Ayala-Chauvin, Manuel Ignacio
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Ayala-Chauvin, Manuel Ignacio
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Ambato
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mayala@uti.edu.ec
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57215428914

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Data Analysis for Performance Improvement of University Students Using IoT

2024 , Ayala-Chauvin, Manuel Ignacio , Lara-Álvarez P. , Castro R.

Using Internet of Things (IoT) devices and data analysis techniques can potentially transform how universities approach improving student achievement. In this sense, the project is based on implementing a remotely operated pneumatic bank applying IoT for university education. With this technology, it is possible to obtain information about the factors that impact student achievement and design targeted interventions to help students improve their performance. The control system with low-cost technology was developed with Raspberry Pi, AnyDesk, and Canvas LMS for the remote connection. The experiment was carried out with two groups of 7 people, and it was identified that there are correlations of 0.87 and 0.62 between the performance of the students and the time they dedicate to studying and the hours they spend on the platform; this suggests a positive correlation between these variables. Therefore, as students spend more time studying and spending more hours on the platform, they are more likely to achieve better academic results. On the other hand, the study time of the group of students who used the bank remotely increased by 32% compared to those who used the bank in person; therefore, we can infer that with the implementation of the IoT, the use of the system is encouraged. Finally, based on the insights gained from the analysis, targeted interventions can be designed to help students improve their academic performance. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Evolution, Collaborations, and Impacts of Big Data Research in Ecuador: Bibliometric Analysis

2024 , Avilés-Castillo, Fátima , Ayala-Chauvin, Manuel Ignacio , Buele J.

Big Data has been gaining significant attention globally due to its potential to drive innovation, guide decision-making, and stimulate economic growth. As part of this global trend, Ecuador has also witnessed a surge in Big Data-related research over the past decade. This study comprehensively analyzes Big Data research evolution, collaborations, and impacts in Ecuador from 2012 to 2023. By examining the patterns of publication, researcher demographics, primary languages, significant publishers, most cited research papers, patterns of author collaboration, and prevalent keywords, we strive to construct a detailed portrayal of the Big Data research landscape in the country. Our investigation reveals a noticeable increase in Big Data research activity post-2015, particularly within major cities like Quito and Guayaquil. Notably, the study also underscores the predominance of English in research publications, with leading publishers such as IEEE and Springer playing significant roles. The diverse themes of the most cited articles illustrate the wide-ranging applications of Big Data research within the country. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Lifecycle assessment of electricity generation transition in ecuador

2021 , Ayala-Chauvin, Manuel Ignacio , Samaniego-Ojeda C. , Riba G. , Maldonado-Correa J.

Ecuador’s energy mix has greatly reduced its dependency on fossil fuels the last 15 years, down to a marginal role (5%) in electricity generation in 2017. The development plan for the Ecuadorian power network aims to keep adding hydropower to meet the increasing demand. A prospective lifecycle assessment (LCA) of the future power network (2012–2050) can determine the feasibility of the development plan and its environmental sustainability in the long run. For a quantitative analysis of the energy transition over the entire lifecycle, the simulation software® Global Emission Model of Integrated System (GEMIS) is used. The results show that the current development path of the Ecuadorian energy system reduces the emissions of CO2 per kWh generated by 65% due to the large share of renewable energies, mainly hydropower, which costs 1% of Gross Domestic Product. The obtained LCA footprints are similar to the literature benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

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Augmented Reality Application with Multimedia Content to Support Primary Education

2023 , Buele, Jorge , Espinoza J. , Ruales, María Belén , Camino-Morejón V.M. , Ayala-Chauvin, Manuel Ignacio

Education is continually reinventing itself to meet the growing needs of learners. In the context of an emergency, confinement and mobilization difficulties have necessitated the adoption of online education. This new offer brings technological means to conventional processes, but its main disadvantage is the limited access in some places. This has motivated the present study, which proposes the development of a mobile application using augmented reality (AR) to complement primary education. This application aims to disseminate multimedia content without needing a stable internet connection. A high-performance computer is required for the design and a mid-range smartphone for its execution. Four scripts are generated in c# programming language using Visual Studio. The environment and the three-dimensional objects are developed using Unity software and the packages ARFoundation, Unity MARS, and Vuforia. Two groups of 13 children each participated in the experimental testing. The experimental group used the application for two weeks to complement the virtual classes in the subjects of language, natural sciences, and mathematics. The analysis with SPSS software shows a statistically significant increase in the average grades compared to the control group. This research shows that the use of technology can contribute to improving the current teaching-learning processes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Big Data as a Tool for Analyzing Academic Performance in Education

2024 , Ayala-Chauvin, Manuel Ignacio , Chucuri-Real B. , ESCUDERO VILLA, PEDRO FERNANDO , Buele, Jorge

Educational processes are constantly evolving and need upgrading according to the needs of the students. Every day an immense amount of data is generated that could be used to understand children’s behavior. This research proposes using three machine learning algorithms to evaluate academic performance. After debugging and organizing the information, the respective analysis is carried out. Data from eight academic cycles (2014–2021) of an elementary school are used to train the models. The algorithms used were Random Trees, Logistic Regression, and Support Vector Machines, with an accuracy of 93.48%, 96.86%, and 97.1%, respectively. This last algorithm was used to predict the grades of a new group of students, highlighting that most students will have acceptable grades and none with a grade lower than 7/10. Thus, it can be corroborated that the daily stored data of an elementary school is sufficient to predict the academic performance of its students using computational algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Control System Test Platform for a DC Motor

2022 , Saá-Tapia F. , Mayorga-Miranda L. , Ayala-Chauvin, Manuel Ignacio , Domènech-Mestres C.

Currently, control systems are used to improve the behavior of actuators that are part of an equipment or process. However, to enhance their performance, it is necessary to perform tests to evaluate the responses of its operation depending on the type of controller. In this sense, a test platform was developed to compare and optimize the speed control of a DC motor with three types of controllers: Predictive Model Control (MPC), Proportional Integral Derivative (PID) and Fuzzy Logic. Data acquisition was performed using the Arduino MEGA board and LabVIEW software. The mathematical model of the three controllers was developed, taking into account the electrical and physical properties of the DC motor. Through MATLAB IDENT, the state space (SS) and transfer function F(S) equations were generated for the MPC and PID controller, respectively; on the other hand, input/output ranges for the Fuzzy Logic controller were input/output ranges defined by assigning belonging functions and linguistic variables. Experimental tests were carried out with these models under no-load and load. Tests performed in vacuum show that performance index with the motor at 100 rpm results in a PID of 0.2245, a Fuzzy Logic of 0.3212 and an MPC of 0.3576. On the other hand, with load at 100 rpm, a PID of 0.2343, a Fuzzy Logic of 0.3871 and an MPC of 0.3104 were obtained. It was determined that the Fuzzy Logic controller presents a higher over impulse; the PID and MPC have a faster stabilization time and with negligible over impulses. Finally, the MPC controller presents a better performance index analysis according to the Integral Square Error criterion (ISE). © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Inverse kinematics of a redundant manipulator robot using constrained optimization

2020 , Varela Aldas, José , Ayala-Chauvin, Manuel Ignacio , Andaluz, V.H. , Santamaría, M.

Redundant manipulative robots are characterized by greater manipulability improving performance but complicating inverse kinematics, on the other hand, optimization techniques allow solving complex problems in robotics applications with greater efficiency. This paper presents the inverse kinematics of a redundant manipulative robot with four degrees of freedom to track a desired trajectory, and considering constraint in manipulability. The optimization problem is proposed using the quadratic position errors of the operative end and the constraint is established by a manipulability index, for this the kinematic model of the robot is determined. The results show the points of singularity of the robot and the performance of the proposal implemented, observing the positional errors and the manipulability for each point of the trajectory. In addition, the optimization is evaluated for two desired manipulability values. Finally, it is concluded that the implemented method optimizes the inverse kinematics to track the desired path while constraining the manipulability. © Springer Nature Switzerland AG 2020.

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Exploring the Landscape of Data Analysis: A Review of Its Application and Impact in Ecuador

2023 , Ayala-Chauvin, Manuel Ignacio , Avilés-Castillo F. , Buele, Jorge

Latin America has shown increased big data adoption since 2012; Ecuador is now entering this transformative field. Science and engineering in Ecuador have benefited most from data analysis, with untapped potential in health and services sectors. Big data is shaping sectors in Ecuador, including disaster prediction, agriculture, smart city development, and electoral data analysis. Despite public sector inefficiencies, residential ICT adoption provides opportunities for Ecuador’s smart city advancements. Despite some data underutilization, big data’s transformative potential is evident in Ecuador’s healthcare and education advancements. Highlights: Data analysis is increasingly critical in aiding decision-making within public and private institutions. This paper scrutinizes the status quo of big data and data analysis and its applications within Ecuador, focusing on its societal, educational, and industrial impact. A detailed literature review was conducted from academic databases such as SpringerLink, Scopus, IEEE Xplore, Web of Science, and ACM, incorporating research from inception until May 2023. The search process adhered to the PRISMA statement, employing specific inclusion and exclusion criteria. The analysis revealed that data implementation in Ecuador, while recent, has found noteworthy applications in six principal areas, classified using ISCED: education, science, engineering, health, social, and services. In the scientific and engineering sectors, big data has notably contributed to disaster mitigation and optimizing resource allocation in smart cities. Its application in the social sector has fortified cybersecurity and election data integrity, while in services, it has enhanced residential ICT adoption and urban planning. Health sector applications are emerging, particularly in disease prediction and patient monitoring. Educational applications predominantly involve student performance analysis and curricular evaluation. This review emphasizes that while big data’s potential is being gradually realized in Ecuador, further research, data security measures, and institutional interoperability are required to fully leverage its benefits. © 2023 by the authors.

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Evaluation of the energy autonomy of urban areas as an instrument to promote the energy transition

2022 , Ayala-Chauvin, Manuel Ignacio , Riba Sanmartí G. , Riba C. , Lara P.

The management of energy systems with a high share of renewables is a challenge for grid planners and operators, as weather and energy demand do not always coincide. Investigating the energy autonomy of cities and their local energy resources can help to overcome this challenge. To this end, real energy demand data from the city of Loja, Ecuador, and wind energy generation from a nearby wind farm were compared. This showed that wind energy provides 53% of the city’s demand. It is exposed that despite the excess energy, the wind farm’s ability to supply the city with electricity is limited to about 74% when the wind farm is expanded to twice its rated capacity. The results show that in order to improve the autonomy, other energy sources, such as photovoltaic, as well as useful size energy storage are needed. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

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Static reactive power compensator design, based on three-phase voltage converter

2021 , Ayala-Chauvin, Manuel Ignacio , Kavrakov B.S. , Buele, Jorge , Varela Aldas, José

At present, electrical network stability is of the utmost importance because of the increase in electric demand and the integration of distributed generation deriving from renewable energy. In this paper, we proposed a static reactive power compensator model with common direct current voltage sources. Converter parameters were calculated and designed to fulfill specifications. In order to ascertain the device response for different operating modes as reactive power consumer and generator, we developed the model’s power and control circuits in Matlab Simulink. Simulations were performed for different conditions, and as a result, the current and voltage waveforms and the circular power chart were obtained. This paper has theoretically proven it is possible to achieve the consumption or generation of purely active or reactive power by implementing a static reactive power compensator with common DC voltage sources. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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