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En los últimos años se está explorando el uso y adopción de tecnologías innovadoras en el sector de la educación y aprendizaje. Asimismo, modelos de educación y docencia online están ganando protagonismo, ya sea debido a una implantación voluntaria o forzosa de programas de educación remota y/o híbrida. Este auge ha hecho palpable las limitaciones de los sistemas de comunicaciones audiovisuales 2D, como la videoconferencia, en varios sentidos: confort, calidad de interacción, conciencia situacional, (co-)presencia, etc. Este trabajo introduce un nuevo medio de comunicación, interacción y colaboración que promete ser un candidato idóneo para superar estas limitaciones haciendo uso de tecnologías inmersivas: la Realidad Virtual (RV) Social. En primer lugar, se aportará una revisión de evidencias científicas recientes que vislumbran y demuestran potenciales beneficios de este medio para diferentes casos de uso de interés, en comparación al uso de sistemas de videoconferencia 2D tradicionales. Asimismo, se destacarán los potenciales beneficios que puede aportar la disponibilidad de representaciones holográficas 3D de los usuarios en comparación al uso de avatares sintéticos (y por tanto, poco realistas) en entornos de RV Social. A continuación, se destacarán una serie de retos a nivel tecnológico y de experiencia de usuario a superar con tal de conseguir una implantación efectiva y masiva de este nuevo medio de comunicación. Palabras clave: realidad virtual social, comunicaciones holográficas, metaverso, holoportación, educación inmersiva, educación virtual.

Next-generation IoT systems will allow sustainable performance in long-term monitoring systems. This sustainability concept applies to soundscape description, as it allows monitoring in urban environments. In this work, the implementation of psycho-acoustic annoyance models in a 5G-enabled IoT system is proposed, applying two edge-computing approaches. A modified Zwicker’s model is adopted in this research, introducing a term that takes into account the tonal component of the captured sound. These implementations have been validated in a measurement campaign where several IoT devices have been deployed to evaluate different sound environments of a university campus. Then, the analysis of the sound-quality metrics is conducted in a different location, showing that if tonality is present in a noisy environment, it results in greater subjective annoyance. Moreover, the Just-Noticeable Difference of these results is derived from Zwicker’s psycho-acoustic annoyance to establish a limitation for this metric.

Preserving the Intangible Cultural Sound Heritage of Humanity is a crucial aspect of safeguarding a people’s culture and history. By employing objective acoustic and psychoacoustic parameters, we can effectively analyze and characterize these auditory environments based on objective, aesthetic, and emotional criteria. The ISO 12913 standard governs the depiction of soundscapes, while the evaluation of outdoor sites involves conducting sound-walks. This study focuses on assessing different soundscapes observed during festivities in Spain as sound walk (dynamic) and as in fireworks (static). The festivities assessed were: "Fallas" in Valencia, Sanfermines in Pamplona, "Festa de la Mare de Deu" in Algemesi, and "Moros y Cristianos" in Villena. To evaluate these soundscapes, we captured ambient sound recordings while traversing through or staying between the festival crowds. Subsequently, we employed various psychoacoustic metrics, such as loudness, sharpness, roughness, fluctuation stress, and tonality, and analyzed them using Zwicker models. Additionally, we conducted a subjective survey to compare the subjective responses with the psychoacoustic metrics obtained.

This study analyses the detection efficiency of the Worldwide Lightning Location Network (WWLLN) of sensors over Spain, a comparison is made with the Meteorological Spanish Agency (AEMET) Lightning Detection Network. The WWLLN operates a planetary distributed network of Very Low Frequency (VLF) antennas which detect lightning VLF signals around the Earth. Very high currents from lightning strokes radiate strong VLF signals in the band 6-22 kHz, which are detected up to 10,000 km, therefore WWLLN receiving sensors can be sparsely spaced. However the detection capability of VLF signals depends on the environment, and clean areas with a good ground and no metal parts around must be selected for proper reception. For the area of Spain and Portugal we had two WWLLN sensors in 2012, and three sensors later on for the data of 2020, 2021 and 2022. The sensors in Iberian Peninsula are at a distance of around 760 km; that is very close in comparison with other WWLLN sensors in the Earth which are around 5.000-15.000 km. The WWLLN sensors send the timing of the detection to the central sensor where the location of the lightning is determined with an improved algorithm when a mini-mum of 5 sensors detect the VLF signal. We show that detection efficiency was excellent and consistent with previous studies. Lightning location data from 1st January 2012 to 30st April 2012 from AEMET was used to analyze time and space shared events with the WWLLN network with 0.5s time difference and 20 km distance. The results improved in 2020, 2021 and 2022. More than 40,000 lightning strikes were analyzed in the present work, and we found a detection efficiency > 38%.

Next Generation IoT systems will allow sustainable performance in long-term monitoring systems. This sustainability concept is applicable to soundscape description, as it allows monitoring in urban environments. In this work, the implementation of psycho-acoustic annoyance models in a 5G-enabled IoT system is proposed applying two Edge Computing approaches. A modified Zwicker’s model is adopted in this research, introducing a term that takes into account the tonal component of the captured sound. These implementations have been validated in a measurement campaign where several IoT devices have been deployed to evaluate different sound environments of a University Campus. Then, the analysis of the sound quality metrics is done in different location showing that if tonality is present in a noisy environment, it results in greater subjective annoyance. Moreover, the Just Noticeable Difference of these results are derived for the Zwicker’s psycho-acoustic annoyance to establish a limitation for this metric.

The emergence of low cost Ultra Wide Band (UWB) transceivers has enabled the implementation of Wireless Sensor Networks (WSN) based on this communication technology. These networks are composed of distributed autonomous low cost nodes (also known as motes) with their own processing unit, memory and communications. Usually these nodes are power-limited and due to the poor performance and quality of their clocks, time synchronization is in the order of milliseconds and in some specific scenarios till microseconds. The integration of commercial UWB transceivers in these nodes can improve the synchronization accuracy. In particular, we focus on WSN nodes based on off-the-shelf commercial products and commodity hardware. In this paper we analyze step by step, from a practical and experimental point of view, the different elements involved in the time synchronization using UWB technology on WSN with static nodes. From our experimental results, with timestamps captured during the packet exchanges, we analyze and discuss the application of different communication schemes and simple statistical methods (in order to be run in WSN nodes). The results obtained with timestamps captured at the UWB transceivers and by using linear regression show that the lowest time synchronization error achieved between two nodes is 0.14 ns. Employing the same setup and performing the synchronization with the timestamps captured internally at the microcontrollers of the nodes, the error rises to 31 ns, due to the higher time period of the microcontrollers’ timers and the inaccuracies that affect the acquisition of the timestamps. Nevertheless, the synchronization of the microcontrollers’ clocks allows the setting up of a common time reference at the network nodes, enabling the implementation of applications with tight synchronization requirements, such as collaborative beamforming and ranging.

Environmental noise monitoring for smart cities need to be as much efficient as possible in order to mitigate its significant impact in the health of their inhabitants. 5G Internet of Things (IoT) systems offer a big opportunity to offload the computation from the sensor nodes, since it provides a series of new concepts for dynamic computing that the previous technologies did not offer. In this article, a complete 5G IoT system for psycho-acoustic monitoring has been designed and implemented using different options for offloading computation to different parts of the system. This offloading has been done by developing different functional splittings of the psycho-acoustic metrics algorithms to allocate such splits in different locations. Finally, a performance comparison among different functional splittings and their implementation are shown with a detailed discussion.

Traffic surveillance is an important issue for Intelligent Transportation Systems (ITS) that helps detect incidents automatically, such as wrong-way drivers, still-standing vehicles and jams. Sometimes these systems require a fast and short-term deployment of video cameras. In these cases, ad-hoc networks could be a low-cost and feasible option, but they have poor performance for video delivery. Thus, we propose a smart live video adaptive streaming technique in order to transport video streams from the cameras to the external road traffic monitoring servers. To achieve this goal, these networks need a thorough study in order to analyze video quality under their inherent constraints, given by their specific topologies (once deployed), video streaming protocol, nodes’ performance and routing protocols. From our results both in simulated and real scenarios, we demonstrate the feasibility of our proposal in these specific scenarios, validated with several performance metrics in terms of Quality of Service and video quality.

Sensor networks have become an extremely useful tool for monitoring and analysing many aspects of our daily lives. Noise pollution levels are very important today, especially in cities where the number of inhabitants and disturbing sounds are constantly increasing. Psycho-acoustic parameters are a fundamental tool for assessing the degree of discomfort produced by different sounds and, combined with wireless acoustic sensor networks (WASNs), could enable, for example, the efficient implementation of acoustic discomfort maps within smart cities. However, the continuous monitoring of psycho-acoustic parameters to create time-dependent discomfort maps requires a high computational demand that prevents real-time computations within the nodes. Moreover, sending audio streams outside of the WASN for their further computation, would require extra communication and computational efforts without warranting a real-time monitoring, with the added problem of violating some privacy laws. As a result, most existing systems for nuisance assessment are usually based on less accurate indicators that require lower computational cost. In this paper, we describe the design and analysis of a deep convolutional neural network (CNN) trained with a big dataset of typical sounds occurrying in a city. The CNN allows to predict the psycho-acoustic parameters considered by the well-known Zwicker’s psycho-acoustic nuisance model with great accuracy, directly from the raw recorded audio signal. The proposed CNN-based system has been tested on both desktop computers and typical WASN devices (such as Raspberry Pi), achieving very fast calculation times that allow real-time operation and a continuous monitoring of psycho-acoustic parameters.

Soundscape standard (ISO 12913) is mainly oriented to describe the psychoacoustic annoyance (PA) due to the perceived sound in different environments. The evaluation of this annoyance is commonly based on the Zwicker and Fastl model that defines several components related to this subjective annoyance, such as loudness, sharpness, roughness, and fluctuation strength. But due to their complexity, these components are difficult to be calculated on small board computers (SBCs) in real time in order to enable a wireless acoustic sensor network for PA monitoring. In this article, we describe the necessary procedures to implement the complete psychoacoustic model by Zwicker and Fastl in a precise and efficient way, keeping the standards and criteria defined for each model, adding hints to improve its performance. We evaluate their execution time on different platforms and languages, including SBCs, in particular on Raspberry Pi family. Thus, this article shows a feasible implementation of this monitoring approach on low-cost platforms as well as a visualization tool.

Urban parks constitute one of the main leisure areas, especially for the most vulnerable people in our society, children, and the elderly. Contact with soils can pose a health risk. Microbiological testing is a key aspect in determining whether they are suitable for public use. The aim of this work is to map the spatial distribution of potential dangerous Enterobacteria but also bioremediation useful (lipase producers) isolates from soils in an urban park in the area of Valencia (Spain). To this end, our team has collected 25 samples of soil and isolated 500 microorganisms, using a mobile application to collect information of the soil samples (i.e. soil features, temperature, humidity, etc.) with geolocation. A combined protocol including matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and 16S rDNA sequencing PCR has been established to characterize the isolates. The results have been processed using spatial statistical techniques (using Kriging method), taking into account the number of isolated strains, also proving the reactivity against standard pathogenic bacterial strains (Escherichia coli, Bacillus cereus, Salmonella, Pseudomonas and Staphylococcus aureus), and have increased the number of samples (to 896 samples) by interpolating spatially each parameter with this statistical method. The combined use of methods from biology and computer science allows the quality of the soil in urban parks to be predicted in an agile way, which can generate confidence in its use by citizens.

[ES] La innovación educativa es un proceso que se extiende más allá de un curso académico. En su desarrollo se distinguen las etapas de planificación, implementación, evaluación y realimentación, para identificar aspectos susceptibles de mejora. En esta contribución presentamos el trabajo desarrollado en los dos últimos cursos en la asignatura Teoría de la Comunicación (materia de Comunicaciones Digitales), Grado en Ingeniería Telemática, de la Universitat de València. Concretamente, se incorporan dispositivos de radio definida por software en los laboratorios como herramienta para conseguir unas prácticas más realistas. El artículo describe el proceso de adaptación de una sesión de laboratorio, que inicialmente fue desarrollada por un grupo piloto reducido en el curso 2018-2019, para un grupo experimental de laboratorio en el curso 2019-2020. Para evaluar el impacto de la innovación se cuantifica la implicación del alumnado, comparando los resultados del grupo experimental con respecto a dos grupos de control que han continuado con las sesiones simuladas estándar. Los resultados indican que el impacto ha sido positivo en la capacidad de los estudiantes para afrontar nuevos retos y en su percepción de la relevancia de las actividades que realizan, aunque esta mejora no se refleje en su capacidad de centrarse en ellas., [EN] Educational innovation is a process that extends beyond an academic year. In its development, the stages of planning, implementation, evaluation and feedback are distinguished in order to identify aspects that could be improved. In this contribution, we present the work developed over the last two years in the subject Communication Theory (Digital Communications), Degree in Telematic Engineering, from the University of Valencia. Specifically, software defined radio devices have been incorporated in the laboratories as a tool to bring students closer to more realistic practices. The paper describes the adaptation process of a laboratory session, which was initially developed by a small pilot group in the academic year 2018-2019, for an experimental laboratory group in the academic year 2019-2020. In order to evaluate the impact of the innovation, the involvement of the students is quantified, comparing the results of the experimental group with two control groups that have continued with the standard simulated sessions. The results indicate that the impact has been positive on the students’ ability to face new challenges and on their perception of the relevance of the activities they carry out, although this improvement is not reflected in their ability to focus on them.

Nowadays, the use of virtual reality/virtual acoustics (VR/VA) in archaeology for rendering lost buildings is an important topic in the cultural heritage field. Moreover, the addition of additional senses apart from the sight increases the feeling of immersion in virtual environments. The aim of this paper is to show the interaction work developed in a VA system, based on Unity and FMOD, the graphical and acoustical reconstruction of an ancient building and the development of a VR goggles with headphones to render 3D audio and video interactively. This system has been implemented to render auralizations in a binaural system and has been applied to the renderization of an old and lost theatre in València (Spain). The first building of theatre was built in the 16th century, and was rebuilt several times until the 18th century. The auralization of several theatrical excerpts of different Spanish authors of that time is also presented. The integrated system has been subjectively evaluated, obtaining very satisfactory results.

In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, we study the application of a WASN for room acoustic measurements. To evaluate the acoustic characteristics, a set of Raspberry Pi 3 (RPi) has been used. One is used to play different acoustic signals and four are used to record at different points in the room simultaneously. The signals are sent wirelessly to a computer connected to a server, where using MATLAB we calculate both the impulse response (IR), and different acoustic parameters, such as the Speech Intelligibility Index (SII). In this way, the evaluation of room acoustic parameters with asynchronous IR measurements two different applications has been explored. Finally, the network features have been evaluated to assess the effectiveness of this system.