AutoMat CVIM——汽车大数据市场的可扩展数据模型

Johannes Pillmann, Benjamin Sliwa, C. Wietfeld
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引用次数: 7

摘要

在过去的几年里,连接已经被引入汽车生产系列,使车辆成为高度移动的物联网(IoT)传感器和参与者。地平线2020研究项目AutoMat通过建立一个车辆大数据市场来解决这一问题,以利用和利用众包传感器数据,这是迄今为止尚未挖掘的宝藏。作为该项目的一部分,开发了作为协调数据模型的通用车辆信息模型(CVIM)。CVIM允许一个共同的理解和通用的表示,在整个数据价值和处理链中独立于品牌。该演示器由CVIM车辆传感器数据组成,该数据贯穿整个AutoMat车辆大数据处理管道的不同组件。最后,以交通测量服务为例,对整个车队的数据进行了汇总和评估。
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The AutoMat CVIM - A Scalable Data Model for Automotive Big Data Marketplaces
In the past years, connectivity has been introduced in automotive production series, enabling vehicles as highly mobile Internet of Things (IoT) sensors and participants. The Horizon 2020 research project AutoMat addressed this scenario by building a vehicle big data marketplace in order to leverage and exploit crowd-sourced sensor data, a so far unexcavated treasure. As part of this project the Common Vehicle Information Model (CVIM) as harmonized data model has been developed. The CVIM allows a common understanding and generic representation, brand-independent throughout the whole data value and processing chain. The demonstrator consists of CVIM vehicle sensor data, which runs through the different components of the whole AutoMat vehicle big data processing pipeline. Finally, at the example of a traffic measurement service the data of a whole vehicle fleet is aggregated and evaluated.
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