Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Sensor Networks and Systems to Enable Industry 4.0 Environments

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Benefits of Publishing in a Special Issue
Published Papers

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

Deadline for manuscript submissions: closed (31 August 2018) | Viewed by 55652

Share This Special Issue

Special Issue Editor

Prof. Dr. Francisco Falcone

E-Mail Website
Guest Editor

Department of Electrical, Electronic and Communication Engineering & Institute for Smart Cities (ISC), Public University of Navarre, 31006 Pamplona, Spain
Interests: wireless networks; performance evaluation; distributed systems; context-aware environments; IoT; next-generation wireless systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The growth in number and application areas of connected devices is leading towards truly interactive environments, foreseen in the paradigm of the Internet of Things, providing the means to increase functionality and interrelation between multiple systems, such as Intelligent Transportation Systems, Smart Grids or Smart Health, among others. These capabilities can also be extended into production, manufacturing, logistic and maintenance areas, in which communication capabilities combined with data analysis and advances in Cyber Physical Systems provide the grounds for the advent of Industry 4.0 environments.

In this context, multi-disciplinary approaches can be followed in order to provide the required context-awareness, adaptability, robustness and resilience, compulsory in the implementation of next generation industrial scenarios. In this sense, multiple challenges must be handled, such as distributed real time operation and communication capabilities, predictive device/system operation, interoperability, security and energy efficiency.

This Special Issue aims to highlight advances in the development, testing, and modeling of Sensor Networks and Systems as enablers of Industry 4.0, within the realm of potential applications of such systems. Topics include, but are not limited to:

Industry 4.0 Testbeds
Wireless Sensor Network and device design following Industry 4.0 requirements
Integration of Industry 4.0 with cloud processing capabilities
Simulation and modelling of Industry 4.0 enabled processes
Use cases of Cyber Physical Systems enabled for Industry 4.0 applications via WSN integration

Prof. Dr. Francisco Javier Falcone Lanas
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 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.

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (7 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

24 pages, 6332 KiB

Open AccessArticle

A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision

by Marianne Silva, Elton Vieira, Gabriel Signoretti, Ivanovitch Silva, Diego Silva and Paolo Ferrari

Sensors 2018, 18(10), 3298; https://doi.org/10.3390/s18103298 - 1 Oct 2018

Cited by 43 | Viewed by 8362

Abstract

In the last decade, the growth of the automotive market with the aid of technologies has been notable for the economic, automotive and technological sectors. Alongside this growing recognition, the so called Internet of Intelligent Vehicles (IoIV) emerges as an evolution of the Internet of Things (IoT) applied to the automotive sector. Closely related to IoIV, emerges the concept of Industrial Internet of Things (IIoT), which is the current revolution seen in industrial automation. IIoT, in its turn, relates to the concept of Industry 4.0, that is used to represent the current Industrial Revolution. This revolution, however, involves different areas: from manufacturing to healthcare. The Industry 4.0 can create value during the entire product lifecycle, promoting customer feedback, that is, having information about the product history throughout it is life. In this way, the automatic communication between vehicle and factory was facilitated, allowing the accomplishment of different analysis regarding vehicles, such as the identification of a behavioral pattern through historical driver usage, fuel consumption, maintenance indicators, so on. Thus, allowing the prevention of critical issues and undesired behaviors, since the automakers lose contact with the vehicle after the purchase. Therefore, this paper aims to propose a customer feedback platform for vehicle manufacturing in Industry 4.0 context, capable of collecting and analyzing, through an OBD-II (On-Board Diagnostics) scanner, the sensors available by vehicles, with the purpose of assisting in the management, prevention, and mitigation of different vehicular problems. An intercontinental evaluation conducted between Brazil and Italy locations shown the feasibility of platform and the potential to use in order to improve the vehicle manufacturing process. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Figure 1

17 pages, 6973 KiB

Open AccessArticle

RFID Technology for Management and Tracking: e-Health Applications

by Yuri Álvarez López, Jacqueline Franssen, Guillermo Álvarez Narciandi, Janet Pagnozzi, Ignacio González-Pinto Arrillaga and Fernando Las-Heras Andrés

Sensors 2018, 18(8), 2663; https://doi.org/10.3390/s18082663 - 13 Aug 2018

Cited by 71 | Viewed by 13526

Abstract

Radio frequency identification (RFID) has become a key technology in the logistics and management industry, thanks to distinctive features such as the low cost of RFID tags, and the easiness of the RFID tags’ deployment and integration within the items to be tracked. In consequence, RFID plays a fundamental role in the so-called digital factory or 4.0 Industry, aiming to increase the level of automatization of industrial processes. In addition, RFID has also been found to be of great help in improving the tracking of patients, medicines, and medical assets in hospitals, where the digitalization of these operations improves their efficiency and safety. This contribution reviews the state-of-the-art of RFID for e-Health applications, describing the contributions to improve medical services and discussing the limitations. In particular, it has been found that a lot of effort has been put into software development, but in most of the cases a detailed study of the physical layer (that is, the characterization of the RFID signals within the area where the system is deployed) is not properly conducted. This contribution describes a basic RFID system for tracking and managing assets in hospitals, aiming to provide additional details about implementation aspects that must be considered to ensure proper functionality of the system. Although the scope of the RFID system described in this contribution is restricted to a small area of the hospital, the architecture is fully scalable to cover the needs of the different medical services in the hospital. Ultra high-frequency (UHF) RFID technology is selected over the most extended near-field communication (NFC) and high-frequency (HF) RFID technology to minimize hardware infrastructure. In particular, UHF RFID also makes the coverage/reading area conformation easier by using different kinds of antennas. Information is stored in a database, which is accessed from end-user mobile devices (tablets, smartphones) where the position and status of the assets to be tracked are displayed. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Graphical abstract

18 pages, 2685 KiB

Open AccessArticle

Industrial Data Space Architecture Implementation Using FIWARE

by Álvaro Alonso, Alejandro Pozo, José Manuel Cantera, Francisco De la Vega and Juan José Hierro

Sensors 2018, 18(7), 2226; https://doi.org/10.3390/s18072226 - 11 Jul 2018

Cited by 61 | Viewed by 7045

Abstract

We are in front of a new digital revolution that will transform the way we understand and use services and infrastructures. One of the key factors of this revolution is related to the evolution of the Internet of Things (IoT). Connected sensors will be installed in cities and homes affecting the daily life of people and providing them new ways of performing their daily activities. However, this revolution will also affect business and industry bringing the IoT to the production processes in what is called Industry 4.0. Sensor-enabled manufacturing equipment will allow real time communication, smart diagnosis and autonomous decision making. In this scope, the Industrial Data Spaces (IDS) Association has created a Reference Architecture model that aims to provide a common frame for designing and deploying Industry IoT infrastructures. In this paper, we present an implementation of such Reference Architecture based on FIWARE open source software components (Generic Enablers). We validate the proposed architecture by deploying and testing it in a real industry use case that tries to improve the maintenance and operation of milling machines. We conclude that the FIWARE-based IDS implementation fits the requirements of the IDS Reference Architecture providing open source software suitable to any Industry 4.0 environment. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Figure 1

26 pages, 45012 KiB

Open AccessArticle

A Fog Computing Based Cyber-Physical System for the Automation of Pipe-Related Tasks in the Industry 4.0 Shipyard

by Tiago M. Fernández-Caramés, Paula Fraga-Lamas, Manuel Suárez-Albela and Manuel A. Díaz-Bouza

Sensors 2018, 18(6), 1961; https://doi.org/10.3390/s18061961 - 17 Jun 2018

Cited by 68 | Viewed by 7630

Abstract

Pipes are one of the key elements in the construction of ships, which usually contain between 15,000 and 40,000 of them. This huge number, as well as the variety of processes that may be performed on a pipe, require rigorous identification, quality assessment and traceability. Traditionally, such tasks have been carried out by using manual procedures and following documentation on paper, which slows down the production processes and reduces the output of a pipe workshop. This article presents a system that allows for identifying and tracking the pipes of a ship through their construction cycle. For such a purpose, a fog computing architecture is proposed to extend cloud computing to the edge of the shipyard network. The system has been developed jointly by Navantia, one of the largest shipbuilders in the world, and the University of A Coruña (Spain), through a project that makes use of some of the latest Industry 4.0 technologies. Specifically, a Cyber-Physical System (CPS) is described, which uses active Radio Frequency Identification (RFID) tags to track pipes and detect relevant events. Furthermore, the CPS has been integrated and tested in conjunction with Siemens’ Manufacturing Execution System (MES) (Simatic IT). The experiments performed on the CPS show that, in the selected real-world scenarios, fog gateways respond faster than the tested cloud server, being such gateways are also able to process successfully more samples under high-load situations. In addition, under regular loads, fog gateways react between five and 481 times faster than the alternative cloud approach. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Figure 1

18 pages, 18769 KiB

Open AccessArticle

A Fog Computing and Cloudlet Based Augmented Reality System for the Industry 4.0 Shipyard

by Tiago M. Fernández-Caramés, Paula Fraga-Lamas, Manuel Suárez-Albela and Miguel Vilar-Montesinos

Sensors 2018, 18(6), 1798; https://doi.org/10.3390/s18061798 - 2 Jun 2018

Cited by 115 | Viewed by 9148

Abstract

Augmented Reality (AR) is one of the key technologies pointed out by Industry 4.0 as a tool for enhancing the next generation of automated and computerized factories. AR can also help shipbuilding operators, since they usually need to interact with information (e.g., product datasheets, instructions, maintenance procedures, quality control forms) that could be handled easily and more efficiently through AR devices. This is the reason why Navantia, one of the 10 largest shipbuilders in the world, is studying the application of AR (among other technologies) in different shipyard environments in a project called “Shipyard 4.0”. This article presents Navantia’s industrial AR (IAR) architecture, which is based on cloudlets and on the fog computing paradigm. Both technologies are ideal for supporting physically-distributed, low-latency and QoS-aware applications that decrease the network traffic and the computational load of traditional cloud computing systems. The proposed IAR communications architecture is evaluated in real-world scenarios with payload sizes according to demanding Microsoft HoloLens applications and when using a cloud, a cloudlet and a fog computing system. The results show that, in terms of response delay, the fog computing system is the fastest when transferring small payloads (less than 128 KB), while for larger file sizes, the cloudlet solution is faster than the others. Moreover, under high loads (with many concurrent IAR clients), the cloudlet in some cases is more than four times faster than the fog computing system in terms of response delay. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Figure 1

28 pages, 4807 KiB

Open AccessArticle

An Effective Delay Reduction Approach through a Portion of Nodes with a Larger Duty Cycle for Industrial WSNs

by Minrui Wu, Yanhui Wu, Chuyao Liu, Zhiping Cai, Neal N. Xiong, Anfeng Liu and Ming Ma

Sensors 2018, 18(5), 1535; https://doi.org/10.3390/s18051535 - 12 May 2018

Cited by 30 | Viewed by 4230

Abstract

For Industrial Wireless Sensor Networks (IWSNs), sending data with timely style to the stink (or control center, CC) that is monitored by sensor nodes is a challenging issue. However, in order to save energy, wireless sensor networks based on a duty cycle are widely used in the industrial field, which can bring great delay to data transmission. We observe that if the duty cycle of a small number of nodes in the network is set to 1, the sleep delay caused by the duty cycle can be effectively reduced. Thus, in this paper, a novel Portion of Nodes with Larger Duty Cycle (PNLDC) scheme is proposed to reduce delay and optimize energy efficiency for IWSNs. In the PNLDC scheme, a portion of nodes are selected to set their duty cycle to 1, and the proportion of nodes with the duty cycle of 1 is determined according to the energy abundance of the area in which the node is located. The more the residual energy in the region, the greater the proportion of the selected nodes. Because there are a certain proportion of nodes with the duty cycle of 1 in the network, the PNLDC scheme can effectively reduce delay in IWSNs. The performance analysis and experimental results show that the proposed scheme significantly reduces the delay for forwarding data by 8.9~26.4% and delay for detection by 2.1~24.6% without reducing the network lifetime when compared with the fixed duty cycle method. Meanwhile, compared with the dynamic duty cycle strategy, the proposed scheme has certain advantages in terms of energy utilization and delay reduction. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Figure 1

5335 KiB

Open AccessArticle

WARCProcessor: An Integrative Tool for Building and Management of Web Spam Corpora

by Miguel Callón, Jorge Fdez-Glez, David Ruano-Ordás, Rosalía Laza, Reyes Pavón, Florentino Fdez-Riverola and Jose Ramón Méndez

Sensors 2018, 18(1), 16; https://doi.org/10.3390/s18010016 - 22 Dec 2017

Cited by 1 | Viewed by 4279

Abstract

In this work we present the design and implementation of WARCProcessor, a novel multiplatform integrative tool aimed to build scientific datasets to facilitate experimentation in web spam research. The developed application allows the user to specify multiple criteria that change the way in which new corpora are generated whilst reducing the number of repetitive and error prone tasks related with existing corpus maintenance. For this goal, WARCProcessor supports up to six commonly used data sources for web spam research, being able to store output corpus in standard WARC format together with complementary metadata files. Additionally, the application facilitates the automatic and concurrent download of web sites from Internet, giving the possibility of configuring the deep of the links to be followed as well as the behaviour when redirected URLs appear. WARCProcessor supports both an interactive GUI interface and a command line utility for being executed in background. Full article

(This article belongs to the Special Issue Sensor Networks and Systems to Enable Industry 4.0 Environments)

► Show Figures

Journal Menu

Journal Browser

Sensor Networks and Systems to Enable Industry 4.0 Environments

Share This Special Issue

Special Issue Editor

Special Issue Information

Benefits of Publishing in a Special Issue

Published Papers (7 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI