CNS Core: Small: Collaborative Research: loTScope: Sensing Physical Materials via Inexpensive loT Radios

CNS 核心：小型：协作研究：loTScope：通过廉价的物联网无线电传感物理材料

• 批准号: 2008338
• 负责人: Romit Roy Choudhury
• 金额: $ 25万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008338&HistoricalAwards=false
• 关键词: CNS; Core; Small; Collaborative; Research

Maturing wireless technology and low-cost IoT devices are enabling new kinds of approaches to conventional fields and applications. This project will design a system called IoTScope that aims to shine wireless signals on any object and identify the material properties by analyzing the reflected and refracted signals. Such a capability has the potential to impact many applications helpful to society. Soil moisture detection using drones can help predict crop yield and fertilizer requirement, thus benefitting precision agriculture. Detection of the caloric values of liquids and of water contamination have important health-care applications. Being able to distinguish humans, cars, and other objects can be useful in autonomous-driving and security applications. The project aims to tackle algorithmic and practical challenges in enabling material detection using wireless signals. The simulations, experimental data, and software libraries that will be developed in the project will be made available to students through mini-projects. Given the “Sci-Fi" like nature of this work, it is designed to naturally draw students towards research, while also teaching fundamental principles of wireless communications, signal processing, and wave-matter interaction. The project attempts to harness the rich information inherent in wireless signals for detecting materials and enabling disruptive IoT applications. Detection can be challenging due to noisy data, wireless multipath (environmental reflections) and diffraction, complexity of material surface, arbitrary user mobility, etc. The specific research tasks are: (I) Fusion of physics models of signal-material interaction with measurements of reflected and refracted signals. This allows IoTScope to decouple signal entanglement with multipath with potentially higher accuracy than state-of-the art multipath deconvolution techniques. (II)Iterative hardware cancellation techniques for subtracting environmental multipath to amplify weak refracted signal. (III) Actuation/mobility based control of probing the material at various angles of incidence, antenna orientations, and frequencies to extract maximal spatial diversity with minimal overhead. (IV) To handle application-specific challenges in soil-moisture detection, the proposal exploits RF-vision fusion together with prior information about soil moisture properties.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

成熟的无线技术和低成本物联网设备正在为传统领域和应用提供新的方法。该项目将设计一个名为IoTScope的系统，旨在将无线信号照射到任何物体上，并通过分析反射和折射信号来识别材料属性。这种能力有可能影响许多对社会有益的应用。 使用无人机进行土壤湿度检测可以帮助预测作物产量和肥料需求，从而有利于精准农业。检测液体的热值和水污染具有重要的保健应用。能够区分人、汽车和其他物体在安全驾驶和安全应用中是有用的。该项目旨在解决使用无线信号进行材料检测的算法和实际挑战。模拟，实验数据和软件库，将在该项目中开发将提供给学生通过迷你项目。鉴于这项工作的“科幻”性质，它旨在自然地吸引学生进行研究，同时也教授无线通信，信号处理和波物质相互作用的基本原理。该项目试图利用无线信号中固有的丰富信息来检测材料并实现颠覆性的物联网应用。由于噪声数据，无线多径（环境反射）和衍射，材料表面的复杂性，任意用户移动性等，检测可能具有挑战性。具体研究任务是：（I）融合信号-材料相互作用的物理模型与反射和折射信号的测量。这使得IoTScope能够以比最先进的多径反卷积技术更高的精度将信号纠缠与多径解耦。（二）利用迭代硬件相消技术消除环境多径效应放大弱折射信号。(III)以各种入射角、天线方向和频率探测材料的基于致动/移动性的控制，以最小的开销提取最大的空间分集。(IV)为了应对土壤水分检测中的特定应用挑战，该提案将RF视觉融合技术与土壤水分特性的先验信息结合起来。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。