Emergency situations such as wildfires, water floods, or even terrorist attacks require continuous communication between the coordination centres, the several on-the-field teams, and their respective devices to properly address the adverse circumstances. From a technological point of view, this can be best seen as a live Ubiquitous Sensor Network—composed of human beings (e.g., first responders, victims) and devices (e.g., drones, environmental sensors, radios)—with stringent and special communication requirements in terms of flexibility, mobility, reliability, bandwidth, heterogeneity, and speed of deployment. However, for this specific use case, most of the already deployed and well-known communication technologies (e.g., satellite, 4G/5G) might become unusable and hard to repair due to the associated effects of the disaster itself. The purpose of this paper is (1) to review the emergency communications challenges, (2) to analyse the existing surveys on technologies for emergency situations, (3) to conduct a more updated, extensive, and systematic review of the emergency communications’ technologies, and (4) to propose a heterogeneous communication architecture able to communicate between moving agents in harsh conditions. The proposed approach is conceived to link the relocating agents that constitute a Ubiquitous Sensor Network spanning a large-scale area (i.e., hundreds of square kilometres) by combining Near Vertical Incidence Skywave technologies with Drone-Based Wireless Mesh Networks. The conclusions derived from this research aim to set up the fundamentals of a rapidly deployable Emergency Communications System inspired by the Ubiquitous Sensor Network paradigm.

Industry 4.0 corresponds to the Fourth Industrial Revolution, resulting from technological innovation and research multidisciplinary advances. Researchers aim to contribute to the digital transformation of the manufacturing ecosystem both in theory and mainly in practice by identifying the real problems that the industry faces. Researchers focus on providing practical solutions using technologies such as the Industrial Internet of Things (IoT), Artificial Intelligence (AI), and Edge Computing (EC). On the other hand, universities educate young engineers and researchers by formulating a curriculum that prepares graduates for the industrial market. This research aimed to investigate and identify the industry’s current problems and needs from an educational perspective. The research methodology is based on preparing a focused questionnaire resulting from an extensive recent literature review used to interview representatives from 70 enterprises operating in 25 countries. The produced empirical data revealed (1) the kind of data and business management systems that companies have implemented to advance the digitalization of their processes, (2) the industries’ main problems and what technologies (could be) implemented to address them, and (3) what are the primary industrial needs and how they can be met to facilitate their digitization. The main conclusion is that there is a need to develop a taxonomy that shall include industrial problems and their technological solutions. Moreover, the educational needs of engineers and researchers with current knowledge and advanced skills were underlined.

Knowledge and skills in the field of Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing (EC) are more and more important for industry. Therefore, it is crucial to know what current students and future employees can offer to the industry. University students develop their knowledge and skills to support the industry in implementing modern technologies in the future. It can be expected that the first source of information for students will be lectures and other activities at the university. However, they may obtain knowledge from other sources. This article presents the results of research conducted among students assessing their own knowledge and skills in the field of IoT, AI, and EC. The research was preceded by an analysis of curricula at selected universities in terms of topics related to AI, IoT, and EC. Based on the results of the analysis, survey questions were prepared. The developed questionnaire was made available to students. The research sample for the survey participants was 563 students. The results obtained were analyzed. The results of the analysis show which issues are better known to students and which are worse. The information presented in this paper can be a source of information for the industry that can assess the competences that are or will be available on the labor market in the near future. Additionally, universities can obtain information on the areas in which there are competency gaps and which methods of teaching AI, IoT, and EC are better perceived by students.

In the era of Industry 4.0 (I4.0), a significant challenge hindering digital transformation is the lack of mutual understanding between academia—particularly within engineering and computer science—and the industrial sector, especially small to medium-sized enterprises (SMEs). This gap can result in industries missing out on the potential benefits of cutting-edge scientific research and innovations that can address their daily concerns. At the same time, academics may struggle to identify real-world application areas for their emerging technological solutions. Moreover, the ever-increasing complexity of industrial challenges and technologies has widened the hiatus. To address this issue, our study introduces a comprehensive taxonomy, developed through a transparent, iterative process and presented via a user-centric web platform. Distinct from existing taxonomies, ours emphasizes practical applicability by categorizing and connecting industrial challenges with I4.0 technologies using articles, best practices, and use cases from academic and grey literature, thereby effectively bridging the academic-industrial communication gap. Its effectiveness and practical utility were validated in a workshop as part of the Erasmus+ project PLANET4, where industry professionals provided positive feedback after applying it to real-world challenges. Future work will include expanding the taxonomy, developing an Industry 4.0 ontology, and further enhancing the usability and maintainability of the developed web platform.

On starting to think about interaction design for low-functioning persons in the autistic spectrum (PAS), especially children, one finds a number of questions that are difficult to answer: Can we typify the PAS user? Can we engage the user in interactive communication without generating frustrating or obsessive situations? What sort of visual stimuli can we provide? Will they prefer representational or abstract visual stimuli? Will they understand three-dimensional (3D) graphic representation? What sort of interfaces will they accept? Can we set ambitious goals such as education or therapy? Unfortunately, most of these questions have no answer yet. Hence, we decided to set an apparently simple goal: to design a "fun application," with no intention to reach the level of education or therapy. The goal was to be attained by giving the users a sense of agency--by providing first a sense of control in the interaction dialogue. Our approach to visual stimuli design has been based on the use of geometric, abstract, two-dimensional (2D), real-time computer graphics in a full-body, non-invasive, interactive space. The results obtained within the European-funded project MultiSensory Environment Design for an Interface between Autistic and Typical Expressiveness (MEDIATE) have been extremely encouraging.