Smart Cyber-Physical Spatial-Temporal System for Data-Driven Logistics Operation Management

Abstract
Operation management in logistics must be associated with three essential factors, people, machine and material. In the conventional case, they could not be correlated together in a real-time manner, thus causing errors in execution and decision making. In this study, a smart cyber-physical system is developed to cope with the problem, which can not only makes the data-driven solutions solvable with existing operation research techniques, but also motivates more real-life industrial applications. It can be mainly divided into four layers. First, in the physical layer, a variety of IoT devices are deployed to collect data from smart objects equipped with smart tags and launch initial processing. Second, the physical layer is synchronized with the cyber layer by smart gateways so that mounts of data captured in the physical layer can be conveyed concurrently to the cyber for further data mining and sharing. Third, in the cyber layer, useful digital information extracted from data flows among smart objects in a peer-to-peer method by leveraging novel blockchain techniques. Fourth, assisted with multiple localization techniques, being aware of the spatial positions of smart objects bound with temporal stamp enhances the visibility and traceability of operations, thus reducing the complexity and uncertainty, and meanwhile improving the operational efficiency noticeably. A case study of real-life staff security monitoring in cold storage is investigated for testifying how this smart cyber-physical spatial-temporal system is capable of facilitating operation management.