Alberto Morato

Accurate trajectory tracking is a key requirement in unmanned ground vehicles (UGVs) operating in autonomous driving, mobile robotics, and industrial automation. In wireless Time-Sensitive Networking (WTSN) scenarios, trajectory accuracy strongly depends on deterministic packet delivery, precise traffic scheduling, and time synchronization among distributed devices. This paper quantifies the impact of IEEE 802.1Qbv time-aware traffic scheduling on trajectory tracking accuracy in UGVs operating over Wi-Fi-enabled TSN networks. The analysis focuses on how misconfigured real-time (RT) and best-effort (BE) transmission windows, as well as clock misalignment between devices, affect packet reception and control performance. A mathematical framework is introduced to predict the number of correctly received RT packets based on cycle time, packet periodicity, scheduling window lengths, and synchronization offsets, enabling the a priori dimensioning of RT and BE windows. The proposed model is validated through extensive simulations conducted in an ROS–Gazebo environment, utilising Linux-based traffic shaping and scheduling tools. Results show that improper traffic scheduling and synchronization offsets can significantly degrade trajectory tracking accuracy, while correctly dimensioned scheduling windows ensure reliable packet delivery and stable control, even under imperfect synchronization. The proposed approach provides practical design guidelines for configuring wireless TSN networks supporting real-time trajectory tracking in mobile robotic systems.

This paper explores the challenges of integrating existing in-vehicle networks (IVNs) with ethernet, explicitly focusing on the coexistence of traditional Controller Area Network (CAN) systems with Single Pair Ethernet (SPE) and Time-Sensitive Networking (TSN). The research presents an experimental setup using real hardware to simulate a zonal vehicle architecture, where CAN nodes are integrated into the in-vehicle ethernet network. The approach utilizes a gateway implemented on a TSN-enabled switch, facilitating seamless connectivity between the real-time CAN network and the TSN-enabled in-vehicle Ethernet. The study demonstrates the feasibility of combining real-time CAN traffic with high-bandwidth Ethernet traffic through the integrated gateway. It also emphasizes the crucial role of TSN features in maintaining the real-time properties of the CAN network, even in the presence of additional traffic loads.

In the era of electrical substation digitalization, the reliability of Phasor Measurement Units (PMUs) is crucial. This paper addresses the impact of fault conditions in PMUs on system reaction time in a 5G network environment. We focus on fault-critical conditions in communication systems, particularly in the presence of PMU-based measurement systems. We perform a series of simulations to evaluate the performance of the 5G infrastructure for transmitting IEC61850 data. Results from simulations show that the performance in terms of latency and packet loss is strongly influenced by the topology of 5G networks, particularly the number and deployment of gNBs (5G base stations) serving PMU systems. The analysis of the two case studies underscores the importance of considering the specific characteristics of each fault event when designing and deploying PMU/PDC systems capable of real-time fault detection and response, ensuring the stability and reliability of the power grid. This will involve simulating various fault scenarios and communication network impairments to better understand their impact on the overall system performance and to mitigation strategies to improve the reliability and resilience of the PMU system in real-world deployment scenarios.

In recent years, there has been a rapid shift towards a fully digital paradigm in electrical substations. This shift is driven by the need for greater interoperability between different instruments and control actions, which is facilitated by the IEC 61850 series of standards. In this paper, we specifically focus on Phasor Measurement Units (PMUs) and their role in this digital transformation. One of the challenges in adopting high-performance wired communication standards such as Ethernet and TSN is the cost associated with wiring over long distances between substations. To overcome this limitation, we explore the feasibility of utilizing a 5G communication infrastructure to transmit PMU measurements. Our study simulates a real-world distribution network and assesses the worst-case latency between PMUs and Phasor Data Concentrator (PDC) by scaling the number of PMUs considered. With a mean communication latency of 20 ms, the 5G communication infrastructure proves to be a valuable solution, particularly in distribution networks where the monitoring applications rely on update rates in the order of few tens of ms.

Industry 4.0 has significantly improved the industrial manufacturing scenario in recent years. The Industrial Internet of Things (IIoT) enables the creation of globally interconnected smart factories, where constituent elements seamlessly exchange information. Industry 5.0 has further complemented these achievements, as it focuses on a human-centric approach where humans become part of this network of things, leading to a robust human–machine interaction. In this distributed, dynamic, and highly interconnected environment, functional safety is essential for adequately protecting people and machinery. The increasing availability of wireless networks makes it possible to implement distributed and flexible functional safety systems. However, such networks are known for introducing unwanted delays that can lead to safety performance degradation due to their inherent uncertainty. In this context, the Time-Sensitive Networking (TSN) standards present an attractive prospect for enhancing and ensuring acceptable behaviors. The research presented in this paper deals with the introduction of TSN to implement functional safety protocols for wireless networks. Among the available solutions, we selected Wi-Fi since it is a widespread network, often considered and deployed for industrial applications. The introduction of a reference functional safety protocol is detailed, along with an analysis of how TSN can enhance its behavior by evaluating relevant performance indexes. The evaluation pertains to a standard case study of an industrial warehouse, tested through practical simulations. The results demonstrate that TSN provides notable advantages, but it requires meticulous coordination with the Wi-Fi MAC layer protocol to guarantee improved performance.

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible.

The groundbreaking transformations triggered by the Industry 4.0 paradigm have dramatically reshaped the requirements for control and communication systems within the factory systems of the future. The aforementioned technological revolution strongly affects industrial smart and distributed measurement systems as well, pointing to ever more integrated and intelligent equipment devoted to derive accurate measurements. Moreover, as factory automation uses ever wider and complex smart distributed measurement systems, the well-known Internet of Things (IoT) paradigm finds its viability also in the industrial context, namely Industrial IoT (IIoT). In this context, communication networks and protocols play a key role, directly impacting on the measurement accuracy, causality, reliability and safety. The requirements coming both from Industry 4.0 and the IIoT, such as the coexistence of time-sensitive and best effort traffic, the need for enhanced horizontal and vertical integration, and interoperability between Information Technology (IT) and Operational Technology (OT), fostered the development of enhanced communication subsystems. Indeed, established technologies, such as Ethernet and Wi-Fi, widespread in the consumer and office fields, are intrinsically non-deterministic and unable to support critical traffic. In the last years, the IEEE 802.1 Working Group defined an extensive set of standards, comprehensively known as Time Sensitive Networking (TSN), aiming at reshaping the Ethernet standard to support for time-, mission- and safety-critical traffic. In this paper, a comprehensive overview of the TSN Working Group standardization activity is provided, while contextualizing TSN within the complex existing industrial technological panorama, particularly focusing on industrial distributed measurement systems. In particular, this paper has to be considered a technical review of the most important features of TSN, while underlining its applicability to the measurement field. Furthermore, the adoption of TSN within the Wi-Fi technology is addressed in the last part of the survey, since wireless communication represents an appealing opportunity in the industrial measurement context. In this respect, a test case is presented, to point out the need for wirelessly connected sensors networks. In particular, by reviewing some literature contributions it has been possible to show how wireless technologies offer the flexibility necessary to support advanced mobile IIoT applications.

The Industrial IoT (IIoT) paradigm represents an attractive opportunity for new generation measurement applications, which are increasingly based on efficient and reliable communication systems to allow the extensive availability of continuous data from instruments and/or sensors, thus enabling real-time measurement analysis. Nevertheless, different communication systems and heterogeneous sensors and acquisition systems may be found in an IIoT-enabled measurement application, so that solutions need to be defined to tackle the issue of seamless, effective, and low-latency interoperability. A significant and appropriate solution is the Open Platform Communications (OPC) Unified Architecture (UA) protocol, thanks to its object–oriented structure that allows a complete contextualization of the information. The intrinsic complexity of OPC UA, however, imposes a meaningful performance assessment to evaluate its suitability in the aforementioned context. To this aim, this paper presents the design of a general yet accurate and reproducible measurement setup that will be exploited to assess the performance of the main open source implementations of OPC UA. The final goal of this work is to provide a characterization of the impact of this protocol stack in an IIoT-enabled Measurement System, in particular in terms of both the latency introduced in the measurement process and the power consumption.