的增加，该CAREER项目旨在通过利用不同物联网设备的各种传感能力来提高现有的传感性能。这项研究的成功可以充分释放越来越多的物联网设备的潜力，显著改善人们的日常生活。研究结果可能会激发新的理论和系统研究，开辟物联网研究的新领域。这一职业发展计划的广泛影响通过以下方式得以扩大：(i)通过加强课程项目来改善课程发展；（ii）通过开放日提高K-12学生和少数族裔对科技的兴趣；（三）支持优秀女、少数民族博士生顺利完成博士学业；（四）通过高知名度的教程和开源网站传播研究成果。CAREER项目的主要目标是使物联网设备能够进行准确、高效和可扩展的n向传感。该项目将提供具有模块化结构的网络化系统，以适应跨物联网传感、无线通信、机器学习和边缘数据处理的各种解决方案。新的设计将结合不同的物联网硬件平台来实现，该项目将为研究界提供可重用的系统设计、算法和协议库。除了学术论文和技术报告之外，这个CAREER项目预计将在跨多个学科的更广泛的应用社区中为系统开发做出贡献，例如人类行为研究、睡眠监测和增强现实。

Internet-of-Things (IoT) devices have been increasingly used in people's daily life for applications such as personal health monitoring, global positioning, power grids management, supply chain control, and smart home automation. These IoT devices are expected to be widely deployed in environments ranging from residential houses to highly dynamic urban surroundings. With the increasing number of IoT devices, this CAREER project aims at improving the existing sensing performance by leveraging various sensing capabilities from different IoT devices. The success of this research can fully unleash the potential of increasing number of IoT devices and significantly improve people's daily life. The research results are likely to inspire novel theoretical and systematic studies that open up new areas of research in Internet-of-Things. The broader impact of this CAREER project is amplified by (i) improving curriculum development with enhanced course projects; (ii) raising interest in technology among K-12 students and under-represented minority groups through open houses; (iii) supporting talented female and minority PhD students to successfully accomplish their doctoral studies; and (iv) disseminating research results through high-profile tutorials and open-source sites.The main goal of this CAREER project is to enable IoT devices to conduct accurate, efficient, and scalable N-way sensing. This project will deliver a networked system with modularized structure that accommodates various solutions for cross-IoT sensing, wireless communication, machine learning, and data processing in the edge. New designs will be implemented with a combination of different IoT hardware platforms and this project will deliver reusable system designs, algorithms, and protocol libraries to the research community. In addition to academic papers and technical reports, this CAREER project is expected to contribute to the system development in broader application communities across multiple disciplines, such as human behavior study, sleep monitoring, and augmented reality.