Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Rubén Baena-Navarro
Universidad de Córdoba
Computer Science & IT Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
IoT-based drinking water quality measurement: systematic literature review Yulieth Carriazo-Regino; Rubén Baena-Navarro; Francisco Torres-Hoyos; Juan Vergara-Villadiego; Sebastián Roa-Prada
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp405-418

Abstract

Sustainable development throughout the world depends on several factors such as the economy, quality education, agriculture, industry, among others, but the environment is one of the most important. Industrialization and new land use plans have caused the proliferation of pollutants in water resources, which poses a serious public challenge. As outlined in the sustainable development goals (SDGs), innovative water quality monitoring methods are needed to ensure access to water, sustainable management and sanitation. In this sense, technologies are sought that contribute to the development and implementation of groundwater and surface water quality monitoring systems in real time, so that their parameters can be evaluated through descriptive analysis, in rural populations and areas of difficult access. Nowadays, the internet of things (IoT) and the development of modern sensors are more used, so this research reviews the latest technologies to monitor and evaluate water quality using the potential and possibilities of the IoT. The main contribution of this article is to present an overview of the state of the art of IoT applications and instrumentation for water quality monitoring, focusing on the latest innovations, in order to identify interesting and challenging areas that can be explored in future research.
Implementation and feasibility of green hydrogen in Colombian kitchens: an analysis of innovation and sustainability Jhon Vidal-Durango; Rubén Baena-Navarro; Kevin Therán-Nieto
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp726-744

Abstract

This study explores the potential of green hydrogen as a sustainable energy solution in domestic cooking, focusing on Colombia. It employs a systematic literature review following the PRISMA framework, analyzing articles published between 2018 and 2023 to assess the feasibility and challenges of implementing green hydrogen in the culinary sector. The research emphasizes the projected growth in the demand for clean hydrogen, particularly in the industrial sector by 2030 and in new applications by 2050, with an estimated increase from less than 1% currently to about 30% of the total hydrogen demand. It is anticipated that green hydrogen production will dominate the global supply mix by 2050, reflecting a share of between 50% and 65% in various scenarios. The study concludes that while green hydrogen holds great potential for transforming Colombia's energy matrix towards a cleaner, more sustainable future, it faces significant regulatory and technical challenges that require concerted, collaborative action, aligning with the sustainable development goals.
Interpretable artificial intelligence system for personalized cognitive stimulation Rubén Baena-Navarro; Yulieth Carriazo-Regino; Mario Macea-Anaya
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp164-176

Abstract

The growing need to preserve cognitive health in aging populations has intensified interest in adaptive digital interventions that provide personalized and interpretable support. This study presents a web-based cognitive stimulation system for older adults integrating a multilayer perceptron (MLP) classifier, expert-derived symbolic rules, and explainable artificial intelligence (XAI) techniques, including Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME). The platform was evaluated through a 24-week intervention involving 150 participants aged 65 years and older, combining baseline cognitive profiling, rule-guided recommendation logic, and neural prediction to support individualized task allocation. Compared with a control group, participants in the intervention arm showed statistically significant improvements in cognitive outcomes (p <0.05), with measurable gains in memory- and attention-related tasks. The explainability component enabled examination of model behavior at the level of individual features through feature attribution analysis and symbolic consistency checks, supporting interpretation beyond aggregate performance metrics. Unlike approaches dependent on high-end extended reality (XR) infrastructures or game centered interaction, the system was implemented to operate under low connectivity conditions and was tested with participants from diverse educational backgrounds. This hybrid configuration provides an interpretable basis for cognitive support initiatives adaptable to community settings contexts.
Co-Authors Francisco Torres-Hoyos Jhon Vidal-Durango Juan Vergara-Villadiego Kevin Therán-Nieto Mario Macea-Anaya Sebastián Roa-Prada Yulieth Carriazo-Regino Yulieth Carriazo-Regino