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Implementation of an IoT- and Cloud-based Digital Twin for Real-Time Decision Support in Port Operations

机译:实施基于物联网和基于云的数字孪生技术以在港口运营中提供实时决策支持

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Seaborne trade volumes are growing and the resulting traffic load on the road infrastructure in port areas calls for new solutions to improve handling and coordination of vehicles and shipments. In this contribution, a digital twin for truck dispatching operator assistance is presented, which enables the determination of optimal dispatching policies using simulation-based performance forecasts. Proprietary simulation software with limited interfaces, the application deployment in demanding industrial environments, and the integration of real-time sensor information represent three major challenges when realizing digital twin applications for logistics systems. This implementation, therefore, uses an extensible open-source simulation package and it is coupled with an IoT-platform for easy integration of real-time information. The digital twin is deployed as a cloud-based service, allowing for simple deployment and scalability.
机译:海运贸易量不断增长,港口地区道路基础设施上产生的交通负荷要求采用新的解决方案,以改善对车辆和货运的处理和协调。在此文稿中,提出了用于卡车调度操作员协助的数字孪生模型,该模型可以使用基于模拟的性能预测确定最佳调度策略。当为物流系统实现数字孪生应用时,接口有限的专有仿真软件,在苛刻的工业环境中的应用程序部署以及实时传感器信息的集成是三个主要挑战。因此,此实现使用可扩展的开源仿真程序包,并与IoT平台结合使用,以便轻松集成实时信息。数字孪生被部署为基于云的服务,从而实现了简单的部署和可伸缩性。

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