CRIS

Permanent URI for this communityhttps://cris-udd.scimago.es/handle/123456789/1

Browse

Settings

Subject: search.filters.subject.IoT

Search Results

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Monitoring Air Pollutants in Industrial Settings: a Study in Tungurahua, Ecuador
    (2025)
    Lara Calle, Andrés  
    ;
    Jhonathan Espinoza-Tenemaza
    ;
    Buele, Jorge  
    Air quality in work environments is essential for workers’ health, particularly in industrial sectors where processes emit hazardous pollutants. This study, conducted in the province of Tungurahua, Ecuador, assessed air quality across various industrial companies using an IoT device to measure suspended particles (PM1.0, PM2.5, PM10) and other pollutants such as CO2, formaldehyde, and total volatile organic compounds. The goal was to identify variations in pollutant concentrations and evaluate associated health risks. Air quality measurements were conducted using an IoT-based device designed to detect real-time levels of particulate matter and other pollutants. The study focused on different industrial sectors, including plastics production, wood processing, agricultural machinery, car dealerships, and industrial laundries, to provide a comprehensive overview of workplace air quality. The study found that companies involved in plastics, wood, and agricultural machinery production exhibited high levels of particulate matter, with PM1.0 concentrations between 1000 and 2000 μg/m3 and spikes in PM2.5 and PM10 exceeding permissible limits, posing health risks to workers. In contrast, car dealerships and industrial laundries showed significantly lower pollutant levels, suggesting more effective emissions control measures. These findings highlight the need for continuous air quality monitoring and stricter emissions control in high-pollution sectors to safeguard workers’ health. The study also provides a foundation for future research, which should expand to include other sectors and regions in Latin America, where strict air quality regulations in work environments are often lacking.
      17