Vayas Ortega, Germania
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Vayas Ortega, Germania
Main Affiliation
Ambato
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germaniavayas@uti.edu.ec
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Scopus Author ID
57194585958

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Bibliometric study for CO2 measurement using IoT: Looking for the Latin American contributions

2022 , Páez-Carabajo J.-D. , Huerta M.-K. , Rivas-Lalaleo D. , Vayas Ortega, Germania , Clotet-Martinez R. , Castillo-Velazquez J.-I.

In recent years, the number of deaths due to environmental pollution has increased. The main air pollutants are carbon monoxide, carbon dioxide, and sulfur dioxide. These are produced by the consumption of fossil fuels in vehicles, industrial activity, and agricultural practices, among others. Various technologies have been used to detect carbon dioxide (CO2), including the Internet of Things (IoT). However, no studies have been carried out to visualize the impact of IoT on CO2 monitoring and which countries are focused on minimizing emissions. This work shows a bibliometric study for CO2 environmental sensing using IoT. SCOPUS was the selected database, and PRISMA was the methodology used. The first search returned 13.207 documents written between 2013 and 2022, after filtering selected keywords, selecting only English articles, and abstract review we selected finally 79 documents for the measurement of CO2 using IoT. The results of analyzing them, show that the Asian countries produces more than the western countries, where India and Indonesia are leading. Also is interesting to note that the USA and Latin America produced the same quantity of documents, where the four countries contributing to Latin America are Brazil, Mexico, Peru, and Ecuador. The main area of knowledge covered by the documents was Engineering with 25 percent followed by computer sciences, and 40 percent of documents were published by IEEE. Finally, the Latin American contributions to this field are outlined, verifying in detail the architectures for the proposed solutions with emphasis in sensors. © 2022 IEEE.

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A long-range, low-cost technique to measure water level variations over limnimeters on hydraulic weir using machine vision and IoT

2022 , Chiliquinga-Chiliquinga A. , Garcés-Llerena R. , Bautista-Naranjo V. , Vayas Ortega, Germania , Castillo-Velazquez J.-I. , Clotet R. , Huerta M. , Rivas-Lalaleo D.

It is neither practical nor economical to make continuous and direct measurements of the water flow in a stream, so indirect methods must be used to measure the water level and, based on a calibration curve, relate it to the corresponding flow rate. A hydraulic weir with a limnimeter fulfills this purpose, but its disadvantage is that it does not allow the automated registration of the water level and therefore new and more efficient technologies must be used to perform this measurement automatically and thus have a lower waste and optimization of the resource. This experiment develops an algorithm based on computer vision and the inclusion of the concepts of the Internet of Things, in order to measure and record the values of the water level in a hydraulic dam, also includes energy storage system, power supply, remote computer, devices with wireless communication and IoT platform that allow a measurement error of less than ± 2% to be obtained with respect to a visual measurement made by the operator. © 2022 IEEE.

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