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CAREER: Backscatter Propagation-based Multi-hop Networks for Battery-less Devices

CAREER: Backscatter Propagation-based Multi-hop Networks for Battery-less Devices
职业:用于无电池设备的基于反向散射传播的多跳网络
批准号:
0954031
负责人:
Maciej Zawodniok
金额:
$32.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-01-15 至 2014-12-31

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中文摘要
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英文摘要
A backscatter communication enables development and implementation of battery-less sensors, miniaturized (MEMS) robots, or even nano devices. However, the current stat-of-the-art technology limits communication scenario to a direct transmission between active and passive devices, for example in radio frequency identification (RFID) system between a reader and a passive tag. In contrast, the goal of this project is to develop a novel multi-hop network that utilizes backscatter signal as communication for passive, battery-less devices. The objectives of this work include mathematical representation of such passive multi-hop networks and development of novel cross-layer communication protocols and control schemes with learning methodology for beam-forming. The expected contributions include an improved theoretical understanding of the multi-hop network of battery-less devices and a novel cross-layer optimization framework of network protocols that are feasible and practically viable. The end result of this effort would lead into a truly pervasive, backscatter-based networking paradigm.The proposal?s outcomes include extending the range and improved capabilities of RFID systems to support larger and more complex sensing applications while lowering cost and minimizing environmental impacts (batteries-less operation). Moreover, a set of outreach activities include engagement of women and students from under-represented minorities through Missouri S&T Student Diversity Programs' office and Project Lead the Way (K-12 outreach). In long term, the outcomes will support various applications of MEMS and nano devices through facilitating a communication and control of such devices, with a potential to transform the healthcare, manufacturing into something that now is considered a science fiction.
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A Systematic Methodology for Data Validation and Verification for Prognostics Applications
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