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Instruments
Special Issues
Instrumentation and Measurement Methods for Industry 4.0 and IoT
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Instrumentation and Measurement Methods for Industry 4.0 and IoT

A special issue of Instruments (ISSN 2410-390X).

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1415

Special Issue Editor

Prof. Dr. Mauro Serpelloni

E-Mail Website
Guest Editor
Department of Information Engineering, University of Brescia, 25123 Brescia, Italy
Interests: innovative fabrication technologies; printed sensor applications; flexible/stretchable electronics; printed sensor system; additive manufacturing; sensors for smart devices; innovative fabrication methods for sensors directly on objects; metrological characterization of sensors for biomedical and industrial applications; signal processing for printed sensors and smart objects; printed sensors integrated on wearable and IoT devices; hybrid printed electronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting selected authors to submit extended versions of their papers on the 8th International workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) to Instruments. The extended version must provide a minimum of 50% new content and must not exceed 30% copy/paste from the proceedings paper. In addition, authors who also focus on topics related to the MetroInd4.0&IoT workshop may be considered upon writing to the Guest Editor about their interest in contributing to this Special Issue.

The main topics of this Special Issue cover all aspects of metrology that contribute to the development of Industry 4.0 and IoT, as well as the new opportunities offered by Industry 4.0 and IoT for the development of new measurement methods and instruments. In particular, topics of emerging interest comprise integrating new technologies into products and applications, experience with existing and novel techniques, and the identification of unsolved challenges. In addition, there are special sessions included in the workshop, which include positioning and tracking, virtual measurements, and instrumentation and measurement for human health and medical applications. We also welcome papers on these topics.

Prof. Dr. Mauro Serpelloni
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Instruments is an international peer-reviewed open access quarterly 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 1400 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

  • instrumentation and measurement methods
  • Industry 4.0
  • Internet of Things
  • wireless sensor network
  • localization technology
  • sensors for human and industry applications

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

21 pages, 2306 KB  
Article
Deep-Learning-Based Bearing Fault Classification Using Vibration Signals Under Variable-Speed Conditions
by Luca Martiri, Parisa Esmaili, Andrea Moschetti and Loredana Cristaldi
Instruments 2025, 9(4), 33; https://doi.org/10.3390/instruments9040033 - 4 Dec 2025
Viewed by 326
Abstract
Predictive maintenance in industrial machinery relies on the timely detection of component faults to prevent costly downtime. Rolling bearings, being critical elements, are particularly prone to defects such as outer race faults and ball spin defects, which manifest as characteristic vibration patterns. In [...] Read more.
Predictive maintenance in industrial machinery relies on the timely detection of component faults to prevent costly downtime. Rolling bearings, being critical elements, are particularly prone to defects such as outer race faults and ball spin defects, which manifest as characteristic vibration patterns. In this study, we introduce a novel bearing vibration dataset collected on a testbench under both constant and variable rotational speeds (0–5000 rpm), encompassing healthy and faulty conditions. The dataset was used for failure classification and further enriched through feature engineering, resulting in input features that include raw acceleration, signal envelopes, and time- and frequency-domain statistical descriptors, which capture fault-specific signatures. To quantify prediction uncertainty, two different approaches are applied, providing confidence measures alongside model outputs. Our results demonstrate the progressive improvement of classification accuracy from 87.2% using only raw acceleration data to 99.3% with a CNN-BiLSTM (Convolutional Neural Network–Bidirectional Long Short-Term Memory) ensemble and advanced features. Shapley Additive Explanation (SHAP)-based explainability further validates the relevance of frequency-domain features for distinguishing fault types. The proposed methodology offers a robust and interpretable framework for industrial fault diagnosis, capable of handling both stationary and non-stationary operating conditions. Full article
(This article belongs to the Special Issue Instrumentation and Measurement Methods for Industry 4.0 and IoT)
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9 pages, 1500 KB  
Communication
Conceptual Study on the Implementation of NRTA for Industrial Applications
by Melissa Azzoune, Ludovic Mathieu, Ngoc Duy Trinh, Mourad Aïche, Laurence Villatte, Fabrice Piquemal, Lionel Tondut and Sylvain Pelletier
Instruments 2025, 9(4), 30; https://doi.org/10.3390/instruments9040030 - 26 Nov 2025
Viewed by 184
Abstract
Neutron Resonance Transmission Analysis (NRTA) is a non-destructive technique allowing the elemental and isotopic characterization of materials and objects. This study represents a first step toward understanding the NRTA technique and developing a novel compact system adapted for industrial applications. The industrial feasibility [...] Read more.
Neutron Resonance Transmission Analysis (NRTA) is a non-destructive technique allowing the elemental and isotopic characterization of materials and objects. This study represents a first step toward understanding the NRTA technique and developing a novel compact system adapted for industrial applications. The industrial feasibility of the NRTA was assessed by simulating a compact system using the Monte Carlo code MCNP 6.1. Neutron transmission spectra were generated for various metallic samples, ranging from 0.1 mm to 1 cm in thickness, and analyzed using a home-developed quantification method that incorporates nuclear cross sections from the ENDF/B-VIII.0 library and accounts for instrumental resolution. For this first study, an idealized configuration was considered, with a 0 µs pulsed neutron source and a Gaussian resolution function, to validate the methodology under a simple controlled condition. The results demonstrate that the areal densities of isotopes of Uranium and Plutonium can be determined with relative deviations below 10%, even under compact measurement conditions. This study validates the characterization method and represents a first step toward the continued development of an industrial NRTA prototype for rapid, non-destructive isotopic control of nuclear materials. Full article
(This article belongs to the Special Issue Instrumentation and Measurement Methods for Industry 4.0 and IoT)
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