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Alteryx > 实例探究 > 改善迪拜国际机场的资源配置和旅客体验
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Predicting Passenger Flows at Dubai International Airport: An IoT Case Study

技术
  • 传感器 - 流量计
  • 传感器 - 液体检测传感器
适用行业
  • 航天
  • 设备与机械
适用功能
  • 采购
用例
  • 实时定位系统 (RTLS)
  • 虚拟原型与产品测试
挑战
迪拜国际机场需要客流预测工具来预测客流量的变化并相应地分配资源。
关于客户
迪拜国际机场是一座客流量大的机场,转机交通量巨大。他们需要一种工具来预测客流并有效地分配资源。
解决方案
该机场使用 Alteryx 和 Tableau 开发了一个原型来创建客流模型。该模型使用实时航班数据和参考表来预测乘客负载并优化资源分配。工作流程计划每 5 分钟运行一次,以使数据尽可能接近实时。输出数据在 Tableau 仪表板中可视化并在整个组织内共享。
运营影响
  • The passenger flow prediction tool provided significant operational benefits. Days after the tool went live, operational teams used the information to move resources from one terminal to another, thereby preventing serious overcrowding and queue build-up. This was not possible before as the information was not available. After a few months of using the tool, the airport observed clear decreases in queue lengths and wait times across many different touchpoints. The tool also proved to be invaluable during the Covid-19 pandemic, when the airport had to introduce PCR test stations, segregate passengers based on origin, and temporarily close terminals. The tool's flexibility and the close collaboration between teams allowed the airport to respond rapidly to changes and release multiple updates per week. The tool has been running successfully for over two years and has given the airport the flexibility to continue to add value in a cost-effective way.

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