The learning of programming is a field of research with relevant studies and publications for more than 25 years. Since its inception, it has been shown that its difficulty lies in the high level of abstraction required to understand certain programming concepts. However, this level can be reduced by using tools and graphic representations that motivate students and facilitate their understanding, associating real-world elements with specific programming concepts. Thus, this paper proposes the use of an intelligent tutoring system (ITS) that helps during the learning of programming by using a notation based on a metaphor of roads and traffic signs represented by 3D graphics in an augmented reality (AR) environment. These graphic visualizations can be generated automatically from the source code of the programs thanks to the modular and scalable design of the system. Students can use them by leveraging the available feedback system, and teachers can also use them in order to explain programming concepts during the classes. This work highlights the flexibility and extensibility of the proposal through its application in different use cases that we have selected as examples to show how the system could be exploited in a multitude of real learning scenarios.

Mixed reality is the combination of virtual and augmented reality to interactively and believably merge physical and computer-generated environments. This paper discusses the design of Health-5G, a scalable mixed reality-based system that facilitates and supports emergency response by medical emergency teams. Health-5G is supported by a distributed architecture divided into four interrelated applications responsible for advanced computer-human interaction, effective real-time videoconference, medical device integration, and communication infrastructure, respectively. The mixed reality layer is provided by the headset Microsoft Hololens 2™. Health-5G is based on scenarios in which emergency personnel wear mixed reality glasses that can transmit audio, video, and data streams bidirectionally over a 5G network to medical specialists stationed in a hospital at any distance. Thanks to Health-5G, the specialist will be able to access the emergency team’s point of view at any time and provide verbal and visual instructions, including gestures and positioning of graphical markers in 3D space. In this way, emergency personnel can provide the best possible care to the patient without having to wait for them to arrive at the hospital, saving a lot of time in scenarios where every second can make a difference. Health-5G also addresses the integration of medical devices and the collection of the patient’s medical data in a scalable way through optical character recognition. A case study is discussed where Health-5G is used to attend a patient in the street suffering from syncope due to third-degree atrioventricular block. Latency and performance tests over a 5G network are also discussed. To the best of our knowledge, there is no comprehensive solution in the literature that provides all the capabilities offered by Health-5G in terms of functionality and advanced interaction mechanisms within the context of remote, immersive support in emergency situations.

Virtual Reality (VR) is and will be a key driver in the evolution of e-commerce, providing an immersive and gamified shopping experience. However, for VR shopping spaces to become a reality, retailers’ product catalogues must first be digitised into 3D models. While this may be a simple task for retail giants, it can be a major obstacle for small retailers, whose human and financial resources are often more limited, making them less competitive. Therefore, this paper presents an analysis of low-cost scanning technologies for small business owners to digitise their products and make them available on VR shopping platforms, with the aim of helping improve the competitiveness of small businesses through VR and Artificial Intelligence (AI). The technologies to be considered are photogrammetry, LiDAR sensors and NeRF.In addition to investigating which technology provides the best visual quality of 3D models based on metrics and quantitative results, these models must also offer good performance in commercial VR headsets. In this way, we also analyse the performance of such models when running on Meta Quest 2, Quest Pro and Quest 3 headsets (Reality Labs, Reality Labs, CA, USA) to determine their feasibility and provide use cases for each type of model from a scalability point of view. Finally, our work describes a model optimisation process that reduce the polygon count and texture size of high-poly models, converting them into more performance-friendly versions without significantly compromising visual quality.