Disruptions and exceptions are an important source of risks in logistics, as far as the planning of transportation services is concerned. Failing to rapidly react on and handle such events may lead to serious depreciation of the transported cargo and reputation damage. The Internet of Things seems to be the technology capable of providing the tools required to detect exceptions nearly real-time. However, currently, there is little research on how to enhance the detected exceptions with related information from internal or external sources. Furthermore, most exception detection capabilities rely on experience and not much research exist on how to improve the accuracy of using third-party knowledge. In this paper, we propose a reference architecture for situation-aware logistics. The architecture specification follows the key principles derived from an extensive requirements analysis, the state of the art literature, and the ideas promoted by the Industrial Data Space initiative. The proposed architecture has been instantiated and tested by means of a prototype designed for the case of temperature-controlled transportation services.
Building on earlier work, this paper aims to demonstrate and discuss an instantiated architecture for situation-aware logistics in an operational environment using smart returnable assets. The demonstration is based on a motivation scenario focusing on exception management. The system outline and its components, interfaces, and enabling technologies are described and linked to the different layers of the architecture. This paper documents and illustrates the use of the system with detailed models and screenshots. Earlier work is extended using business rules to identify and quantify exceptions and potential disruptions. Specifically, it is shown how shipment data are enhanced with data from IoT sensors of smart returnable assets to provide situation-aware decision support based on data analytical methods. This demonstration provides scholars and practitioners, active in the fields of enterprise computing, insights into the concepts, models and engineering technologies used to implement an architecture for situation-aware logistics. The instantiated architecture provides a rich testbed for experiments, measurements, and incorporate the ideas promoted by the international data space initiative. An online recording is available to support the demonstration and ignite discussion about the potential of IoT technologies and future research directions in pursuit of the smart logistics vision.
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