Valencia-Aragón, Kevin
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Valencia-Aragón, Kevin
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Quito

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Evaluating Signage Accessibility for Individuals with Visual Impairments: A Case Study in Ecuador

2024 , Arias Flores, Hugo Patricio , Valencia-Aragón, Kevin , Sandra Sanchez-Gordon , Tania Calle-Jimenez

A signage system is a visual design consisting of identification, guidance, explanation, warning, and other functions through a combination of text, graphics, and color that facilitates the orientation and movement of occupants in buildings by representing explicit information about the configuration and overall structure of the building. In this sense, well-placed signage provides information and significantly influences the search for paths in public spaces, but not all of these spaces meet the conditions of accessibility and inclusion. From this perspective, the general objective of this research is to identify, analyze, and evaluate the shortcomings of signage for individuals with visual impairments based on the requirements and legal regulations in Ecuador. The methodology was based on collecting photographs of signage located in a higher education institution. These photographs were selected in a way that they encompass the most important characteristics of informative signage. The results show that 44.44% comply with the current regulations in Ecuador, and 66.66% comply with the regulations for the inclusion of individuals with low vision. In the future, it is considered to propose a signage system that incorporates technology.

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Optimizing Agriculture with LoRaWAN and HCI: A Smart Approach to Sustainable Farming

2025 , Valencia-Aragón, Kevin , Zapata, Mireya , Cristopher Toapanta , Arias Flores, Hugo Patricio

Modern agriculture faces challenges including water scarcity, excessive fertilizer use, and limited connectivity in rural areas, all exacerbated by climate change. This paper presents a smart agriculture system leveraging LoRaWAN technology and human-computer interfaces (HCI) to address these issues. The proposed system integrates low-cost sensors, a LoRaWAN-based network, and a user-friendly dashboard for real-time monitoring of critical variables such as soil moisture, ambient humidity and temperature. A proof-of-concept implementation demonstrates the system’s effectiveness in optimizing water and fertilizer use while maintaining scalability for large agricultural operations. The system operates reliably within rural environments without relying on traditional internet infrastructure, offering an affordable and sustainable solution. Field tests validate the system’s performance, highlighting its potential to enhance decision-making and resource efficiency in floriculture and beyond. Future work aims to expand the system’s capabilities with additional sensors, artificial intelligence for predictive analytics, and automated control mechanisms, further supporting sustainable farming practices.

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Kiteracy-PiFo: Technological Tool for Teaching the Rules of Grapheme-Phoneme Correspondence

2025 , María de los Ángeles Carpio-Brenes , Jadán Guerrero, Janio , Arias Flores, Hugo Patricio , Valencia-Aragón, Kevin

This study presents Kiteracy-PiFo, a technological tool designed to teach grapheme-phoneme correspondence to preschool students. Combining computer engineering and special education, the tool was developed to enhance Human-Computer Interaction in early literacy education. Despite challenges, including unforeseen events and technical issues, the tool was successfully implemented across schools in Cartago, Costa Rica. Statistical analysis revealed significant differences in vowel recognition between the experimental group using Kiteracy-PiFo and the control group using traditional methods, with the experimental group achieving higher results in less time. These findings suggest that integrating innovative technologies like Kiteracy-PiFo into educational practices can effectively accelerate learning in early childhood settings. However, successful implementation depends on strong pedagogical support and alignment with psychological principles to meet students’ cognitive and emotional needs.

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Environmental Patterns of Phytoplankton Community Composition Across Lentic and Lotic Systems in Ecuador

2026 , Andrés Arévalo-Moreno , Mabel Cadena , Kevin Valencia , Tobes, Ibon

Phytoplankton are key indicators of water quality and low-cost tools for freshwater monitoring, yet their diversity and ecological drivers remain poorly documented in the Tropical Andes. This study provides the first national-scale, multi-ecosystem assessment of net phytoplanktonic communities (including microalgae and cyanobacteria), across Ecuador, integrating physicochemical, multivariate, and geospatial analyses. Eighteen lakes and rivers from three biogeographic regions and a wide altitudinal gradient were surveyed, yielding 129 taxa, 77 identified at species level, the most comprehensive checklist reported to date for Ecuador. Community structure showed a clear lentic–lotic differentiation driven by hydrodynamic contrasts, while the absence of distance–decay patterns indicated high dispersal and environmental filtering pattern rather than spatial structuring. Anthropogenic pressure acted as a secondary gradient: pristine high-Andean lakes were dominated by desmids and diatoms, whereas agricultural and urban basins showed chlorophyte and potentially toxic cyanobacterial assemblages. Palmer’s Index detected organic pollution but underestimated eutrophication in endorheic, geochemically enriched lakes. Land-use effects presented strong basin-scale signals in lakes but weak correlations in rivers due to overriding hydromorphological constraints. These findings establish a robust spatial baseline for freshwater bioassessment in the Andes, demonstrating the value of phytoplankton as effective, low-cost indicators readily applicable to national water-quality assessment programs.

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Low-Cost Non-Wearable Fall Detection System Implemented on a Single Board Computer for People in Need of Care

2024 , Vanessa Vargas , Pablo Ramos , Edwin A. Orbe , Zapata, Mireya , Valencia-Aragón, Kevin

This work aims at proposing an affordable, non-wearable system to detect falls of people in need of care. The proposal uses artificial vision based on deep learning techniques implemented on a Raspberry Pi4 4GB RAM with a High-Definition IR-CUT camera. The CNN architecture classifies detected people into five classes: fallen, crouching, sitting, standing, and lying down. When a fall is detected, the system sends an alert notification to mobile devices through the Telegram instant messaging platform. The system was evaluated considering real daily indoor activities under different conditions: outfit, lightning, and distance from camera. Results show a good trade-off between performance and cost of the system. Obtained performance metrics are: precision of 96.4%, specificity of 96.6%, accuracy of 94.8%, and sensitivity of 93.1%. Regarding privacy concerns, even though this system uses a camera, the video is not recorded or monitored by anyone, and pictures are only sent in case of fall detection. This work can contribute to reducing the fatal consequences of falls in people in need of care by providing them with prompt attention. Such a low-cost solution would be desirable, particularly in developing countries with limited or no medical alert systems and few resources.

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Optimizing Agriculture with LoRaWAN and HCI: A Smart Approach to Sustainable Farming

2025 , Valencia-Aragón, Kevin , Zapata, Mireya , Cristopher Toapanta , Arias Flores, Hugo Patricio

Modern agriculture faces challenges including water scarcity, excessive fertilizer use, and limited connectivity in rural areas, all exacerbated by climate change. This paper presents a smart agriculture system leveraging LoRaWAN technology and human-computer interfaces (HCI) to address these issues. The proposed system integrates low-cost sensors, a LoRaWAN-based network, and a user-friendly dashboard for real-time monitoring of critical variables such as soil moisture, ambient humidity and temperature. A proof-of-concept implementation demonstrates the system’s effectiveness in optimizing water and fertilizer use while maintaining scalability for large agricultural operations. The system operates reliably within rural environments without relying on traditional internet infrastructure, offering an affordable and sustainable solution. Field tests validate the system’s performance, highlighting its potential to enhance decision-making and resource efficiency in floriculture and beyond. Future work aims to expand the system’s capabilities with additional sensors, artificial intelligence for predictive analytics, and automated control mechanisms, further supporting sustainable farming practices

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Learning Through Play: Implementing an Educational Escape Room for Teaching Traditions and Culture

2025 , Valencia-Aragón, Kevin , Arias Flores, Hugo Patricio , Zapata, Mireya , Luis Aguirre-Morales , Sandra Sanchez-Gordon

This study explores the implementation of an educational Escape Room as a pedagogical strategy to teach tangible cultural heritage to students in Ecuador. This Escape Room was designed using the ADDIE model (Analysis, Design, Development, Implementation and Evaluation) and integrated into the basic education curriculum for Ecuadorian schools. The primary objective was to enhance students’ engagement and understanding of Ecuador’s cultural heritage through an interactive and gamified learning experience. The Escape Room was structured around five missions, each focusing on different aspects of the cultural heritage of five parishes in Ecuador. Students were required to solve puzzles, answer questions, and complete challenges to progress through the game. The results of the implementation, evaluated through observation and student feedback, indicated a high level of student engagement, improved problem-solving skills, and a deeper appreciation for Ecuador’s cultural heritage. The study concludes that Escape Rooms can be an effective tool for teaching cultural heritage, fostering teamwork, creativity, and critical thinking among students. This innovative approach not only makes learning more dynamic and enjoyable but also aligns with modern educational trends that emphasize active and experiential learning.

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Eye-Tracking and Pictograms: Improving Communication and Accessibility for Senior Adults

2024 , Arias Flores, Hugo Patricio , Valencia-Aragón, Kevin , Sandra Sanchez-Gordon

An important factor in exploring the world around us and understanding the cognitive process of individuals is analyzing the characteristics and behavior of the eyes, as they provide reliable information. Improving communication processes with users through visual communication environments can create an accessible environment for virtual interaction. In this context, the global population is aging at a faster rate, leading to social transformation. This population segment may face challenges with language skills, health issues, psychological disorders, and traumas that can limit their ability to speak or move. The purpose of this study is to investigate whether eye-tracking, using the eye-tracking device, will enable senior adults to interact with their caregivers through a pictogram-based interface, allowing them to generate messages and communicate their needs. The research method involves the conceptual development of an experiment designed for senior adults, including the use of an eye-tracking device, calibration tests, and interface responses. This research aims to better understand and promote the importance of meeting the needs and expectations of the elderly segment.

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Indoor Monitoring System Based on Computer Vision for Fall Detection Oriented to Elderly Assistance

2025 , Vanessa Vargas , Pablo Ramos , Zapata, Mireya , Myriam Estrella , Valencia-Aragón, Kevin

This work aims to evaluate a non-wearable fall-detection system for indoor activities of older adults. The computer vision proposal uses a Convolutional Neural Network (CNN) architecture using the lightweight SSD-MobileNet-V2 model. Transfer learning techniques were applied to develop this approach. During the training process, a combined dataset conformed by the UR Fall Detection and an own dataset was used. Verification tests were performed under diverse scenarios, participants, and platforms to provide greater reliability to the evaluation results. Different distances from camera to person, lighting levels, attire, participant’s gender, and age were considered. For evaluation purposes, two platforms were selected: one based on a Single Board Computer (SBC) and the second on a laptop computer. Results show an accuracy of 95.5%, a precision of 99.4%, a sensitivity of 91.6%, and a specificity of 99.5% when executing the approach on a SBC. On the other hand, when the approach runs on a laptop, it achieves an accuracy of 96.6%, a precision of 97.3%, a sensitivity of 96.0%, and a specificity of 97.4%. Lastly, the system sends an alert notification when a fall is detected through a messaging platform. This event supports effectively medical assistance in reducing fatal consequences, especially for older adults living alone

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Microplastics in Two Tropical Andean Lakes: Contrasting Human-Impacted and Minimally Disturbed Watersheds

2026 , Andrés Arévalo-Moreno , Silvana Gallegos-Sánchez , Kevin Valencia , Tobes, Ibon

Microplastics (MPs) are emerging contaminants in freshwater systems, yet their sources and transport pathways in tropical high-altitude lakes remain poorly understood. This study quantified and characterized MPs in two Andean lakes in Ecuador with contrasting watershed conditions: San Pablo (2672 m a.s.l.), influenced by agricultural and urban land use, and Caricocha (3724 m a.s.l.), a protected high-Andean lake. Sixteen samples per lake were collected during four field campaigns. MPs were identified using visual and morphological criteria, and classified by shape, color, and size. MP concentrations were higher in San Pablo (238 ± 32 MP m−3, mean ± SD) than in Caricocha (32 ± 10 MP m−3). Fibers dominated (87.3%), followed by fragments, while microspheres were detected only in Caricocha. MP concentrations showed positive correlations with urban-agricultural land use (ρ = 0.87, p < 0.0001) and negative correlations with natural vegetation cover (ρ = −0.87, p < 0.0001). Principal Component Analysis linked fiber abundance and small size classes (<500 µm) and anthropogenic land use, consistent with surface runoff and wastewater-associated pathways. In contrast, MPs in the protected lake may originate from long-range atmospheric deposition. These results indicate that watershed configuration and protection status shape MP inputs in high-Andean lakes.

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