SBIR Phase I: Icy Road Forecast and Alert Product Using Road-Physics-Enhanced Weather Forecast Model and Remote Sensing Technologies
SBIR Phase I: Icy Road Forecast and Alert Product Using Road-Physics-Enhanced Weather Forecast Model and Remote Sensing Technologies
批准号:
1931673
负责人:
Menglin Jin
金额:
$22.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-02-01 至 2022-05-31
中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to reduce risks on icy winter roads and thus enhance transportation safety. Snow-covered and icy roads result in fatalities and disruption of commercial transportation. Decision-makers in government and industry need real-time observations and reliable weather forecasts to support timely decisions to reduce risks associated with icy road conditions. This SBIR project aims to develop and commercialize an innovative technology to detect, forecast and alert end users to icy road conditions. This Small Business Innovation Research (SBIR) Phase I project will integrate multi-satellite precipitation (liquid and frozen) and remote cloud sensing observations with a new physics-based road condition forecasting model to produce timely, secure, and efficient prediction of icy road conditions. Specifically, the proposed technology will use NOAA rainfall observations and NASA cloud observation services to assess surface temperature and water availability at a road surface, the two key parameters for ice formation on a road. In addition, a model incorporating a new surface energy budget and parameters to represent the physical and thermodynamic processes of road energy transportation will be developed to forecast icy road conditions up to 24 hours in advance. Furthermore, drone-mounted hyperspectral cameras using visible and near-infrared bands to detect ice on road surfaces will be developed. Collected black ice data from such cameras will be compared with the ground measurements from Road Weather Information Systems (RWIS) for validation. By combining these three new approaches, the technology is expected to reach an accuracy of approximately 85% for icy road forecasts.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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I-Corps: Improving Energy Management using Surface Temperature Forecasts
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资助金额:$5.0万
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财政年份:2016
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负责人:Menglin Jin
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依托单位:
Assessing Global and Regional Land Surface Skin Temperature Variations
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批准号:0855480
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资助金额:$42.0万
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财政年份:2007
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依托单位:
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