Jose Manuel Lopez-Guede

University of the Basque Country | UPV/EHU · Systems and Automatic Engineering

Reducing reliance on fossil fuels has driven the development of innovative technologies in recent years due to the increasing levels of greenhouse gases in the atmosphere. Since the automotive industry is one of the main contributors of high CO2 emissions, the introduction of more sustainable solutions in this sector is fundamental. This paper pres...

En los sistemas integrados, la computación de borde procesa datos localmente, mejorando la eficiencia y reduciendo la dependencia de los servidores en la nube. Arduino, conocido por su accesibilidad, ayuda en proyectos integrados. El auge de los vehículos eléctricos requiere el despliegue generalizado de estaciones de carga para una movilidad soste...

En esta investigación, introducimos un nuevo Enfoque de Ventana Dinámica Predictiva (P-DWA), donde el algoritmo no solo anticipa la trayectoria óptima en términos de tiempo, sino que también evalúa el consumo energético del movimiento del robot móvil. El P-DWA predice nueve posibles destinos, evalúa su rendimiento temporal y elige las tres mejores...

The integration of Artificial Intelligence (AI) tools and techniques has provided a significant advance in drone technology. Besides the military applications, drones are being increasingly used for logistics and cargo transportation, agriculture, construction, security and surveillance, exploration, and mobile wireless communication. The synergy b...

This study employs Particle Image Velocimetry (PIV) to investigate flow structures, focusing on the separation bubble and secondary vortices, in a backward-facing step (BFS) configuration. The BFS geometry generates coherent vortex structures, including the free shear region, corner region, redeveloping region, and mean reattachment point, each exh...

Phishing attacks pose a significant threat to online security, utilizing fake websites to steal sensitive user information. Deep learning techniques, particularly convolutional neural networks (CNNs), have emerged as promising tools for detecting phishing attacks. However, traditional CNN-based image classification methods face limitations in effec...

In recent times, there have been notable advancements in solar energy and other renewable sources, underscoring their vital contribution to environmental conservation. Solar cells play a crucial role in converting sunlight into electricity, providing a sustainable energy alternative. Despite their significance, effectively optimizing photovoltaic s...

Background: The declaration of the COVID-19 pandemic triggered global efforts to control and manage the virus impact. Scientists and researchers have been strongly involved in developing effective strategies that can help policy makers and healthcare systems both to monitor the spread and to mitigate the impact of the COVID-19 pandemic. Machine Lea...

Payload transportation and manipulation by rotorcraft drones are receiving a lot of attention from the military, industrial and logistics research areas. The interactions between the UAV and the payload, plus the means of object attachment or manipulation (such as cables or anthropomorphic robotic arms), may be nonlinear, introducing difficulties i...

Authors propose a new intelligent optimization algorithm. This algorithm tries to learn the cost function shape in order to decide which points must be evaluated, and how many optimization iterations are enough. As far as the authors know, there is no optimization algorithm that applies prediction with all the evaluated points. Authors have perform...

Nowadays, Twitter is one of the most popular social networking services. People post messages called “tweets”, which may contain photos, videos, links and text. With the vast amount of interaction on Twitter, due to its popularity, analyzing Twitter data is of increasing importance. Tweets related to finance can be important indicators for decision...

This study introduces a novel trajectory planning approach for the transportation of cable-suspended loads employing three quadrotors, relying on a reinforcement learning (RL) algorithm. The primary objective of this path planning method is to transport the cargo smoothly while avoiding its swing. Within this proposed solution, the value function o...

The improvement of electrical power system efficiency by solving the Optimal Power Flow problem involves identifying optimal controllable setpoints. This study presents a methodology that integrates a Particle Swarm Optimization algorithm with Artificial Neural Networks to minimize losses and costs. The objective is to reduce both generation fuel c...

Physical models are suitable for the development and optimization of materials and cell designs, whereas models based on experimental data and electrical equivalent circuits (EECs) are suitable for the development of operation estimators, both for cells and batteries. This research work develops an innovative unsupervised artificial neural network...

Object detection is an essential and impactful technology in various fields due to its ability to automatically locate and identify objects in images or videos. In addition, object-distance estimation is a fundamental problem in 3D vision and scene perception. In this paper, we propose a simultaneous object-detection and distance-estimation algorit...

The study focuses on the integration of a fuzzy logic-based Maximum Power Point Tracking (MPPT) system, an optimized proportional Integral-based voltage controller, and the Jellyfish Optimization Algorithm into a solar PV battery setup. This integrated approach aims to enhance energy harvesting efficiency under varying environmental conditions. The...

These days, the implementation of sustainable power generation has led to a difference in propensity in the energy creation and capacity frameworks, compelling them to conquer the hardships that it addresses. Considering the entirety among the suggested technologies, vanadium redox flow batteries (VRFB) stand out as a wonderful choice regarding cyc...

This research continues the previous work “Robotic-Arm-Based Force Control in Neurosurgical Practice”. In that study, authors acquired an optimal control arm speed shape for neurological surgery which minimized a cost function that uses an adaptive scheme to determine the brain tissue force. At the end, the authors proposed the use of reinforcement...

The air quality is a parameter to be controlled in order to live in a comfortable place. This paper analyzes the trajectory of aerosols exhaled into the environment in a classroom. Three scenarios are investigated; without ventilation, with natural and with mechanical ventilation. A multi-phase computational fluid study based on Eulerian-Lagrangian...

The mortality impact of COVID-19 across European countries is a complex phenomenon that appears to be influenced by political, social, economic, and environmental factors. The western European countries have implemented similar policies, with some specific minor divergences, like in the implementations of lockdowns and vaccination passes, so that s...

Active Learning is a known and very promising approach to boost the learning processes driven by the students. In this paper a novel Educational Innovation Project is described in order to solve several problems found in two specific subjects related to Computer Architecture. More specifically, the project is based on Research Based Project, a less...

The degradation and safety study of lithium-ion batteries is becoming increasingly important given that these batteries are widely used not only in electronic devices but also in automotive vehicles. Consequently, the detection of degradation modes that could lead to safety alerts is essential. Existing methodologies are diverse, experimental based...

Alzheimer’s is a neurodegenerative disorder affecting the central nervous system and cognitive processes, explicitly impairing detailed mental analysis. Throughout this condition, the affected individual’s cognitive abilities to process and analyze information gradually deteriorate, resulting in mental decline. In recent years, there has been a not...

The automatic classification of marine species based on images is a challenging task for which multiple solutions have been increasingly provided in the past two decades. Oceans are complex ecosystems, difficult to access, and often the images obtained are of low quality. In such cases, animal classification becomes tedious. Therefore, it is often...

Deep Learning (DL) has provided a significant breakthrough in many areas of research and industry. The development of Convolutional Neural Networks (CNNs) has enabled the improvement of computer vision-based techniques, making the information gathered from cameras more useful. For this reason, recently, studies have been carried out on the use of i...

The presence of suspended particles in liquid fluids is one of the main reasons for hydraulic system failure. Metallic impurities in particular increase the presence of toxic substances in wastewater; therefore, it is vital to study and address the behaviour of such particles in water flows. The current literature lacks studiees approaching the com...

The authors wish to correct the following error in the original paper [...]

This paper introduces the use of a new low-computation cost algorithm combining neural networks with the Nelder–Mead simplex method to monitor the variations of the parameters of a previously selected equivalent circuit calculated from Electrochemical Impedance Spectroscopy (EIS) corresponding to a series of battery aging experiments. These variati...

COVID-19 has been spread to many countries all over the world in a relatively short period, largely overwhelmed hospitals have been a direct consequence of the explosive increase of coronavirus cases. In this dire situation, the demand for the development of clinical decision support systems based on predictive algorithms has increased, since these...

Nowadays everyone should be aware of the importance of reducing CO2 emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before undertaking a modification in any part of a building focused on improving the energy performance, it is...

This paper deals with the control of a team of unmanned air vehicles (UAVs), specifically quadrotors, for which their mission is the transportation of a deformable linear object (DLO), i.e., a cable, hose or similar object in quasi-stationary state, while cruising towards destination. Such missions have strong industrial applications in the transpo...

The COVID-19 pandemic has increased the pressure on developing clinical decision-making systems based on predictive algorithms, potentially helping to reduce the unmanageable strain on healthcare systems. In an attempt to address this challenging health situation, we attempted to provide a contribution to this endeavour with an in-depth study of a...

In the present work, an artificial neural network (ANN) will be developed to estimate the relative rotation and translation of the autonomous mobile robot (AMR). The ANN will work as an iterative closed point, which is commonly used with the singular value decomposition algorithm. This development will provide better resolution for a relative posit...

This work evaluates the evolution of electrochemical parameters, such as voltage and impedance spectra, to determine the state of charge (SOC), state of health (SOH), and electrolyte level of vented NiCd batteries. Similar to previous studies on lead acid batteries, valuable results are presented for SOC estimation based on open-circuit voltage. So...

Random forest (RF) models were developed to estimate the biomass for the Pinus radiata species in a region of the Basque Autonomous Community where this species has high cover, using the National Forest Inventory, allometric equations and low-density discrete LiDAR data. This article explores the tuning for RF hyperparameters, obtaining two models...

There are few studies concerning the propagation of COVID-19 pandemic, besides theoretical models that have produced alarming predictions. These models assume wave-like propagation dynamics on an uniform medium. However, it appears that COVID-19 follows unexpected propagation dynamics. In this paper we consider the state-wise data on COVID-19 morta...

Abstract: Flow control device modeling is an engaging research field for wind turbine optimization, since in recent years wind turbines have grown in proportions and weight. The purpose of the present work was to study the performance and effects generated by a rotating microtab (MT) implemented on the trailing edge of a DU91W250 airfoil through th...

In this work, a maximum power point tracking (MPPT) system for its application to a new piezoelectric wind energy harvester (PWEH). The motivation for such MPPT unit comes from the power scales of the piezoelectric layers being in the order of μW. In addition, the output generates highly disturbed voltage waveforms with high total harmonic distorti...

The protection provided by wearing masks has been a guideline worldwide to prevent the risk of COVID-19 infection. The current work presents an investigation that analyzes the effectiveness of face shields as personal protective equipment. To that end, a multiphase computational fluid dynamic study based on Eulerian–Lagrangian techniques was define...

In this article, a control strategy approach is proposed for a system consisting of a quadrotortransporting a double pendulum. In our case, we attempt to achieve a swing free transportationof the pendulum, while the quadrotor closely follows a specific trajectory. This dynamic system ishighly nonlinear, therefore, the fulfillment of this complex ta...

Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) has been identified as one of the most prom...

This work presents a battery management system for lead-acid batteries that integrates a battery-block (12 V) sensor that allows the online monitoring of a cell's temperature, voltage, and impedance spectra. The monitoring and diagnostic capabilities enable the implementation of improved battery management algorithms in order to increase the life e...

Nowadays, most areas of human activity should be reviewed with the aim of reducing CO2 emissions, since these activities are producing the majority of these emissions. Specifically, the building sector is one of the main responsible activities. In order to minimize the ecological footprint and ensure energy sufficiency, European Union created the n...

This work presents the results of experimental analysis of the correlation between open-circuit voltage at 0% and the state of charge of a set (3 × 6) of high-temperature valve-regulated lead acid batteries, which provides a valuable health diagnosis tool when performing predictive maintenance actions. The proposed test could be executed after any...

The design procedure of a Machine Learning (ML) based yaw control strategy for a Horizontal Axis Wind Turbine (HAWT) is presented in the following chapter. The proposed yaw control strategy is based on the interaction of three different Artificial Intelligence (AI) techniques to design a ML system: Reinforcement Learning (RL), Artificial Neural Net...

One of the materials that is used widely for wind turbine blade manufacturing are fiber-reinforced composites. Although glass fiber reinforcement is the most used in wind turbine blades, the use of carbon fiber allows larger blades to be manufactured due to their better mechanical characteristics. Some turbine manufacturers are using carbon fiber i...

Road landmark inventory is becoming an important data product for the maintenance of transport infrastructures. Several commercial sensors are available which include synchronized optical cameras that allowto build 360° panoramic images of the surroundings of the the vehicle used for road inspection. This paper is devoted to the analysis of such pa...

Academic programs are trying to implement edge technologies on their Bachelor’s and Master’s degrees offerings. In this paper authors present the experience of a dedicated electromobility research project and its alternative use for academic purposes. A case study is selected in a university in Chile, where the design of a new laboratory that serve...

One of the implementations of novel initiatives in the field of education that requires more efforts is the entire implementation of a new Bachelor’s degree based on dual training. These efforts involve on one hand the design of an extremely experimental degree and on the other hand, the engagement of local companies that must collaborate in a rigo...

This paper presents an expansion of an Artificial Intelligence workshop developed with Scratch for high school students, which already proved its evidence for the demystification and mathematic basis understanding of this discipline. Students will be able to understand and practice with two simple algorithms, following closely the short instruction...

Autonomous Mobile Robots (AMR) need a positioning function to move into unknown areas. These kinds of vehicles do not use a magnetic tape to guide into warehouses. Therefore, AMR use two different alternative techniques to solve the localization problem. First one is based on absolute positioning, and second one is established on relative localizat...

With the development of artificial intelligence, alternative advanced machine learning approaches have allowed the training of increasingly sophisticated models via the available data. The light detection and ranging (LiDAR) remote sensing technique is being increasingly applied to obtain informative terrain maps, due to its ability to collect larg...

Road landmark inventory is becoming an important industry for the maintenance of transport infrastructures among others. Several commercial sensors are available witch include LiDAR sensors allowing to capture up to 1.5 million data point per second. We obtain an intensity based image from the LiDAR point cloud intensity. The landmark detection is...

Large-scale energy storage systems (ESS) are nowadays growing in popularity due to the increase in the energy production by renewable energy sources, which in general have a random intermittent nature. Currently, several redox flow batteries have been presented as an alternative of the classical ESS; the scalability, design flexibility and long lif...

Within the different modeling possibilities to describe the behavior of complex dynamic systems, Artificial Neural Networks (ANN) are one of the most outstanding approaches. In this paper authors have used that approach to model the electrical performance of a specific commercial single proton exchange (PEM) fuel cell (FC). More specifically, a 2 K...

At a very high energy consumption level at national level the Human Development Index actually begins to decrease. The basis is a large data set with all nations energy and HDI stats. The article discusses the statistical findings in detail.

The former consensus on a link between energy consumption and improved well-being of a country has been scrutinized by scholars for decades and is, succinctly, for the time being a contested thesis. Until the 1970s the relation of energy to well-being was defined as linearly proportional, and in a later period still as an increasing logarithmic fun...

In this article authors propose a temperature based Maximum Power Point Tracking algorithm (MPPT). Authors show that there is an optimal current vs maximum power curve that depends on photovoltaic (PV) module temperature. Therefore, the maximum power point (MPP) can be achieved in very few commutation steps if the control forces the PV module to wo...

Over the last few years, the advances in size and weight for wind turbines have led to the development of flow control devices. The current work presents an innovative method to model flow control devices based on a cell-set model, such as Gurney flaps (GFs). This model reuses the cells which are around the required geometry and a wall boundary con...

Vortex generators (VGs) are used increasingly more by the wind turbine manufacture industry as flow control devices to improve rotor blade aerodynamic performance. The VG height is usually designed with equal thickness of the local boundary layer at the VG position. Nevertheless, these conventional VGs may produce excess residual drag in some appli...

An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic vari...

This paper presents several educational applications in Scratch that are proposed for the active participation of undergraduate students in contexts of Artificial Intelligence. The students are asked to understand the mathematics involved in an automatic clustering algorithm and two simple neural networks for data learning. They must practice with...

Hydrogen based technologies are a growing field among the renewable energies options, being the single proton exchange membrane (PEM) fuel cells (FC) one of the most promising. There are a number of possibilities to model the electrical behavior of this kind of devices. Among them, in this paper authors have tackled the problem using an Artificial...

The considerable increase of wind turbine rotor size and weight in the last years has made impossible to control as they were controlled 20 years ago. The cost of energy is an essential role to maintain this type of energy as a viable alternative in economic terms with traditional or other renewable energies. Through the last decades many different...

Estimation of forestry aboveground biomass (AGB) by means of aerial Light Detection and Ranging (LiDAR) data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available research budgets. In this paper we exploit already existing public low-density LiDAR data obtained for other purposes, such as cart...

In this paper we present a state-of-the-art review about road lane landmark extraction. Automatic lane landmark extraction has been studied during the last decade for different practical applications. The purpose of this paper is to gather and discuss methodologies of road lane landmark extraction based on signals from different sensors in order to...