Event-driven Architecture for Sensor Data Integration for Logistics Services

Jens Leveling, Luise Weickhmann, Christian Nissen, Christopher Kirsch
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引用次数: 2

Abstract

Sensor data offers a massive potential for the logistics sector. To achieve an optimal, effective and productive supply chain, operators and manufacturers are challenged to use this information and extract value from it. They have to comply with the main task of efficiently managing logistics processes as well as fulfilling requirements and guidelines. To do so, it is necessary to monitor all processes and understand exceptions and anomalies. Sensor and Internet of Things (IoT) data is the key for these tasks. Currently, the data is available but not (sufficiently) used. The heterogeneity of sensor data is a major obstacle for the usage. Therefore, we present an architecture, which addresses these challenges by integrating heterogenic data in well-formed data sets.
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物流服务传感器数据集成的事件驱动架构
传感器数据为物流行业提供了巨大的潜力。为了实现最优、有效和高效的供应链,运营商和制造商面临着利用这些信息并从中提取价值的挑战。他们必须遵守有效管理物流过程以及满足要求和指导方针的主要任务。为此,有必要监控所有流程并了解异常和异常。传感器和物联网(IoT)数据是这些任务的关键。目前,数据是可用的,但没有(充分)使用。传感器数据的异构性是其应用的主要障碍。因此,我们提出了一种架构,通过在格式良好的数据集中集成异质数据来解决这些挑战。
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