The vision of Industry 5.0 builds upon the advanced technologies of Industry 4.0, aligning its emerging concepts with three key pillars: human-centricity, sustainability, and resilience. In this context, the idea of the Product Digital Twin (PDT), first introduced in 2002, which has further matured (and refined) by the Asset Administration Shell (AAS) standard, must continue evolving to integrate the vision of Digital Product Passport (DPP) as promoted via several initiatives from the European Commission. Moreover, positioning PDT correctly within this broader context of Industry 5.0 is crucial, as it involves the modeling and implementation of PDT instances, which then significantly influence manufacturing applications. To address this need, this paper first harmonizes different PDT definitions and then proposes a modeling and deployment approach appropriate to the new concept of PDT information models.

Digital Twin, the technological advance that has emerged in the Industry 4.0 era, will become one of the six technological pillars forming Industry 5.0, according to the vision of the European Commission. This promotion relies on the fact that digital-twin technologies are getting more mature and widely adopted in both the public and private sectors. Besides the progressions, a new challenge has arisen: harmonizing multiple digital twins in a single digital twin system. Indeed, digital twins built on different technologies addressing different aspects of an asset are not interoperable by default, making the interaction between them uneasy. Moreover, as an asset must have a connection with each digital twin for data exchange, its multiple connections with multiple digital twins may cause the asset itself and the involved network infrastructures to be overloaded. Regarding the above challenge, this paper proposes an approach based on the Asset Administration Shell (AAS) standard to harmonize multiple digital twins as a single digital twin with multiple facets.

Companies are increasingly needed to exchange data about their products and processes via a common secured and trusted network, in which they can self-determine who and how their data will be accessed and used. To address this growing need, we propose in this paper a model-based engineering approach that integrates the standards of the domain: the Asset Administration Shell (AAS) for creating data models representing the company's assets, ODRL for the specification of the data usage policies and the Eclipse Dataspace Connector (EDC) for International Data Spaces (IDS) compliant data exchange.

Switched beam antennas (SBA) have been shown to offer many advantages when used in confined and obstructed environments that represent a difficult radio propagation environment. However, when SBA are used in wireless network, the popular contention-based medium access control protocol such as IEEE 802.15.4 MAC is no longer effective. Furthermore, the contention based nature of IEEE 802.15.4 MAC makes it not suitable for deterministic transmissions. In order to have a good compromise between range, data rate and deterministic behavior, in this paper, we propose data collection schemes based on polling-selecting strategies for low latency deterministic networked (LLDN) systems where the sink is equipped with a SBA and sensor nodes with usual omnidirectional antennas. Our solution is based on IEEE 802.15.4 frame exchanges in star topology. We present an analytical model to evaluate the benefit of using an extra slot in a collection scheme based on polling strategy. Several simulations were conducted to validate the analytical model and show that using an extra slot in a collection scheme based on polling strategy improves the frame delivery rate.

Wireless Sensor Networks (WSNs) are often used for gathering data collected by sensor nodes spread over large monitored areas. Star topologies, having a sink node at their center, are becoming a clear trend when the size of the monitored area allows it. The range of the radio links used, increases due to the decision to use a sub-GHz frequency and/or a particular signal coding that ensures a significant processing gain in the radio link budget. Even though such long-range radio links are beneficial in specific applications, in spite of the low data rate limit, often remains a weakness for application in many domains. Our overall objective is to consider combining the use of a switched-beam antenna only for the sink node of a star topology and omnidirectional antennas for wireless sensor nodes, in order to achieve a better balance between Range and Data Rate. When switched- beam antennas are used to equip some nodes, usual medium access methods have to be revised as does the discovery of the neighborhood of the sink. In this paper, we propose a scheme that allows the sink node to discover all its neighboring nodes within a limited timeframe, despite the hidden terminal problem effects worsen by antennas directivity.

One of the key element in performance measurement for a neighbor discovery algorithm with switched beam antennas is how long it takes to discover the neighbors given that nodes do not have any prior knowledge about their neighbors. An impression we may have in neighbor discovery is that algorithms based on directional antennas takes longer time for a node to discover all its neighbors than those entirely based on omnidirectional antennas. We propose two neighbor discovery schemes, one is based on time slotting and the other on the well known CSMA/CA unslotted version. We evaluate the time that the sink needs to discover its neighbors when it is equipped with a switched beam antenna, and when it uses an omnidirectional antenna. Through our simulation results, we show that when neighbor discovery algorithms based on directional antennas are correctly designed, they achieve the same order of performance in terms of time needed by the sink to discover all its neighbors as those based on omnidirectional antennas. Our simulation results also show that when using a switched beam antenna and CSMA/CA algorithm for medium access at the sink, the discovery delay is higher.