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Geospatial Visualization of Automotive Sensor Data: A Conceptual and Implementational Framework for Environment and Traffic-Related Applications

机译:汽车传感器数据的地理空间可视化:环境和交通相关应用的概念和实施框架

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In the era of Big Data and the Internet of Things modern automotive vehicles have become complex mobile computational systems on wheels. The sensors included in these systems record a multitude of car- and traffic-related data, as well as environmental parameters outside the vehicle. The data recorded can be characterized as "spatio-temporal" by their nature and can, thus, be classified as "geodata". As such, they allow for, comprehensive analysis and visualizations. Their geospatial and application potential has, however, not been fully unlocked so far. This paper deals with the ongoing research on these new kinds of massive geodata. It presents an approach to process and visualize this data for context-sensitive applications. Cartographic visualization is a particularly effective means to make the enormous stock of machine-recorded data available to human perception, exploration and analysis.
机译:在大数据和物联网时代,现代汽车已成为带轮子的复杂移动计算系统。这些系统中包含的传感器记录了大量与汽车和交通相关的数据,以及车辆外部的环境参数。记录的数据可以通过其性质被描述为“时空”,因此可以被分类为“地理数据”。因此,它们允许进行全面的分析和可视化。但是,到目前为止,它们的地理空间和应用潜力还没有完全释放出来。本文涉及对这些新型海量地理数据的正在进行的研究。它为上下文相关的应用程序提供了一种处理和可视化此数据的方法。制图可视化是一种特别有效的手段,可以使大量的机器记录数据可供人类感知,探索和分析。

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