SBIR Phase I: Universal Chip-less Identification of Inventory Using Antennas Tuned to Existing Networks

SBIR 第一阶段：使用针对现有网络调整的天线进行通用无芯片库存识别

• 批准号: 1940248
• 负责人: Brandon Young
• 金额: $ 22.46万
• 依托单位: Pascal Tags, L.L.C.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940248&HistoricalAwards=false
• 关键词: SBIR; Phase; Universal; Chip; less

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project will be to create an active supply chain through serialization of nearly every product for better data and efficiency. Each year corporations lose over $818 B because of inadequate inventory systems. This affects the entire supply chain and reduces the potential for faster distribution of better products. Manufacturers, shippers and consumers need to track their products from manufacturing, logistics, retail and even the home using a singular tag. The savings from accurately tracking and identifying inventory will be billions of dollars per year and will significantly reduce waste. The opportunities for data collection for individuals and companies throughout the lifecycle of the product will also potentially spur new industries and disrupt older industries. The proposed project brings together several different innovations into an inventory tracking and identification system, including antennas, thin film detection and polarized dielectrics. The project involves both computational and laboratory experiments that will design and validate the technology, including the development of software tools to assist distinguishing the tags in real-life environments. The problems to be studied are reading data from ambient network (4G, 5G, or even Wi-Fi) signals via chip-less tags, omni-directional detection, and printing directly onto non-conductive material. The project will iteratively and effectively tackle these problems through advanced R&D focusing on antenna design, thin-film manufacturing, and signal-processing.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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛/商业影响将是通过几乎每种产品的序列化来创建一个活跃的供应链，以获得更好的数据和效率。每年，由于库存系统不足，公司损失超过818 B美元。这影响了整个供应链，并降低了更好产品更快分销的潜力。制造商、托运人和消费者需要使用单一标签从制造、物流、零售甚至家庭跟踪他们的产品。准确跟踪和识别库存每年将节省数十亿美元，并将大大减少浪费。在产品的整个生命周期中为个人和公司收集数据的机会也将潜在地刺激新的行业并破坏旧的行业。拟议的项目将几种不同的创新纳入库存跟踪和识别系统，包括天线、薄膜探测和偏振探测。该项目涉及计算和实验室实验，将设计和验证该技术，包括开发软件工具，以帮助区分现实环境中的标签。要研究的问题是通过无芯片标签从环境网络（4G，5G甚至Wi-Fi）信号中阅读数据，全方位检测以及直接打印到非导电材料上。该项目将通过专注于天线设计、薄膜制造和信号处理的先进研发来迭代和有效地解决这些问题。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。