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Automated transportation transfer detection using GPS enabled smartphones

机译:使用支持GPS的智能手机自动进行交通运输中转检测

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Understanding the mobility of a traveller from mobile sensor data is an important area of work in context aware and ubiquitous computing. Given a multimodal GPS trace, we will identify where in the GPS trace the traveller changed transportation modes. For example, where in the GPS trace the traveller alight a bus and boards a train, or where did the client stop running and start walking. Using data mining schemes to understand mobility data, in conjunction with real world observations, we propose an algorithm to identify mobility transfer points automatically. We compared the proposed algorithm against the state of the art that is used in the previously proposed work. Evaluation on real world data collected from GPS enabled mobile phones indicate that the proposed algorithm is accurate, has a good coverage, and a good asymptotic run time complexity.
机译:从移动传感器数据中了解旅行者的机动性是上下文感知和普遍计算中的重要工作领域。给定多模式GPS轨迹,我们将确定旅行者在GPS轨迹中的何处更改了运输方式。例如,旅行者在GPS轨迹中的哪里下车,乘公共汽车上火车,或者客户在哪里停止跑步并开始行走。使用数据挖掘方案来了解移动性数据,结合现实世界的观察,我们提出了一种算法来自动识别移动性转移点。我们将提出的算法与先前提出的工作中使用的现有技术进行了比较。对从启用GPS的手机中收集到的现实世界数据的评估表明,该算法准确,覆盖范围广且渐近运行时复杂度高。

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