Centro de investigación en Mecatrónica y Sistemas Interactivos

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Universidad Indoamérica

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Does the use of dedicated mobile devices in magnetism classes improve student learning?
(Frontiers Media SA, 2026-04-21)
Varela Aldas, José
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Collay, Washington
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Del-Valle-Soto, Carolina
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Palacios-Navarro, Guillermo
Mobile devices have been evaluated from multiple perspectives as tools to support classroom learning; however, devices specifically dedicated to learning activities still require further research to elucidate their influence in the classroom. This study aimed to evaluate whether the use of dedicated mobile devices for teaching basic magnetism content improves learning among secondary school students. A quantitative, comparative quasi-experimental study with non-equivalent groups was conducted ((Formula presented)) with secondary school students in Ecuador. The experimental group used an educational application running on a dedicated mobile device (M5Stack Core2) and interacted with an electromagnet as a didactic peripheral, whereas the control group received a traditional teacher-centered lesson supported by slides. Learning outcomes were measured using a teacher-designed theoretical test administered at the end of a 90-min session. Mean scores were similar between groups (experimental: 7.32; control: 7.58). After verifying assumptions of normality and homogeneity of variance, an independent-samples t-test showed no statistically significant differences ((Formula presented)), and the effect size was small (Cohen’s (Formula presented)). Under the conditions evaluated, the dedicated mobile device did not produce measurable gains in knowledge performance compared to the traditional lesson. Longer interventions, larger samples, and longitudinal study designs are needed to clarify when and how this technology may provide educational benefits.
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Addressing the Accessibility Gap in Biometric Security: A Low-Cost, Open-Source Approach for High-Risk Environments
(Springer Nature Switzerland, 2026)
Vargas-Bustamante, Miguel
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Zapata, Mireya
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García-Muñoz, Gabriel
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Álvarez-Tello, Jorge
Facial recognition has become established as a key technology for access control in high-insecurity contexts; however, its adoption in resource-constrained environments remains limited. This study addresses the existing gap in the empirical validation of low-cost biometric systems deployed in real-world scenarios. A prototype access control system based on facial recognition was developed using low-cost embedded hardware and open-source software. The research followed a quantitative, experimental, and applied approach, evaluating system performance using standardized biometric metrics (accuracy, FAR, and FRR) under different environmental conditions. The system achieved 97% accuracy in authorized access attempts and 96% accuracy in unauthorized attempts, with an average latency of 1.8 s and complete resistance to basic spoofing attacks. The results demonstrate that low-cost biometric solutions can achieve acceptable levels of reliability and usability for access control in high-insecurity contexts, contributing to the democratization of technological security
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Using Predictive Modeling to Assess Social Media's Impact on Parental Well-Being: A Pilot Study
(Springer Nature Switzerland, 2026)
Tutillo, Jimena
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Martinez, Danilo
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Zapata, Mireya
Social media is part of daily life, facilitating communication, entertainment, and immediate access to information. However, it can negatively affect personal well-being and contribute to the development of addictive behavior. The objective of this paper is to examine how social media users in the economically productive age group of 36 to 56 years are affected by these platforms, and how machine learning (ML) and app development can be used to mitigate the impacts of these dopamine-stimulated behaviors. For this purpose, an empirical study using the Social Media Disorder Test showed that 37.5% of the sample had prolonged usage. To aid in the solution, an app was developed that uses machine learning (ML) to classify addiction levels into 8 categories across 3 social media apps. The app monitors usage in real time and issues alerts for excessive consumption patterns to reduce digital dependence. The results show real patterns of moderate addiction among users. It also seeks to raise awareness of social media use so they can set limits and reduce the impact of their use
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Fiber–matrix interaction governs compressive strength in agave-bagasse-reinforced adobe: a factorial experiment with two-way ANOVA and competing mechanism analysis
(Frontiers Media SA, 2026-07-31)
De-Obaldia-Escalante, Marcela
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Del-Valle-Soto, Carolina
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Acevedo-Parra, H. R.
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Montoya-Márquez, Orlando
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Varela Aldas, José
Natural-fiber reinforcement is widely cited as a pathway to improve the mechanical performance of adobe, but reported effects on compressive strength are inconsistent across studies: some find improvement, others find degradation, and the choice of experimental conditions rarely disentangles the role of the fiber from that of the matrix. This study quantifies the coupling through a balanced factorial experiment. Forty-nine adobe specimens of (Formula presented) cm were manufactured with three granular compositions (sand-dominated, jal-dominated, and balanced, where jal is a regional non-plastic silt of Jalisco, Mexico) and four mass fractions of agave-bagasse fiber (0%, 0.5%, 1%, and 2%), and were tested under Mexican standard NMX-C-036-ONNCCE by an accredited external laboratory. Three complementary analytical tools are applied to the resulting dataset: (i) a two-way analysis of variance (ANOVA), (ii) a reinforcement efficiency index (Formula presented) with bootstrap confidence intervals, and (iii) a competing mechanism phenomenological descriptor (Formula presented) that separates a saturating reinforcement term from a linear disruption term. The two-way ANOVA reveals a highly significant mixture–fiber interaction ((Formula presented), (Formula presented), and partial (Formula presented)), which is stronger than either main effect and statistically demonstrates that the sign of the fiber effect is not an intrinsic property of the fiber but rather a property of the fiber–matrix pair. For sand-containing mixtures, the reinforcement efficiency index is (Formula presented) [M1, 95% bootstrap CI (0.96, 1.32)] and (Formula presented) [M3, (0.92, 1.59)] at the optimum (Formula presented); a non-parametric bootstrap over 5, 000 resamples places the optimum at (Formula presented) with posterior probability (Formula presented) (M1) and (Formula presented) (M3). For the jal-dominated mixture, fiber inclusion is net destructive [(Formula presented), (0.68, 0.95) at (Formula presented)], with Welch (Formula presented)-tests rejecting equivalence with the control at (Formula presented) (0.5%) and (Formula presented) (2%) and Cohen’s effect sizes (Formula presented). The best-performing conditions yield mean compressive strengths of 3.22 MPa, which exceeds the 2.0 MPa minimum required by NMX-C-441-ONNCCE-2011 for non-structural masonry by 60%. An immersion test shows that unstabilized specimens disintegrate within 2–3 min, bounding applications to non-exposed or externally protected uses and defining the primary direction for future work.
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From Simulation to Reality: A Digital Twin Implementation of a 4-DOF Robotic Manipulator
(2025)
Bryan S. Guevara
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Varela Aldas, José
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Viviana Moya
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Angéelica Veróonica Quito Carrióon
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Marcelo Ortiz
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ROS2-Based Low-Cost Mobile Robot for Educational Assistance with Reactive Navigation and Semantic-Cached Language Processing
(MDPI AG, 2026-07-08)
Aucapiña, Sebastián Alexis
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Benalcázar, Nataly Cecilia
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Varela Aldas, José
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Isa-Jara, Ramiro
Educational environments, particularly those with limited resources, require affordable mobile robots capable of combining human–robot interaction, autonomous assistance, and academic support without continuous dependence on cloud services. This work presents a low-cost ROS2-based mobile robot implemented on a Raspberry Pi 4B to provide educational assistance in Spanish within controlled classroom environments. The system integrates voice interaction, text-to-speech synthesis, YOLOv8n-based object perception, a specialized door detection model, ultrasonic and inertial sensing, differential-drive control, and a hybrid natural language processing architecture based on semantic caching, local inference, and optional cloud connectivity. Two task-dependent operating modes, education and navigation, selectively activate ROS2 nodes to reduce computational load and energy consumption. Experimental tests conducted in a university classroom evaluated speech recognition, vision models, natural language processing alternatives, sensor behavior, and battery life. The speech recognition module achieved 98% accuracy under both quiet and noisy conditions. YOLOv8n achieved an F1-score of 0.975 for common classroom objects, while the specialized door detector achieved 100% recall with 58.7% precision. The semantic cache correctly resolved recurrent academic queries in the exact-match evaluation, with an average latency of 3.8 s, reducing the need for external language models in known-question scenarios. The robot operated for 96 min in education mode and 75.6 min in navigation mode. These results demonstrate that Spanish voice interaction, reactive navigation, academic question answering, and resource-aware operation can be integrated into a single low-cost edge robotic platform for educational environments. © 2026 by the authors.
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From Simulation to Reality: A Digital Twin Implementation of a 4-DOF Robotic Manipulator
(2025)
Bryan S. Guevara
;
Varela Aldas, José
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Viviana Moya
;
Angéelica Veróonica Quito Carrióon
;
Marcelo Ortiz
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From simulation to reality: a learning methodology for understanding control systems and robotic arms with the ARCHIE robot
(Frontiers Media SA, 2026-04-10)
Saeteros, Juan
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Mendoza, Erick
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Ramirez, Jefferson
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Fajardo-Pruna, Marcelo
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Buele, Jorge
Bridging the gap between theoretical concepts and real-world implementation remains a critical challenge in the teaching of control systems and robotics. This paper presents an education method using ARCHIE, a low-cost, open-source articulated robot with six degrees of freedom, as an educational platform designed to enhance students’ understanding of control theory through practical learning. The study combines simulation (using MATLAB’s Simscape) with hands-on practice using the physical robot, following a Sim2Real methodology. A two-hour workshop was conducted with undergraduate mechatronics engineering students, incorporating pre- and post-assessments to evaluate learning gains. Preliminary results suggest a statistically significant improvement in students’ understanding of PID control concepts, with average test scores rising from 46.6% to 63.3% (p = 0.0454, two-tailed). The study also highlights the benefits of active learning, allowing students to experience real-world control system behavior and reflect on discrepancies between simulations and physical implementation. ARCHIE proves to be a valuable educational tool for fostering deeper comprehension of control systems in engineering curricula. © 2026 Saeteros, Mendoza, Ramirez, Fajardo-Pruna, Buele, Yumbla and Saldarriaga.
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Lyapunov-Stable Neural Network Control for Position and Force Coordination in Delayed Bilateral Teleoperation Systems
(Institute of Electrical and Electronics Engineers (IEEE), 2026)
Slawiñski, Emanuel
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Chicaiza Claudio, Fernando
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Rossomando, Francisco G.
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Mut, Vicente
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Moreno-Valenzuela, Javier
Stability and transparency are intrinsically coupled and must be addressed simultaneously in delayed bilateral teleoperation systems, where there is a fundamental tradeoff between ensuring closed-loop stability and achieving accurate force–position coordination. This challenge becomes particularly critical when interacting with remote environments under time-varying communication delays, since the human operator introduces nonlinear, time-varying, and often unpredictable dynamics into the closed-loop system. This article presents an adaptive neural-network (NN)-based compensation strategy embedded within a model-based control framework to enhance dual coordination in bilateral teleoperation. By combining classical control design with online NN adaptation, the proposed controller compensates for parametric uncertainties, unmodeled dynamics, interaction forces, and communication delays without requiring explicit models of the human operator or the remote environment. The adaptive structure enables real-time learning of unknown nonlinearities while preserving the stability guarantees provided by the underlying control architecture. A theoretical analysis of the closed-loop teleoperation system is developed, demonstrating stability in the presence of human-applied forces, environment interaction forces, and time-varying communication delays. Numerical simulations conducted on two-degrees-of-freedom manipulators validate the feasibility and practical viability of the proposed approach. Different explicit models of the human operator are considered in simulation to assess the sensitivity to operator dynamics. The results show that a bounded dual coordination of force and position is achieved under delayed communication regardless of the assumed operator model, supporting the potential application of the method in real-world teleoperation scenarios.
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Invasion Status, Distribution, and Environmental Preferences of Non-Native Ornamental Thunbergia Species (Acanthaceae) in Ecuador: An Emerging Threat to Tropical Montane Forests
(2026)
Ana Reyes-Hernández
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Ileana Herrera
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Anahí Vargas
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Oleas Gallo, Nora Helena
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Josue Alvarez
Species of the genus Thunbergia, native to Africa, Asia, and Australia, are widely cultivated as ornamental plants; however, their ability to escape cultivation and establish themselves in novel environments poses a growing threat to tropical forests. Here, we provide the first nationwide assessment of Thunbergia species occurring in Ecuador, integrating data from citizen science platforms, herbarium collections, and field surveys. We analyzed spatiotemporal patterns of occurrence, evaluated invasion status based on wild persistence and spread, and assessed environmental preferences using climatic niche analyses. Species distributions were further examined across land-cover types, conservation areas, and forest–non-forest interfaces. We confirmed the presence of five Thunbergia species in Ecuador, two of which also occur in the Galapagos Islands. All species were recorded both in cultivation and in the wild, indicating ornamental horticulture as the main introduction pathway for the genus, and occurrences were documented within 24 conservation areas. Thunbergia alata, T. fragrans, and T. grandiflora were categorized as invasive in Ecuador. Among them, T. fragrans exhibited broad environmental tolerance across bioregions. Wild occurrences were predominantly associated with human-modified landscapes but frequently occurred near forest edges, indicating ongoing encroachment into natural forests. These findings highlight the urgent need for preventive and targeted management strategies, particularly against T. alata, which represents an emerging threat to Andean forest ecosystems.

Centro de investigación en Mecatrónica y Sistemas Interactivos

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