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IoT & AI Application for Smarter Workspaces

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

Deadline for manuscript submissions: closed (20 July 2022) | Viewed by 3072

Special Issue Editors


E-Mail Website
Guest Editor
University of Oulu, Oulu, Finland
Interests: edge computing; artificial intelligence; machine learning; data management

E-Mail Website
Guest Editor
University of Oulu, Oulu, Finland
Interests: ubiquitous computing, context modelling and reasoning, machine learning in IoT and data-intensive systems

Special Issue Information

Dear Colleagues,

In a best case scenario, the rapid development of IoT, AI and communication technologies enhance the engagement of people and wellbeing in their work. Sensed IoT data combined with artificial intelligence can produce actionable insight in the working environments. Fast, intelligent, and reliable processing and analysis of data enables supporting people in achieving their tasks and improving their safety and health. Optimized operation of the smart workspace can be a backbone of the overall efficiency of organizations.

Workspaces vary a lot in their goals, physical and technological settings. Different solutions in terms of architecture, technologies, as well as computational processes are required for each particular workplace. This special issue aims to explore and share the experiences in creating smarter workspaces, e.g., spaces supporting wellbeing and safety of the workers. Therefore, we welcome papers addressing the following, but not limited to, topics in the context of workspaces:

  • IoT Architectures and infrastructures
  • Data management frameworks and platforms
  • Data processing, data mining, machine learning
  • Distributed AI and Edge intelligence
  • Data security, privacy, and ethical assessment of systems
  • Ambient intelligence
  • Context- and situation-awareness
  • Digital twins
  • Real-world applications and experiments
  • Simulations

Dr. Susanna Pirttikangas
Dr. Ekaterina Gilman
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.

Published Papers (1 paper)

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Research

15 pages, 3545 KiB  
Article
Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories
by Cheng-Jung Yang, Ming-Huang Chen, Keng-Pei Lin, Yu-Jie Cheng and Fu-Chi Cheng
Sensors 2020, 20(20), 5791; https://0-doi-org.brum.beds.ac.uk/10.3390/s20205791 - 13 Oct 2020
Cited by 2 | Viewed by 2302
Abstract
Dental laboratories require manpower resources for manufacturing prostheses and inventory management. In this paper, we developed an automated inventory management system for dental laboratories to improve the production efficiency. A sensing system was developed based on the framework of Internet of things to [...] Read more.
Dental laboratories require manpower resources for manufacturing prostheses and inventory management. In this paper, we developed an automated inventory management system for dental laboratories to improve the production efficiency. A sensing system was developed based on the framework of Internet of things to collect the information of cobalt-chromium disks both in the storage room and manufacturing area, and an expert system was developed to automatically conduct inventory management based on the established rules. The proposed system can reduce the time of recording data and also assist the manager in configuring and managing material orders. The experimental results showed that a large amount of working time is reduced, resulting in the benefits of saving money and improving efficiency in dental manufacturing. Full article
(This article belongs to the Special Issue IoT & AI Application for Smarter Workspaces)
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