Towards integration of logistics processes from a cloud/fog-edge computing perspective

The emergence of the Internet of Things (IoT) and the cloud/fog-edge paradigm contributes for appearance of innovative designs for smart systems. The purpose of the doctoral research outlined in this article to design a method which will discover how IoT and the cloud/fog-edge computing can be utilized for advancing the reliability, transparency, and fault detection in processes within a smart transport and logistics system. The method is designed to contribute to the integrated use of different logistics modes in order to support decision-making and transparency for enterprises. The main focus is to detect how the envisioned system can ultimately provide an enhanced quality of service and integration of logistic shipments. The doctoral plan outlines five contributions that will lead towards integration of the logistics processes in a logistics setting. The first contribution is a taxonomy of functional and non-functional requirements that can be utilized for designing a new IoT platform for transport and logistics. The second contribution examines the cloud/fog-edge computing paradigm by considering existing IoT resource management techniques. The third contribution provides a holistic view of the structure and systems required for embedding the cloud/fog-edge paradigm in a specific demonstration. This conceptual blueprint aligns organizational needs for such system by using an enterprise architecture model. The fourth contribution combines previous results in a smart transport and logistics blueprint. The fifth contribution evaluates how a ML framework can be used to improve the alert detection, and quality of shipments based on the cloud/fog-edge paradigm.