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US Ignite: Collaborative Research: Focus Area 1: Fiber Network for Mapping, Monitoring and Managing Underground Urban Infrastructure

US Ignite：合作研究：重点领域 1：用于测绘、监测和管理地下城市基础设施的光纤网络

基本信息

批准号：
1647175
负责人：
Dalei Wu
金额：
$ 29.99万
依托单位：
University of Tennessee Chattanooga
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2021-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1647175&HistoricalAwards=false
关键词：
US Ignite Collaborative Research Focus

项目摘要

Underground infrastructure supports services critical to daily human life, including fresh water supply, waste and storm water sewage, natural gas, electric power, steam and telecommunications. Much of the infrastructure is aging, and in unknown locations and condition. This project proposes innovative research to monitor and map underground infrastructure by integrating gigabit network-enabled sensing and mapping, cutting-edge networking, and data analytics. These real-time and automated sensing and mapping techniques can improve maintenance and management operations through better planning, incident response and condition assessment. Success will improve construction and repair efficiency, and reduce unplanned service interruptions, and accidents that harm the public safety and environment. This is a collaborative research project between the University of Vermont and the University of Tennessee at Chattanooga. The cities of Burlington, VT, Winooski, VT and Chattanooga, TN are providing access to their infrastructure facilities for testing. A notable feature is that all three cities have deployments of gigabit networks that are available for use on this project. The three participating cities are located in small metropolitan regions that ease implementation of research efforts, yet are big enough to identify key issues affecting scaling up to larger cities. This project also provides educational experiences for graduate students and participating municipal utility officials in gigabit network-enabled sensing and underground urban infrastructure. This project uses gigabit networks to integrate a mobile ground penetrating radar sensing with a cohesive network of sensors for detecting, assessing and reporting incipient conditions, such as emergent leaks. The processing and presentation of underground information will be rapidly transmitted to interested parties through secure, timely, and reliable communication, This project helps to build network-augmented position registration in an urban environment. Performance of the gigabit network-enabled utility mapping and sensing system will be measured in three participating cities. Success with this research will enable cities to manage, maintain and grow their infrastructure in manners that improve service, sustainability and resilience, while reducing costs, energy consumption and wasted resources. Since many of the aging underground infrastructure lies in older cities, often subjected to economic distress and decay, this project can help to provide basic human needs and rights, and help to provide social justice through reliable low-cost provision of clean drinking water, functional storm and waste water sewers, heat, electricity and telecommunications. Additionally, there is significant potential for increased resilience and rapid effective management of recovery from disasters.

地下基础设施支持对人类日常生活至关重要的服务，包括淡水供应、废水和雨水污水、天然气、电力、蒸汽和电信。许多基础设施已经老化，地点和状况不明。该项目提出了创新研究，通过集成千兆网络传感和映射，尖端网络和数据分析来监控和映射地下基础设施。这些实时和自动化的传感和绘图技术可以通过更好的规划、事件响应和状态评估来改善维护和管理操作。成功将提高施工和维修效率，减少计划外的服务中断以及危害公共安全和环境的事故。这是佛蒙特大学和田纳西大学查塔努加分校之间的一个合作研究项目。佛蒙特州伯灵顿市、佛蒙特州威诺斯基市和田纳西州查塔努加市正在提供其基础设施的测试通道。一个值得注意的特点是，这三个城市都部署了千兆网络，可用于该项目。这三个参与城市都位于小的大都市地区，便于开展研究工作，但又足够大，可以确定影响扩大到大城市的关键问题。该项目还为研究生和参与千兆网络传感和地下城市基础设施的市政公用事业官员提供教育经验。该项目使用千兆网络将移动的探地雷达传感与内聚传感器网络集成在一起，以检测、评估和报告紧急泄漏等初期情况。地下信息的处理和呈现将通过安全、及时和可靠的通信迅速传输给有关各方，该项目有助于在城市环境中建立网络增强的位置登记。千兆网络支持的公用事业映射和传感系统的性能将在三个参与城市进行测量。这项研究的成功将使城市能够以改善服务，可持续性和弹性的方式管理，维护和发展其基础设施，同时降低成本，能源消耗和浪费的资源。由于许多老化的地下基础设施位于老城市，往往受到经济困难和衰败的影响，该项目可以帮助满足基本的人类需求和权利，并通过可靠的低成本供应清洁饮用水、功能性暴雨和废水下水道、供暖、供电和电信，帮助实现社会正义。此外，在提高抗灾能力和迅速有效地管理灾后恢复工作方面也有很大潜力。

项目成果

期刊论文数量（11）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Resource Modeling and Scheduling for Mobile Edge Computing: A Service Provider’s Perspective

DOI：
10.1109/access.2018.2851392
发表时间：
2018-06
期刊：
IEEE Access
影响因子：
3.9
作者：
Shuaishuai Guo;Dalei Wu;Haixia Zhang;D. Yuan
通讯作者：
Shuaishuai Guo;Dalei Wu;Haixia Zhang;D. Yuan

Enhanced Underground Object Detection with Conditional Adversarial Networks

使用条件对抗网络增强地下物体检测

DOI：
发表时间：
2019
期刊：
ISSAT International Conference on Data Science and Intelligent Systems
影响因子：
0
作者：
Will, Rice;Omwenga, Maxwell;Wu, Dalei;Liang, Yu
通讯作者：
Liang, Yu

Extensive Huffman-tree-based Neural Network for the Imbalanced Dataset and Its Application in Accent Recognition

不平衡数据集的扩展哈夫曼树神经网络及其在口音识别中的应用

DOI：
10.1109/icaiic51459.2021.9415243
发表时间：
2021
期刊：
2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC
影响因子：
0
作者：
Merrill, Jeremy;Liang, Yu;Wu, Dalei
通讯作者：
Wu, Dalei

Classifying GPR Images Using Convolutional Neural Networks

使用卷积神经网络对探地雷达图像进行分类