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SBIR Phase I: Smart Skins for shipping containers tracking and identification

SBIR Phase I: Smart Skins for shipping containers tracking and identification
SBIR 第一阶段:用于集装箱跟踪和识别的智能皮肤
批准号:
1843302
负责人:
Jimmy Hester
金额:
$22.5万
依托单位:
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
项目状态:
已结题
起止时间:
2019-02-01 至 2020-02-29

项目摘要

项目成果

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中文摘要
翻译
这个小型企业创新研究(SBIR)第一阶段项目的更广泛的影响/商业潜力将首先揭示毫米波后向散射技术在具有挑战性的工业环境中的优势和局限性。更重要的是,如果成功的话,在这个项目中吸取的经验教训可能会带来突破性的能源自主实时跟踪技术的出现,这将大大提高效率,降低全球集装箱运输的成本,并提供直接价值,从而促进智能集装箱的采用。集装箱航运业是现代世界的无名英雄之一,自20世纪60年代诞生以来,它将地球仪的货物运输成本降低了几个数量级,从而实现了大规模的全球贸易并催化了世界。的经济发展。尽管如此,这个行业在很大程度上仍然不为大数据和物联网(IoT)技术的出现所动。这项创新可以使这些工具的普遍引入和利用,进一步降低成本,增加全球航运的可及性,并使世界和美国受益匪浅。在走向商业化的道路上,拟议的项目将需要在复杂的高度杂乱的环境中探索反向散射毫米波定位方法和信道的特性,例如金属部件拥挤的维修设施和覆盖有集装箱堆的码头。虽然目前在规划和推出即将到来的蜂窝5G网络所需的毫米波传输信道的表征和映射方面投入了大量的研究工作,但尚未报道针对其反向散射同行的此类工作,也没有用于本地化目的。此外,虽然标准的基于射频识别的定位系统的信道的影响已经受益于几十年的调查,其较高的频率对应的几乎是未开发的,应该显示不同的属性,并提出新的挑战和机遇,由于杂波衍射和吸收的主要差异。这项工作将从最终确定标签和阅读器硬件开始,考虑到在上述环境中收集检测数据,然后制定用于检索标签位置和身份的高性能信号处理方案,与优化的标签通信调制方案一起开发。最后,将对设计的高速嵌入式处理的数值处理方案进行调整。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。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to, firstly, shed light on the benefits and limitations of mm-wave backscatter technologies in challenging industrial environments. More importantly, the lessons learned during this project could, if successful, bring about the emergence of breakthrough energy-autonomous real-time tracking technologies that would significantly increase the efficiency and reduce the costs of worldwide container shipping as well as provide a direct value that could bring about the adoption of the smart container. The container shipping industry stands as one of the unsung heroes of the modern world which, from its birth in the 1960s, cut the cost of shipping goods across the globe by several orders of magnitude, thereby enabling global trade on a massive scale and catalyzing the world?s economic development. Nevertheless, this industry has remained largely unmoved by the advent of big data and Internet of Things (IoT) technologies. This innovation could empower the general introduction and leveraging of such tools, further lower the costs and increase the accessibility of worldwide shipping, and significantly benefit the world and the United States? economies.The proposed project will require, on the road towards commercialization, the exploration of the properties of backscatter mm-wave localization approaches and channels in complex highly cluttered environments such as that of metallic-parts-crowded repair facilities and terminals covered with container stacks. While significant research efforts are currently invested in the characterization and mapping of mm-wave transmission channels necessary to the planning and rolling out of upcoming cellular 5G networks, no such work has yet been reported for their backscatter counterparts, nor for localization purposes. In addition, although the influence of channels for standard Radio Frequency IDentification-based localization systems has benefited from decades of investigation, that of its higher-frequency correspondent is virtually unexplored and should display different properties and present novel challenges and opportunities, due to major differences in clutter diffraction and absorption. The work will start with the finalization of tag and reader hardware in view of the gathering of detection data in the aforementioned environments, followed by the formulation of the high-performance signal processing schemes used to retrieve tag positions and identities, developed hand in hand with optimized communications modulation schemes for the tags. Finally, a tuning of the devised numerical processing schemes for high-speed embedded processing will take place.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.
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SBIR Phase II: New 5G and internet-of-things systems for tracking and identification in shipping
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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