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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.

Urban parks are a rich source of microbial diversity, as they are heavily used by city residents. In this study, we sampled a Mediterranean park and were able to isolate bacteria that have the ability to inhibit the growth of control microorganisms. Out of the 560 bacteria we tested, many displayed antibacterial activity, particularly against Salmonella sp. and K. pneumoniae. These results suggest that the microorganisms in the park are in close proximity to the human population. Additionally, the isolated bacteria demonstrated diverse enzymatic activities, possibly as a response to the environmental substances available to them, which could aid in the degradation of different compounds of interest. The study of the spatial distribution of soil parameters and the inhibition against relative-safe pathogens in an urban park in València (Spain) demonstrated a higher proportion of isolates in certain areas. These spatial data maps can help researchers understand the behaviors of bacterial populations on a regional level, which can assist in the creation of novel antimicrobial agents and promote advancements in public health.

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.

Aquaponic health is a very important in the food industry field, as currently there is a huge amount of fishing farms, and the demands are growing in the whole world. This work examines the process of developing an innovative aquaponics health monitoring system that incorporates high-tech back-end innovation sensors to examine fish and crop health and a data analytics framework with a low-tech front-end approach to feedback actions to farmers. The developed system improves the state-of-the-art in terms of aquaponics life cycle monitoring metrics and communication technologies, and the energy consumption has been reduced to make a sustainable system.

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.

In educational context, a source of nuisance for students is carbon dioxide ($$CO_2$$ C O 2 ) concentration due to closed rooms and lack of ventilation or circulatory air. Also, in the pandemic context, ventilation in indoor environments has been proven as a good tool to control the COVID-19 infections. In this work, it is presented a low cost IoT-based open-hardware and open-software monitoring system to control ventilation, by measuring carbon dioxide ($$CO_2$$ C O 2 ), temperature and relative humidity. This system provides also support for automatic updating, auto-self calibration and adds some Cloud and Edge offloading of computational features for mapping functionalities. From the tests carried out, it is observed a good performance in terms of functionality, battery durability, compared to other measuring devices, more expensive than our proposal.

Las comunicaciones digitales se enseñan tradicionalmente en sesiones de laboratorio desde un punto de vista teórico, utilizando plataformas de simulación. Sin embargo, el sistema de Acreditación Académica incluye la dimensión de "lo que se espera que los estudiantes sean capaces de hacer", lo que plantea la necesidad de disminuir la brecha entre las sesiones de laboratorio simuladas y un enfoque más práctico y realista. En este trabajo, proponemos una metodología para mejorar el aprendizaje de los aspectos prácticos relacionados con los cursos de Comunicaciones Digitales, así como para aumentar la motivación de los estudiantes, mediante el uso de dispositivos de radio definida por software de bajo coste. Esta metodología se ha aplicado en el Grado en Ingeniería Telemática de la Escuela Técnica Superior de Ingeniería de la Universidad de Valencia, España. Con el objetivo de mejorar el compromiso de los estudiantes de máster y de grado, se ha implementado una metodología de aprendizaje basado en proyectos. En el trabajo se describe la metodología, se describen varias actividades de laboratorio basadas en el estándar 802.11 y se dan recomendaciones para la implementación de esta metodología. UV-SFPIE PID-1353656 Digital Communications have been traditionally taught in laboratory sessions from a theoretical point of view, using simulation platforms. However, current Academic Accreditation includes the dimension of “what students are expected to be able to do”, which poses the need of decreasing the gap between standard simulated laboratory sessions and more practical and realistic approaches. In this paper, we propose a methodology to enhance the learning of practical aspects related to Digital Communications courses, as well as increasing the student’s engagement, via the use of low-cost software defined radio devices. This methodology has been applied in the Degree in Telematics Engineering at the School of Engineering from the University of Valencia, Spain. With the aim of improving the engagement of both master and undergraduate students, a project based learning methodology has been implemented. In the paper, the methodology is described, several laboratory activities based on the 802.11 standard are presented, and recommendations for practice are given.

The emergence of pathogenic bacteria that are multi-resistant to antibiotics lurks in today's society. In the golden age of the discovery of new antibiotic-producing microorganisms, each contribution was a step forward, but currently the progression is no longer so spectacular. The probability of finding new microorganisms and different antibiotics is lower and lower. The use of spatial statistical methods such as the Kriging technique has been shown to be suitable for this purpose, allowing us to determine areas with greater possibilities of locating these microorganisms. For a practical approach of our estimations, a total of 12 isolates capable of inhibiting the growth of several control strains (Escherichia coli, Bacillus cereus and at least one other) were analyzed. The isolates were preliminarily characterized, and subsequently identified at the species level by DNA sequence analyses (16S rDNA PCR) and protein analyses (MALDI-TOF MS). However, between soil pH values and the number of isolates capable of inhibiting the control strains. Geospatial mapping with RStudio software provide a satisfactory predictive tool for isolation of new microbial isolates.

[EN] The acoustic evaluation of indoor environments is common in the application of virtual acoustics. In addition, in the study of cultural heritage buildings, it is a useful tool, but it is not so common when describing the acoustic environment in intangible cultural heritage events and even in outdoor environments. In this paper, the acoustic environment of the Water Tribunal of the Plain of Valencia (Spain) is studied. It is analyzed from a soundscape perspective, characterizing the sound source and evaluating it within relation to the environment and evaluating its subjective response. With the research carried out, it has been obtained, on the one hand, a complete study of the acoustics of the environment of the Water Tribunal and, on the other, an enhancement of the Valencian tangible and intangible heritage., This research was partially funded by Spanish Ministry of Science, Innovation and Universities, grant number BIA2016-76957-C3-3-R and by the Universitat de Valencia with the grant UV-INV-AE-1550319.

The proliferation of commercial low-cost Small Board Computers (SBC) devices have allowed the deployment of many Wireless Sensor Networks (WSN) focused on different applications, mainly based on monitoring issues. These networks are characterized by a set of these SBCs devices working in a collaborative way where each device is sensing, processing and later sending out the data to the sink. These devices are equipped with power supply, a processing unit and communications capabilities (in particular WiFi), making themselves very interesting to fit in many topologies. However, their performance in terms of communications basically depends on the environment and usually heuristic techniques are used with any guarantee if they will succeed or not. To model the different scenarios there are theoretically several approaches, such as ray tracing technique, two-ray, as well as semi-empirical models, but it should be interesting to analyze them also from a experimental point of view. In this paper we carry out a thorough performance analysis, in particular using Raspberry Pi3 (RPi3) devices, in order to understand their behavior in terms of Quality of Services (throughput, delay, losses and jitter (delay variation) for different types of communications: indoor and outdoor environments, with and without multipath reflections in order to establish precisely the amount of signal required depending on the required througput. In the outdoor environments, we analyze the QoS over the links between two nodes in a deployment.We conclude that using this type of devices we can achieve a throughput of more than 45 Mbps in indoor within distances shorter than 50 m and 40 Mbps in outdoor till 100 m and then it starts decaying till 300 m in normal conditions.

Wireless sensor networks (WSN) are groups of small devices that contain a microcontroller in which a large number of sensors can be added. They transmit data and communicate to each other in the ISM band, standard IEEE 802.15.4, exchanging packets using a multi-hop routing. These devices are named motes and are nodes of the WSN. They are very simple and easy to program, powered by batteries of 1.5Volts (AA and AAA). The nodes are autonomous elements that can be deployed implementing any type of network. In a typical deployment the nodes communicate with each other and with a master node or Base Station (BS), which in turn transmits the information to an external server, which collects the environmental and any type of parameters collected by each sensor. WSNs are used in a multitude of military, industrial and civil applications. They use a very low amount of power, and this fact limits the maximum communication distance between motes within the WSN, which is around 50m for civil current motes. The Stochastic Collaborative Beamforming (SCB), was proposed as a way to overcome the low range. in which we take advantage of the synchronization errors of the clocks. In SCB, it is possible to obtain the adequate time delay that permits the interference or sufficient gain in the direction of the receiver. However the dimensions of the WSN deployment are so large as to consider the effects of the near field. WSN with 200m diameter have Fresnel areas ranging to distances as far as 325Km. In the present work we present the theoretical background to analyze the SCB transmission of a cluster of radiating motes, and also the theoretical planning for a SCB long range communication in the Albufera de Valencia natural reservation area, some preliminary simulations and measurements are also presented.

In Next-Generation Technologies, the monitoring of environmental noise nuisance in the Smart City should be as efficient as possible. 5G IoT systems offer a great opportunity to offload the node calculation, as they provide a number of new concepts for dynamic computing that previous technologies did not offer. In this case, a complete 5G IoT system for psycho-acoustic monitoring has been implemented using different options to offload the calculation of the parameters to different parts of the system. This offloading has been implemented by directly computing the metrics in the node (as a Raspberry Pi), and in a ESP32 device (FiPy) and by sampling the audio and sending it to the EDGE in the psycho-acoustic metrics algorithm in order to evaluate the performance of the system and has been compared with the calculation at the node itself.

Reducing energy consumption has become a hot research topic in the past few years. The concept of Green Networking is gaining popularity not only because of the growing environmental awareness worldwide but also the economic opportunities and benefits of reducing energy consumption in the ICT industry. In this work, we will identify the importance of green research and explore the state of the art in the field with a special focus on green base stations. After identifying the key green metrics, we will explore the energy efficiency of traditional base stations and review the main possible improvements to its current structure as a standalone unit as well as the base station as a component in a cellular network. We find that a substantial mitigation of CO2 emissions from 2.4% to 7% of total emissions could be achieved, where the use of renewable energies is economically and technically feasible.

This paper reports on the work being done towards achieving an immersive and accessible reconstruction of Historical and Cultural Heritage, focusing on Theaters of the Early Modern as use case. In particular, the paper presents and discusses potential possibilities to enable: 1) the acoustical reconstruction of the virtual (lost) environments – beyond the graphical reconstruction for the buildings, elements and performances; 2) effective interaction features and navigation within the virtual environment (e.g. by means of adaptive interfaces, guiding methods, insertion of Point of Interest); and 3) accessible experiences, by means of an innovative and personalized presentation modes for access services, like subtitles and audio description. For most of these aspects and features, proof of concept implementation are provided, and opportunities for future work are outlined. With an effective combination of all these contributions, the goal is to bring back valuable (both tangible and intangible) Cultural Heritage from the past, providing high benefits in relevant sectors like Culture, Tourism and Education.

Nowadays, more than 75% of Internet traffic is multimedia traffic, moreover mobile traffic is growing at a rate of 50% each year. All these data together with the evolution of the cloud infrastructures lead us to develop Cloud Mobile Media (CMM) architectures to support the needs demanded by end users. Nevertheless, due to an inherit higher and variable end to end delay mainly as a result of the virtualization process, new challenges appear in particular for live video streaming applications in order to keep a good Quality of Experience (QoE) of the delivered video. Thus, to keep client’s satisfaction within good levels in terms of Mean Opinion Score (MOS), we propose an adaptive QoE-based architecture running on CMM infrastructures for live streaming services. In order to carry out this goal, we propose an estimation of MOS values using an statistical method based on factor analysis. This estimation is based on different measured variables throughout the CMM infrastructure. In addition, we compare the accuracy of the estimated MOS against well-known publicly available video quality algorithms. With these estimations, our proposal is based on two added controllers to the CMM infrastructure: (a) the Software Defined Network controller that acts as a master and (b) the Media Streamer controller. Each one does different actions on the CMM infrastructure in order to maintain and improve the QoE at each end user. Finally, this architecture has been implemented over a fat tree topology in order to show their functionality. The results show that our proposal works properly and it adapts quickly to the network changes in order to deliver a good MOS.

Lightning and thunder are some of the most violent natural phenomena. They generate a great deal of expenditure and economic loss, especially when they strike in cities. The identification of the concrete geographic area where they strike is of critical importance for emergency services in order to enhance their effectiveness by doing an intensive coverage of the affected area. To achieve this purpose at the city scale, this paper proposes the design, prototype, and validation of a distributed network of Internet of Things (IoT) devices. The IoT devices are empowered with lightning detection capabilities and are synchronized with the other devices in the sensor network. All of them cooperate within a network that is able to locate different events thanks to a trilateration algorithm implemented in a big data environment. The designed low-cost lightning detection system is based on the AS3935 sensor. This system alone has a limited range of effective detection, but when it is embedded in an IoT mesh network, the accuracy and performance are increased. A fully operational IoT network was deployed, and a functional validation and empirical measurements are provided.

The Internet of Things (IoT) is a network widely used with the purpose of connecting almost everything, everywhere to the Internet. To cope with this goal, low cost nodes are being used, otherwise, it would be very expensive to expand so fast. These networks are set up with small distributed devices (nodes) that have a power supply, processing unit, memory, sensors, and wireless communications. In the market, we can find different alternatives for these devices, such as small board computers (SBCs), e.g., Raspberry Pi (RPi)), with different features. Usually these devices run a coarse version of a Linux operating system. Nevertheless, there are many scenarios that require enhanced computational power that these nodes alone are unable to provide. In this context, we need to introduce a kind of collaboration among the devices to overcome their constraints. We based our solution in a combination of clustering techniques (building a mesh network using their wireless capabilities), at the same time we try to orchestrate the resources in order to improve their processing capabilities in an elastic computing fashion. This paradigm is called fog computing on IoT. We propose in this paper the use of cloud computing technologies, such as Linux containers, based on Docker, and a container orchestration platform (COP) to run on the top of a cluster of these nodes, but adapted to the fog computing paradigm. Notice that these technologies are open source and developed for Linux operating system. As an example, in our results we show an IoT application for soundscape monitoring as a proof of concept that it will allow us to compare different alternatives in its design and implementation, in particular, with regard to the COP selection, between Docker Swarm and Kubernetes. We conclude that using and combining these techniques, we can improve the overall computation capabilities of these IoT nodes within a fog computing paradigm.

Current mobile service providers are offering Gigabit Internet access over LTE-Advanced networks. Traditional services, such as live video streaming, over wired networks are feasible on these networks. However different aspects should be taken into account due to the fast changing network conditions as well as the constrained resources of the mobile phones, in order to provide a good subjective video quality in terms of Mean Opinion Score (MOS). Our goal is to estimate and predict this subjective metric without information or reference from the original video, known as Non Reference approach. This approach is important for the Service Provider from a practical point of view, because it can keep the customer satisfaction at good levels. We analyze different estimation techniques running over a set of monitored variables throughout the whole steaming system, from the streaming server to the mobile phone. We have gathered variables related to bit stream, basic video quality metrics as well as Quality of Services variables. These variables are used to estimate MOS in a reliable and robust way. We compare three techniques such as Artificial Neural Networks (ANN), Factor Analysis (FA) and Multinomial Linear Regression, at different time scales and with Full Reference and Non Reference approaches. We carry out a performance evaluation of these techniques, concluding that the behavior of MOS estimation based on FA is more accurate, unless we had a lossless scenario related to Guaranteed Bit Rate services, where ANN performs better. The subjective video quality has been evaluated through surveys. Finally, we evaluate the accuracy of the estimated MOS against well known publicly available video quality algorithms following the recommendations given by Video Quality Experts Group (VQEG).

The adoption of smart phones, the increased access to mobile broadband networks and the availability of public cloud infrastructures are aligning to the next generation of truly ubiquitous multimedia services, known as Cloud Mobile Media (CMM) services offering mobile video. Nevertheless, due to an inherit higher and variable end to end delay mainly as a result of the virtualization process, new challenges appear. One challenge is given by live video streaming applications when trying to keep a good Quality of Experience of the delivered video, measured in terms of a subjective video quality metric, named Mean Opinion Score (MOS). Our goal is to estimate and predict this subjective metric in a holistic manner using different estimation techniques, such as Artificial Neural Networks, Factor Analysis and Multinomial Linear Regression, with Full Reference and Non Reference approaches. For this, we have analyzed and measured different variables related to Quality of Service, bit stream and basic video quality metrics, throughout the CMM infrastructure. With these variables, we apply the mentioned techniques which allows us to estimate MOS of the delivered video in a robust and reliable way, achieving an average estimation error between 0.46 and 15.94% depending on the technique used. The real MOS has been evaluated through surveys. Finally, we compare the accuracy of the estimated MOS against well known publicly available video quality algorithms, following the recommendations given by Video Quality Experts Group.

Current mobile networks are providing high speed access to Internet at a rate of Gigabits per second. In this scenario, traditional services over wired networks are an alternative, in particular those based on live video streaming. But in the transition, different issues should be considered due to the rapid changing network conditions and the limited resources of the mobile devices. These issues should be taken into account to keep a good Quality of Experience (QoE) of the video in terms of a high Mean Opinion Score (MOS), a subjective video quality. Our goal is to estimate and predict this subjective metric in a holistic manner. Thus, we have analyzed and measured different variables related to Quality of Service, bit stream and basic video quality metrics of live video streaming over LTE Advanced (4G) mobile networks, as well as server side. With these variables, we apply a statistical method, called Factor Analysis based on the correlation of the variables, which allows us to estimate MOS of the delivered video in a robust and reliable way, both in Full Reference and Non Reference approaches. The real MOS has been evaluated through surveys. Finally, we compare the accuracy of the estimated MOS for the different approaches and compare their performance with well known publicly available video quality algorithms.

Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor networks (WASNs) can be an interesting solution for monitoring subjective annoyance in certain soundscapes, since they can be used to register the evolution of such parameters in time and space. Unfortunately, the calculation of the psycho-acoustic parameters involved in common annoyance models implies a significant computational cost, and makes difficult the acquisition and transmission of these parameters at the nodes. As a result, monitoring psycho-acoustic annoyance becomes an expensive and inefficient task. This paper proposes the use of a deep convolutional neural network (CNN) trained on a large urban sound dataset capable of efficiently predicting psycho-acoustic annoyance from raw audio signals continuously. We evaluate the proposed regression model and compare the resulting computation times with the ones obtained by the conventional direct calculation approach. The results confirm that the proposed model based on CNN achieves high precision in predicting psycho-acoustic annoyance, predicting annoyance values with an average quadratic error of around 3%. It also achieves a very significant reduction in processing time, which is up to 300 times faster than direct calculation, making CNN designed a clear exponent to work in IoT devices.

In the last decade there has been an increasing interest and demand on the Internet of Things (IoT) and its applications. But, when a high level of computing and/or real time processing is required for these applications, different problems arise due to their requirements. In this context, low cost autonomous and distributed Small Board Computers (SBC) devices, with processing, storage capabilities and wireless communications can assist these IoT networks. Usually, these SBC devices run an operating system based on Linux. In this scenario, container-based technologies and fog computing are an interesting approach and both have led to a new paradigm in how devices cooperate, improving overall capacity in a cluster of these SBC devices. The use of containers is considered a lightweight virtualization, allowing an application to be broken into small tasks as services, enabling load balancing, flexibility and scalability. Nevertheless when the number of devices and containers increases in the cluster, it is required an orchestration layer. There are not many solutions and available alternatives using these technologies applied on these networks, and less an assessment of their performances. This paper focuses on these technologies when we use fog computing with low cost SBC devices in a context of IoT. We use Linux containers and different available orchestration platforms (in particular Docker Swarm and Kubernetes), to run on the top of the cluster of commercial SBC devices. Thus, we carry out a thorough functional and performance comparison with different real topologies (wired and wireless) and using both homogeneous and heterogeneous clusters of SBC devices, showing their results. We conclude that with the collected experimental results, Docker Swarm orchestration platform outperforms its counterparts in the scenarios shown.

The evaluation of QoS in mobile multipath environments is an interesting topic in modern communications. The use of Raspberry Pi as a low cost microcomputer board developed in the United Kingdom by the Raspberry Pi Foundation can be helpful in onsite deployments. The Pi3 model has integrated WiFi and Bluetooth connectivity and also 4 USB ports to expand the device with all kinds of peripheral. Under the premise of offering the power of a computer at low prices, this device is one of the most affordable ways to have a particularly efficient and dynamic hardware accessible at a low price to develop a Wireless Sensor Netwok (WSN). The use of the Raspberry Pi3 permits the development of a powerful and hight efficient mote in the development of a WSN, where data is highly processed in each mote and transmissions between motes and the sink or base station (BS) can be keep at minimum. We develop an experimental setup to analyse the quality of transmission between these devices in order to a further modelization of the channel. We program the Raspberry Pi3 to evaluate the quality of the transmission between two devices within a controlled multipath environment, particularly within an anechoic chamber.

Wireless Sensor Networks (WSNs) are composed of spatially distributed autonomous sensor devices, named motes. These devices are constituted by a microcontroller, sensors, and they have the ability to communicate in the ISM frequency band using the IEEE 802.15.4 standard. They have their own power supply, AA or AAA batteries, processing unit, sensors and wireless communications. Usually, the motes exchange packets using a multihop routing, and the maximum communication distance emitter-receiver is around 100m. At least one mote acts as a gateway, and the data gathered by the sensors of each mote have to be sent to this mote that is named sink or Base Station (BS). In a WSN the BS is within the area of the WSN in order to receive the information. The distance between the BS and the nearest mote must be at the most 100m to be able to receive the packets. If the BS distance is farther than this distance, the communication fails, because the motes have limited power. Some techniques are proposed to overcome this distance in order to achieve a long range communication to reach the BS, for instance to communicate to a low orbit satellite. The difficulties are related to synchronization errors in the clocks of the motes. We propose an alternative technique based in a collaborative beamforming scheme, named stochastic collaborative transmission or stochastic beamforming, in which we take advantage of the synchronization errors of the clocks to achieve a large gain in a limited number of trials.

eHealth systems provide medical support to users and contribute to the development of mobile and quality health care. They also provide results on the prevention and follow-up of diseases by monitoring health-status indicators and methodical data gathering in patients. Telematic management of health services by means of the Internet of Things provides immediate support and it is cheaper than conventional physical presence methods. Currently, wireless communications and sensor networks allow a person or group to be monitored remotely. The aim of this paper is to develop and assess a system for monitoring physiological parameters to be applied in different scenarios, such as health or sports. This system is based on a distributed architecture, where physiological data of a person are collected by several sensors, next, a Raspberry Pi joins the information and makes a standardization process, then, these data are sent to the Cloud to be processed. Our Cloud system stores the received data and makes a data fusion process in order to indicate the athlete&rsquo, s fatigue status at every moment. This system has been tested in collaboration with a small group of voluntary tri-athletes. A network simulation has been performed to plan a monitoring network for a bigger group of athletes. Finally, we have found that this system is useful for medium-term monitoring of the sports activities.

Exposure to extremely low frequency electromagnetic fields (ELFs) is almost inevitable almost anywhere in the world. An ELF magnetic field (ELF-MF) of around 1 mG = 0.1 &mu, T is typically measured in any home of the world with a certain degree of development and well-being. There is fear and concern about exposure to electromagnetic fields from high- and medium-voltage wiring and transformer stations, especially internal transformer stations (TSs), which in Spain are commonly located inside residential buildings on the ground floor. It is common for neighbors living near these stations to ask for stations to be moved away from their homes, and to ask for information about exposure levels and their effects. Municipality is the closest administration to the citizens that must solve this situation, mediating between the citizens, the utility companies and the national administration. In this case, the municipality of Silla (Val&egrave, ncia, Spain) wanted to know the levels of exposure in the dwellings annexed to the TSs, to compare them with Spanish legislation and the recommendations coming from epidemiological studies. This article presents the first systematic campaign of ELF-MF measurements from TSs carried out in a Spanish city. Many measurements were carried out in the rooms of the apartments doing spatial averages of spatial grid measurements. Measurements are made in the bed and bedrooms and a weighted average and an environmental impact indicator were obtained for each location. We found that old TSs usually provide the highest peak exposure levels. A notable result of this work is that approximately one quarter of the population living above or next to a TS would be exposed to a weighted MF level greater than 0.3 &mu, T, and that about a 10% of this population would not be able to relocate their bedroom or living room to minimize the level of exposure.

Sound pleasantness or annoyance perceived in urban soundscapes is a major concern in environmental acoustics. Binaural psychoacoustic parameters are helpful to describe generic acoustic environments, as it is stated within the ISO 12913 framework. In this paper, the application of a Wireless Acoustic Sensor Network (WASN) to evaluate the spatial distribution and the evolution of urban acoustic environments is described. Two experiments are presented using an indoor and an outdoor deployment of a WASN with several nodes using an Internet of Things (IoT) environment to collect audio data and calculate meaningful parameters such as the sound pressure level, binaural loudness and binaural sharpness. A chunk of audio is recorded in each node periodically with a microphone array and the binaural rendering is conducted by exploiting the estimated directional characteristics of the incoming sound by means of DOA estimation. Each node computes the parameters in a different location and sends the values to a cloud-based broker structure that allows spatial statistical analysis through Kriging techniques. A cross-validation analysis is also performed to confirm the usefulness of the proposed system. Ingeniería, Industria y Construcción

[ES] Hoy en día el tráfico de video de internetsignifica alrededor del 65-70% del tráfico total. Se prevéque en 2019 aumente hasta el 80%. Debido a esto se hacenecesario optimizar y mejorar las tecnologías relacionadascon la transmisión de video para garantizar una calidad deexperiencia adecuada. Es por ello que se están desarrollando nuevos protocolos de transmisión de videoadaptativos basados en DASH. Debido a que su uso estáaumentando en los últimos años para realizar streamingsobre HTTP. En este artículo presentamos la herramientaMediaDASH Tool, la cual es una aplicación web quepermite de manera muy intuitiva poder comprimir ypreparar videos para su difusión con DASH. Así como suposterior visualización a través de la misma plataforma.Esta herramienta puede ser de gran utilidad para usuariosfinales que quieran disponer de su sistema DASH comotambién para investigadores que quieran testear suscontenidos multimedia haciendo uso de estos protocolos., Este trabajo ha sido parcialmente subvencionado por la Universitat de València a través de los proyectos UVINV-PRECOMP14-207134, UV-INVAE15-339582, por la Generalitat Valenciana a través del proyecto GV2016-002 y por el Ministerio de Economía a través del proyecto BIA2016-76957-C3-1-R.

The application of the VR to the renderization of ancient and lost buildings is one important topic in the cultural heritage field nowadays. Moreover, the addition of other senses apart from the graphical view, increases the sensation of immersion in a virtual application. The aim of this paper is to show the work on a virtual acoustic system, based on Unity, FMOD and Csound. This system has been implemented to render binaural auralizations and has been applied to the renderization of an old and lost theatre in Valencia (Spain). This theatre was firstly build in the 16th century, and rebuilt several times until the 18th century. It has been modelled from ancient documents. The auralization of several theatrical excerpts of different Spanish authors of that time is also presented.

Although much work has been done since wireless sensor networks appeared, there is not a great deal of information available on real deployments that incorporate basic features associated with these networks, in particular multihop routing and long lifetimes features. In this article, an environmental monitoring application (Internet of Things oriented) is described, where temperature and relative humidity samples are taken by each mote at a rate of 2 samples/min and sent to a sink using multihop routing. Our goal is to analyse the different strategies to gather the information from the different motes in this context. The trade-offs between ‘sending always’ and ‘buffering locally’ approaches were analysed and validated experimentally, taking into account power consumption, lifetime, efficiency and reliability. When buffering locally, different options were considered such as saving in either local RAM or FLASH memory, as well different alternatives to reduce overhead with different packet sizes. The conclusion is that in terms of energy and durability, the best option is to reduce the overhead. Nevertheless, sending larger packets is not worthy when the probability of retransmission is high. If real-time monitoring is required, then sending always is better than buffering locally.

Noise pollution caused by vehicular traffic is a common problem in urban environments that has been shown to affect people's health and children's cognition. In the last decade, several studies have been conducted to assess this noise, by measuring the equivalent noise pressure level (called L eq ) to acquire an accurate sound map using wireless networks with acoustic sensors. However, even with similar values of L eq , people can feel the noise differently according to its frequency characteristics. Thus, indexes, which can express people's feelings by subjective measures, are required. In this paper, we analyze the suitability of using the psychoacoustic metrics given by the Zwicker's model, instead of just only considering L eq . The goal is to evaluate the hardware limitations of a low-cost wireless acoustic sensor network that is used to measure the annoyance, using two types of commercial and off-the-shelf sensor nodes, Tmote-Invent nodes and Raspberry Pi platforms. Moreover, to calculate the parameters using these platforms, different simplifications to the Zwicker's model based on the specific features of road traffic noise are proposed. To validate the different alternatives, the aforementioned nodes are tested in a traffic congested area of Valencia City in a vertical and horizontal network deployment. Based on the results, it is observed that the Raspberry Pi platforms are a feasible low-cost alternative to increase the spatial-temporal resolution, whereas Tmote-Invent nodes do not confirm their suitability due to their limited memory and calibration issues.

[ES] En la docencia de sistemas de comunicación hay una componente teórica elevada. La percepción de los estudiantes al estudiar estas asignaturas es negativa. Este trabajo trata de explicar la motivación y la estrategia seguida para reorientar esta percepción a partir de la introducción de elementos de “Software-Defined Radio” (SDR) y “Universal Software Radio Peripherals” (USRP) en diferentes asignaturas del Grado de Ingenier´ıa Telem´atica de la Universitat de València, Los autores quieren agradecer al Servei de Formació Permanent i Innovació Educativa - Centre de Formació i Qualitat "Manuel Sanchis Guarner" de la Universitat de València por la ayuda concedida para el soporte parcial de este proyecto de innovación docente (ref: UVSFPIE_RMD15-314373) y la Ministerio de Economía e Innovación por la ayuda con referencia TEC2013-47141-C4-4-R con la que se ha financiado parcialmente este trabajo.

[EN] We present the results from a measurementbasedperformance evaluation of wireless networks basedon IEEE 802.11ac standard in an indoor environment, withthe aim to analyze their performance under high definitionstreaming video applications. We focus our study on analyzingthe highest performance of these standards using off-theshelfequipment as well as the behavior of Quality of Servicevariables and how they affect to the video quality. Thus, wehave analyzed and measured these variables and have applieda multivariate statistical technique, called Factor Analysis,and finally discuss their behavior., This work was supported by the Universitat de Valencia under the projects UV-INV-PRECOMP14-207134, UVINVAE15-339582, by the Generalitat Valenciana under the project GV-2016-002 and by the Ministry of Economy under the project BIA2016-76957-C3-1-R

We present the results from a measurement-based performance evaluation of wireless networks based on IEEE 802.11n and IEEE 802.11ac standards in an indoor environment, with the aim to analyze their performance under high definition streaming video applications. We focus our study on analyzing the highest performance of these standards using off-the-shelf equipment, both with synthetic TCP and UDP traffic to measure the saturation throughput as well as high definition video streams. The measurements have been conducted in the student labs of our university and show good performance for streaming purposes in high definition and also ultra-high definition from a subjective video quality point of view. IEEE 802.11ac performance is very sensitive to the channel conditions. According to our experiments, these results heavily depend on the implementation of the IEEE 802.11ac standard of the commercial access points.

Recent studies about the use of cloud platforms indicate that more than three-fourths of healthcare institutions apply these technologies in their daily lives. However, in most cases the cloud is based on “Infrastructure as a Service”, instead of developing new applications using the benefits that can bring us this type of technology. For these reasons, this paper shows a private cloud-based system to provide a new application based on thermographic video streaming. In this case, the cloud architecture is divided into three zones. The first zone is where the patient is under medical supervision through body temperature analysis using a global thermal camera. The second zone is the cloud itself, where the video is encoded, but taking into account that the received video must ensure a correct measurement of the temperature. The third zone is the access network, where people or processes receive and analyze these videos. Finally, a performance evaluation using several video codecs and bitrates is done in order to see which one is more accurate and fits better medical requirements. Finally, we conclude that the system works properly, indicating which video codecs are more suitable for each scenario.