NeTS: Small: Networking and Sensing Using Visible Light Communications

NeTS：小型：使用可见光通信进行网络和传感

• 批准号: 1421528
• 负责人: Xia Zhou
• 金额: $ 50万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421528&HistoricalAwards=false
• 关键词: NeTS; Small; Networking; Sensing; Using

Mobile computing is accelerating beyond the smartphone era. Today, people wear smart glasses, smart watches, and fitness devices and carry smartphones, tablets and laptops. In a decade, the very same people are likely to wear or carry tens of wireless devices and interact with the Internet and computing infrastructure in markedly different ways. Two fundamental challenges emerge in a post-smartphone era: dealing with the impending spectrum crunch before it becomes a full-fledged crisis, and, advancing human-computer interaction (HCI) before people buckle under the demands of dealing with an ever increasing number of personal devices. This project seeks to address these two challenges by proposing a first of its kind integrated networking and sensing environment based on visible light communication (VLC). The proposed research advances VLC research in two new directions: VLC networking and VLC sensing.The project designs integrated VLC networking and sensing for smart spaces (iVLC) and a set of robust VLC networking and sensing algorithms. The VLC networking algorithms address the following challenges: 1) frequent connection disruptions caused by user mobility and the limited coverage of individual VLC links, 2) link interference from diffusive lights, and 3) determining the optimal placement and density of LED lights. Addressing these challenges requires efficient handoff schemes between adjacent LEDs, interference handling schemes for VLC networks, and optimization algorithms to determine the LED light deployment in smart spaces. The VLC sensing requires accurate inference of user gestures using shadows rendered on the floor. The combination of light from multiple light sources on the ceiling obfuscates and distorts these shadows. To tackle this challenge, the iVLC system separates shadow components by embedding identifiers into light signals from LEDs allowing light sensors on the floor to measure the light illuminance of individual light sources. Finally, a novel proof-of-concept iVLC testbed will be designed, built, and deployed, which comprises LEDs and light sensors. Results from the Bits in the Light Project will help accelerate the deployment of VLC as a new mobile networking and sensing technology.

移动的计算正在加速超越智能手机时代。如今，人们佩戴智能眼镜、智能手表和健身设备，并携带智能手机、平板电脑和笔记本电脑。在十年内，同样的人可能会佩戴或携带数十种无线设备，并以明显不同的方式与互联网和计算基础设施进行交互。后智能手机时代出现了两个基本挑战：在即将到来的频谱危机成为全面危机之前处理它，以及在人们在处理越来越多的个人设备的要求下屈服之前推进人机交互（HCI）。该项目旨在通过提出基于可见光通信（VLC）的第一种集成网络和传感环境来解决这两个挑战。本研究将VLC的研究推向两个新的方向：VLC网络和VLC感知，设计了智能空间的集成VLC网络和感知（iVLC）以及一套鲁棒的VLC网络和感知算法。VLC网络算法解决了以下挑战：1）由用户移动性和单个VLC链路的有限覆盖范围引起的频繁连接中断，2）来自漫射光的链路干扰，以及3）确定LED灯的最佳放置和密度。解决这些挑战需要相邻LED之间的高效切换方案、VLC网络的干扰处理方案以及确定智能空间中LED灯部署的优化算法。VLC感测需要使用在地板上呈现的阴影来准确推断用户手势。来自天花板上多个光源的光的组合模糊和扭曲了这些阴影。为了应对这一挑战，iVLC系统通过将标识符嵌入到来自LED的光信号中来分离阴影分量，从而允许地板上的光传感器测量各个光源的光照度。最后，将设计、建造和部署一个新的概念验证iVLC测试平台，该平台包括LED和光传感器。光中比特项目的成果将有助于加速VLC作为一种新的移动的网络和传感技术的部署。