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IoT Sensors and Technologies for Education
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IoT Sensors and Technologies for Education

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 53875

Special Issue Editors

Dr. Claudio Fornaro

E-Mail Website
Guest Editor
Facoltà di Ingegneria presso l’Università Telematica Internazionale UNINETTUNO, 00186 Roma, Italy
Interests: embedded system software; computer security; Internet of Things; computer vision; software implemented hardware fault tolerance (SIHFT)
Dr. Dario Assante

E-Mail Website1 Website2
Guest Editor
Faculty of Engineering, Università Telematica Internazionale Uninettuno, 00186 Rome, Italy
Interests: electromagnetic modeling; electromagnetic compatibility; shielding; energy management; smart grids; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things is a key factor for the transition to the digital society. Communication networks already interconnect people and many autonomous and semi-autonomous devices. The IoT not only has a direct social impact, but the industry finds in it the best approach to solve problems; thus, it is seen as a great opportunity to enhance the competitiveness of companies. In particular, the IoT is considered to be one of the key drivers for the implementation of the so-called Industry 4.0 and for the digital transformation of companies.

The rapid diffusion of IoT technologies requires an adequate response from the educational system; an increasingly large number of qualified professionals are needed that are able to design and manage IoT-based devices, networks, and systems for a large number of different sectors.

As the IoT technology is increasingly becoming part of every aspect of life and productive environments, security and safety are a major concern. A huge number of widely distributed devices with a computing power that frequently is not trivial sum up to an extremely powerful computing system with ramifications everywhere, which can be considered outposts in the wrong hands. Security and safety aspects are central to the safe development of IoT technologies; “security by design” must not be an option, and must be enforced in any software and hardware application.

The Special Issue “IoT Sensors and Technologies for Education” focuses on the educational activities related to the IoT, including the uses of IoT sensors and technologies in education activities and the educational programs related to IoT, without forgetting security and safety aspects.

Potential topics in this Special Issue include, but are not limited to:

  • IoT sensors for education
  • IoT-aided education
  • IoT-based virtual and remote laboratories
  • IoT education for Industry 4.0
  • IoT security education
  • IoT best practices in education

Dr. Claudio Fornaro
Dr. Dario Assante
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IoT, sensors
  • education
  • remote laboratories
  • Industry 4.0
  • security
  • safety
  • best practices

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Published Papers (6 papers)

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Research

20 pages, 10624 KiB  
Article
Design and Implementation of ESP32-Based IoT Devices
by Darko Hercog, Tone Lerher, Mitja Truntič and Oto Težak
Sensors 2023, 23(15), 6739; https://doi.org/10.3390/s23156739 - 27 Jul 2023
Cited by 45 | Viewed by 32341
Abstract
The Internet of Things (IoT) has become a transformative technology with great potential in various sectors, including home automation, industrial control, environmental monitoring, agriculture, wearables, health monitoring, and others. The growing presence of IoT devices stimulates schools and academic institutions to integrate IoT [...] Read more.
The Internet of Things (IoT) has become a transformative technology with great potential in various sectors, including home automation, industrial control, environmental monitoring, agriculture, wearables, health monitoring, and others. The growing presence of IoT devices stimulates schools and academic institutions to integrate IoT into the educational process, since IoT skills are in demand in the labor market. This paper presents educational IoT tools and technologies that simplify the design, implementation, and testing of IoT applications. The article presents the introductory IoT course that students perform initially and then presents some of the projects that they develop and implement on their own later in the project. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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17 pages, 3357 KiB  
Communication
Proposal of Design and Innovation in the Creation of the Internet of Medical Things Based on the CDIO Model through the Methodology of Problem-Based Learning
by Jefferson Sarmiento-Rojas, Pedro Antonio Aya-Parra and Oscar J. Perdomo
Sensors 2022, 22(22), 8979; https://doi.org/10.3390/s22228979 - 20 Nov 2022
Cited by 2 | Viewed by 2423
Abstract
The educational framework—Conceive, Design, Implement, and Operate—is part of an international proposal to improve education in the field of engineering, emphasizing how to teach engineering comprehensively, which allows the standardization of skills in professionals as a model for teaching engineering. Moreover, problem-based learning [...] Read more.
The educational framework—Conceive, Design, Implement, and Operate—is part of an international proposal to improve education in the field of engineering, emphasizing how to teach engineering comprehensively, which allows the standardization of skills in professionals as a model for teaching engineering. Moreover, problem-based learning allows students to experiment with challenging situations through cases that simulate natural contexts with their profession. The integration of these two education strategies applied to the Internet of Things (IoT) Education for Industry 4.0 has promoted the generation of teaching challenges. Our education strategy proposes the synergy between laboratory guides and the classroom with the following actions: the content of the topic is presented, followed by the presentation of an issue focused into a realistic context, with practical exercises integrating software and hardware for the deployment of the solution to be reported as a final project. Moreover, undergraduate students in the biomedical engineering area acquired new knowledge about IoT, but at the same time, they may develop skills in the field of programming and structuring different architectures to solve real-world problems. Finally, traditional models of education require new teaching initiatives in the field of biomedical engineering concerning the current challenges and needs of the labor market. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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24 pages, 1252 KiB  
Article
Teaching Digital Electronics during the COVID-19 Pandemic via a Remote Lab
by Felipe Valencia de Almeida, Victor Takashi Hayashi, Reginaldo Arakaki, Edson Midorikawa, Sérgio de Mello Canovas, Paulo Sergio Cugnasca and Pedro Luiz Pizzigatti Corrêa
Sensors 2022, 22(18), 6944; https://doi.org/10.3390/s22186944 - 14 Sep 2022
Cited by 11 | Viewed by 2629
Abstract
Practical knowledge is essential for engineering education. With the COVID-19 pandemic, new challenges have arisen for remote practical learning (e.g., collaborations/experimentations with real equipment when face-to-face offerings are not possible). In this context, LabEAD is a remote lab project that aims to provide [...] Read more.
Practical knowledge is essential for engineering education. With the COVID-19 pandemic, new challenges have arisen for remote practical learning (e.g., collaborations/experimentations with real equipment when face-to-face offerings are not possible). In this context, LabEAD is a remote lab project that aims to provide practical knowledge learning opportunities for Brazilian engineering students. This article describes how engineering project management methods consisting of application domains, requirement identification, technical solution specification, implementation, and delivery phases, were applied to the development of an Internet of Things (IoT) remote lab architecture. The distributed computing environment allows integration between students’ smartphones and IoT devices deployed in campus labs and in student residences. The code is open-source for facilitated replication and reuse, and the remote lab was built in six months to enable six experiments for the digital electronics lab during the COVID-19 pandemic, covering all the experiments of the original face-to-face offering. More than 70% of the 32 students preferred remote labs over simulations, and only 2 were not approved in the digital electronics course offered remotely.Student perceptions collected by questionnaires showed that they could successfully specify, develop, and present their projects using the remote lab infrastructure in four weeks. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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28 pages, 17772 KiB  
Article
MEIoT 2D-CACSET: IoT Two-Dimensional Cartesian Coordinate System Educational Toolkit Align with Educational Mechatronics Framework
by Rocío Carrasco-Navarro, Luis F. Luque-Vega, Jesús Antonio Nava-Pintor, Héctor A. Guerrero-Osuna, Miriam A. Carlos-Mancilla and Celina Lizeth Castañeda-Miranda
Sensors 2022, 22(13), 4802; https://doi.org/10.3390/s22134802 - 25 Jun 2022
Cited by 7 | Viewed by 2849
Abstract
The educational sector has made extraordinary efforts to neutralize the impact of the pandemic caused by COVID-19, forcing teachers, scholars, and academic personnel to change the way education is delivered by developing creative and technological solutions to improve the landscape for education. The [...] Read more.
The educational sector has made extraordinary efforts to neutralize the impact of the pandemic caused by COVID-19, forcing teachers, scholars, and academic personnel to change the way education is delivered by developing creative and technological solutions to improve the landscape for education. The Internet of Things (IoT) is crucial for the educational transition to digital and virtual environments. This paper presents the integration of IoT technology in the Two-Dimensional Cartesian Coordinate System Educational Toolkit (2D-CACSET), to transform it into MEIoT 2D-CACSET; which includes educational mechatronics and the IoT. The Educational Mechatronics Conceptual Framework (EMCF) is extended to consider the virtual environment, enabling knowledge construction in virtual concrete, virtual graphic, and virtual abstract levels. Hence, the students acquire this knowledge from a remote location to apply it further down their career path. Three instructional designs are designed for this work using the MEIoT 2D-CACSET to learn about coordinate axes, quadrants, and a point in the 2D Coordinate Cartesian System. This work is intended to provide an IoT educational technology to offer an adequate response to the educational system’s current context. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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20 pages, 1184 KiB  
Article
A Novel Redundant Validation IoT System for Affective Learning Based on Facial Expressions and Biological Signals
by Antonio Costantino Marceddu, Luigi Pugliese, Jacopo Sini, Gustavo Ramirez Espinosa, Mohammadreza Amel Solouki, Pietro Chiavassa, Edoardo Giusto, Bartolomeo Montrucchio, Massimo Violante and Francesco De Pace
Sensors 2022, 22(7), 2773; https://doi.org/10.3390/s22072773 - 4 Apr 2022
Cited by 6 | Viewed by 2718
Abstract
Teaching is an activity that requires understanding the class’s reaction to evaluate the teaching methodology effectiveness. This operation can be easy to achieve in small classrooms, while it may be challenging to do in classes of 50 or more students. This paper proposes [...] Read more.
Teaching is an activity that requires understanding the class’s reaction to evaluate the teaching methodology effectiveness. This operation can be easy to achieve in small classrooms, while it may be challenging to do in classes of 50 or more students. This paper proposes a novel Internet of Things (IoT) system to aid teachers in their work based on the redundant use of non-invasive techniques such as facial expression recognition and physiological data analysis. Facial expression recognition is performed using a Convolutional Neural Network (CNN), while physiological data are obtained via Photoplethysmography (PPG). By recurring to Russel’s model, we grouped the most important Ekman’s facial expressions recognized by CNN into active and passive. Then, operations such as thresholding and windowing were performed to make it possible to compare and analyze the results from both sources. Using a window size of 100 samples, both sources have detected a level of attention of about 55.5% for the in-presence lectures tests. By comparing results coming from in-presence and pre-recorded remote lectures, it is possible to note that, thanks to validation with physiological data, facial expressions alone seem useful in determining students’ level of attention for in-presence lectures. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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22 pages, 6082 KiB  
Article
Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
by Patrik Jacko, Matej Bereš, Irena Kováčová, Ján Molnár, Tibor Vince, Jozef Dziak, Branislav Fecko, Šimon Gans and Dobroslav Kováč
Sensors 2022, 22(4), 1440; https://doi.org/10.3390/s22041440 - 13 Feb 2022
Cited by 35 | Viewed by 8165
Abstract
The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the [...] Read more.
The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the data to the server to which the teacher is connected via the control application. The teacher has the opportunity to monitor the development of tasks and student code of the program, where the functionality of these tasks can be verified. Thanks to the IoT remote laboratory implementation, students’ tasks during the lesson were improved. As many as 53% (n = 8) of those students who could improve their results achieved an improvement of one or up to two tasks during class. Before the IoT remote laboratory application, up to 30% (n = 6) of students could not solve any task and only 25% (n = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (n = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (n = 10) of students solved the full number of tasks. In contrast, only 10% (n = 2) of students did not solve any task. Full article
(This article belongs to the Special Issue IoT Sensors and Technologies for Education)
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