基于gps的内涝预测及智能路径生成方法

A. Choudhury, A. Agrawal, Priyanka Sinha, C. Bhaumik, Avik Ghose, S. Bilal
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引用次数: 5

摘要

本文介绍了一种多路径内涝易发区预测系统。这种方法是基于这样的理论:水倾向于在低洼地区积聚,因此一条包含更多更大盆地的路线在雨天更有可能表现得更差。利用这一基本原理,制定并应用算法来识别和量化路线上的内涝区。为了证明该系统的有效性,将系统给出的多条路线的置信度分数与人类通勤者给出的判断进行了比较。谷歌地图显示了所有可能路线的视图以及对内涝置信度评分的量化估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A methodology for GPS-based waterlogging prediction and smart route generation
This paper describes a system for predicting water logging prone areas in multiple routes. The approach is based on the theory that water tends to accumulate in low-lying areas and hence a route which contains more and bigger basins is more likely to behave worse on a rainy day. Using this basic principle, algorithms are formulated and applied to identify and quantify water logging zones on a route. To prove the effectiveness of the proposed system, the derived confidence scores for multiple routes given by the system are compared to judgements given by human commuters. A view of all possible routes along with quantified estimates of waterlogging confidence scores are rendered in Google map.
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