IoT-Based Digital Twin Model for Industrial Applications

A digital twin (DT) is a virtual representation of a physical object or system created using data obtained through numerical simulation or sensor measurements from Internet of Things (IoT) technologies, among others. These measurements allow the virtual model to be specific to a particular object or system, enabling diagnosis, predictive, and prescriptive maintenance. In this paper, we present the development of a DT for an IoT monitoring network with applications in Industry 5.0. To achieve this, we employ reduced-order models (ROM) based on the proper orthogonality decomposition (POD) technique to reconstruct a field of interest, e.g., temperature in a cold room or on a pig livestock farming, from a reduced set of optimally placed sensors. The results demonstrate that optimal placement can achieve low reconstruction errors even when only a few sensors are deployed - for example, three or four.