5G in airports: challenges and use cases.

5G is the new generation of cellular communications that aims to provide high-throughput high-reliability connectivity to greatly diversified scenarios. With this objective, it shall act as a viable solution for environments as complex as an airport terminal, whose daily work cycle includes a wide range of diversified activities. As such, in this paper, 5G capacities are assessed, identifying those airport processes that can benefit from its application. From the proposed use cases, the monitoring of luggage trolleys is identified as a key use case that poses a problematic that is usually approached in a very inefficient way, due to the lack of information about the position and state of the trolleys. In this sense, a management system for the luggage trolleys using NarrowBand Internet of Things (NB-IoT) and Bluetooth Low Energy (BLE) is proposed.This work has been partially funded by: Junta de Andalucía and EDRF in the framework of 5G-SCARF: 5G Smart Communications for the AiRport of the Future (Ref. UMACEIATECH- 17) project, Ministerio de Asuntos Económicos y Transformación Digital and European Union – NextGenerationEU within the framework “Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia” under the project MAORI and Universidad de Málaga through the “II Plan Propio de Investigación, Transferencia y Divulgación Científica”. The authors are grateful to Aertec Solutions’ Airport Area for their support and collaboration in this work

Sistema IoT de sensorización, almacenamiento y representación de datos para espacios universitarios

In the past years, the concept of Smart City has been a main paradigm for public developments, with the objective of improving the well-being of the citizens, and the performance of public services by means of a detailed monitoring and actions over the different parameters associated to them. Among these monitoring, environmental measurements related with air quality and such are needed. The university campuses, as relevant areas with high concentration of people and infrastructure, as well as centers for education, research and innovation, are perfect areas for the adoption and testing of several projects of this kind. In this way, the present paper presents the ICT design and development of the SmartTree project in which a public infrastructure will be created with capacities such as providing clean energy and gathering environmental data in an integrated way.Este trabajo ha sido realizado dentro de la iniciativa Smart- Campus de la universidad de Málaga, en colaboración con el resto del equipo de desarrollo del proyecto Smart Trees financiado por el I Plan Propio de Smart-Campus de la Universidad de Málaga y por la Universidad de Málaga a través del I Plan Propio de Investigación y Transferencia. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Close detection robotic platform for Search And Rescue missions based on Bluetooth Low Energy

Improvements in telecommunications and digitalization directly improve the efficacy of a wide variety of processes. Recently, detection systems have received considerable attention because of the importance of tracking infected people contacts during SARS-CoV-2 pandemic. Such implementations can be useful in the task of finding potential victims in the context of emergency response, especially in situations where GPS is not available or inspection by imaging is not practical. Radio signals come into play, and specifically from devices that transmit periodically and with low power consumption. With the rise of Internet of Things over the last years, the number of wearable devices that support BLE, such as smartbands, smartwatches or smartphones, has been increasing constantly, as well as the number of users that carry them. Those devices can provide considerable assistance in locating injured or unconscious people. This work presents a system for detecting victims by means of a terrestrial search and rescue (SAR) robot. A real implementation of a close detection robotic platform based on BLE for SAR interventions is laid out. To estimate the distance between a robotic agent and potential victims within an experimental area, a Log-distance path loss model is presented. The proposed scheme has been tested in realistic scenarios during SAR exercises.This work was partially funded by the Spanish project RTI2018-093421-B-I00. It has been also performed in the framework of the Horizon 2020 project LOCUS (ICT-871249) receiving funds from the European Union. This work has been also partially funded by Junta de Andalucía and ERDF projects: Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Proyecto de Excelencia PENTA, P18-FR-4647; postdoctoral grant (Ref., DOC 01154, “selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020) and the I Plan Propio de Investigación, Transferencia y Divulgación Científica of the University of Málaga. The authors want to thank the collaboration of the Chair for Safety, Emergencies and Disasters of the University of Malaga, led by Prof. Jesús Miranda, as well as Javier Serón Barba for his support during the experiments. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Sistema de detección cercana para misiones SAR basado en BLE y sistemas robóticos

Detection systems have recently received considerable attention because of the importance of tracking infected people during SARS-CoV-2 pandemic. Such implementations can be very useful for finding potential victims in the context of emergency response, especially in situations where GPS is not available for inspection by imaging is not practical. Radio signals come into play, and specifically from devices that transmit periodically and with low power consumption. With the rise of Internet of Things and the plethora of wearable devices used in everyday life, like a smartphone, Bluetooth Low Energy (BLE) can provide considerable assistance in locating lost people. This work presents a system for detecting victims in a non-structured environment, by means of a search and rescue (SAR) robot. A real implementation of a close detection robotic platform based on BLE for SAR interventions is laid out. In order to estimate the distance between a robotic agent and potential victims within an experimental area, a Log-distance path loss model is presented, which has been tuned to detect beacons with reasonable accuracy within a range of 25 meters in rugged environments. The proposed scheme has been tested in realistic scenarios during SAR exercises.Los autores quieren agradecer la colaboración de la Cátedra de Seguridad, Emergencias y Catástrofes de la Universidad de Málaga, dirigida por el profesor Jesús Miranda, así como a Javier Serón Barba por su apoyo durante los experimentos. Este trabajo ha sido parcialmente subvencionado por el proyecto RTI2018-093421-B-I00. Se ha realizado en el cuadro del proyecto Horizonte 2020 proyecto LOCUS (ICT-871249) recibiendo fondos de la UE. Este trabajo también ha sido parcialmente subvencionado por la Junta de Andalucía y el ERDF (Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Proyecto de Excelencia PENTA, P18-FR-4647). Este trabajo ha sido parcialmente financiado por la Junta de Andalucía y el ERDF en el marco del proyecto 5G-SCARF - 5G Smart Communications for the AiRport of the Future (Ref. UMA-CEIATECH-17, “Proyecto singular de actuaciones de transferencia del conocimiento Campus Excelencia Internacional Andalucía TECH. Ecosistema innovador con inteligencia artificial para Andalucía 2025”). Finalmente, al I Plan Propio de Investigación y Transferencia de Universidad de Málaga. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Análisis y clasificación automática de anomalías de red mediante análisis multiresolución y métodos no supervisados

Cellular networks have been increasing in size and complexity constantly since the earliest generations. This growing complexity makes it harder for network operators to manage and improve the efficiency of the network while maximizing the quality of experience (QoE) of its users. As a way to ease the management of such complex networks, self-healing and automatic network-optimization methods have been developed over the years. Implementation of this methods made networks capable of troubleshooting problems previously identified by network experts, reducing the work effort required to maintain a high QoE. To automatically identify these network problems, unsupervised classification techniques have been put to use, since the amount of labelled data required for supervised techniques is not always available or complete. This paper proposes a method based on multi-resolution analysis and clustering for the detection and identification of anomalies in cellular networks through different Key-Performance Indicators (KPIs).Este trabajo ha sido parcialmente financiado por la Universidad de Málaga a traves del II Plan Propio de Investigación y Transferencia de la Universidad de Málaga. Ha recibido fondos del contrato con referencia Ref.- 8.06/5.59.5705 -3 IDEA, “Desarrollo de casos de uso para el diseño, optimización y dimensionado de redes móviles - Líneas B1 y D1”, en el marco de los incentivos de la Agencia IDEA. Así como mediante la beca postdoctoral (Ref., DOC 01154, “Selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020) y el proyecto MAORI del Ministerio de Asuntos Económicos y Transformación Digital y la Unión Europea - NextGenerationEU, en el marco del Plan de Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia

Sistema IoT para la monitorización de gases contaminantes en pila de compost.

Pollution is a significant environmental issue that continues to have profound effects on human health and the planet’s ecosystems. One notable source of pollution is greenhouse gas emissions, which contribute to global climate change. Composting, a popular method of organic waste management, has the potential to reduce pollution by diverting waste from landfills and producing a nutrient-rich soil amendment. However, the environmental impact of composting is not well understood, particularly in terms of greenhouse gas emissions. This article proposes an IoT system to monitor the data of different greenhouse gases, temperature, and humidity of a compost pile to know the carbon footprint during the composting process and even reduce it by modifying the process thanks to real-time monitoring of the parameters of interest.Este trabajo ha sido realizado dentro de la iniciativa Smart- Campus de la Universidad de Málaga, colaboración con el resto del equipo de desarrollo del proyecto UMA Composta financiado por el II Plan Propio de Smart-Campus de la Universidad de Málaga. Los autores agradecen la labor de los demás miembros de los grupos de investigación parte de este proyecto. También ha sido parcialmente financiado a través del II Plan Propio de Investigación y Transferencia de la Universidad de Málaga

Identificación de la relevancia de métricas celulares en clústeres no supervisados

The increase in the size and complexity of the cellular network is progressively complicating the operation and maintenance activities, as well as rising its operation cost. The growing complexity of the networks makes them more prone to failures, which can degrade the quality of experience (QoE) of the network users. In this way, to prevent the degradation of QoE, network operators are focusing on creating networks with self-healing functions, which are capable of automatically troubleshooting problems, making them more reliable and reducing their operation costs. For this matter, unsupervised Machine Learning (ML) algorithms are deployed to detect anomalous network status, however, these frequently lack explanation and network experts are required for this step. For this matter, the proposed paper presents a method to determine the relevant Key-Performance Indicators for any unsupervised clustering to facilitate the explanation of the clusters.Este trabajo ha sido parcialmente financiado recibiendo fondos del contrato con referencia Ref.- 8.06/5.59.5705 -3 IDEA, “Desarrollo de casos de uso para el diseño, optimización y dimensionado de redes móviles - Líneas B1 y D1”, en el marco de los incentivos de la Agencia IDEA, y el proyecto MAORI (Real Decreto 1040/2021, de 23 de noviembre) del Ministerio de Asuntos Económicos y Transformación Digital y la Unión Europea - NextGenerationEU, en el marco del Plan de Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia. Así como mediante la beca postdoctoral (Ref., DOC 01154, “Selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020), y por la Universidad de Málaga a través del II Plan Propio de Investigación y Transferencia de la Universidad de Málaga

Transform-based Multiresolution Decomposition for Unsupervised Learning and Data Clustering of Cellular Network Behaviour.

The growing complexity of cellular networks makes it harder for network operators to monitor and manage the system. To ease the management and automatically detect network problems, unsupervised techniques have been put to use. This work proposes a novel method that combines Multi-Resolution Analysis (MRA) by wavelet transforms and unsupervised clustering for the totally unsupervised grouping of cellular network behaviours through different Key-Performance Indicator (KPI)s. The application of multi-resolution decomposition, allows the much simpler clustering technique to take into account temporal information that would require of a much complex method otherwise. The proposed approach has been tested with real network data successfully separating different behaviours.</p

Smart Tree: An Architectural, Greening and ICT Multidisciplinary Approach to Smart Campus Environments

At present, climate change, pollution, and uncontrolled urbanism threaten not only natural ecosystems, but also the urban environment. Approaches to mitigate these challenges and able to provide an alternative for the use of the space are deemed to be multidisciplinary, combining architecture, vegetation integration, circular economy and information and communications technologies (ICT). University campuses are a key scenario to evaluate such solutions as their student and research community is intrinsically willing to support these experiences and provide a wide knowledge on the fields necessary for their design and implementation. However, the creation of areas combining usability and sustainability is commonly lacking a multidisciplinary approach combining all these different perspectives. Hence, the present work aims to overcome this limitation by the development of a novel integrated approach for campus spaces for co-working and leisure, namely a “Smart Tree”, where novel architecture, furniture design, flora integration, environmental sensoring and communications join together. To this end, a survey of the literature is provided, covering related approaches as well as general principles behind them. From this, the general requirements and constraints for the development of the Smart Tree area are identified, establishing the main interactions between the architecture, greening and ICT perspectives. Such requirements guide the proposed system design and implementation, whose impact on the environment is analyzed. Finally, the research challenges and lessons learned for their development are identified in order to support future works

Smart trees. Reusing UMA´s waste: un árbol biotecnológico para mejorar entornos docentes universitarios y ofrecer servicios conectivos

Resumen en inglés: At present, climate change will affect not only natural ecosystems, but also strongly threatens our urban environment, so mitigation work is necessary in our cities. Aware of this, the Smart Campus Vice-Rectorate of the University of Malaga (UMA) is working to make its Campus more environmentally friendly, sustainable, more technological, healthier and friendlier. Within this idea, the project presented here, framed within SDG 13 (Climate Action) is called “Smart-tree”. This is aimed at creating a relaxed and friendly co-working space, where nature (mainly plants) provides a microclimate of environmental and sensory comfort, and access technology to renewable energy and information is able. At the same time, the space is also intended to generate a friendly green atmosphere of leisure and recreation. It is widely known and proven that the benefits provided by green spaces to citizens are multiple: reduction of noise pollution, increase in evapotranspiration, decrease in wind when making a barrier effect, increase in the biodiversity of the area and increase in perceptual and sensory quality (landscape, environmental, aesthetic and aromatic qualities). The development of the project is being carried out by an interdisciplinary group of professors from the university knowledge areas of Architecture, Communications Engineering, Industrial Engineering Design and Botany, as well as students (through the elaboration of their final degrees works and final projects of Master) in the surroundings of the Teatinos Campus of the UMA (Malaga city, Spain). The structure of the Smart-Tree and its furniture have been designed to be built, based on the “re-using” of campus materials that have exhausted their first useful life (circular economy). For this, a catalogue of obsolete materials has been made, from both the different centres and the warehouses that the UMA has available and where there is material that can be used again. Therefore, it is possible to increase the life cycle of the products and decrease the use of new resources, achieving eco-efficiency in an nZEB (“Nearly Zero Energy Buildings”) prototype. In order to create the space and therefore provide it with plants that generate a new environmental and sensory microclimate, a proposal based on the use of primarily native flora has been developed and also considering the water requirement, maintenance needs, functionality, moments were flowering occurs and the ability to fix carbon. Taking all this into account, and through the use of Geographic Information Systems (GIS), the design of the most optimal nature tuning of the structure and surrounding area has been developed. The Smart-Tree also belongs to the IoT (Internet Of Things) and Smart-Campus paradigms, with the aim of apply the potential of Information and Communication Technologies (ICT) to monitor and guide its management in an efficient and ecological way. In this way, the necessary mechanisms for the monitoring of various environmental and energy variables through a near-range IoT system have been established in the Smart-Tree. This system has been designed based on the modification and appropriate hardware for the measurement of the desired variables and a system that allows the visualization of this information obtained in a web address. A small photovoltaic solar installation has also been defined in line with the nature of the project, which will provide infrastructure users with access to clean and sustainable electricity, in addition to meeting the energy needs of the aforementioned data collection system. As a result, the Smart-Tree space is being built in the environment of the Faculty of Sciences of the UMA, under the environmental and sustainability premises pursued. Specifically, the space has been located in the NW area of the Faculty, next to the Central Research Support Services (SCAI) and is in the assembly phase.En la actualidad, el cambio climático amenaza no sólo a los ecosistemas naturales, también a nuestro entorno urbano, por lo que se hace necesaria una labor de mitigación de éste en las ciudades. Conscientes de ello, desde la UMA se está trabajando por hacer un Campus más sostenible, más saludable y más tecnológico. Dentro de esa idea, surge el proyecto presentado, enmarcado dentro del ODS 13 denominado como “SMART-TREE”. Éste tiene por objetivo la creación de un espacio de “co-working”, que aporte un microclima de confort ambiental y sensorial, y la tecnología de acceso a las energías renovables y a la información. A la vez, también se pretende que el espacio contenga una atmósfera verde (fundamentalmente a base de plantas). El espacio se está ejecutando en el entorno de la Facultad de ciencias de la UMA y está siendo construido a través de materiales reutilizados (economía circular). El espacio está siendo naturado, dotándolo de plantas que generen un nuevo microclima ambiental y sensorial. Se ha elaborado una propuesta basada en la utilización de flora fundamentalmente autóctona y se atendió al requerimiento hídrico, las necesidades de mantenimiento, la funcionalidad, los momentos de floración. También se está dotando de toda la teconología TIC necesaria dentro de los despliegues de IoT (Internet Of Things) y Smart-Campus, con el objetivo de aprovechar las potencialidades TIC para monitorizar y guiar la gestión del mismo de un modo eficiente y ecológico. Este sistema ha sido diseñado partiendo de la determinación y hardware adecuado para la medición de las variables deseadas y un sistema que permite la visualización de esta información obtenida en una dirección web. También se ha dimensionado una pequeña instalación solar fotovoltaica, que proporcionará a los usuarios de la infraestructura el acceso a energía eléctrica limpia y sostenible, además de satisfacer las necesidades energéticas del sistema de toma de datos.Ayuda del Plan Propio de Investigación de la UMA: va a servir para justificar su solicitud, debe incluir en este campo: Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech