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Future Internet
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Internet of Things (IoT) for Industry 4.0
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Internet of Things (IoT) for Industry 4.0

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (5 July 2022) | Viewed by 17257

Special Issue Editors

Dr. Sylvain Kubler

E-Mail Website
Guest Editor
Université de Lorraine, CRAN (Centre de Recherche en Automatique de Nancy), UMR 7039 Campus Sciences, BP 70239–54506, Vandoeuvre Cedex, France
Interests: internet of things; cyber physical systems; semantic web; multi criteria decision making (MCDM); context-awareness
Special Issues, Collections and Topics in MDPI journals
Dr. Jérémy Robert

E-Mail Website
Guest Editor
Université of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust (SnT), CAMPUS KIRCHBERG 6 Rue Richard Coudenhove-Kalergi, L-1359, Luxembourg
Interests: industry 4.0/industrial IoT; machine learning; blockchain; real-time ethernet

Special Issue Information

Dear Colleagues,

The fourth industrial revolution (also referred to as Industry 4.0) is transforming the economic paradigm and the mechanisms for creating value that underpin it. Industry has, in effect, switched from a mindset of mass production to one of mass customization, as it is no longer based on scale and volume effects but rather “on demand”. Thanks to the advent of the Internet of Things (IoT) used in industrial environments, an increasingly amount of data is now available. In that context, five main drivers are leading this paradigm shift:

  1. Virtual factories: to enable new products to be industrialized virtually before disrupting the physical system and offer managers a new way of overseeing operations and intervening in them;
  2. Automated flows: to make the whole system more flexible and responsive, cutting inventory levels and throughput;
  3. Smart machines: to reduce operator interventions by enabling machines to operate both separately from and in connection with each other;
  4. Predictive maintenance and decision support systems: to enable improved planning of machine downtime;
  5. Cyber-production systems: to enable mass customization and the readjustment of production planning in line with demand variations.

Several research issues remain to be addressed regarding each of these drivers. This MDPI Future Internet Special Issue is currently open for submission and aims to bring together researchers and application developers working out research issues, strategies, and methodologies in these different areas. We also welcome quality review articles that analyze the gap between the state-of-the-art and the state-of-the-practice in the above areas. Potential topics include but are not limited to:

  • Interoperability in data collection;
  • Cloud manufacturing;
  • Green and sustainable manufacturing;
  • Big data analytics for manufacturing applications;
  • Machine learning for enhanced process control and quality;
  • Predictive manufacturing and maintenance;
  • Blockchain and smart contracts for industrial and manufacturing purposes;
  • Physical internet.

Dr. Sylvain Kubler
Dr. Jérémy Robert
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. Future Internet 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 1600 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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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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16 pages, 3431 KiB  
Article
Improved Dragonfly Optimization Algorithm for Detecting IoT Outlier Sensors
by Maytham N. Meqdad, Seifedine Kadry and Hafiz Tayyab Rauf
Future Internet 2022, 14(10), 297; https://doi.org/10.3390/fi14100297 - 17 Oct 2022
Cited by 2 | Viewed by 2221
Abstract
Things receive digital intelligence by being connected to the Internet and by adding sensors. With the use of real-time data and this intelligence, things may communicate with one another autonomously. The environment surrounding us will become more intelligent and reactive, merging the digital [...] Read more.
Things receive digital intelligence by being connected to the Internet and by adding sensors. With the use of real-time data and this intelligence, things may communicate with one another autonomously. The environment surrounding us will become more intelligent and reactive, merging the digital and physical worlds thanks to the Internet of things (IoT). In this paper, an optimal methodology has been proposed for distinguishing outlier sensors of the Internet of things based on a developed design of a dragonfly optimization technique. Here, a modified structure of the dragonfly optimization algorithm is utilized for optimal area coverage and energy consumption reduction. This paper uses four parameters to evaluate its efficiency: the minimum number of nodes in the coverage area, the lifetime of the network, including the time interval from the start of the first node to the shutdown time of the first node, and the network power. The results of the suggested method are compared with those of some other published methods. The results show that by increasing the number of steps, the energy of the live nodes will eventually run out and turn off. In the LEACH method, after 350 steps, the RED-LEACH method, after 750 steps, and the GSA-based method, after 915 steps, the nodes start shutting down, which occurs after 1227 steps for the proposed method. This means that the nodes are turned off later. Simulations indicate that the suggested method achieves better results than the other examined techniques according to the provided performance parameters. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Industry 4.0)
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12 pages, 371 KiB  
Article
IoT Group Membership Management Using Decentralized Identifiers and Verifiable Credentials
by Nikos Fotiou, Vasilios A. Siris, George Xylomenos and George C. Polyzos
Future Internet 2022, 14(6), 173; https://doi.org/10.3390/fi14060173 - 1 Jun 2022
Cited by 1 | Viewed by 2299
Abstract
Many IoT use cases can benefit from group communication, where a user requests an IoT resource and this request can be handled by multiple IoT devices, each of which may respond back to the user. IoT group communication involves one-to-many requests and many-to-one [...] Read more.
Many IoT use cases can benefit from group communication, where a user requests an IoT resource and this request can be handled by multiple IoT devices, each of which may respond back to the user. IoT group communication involves one-to-many requests and many-to-one responses, and this creates security challenges. In this paper, we focus on the provenance that has been received by an authorized device. We provide an effective and flexible solution for securing IoT group communication using CoAP, where a CoAP client sends a request to a CoAP group and receives multiple responses by many IoT devices, acting as CoAP servers. We design a solution that allows CoAP servers to digitally sign their responses in a way that clients can verify that a response has been generated by an authorized member of the CoAP group. In order to achieve our goal, we leverage Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs). In particular, we consider that each group is identified by a DID, and each group member has received a VC that allows it to participate in that group. The only information a client needs to know is the DID of the group, which is learned using DNSSEC. Our solution allows group members to rotate their signing keys, it achieves group member revocation, and it has minimal communication and computational overhead. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Industry 4.0)
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45 pages, 12696 KiB  
Article
HyDSMaaS: A Hybrid Communication Infrastructure with LoRaWAN and LoraMesh for the Demand Side Management as a Service
by Artur Felipe da Silva Veloso, José Valdemir Reis Júnior, Ricardo de Andrade Lira Rabelo and Jocines Dela-flora Silveira
Future Internet 2021, 13(11), 271; https://doi.org/10.3390/fi13110271 - 26 Oct 2021
Cited by 4 | Viewed by 3566
Abstract
Seeking to solve problems in the power electric system (PES) related to exacerbated and uncontrolled energy consumption by final consumers such as residences, condominiums, public buildings and industries, electric power companies (EPC) are increasingly seeking new information and communication technologies (ICTs) to transform [...] Read more.
Seeking to solve problems in the power electric system (PES) related to exacerbated and uncontrolled energy consumption by final consumers such as residences, condominiums, public buildings and industries, electric power companies (EPC) are increasingly seeking new information and communication technologies (ICTs) to transform traditional electric power distribution networks into smart grids (SG). With this implementation, PES will be able to remotely control electric power consumption as well as monitor data generated by smart meters (SM). However, Internet-of-Things (IoT) technologies will enable all this to happen quickly and at low cost, since they are low-cost devices that can be deployed quickly and at scale in these scenarios. With this in mind, this work aimed to study, propose, and implement a hybrid communication infrastructure with LoRaWAN and LoraMesh for the demand-side management as a service (HyDSMaaS) using IoT devices such as long range (LoRa) to provide an advanced metering infrastructure (AMI) capable of performing all these applications as a service offered by EPC to end consumers. Additionally, services such as demand-side management (DSMaaS) can be used in this infrastructure. From the preliminary results it was found that the LoRaWAN network achieved a range of up to 2.35 km distance and the LoRaMESH one of 600 m; thus, the latter is more suitable for scenarios where there is little interference and the SMs are at long distances, while the other is used for scenarios with greater agglomeration of nearby SMs. Considering the hybridized scenario between LoraWAN and LoRaMESH, it can be seen that the implementation possibilities increase, since its range was approximately 3 km considering only one hop, and it can reach 1023 devices present in a mesh network. Thus, it was possible to propose the actual implementation of LoRaWAN and LoRaMESH protocols as well as the hybridization of the two protocols for HyDSMaaS. Additionally, the results obtained are exclusively from Radioenge’s LoRa technology, which can be further improved in the case of using more powerful equipment. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Industry 4.0)
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23 pages, 1904 KiB  
Article
Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda
by Irene Niyonambaza, Marco Zennaro and Alfred Uwitonze
Future Internet 2020, 12(12), 224; https://doi.org/10.3390/fi12120224 - 7 Dec 2020
Cited by 19 | Viewed by 7843
Abstract
The success of all industries relates to attaining the satisfaction to clients with a high level of services and productivity. The success main factor depends on the extent of maintaining their equipment. To date, the Rwandan hospitals that always have a long queue [...] Read more.
The success of all industries relates to attaining the satisfaction to clients with a high level of services and productivity. The success main factor depends on the extent of maintaining their equipment. To date, the Rwandan hospitals that always have a long queue of patients that are waiting for service perform a repair after failure as common maintenance practice that may involve unplanned resources, cost, time, and completely or partially interrupt the remaining hospital activities. Aiming to reduce unplanned equipment downtime and increase their reliability, this paper proposes the Predictive Maintenance (PdM) structure while using Internet of Things (IoT) in order to predict early failure before it happens for mechanical equipment that is used in Rwandan hospitals. Because prediction relies on data, the structure design consists of a simplest developed real time data collector prototype with the purpose of collecting real time data for predictive model construction and equipment health status classification. The real time data in the form of time series have been collected from selected equipment components in King Faisal Hospital and then later used to build a proposed predictive time series model to be employed in proposed structure. The Long Short Term Memory (LSTM) Neural Network model is used to learn data and perform with an accuracy of 90% and 96% to different two selected components. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Industry 4.0)
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