Centro de investigación en Mecatrónica y Sistemas Interactivos

Parent Organisation

Universidad Indoamérica

Country

Now showing 1 - 10 of 523

Some of the metrics are blocked by your
consent settings
IoT Architecture Prototype for Real-Time Monitoring and Control in a Simulated Automation Environment
(Springer Nature Switzerland, 2026)
Chuchico, Cristian P.
;
Semanate, Clinton
;
Chicaiza Claudio, Fernando
;
Pilatásig, Marco
The Internet of Things (IoT) has become a fundamental element for digital transformation in industry, boosting efficiency, security, and innovation. This paper presents an IoT architecture designed for real-time monitoring and control of a virtual level station, addressing critical challenges in industrial automation. The level process is simulated using Factory IO and regulated by a control algorithm developed in TIA Portal V16, executed via PLC Sim Advanced. Data is acquired by Node-RED from the PLC and transmitted to an MQTT broker, while a dashboard hosted on Ubidots enables remote access. Historical data of key parameters is recorded to facilitate detailed analysis of process behavior. Its flexible design allows the simulated process to be easily replaced or expanded with additional sensors and parallel processes, providing significant scalability for future applications. Results show a 55ms response time, data transmission with less than 100ms latency (PLC to cloud), and system integrity during network failures. Based on the Industrial Internet Reference Architecture (IIRA), this system provides a replicable framework for Industry 4.0 implementations, particularly in: Digital twin development, safe operator training, and cost-effective modernization of existing systems. © 2026, Springer Science and Business Media Deutschland GmbH. All rights reserved.
Some of the metrics are blocked by your
consent settings
Designing the UI/UX of a Gamified Platform to Raise Awareness About Water Conservation Using the User-Centered Design Method
(Springer Nature Switzerland, 2026)
Jadán Guerrero, Janio
;
Arias Flores, Hugo Patricio
;
Piedra Ansatuña, Mario
;
Sanchez-Gordon, Sandra
;
Acosta-Vargas, Patricia
Water conservation and responsible usage are critical to ensuring the sustainability of life on Earth. Raising awareness about these practices is essential to fostering behavioral changes in everyday life. This study aimed to design a gamified environment, integrating both digital and physical mediums, to promote awareness of water conservation. The proposed solutions included digital games, board games, interactive maps, and card games, blending entertainment with education. The research employed the Game Thinking methodology, involving ten master’s students specializing in user experience design. The process adhered to the principles of user-centered design across all phases. Initially, the problem of water scarcity was explained to participants, who subsequently proposed design concepts tailored to this issue. These concepts were developed into prototypes and tested with users representative of the intended age groups. Preliminary results from the first usability tests revealed areas for improvement. Feedback from peer reviews highlighted the need to enhance narrative elements, interface design, usability, and accessibility. Iterative refinements based on this feedback significantly improved the prototypes’ alignment with the project’s educational objectives. In conclusion, the study demonstrated the potential of gamification as a powerful tool for promoting water conservation awareness. Future work will focus on completing functional prototypes and evaluating their impact in real-world settings to measure their effectiveness in instilling responsible water usage behaviors
Some of the metrics are blocked by your
consent settings
The hierarchical scaffolding model of executive functioning in university students: a self-reported explanatory approach
(Frontiers Media SA, 2026-07-29)
Díaz-Guerra, Diego D.
;
Hernández-Lugo, Marena de la C.
;
Ramos-Galarza, Carlos
;
Broche-Pérez, Yunier
;
Arias Flores, Hugo Patricio
Introduction Executive functions are cognitive processes that are fundamental to academic success among university students. However, most explanatory models have been developed using laboratory-based tasks, which limits their ecological validity. Self-report measures offer a complementary approach by capturing perceived executive functioning in real academic contexts. Objective To construct and validate an explanatory model of executive functioning in Cuban university student Methods A cross-sectional sample of 1,233 students was analyzed (mean age = 20.08 years, SD = ±1.02; 59.3% women). The Cuban adaptation of the UEF-1 was administered. Analyses combined decision trees using the CHAID method to identify predictors and structural equation modeling (SEM) to confirm the relationships among variables and construct a unified model. Results The final model showed satisfactory fit (CFI = 0.915, RMSEA = 0.048, SRMR = 0.045). Executive functions were organized into four hierarchical levels: (1) Metacognitive Evaluation and Supervision, comprising Conscious Monitoring of Responsibilities and Behavioral Verification for Learning; (2) Emotional and Behavioral Regulation, comprising Conscious Regulation of Emotions and Conscious Regulation of Behavior; (3) the Operational Attentional System; and (4) Goal-Directed Action and Task Resolution, comprising Decision-Making and Management of Elements to Solve Tasks. Conclusion The proposed model constitutes the first unified explanatory framework of executive functioning in Cuban university students, specifically as assessed through self-report measures. Its four-level hierarchical structure provides an empirically grounded guide for future research and interventions, capturing the subjective dimension of executive performance as a complementary and ecologically relevant level of analysis closely tied to academic adaptation and self-regulation.
Some of the metrics are blocked by your
consent settings
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
;
Del-Valle-Soto, Carolina
;
Acevedo-Parra, H. R.
;
Montoya-Márquez, Orlando
;
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.
Some of the metrics are blocked by your
consent settings
Channel-Specific Stimulus Sensitivity, Reliability, and Complementarity of Multimodal Wearable Sensing During Short-Form Influencer Video Exposure
(MDPI AG, 2026-10-08)
Del-Valle-Soto, Carolina
;
Corona, Violeta
;
Gómez Padilla, Regina
;
Walls Fernández, Fátima Sofía
;
López-Pimentel, Juan-Carlos
Multimodal wearable sensing is increasingly used to quantify audience engagement with short-form video, yet it remains unclear which sensing channels actually carry stimulus-driven information at the exposure durations typical of this format. We recorded electrodermal activity, photoplethysmographic pulse, triaxial acceleration, video-based eye tracking, and automated facial expression analysis from 50 young adults while they viewed 20 short-form influencer clips (5.6–19.3 s) presented in individually randomized order, yielding 1000 participant × clip trials and 12 primary indices spanning four modalities. Using crossed random-effects variance partitioning, split-half reliability with Spearman–Brown projection, permutation-based multivariate testing, participant-wise decoding, and inter-subject correlation, we show that stimulus-driven variance is strongly channel-specific: it reaches 13.7% for fixation rate and 10.2% for facial engagement but only 0.11% for pulse rate and 0.23% for RMSSD. Clip-level estimates were highly reliable for facial and oculomotor indices ((Formula presented.) – (Formula presented.)) and poor for autonomic indices ((Formula presented.) – (Formula presented.)), which would require 134–370 participants to reach (Formula presented.). Between-modality dependence was almost six times weaker than within-modality dependence, and five components were retained by parallel analysis. Oculomotor and facial features jointly identified individual clips at 16.8% balanced accuracy against a 5% chance level, whereas electrodermal and pulse features, taken separately, did not exceed chance. Electrodermal responses were nonetheless stimulus-locked in 18 of 20 clips. A per-second re-analysis of nine channels showed that the ordering partly reverses for within-clip dynamics: tonic electrodermal and pupil time courses were reliable across viewers ((Formula presented.) and (Formula presented.)), facial time courses were not ((Formula presented.)), and pulse rate was unreliable under both treatments. We derive explicit design guidance for sensor selection and sample size in short-exposure multimodal engagement studies. © 2026 by the authors.
Some of the metrics are blocked by your
consent settings
A Cyclical Action Research Approach to Active Learning in Data Structures
(IEEE, 2026-07)
Aguas-Bucheli, Luis
;
Zapata, Mireya
;
Acosta-Vargas, Patricia
;
Ponce-Villacis, Paulina
;
Amoroso-Garcés, Sylvia
The teaching of Data Structures in the Software Engineering program poses a fundamental challenge in the development of core algorithmic thinking and problem-solving skills. This article reports on an educational innovation experience implemented during the fourth semester of the program, which integrates Active Learning strategies with iterative Action Research cycles tailored to the specific demands of the subject. The pedagogical intervention is grounded in participatory and gamified methodologies, with a strong emphasis on professional practice and real-world application. By fostering student engagement through interactive problemsolving activities, code-based challenges, and collaborative learning environments, the experience aims to enhance both academic performance and the meaningful understanding of data structures. The results of the implementation revealed significant improvements in students' motivation, practical competencies, and their ability to apply data structures contextually to solve complex programming problem © 2026 IEEE.
Some of the metrics are blocked by your
consent settings
From Simulation to Reality: A Digital Twin Implementation of a 4-DOF Robotic Manipulator
(2025)
Bryan S. Guevara
;
Varela Aldas, José
;
Viviana Moya
;
Angéelica Veróonica Quito Carrióon
;
Marcelo Ortiz
Some of the metrics are blocked by your
consent settings
Bridging Two Worlds: Sensor Technologies and AI for Fruit Detection in Latin America and Beyond—A Scoping Review
(MDPI AG, 2026-08-10)
Parrales-Bravo, Franklin
;
Gracia-Chinga, Joan
;
Jadán Guerrero, Janio
;
Vasquez-Cevallos, Leonel
;
Cevallos-Torres, Lorenzo
This scoping review synthesizes 35 studies on sensor technologies and artificial intelligence for fruit detection, classification, and quality assessment, contrasting Latin American and international research traditions. The analysis suggests notable differences in technological approaches between the included Latin American and international studies: Latin American research tends to emphasize in developing accessible, practical solutions using classical computer vision and low-cost hardware, while international studies more frequently employ through deep learning architectures, multi-modal sensing, and complete robotic automation systems. Across the included studies, relatively limited attention was given to AI-assisted decision support for agricultural practitioners, insufficient consideration of inclusivity, and the scarce integration of environmental sustainability into intelligent sensing system design. The review identifies that only 8 of 35 studies originate from Latin America, suggesting an uneven geographical distribution of the available evidence. The included studies generally reported high accuracy values, yet these findings must be interpreted with caution given the reliance on curated datasets that may not represent real-world variability. The reviewed evidence suggests that future research may benefit not from one approach dominating the other, but from a thoughtful integration of complementary strategies, including knowledge transfer, edge computing democratization, and human-centered design. Overall, this review suggests that the ultimate goal extends beyond accuracy metrics to the transformation of agricultural practices that enhance food security, economic development, and environmental sustainability across the global agricultural landscape. It is important to note that this work does not propose or validate a new fruit detection algorithm but rather synthesizes and critically evaluates existing scientific evidence regarding sensor technologies and artificial intelligence applied to fruit detection and quality assessment. © 2026 by the authors.
Some of the metrics are blocked by your
consent settings
Experimental and data-driven evaluation of transport-layer and application-layer security for MQTT-based IoT networks
(Elsevier BV, 2026-12)
Del-Valle-Soto, Carolina
;
Alvarez-Garcia, Maria Fernanda
;
Valdivia, Leonardo J.
;
Del-Puerto-Flores, José A.
;
Varela Aldas, José
The rapid expansion of Internet of Things (IoT) deployments has intensified the need for secure and efficient communication mechanisms tailored to resource-constrained devices. Message Queuing Telemetry Transport (MQTT) is widely adopted due to its lightweight design; however, it lacks native security support, requiring external protection mechanisms that may significantly affect system performance. This paper presents a comprehensive experimental and data-driven evaluation of two security paradigms for MQTT-based IoT networks implemented on ESP32 microcontrollers: transport-layer security using TLS and application-layer encryption based on elliptic curve cryptography (ECC) for key exchange combined with AES symmetric encryption. The analysis jointly evaluates memory utilization, end-to-end latency, energy consumption, and resistance to passive traffic interception under identical experimental conditions. In addition to conventional metric-based comparisons, multivariate statistical analysis and unsupervised learning techniques are employed as exploratory tools to characterize the system-level behavior induced by each security scheme. Results show that Transport Layer Security (TLS) offers stronger confidentiality guarantees at the cost of higher memory overhead, while the ECC–(Advanced Encryption Standard) AES approach significantly reduces memory footprint with moderate latency penalties and comparable energy consumption. Multivariate analysis further reveals that each security mechanism induces a distinct performance regime, providing a compact joint characterization of the security–performance trade-offs across the evaluated configurations.
Some of the metrics are blocked by your
consent settings
Low-Cost IoT System with Containerized AI and Telegram Bot for Real-Time Air Quality Risk Communication and Preventive Behavior Change
(Springer Nature Switzerland, 2026)
Zapata, Mireya
;
Álvarez-Tello, Jorge
;
Rugel-Sanchez, Keyla
;
Vargas-Bustamante, Miguel
Air pollution constitutes one of the main environmental risk factors for public health, particularly in urban environments with limited real time monitoring infrastructure. Although low-cost IoT architectures have emerged as scalable alternatives to extend the spatial coverage of measurements, many implementations lack statistically validated risk classification models capable of translating the environmental data into information to service the public. This study presents the development and statistically validates in real time a risk index for air quality, implemented though a low-cost IoT architecture which integrates supervised artificial intelligence (AI) models deployed at the edge. The system was implemented for eight weeks the Universidad de Guayaquil campus, taking records of PM2.5, PM10 concentrations, temperature and humidity using calibrated sensors. The classification model based on Classification and Regression Trees reached a global accuracy greater which surpassed 90%, with 91.7% concordance to data retrieved from official stations for moderate conditions of PM2.5. K-fold method was used during the validation process and direct comparison with certified infrastructure. Additionally, user evaluation (n = 85) showed 82% adoption of preventive behavior after the implementation of proactive communication with a conversational bot. The results show that the integration of the presented low-cost IoT with validated risk models and user focused communication can generate reliable environmental intelligence and supports preventive decision-making in urban contexts with infrastructure constraints.

Centro de investigación en Mecatrónica y Sistemas Interactivos

Filters

Settings

Sort By

Results per page