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Metrology for Industry 4.0 & IoT 2023
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Metrology for Industry 4.0 & IoT 2023

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

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 10363

Special Issue Editors

Dr. Matteo Nardello

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Trento, I-38123 Trento, Italy
Interests: signal processing; embedded electronic systems; Internet of Thing
Special Issues, Collections and Topics in MDPI journals
Dr. Daniela Lo Presti

E-Mail Website
Guest Editor
Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy
Interests: Fiber Bragg gratings; measuring systems development and assessment; wearables for health monitoring; physiological monitoring; joint movements detections
Special Issues, Collections and Topics in MDPI journals
Dr. Sarah Tonello

E-Mail Website
Guest Editor
Department of Information Engineering, University of Padua, 35131 Padua, Italy
Interests: biosensors; electrochemical biosensing; cell culture electrical monitoring; tissue engineering; printed electronics for biotechnological applications; points of care development; biosignal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 2023 IEEE International Workshop on Metrology for Industry 4.0 & IoT (https://www.metroind40iot.org/) will be held in Italy.

The authors of the papers presented at the workshop related to Sensors are invited to submit extended versions of their work to this Special Issue for publication.

The 6th edition of IEEE MetroInd4.0&IoT aims to discuss the contributions both of the metrology for the development of Industry 4.0 and IoT and the new opportunities offered by Industry 4.0 and IoT for the development of new measurement methods and instruments.

Topics:

  • Industrial sensors;
  • Virtual sensors, sensor interfacing;
  • IoT enabled sensors and measurement systems;
  • Measurement applications based on IoT;
  • Industrial IoT and Factory of Things and Internet of Things;
  • Wireless sensor networks and IoT;
  • Wearables and Body Sensor Networks;
  • Sensors Data Management;
  • Localization Technologies.

Dr. Matteo Nardello
Dr. Daniela Lo Presti
Dr. Sarah Tonello
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.

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Published Papers (4 papers)

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Research

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16 pages, 2671 KiB  
Article
Advancing Thrombosis Research: A Novel Device for Measuring Clot Permeability
by Elia Landi, Marco Mugnaini, Tunahan Vatansever, Ada Fort, Valerio Vignoli, Elvira Giurranna, Flavia Rita Argento, Eleonora Fini, Giacomo Emmi, Claudia Fiorillo and Matteo Becatti
Sensors 2024, 24(12), 3764; https://doi.org/10.3390/s24123764 - 9 Jun 2024
Viewed by 1211
Abstract
Thromboembolism, a global leading cause of mortality, needs accurate risk assessment for effective prophylaxis and treatment. Current stratification methods fall short in predicting thrombotic events, emphasizing the need for a deeper understanding of clot properties. Fibrin clot permeability, a crucial parameter in hypercoagulable [...] Read more.
Thromboembolism, a global leading cause of mortality, needs accurate risk assessment for effective prophylaxis and treatment. Current stratification methods fall short in predicting thrombotic events, emphasizing the need for a deeper understanding of clot properties. Fibrin clot permeability, a crucial parameter in hypercoagulable states, impacts clot structure and resistance to lysis. Current clot permeability measurement limitations propel the need for standardized methods. Prior findings underscore the importance of clot permeability in various thrombotic conditions but call for improvements and more precise, repeatable, and standardized methods. Addressing these challenges, our study presents an upgraded, portable, and cost-effective system for measuring blood clot permeability, which utilizes a pressure-based approach that adheres to Darcy’s law. By enhancing precision and sensitivity in discerning clot characteristics, this innovation provides a valuable tool for assessing thrombotic risk and associated pathological conditions. In this paper, the authors present a device that is able to automatically perform the permeability measurements on plasma or fibrinogen in vitro-induced clots on specific holders (filters). The proposed device has been tailored to distinguish clot permeability, with high precision and sensitivity, between healthy subjects and high cardiovascular-risk patients. The precise measure of clot permeability represents an excellent indicator of thrombotic risk, thus allowing the clinician, also on the basis of other anamnestic and laboratory data, to attribute a risk score to the subject. The proposed instrument was characterized by performing permeability measurements in plasma and purified fibrinogen clots derived from 17 Behcet patients and 15 sex- and age-matched controls. As expected, our results clearly indicate a significant difference in plasma clot permeability in Behcet patients with respect to controls (0.0533 ± 0.0199 d vs. 0.0976 ± 0.0160 d, p < 0.001). This difference was confirmed in the patient’s vs. control fibrin clots (0.0487 ± 0.0170 d vs. 0.1167 ± 0.0487 d, p < 0.001). In conclusion, our study demonstrates the feasibility, efficacy, portability, and cost-effectiveness of a novel device for measuring clot permeability, allowing healthcare providers to better stratify thrombotic risk and tailor interventions, thereby improving patient outcomes and reducing healthcare costs, which could significantly improve the management of thromboembolic diseases. Full article
(This article belongs to the Special Issue Metrology for Industry 4.0 & IoT 2023)
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14 pages, 2465 KiB  
Article
Flexible Matrices for the Encapsulation of Plant Wearable Sensors: Influence of Geometric and Color Features on Photosynthesis and Transpiration
by Daniela Lo Presti, Sara Cimini, Francesca De Tommasi, Carlo Massaroni, Stefano Cinti, Laura De Gara and Emiliano Schena
Sensors 2024, 24(5), 1611; https://doi.org/10.3390/s24051611 - 1 Mar 2024
Cited by 1 | Viewed by 1416
Abstract
The safeguarding of plant health is vital for optimizing crop growth practices, especially in the face of the biggest challenges of our generation, namely the environmental crisis and the dramatic changes in the climate. Among the many innovative tools developed to address these [...] Read more.
The safeguarding of plant health is vital for optimizing crop growth practices, especially in the face of the biggest challenges of our generation, namely the environmental crisis and the dramatic changes in the climate. Among the many innovative tools developed to address these issues, wearable sensors have recently been proposed for monitoring plant growth and microclimates in a sustainable manner. These systems are composed of flexible matrices with embedded sensing elements, showing promise in revolutionizing plant monitoring without being intrusive. Despite their potential benefits, concerns arise regarding the effects of the long-term coexistence of these devices with the plant surface. Surprisingly, a systematic analysis of their influence on plant physiology is lacking. This study aims to investigate the effect of the color and geometric features of flexible matrices on two key plant physiological functions: photosynthesis and transpiration. Our findings indicate that the negative effects associated with colored substrates, as identified in recent research, can be minimized by holing the matrix surface with a percentage of voids of 15.7%. This approach mitigates interference with light absorption and reduces water loss to a negligible extent, making our work one of the first pioneering efforts in understanding the intricate relationship between plant wearables’ features and plant health. Full article
(This article belongs to the Special Issue Metrology for Industry 4.0 & IoT 2023)
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Review

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17 pages, 424 KiB  
Review
Exploring Digital Twin-Based Fault Monitoring: Challenges and Opportunities
by Jherson Bofill, Mideth Abisado, Jocelyn Villaverde and Gabriel Avelino Sampedro
Sensors 2023, 23(16), 7087; https://doi.org/10.3390/s23167087 - 10 Aug 2023
Cited by 8 | Viewed by 4002
Abstract
High efficiency and safety are critical factors in ensuring the optimal performance and reliability of systems and equipment across various industries. Fault monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults [...] Read more.
High efficiency and safety are critical factors in ensuring the optimal performance and reliability of systems and equipment across various industries. Fault monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring system performance and identifying the presence of faults or abnormalities. However, traditional FM methods face limitations in fully capturing the complex interactions within a system and providing real-time monitoring capabilities. To overcome these challenges, Digital Twin (DT) technology has emerged as a promising solution to enhance existing FM practices. By creating a virtual replica or digital copy of a physical equipment or system, DT offers the potential to revolutionize fault monitoring approaches. This paper aims to explore and discuss the diverse range of predictive methods utilized in DT and their implementations in FM across industries. Furthermore, it will showcase successful implementations of DT in FM across a wide array of industries, including manufacturing, energy, transportation, and healthcare. The utilization of DT in FM enables a comprehensive understanding of system behavior and performance by leveraging real-time data, advanced analytics, and machine learning algorithms. By integrating physical and virtual components, DT facilitates the monitoring and prediction of faults, providing valuable insights into the system’s health and enabling proactive maintenance and decision making. Full article
(This article belongs to the Special Issue Metrology for Industry 4.0 & IoT 2023)
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30 pages, 753 KiB  
Review
A Survey of Image-Based Fault Monitoring in Additive Manufacturing: Recent Developments and Future Directions
by Ryanne Gail Kim, Mideth Abisado, Jocelyn Villaverde and Gabriel Avelino Sampedro
Sensors 2023, 23(15), 6821; https://doi.org/10.3390/s23156821 - 31 Jul 2023
Cited by 9 | Viewed by 3114
Abstract
Additive manufacturing (AM) has emerged as a transformative technology for various industries, enabling the production of complex and customized parts. However, ensuring the quality and reliability of AM parts remains a critical challenge. Thus, image-based fault monitoring has gained significant attention as an [...] Read more.
Additive manufacturing (AM) has emerged as a transformative technology for various industries, enabling the production of complex and customized parts. However, ensuring the quality and reliability of AM parts remains a critical challenge. Thus, image-based fault monitoring has gained significant attention as an efficient approach for detecting and classifying faults in AM processes. This paper presents a comprehensive survey of image-based fault monitoring in AM, focusing on recent developments and future directions. Specifically, the proponents garnered relevant papers from 2019 to 2023, gathering a total of 53 papers. This paper discusses the essential techniques, methodologies, and algorithms employed in image-based fault monitoring. Furthermore, recent developments are explored such as the use of novel image acquisition techniques, algorithms, and methods. In this paper, insights into future directions are provided, such as the need for more robust image processing algorithms, efficient data acquisition and analysis methods, standardized benchmarks and datasets, and more research in fault monitoring. By addressing these challenges and pursuing future directions, image-based fault monitoring in AM can be enhanced, improving quality control, process optimization, and overall manufacturing reliability. Full article
(This article belongs to the Special Issue Metrology for Industry 4.0 & IoT 2023)
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