A completely automatic near-field mapping system has been developed within the Research Institute for Electronic Embedded Systems (IRSEEM) in order to determine the electromagnetic field created by electronic systems and components. This test bench uses a 3-D positioning system of the probe to make accurate measurements. This paper presents some applications of the near-field techniques in EMC investigations. In the first part, near-field measurements are used to locate precisely the electromagnetic sources of a limiter device. In the second part, we present an equivalent model of the radiated emission of an integrated circuit. In the last part, the near-field test bench is used to characterize faults in a cable.

In recent years, the use of digital twins (DT) to improve maintenance procedures has increased in various industrial sectors (e.g., manufacturing, energy industry, aerospace) but is more limited in the construction industry. However, the operation and maintenance (O&M) phase of a building’s life cycle is the most expensive. Smart buildings already use BIM (Building Information Modeling) for facility management, but they lack the predictive capabilities of DT. On the other hand, the use of extended reality (XR) technologies to improve maintenance operations has been a major topic of academic research in recent years, both through data display and remote collaboration. In this context, this paper focuses on reviewing projects using a combination of these technologies to improve maintenance operations in smart buildings. This review uses a combination of at least three of the terms “Digital Twin”, “Maintenance”, “BIM” and “Extended Reality”. Results show how a BIM can be used to create a DT and how this DT use combined with XR technologies can improve maintenance operations in a smart building. This paper also highlights the challenges for the correct implementation of a BIM-based DT combined with XR devices. An example of use is also proposed using a diagram of the possible interactions between the user, the DT and the application framework during maintenance operations.

In the context of the Industry 4.0 and of the digital factory, digital twin and virtual reality represent key technologies to design, simulate and optimize cyber-physical production system and interact with it remotely or in a collaborative way. Moreover, these technologies open up new possibilities which can be involved in the co-design and ergonomics studies of workstations, based on Industry 4.0 components like cobots. In order to satisfy these needs and to create dynamic and immersive virtual environment, it is therefore necessary to combine the capacities of the digital twin to perform simulation of the production system with the capacities of the immersive virtual environment in term of interactions. This paper proposes a co-simulation and communication architecture between digital twin and virtual reality software, then it presents a use case on a human-robot collaborative workplace design and assessment.

EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT) emerges as a promising next-generation technology. Its diverse applications hod the potential to revolutionize multiple facets of Industry 4.0 and serve as a cornerstone for the rise of Industry 5.0. However, current systems are still not effective in providing a high-quality experience for users due to various factors, one of which is their limited resources for processing and transmitting complex data and big data. To overcome these challenges, this paper presents an in-depth analysis of performance optimization techniques for resource-constrained Augmented Reality (AR) and/or Virtual Reality (VR) environments operating with DT, with a specific focus on Quality of Service (QoS), Quality of Experience (QoE), Edge-Cloud architectures and future research directions. Furthermore, this study delves into the intricate complex trade-off relationships involving optimization factors, including system quality, information quality, and QoE. In addition, it also explores potential solutions based on powerful emerging technological tools, including data compression, blockchain, cloud computing, quantum computing, Artificial Intelligence (AI) / Machine Learning (ML), and cybersecurity in the Cyber-Physical Systems (CPS). The insights provided in this comprehensive survey can inspire and guide researchers and industrial practitioners in optimizing performance for XR with DT applications in resource-constrained Smart Manufacturing System (SMS).