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Measurement Uncertainty in IoT Networks
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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: closed (31 December 2021) | Viewed by 11002

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, Collections and Topics 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
Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796 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 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

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

Published Papers (5 papers)

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Research

18 pages, 1387 KiB  
Article
The Desirable Systemic Uncertainty in Complex IoT Sensor Networks—General Anticipatory Foresight Perspective
by Andrzej Magruk
Sensors 2022, 22(5), 1698; https://0-doi-org.brum.beds.ac.uk/10.3390/s22051698 - 22 Feb 2022
Cited by 1 | Viewed by 1293
Abstract
A wide methodological spectrum regarding future research is offered by anticipation studies, with a special role of foresight studies. Many studies of this type focus on generating the desired future, taking into account the fact that it is accompanied by uncertainty. The author [...] Read more.
A wide methodological spectrum regarding future research is offered by anticipation studies, with a special role of foresight studies. Many studies of this type focus on generating the desired future, taking into account the fact that it is accompanied by uncertainty. The author of this publication postulates treating uncertainty as an equivalent—in relation to the future—research object. This approach allows us to formulate general assumptions for a model of the anticipatory management of systemic uncertainty in IoT networks. The goal of such a model will not be to eliminate or even minimize uncertainty, but to regulate it to a desired level. Such an action can bring many more benefits than trying to zero out uncertainty. On the general side, uncertainty can be studied in two ways: (1) as an abstract idea, or (2) as a feature of a particular structure, also with elements of research on its abstract component. In this paper the attention is focused on the second approach. The main research area is the IoT network in its broadest sense, with a particular role of the social construct, in the context of the study of systemic uncertainty in relation to selected anticipatory actions. The overarching goal is to define a desired state, or to determine what such a desired state is, of anticipatory IoT uncertainty. Full article
(This article belongs to the Special Issue Measurement Uncertainty in IoT Networks)
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12 pages, 894 KiB  
Article
IoT Application of Transfer Learning in Hybrid Artificial Intelligence Systems for Acute Lymphoblastic Leukemia Classification
by Krzysztof Pałczyński, Sandra Śmigiel, Marta Gackowska, Damian Ledziński, Sławomir Bujnowski and Zbigniew Lutowski
Sensors 2021, 21(23), 8025; https://0-doi-org.brum.beds.ac.uk/10.3390/s21238025 - 01 Dec 2021
Cited by 10 | Viewed by 2028
Abstract
Acute lymphoblastic leukemia is the most common cancer in children, and its diagnosis mainly includes microscopic blood tests of the bone marrow. Therefore, there is a need for a correct classification of white blood cells. The approach developed in this article is based [...] Read more.
Acute lymphoblastic leukemia is the most common cancer in children, and its diagnosis mainly includes microscopic blood tests of the bone marrow. Therefore, there is a need for a correct classification of white blood cells. The approach developed in this article is based on an optimized and small IoT-friendly neural network architecture. The application of learning transfer in hybrid artificial intelligence systems is offered. The hybrid system consisted of a MobileNet v2 encoder pre-trained on the ImageNet dataset and machine learning algorithms performing the role of the head. These were the XGBoost, Random Forest, and Decision Tree algorithms. In this work, the average accuracy was over 90%, reaching 97.4%. This work proves that using hybrid artificial intelligence systems for tasks with a low computational complexity of the processing units demonstrates a high classification accuracy. The methods used in this study, confirmed by the promising results, can be an effective tool in diagnosing other blood diseases, facilitating the work of a network of medical institutions to carry out the correct treatment schedule. Full article
(This article belongs to the Special Issue Measurement Uncertainty in IoT Networks)
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10 pages, 676 KiB  
Communication
Pass/Fail Quality Assessment in Last Mile Smart Metering Networks Based on PRIME Interface
by Piotr Kiedrowski and Beata Marciniak
Sensors 2021, 21(22), 7444; https://0-doi-org.brum.beds.ac.uk/10.3390/s21227444 - 09 Nov 2021
Viewed by 1177
Abstract
The pass/fail form is one of the presentation methods of quality assessment results. The authors, as part of a research team, participated in the process of creating the PRIME interface analyzer. The PRIME interface is a standardized interface—considered as communication technology for smart [...] Read more.
The pass/fail form is one of the presentation methods of quality assessment results. The authors, as part of a research team, participated in the process of creating the PRIME interface analyzer. The PRIME interface is a standardized interface—considered as communication technology for smart metering wired networks, which are specific kinds of sensor networks. The frame error ratio (FER) assessment and its presentation in the pass/fail form was one of the problems that needed to be solves in the PRIME analyzer project. In this paper, the authors present their method of a unified FER assessment, which was implemented in the PRIME analyzer, as one of its many functionalities. The need for FER unification is the result of using different modulation types and an optional forward error correction mechanism in the PRIME interface. Having one unified FER and a threshold value makes it possible to present measurement results in the pass/fail form. For FER unification, the characteristics of FER vs. signal-to-noise ratio, for all modulations implemented in PRIME, were used in the proposed algorithm (and some are presented in this paper). In communication systems, the FER value is used to forecast the quality of a link or service, but using PLC technology, forecasting is highly uncertain due to the main noise. The presentation of the measurement results in the pass/fail form is important because it allows unskilled staff to make many laborious measurements in last mile smart metering networks. Full article
(This article belongs to the Special Issue Measurement Uncertainty in IoT Networks)
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12 pages, 5123 KiB  
Article
Steered Molecular Dynamics of Lipid Membrane Indentation by Carbon and Silicon-Carbide Nanotubes—The Impact of Indenting Angle Uncertainty
by Przemysław Raczyński, Krzysztof Górny, Piotr Bełdowski, Steven Yuvan, Beata Marciniak and Zbigniew Dendzik
Sensors 2021, 21(21), 7011; https://0-doi-org.brum.beds.ac.uk/10.3390/s21217011 - 22 Oct 2021
Cited by 2 | Viewed by 1323
Abstract
Due to the semi-liquid nature and uneven morphologies of biological membranes, indentation may occur in a range of non-ideal conditions. These conditions are relatively unstudied and may alter the physical characteristics of the process. One of the basic challenges in the construction of [...] Read more.
Due to the semi-liquid nature and uneven morphologies of biological membranes, indentation may occur in a range of non-ideal conditions. These conditions are relatively unstudied and may alter the physical characteristics of the process. One of the basic challenges in the construction of nanoindenters is to appropriately align the nanotube tip and approach the membrane at a perpendicular angle. To investigate the impact of deviations from this ideal, we performed non-equilibrium steered molecular dynamics simulations of the indentation of phospholipid membranes by homogeneous CNT and non-homogeneous SiCNT indenters. We used various angles, rates, and modes of indentation, and the withdrawal of the relative indenter out of the membrane in corresponding conditions was simulated. Full article
(This article belongs to the Special Issue Measurement Uncertainty in IoT Networks)
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19 pages, 3105 KiB  
Article
A Conceptual Model of Measurement Uncertainty in IoT Sensor Networks
by Piotr Cofta, Kostas Karatzas and Cezary Orłowski
Sensors 2021, 21(5), 1827; https://0-doi-org.brum.beds.ac.uk/10.3390/s21051827 - 05 Mar 2021
Cited by 12 | Viewed by 2852
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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