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.
Highlights
Technological advancement derived from more than 50 years of Moore’s Law has brought humanity into an era where the life cycles of products and technologies have been shortened
This work presents a weather station paired with a controlled exogenous disturbance in the context of an educational mechatronics framework that is adapted to a remote laboratory operation to give students an online hands-on learning (HOL) experience
The integration of an actuator to disturb a sensor input allows the interaction demanded by hands-on learning
Summary
Technological advancement derived from more than 50 years of Moore’s Law has brought humanity into an era where the life cycles of products and technologies have been shortened. For some monitoring applications where studied variables have a natural low change rate, such as climate variables, an interesting approach would be to generate a controlled exogenous disturbance to accelerate the change rate of the monitored variables in order to obtain a better understanding of the variables range and their interactions. Such exogenous disturbances can be generated physically with an adequate actuator and an open-loop controller This combination of facts leads us to the following research questions: how could a weather station, which by design only monitors variables, be repurposed for hands-on usage to enhance the learning experience? This work presents a weather station paired with a controlled exogenous disturbance in the context of an educational mechatronics framework that is adapted to a remote laboratory operation to give students an online HOL experience.
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