Conference Agenda

Companies must meet customer demands to remain competitive, which requires implementing technological solutions through IT. However, software development firms often struggle to meet delivery deadlines set by their clients. In such cases, they turn to outsourcing, a strategy that allows them to temporarily delegate specific tasks to external companies to ensure the timely delivery of the final product. Companies operating under this model must accurately track the hours invested in each project activity. This monitoring is not only crucial for optimizing processes and enhancing development quality but also essential for managing billing efficiently. Currently, many companies still perform this tracking manually on a monthly basis, leading to significant inefficiencies and increased workload on human resources. To address this challenge, a web-based system was developed to automate the tracking and management of time spent on various activities. This tool generates real-time reports, streamlining project management and facilitating data-driven decision-making.

In recent decades, there has been growing concern about air quality, driven by constant industrial and urban growth. This increase is due in part to increased awareness of the adverse impacts of air pollution on human health and ecosystems. This proposal seeks the design of a low-cost monitoring system that allows the measurement of the variables of suspended particles (such as dust and soot) PM10 and PM2.5, nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO) and tropospheric ozone (O3). This system will be made up of three fixed stations located in strategic locations in the city. These stations will in turn be interconnected through a point-to-point link that will be centralized in a local server for storage, processing, validation and analysis of data, which will allow us to monitor these concentrations in real time and report air quality indices. This project seeks to impact and contribute positively to some of the sustainable development goals defined by the UN, also to the objectives and challenges defined by this call, among other results that are proposed, in addition to monitoring concentrations that exceed the maximum permissible limits that generate adverse effects on the respiratory, cardiovascular and neurological health of people.

Linear algebra is a fundamental pillar in engineering programs, traditionally addressed during the third or fourth semester. Despite its relevance, its abstract nature and conventional pedagogical methods represent significant barriers to effective student learning. Numerous studies highlight that the inclusion of playful tools in the educational field can enrich the learning experience, favoring active participation and interest of students. In this context, the present project aims to optimize the engineering curriculum at the Universidad Latina de Costa Rica by incorporating game-based teaching strategies, with an initial focus on the linear algebra course. Through bibliographical consultations, key aspects such as the importance of linear algebra in engineering, its practical applications, and the impact of playful learning were analyzed. In addition, through a qualitative data collection method, perceptions and experiences of students who were studying linear algebra at that time were obtained. Based on this data, a set of educational activities was designed based on tools such as Lego Mindstorms, Lego Spike, computer games, and card games. These activities seek to demystify mathematical concepts, making them accessible and applicable. The proposed approach not only aims to improve academic results, but also to foster a deep and practical understanding of mathematical concepts in engineering contexts. This pedagogical model transforms learning into an interactive and meaningful experience, motivating students to face technical challenges with greater creativity and effectiveness.

At the university, one of the objectives of Research is being implemented: the generation of alternative solutions to improvement or application problems in real scenarios, mainly at the regional level. Currently, these objectives can be achieved with academic research initiatives, identification of practical cases, formation of multidisciplinary teams, availability of economic resources mainly from the state, business organizations and high-risk capital with well-defined technology transfer protocols and with easy access for end users, in a well-defined ethical framework

The observation of agricultural crop conditions through satellite platforms has been of vital importance for the development of decision-making systems in the field. Passive sensors determine land surface conditions by measuring the reflectance of solar radiation, while radar satellites emit their own radiation. Active satellites can acquire information even under cloudy conditions, unlike passive satellites, which lose functionality. The purpose of this work is to study the use of both types of satellites for analyzing vegetation cover in citrus crops and to evaluate the possibility of replacing passive sensor data with active data, along with training recurrent neural networks, particularly Long Short-Term Memory (LSTM). Preliminary results indicate that time series from both types of satellites provide relevant information for crop management. The development of a software tool for downloading and generating time series of remote sensing data for specific locations is presented, using a plugin developed in QGIS and Python. Future research will focus on developing a methodology for fusing data from both types of information acquisition technologies for citrus crops.

This study investigates the evolving attitudes of first-year engineering students toward artificial intelligence (AI) in the era of generative AI and ChatGPT. It explores how students exposed to ChatGPT perceive AI compared to their peers with less exposure to such technologies. A mixed-methods research design, incorporating a computational thinking diagnostic and an open-ended survey question, was employed to understand students' attitudes toward AI’s impact on their future careers. Preliminary results reveal that students who frequently use generative AI tools like ChatGPT tend to demonstrate stronger computational thinking skills and hold more positive views on AI. The findings also suggest that students with prior computing experience exhibit more favorable attitudes toward AI, although the correlation between computational thinking skills and AI attitudes was not statistically significant. The research highlights the critical need for introducing AI/ML education early in the academic journey, particularly in the first year of engineering studies, to ensure students are adequately prepared for advanced AI topics by their senior year. The study further calls for a deeper discussion on how to equip engineering students—who are likely to drive AI advancements—with the skills and mindset necessary for responsible AI development and use.

The development of the CanSat called Tláloc-I, focuses on the ability to collect hydrological data from remote areas from an altitude of three kilometers using image capture by camera for subsequent analysis with a machine learning model, this arises due to the lack of water sources to continue with daily activities such as agriculture and livestock between others; this resource is important and there are areas where humans can not easily reach. The target altitude will be reached by a launcher with gyroscopes and parachutes, ensuring a safe landing for the payload. The CanSat is equipped with multiple sensors whose data is processed by a Python program, stored in text files and sent via serial communication to the operator location of the human machine interface. Real-time monitoring is performed with LabVIEW as the receiving interface of data from the serial port of XBee. The essential functions of the program have been successfully implemented and the team is currently working underway on the manufacture of printed circuit boards for electronic systems. The conclusions focus on the lessons learned during the development process with the expectation of successfully achieving the mission of collecting hydrological data in remote areas. It is relevant to highlight the increasingly important role of new technologies such as artificial intelligence, neural networks as well as learning models, which are transforming many aspects of daily life, including the economic one. This project contributes to improving the lives of farmers, ranchers and residents in areas with water scarcity.

This paper outlines the application of the CRISP-DM methodology to develop a data mining approach for both predicting dropout and understanding its underlying causes. Using data from the university's University Academic Information System (SIAU) and additional data sources. The project is currently in the Data Preparation phase, where an ETL (Extraction, Transformation, and Loading) process is being implemented to prepare the data for later modeling. The research aims to explore machine learning algorithms, such as decision trees and neural networks, to identify predictive patterns and reveal correlations related to dropout factors. This Work in Progress paper details the adapted CRISP-DM methodology and the planned stages of model development, evaluation, and software prototyping, with the ultimate goal to inform effective interventions and promote student success at FCBI-Unillanos.

Various studies highlight the importance of training and personnel development in achieving organizations' strategic goals, suggesting it should be considered a business investment. However, measuring the return on investment (ROI) in training remains a challenge for many companies, particularly in engineering and productive systems. This article presents an exploratory study on the perception of companies in Santander regarding training as an investment, focusing on ROI assessment within the context of engineering education and its impact on human talent management in productive environments. Through a panel of 17 experts using the Delphi model in two rounds, the study analyzed the extent to which organizations apply formal methodologies to calculate the cost-benefit of training and its impact on operational performance. The results show consensus that training is crucial for organizational success but reveal a lack of sophistication in both the ex-ante decision-making phase and the ex-post evaluation. It is concluded that a more precise measurement of ROI would allow for more efficient resource allocation and improved strategic decision-making regarding training in engineering and productive systems.

UNESCO's work over the last decade has laid the foundations for Education for Sustainable Development, which provides the roadmap for integrating it meaningfully and constructively into any school's curriculum. As with the SDGs, Education for Sustainable Development is related to all aspects of our lives and the different subjects taught at varying levels of education. This particularity gives Education for Sustainable Development a unique role among all the other teachings as it can integrate them as a whole, not vice versa. In this context, this paper presents an innovative idea for students to acquire the knowledge and skills related to sustainability and the Sustainable Development Goals necessary for today's employment market. Several professors at the University of Malaga, concerned about the importance that the SDGs are currently acquiring and their inclusion in the curricula, are currently developing this project, which is detailed in this paper. For this reason, at the time of writing and preparing this contribution, it was hardly possible to provide results, but it is hoped that the results of this first year of developing sustainability-related competences will be available during the conference. However, it can be said that the students have worked very hard and think very positively about this initiative.

This paper presents the development of a personal language translation assistant, focused on the particularities of Salvadoran Spanish to English, using artificial intelligence (AI) and cloud computing. The technical and economic feasibility is analyzed and Microsoft Azure is selected as the most appropriate platform for its implementation. The system integrates advanced natural language processing (NLP) and deep learning technologies to improve the accuracy and fluency of translations. The results highlight an innovative solution adapted to specific cultural contexts that positively impact global communication and access to information.

Water scarcity affects millions of people, especially in rural communities with limited access to safe drinking water sources. In this study, a solar PV-powered water condensation system is developed and validated as a sustainable alternative for drinking water production. The methodology employed includes a bibliometric analysis, 3D modeling, CFD simulation, experimental implementation and modeling in TRNSYS. The system integrates a solar-driven compression refrigeration cycle, allowing the condensation of water from ambient air. Experimental results show an average production of 6.9 liters of water per day, with a 25% increase in nighttime production. Validation of the simulation model showed a high correlation with the experimental data, with Pearson and R² coefficients higher than 0.8. These findings confirm the feasibility of the system as an affordable and efficient solution for water-scarce communities.

The purpose of this study was to analyze the perceptions of the academic heads of engineering at a Honduran university on the formation of competencies in their careers and the challenges and opportunities in their specific context. Using a homogeneous sample of experts, a semi-structured interview was applied under three categories a, obtaining 7 dimensions and 205 codes, the largest being the challenges in the formation of competencies. The formation of competencies for this university occurs simultaneously for both technical, soft and transversal axes, it is necessary to continue working on updating lesson plans that respond to the demands of the labor market and the increasing digitalization of processes.

Engineering is a profession where there are greater differences between the number of professional women and men, with the highest percentage being men. Actually, this has led to efforts to ensure equal opportunities and thereby bring these percentages closer to both active students and graduates. If this is transferred to postgraduate courses that have engineering as their base profession, the percentages are even higher. In the case of the master’s degree in project management at the Tecnológico de Costa Rica, with the implementation of virtuality as a result of the COVID pandemic, starting in 2020, the number of active students and graduates has increased to be higher than that of men. This motivated this study to analyze whether virtuality in itself is a gender equity strategy, whether virtuality allows these data to be sustainable over time and, if not, what strategies should be articulated so that the results are not immediate, but in the long term. For this, the study is carried out with a qualitative approach where the group under study corresponded to the graduates of the program in the period 2020 - 2024 who have experienced the process of virtuality and with it, obtain possible scenarios and proposals towards the master's program.

In the current digital era, marked by rapid and disruptive technological advances, engineering education must evolve to equip students with the necessary competencies to face future challenges [1]. This document explores the transformative impact of integrating Artificial Intelligence (AI), Machine Learning, and Matlab into mathematics education, particularly in an engineering school.

The Dynamic Theoretical Learning (DTL) methodology, adapted to include these advanced technologies, not only facilitates a deeper understanding of mathematical concepts but also promotes practical, active, and collaborative learning aligned with current industry demands. The incorporation of gamification within the DTL framework adds an additional layer of motivation, transforming the educational process into an immersive and challenging experience.

Through thematic missions, programming challenges, and rewards, students are encouraged to actively participate, enhance their collaboration skills, and apply acquired knowledge to real-world engineering contexts. The results of implementing this methodology have shown a significant improvement in academic performance, with notable increases in pass rates and greater student adaptability to using advanced technologies.

This approach not only prepares students to be competent in their future professional fields but also inspires them to lead innovations in a world increasingly dominated by technology and artificial intelligence. This document offers a comprehensive and practical vision of how engineering education can be transformed through the integration of AI, Machine Learning, and Matlab, laying the foundation for an innovative and effective educational model for training the engineers of the future.

Microscopy has evolved significantly with the development of high-resolution techniques, overcoming the limitations of optical diffraction. Fourier ptychography (FP) has established itself as a powerful alternative for high-resolution image reconstruction without lenses, employing iterative algorithms based on the Fourier transform. In this work, we present the design and development of a Fourier ptychography prototype using a trinocular microscope, an LED array, and different processing platforms, such as Raspberry Pi-type single-board computers (SBCs), graphical processing units (GPUs), and processor and FPGA integrated circuits (FPSoCs). Different experimental configurations reported in the literature are analyzed, and the viability of each processing platform is evaluated in terms of accuracy, speed, and computational efficiency. As a result, an optoelectronic design for the prototype is proposed, and the essential elements for its construction are defined.

This article demonstrates the implementation of a measurement system to monitor energy consumption and environmental conditions in order to analyze the impact of their variations on the energy consumption of residential buildings. The monitoring system uses ESP32 boards, DHT11 sensors for temperature and humidity, the PZEM-004T current and voltage sensor for energy consumption, and WiFi communication modules to transmit data to the ThingSpeak platform, forming a Wi-Fi Mesh network. The results showed that temperature and humidity variations directly affect the efficiency of electrical devices, increasing energy consumption. These findings highlight the importance of properly managing environmental conditions to optimize energy usage. The practical application of these results suggests that technologies such as IoT, Wi-Fi Mesh networks, and platforms like ThingSpeak can enhance energy efficiency and promote sustainability in residential and commercial environments, enabling more precise, real-time energy management.

1. The rapid advancement of semiconductor manufacturing requires innovative educational strategies to enhance student's understanding of complex industrial processes. This study aims to implement immersive experiences through Virtual Reality (VR) for the exploration of the Assembly, Packaging, and Testing (ATP) process of semiconductors in engineering programs at Universidad Fidélitas de Costa Rica in 2025. The research follows a structured methodology based on three specific objectives: describing the ATP process, developing immersive audiovisual materials to illustrate semiconductor ATP workflows, and designing educational activities incorporating VR-based simulations for interactive learning. The expected outcome is an interactive and engaging learning tool that enhances students' comprehension of semiconductor manufacturing, providing a practical and immersive approach to industrial engineering education. This research contributes to the integration of VR technologies in engineering curricula, fostering a deeper understanding of advanced manufacturing processes through experiential learning.

Abstract–. The article "Integrated Model for Humanitarian Engineering (IMHE): Participatory Design, Empathy, and Holistic Evaluation in Multi-Stakeholder ESF Projects" proposes a methodological framework that combines technical, social, and ethical approaches to address critical problems in vulnerable communities. This model, implemented by Energy Without Borders (ESF), is structured in five stages: problem identification, collaborative design, implementation of sustainable technologies, impact assessment, and continuous improvement. Through its implementation in 32 countries, the IMHE has benefited more than 5.7 million people through projects providing access to drinking water, clean energy, and sanitation, achieving impacts such as a 40% reduction in diseases related to contaminated water and 85% technological sustainability in its solutions.

Its main contributions include participatory design, which ensures cultural relevance and sustainability; holistic evaluation, which measures social, environmental, and economic impacts; and technological adaptability, which adjusts solutions to local constraints. Furthermore, the model fosters the development of empathetic and ethically responsible engineers.

The paper also highlights the contribution of Gómez Sánchez's (2021) Problem/Solution/Product/Project (PSPP) model, which complements the MIIH by structuring the transition from social problems to viable projects. This approach promotes technical innovation and ethical commitment among engineering students.

Together, the MIIH and the PSPP represent a significant step toward more inclusive and sustainable humanitarian engineering, aligned with the Sustainable Development Goals (SDGs) and centered on human dignity, social justice, and multi-stakeholder collaboration.

The paper details a tension pile test conducted on the university campus as part of a Foundation Design course. The process included coordinating with the facilities office, drilling to a depth of 12 feet using a manual 4-inch auger, collecting soil samples every 3 feet for classification and capacity estimation, installing a ½-inch steel strand, pouring concrete, and applying tension with a hydraulic jack and reaction beam. The reaction beam, constructed from aluminum channels, was designed to transfer a 25-kip load from the jack to the strand without disturbing the surrounding soil.
Students calculated the theoretical pile tensile capacity based on soil tests and compared it with experimental results, finding a strong correlation. Post-test observations revealed soil adhesion to the concrete pile, demonstrating the role of soil shear capacity in tension resistance. Conducted over two weeks, the project provided valuable hands-on experience, enhancing students' understanding of pile behavior under tension loads.

This paper investigates the impact of student confidence and perceived relevance on motivation and academic performance in an introductory electrical fundamentals course. Based on Bandura's self-efficacy theory and Keller's ARCS model, interventions were designed to improve student confidence and relevance perception. Pre- and post-intervention surveys indicate significant improvements in perceived relevance and overall academic performance. These findings suggest that targeted activities can enhance motivation and learning outcomes in engineering education.