Article Per Year (5 Year)
p-Index From 2021 - 2026
1.652
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Vladimir Henao-Cespedes
Universidad Católica de Manizales
Computer Science & IT Electrical & Electronics Engineering

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Analysis of electromagnetic pollution by means of geographic information system Vladimir Henao-Cespedes; Yeison Alberto Garcés-Gómez
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5099-5106

Abstract

Currently, telecommunications systems have become more widespread and there is still a discrepancy between whether or not non-ionizing radiation produces health problems in living beings at cellular level. From an experimental point of view, it is interesting to raise the correlation of high levels of electromagnetic pollution with health problems in urban populations which would make it possible to clearly determine the effects of this type of radiation on human health and the environment. By means of remote sensing, a geographic information system (GIS) has been developed for the analysis of electromagnetic pollution levels generated by emissions from non-ionizing radiation (NIR) sources in a city. A method for measuring electromagnetic pollution was applied, which allows the generation of a table of attributes of the GIS that is the input to generate by inverse distance weighting (IDW), the layer of electromagnetic pollution. The method, as a case study, was applied in the city of Manizales, located in Colombia, obtaining as a result a layer that allows evidence that the highest levels of electromagnetic pollution are concentrated in the most central area of the city. In this way, the effects of NIR on public health can be analyzed by means of correlations.
Electromagnetic pollution maps as a resource for assessing the risk of emissions from mobile communications antennas Yeison Alberto Garces-Gomez; Vladimir Henao-Cespedes; Luis Fernando Diaz-Cadavid
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1063.66 KB) | DOI: 10.11591/ijece.v10i4.pp4244-4251

Abstract

Electromagnetic pollution has taken on importance in recent decades, as interest is growing in knowing how the proliferation of mobile communication devices can affect the environment and generate health problems in the population. In this document, a systematic review of the methodologies for measuring electromagnetic radiation is carried out with a view to generating pollution profiles. It also develops a novel methodology for measuring electromagnetic pollution (EMP) in urban areas, and is validated with a case study using a map of EMP in the city of Manizales (Colombia), determining the spatial distribution of radiation levels. In order to generate the map, EMP measurements were carried out in the bands of local mobile telephone operators, in addition to the LPWAN (low power wide area network) LoRaWAN and Sigfox networks, Wi-Fi, and those related to IoT technologies.
Landslide early warning systems: a perspective from the internet of things Vladimir Henao-Céspedes; Yeison Alberto Garcés-Gómez; María Nancy Marín Olaya
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2214-2222

Abstract

Populations located in the vicinity of slopes and soils derived from volcanic ash are constantly at risk due to the possibility of landslides. Such is the case of the city of Manizales, Colombia, which, due to its geomorphological characteristics, has experienced a significant number of landslides that have caused human and economic losses. The Internet of things (IoT) has allowed important technological advances for monitoring, thanks to the low cost and wide coverage of IoT-based systems. Slope monitoring and the development of landslide early warning systems (EWS) have been positively impacted by IoT developments, which shows a relationship. The objective of this article is to review, from the scientific production, the relationship between IoT and EWS. For this purpose, a fragmenting-deriving-combining methodology is applied to focus on a research trends analysis of the subject, from macro-areas such as IoT and EWS to micro areas such as EWS by IoT-based landslides. Finally, the analysis concluded that the conceptual models of IoT and EWS for landslides have some correspondence in some of their layers.
International Journal of Electrical and Computer Engineering: a bibliometric analysis Yeison Alberto Garcés-Gómez; Vladimir Henao-Céspedes
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp5667-5673

Abstract

This study is focused on analyzing seven years of bibliometric data of the International Journal of Electrical and Computer Engineering (IJECE) from 2014 to 2020. The analysis of 2,928 papers exhibits multi-folded growth of 34.25%, rising from 109 articles in 2014 to 638 articles by 2020. In addition, the analysis of the structure of publications as well as the mapping of bibliographic data based on co-citation, bibliographic coupling, and co-occurrence showed the intellectual structure and connection between universities, countries, and contributing authors. As the journal’s first retrospective, this study not only educates and enriches IJECE’s global readership and aspiring contributors, but may also be useful to its editorial board, as it provides several inputs for navigating future research.
Bibliometrics on the use of remote sensing and machine learning in crop classification Andrea del Pilar Sánchez-Chavez; Vladimir Henao-Cespedes; Yeison Alberto Garcés-Gómez
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10476

Abstract

This study presents a bibliometric analysis of global research on crop classification using remote sensing and machine learning (ML), a field critical to advancing precision agriculture. A systematic search in Scopus identified 2,122 peer-reviewed articles published between 2014 and 2023. The analysis employed VOSviewer and the Bibliometrix package in R to assess publication trends, citation impact, and keyword co-occurrence networks. Results reveal a marked increase in scientific production after 2017, coinciding with the availability of high-resolution satellite imagery and the adoption of deep learning algorithms, particularly convolutional neural networks (CNNs). China emerged as the leading contributor, followed by the United States and India, reflecting strong investments in agricultural modernization and remote sensing infrastructure. Thematic mapping highlights both traditional research areas, such as vegetation indices and land cover classification, and emerging themes, including AI-supported algorithms and food security. Despite this growth, disparities persist, with most countries contributing fewer than 100 publications, underscoring the need to promote participation in underrepresented regions. Findings demonstrate the field’s rapid evolution, emphasize the integration of AI-driven methods in crop monitoring, and suggest future directions combining remote sensing, ML, and internet of things (IoT) technologies to address global challenges in food security and sustainable agricultural management.
Remote sensing in the analysis of the behavior of CO associated with confinement due to COVID-19, in the city of Manizales Vladimir Henao-Céspedes; Yeison Alberto Garcés-Gómez; Oscar Cardona-Morales
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7441

Abstract

This article analyzed the behavior of carbon monoxide (CO) levels in Manizales during pre-lockdown, lockdown, and post-lockdown, as a response to the coronavirus disease (COVID-19) pandemic. The analysis focuses on the data of CO levels obtained from the tropospheric monitoring instrument (TROPOMI), precipitation, and temperature (T) recorded by the network of stations of Caldas. The data allowed us to find that during the lockdown, the average value of CO was 9.92% lower than the value registered before the lockdown, and it was 11.75% lower after the lockdown. On the other hand, the correlation between CO levels and population density during the three periods was analyzed, obtaining an R^2=0.816 after lockdown. Finally, considering other possible variables that can affect the CO levels, an analysis of the behavior of CO was carried out concerning the temperature and precipitation of the city registered before, during, and after the lockdown. Regarding CO and temperature, the correlation was inverse with Pearson’s r=-0.599 (Fisher’s z=-0.692), which also supports the decreasing trend of the value measured, and that the variation of CO levels does not depend only on lockdown but also on other factors. Regarding CO and precipitation, a positive correlation of Pearson’s r =0.165 (Fisher’s z=0.167) was obtained.
Agrivoltaic systems: a literature review Mariajosé Durán-Cabezas; Catalina Gómez-Gaviria; Vladimir Henao-Céspedes
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9964

Abstract

Agrivoltaic systems integrate solar energy generation with agricultural production to achieve efficient land use and mitigate climate change. This study presents a bibliometric analysis of the scientific literature on this topic, published from 2013 to 2023, to identify key trends, research areas, and emerging topics. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology and data from the Scopus database, the analysis was conducted with the R package bibliometrix and VOSviewer software. The results show remarkable growth in scientific output since 2020, with the United States, China, and Germany as the leading countries. The findings reveal the benefits of agrivoltaic systems, such as increased crop productivity, water-use efficiency, and income diversification for farmers. Emerging topics include the optimization of panel configurations and socioeconomic implications. Despite these benefits, challenges like high initial costs, social acceptance, and the need for adaptable designs persist. The conclusions underscore the importance of specific policies and incentives to support the adoption of these technologies. This analysis provides a comprehensive overview of the state of agrivoltaic systems, offering valuable insights for researchers, policymakers, and other stakeholders.
Co-Authors Andrea del Pilar Sánchez-Chavez Catalina Gómez-Gaviria Luis Fernando Diaz-Cadavid María Nancy Marín Olaya Mariajosé Durán-Cabezas Oscar Cardona-Morales Yeison Alberto Garcés-Gómez