Collaborative Research: Correlating Geospatial Data Lineage and Positional Accuracy for Excavation Damage Prevention
Collaborative Research: Correlating Geospatial Data Lineage and Positional Accuracy for Excavation Damage Prevention
批准号:
1265895
负责人:
Hubo Cai
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-06-01 至 2016-05-31
中文摘要
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英文摘要
The objective of this research is to explore methods that model and quantify the uncertainty associated with recorded underground utility location data. Locational uncertainty is the error associated with the methods of mapping underground utilities, and will be modeled as three-dimensional geometric shapes that correspond to the probability that these shapes contain the utilities. Locational uncertainty is dependent on locational accuracy, which will be estimated from data lineage - the format and process used to collect data. The premise associated with this research is that locational uncertainty results from inaccurate locational information that, in turn, is a function of data lineage. The utility data and its quantified uncertainty will be integrated with excavation operations, and communicated to operators by blending the geometry and attribute information with operators' views of the work environment using video-see-through augmented reality. Field experiments will be conducted with industry partners to validate the proposed geospatial uncertainty model and evaluate its benefits of improving excavation safety.If successful, the research results will lead to improvements in construction operations such as, excavation in the presence of buried utilities, drilling in the presence of hidden obstructions, and robotic construction in the absence of exact prior knowledge of the environment. The project will impact education by promoting subsurface utility engineering as an area of specialization. A diverse group of under-represented students will participate in the project through active collaboration with the Women in Science and Engineering, and the Minority Engineering Program offices at Purdue and the University of Michigan. In summary, the societal benefits of the project are expected to be the improved safety of excavation and other construction operations, and the multi-disciplinary education and training of current and future engineers in an emerging engineering specialty.
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PFI-TT: Development of a Mapping and Visualization System to Inform Excavators of Buried Utility Pipes
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批准号:2213750
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项目类别:Standard Grant
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资助金额:$25.0万
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财政年份:2022
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负责人:Hubo Cai
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依托单位:
Mapping the Underworld of Buried Utilities - A Hybrid Sensing Approach
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批准号:1462638
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项目类别:Standard Grant
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资助金额:$21.65万
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财政年份:2015
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负责人:Hubo Cai
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依托单位:
国内基金
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