Any life event or action can be seen as a potential source of data to analyze. By analyzing such data, we can gain insights into the facts. The situation is no different in public transport. Researchers working in the fields of transport and traffic have stated that such an analysis would be invaluable in designing urban transport and particularly in adapting to current changes. In this study, a scalable public transport analysis platform named Cermoni is developed using the Apache Beam programming model. It can analyze in near-real-time smart card and vehicle location data collected, classified as big data with its high production speed. The performance of the platform was tested on Google Cloud Dataflow service using real-world data gathered from Konya, one of the largest metropolitan cities in Turkey, and the results are discussed in detail.

中文翻译：

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公共交通大数据分析的可扩展平台

任何生活事件或行动都可以被视为潜在的数据分析来源。通过分析这些数据，我们可以深入了解事实。公共交通的情况也不例外。在交通运输领域工作的研究人员表示，这种分析对于设计城市交通，特别是在适应当前变化方面非常宝贵。在这项研究中，使用 Apache Beam 编程模型开发了一个名为 Cermoni 的可扩展公共交通分析平台。它可以对收集到的近实时智能卡和车辆位置数据进行分析，并以高生产速度归类为大数据。使用从土耳其最大的大都市之一科尼亚收集的真实数据在 Google Cloud Dataflow 服务上测试了该平台的性能，并对结果进行了详细讨论。