Abstract
Over the years, industrial evolution has proved to be a complex process, since there are several aspects that need to be considered to achieve highly functional processes and differentiated quality products. To date, four industrial revolutions have been implemented. Thus, the paradigm of Industry 4.0 (I4.0) was born, a concept that aims to improve the efficiency, productivity, automation, and safety of industrial processes, but which also considers the operator’s relevance and centrality in these processes. Besides these four revolutions one more concept is emerging, called Industry 5.0 (I5.0). In recent years, and with the advance of scientific research, the implementation of wearables has proven to be the ideal solution to move towards the digitisation of Industrial sector. In this sense, the aim of this work is to provide a systematic review on the currently available knowledge about wearable technology and its applicability within I4.0. Through these technologies, both processes and operators can be monitored in real time, actively contributing to the identification of limitations and to the implementation of improvements. On the other hand, studies on the acceptance of these devices have shown a certain apprehension by users regarding the security and privacy of collected data. Therefore, studies should be conducted to analyse in depth these limitations, to raise users’ confidence and contribute, in a broader perspective, to the success of industrial processes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.

Abstract
The significant changes the electricity sector has been suffering in the latest decades increased the complexity and unpredictability of power and energy systems (PES). To deal with such a volatile environment, different software tools are available to simulate, study, test, and support the decisions of the various entities involved in the sector. However, being developed for specific subdomains of PES, these tools lack interoperability with each other, hindering the possibility to achieve more complex and complete simulations, management, operation and decision support scenarios. This paper presents the Intelligent Energy Systems Ontology (IESO), which provides semantic interoperability within a society of multi-agent systems (MAS) in the frame of PES. It leverages the knowledge from existing and publicly available semantic models developed for specific domains to accomplish a shared vocabulary among the agents of the MAS society, overcoming the existing heterogeneity among the reused ontologies. Moreover, IESO provides agents with semantic reasoning, constraints validation, and data uniformization. The use of IESO is demonstrated through a case study that simulates the management of a distribution grid, considering the validation of the network's technical constraints. The results demonstrate the applicability of IESO for semantic interoperability, reasoning through constraints validation, and automatic units' conversion. IESO is publicly available and accomplishes the pre-established requirements for ontology sharing.

Abstract
The widespread of distributed renewable energy is leading to an increased need for advanced energy management solutions in buildings. The variability of generation needs to be balanced by consumer flexibility, which needs to be accomplished by keeping the consumption cost as low as possible, while guaranteeing consumer comfort. This paper proposes a rule-based system with the aim of generating recommendations for actions regarding the energy management of different energy consumption devices, namely lights and air conditioning. The proposed set of rules considers the forecasted values of building generation, consumption, user presence in different rooms and energy prices. In this way, building energy management systems are endowed with increased adaptability and reliability considering the lowering of energy costs and maintenance of user comfort. Results, using real data from an office building, demonstrate the appropriateness of the proposed model in generating recommendations that are in line with current context.

Abstract
Virtual assistants offer a new type of solution to handle interaction between human and machine and can be applied in various business contexts such as Industry or Education. When designing and building a virtual assistant the developers must ensure a set of parameters to achieve a good solution. Various platforms and frameworks emerged to allow developers to create virtual assistant solutions easier and faster. This paper provides a review of available platforms and frameworks used by authors to create their own solutions in different areas. Big tech companies like Google with Dialogflow, IBM with Watson Assistant and Microsoft with Bot Framework, present mature solutions to build virtual assistants that provide to the developer all components of the basic architecture to build a fast and solid solution. Open-Source solutions focus on providing to the developer the main components to build a virtual assistant, namely language understanding and response generation.

Abstract
This paper proposes a new model to allocate reserve costs among the involved players, considering the characteristics of the several entities, and the particular circumstances at each moment. The proposed model is integrated in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which enables complementing the multi-agent simulation of diverse electricity market models, by including the joint simulation of energy and reserve markets. In this context, the proposed model allows allocating the payment of reserve costs that result from the reserve market. A simulation based on real data from the Iberian electricity market - MIBEL, is presented. Simulation results show the advantages of the proposed model in sharing the reserve costs fairly and accordingly to the different circumstances. This work thus contributes the study of novel market models towards the evolution of power and energy systems by adapting current models to the new paradigm of high penetration of renewable energy generation.