Implementation of a MEIoT Weather Station with Exogenous Disturbance Input
Due to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, whi...
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MDPI AG
2021-02-01
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Online Access: | https://www.mdpi.com/1424-8220/21/5/1653 |
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author | Héctor A. Guerrero-Osuna Luis F. Luque-Vega Miriam A. Carlos-Mancilla Gerardo Ornelas-Vargas Víctor H. Castañeda-Miranda Rocío Carrasco-Navarro |
author_facet | Héctor A. Guerrero-Osuna Luis F. Luque-Vega Miriam A. Carlos-Mancilla Gerardo Ornelas-Vargas Víctor H. Castañeda-Miranda Rocío Carrasco-Navarro |
author_sort | Héctor A. Guerrero-Osuna |
collection | DOAJ |
description | Due to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, which incorporates an exogenous disturbance input, within the National Digital Observatory of Smart Environments (OBNiSE) architecture. The exogenous disturbance input involves a wind blower based on a DC brushless motor. It can be controlled, via Node-RED platform, manually through a sliding bar, or automatically via different predefined profile functions, modifying the wind speed and the wind vane sensor variables. An application to Engineering Education is presented with a case study that includes the instructional design for the least-squares regression topic for linear, quadratic, and cubic approximations within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work’s main contribution to the state-of-the-art is to turn a weather monitoring system into a hybrid hands-on learning approach thanks to the integrated exogenous disturbance input. |
first_indexed | 2024-03-09T06:19:00Z |
format | Article |
id | doaj.art-9cfa38bf58aa48b0b3f30e208ccbec96 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-09T06:19:00Z |
publishDate | 2021-02-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-9cfa38bf58aa48b0b3f30e208ccbec962023-12-03T11:50:24ZengMDPI AGSensors1424-82202021-02-01215165310.3390/s21051653Implementation of a MEIoT Weather Station with Exogenous Disturbance InputHéctor A. Guerrero-Osuna0Luis F. Luque-Vega1Miriam A. Carlos-Mancilla2Gerardo Ornelas-Vargas3Víctor H. Castañeda-Miranda4Rocío Carrasco-Navarro5Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, MexicoCentro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVM, Universidad del Valle de México, Tlaquepaque 45601, Jalisco, MexicoCentro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVM, Universidad del Valle de México, Tlaquepaque 45601, Jalisco, MexicoUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, MexicoUnidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, MexicoDepartment of Mathematics and Physics, ITESO AC, Tlaquepaque 45604, Jalisco, MexicoDue to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, which incorporates an exogenous disturbance input, within the National Digital Observatory of Smart Environments (OBNiSE) architecture. The exogenous disturbance input involves a wind blower based on a DC brushless motor. It can be controlled, via Node-RED platform, manually through a sliding bar, or automatically via different predefined profile functions, modifying the wind speed and the wind vane sensor variables. An application to Engineering Education is presented with a case study that includes the instructional design for the least-squares regression topic for linear, quadratic, and cubic approximations within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work’s main contribution to the state-of-the-art is to turn a weather monitoring system into a hybrid hands-on learning approach thanks to the integrated exogenous disturbance input.https://www.mdpi.com/1424-8220/21/5/1653sensing systeminternet of thingseducational mechatronicsengineering educationhands-on learning |
spellingShingle | Héctor A. Guerrero-Osuna Luis F. Luque-Vega Miriam A. Carlos-Mancilla Gerardo Ornelas-Vargas Víctor H. Castañeda-Miranda Rocío Carrasco-Navarro Implementation of a MEIoT Weather Station with Exogenous Disturbance Input Sensors sensing system internet of things educational mechatronics engineering education hands-on learning |
title | Implementation of a MEIoT Weather Station with Exogenous Disturbance Input |
title_full | Implementation of a MEIoT Weather Station with Exogenous Disturbance Input |
title_fullStr | Implementation of a MEIoT Weather Station with Exogenous Disturbance Input |
title_full_unstemmed | Implementation of a MEIoT Weather Station with Exogenous Disturbance Input |
title_short | Implementation of a MEIoT Weather Station with Exogenous Disturbance Input |
title_sort | implementation of a meiot weather station with exogenous disturbance input |
topic | sensing system internet of things educational mechatronics engineering education hands-on learning |
url | https://www.mdpi.com/1424-8220/21/5/1653 |
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