8 research outputs found
Table Organization Optimization in Schools for Preserving the Social Distance during the COVID-19 Pandemic
[EN] The COVID-19 pandemic has supposed a challenge for education. The school closures during the initial coronavirus outbreak for reducing the infections have promoted negative effects on children, such as the interruption of their normal social relationships or their necessary physical activity. Thus, most of the countries worldwide have considered as a priority the reopening of schools but imposing some rules for keeping safe places for the school lessons such as social distancing, wearing facemasks, hydroalcoholic gels or reducing the capacity in the indoor rooms. In Spain, the government has fixed a minimum distance of 1.5 m among the students’ desks for preserving the social distancing and schools have followed orthogonal and triangular mesh patterns for achieving valid table dispositions that meet the requirements. However, these patterns may not attain the best results for maximizing the distances among the tables. Therefore, in this paper, we introduce for the first time in the authors’ best knowledge a Genetic Algorithm (GA) for optimizing the disposition of the tables at schools during the coronavirus pandemic. We apply this GA in two real-application scenarios in which we find table dispositions that increase the distances among the tables by 19.33% and 10%, respectively, with regards to regular government patterns in these classrooms, thus fulfilling the main objectives of the paper.SIMinisterio de Ciencia, Innovación y Universidade
Hyperconnectivity Proposal for Smart Manufacturing
[EN] Smart Manufacturing is characterized by the digitization and massive communication of Cyber-Physical Systems under the Industrial Internet of Things paradigm. However, the heterogeneity of communication protocols hinders connectivity among assets due to lack of interoperability. Moreover, the decomposition of the classical production hierarchy towards decentralized self-organization makes the implementation of interoperability in industrial environments key to help decision-making. In this sense, the interoperability of heterogeneous assets (e.g., external, internal, and human) has been defined as hyperconnectivity and supposes a technological challenge in the scientific literature. To prove this novel hyperconnectivity definition, the authors propose and develop a novel hyperconnected demonstrator where all types of assets are interconnected in a case study consisting of the automation of an inspection process. For this purpose, an industrial internet platform has been used for connecting industrial equipment creating a collaborative environment through the use of interoperability. In this regard, it has been possible to communicate assets among the cloud, humans, and CPS with a processing time of less than 10 ms, which demonstrates that the technological challenge of implementing the hyperconnectivity concept of this paper has been successfully addressed.SIThis research has been developed and funded by the Spanish Ministry of Science and Innovation project grant number PID2019-108277GB-C21/AEI/10.13039/501100011033 and by the Universidad de León.Ministerio de Ciencia, Innovación y Universidade
Analysis of reliable deployment of TDOA local positioning architectures
.Local Positioning Systems (LPS) are supposing an attractive research topic over the last few years. LPS are ad-hoc deployments of wireless sensor networks for particularly adapt to the environment characteristics in harsh environments. Among LPS, those based on temporal measurements stand out for their trade-off among accuracy, robustness and costs. But, regardless the LPS architecture considered, an optimization of the sensor distribution is required for achieving competitive results. Recent studies have shown that under optimized node distributions, time-based LPS cumulate the bigger error bounds due to synchronization errors. Consequently, asynchronous architectures such as Asynchronous Time Difference of Arrival (A-TDOA) have been recently proposed. However, the A-TDOA architecture supposes the concentration of the time measurement in a single clock of a coordinator sensor making this architecture less versatile. In this paper, we present an optimization methodology for overcoming the drawbacks of the A-TDOA architecture in nominal and failure conditions with regards to the synchronous TDOA. Results show that this optimization strategy allows the reduction of the uncertainties in the target location by 79% and 89.5% and the enhancement of the convergence properties by 86% and 33% of the A-TDOA architecture with regards to the TDOA synchronous architecture in two different application scenarios. In addition, maximum convergence points are more easily found in the A-TDOA in both configurations concluding the benefits of this architecture in LPS high-demanded applicationS
Digital Twin for Automatic Transportation in Industry 4.0
[EN] Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper.SIMinisterio de Ciencia, Innovación y Universidade
Analysis of synchronous localization systems for UAVs urban applications
[EN] Unmanned-Aerial-Vehicles (UAVs) represent an active research topic over multiple fields for performing inspection, delivery and surveillance applications among other operations. However, achieving the utmost efficiency requires drones to perform these tasks without the need of human intervention, which demands a robust and accurate localization system for achieving a safe and efficient autonomous navigation. Nevertheless, currently used satellite-based localization systems like GPS are insufficient for high-precision applications, especially in harsh scenarios like indoor and deep urban environments. In these contexts, Local Positioning Systems (LPS) have been widely proposed for satisfying the localization requirements of these vehicles. However, the performance of LPS is highly dependent on the actual localization architecture and the spatial disposition of the deployed sensor distribution. Therefore, before the deployment of an extensive localization network, an analysis regarding localization architecture and sensor distribution should be taken into consideration for the task at hand. Nonetheless, no actual study is proposed either for comparing localization architectures or for attaining a solution for the Node Location Problem (NLP), a problem of NP-Hard complexity. Therefore, in this paper, we propose a comparison among synchronous LPS for determining the most suited system for localizing UAVs over urban scenarios. We employ the Cràmer–Rao-Bound (CRB) for evaluating the performance of each localization system, based on the provided error characterization of each synchronous architecture. Furthermore, in order to attain the optimal sensor distribution for each architecture, a Black-Widow-Optimization (BWO) algorithm is devised for the NLP and the application at hand. The results obtained denote the effectiveness of the devised technique and recommend the implementation of Time Difference Of Arrival (TDOA) over Time of Arrival (TOA) systems, attaining up to 47% less localization uncertainty due to the unnecessary synchronization of the target clock with the architecture sensors in the TDOA architecture.S
Experiencia docente con realidad aumentada para el diseño de máquinas
[ES] La mejora continua en las metodologías docentes requiere de innovación. Por este motivo, los docentes deben
estar al tanto de las nuevas tendencias educativas, así como de los avances tecnológicos. Esto implica que los
profesores deben implementar técnicas y herramientas novedosas en sus clases para mejorar la experiencia de
la enseñanza. Por este motivo, se ha desarrollado una aplicación de Realidad Aumentada (RA) para que los
alumnos aprendan a identificar los elementos mecánicos de una máquina. La aplicación de RA permite al alumno
visualizar de forma tridimensional las piezas pudiendo identificar mejor las particularidades de estas. Además,
con la aplicación de RA el alumno puede ver la pieza a tamaño real mediante un dispositivo móvil inteligente y
un código impreso. Esta experiencia docente se ha realizado en la asignatura de diseño avanzado de máquinas
en el máster universitario de ingeniería industrial con el objetivo de facilitar el proceso de aprendizaje al alumno
mediante una experiencia inmersiva en una práctica síncrona de dos horas de duración. De acuerdo con los
resultados obtenidos se ha mejorado en las pruebas de evaluación continua, así como el interés por parte del
alumnado en utilizar estas técnicas. Por lo tanto, esta aplicación de RA demuestra la utilidad de poner en práctica
herramientas innovadoras durante la enseñanza para mejorar el proceso educativo
EducaFarma 9.0
Memoria ID-020 Ayudas de la Universidad de Salamanca para la innovación docente, curso 2020-2021