NeTS: Small: Continuous Spatial Awareness (CoSA) for Smart and Connected Objects

持续空间感知(COSA)项目旨在利用先进的信号处理技术，使已经部署在大多数工作场所、公共场所和家庭中的Wi-Fi基础设施能够持续感知和评估室内环境中发生的事情。该项目强调可用性和适用性，旨在支持附近只有一个Wi-Fi接入点和只有两到三个天线的移动设备的操作。利用拟议的研究技术，该项目将调查手机和射频识别(RFID)标签的本地化以及建筑断层扫描。嵌入式、智能、物联网(IoT)对象，如无线电标签、灯泡和可穿戴电子健康设备，正在进入我们的日常生活。这些物联网对象的一个共同属性是，它们都具有紧凑、方便的外形因素，可以很好地融入我们的世界。随之而来的挑战是，这些设备中的大多数因此都受到天线的限制：每台设备通常只有一到三个天线。针对这一挑战，我们提出了三种新的方法来连续无缝地跟踪物联网对象并绘制我们的世界。首先，客户端辅助定位(CAL)利用强大的联合到达时间和到达角信号处理，使用单个频段上的单个附近接入点定位移动设备。其次，无线建筑物层析成像技术可以绘制出室内墙壁的位置，因此不再需要摄像头来逐个查看建筑物的每一个房间。最后，将上述思想应用于天线数量较少的RFID标签领域。建议的方法允许天线受限的设备在附近一个或多个天线丰富的设备(如Wi-Fi接入点)的协作下推断有关其位置的信息。这是对以前在到达角和飞行时间无线方法方面所做工作的一个温和但潜在的强大转折，我们相信这将为通信终端不同硬件平台之间的进一步合作设计铺平道路。这项研究有可能为积极参与物联网的行业提供广泛的技术转移机会。教育计划包括利用研究项目的原型，在新创建的系独立研究研讨会上为计算机科学专业的大三学生举办。

The Continuous Spatial Awareness (CoSA) project aims to leverage advanced signal processing techniques to allow the Wi-Fi infrastructure already deployed in the majority of workplaces, public spaces, and households to constantly sense and assess what is happening in the indoor environment. With an emphasis on availability and applicability, the project aims to support operation when just a single Wi-Fi access point is nearby and with mobiles devices that have only two to three antennas. Leveraging the proposed research techniques, the project will investigate localization of mobiles and Radio Frequency Identification (RFID) tags as well as building tomography.Embedded, smart, Internet-of-Things (IoT) objects such as radio tags, light bulbs, and wearable e-health devices are right now making their way into our daily lives. One property common to these IoT objects is that they all possess compact, convenient form factors that integrate well physically into our world. A resulting challenge is that most of these are therefore antenna-constrained: one to three antennas per device is the norm. In light of this challenge, we propose three novel methods to continuously and seamlessly track IoT objects and map our world. First, Client-Aided Localization (CAL) leverages powerful joint time- and angle-of-arrival signal processing to localize a mobile device using a single nearby access point on a single frequency band. Second, wireless building tomography maps the locations of walls indoors, thus obviating the need for a camera to visit each room of a building individually. Finally, RFID localization applies the above ideas to the domain of RFID tags with a small number of antennas. The proposed methods allow antenna-constrained devices to deduce information about their location with the cooperation of one or more antenna-rich devices nearby (such as a Wi-Fi access point). This is a modest but potentially powerful twist on previous work in angle-of-arrival and time-of-flight wireless methods that we believe will pave the way for further co-design between diverse hardware platforms at the communication end points. This research has the potential for a broad range of technology transfer opportunities to an industry which is actively engaging in the IoT. The education plan includes leveraging the research project's prototypes in a newly-created departmental independent research seminar for juniors in Computer Science.