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

物联网（IoT）设备越来越多地用于人们的日常生活中，用于个人健康监测、全球定位、电网管理、供应链控制和智能家居自动化等应用。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的环境中。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功能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，并显着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。通过以下方式扩大了这一职业项目的广泛影响：㈠通过强化课程项目改进课程编制; ㈡通过开放日提高K-12学生和代表性不足的少数群体对技术的兴趣; ㈢支持有才华的女性和少数民族博士生成功完成博士学业;以及（iv）通过高知名度的教程和开源网站传播研究成果。这个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。该项目将提供一个具有模块化结构的网络系统，可容纳跨物联网传感，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，该项目将为研究社区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外，该CAREER项目还有望为多个学科的更广泛应用社区的系统开发做出贡献，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.