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Technology Advances on IoT Learning and Teaching
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Technology Advances on IoT Learning and Teaching

A topical collection in Technologies (ISSN 2227-7080). This collection belongs to the section "Information and Communication Technologies".

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Editors

Prof. Dr. Sergio Martin Gutiérrez

E-Mail Website
Collection Editor
Electrical and Computer Engineering Department, National Distance Education University, 28040 Madrid, Spain
Interests: ad hoc networks; aquatic surface vehicles deployment; unmanned aerial vehicle fleet; path planning techniques; machine and deep learning; reinforcement learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. George F. Fragulis

E-Mail Website
Collection Editor
Laboratory of Robotics, Embedded and Integrated Systems, Department of Electrical and Computer Engineering, University of Western Macedonia, 50100 Kozani, Greece
Interests: machine learning; control systems; robotics; fuzzy systems

Topical Collection Information

Dear Colleagues,

The Internet of Things (IoT) is widely considered as one of the key drivers of the digital transformation of society and implementation of the so-called Industry 4.0. IoT not only has a huge social impact but can also support employability and boost the competitiveness of companies. Relevant impacts of this technology are expected in a wide range of sectors.

The rapid diffusion of IoT technologies has created an important educational challenge, namely the need to train a large number of professionals able to design and manage a quickly evolving and complex ecosystem. Thus, an important research effort is being carried out in innovative technologies (simulators, virtual and remote labs, mobile apps, robotics, e-learning platforms, gamification, learning analytics, etc.) applied to innovative teaching practices.

This Special Issue focuses on all the technologies involved in improving the teaching and learning process of some of the IoT-related topics such as sensors, devices, protocols, platforms, services or data analysis, among others.

Dr. Sergio Martin
Prof. Dr. George F. Fragulis
Collection 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 collection 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. Technologies is an international peer-reviewed open access monthly 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 1600 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

  • virtual laboratories for IoT
  • remote laboratories for IoT
  • IoT simulators
  • IoT demonstrators
  • mobile apps for IoT learning
  • innovative teaching practices
  • gamification
  • learning analytics
  • open educational resources and repositories for IoT learning
  • platforms for IoT learning
  • big data

Related Special Issue

Published Papers (1 paper)

2023

20 pages, 305 KiB  
Systematic Review
A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology
by Maria Papatsimouli, Panos Sarigiannidis and George F. Fragulis
Technologies 2023, 11(4), 83; https://doi.org/10.3390/technologies11040083 - 22 Jun 2023
Cited by 5 | Viewed by 9447
Abstract
Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, [...] Read more.
Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, have improved their communication capabilities, a significant communication gap still exists between sign language users and non-users. In order to bridge this gap, numerous sign language translation systems have been developed, encompassing sign language recognition and gesture-based controls. Our research aimed to analyze the advancements in real-time sign language translators developed over the past five years and their integration with IoT technology. By closely examining these technologies, we aimed to attain a deeper comprehension of their practical applications and evolution in the domain of sign language translation. We analyzed the current literature, technical reports, and conference papers on real-time sign language translation systems. Our results offer insights into the current state of the art in real-time sign language translation systems and their integration with IoT technology. We also provide a deep understanding of the recent developments in sign language translation technology and the potential for their fusion with Internet of Things technology to improve communication and promote inclusivity for the deaf and hard-of-hearing population. Full article
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