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Sensor Networks for the Industrial Internet of Things
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Sensor Networks for the Industrial Internet of Things

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

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 17193

Special Issue Editors

Prof. Dr. Paolo Ferrari

E-Mail Website
Guest Editor
UNIBS-DIE, Department of Information Engineering, University of Brescia, 25123 Brescia, Italy
Interests: sensor network; distributed measurement systems; industrial communication; real-time ethernet; clock synchronization; industrial IoT; industrial security; wireless sensors; smart city
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ivanovitch Silva

E-Mail Website
Guest Editor
Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil
Interests: big data; Industry 4.0; intelligent vehicles; data modeling and analysis; wireless sensors; smart city
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Dennis Brandão

E-Mail Website
Guest Editor
Dep. of Electrical and Computing Engineering, São Carlos, University of São Paulo
Interests: industrial sensor network; industrial communication; real-time ethernet; process automation; industrial automation; smart factory; intelligent diagnostic systems; smart city
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

The importance of sensor networks is always increasing in the industry. Recent advances in Industry 4.0 demonstrate the significant savings that continuous monitoring of production can achieve. However, the Industrial Internet of Things, where sensors and instruments are placed on a wide area or mobile systems, remains hugely challenging.

In such cases, wireless or other innovative technology is often mandatory, because of intrinsic incompatibilities (the mobile device cannot use wires) or high cost of wired infrastructure to cover large (geographical) areas. In recent years, the 5G revolution and the advent of specialized wireless protocols for low-power wide area networks have boosted Internet-connected devices’ diffusion also in industry. The combination of new technologies has a very positive impact on sensor networks for “production” and “monitoring of product” in the era of the Industrial Internet of Things.

This Special Session is focused on solutions for scenarios or situations where sensor networks are deployed in industrial areas.

Submissions are welcomed on (but not limited to):

  • Industrial sensors and IoT;
  • Virtual sensors, soft sensors, sensor interfacing with Industrial IoT;
  • Wearables and body sensor networks for workers;
  • Sensors for continued tracking of product data after sale (digital twin);
  • Wireless sensor networks for the Industrial Internet of Things;
    • Short-range wireless networks for the Industrial Internet of Things;
    • Bluetooth LE applications to the Industrial Internet of Things;
    • 5G/4G applications to the Industrial Internet of Things;
    • LPWAN systems for the Industrial Internet of Things;
  • Connected industrial vehicles equipped with sensors systems;
  • Distributed mobile IoT sensor systems;
  • Wireless sensor localization in industrial IoT applications;
  • Sensor-based measurement systems for the Industrial Internet of Things;
  • Large scale deployment of sensors (e.g., environment monitoring, fire detection) in the industrial context;
  • Cloud architectures to manage scalable sensor systems and sensing data platform for massive deployment in an industrial scenario;
  • Security of sensor network in the Industrial Internet of Things;
  • Applications of IoT sensors and systems to large industrial plants.

Prof. Dr. Paolo Ferrari
Prof. Dr. Ivanovitch Silva
Prof. Dr. Dennis Brandão
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 (5 papers)

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19 pages, 1760 KiB  
Article
Enabling the Industrial Internet of Things to Cloud Continuum in a Real City Environment
by Fábio Henrique Cabrini, Filippo Valiante Filho, Pedro Rito, Albérico Barros Filho, Susana Sargento, Augusto Venâncio Neto and Sergio Takeo Kofuji
Sensors 2021, 21(22), 7707; https://doi.org/10.3390/s21227707 - 19 Nov 2021
Cited by 14 | Viewed by 3929
Abstract
The Industrial Internet of Things (IIoT) is one of the most demanding IoT applications. The insertion of industries in the context of smart cities and other smart environments, allied with new communication technologies such as 5G, brings a new horizon of possibilities and [...] Read more.
The Industrial Internet of Things (IIoT) is one of the most demanding IoT applications. The insertion of industries in the context of smart cities and other smart environments, allied with new communication technologies such as 5G, brings a new horizon of possibilities and new requirements. These requirements include low latency, the support of a massive quantity of devices and data, and the need to support horizontal communications between devices at the edge level. To make this feasible, it is necessary to establish an IIoT-to-cloud continuum distributing federated brokers across the infrastructure and providing scalability and interoperability. To attend this type of application, we present the Helix Multi-layered IoT platform and its operating modes. We report and discuss its real-world deployment in the Aveiro Tech City Living Lab in Aveiro, Portugal with functional and performance tests. We tested device-to-device communication across edge and core layers and also interconnected the infrastructure with one in São Paulo, Brazil, replicating the use of a global industry. The successful deployment validates the use of a Helix Multi-layered IoT platform as a suitable backend platform for IIoT applications capable of establishing the IIoT-to-cloud continuum. It also helps for the deployment of other applications in such a domain. Full article
(This article belongs to the Special Issue Sensor Networks for the Industrial Internet of Things)
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21 pages, 2074 KiB  
Article
Semantic Description of Quality of Data in Sensor Networks
by Anupam Prasad Vedurmudi, Julia Neumann, Maximilian Gruber and Sascha Eichstädt
Sensors 2021, 21(19), 6462; https://doi.org/10.3390/s21196462 - 28 Sep 2021
Cited by 14 | Viewed by 2897
Abstract
The annotation of sensor data with semantic metadata is essential to the goals of automation and interoperability in the context of Industry 4.0. In this contribution, we outline a semantic description of quality of data in sensor networks in terms of indicators, metrics [...] Read more.
The annotation of sensor data with semantic metadata is essential to the goals of automation and interoperability in the context of Industry 4.0. In this contribution, we outline a semantic description of quality of data in sensor networks in terms of indicators, metrics and interpretations. The concepts thus defined are consolidated into an ontology that describes quality of data metainformation in heterogeneous sensor networks and methods for the determination of corresponding quality of data dimensions are outlined. By incorporating support for sensor calibration models and measurement uncertainty via a previously derived ontology, a conformity with metrological requirements for sensor data is ensured. A quality description for a calibrated sensor generated using the resulting ontology is presented in the JSON-LD format using the battery level and calibration data as quality indicators. Finally, the general applicability of the model is demonstrated using a series of competency questions. Full article
(This article belongs to the Special Issue Sensor Networks for the Industrial Internet of Things)
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18 pages, 925 KiB  
Article
OPAL—The Toolbox for the Integration and Analysis of IoT in a Semantically Annotated Way
by Philipp Hertweck, Tobias Hellmund and Jürgen Moßgraber
Sensors 2021, 21(12), 4002; https://doi.org/10.3390/s21124002 - 10 Jun 2021
Viewed by 2592
Abstract
Industrial Internet of Things (IIoT) applications are being used more and more frequently. Data collected by various sensors can be used to provide innovative digital services supporting increasing efficiency or cost reduction. The implementation of such applications requires the integration and analysis of [...] Read more.
Industrial Internet of Things (IIoT) applications are being used more and more frequently. Data collected by various sensors can be used to provide innovative digital services supporting increasing efficiency or cost reduction. The implementation of such applications requires the integration and analysis of heterogeneous data coming from a broad variety of sensors. To support these steps, this paper introduces OPAL, a software toolbox consolidating several software components for the semantically annotated integration and analysis of IoT-data. Data storage is realized in a standardized and INSPIRE-compliant way utilizing the SensorThings API. Supporting a broad variety of use cases, OPAL provides several import adapters to access data sources with various protocols (e.g., the OPC UA protocol, which is often used in industrial environments). In addition, a unified management and execution environment, called PERMA, is introduced to allow the programming language independent integration of algorithms. Full article
(This article belongs to the Special Issue Sensor Networks for the Industrial Internet of Things)
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14 pages, 889 KiB  
Article
A Hierarchical Routing Graph for Supporting Mobile Devices in Industrial Wireless Sensor Networks
by Sangdae Kim, Cheonyong Kim, Hyunchong Cho and Kwansoo Jung
Sensors 2021, 21(2), 458; https://doi.org/10.3390/s21020458 - 11 Jan 2021
Cited by 5 | Viewed by 2184
Abstract
As many industrial applications require real-time and reliability communication, a variety of routing graph construction schemes were proposed to satisfy the requirements in Industrial Wireless Sensor Networks (IWSNs). Each device transmits packet through a route which is designated based on the graph. However, [...] Read more.
As many industrial applications require real-time and reliability communication, a variety of routing graph construction schemes were proposed to satisfy the requirements in Industrial Wireless Sensor Networks (IWSNs). Each device transmits packet through a route which is designated based on the graph. However, as existing studies consider a network consists of static devices only, they cannot cope with the network changes by movement of mobile devices considered important in the recent industrial environment. Thus, the communication requirements cannot be guaranteed because the existing path is broken by the varying network topology. The communication failure could cause critical problems such as malfunctioning equipment. The problem is caused repeatedly by continuous movement of mobile devices, even if a new graph is reconstructed for responding the changed topology. To support mobile devices exploited in various industrial environments, we propose a Hierarchical Routing Graph Construction (HRGC). The HRGC is consisted of two phases for hierarchical graph construction: In first phase, a robust graph called skeleton graph consisting only of static devices is constructed. The skeleton graph is not affected by network topology changes and does not suffer from packet loss. In second phase, the mobile devices are grafted into the skeleton graph for seamless communication. Through the grafting process, the routes are established in advance for mobile device to communicate with nearby static devices in anywhere. The simulation results show that the packet delivery ratio is improved when the graph is constructed through the HRGC. Full article
(This article belongs to the Special Issue Sensor Networks for the Industrial Internet of Things)
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25 pages, 1177 KiB  
Systematic Review
Reasons and Strategies for Privacy Features in Tracking and Tracing Systems—A Systematic Literature Review
by Christian Jandl, Markus Wagner, Thomas Moser and Sebastian Schlund
Sensors 2021, 21(13), 4501; https://doi.org/10.3390/s21134501 - 30 Jun 2021
Cited by 5 | Viewed by 4561
Abstract
In the course of the digitization of production facilities, tracking and tracing of assets in the supply chain is becoming increasingly relevant for the manufacturing industry. The collection and use of real-time position data of logistics, tools and load carriers are already standard [...] Read more.
In the course of the digitization of production facilities, tracking and tracing of assets in the supply chain is becoming increasingly relevant for the manufacturing industry. The collection and use of real-time position data of logistics, tools and load carriers are already standard procedure in entire branches of the industry today. In addition to asset tracking, the technologies used also offer new possibilities for collecting and evaluating position and biometric data of employees. Thus, these technologies can be used for monitoring performance or for tracking worker behaviour, which can lead to additional burdens and stress for employees. In this context, the collection and evaluation of employee data can influence the workplace of the affected employee in the company to his or her disadvantage. The approach of Privacy by Design can help to benefit from all the advantages of these systems, while ensuring that the impact on employee privacy is kept to a minimum. Currently, there is no survey available that reviews tracking and tracing systems supporting this important and emerging field. This work provides a systematic overview from the perspective of the impact on employee privacy. Additionally, this paper identifies and evaluates the techniques used with regard to employee privacy in industrial tracking and tracing systems. This helps to reveal new privacy preserving techniques that are currently underrepresented, therefore enabling new research opportunities in the industrial community. Full article
(This article belongs to the Special Issue Sensor Networks for the Industrial Internet of Things)
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