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Sensors
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IoT Sensor Systems: Design, Interfaces, Signals, Processing, and Applications
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IoT Sensor Systems: Design, Interfaces, Signals, Processing, and Applications

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 2370

Special Issue Editors

Dr. Manuel José Cabral dos Santos Reis

E-Mail Website
Guest Editor
Department of Engineering/IEETA, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
Interests: signal & image processing and applications; study and development of devices & systems for friendly smart environments; development of multimedia-based teaching/learning methods and tools, with particular emphasis on the use of the internet
Special Issues, Collections and Topics in MDPI journals
Dr. Nishu Gupta

E-Mail Website
Guest Editor
Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), 2815 Gjøvik, Norway
Interests: IoT device propagation; sensor networks; Internet of Things; Internet of Vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internet of Things (IoT) sensor systems have already been conceptually established in the scientific world. However, this area of study continues to transform its design, interfaces, and process. As such, its applications are developing quickly. With its enormous applications in almost every branch of engineering, science and technology, it finds great relevance to more efficient organization and the management of modern communication systems. IoT sensor systems envisage smart techniques that foster the research and development of real-time, scalable and reliable networks, and pave the way to bringing about future research paradigm towards next-generation computation technology.

The objective of this Special Issue is to provide an excellent platform for this field’s academicians, researchers, engineers, and industrial participants to share their research findings with other global experts. In this Special Issue, both original research articles and reviews are welcome. Research areas may cover (but are not limited to) the following:

  • Design space exploration techniques for IoT devices and systems
  • Power, energy, efficient resource management, and energy harvesting
  • Things to cloud: computation and communication gateways
  • Miniaturization: Sensors, CPU, and network
  • IoT interconnections among ISP analysis—QoS, scalability, performance, interference
  • Semantic technologies: information and data models for interoperability
  • Virtualization: multiple sensors aggregated, or a sensor shared by multiple users
  • Privacy/security/trust/identity/anonymity target prediction
  • Design principles and best practices for IoT application development
  • Green IoT: sustainable design and technologies

Dr. Manuel José Cabral dos Santos Reis
Dr. Nishu Gupta
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

22 pages, 17380 KiB  
Article
A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning
by Esteban Cumbajin, Nuno Rodrigues, Paulo Costa, Rolando Miragaia, Luís Frazão, Nuno Costa, Antonio Fernández-Caballero, Jorge Carneiro, Leire H. Buruberri and António Pereira
Sensors 2024, 24(1), 232; https://0-doi-org.brum.beds.ac.uk/10.3390/s24010232 - 31 Dec 2023
Viewed by 1705
Abstract
Defect detection is a key element of quality control in today’s industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can [...] Read more.
Defect detection is a key element of quality control in today’s industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%. Full article
(This article belongs to the Special Issue IoT Sensor Systems: Design, Interfaces, Signals, Processing, and Applications)
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