Collaborative Research: CDI-Type II: VolcanoSRI: 4D Volcano Tomography in a Large-Scale Sensor Network

合作研究:CDI-Type II:VolcanoSRI:大规模传感器网络中的 4D 火山断层扫描

基本信息

  • 批准号:
    1125163
  • 负责人:
  • 金额:
    $ 51.76万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-01 至 2016-08-31
  • 项目状态:
    已结题

项目摘要

This project will create a new paradigm, VolcanoSRI (Volcano Seismic Realtime Imaging), for imaging 4D (four-dimensional) tomography of an active volcano in real-time. VolcanoSRI is a large-scale sensor network of low-cost geophysical stations that analyzes seismic signals and computes real-time, full-scale, three-dimensional fluid dynamics of the volcano conduit system within the active network. The computed 4D tomography model will illuminate complex, time-varying dynamics of an erupting volcano, providing a deeper scientific understanding of volcanic processes, as well as a basis for rapid detection of volcanic hazards. VolcanoSRI will potentially make the fictional holographic projector known as Virgil in the film "Supervolcano" a reality.Realizing the VolcanoSRI system requires a transformative study on the science of complex volcano systems and the design of large-scale sensor networks. Our approach integrates innovations on distributed tomographic algorithms, collaborative signal processing, and situation-aware networking technology for large-scale real-time sensor systems. The distributed tomography algorithm disperses the computational burden to the sensor nodes and performs real-time tomographic inversion within the network. Such an approach has never been attempted before and represents a major achievement for both earth and computer science. The team is composed of computer and earth scientists including early pioneers of wireless sensor networks as applied to volcano monitoring. VolcanoSRI holds vast potential for real-time risk monitoring and development of early-warning systems for volcanoes and other earth hazards. The new approach taken in VolcanoSRI is general, and can be implemented as a new network paradigm for other sensor-network applications, including oil-field exploration and structural and biomedical-health monitoring. The educational activities of this project include enhancing undergraduate and graduate curriculum and research programs at the three collaborating universities. Through this project, we plan to broaden access to these course materials by providing the course lectures, all readings, and assignments online to the public. This project provides many opportunities for collaborations of students across earth and computer science, increasing involvement of women and minorities, at the three collaborating universities.
该项目将创建一个新的范例,VolcanoSRI(火山地震实时成像),用于实时成像活火山的4D(四维)层析成像。VolcanoSRI是一个低成本地球物理台站的大规模传感器网络,分析地震信号,并计算活动网络内火山管道系统的实时、全尺寸、三维流体动力学。计算机4D断层扫描模型将阐明火山爆发的复杂、随时间变化的动力学,为火山过程提供更深入的科学了解,并为快速检测火山灾害奠定基础。VolcanoSRI将有可能使电影“超级火山”中虚构的全息投影仪成为现实。实现VolcanoSRI系统需要对复杂火山系统的科学进行变革性研究,并设计大规模传感器网络。我们的方法集成了分布式层析成像算法,协作信号处理和大规模实时传感器系统的态势感知网络技术的创新。分布式层析成像算法将计算负担分散到传感器节点,并在网络内执行实时层析成像反演。这种方法以前从未尝试过,代表了地球和计算机科学的重大成就。该团队由计算机和地球科学家组成,包括应用于火山监测的无线传感器网络的早期先驱。VolcanoSRI在实时风险监测和开发火山和其他地球灾害预警系统方面具有巨大潜力。VolcanoSRI中采用的新方法是通用的,可以作为其他传感器网络应用的新网络范例来实施,包括油田勘探以及结构和生物医学健康监测。该项目的教育活动包括加强三所合作大学的本科生和研究生课程和研究计划。通过这个项目,我们计划通过在线向公众提供课程讲座,所有阅读材料和作业来扩大这些课程材料的访问范围。该项目为地球和计算机科学领域的学生提供了许多合作机会,增加了三所合作大学的妇女和少数民族的参与。

项目成果

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Guoliang Xing其他文献

Account matching across heterogeneous networks
跨异构网络的账户匹配
Alzheimer’s disease digital biomarkers multidimensional landscape and AI model scoping review
阿尔茨海默病数字生物标志物多维图谱与人工智能模型范围审查
  • DOI:
    10.1038/s41746-025-01640-z
  • 发表时间:
    2025-06-16
  • 期刊:
  • 影响因子:
    15.100
  • 作者:
    Wenhao Qi;Xiaohong Zhu;Bin Wang;Yankai Shi;Chaoqun Dong;Shiying Shen;Jiaqi Li;Kun Zhang;Yunfan He;Mengjiao Zhao;Shiyan Yao;Yongze Dong;Huajuan Shen;Junling Kang;Xiaodong Lu;Guowei Jiang;Lizzy M. M. Boots;Heming Fu;Li Pan;Hongkai Chen;Zhenyu Yan;Guoliang Xing;Shihua Cao
  • 通讯作者:
    Shihua Cao
Exploiting Statistical Mobility Models for Efficient Wi-Fi Deployment
利用统计移动模型实现高效 Wi-Fi 部署
Improving the Robustness of Large Language Models via Consistency Alignment
通过一致性对齐提高大型语言模型的鲁棒性
Fast Release/Capture Sampling in Large-Scale Sensor Networks
大规模传感器网络中的快速释放/捕获采样
  • DOI:
    10.1109/tmc.2011.152
  • 发表时间:
    2012-08
  • 期刊:
  • 影响因子:
    7.9
  • 作者:
    Shaoliang Peng;Shaoliang Peng;Guoliang Xing;Guoliang Xing;Shanshan Li;Shanshan Li;Weijia Jia;Weijia Jia;Yuxing Peng;Yuxing Peng
  • 通讯作者:
    Yuxing Peng

Guoliang Xing的其他文献

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{{ truncateString('Guoliang Xing', 18)}}的其他基金

NeTS: Small: Collaborative Research: Realizing Visual and Acoustic Near Field Communication Systems for Smartphones: Performance Optimization and Security Assurance
NeTS:小型:协作研究:实现智能手机视觉和声学近场通信系统:性能优化和安全保证
  • 批准号:
    1423102
  • 财政年份:
    2014
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Standard Grant
NeTS: Small: SOAR: Leveraging Traffic Signatures to Improve Performance of Vehicular Networks
NeTS:小型:SOAR:利用流量签名提高车辆网络的性能
  • 批准号:
    1423221
  • 财政年份:
    2014
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Standard Grant
CSR: Small: Collaborative Research: Integrated Control of Fidelity and Real-Time Performance in Networked Sensing Systems
CSR:小型:协作研究:网络传感系统中保真度和实时性能的集成控制
  • 批准号:
    1218475
  • 财政年份:
    2012
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Standard Grant
Exploiting Mobility-assisted Collaboration for Adaptive Aquatic Sensor Networks
利用移动辅助协作实现自适应水生传感器网络
  • 批准号:
    1029683
  • 财政年份:
    2010
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Standard Grant
CAREER: Design and Analysis of Performance-Critical Wireless Sensor Networks: A Fusion-Centric Approach
职业:性能关键型无线传感器网络的设计和分析:以融合为中心的方法
  • 批准号:
    0954039
  • 财政年份:
    2010
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Continuing Grant
NeTS:Small:Collaborative Research:Holistic Transparent Performance Assurance within the Crowded Spectrum
NetS:小型:协作研究:拥挤范围内的整体透明性能保证
  • 批准号:
    0916576
  • 财政年份:
    2009
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Standard Grant

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