NeTS: Large: Collaborative Research: ASTRO: A Platform for 3-D Data-Driven Mobile Sensing via Networked Drones

NeTS：大型：协作研究：ASTRO：通过联网无人机进行 3D 数据驱动的移动传感平台

基本信息

批准号：
1801865
负责人：
Edward Knightly
金额：
$ 150万
依托单位：
William Marsh Rice University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2023-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1801865&HistoricalAwards=false
关键词：
NeTS Large Collaborative Research ASTRO

项目摘要

The driving vision of this project is to detect Volatile Organic Compounds (VOCs) through ASTRO, a platform for autonomous 3-D data-driven mobile sensing via networked drones equipped with gas sensors. VOCs are hazardous to human health and the environment; they are released by explosions, gas leaks, and industrial accidents prevalent in low-income and under-resourced urban neighborhoods in close proximity to industrial processing plants, chemical refineries, and other sources of airborne pollutants. The project is located in an economically disadvantaged area of Houston, Texas. With Technology For All (TFA), the project team has a history of engaging the local community via broadband access, technology training, and connected health. The TFA wireless network already serves 1000's of community members in several square kilometers in Houston's East End via a mix of commercial Wi-Fi and software defined radios. The project targets realizing a high-resolution ground truth of environmental conditions in low-income urban areas which can impact emergency response procedures and environmental justice via policy and law. The project will develop a mobile app that alerts community residents of hazardous VOC concentrations near their current location. This project will impact urban areas with a demonstration of fusing next generation environmental sensing with next generation wireless access via networked drones. The project's objective is to realize an unprecedented resolution in VOC sensing by development and demonstration of ASTRO, a system for networked drone sensing missions without ground control. ASTRO will realize the unique capability to dynamically move sensors in 3-D according to real-time measurements. Consequently, networks of drones with on-board sensors can find and track VOC plumes, solely by coordinating among themselves, and without requiring a centralized ground controller. Two inter-related thrusts will realize this vision. The first is target detection, tracking, and modeling high VOC concentration clusters, targeting health and environmental safety. The second is development of the underlying principles and methodologies for data-driven mobile missions via drone networks. The project's outcomes will include lightweight machine learning methods that provide foundations for real-time distributed autonomous sensing with environmental and health objectives. These data sets will yield development of atmospheric models of VOCs at a finer resolution than is possible today. Moreover, the outcomes will also include methods for adaptive communication among the networked drones via software defined radios that can adapt their network topology and spectrum usage to realize mission objectives.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.

该项目的驱动视觉是通过Astro检测挥发性有机化合物（VOC），Astro是一个通过配备有燃气传感器的网络无人机进行自动3-D数据驱动的移动传感的平台。 VOC对人类健康和环境危害；它们是由在低收入和资源不足的城市社区中爆炸，气体泄漏和工业事故释放的，与工业加工厂，化学炼油厂和其他空中污染物的来源非常接近。该项目位于德克萨斯州休斯顿的经济不满地区。借助所有技术（TFA），项目团队拥有通过宽带访问，技术培训和联系健康与当地社区参与的历史。 TFA无线网络已经通过商业Wi-Fi和软件定义的收音机组合来为休斯顿东端几公里的1000名社区成员提供服务。该项目的目标是实现低收入城市地区环境状况的高分辨率基础真理，这可以通过政策和法律影响应急程序和环境正义。该项目将开发一个移动应用程序，向社区居民提醒当前位置附近的危险VOC浓度。该项目将影响城市区域，展示将下一代环境传感与通过网络无人机访问的下一代无线访问融合。该项目的目标是通过开发和演示Astro实现空前的VOC传感分辨率，ASTRO是一个无人机控制的网络无人机传感任务的系统。根据实时测量，Astro将实现在3D中动态传感器的独特功能。因此，具有板载传感器的无人机网络可以找到和跟踪VOC羽流，仅通过他们之间的协调，而无需集中的地面控制器。两个相互关联的推力将实现这一愿景。第一个是目标检测，跟踪和建模高VOC浓度簇，以健康和环境安全为目标。第二个是通过无人机网络开发数据驱动的移动任务的基本原则和方法。该项目的结果将包括轻型机器学习方法，这些方法为实时分布式自主感测的基础提供了环境和健康目标。这些数据集将以比当今可能更优质的分辨率产生大气模型的开发。此外，结果还将包括通过软件定义的无线电在网络无人机之间进行自适应通信的方法，这些方法可以调整其网络拓扑和频谱使用情况以实现任务目标。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估来通过评估来获得支持的。

项目成果

期刊论文数量（20）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Quartz-enhanced photoacoustic sensor for ethylene detection implementing optimized custom tuning fork-based spectrophone

用于乙烯检测的石英增强光声传感器实施优化的定制音叉分光器

DOI：
10.1364/oe.27.004271
发表时间：
2019-02-18
期刊：
OPTICS EXPRESS
影响因子：
3.8
作者：
Giglio, Marilena;Elefante, Arianna;Spagnolo, Vincenzo
通讯作者：
Spagnolo, Vincenzo

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication

DOI：
10.48550/arxiv.2203.10428
发表时间：
2022-03
期刊：
ArXiv
影响因子：
0
作者：
Cheng Wan;Youjie Li;Cameron R. Wolfe;Anastasios Kyrillidis;Namjae Kim;Yingyan Lin
通讯作者：
Cheng Wan;Youjie Li;Cameron R. Wolfe;Anastasios Kyrillidis;Namjae Kim;Yingyan Lin

Robust Environmental Sensing Using UAVs

DOI：
10.1145/3464943
发表时间：
2021-07
期刊：
ACM Transactions on Internet of Things
影响因子：
0
作者：
Ahmed Boubrima;E. Knightly
通讯作者：
Ahmed Boubrima;E. Knightly

CPT: Efficient Deep Neural Network Training via Cyclic Precision

DOI：
发表时间：
2021-01
期刊：
ArXiv
影响因子：
0
作者：
Y. Fu;Han Guo;Meng Li;Xin Yang;Yining Ding;V. Chandra;Yingyan Lin
通讯作者：
Y. Fu;Han Guo;Meng Li;Xin Yang;Yining Ding;V. Chandra;Yingyan Lin

ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes

DOI：
10.1145/3213526.3213527
发表时间：
2018-06
期刊：
Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications
影响因子：
0
作者：
Riccardo Petrolo;Yingyan Lin;E. Knightly
通讯作者：
Riccardo Petrolo;Yingyan Lin;E. Knightly