Facultad de Ingenierías

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Universidad Indoamérica

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Exhaustive Differential Verification of Rule Execution in Building Compliance Software: A Method and Its Application to Seismic Provisions for Earthen Buildings
(MDPI AG, 2026-09-22)
Pinto Almeida, Carlos
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Jordan, Nancy
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Lucio, Diego Ricardo
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Ambato-Jordán, Christopher
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Mendoza, Alvaro Javier
Digital compliance tools increasingly stand between building regulations and the people who apply them, yet research on automated compliance checking has concentrated on whether a rule can be extracted from regulatory text rather than on whether the extracted rule is then executed correctly, so tools issuing compliance verdicts circulate without evidence of computational fidelity. This study proposes a verification method for the large class of provisions stating their requirements as algebraic inequalities over measurable building dimensions. The method combines division-free formalisation, cross-validation against an exact rational oracle, exhaustive enumeration of the discretised design space, differential comparison using asymmetric error classes, and a boundary coverage test suite. It was applied to the wall geometry provisions governing earthen buildings in Peru and Ecuador and to a mobile tool in free circulation. Exhaustive enumeration at the full input resolution of the tool, over 292,364,966,481 configurations, indicates that 7.93 percent of the baseline domain is admissible and that 72.1 percent of inadmissible configurations violate two or more requirements at once. The audit identified three execution defects; the rule sets disagree over 8.26 percent of the domain, and 55.9 percent of the verdicts issued lack normative support. A corrected version reproduced the reference verdict in all 32 device-executed test cases against 24 of 32 for the original, and agrees with the reference on every one of the 292,364,966,481 enumerated configurations. Applying the method to a second provision, the slenderness limit of EN 1996-1-1, reproduces the same defect signature in an unrelated code. Verification of rule execution is therefore inexpensive and necessary before compliance tools can be relied upon on site. The conditions under which the method applies are stated explicitly and are met by provisions in several codes, although transferability beyond the two cases examined remains to be demonstrated empirically. © 2026 by the authors.
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Configuration-Sensitive Decomposition of the Response Modification Factor in Reinforced Concrete Moment Frames
(MDPI AG, 2026-07-10)
Suquillo, Betzabeth
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Villavicencio, Stefanía
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Medina Robalino, Christian David
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Cagua, Brian
The response modification factor R is a fundamental parameter in seismic design, linking the elastic demand expected under strong ground motion to the reduced forces used in practice. It reflects the capacity of well-detailed structures to dissipate energy through stable inelastic behavior while maintaining sufficient strength, stiffness, and deformation capacity to prevent collapse. Accordingly, R directly influences design base shear, member forces, reinforcement demands and expected seismic performance. It is prescribed by seismic codes as a single typology dependent value, although analytical evidence indicates that its magnitude varies systematically with structural configuration. Therefore, this study decomposes R for twelve reinforced concrete moment-resisting frame archetypes that combine three heights (4, 8, and 14 stories) with four span configurations (1–4 spans) over a constant 12 m plan length. All frames are designed per ACI 318-19 and ASCE/SEI 7-22 for the Pedernales, Ecuador, subduction-zone seismic hazard. The response modification factor R is evaluated through a component-based decomposition that separates the effects of ductility, overstrength, and redundancy—namely the capacity ductility (Formula presented.), the demand ductility (Formula presented.), the overstrength (Formula presented.), and a geometric redundancy index (Formula presented.), using bilinearized pushover analyses. Dynamic verification, used here as a consistency check, is explicitly restricted to the low-rise class (four-story frames) through nonlinear response-history analysis under eleven spectrum-matched ground-motion records; results for the 8- and 14-story frames are therefore pushover-based only. To bracket the inelastic reduction capacity, a demand-based companion factor (Formula presented.) is reported and defined as the demand-based counterpart of R, providing a capacity-oriented estimate R and a demand-oriented companion estimate (Formula presented.). R ranges from 3.80 to 14.56, whereas (Formula presented.) ranges from 1.82 to 7.63. The component ranges are the capacity ductility (Formula presented.) – (Formula presented.), the demand ductility (Formula presented.) – (Formula presented.), the overstrength (Formula presented.) – (Formula presented.), and the geometric redundancy index (Formula presented.) – (Formula presented.). Capacity ductility saturates in taller frames (about (Formula presented.) variation). In addition, (Formula presented.) and (Formula presented.) exhibit a mechanical trade-off that challenges the independence assumption implicit in the multiplicative decomposition. Dynamic results corroborate the pushover-implied demand only for the low-rise class; no extrapolation to taller frames is claimed. Overall, the findings motivate configuration-sensitive analytical calibration as a prerequisite for any future normative discussion on R. © 2026 by the authors.
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Artificial intelligence for resilient transportation infrastructure: the first Ecuadorian pavement damage dataset and an assessment of domain transfer across international road networks
(Frontiers Media SA, 2026-08-26)
Zambrano-Salazar, Leonardo
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López, Enma Gamboa
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Pinto Almeida, Carlos
Background Pavement-condition monitoring is a cornerstone of resilient and sustainable transportation infrastructure, yet existing public datasets for automatic damage detection are dominated by data from high-income countries. Deep-learning models trained on those data often transfer poorly to Latin American road networks, where deterioration patterns, materials, and maintenance regimes differ. No publicly available pavement damage dataset for Ecuador has been reported to date, to the best of our knowledge. Methods We present the Ecuadorian Pavement Distress Dataset (EcuPDD), 1,295 images annotated under ASTM D6433 into six damage classes (4,559 annotated instances), collected across seven cities in the three geographic regions of Ecuador (Sierra, Coast, and Amazon). The dataset is released under CC BY 4.0 on Zenodo (DOI: 10.5281/zenodo.20454801 ). On this base we trained five YOLOv8n variants progressively fused with three open international datasets—RDD2022 Japan, RDD2022 China_MotorBike, and McMaster Pavement Crack Detection—for a total corpus of up to 15,941 images (of which roughly 80% were used for training and 20% for validation, following the splits described in Section 3). Each version was trained five times with independent random seeds (25 runs in total), and results are reported as mean ± standard deviation. We evaluated each version on its mixed validation set and, separately, on a fixed 259-image Ecuadorian held-out subset. We complemented the standard mAP50/ mAP50-95 metrics with Wilson 95% confidence intervals on per-class detection rates, a Gini coefficient for class imbalance, and a Domain Gap Index (DGI) that we define as 1 − (mAP50Ecuador/ mAP50general), summarising the divergence between the general and local performance of each model. Results Adding international data lifted the mixed-validation mAP50 from 14.65% (V1, Ecuador only) to 57.66% (V5, Ecuador + McMaster + China_MotorBike), an absolute gain of 43.01 percentage points. However, when evaluated only on the 259 Ecuadorian held-out images, mAP50 stayed between 14.65% and 15.90% across all five versions—a swing of 1.25 pp despite the inclusion of up to 14,646 additional images. The Wilson 95% confidence intervals on those Ecuadorian-only mAP50 values overlap heavily for all versions, indicating substantial overlap and no clear evidence of separation among versions at this sample size. The Domain Gap Index reaches 0.733 for V5 and 0.713 for V2, while remaining ∼0 for V1 and V3. Patching, despite contributing only 2.3% of the instances, reached a Wilson-CI-supported detection rate of 0.78 [0.73, 0.82] thanks to its strong visual distinctiveness when paired with the McMaster dataset. Conclusion International datasets improve a YOLOv8n detector globally but do not, by themselves, close the domain gap to Ecuadorian roads. The bottleneck is the volume and representativeness of local annotated data. EcuPDD provides the first openly licensed Ecuadorian benchmark for this task and an empirical calibration point that researchers in Latin America and other under-represented regions can use to plan dataset-construction and model-development efforts aligned with the resilience and sustainability goals of the AI-for-infrastructure agenda.
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Impact of mixed reality on the care of the elderly: a scoping review
(Springer Science and Business Media LLC, 2026-07-06)
Avilés-Castillo, Fátima
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Buele, Jorge
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Palacios-Navarro, Guillermo
Population aging requires innovative technological strategies that promote autonomy, functionality, and well-being in old age. In this context, mixed reality (MR), a technology that integrates physical and digital elements in a shared and interactive real-time environment, emerges as a promising alternative. To analyze the current state of evidence on the use of MR in the care of older adults, including its theoretical and practical implications. Scientific articles were reviewed in Scopus, Web of Science, PubMed, IEEE Xplore, and EBSCO. Data from 15 studies were organized into an analytical matrix to identify methodological and impact patterns. MR interventions have shown promising preliminary results in physical rehabilitation, cognitive stimulation, emotional well-being, and social interaction by combining sensory feedback, functional tasks, and meaningful experiences. The included studies represent heterogeneous MR configurations along the virtual reality continuum, including transparent or pass-through optical viewers, VR-HMD-based systems with real-world interaction, and sensor- or projection-based platforms. Rather than demonstrating superiority over virtual or augmented reality, the evidence suggests specific advantages related to contextual awareness, physical interaction, and cognitive-motor-affective integration. These features were associated with potential improvements in mobility, executive functions, motivation, positive emotions, and social presence, supporting an interpretive cognitive-motor-emotional framework and the design of safe, meaningful, and context-sensitive interventions. MR shows promising potential for the care of older adults by improving cognitive, motor, emotional, and social outcomes. However, current evidence remains preliminary due to small sample sizes, methodological heterogeneity, a scarcity of comparative studies, and a lack of longitudinal evidence. © The Author(s) 2026.
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Impact of the Integration of Digital Channels on Customer Service in Apparel Stores
(Springer Nature Switzerland, 2026)
Álvarez Sánchez, Ana
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Suárez del Villar, Alexis
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Hidalgo-Potosí, Daniela Alejandra
This study aims to evaluate the impact of integrating digital channels and social networks on customer service in the clothing retail sector. A descriptive and correlational design was used with a random sample of 300 consumers who had interacted with the stores through digital channels in the last six months. Data was collected using a structured questionnaire that assessed customer profile, interaction on digital channels, and customer satisfaction. Descriptive and correlational analyses were performed using statistical software, with the primary evaluation criterion being customer satisfaction, measured using a 5-point Likert scale. The results show that the integration of digital channels increases the satisfaction of very satisfied customers by 26.7%, and 40% of the surveyed consumers expressed a greater willingness to repeat purchases. The correlational analysis revealed a moderate positive relationship (r = 0.56, p < 0.01) between the integration of digital channels and customer satisfaction. Additionally, a reduction in the variability of response times was observed after integration, indicating greater consistency and efficiency in customer service. The questionnaire demonstrated high internal consistency, with a Cronbach's alpha value of 0.84, which ensures the reliability of the measurements. In conclusion, this study demonstrates that the digitalization of customer service in the clothing retail sector significantly improves consumer satisfaction and loyalty, supporting the need for companies to continue innovating in their customer service strategies to maintain a competitive advantage in an increasingly demanding market. These findings have important implications for future research, which could delve deeper into the analysis of the long-term impact of automation on customer relationships and the development of artificial intelligence algorithms that further optimize digital service. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
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Geospatial modeling of urban expansion scenarios and their influence on local development in the Quevedo canton (Ecuador) with a vision towards the year 2030
(Malque Publishing, 2026-08-12)
Muñoz, José Luis
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Sánchez, Jefferson
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Triana, Luis Veas
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Toulkeridis, Theofilos
The urban growth of Quevedo has evolved rapidly due to population growth, economic development, and land-use changes. The current study analyzed such expansion using geospatial modeling, identifying growth patterns and projecting scenarios through 2030. A methodology was based on Markov Chains, involving IDRISI software, integrating geospatial and temporal data obtained from satellite images, official cartography, and socioeconomic records. The application of Geographic Information Systems (GIS) allowed the identification of areas with the greatest potential for urbanization, considering factors such as land use, proximity to road infrastructure, and population density. The results indicated sustained urban growth, with a 32% increase (1,104 ha) in the projected urban area by 2030. At the same time, we yielded a 44.9% reduction in agricultural areas (6,040.4 ha) and a 45.0% reduction in livestock areas (1,360.9 ha), which could generate land-use conflicts and pressure on natural resources. Furthermore, uncontrolled urban expansion was identified as a risk to equitable access to basic services, infrastructure, and security. It was concluded that it is essential to implement sustainable land-use planning strategies that regulate expansion and balance urban growth with environmental conservation and soil productivity. The development of controlled expansion plans that prioritize the provision of basic services and the protection of strategic agricultural zones is recommended, guaranteeing herewith a planned and sustainable urban development. Copyright (c) 2026 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. https://creativecommons.org/licenses/by-nc-nd/4.0/
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Lightweight deep learning for sustainable adobe construction: a block-level baseline aligned with circular economy principles and sustainable development goals
(Frontiers Media SA, 2026-07-08)
Pinto Almeida, Carlos
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Jordan, Nancy
Introduction – The construction sector accounts for nearly 37% of global energy-related CO2 emissions, motivating renewed interest in low-carbon vernacular materials such as stabilized adobe. The integration of recycled inputs into adobe formulations advances circular-economy principles in the built environment, yet large-scale adoption is constrained by the absence of objective, scalable quality-control methods. Methods – We present a methodologically rigorous baseline for AI-driven visual quality control in stabilized adobe construction. A dataset of 330 images was constructed from 55 physical adobe blocks fabricated under controlled laboratory conditions with three circular-economy stabilization mixtures: recycled polyethylene terephthalate (1.5%), sugarcane bagasse fiber (8%), and Portland cement (10%). Each block was photographed from six standardized angles. To eliminate data leakage, we implemented strict block-level data splitting. A MobileNetV2 transfer learning pipeline with frozen ImageNet weights, aggressive data augmentation, L2 regularization, and balanced class weights was developed. Performance was characterized through accuracy with bootstrap 95% confidence intervals, per-class metrics, ROC AUC and Average Precision, five-fold block-level cross-validation, ablation study, and Grad-CAM interpretability. Results – The model achieved 80.95% test accuracy (95% CI: 69.0%–92.9%) on a held-out set of seven physical blocks (42 images). AUC = 0.858 and Average Precision = 0.944. Per-class F1-scores were 0.692 (sound) and 0.862 (defective). Block-level five-fold cross-validation confirmed stability at 70.0% (95% CI: 60.7%–79.2%). Ablation showed: simple CNN 71.43%, MobileNetV2 without augmentation 71.43%, complete pipeline 80.95% (+9.5 pp). Grad-CAM confirmed attention to physically meaningful surface features. The 9.24 MB model footprint enables offline deployment on commodity smartphones. Conclusion – This work establishes a methodologically rigorous baseline for AI-driven quality control in stabilized adobe construction. By demonstrating meaningful performance with modest datasets and edge-deployable architectures, this study supports broader adoption of circular-economy adobe construction and contributes to Sustainable Development Goals 9, 11, 12, and 13. Future work should expand the dataset, evaluate hierarchical classification, and assess field deployment. Copyright © 2026 Pinto Almeida and Jordán Buenaño. Conclusion This work establishes a methodologically rigorous baseline for AI-driven quality control in stabilized adobe construction. By demonstrating meaningful performance with modest datasets and edge-deployable architectures, this study supports broader adoption of circular-economy adobe construction and contributes to Sustainable Development Goals 9, 11, 12, and 13. Future work should expand the dataset, evaluate hierarchical classification, and assess field deployment.
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Rain-Triggered Mass Movement Hazard Assessment of the 2025 Tejar Chimbo Landslide in Andean Ecuador
(Highlights of Science, S.L., 2026-06-16)
Banegas, Fredy
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Salinas, Isela
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Toulkeridis, Theofilos
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Ordoñez-Fernandez, Jose
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Chunga, Kervin
The rainfall-triggered landslide that occurred at the Tejar site in Andean Ecuador on 27 April 2025 (12:35 p.m., local time), provides a representative case for understanding the interaction between extreme precipitation and volcanic geomaterials in slope instability processes. This study aims to characterize the geological and geotechnical conditions controlling the failure and to evaluate the mechanisms associated with rainfall-induced saturation in the Andean foothills of San José de Chimbo. Geological reconnaissance identified three main lithological units: cohesive laharic deposits, massive lapilli tuffs, and andesitic to ignimbritic volcanic rocks. Structural analysis revealed well-defined discontinuity planes, including joint systems and shear fractures with normal components, which extend several meters within the rock mass and act as preferential sliding surfaces. The methodology integrates field mapping, kinematic analysis, aerial photogrammetry, laboratory direct shear testing, and deterministic slope stability modeling using limit equilibrium methods. Additionally, historical precipitation records since 2010 were analyzed and correlated with intense rainfall associated with La Niña Modoki conditions. Results indicate that slope instability is primarily controlled by structurally guided planar failure mechanisms, significantly influenced by rock mass saturation and water infiltration along discontinuity planes. Back-analysis demonstrates that the factor of safety (FS) decreases from stable conditions (FS > 1.2) to values close to failure (FS ≈ 1.0) under fully saturated conditions, consistent with observed field behavior. The landslide evolved into debris flows with runout distances of up to 200 m and variable thicknesses. Based on these findings, mitigation measures including reinforced earth walls (e.g., Terramesh systems), slope regrading with berms, and deep anchoring elements were proposed, resulting in a significant increase in slope stability under both static and pseudo-static conditions. The proposed methodology provides a practical and transferable framework for rapid landslide assessment and mitigation in volcanic terrains, particularly in mountainous urban areas of the Andes and other regions with similar geological and climatic conditions. © 2026 Banegas et al.
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ARLOS: Adaptive Forecasting and Risk-Calibrated Load Operation in Distribution Substations Under Distribution Shift
(MDPI AG, 2026-08-10)
Castillo, Juan Carlos
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Miranda, Alba
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Castillo, Jessica N.
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Naranjo, Jose E.
Forecast accuracy alone is an incomplete proxy for operational value when load distributions change. This paper presents ARLOS, an auditable forecast–uncertainty–decision framework that combines static and adaptive XGBoost forecasts, rolling performance monitoring, residual-bootstrap uncertainty, and explicit fixed-margin, quantile, and risk-target operating rules. The evaluation uses 2021 for ex ante training and capacity-proxy definition and 2022–2023 for strictly sequential testing on two Ecuadorian distribution substations under a measured baseline, smooth growth, and intraday structural shift. Under the four shifted station–scenario cases, adaptive fixed-margin operation reduced the weighted operational objective by 24.8–46.0% relative to the static fixed-margin baseline; baseline-regime changes ranged from (Formula presented.) to 11.2%, showing that adaptation is valuable primarily when mismatch is present rather than universally. A (Formula presented.) ablation further shows that adaptation and uncertainty are distinct, non-additive sources of operational value: aggregate normalized cost changes from 0.987 for static/fixed operation to 0.650 for adaptive/fixed, 0.515 for static/quantile, and 0.546 for adaptive/quantile. Realized one-sided exceedance, computed from observed load rather than from the bootstrap sample itself, remains within 0.0039–0.0111 of the target across the controlled cases, while nominal 10–90% interval coverage ranges from 78.0% to 78.6%. A nine-substation deployment check corroborates the calibration and identifies a measured drift episode in which adaptation limits, but does not eliminate, forecast degradation. The results support ARLOS as a transparent framework for studying how adaptation and uncertainty propagate into operational consequences under distribution shift.These contributions align with Sustainable Development Goal 7 (Affordable and Clean Energy) and Sustainable Development Goal 9 (Industry, Innovation and Infrastructure) by supporting more reliable, efficient, and intelligent operation of electricity distribution infrastructure. © 2026 by the authors.
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Digitalization to Improve Efficiency and Traceability in Personal Protective Equipment Warehouses
(Springer Nature Switzerland, 2026)
Suárez del Villar, Alexis
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Álvarez Sánchez, Ana
Efficient management of industrial warehouses remains a recurring challenge in sectors that rely on strict control of critical supplies, such as personal protective equipment, where manual processes continue to limit inventory accuracy, traceability, and operational responsiveness. In this context, digitalization emerges as a key mechanism for optimizing logistics flows and reducing risks associated with errors in materials management. The main objective of this study was to evaluate the impact of implementing information technologies on the efficiency and traceability of a personal protective equipment warehouse, identifying the operational benefits derived from the automation of recording, control, and tracking processes. A descriptive mixed-methods design was developed, combining direct observation, semi-structured interviews, and document analysis with quantitative measurements taken before and after the technological intervention. The strategy included the incorporation of inventory software, electronic code readers, and digitalized protocols for receiving, dispatching, and replenishment. The primary outcome measure was inventory accuracy, while secondary criteria included traceability, internal request response time, and the reduction of human errors in material registration. Digitalization significantly increased inventory accuracy, showing substantial improvements in the correspondence between physical stock and recorded stock. In addition, traceability demonstrated notable progress by enabling real-time identification of the location and status of supplies, while dispatch and replenishment times were considerably reduced due to the automation of search and verification procedures. Errors associated with duplicated or incomplete records decreased noticeably following digital standardization. In conclusion, the integration of information technologies proved to be an effective tool for improving logistics efficiency and strengthening operational control in personal protective equipment warehouses, confirming the relevance of its adoption in industrial environments seeking to optimize resources, minimize risks, and move toward sustainable management models. These results open the door for future research aimed at analyzing staff satisfaction, budgetary performance, and the scalability of these solutions in larger and more complex organizations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

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