Implementation of a MEIoT Weather Station with Exogenous Disturbance Input.
Sensors (Basel)
; 21(5)2021 Feb 27.
Article
em En
| MEDLINE
| ID: mdl-33673511
ABSTRACT
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Tempo (Meteorologia)
/
Meteorologia
/
Internet das Coisas
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
México