Now showing 1 - 10 of 38
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    Item type:Publication,
    Low-Cost Interfaces and Technological Accessibility: A Human–Computer Interaction Approach for the Inclusion of Individuals with Motor Disabilities
    Cerebral palsy (CP) is a neurological disorder of prenatal or perinatal origin that affects motor control, posture, and frequently speech, thereby limiting autonomy and social participation among individuals who experience it. During the transition to adulthood, these limitations tend to intensify, highlighting the need for assistive technologies (AT) that effectively address real-world contexts of use. However, the high cost and limited adaptability of many existing solutions restrict their adoption, particularly in low- and middle-income countries. This study is situated within the field of Human–Computer Interaction (HCI) and aims to evaluate low-cost input devices based on principles of accessibility, ergonomics, and usability, to improve the work performance of individuals with motor disabilities. A qualitative methodology was employed, based on the think-aloud technique, applied to a case study involving an adult with cerebral palsy who interacted with three devices: a conventional trackpad, a MAKEY MAKEY-based interface, and a wireless keyboard with an integrated touchpad. The results indicate that, although the trackpad allows for a degree of progressive adaptation, it presents limitations in tasks requiring bimanual coordination. The MAKEY MAKEY interface provides greater discrete control but demands high levels of coordination and generates fatigue due to its physical configuration. In contrast, the wireless keyboard with an integrated touchpad emerges as the most efficient and ergonomic alternative, as it distributes functions between both hands and reduces physical effort. It is concluded that the adaptation of mass-market consumer technologies, under a user-centered design approach, can offer accessible, functional, and sustainable solutions for the digital inclusion of individuals with motor disabilities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
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    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) ;
    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.
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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
    ;
    ;
    García-Muñoz, Gabriel
    ;
    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
    ;
    Martinez, Danilo
    ;
    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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    The Biometric Imperative: Low-Cost Facial Recognition to Counter Critical Access Vulnerabilities in High-Insecurity Contexts
    (Springer Nature Switzerland, 2026) ;
    Vargas-Bustamante, Miguel
    ;
    Cevallos-Sornoza, Angie
    ;
    Álvarez-Tello, Jorge
    Rising insecurity in Ecuador, especially on urban areas of Guayaquil, has exposed the high vulnerability of public and educational institutions to unauthorized access. Conventional security control measurements base on physical credentials, or passwords have proved to be insufficient, driving the need for technological solutions for secure access control. In this context, facial recognition has emerged as a feasible biometric solution, even though its implementation gets limited when applied to resource-constrained environments. This study presents and validates an access control system developed with accessible and budget-friendly hardware, open-source tools, aimed at strengthening security in vulnerable spaces. The research adopted a quantitative, experimental, and applied approach, evaluating prototype performance through indicators of operational reliability, correct authentication rate, and rejection of unauthorized attempts under diverse environmental conditions. Results show that the system achieved an identification success rate of 97% of legitimate users and blocked 95% of non-authorized attempts, with an average response time of under two seconds and high resistance to basic spoofing attempts. These findings confirm that low-cost biometric solutions can achieve satisfactory levels of security and usability, contributing to the democratization of technology and offering a replicable and ethical alternative for educational institutions in high-insecurity contexts
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    Item type:Publication,
    Planning and Management of Fiber Optic Networks Based on a Geographic Information System: A Case in Ecuador
    (2025)
    Miguel Vargas-Bustamante
    ;
    ;
    Jorge Álvarez-Tello
    Lean management contributes to pursuit the quality, accessibility and efficiency of healthcare institutions. Its importance of the implementation of lean management in the healthcare sector using different strategies to improve services like: the supply chain in hospitals. In this review was used the model proposed by seuring and gold based on the analyze a sample of articles indexed in Scopus, web of science and also the simulation tool was used to in order to illustrate the approach. After implementation of lean thinking in different hospital in some countries improves the structure, process and outcome of care and management actions and management in healthcare promotes advantages in terms of quality, safety and efficiency of healthcare in hospitals
      9
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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
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    Pablo Ramos
    ;
    Edwin A. Orbe
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    ;
    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.
      11
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    Optimizing Agriculture with LoRaWAN and HCI: A Smart Approach to Sustainable Farming
    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.
      24
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    Item type:Publication,
    Digital Marketing Strategy for B2B Metalworking Industry: A Case Study for Ecuador
    (2025)
    Cruz Cusme-Palma
    ;
    Jorge Alvarez-Tello
    ;
    In a global environment where digitalization is key to competitiveness, B2B companies in the metalworking sector face challenges in adopting digital tools. In Ecuador, the low digital presence of small and medium-sized enterprises limits their ability to attract clients and expand. This study analyzes the case of Manufacturas ESCA Cía. Ltda., an Ecuadorian company with no digital presence, which requires a digital marketing strategy to improve its visibility and market positioning. The research follows a mixed-method approach, combining qualitative and quantitative methods within a non-experimental, descriptive design. Strategic analysis tools such as SWOT, PESTEL, and CANVAS were applied, along with digital audits and keyword research using Google Keyword Planner, Semrush, and Tubular. Additionally, SEO, SEM, social media, and email marketing strategies were integrated into a comprehensive digital marketing plan. The projected results indicate that the strategy will help increase website traffic to 7,000 annual visits, generate 1,200 leads, and achieve an estimated revenue of $183,814.16 in the first year, with a positive return on investment. It is concluded that implementing digital strategies not only enhances visibility and customer acquisition but also strengthens the competitiveness and sustainability of industrial companies in emerging digital markets. Digital transformation is a strategic necessity for B2B companies aiming to optimize their positioning and growth in the digital era.
      20
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    Item type:Publication,
    Low-Cost Human–Machine Interface for Computer Control with Facial Landmark Detection and Voice Commands
    (2022)
    Ramos, P.
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    ;
    Valencia, K.
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    Vargas, V.
    ;
    Nowadays, daily life involves the extensive use of computers, since human beings are immersed in a technological society. Therefore, it is mandatory to interact with computers, which represents a true disadvantage for people with upper limb disabilities. In this context, this work aims to develop an interface for emulating mouse and keyboard functions (EMKEY) by applying concepts of artificial vision and voice recognition to replace the use of hands. Pointer control is achieved by head movement, whereas voice recognition is used to perform interface functionalities, including speech-to-text transcription. To evaluate the interface’s usability and usefulness, two studies were carried out. The first study was performed with 30 participants without physical disabilities. Throughout this study, there were significant correlations found between the emulator’s usability and aspects such as adaptability, execution time, and the participant’s age. In the second study, the use of the emulator was analyzed by four participants with motor disabilities. It was found that the interface was best used by the participant with cerebral palsy, followed by the participants with upper limb paralysis, spina bifida, and muscular dystrophy. In general, the results show that the proposed interface is easy to use, practical, fairly accurate, and works on a wide range of computers. © 2022 by the authors.
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