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Special Issue "Sensor Networks and Systems to Enable Industry 4.0 Environments"

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)

Special Issue Editor

Guest Editor
Dr. Francisco Falcone

Department of Electrical and Electronic Engineering, Public University of Navarre, Spain
Website 1 | Website 2 | E-Mail
Interests: wireless networks; performance evaluation; distributed systems; context aware environments; IoT; next generation wireless systems

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 papers will be 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 monthly 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 1800 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.

Published Papers (6 papers)

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Research

Open AccessArticle RFID Technology for Management and Tracking: e-Health Applications
Sensors 2018, 18(8), 2663; https://doi.org/10.3390/s18082663
Received: 15 July 2018 / Revised: 7 August 2018 / Accepted: 10 August 2018 / Published: 13 August 2018
PDF Full-text (6973 KB) | HTML Full-text | XML Full-text | Supplementary Files
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.
[...] Read more.
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)
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Open AccessArticle Industrial Data Space Architecture Implementation Using FIWARE
Sensors 2018, 18(7), 2226; https://doi.org/10.3390/s18072226
Received: 22 June 2018 / Revised: 6 July 2018 / Accepted: 8 July 2018 / Published: 11 July 2018
PDF Full-text (2685 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
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Open AccessArticle A Fog Computing Based Cyber-Physical System for the Automation of Pipe-Related Tasks in the Industry 4.0 Shipyard
Sensors 2018, 18(6), 1961; https://doi.org/10.3390/s18061961
Received: 27 April 2018 / Revised: 12 June 2018 / Accepted: 13 June 2018 / Published: 17 June 2018
Cited by 4 | PDF Full-text (45012 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
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Open AccessArticle A Fog Computing and Cloudlet Based Augmented Reality System for the Industry 4.0 Shipyard
Sensors 2018, 18(6), 1798; https://doi.org/10.3390/s18061798
Received: 1 May 2018 / Revised: 30 May 2018 / Accepted: 31 May 2018 / Published: 2 June 2018
Cited by 3 | PDF Full-text (18769 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
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Open AccessArticle An Effective Delay Reduction Approach through a Portion of Nodes with a Larger Duty Cycle for Industrial WSNs
Sensors 2018, 18(5), 1535; https://doi.org/10.3390/s18051535
Received: 31 March 2018 / Revised: 5 May 2018 / Accepted: 5 May 2018 / Published: 12 May 2018
Cited by 4 | PDF Full-text (4807 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
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Open AccessArticle WARCProcessor: An Integrative Tool for Building and Management of Web Spam Corpora
Sensors 2018, 18(1), 16; https://doi.org/10.3390/s18010016
Received: 24 November 2017 / Revised: 16 December 2017 / Accepted: 18 December 2017 / Published: 22 December 2017
PDF Full-text (5335 KB) | HTML Full-text | XML Full-text
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
[...] Read more.
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)
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