CRII: NeTS: Power Efficient Millimeter Wave Data Delivery for Remote Invasive Species Monitoring
CRII: NeTS: Power Efficient Millimeter Wave Data Delivery for Remote Invasive Species Monitoring
批准号:
1948568
负责人:
Yao Zheng
金额:
$17.49万
依托单位:
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
项目状态:
已结题
起止时间:
2020-05-01 至 2023-04-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The growing data resolution in remote sensing spurs the adoption of millimeter-wave (mmWave) communication modules on energy-harvesting devices to increase the data delivery bandwidth. The energy conditions on these devices are not always satisfiable to initiate or maintain the mmWave links and require systems to be capable of anticipating communication failures and take preemptive actions to minimize energy expenditures. Fortunately, the environmental information provided by remote sensors contains sufficient knowledge to enable the design of such systems. The goal of this project is to develop algorithms and tools to exploit this information and augment the solar-harvesting remote invasive species monitoring system in the State of Hawaii with mmWave data delivery capability. The work in this project will enable researchers, industry, and students to realize high bandwidth real-time remote sensing with power-constrained devices in real-world applications. The results of this research will impact fields across scientific, industrial, and military interests, including agriculture, ecology, meteorology, infrastructure, and public utility monitoring, etc., where timely communication of high-resolution sensory data is essential.The fundamental intuition of the proposed approach is that environmental factors, such as weather conditions, signal blockages, can be recognized via the inherent capability or interactions between the remote sensors. Knowledge of these factors can be utilized to optimize device awakening, beam scanning, and signal amplification, etc., at the physical layer. Three complimentary research thrusts are pursued: 1) extracting the correlation between solar harvesting conditions and mmWave signal attenuations; developing models and circuits to estimate the mmWave signal attenuations at specific solar conditions; 2) designing a distributed sensing architecture to detect mmWave beam blockage and accelerate beam alignment, by exploiting the low-power decimeter band communication implemented by the existing system; 3) formulating and solving a constrained route placement problem for an autonomous aerial data collector to optimize its mmWave signal reception as it maneuvers between sensor clusters and flight restricted regions. All products of this work will be made freely available to the research community, along with documentation and tutorials. The in-lab testbed to be established during the project will be made available online for remote testing. The hardware schematic of the sensor platform, deployment profiles, data traces, and important meta-data will be posted online to spur further use, test, and research to advance the field.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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Cross-Modality Continuous User Authentication and Device Pairing With Respiratory Patterns
跨模态连续用户身份验证和设备与呼吸模式配对
DOI:
10.1109/jiot.2023.3275099
发表时间:
2023
期刊:
IEEE Internet of Things Journal
影响因子:
10.6
作者:
[Islam, Shekh M. M., Zheng, Yao, Pan, Yanjun, Millan, Marionne, Chang, Willy, Li, Ming, Borić-Lubecke, Olga, Lubecke, Victor, Sun, Wenhai]
通讯作者:
Sun, Wenhai
Advances in High-dimensional Time Series Modeling and Its Interface with Deep Learning
-
批准号:2311178
-
项目类别:Continuing Grant
-
资助金额:$17.42万
-
财政年份:2023
-
负责人:Yao Zheng
-
依托单位:
国内基金
海外基金
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