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I-Corps: Combining Traditional Building Inspection Sensors with Deep Learning and Robotics

I-Corps: Combining Traditional Building Inspection Sensors with Deep Learning and Robotics
I-Corps:将传统建筑检测传感器与深度学习和机器人技术相结合
批准号:
2232494
负责人:
Chen Feng
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-15 至 2024-07-31

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中文摘要
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英文摘要
The broader impact/commercial potential of this I-Corps project is to improve buildings envelopes that exacerbate greenhouse gas emissions and cause quality of life problems. The technology seeks to provide a non-invasive, integrated solution to locate and document moisture intrusion, thermal bridges, and air leaks to diagnose building envelope issues. The system identifies and quantifies common envelope defects and applies long-wave radar and deep learning to detect hidden deep moisture penetration and other major envelope defects. With this system, it is possible to perform low-cost, targeted micro-retrofits to address envelope issues. This project has the potential to (1) increase the efficiency and detection abilities of building health monitoring techniques; (2) increase the resilience of built infrastructure through comprehensive asset management and preventative building maintenance owing to improved early detection capabilities; (3) enable a strong cross collaboration across local government, industry, non-profits, and academia.This I-Corps project is based on the development of a non-invasive, integrated solution to locate and document moisture intrusion, thermal bridges, and air leaks in buildings. The system identifies and quantifies common envelope defects and applies long-wave radar and deep learning to detect hidden deep moisture penetration and other major envelope defects. Once identified, it may be possible to perform low-cost, targeted micro-retrofits to address the envelope issues. This project is a amalgamation of a number of complementary technologies that have the potential to significantly improve the field of building health monitoring. Project outcomes may enhance the ability to solve current building envelope inspections problems, increase the resilience of widely-used aging commercial and residential infrastructures, and provide a foundation for further study of non-destructive testing on building envelopes.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.
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CAREER: Robust and Collaborative Perception and Navigation for Construction Robots
  • 批准号:
    2238968
  • 项目类别:
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  • 资助金额:
    $60.0万
  • 财政年份:
    2023
  • 负责人:
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  • 依托单位:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
    $100.0万
  • 财政年份:
    2023
  • 负责人:
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  • 依托单位:
SCC-CIVIC-PG Track A: Full Building Scans for Targeted Micro-retrofits using Drones, Radars, and Deep Learning
  • 批准号:
    2228568
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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NRI: FND: Collaborative Research: DeepSoRo: High-dimensional Proprioceptive and Tactile Sensing and Modeling for Soft Grippers
  • 批准号:
    2024882
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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  • 负责人:
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