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Special Issue "Measurement Uncertainty in IoT Networks"

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

Deadline for manuscript submissions: 1 November 2021.

Special Issue Editors

Prof. Dr. Kostas Karatzas
E-Mail Website
Guest Editor
Department of Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: environmental informatics; computational intelligence oriented data analytics and modelling; urban air quality management and information systems; computational calibration and performance improvement of low-cost environmental sensors; quality of life information services
Special Issues and Collections in MDPI journals
Prof. Cezary Orłowski
E-Mail Website
Guest Editor
Information Technology Management Department, WSB University in Gdańsk, Poland
Interests: Information Technology; Information System Management; Knowledge Representation; Software Engineering; Computational Intelligence; Business Intelligence; Knowledge Management; Artificial Intelligence; Ontology; IT Project Management
Prof. Dr. Piotr Cofta
E-Mail Website
Guest Editor
Division of Digital Technology, University of Technology and Life Sciences in Bydgoszcz, Bydgoszcz, Poland
Interests: IoT; Technology and Trust

Special Issue Information

Dear Colleagues,

Measurement uncertainty is a complex technical and social phenomenon and is of great importance for the usefulness of any measurement, instrument, or node in the measurement network. Therefore, various methods of assessing and reducing uncertainty are used, referring to one or more sources of uncertainty, such as internal uncertainties of a measuring device, uncertainties characteristic of methods of measuring uncertainty caused by external conditions, and personal errors.

Measurement uncertainty is of particular importance in the Internet of Things networks due to the variety of devices and measurement methods. For this reason, uncertainty analysis becomes an important aspect of the assessment of the usefulness of these networks for measurements, the process of data enrichment, their initial processing and use for diagnosing and forecasting phenomena.

Therefore, when preparing this Special Issue proposal, the potential shareholders of this project are anticipated to be both those who conduct the measurements and those who process data from these measurements. Hence, it is proposed that this edition should contain the results of the work of teams dealing with the measurement of internal and external air pollutants and teams conducting research in CA17136 - Indoor Air Pollution Network, as well as those who will use this data working in CA16215 - European network for the promotion of portable, affordable and simple analytical platforms. Then this Special Issue will contain interesting results of uncertainty studies covering both the measurements themselves and their analysis and implementation processes. 

This Special Issue expands the knowledge in the following areas of sensors:

  • Remote sensors
  • Sensor networks
  • Smart / Intelligent sensors
  • Sensor devices
  • Sensor technology and application
  • Sensing principles
  • Internet of Things
  • Signal processing, data fusion, and deep learning in sensor systems

Prof. Dr. Kostas Karatzas
Prof. Cezary Orłowski
Prof. Dr. Piotr Cofta
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 papers will be 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 2200 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

  • Measurements of internal and external air pollution 
  • Uncertainty of measurement 
  • Internet of Things networks 
  • Sensors and measurement procedures 
  • Big Data processing

Published Papers (1 paper)

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Research

Article
A Conceptual Model of Measurement Uncertainty in IoT Sensor Networks
Sensors 2021, 21(5), 1827; https://doi.org/10.3390/s21051827 - 05 Mar 2021
Cited by 2 | Viewed by 587
Abstract
The growing popularity of inexpensive IoT (Internet of Things) sensor networks makes their uncertainty an important aspect of their adoption. The uncertainty determines their fitness for purpose, their perceived quality and the usefulness of information they provide. Nevertheless, neither the theory nor the [...] Read more.
The growing popularity of inexpensive IoT (Internet of Things) sensor networks makes their uncertainty an important aspect of their adoption. The uncertainty determines their fitness for purpose, their perceived quality and the usefulness of information they provide. Nevertheless, neither the theory nor the industrial practice of uncertainty offer a coherent answer on how to address uncertainty of networks of this type and their components. The primary objective of this paper is to facilitate the discussion of what progress should be made regarding the theory and the practice of uncertainty of IoT sensor networks to satisfy current needs. This paper provides a structured overview of uncertainty, specifically focusing on IoT sensor networks. It positions IoT sensor networks as contrasted with professional measurement and control networks and presents their conceptual sociotechnical reference model. The reference model advises on the taxonomy of uncertainty proposed in this paper that demonstrates semantic differences between various views on uncertainty. This model also allows for identifying key challenges that should be addressed to improve the theory and practice of uncertainty in IoT sensor networks. Full article
(This article belongs to the Special Issue Measurement Uncertainty in IoT Networks)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Conceptualization of measurement uncertainty in IoT sensor networks
Authors: Piotr Cofta; Kostas Karatzas; Cezary Orlowski
Affiliation: Faculty of Telecommunications, Computer Science and Technology, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
Abstract: The growing popularity of inexpensive, opportunistic IoT sensor networks makes their uncertainty an important aspect of their adoption. The uncertainty determines their fitness for purpose, their perceived quality and the usefulness of information they provide. Still, neither the theory nor the industrial practice of uncertainty offer a coherent answer of how to address uncertainty of complete networks and their components. The primary objective of this paper is to facilitate the discussion of what progress should be made to the theory and the practice of uncertainty of IoT sensor networks to satisfy current needs. This paper provides a structured overview of uncertainty, as applied to IoT sensor networks. It presents the conceptual socio-technical reference model of an IoT sensor network, as contrasted with professional measurement networks. The reference model advises on the taxonomy of uncertainty proposed in this paper that demonstrates semantic differences between various views on uncertainty, all applicable to elements of the network. This model also allows to identify key challenges that should be addressed to improve the theory and practice of uncertainty in IoT sensor networks.

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