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Evolution of IoT and IIoT: Opportunities, Challenges, and Applications

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

Deadline for manuscript submissions: closed (1 January 2024) | Viewed by 132626

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Special Issue Editors

Dr. Nicoleta Cristina Gaitan

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Guest Editor

Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, 720229 Suceava, Romania
Interests: Industrial Internet of Things; Smart Cities; data acquisition; distributed systems; embedded systems; FPGA systems; software architecture
Special Issues, Collections and Topics in MDPI journals

Dr. Ioan Ungurean

E-Mail Website
Guest Editor

Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Suceava, Romania
Interests: real time systems; embedded systems; Industrial Internet of Things; fieldbuses; operating system

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is an emerging concept that changes people's interaction with things in everyday life. IoT allows ubiquitous objects/things to be connected to the Internet to provide innovative services that can save people time and money in their daily work and increase their quality of life. The IoT concept is applied in a wide variety of applications, such as for smart buildings, smart transportation, smart cities, smart healthcare, and smart life, in order to provide new services and cost-effectiveness. Initially, the IoT concept only used wireless technologies to connect things to the Internet, but now it can be used by any available technologies, wired and wireless. In fact, IoT can reuse cable or wireless technologies that have been used in other types of applications where different devices can connect to a direct computing system or through a Gateway. Things/objects from everyday life are brought into the virtual environment through sensors or other methods to obtain real data from their environment, such as human–machine interfaces. Acquired data or virtual things are transmitted to computing platforms where they are processed and can interact with each other, then the decisions can be transmitted to execution elements located in the environment. To put it simply, things interact with each other in the virtual environment, paving the way for a wide variety of applications including monitoring, identification, tracking, metering, resource management, etc. IoT is an evolution of the Internet from the "Internet of People", to the “Internet of Things”, and further to the "Internet of Everything". A subset of the IoT is the Industrial Internet of Things (IIoT) which includes the industrial and machine-to-machine (M2M) communication technologies used in the smart factory or the automation fields. IIoT has new challenges, such as latency constraints, network bandwidth constraints, resource-constraint devices, uninterrupted service without Internet access, and new security challenges. If we analyze the IIoT solutions from the literature, we can see that they are specific to the application for which they were developed, and are dedicated only to certain communication technologies (fieldbuses).

This Special Issue hopes to address all types of high-quality and unpublished papers which aim to solve open technical problems, opportunities, and challenges typical of the applications or systems based on intelligent sensors used for the Internet of Things and Industrial Internet of Things. Topics of interest include, but are not limited to, the following:

Smart IoT sensors (e.g., wearables, smart devices), new concepts, and paradigms and architectures;
new trends in real time systems;
sensor networks and smart computing;
heterogeneous IIoT networks;
LPWAN for IIoT (SigFox, LoRa, NB-FI, etc.);
cellular-IoT technologies (NB-IoT, LTE, and Cat-M1);
middleware, architectures, and protocols for IIoT;
5G for IIoT;
fog/edge computing for IIoT;
fieldbuses and IIoT;
intelligent IIoT management and networking services;
trustworthiness, security, and privacy for IIoT;
real time system for IIoT;
and applications and use-cases (Industry 4.0, smart cities, digital health, smart and digital agriculture, etc.).

Dr. Nicoleta Cristina Gaitan
Dr. Ioan Ungurean
Guest Editors

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Keywords

Internet of Things
sensors
Industrial Internet of Things
real time systems
embedded systems
LoRa
tensors decompositions

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Published Papers (10 papers)

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13 pages, 2736 KiB

Open AccessArticle

A Dynamic IIoT Framework Based on the Publish–Subscribe Paradigm

by Ioan Ungurean and Nicoleta Cristina Gaitan

Sensors 2023, 23(24), 9829; https://doi.org/10.3390/s23249829 - 14 Dec 2023

Cited by 2 | Viewed by 1590

Abstract

The use of the Internet of Things (IoT) technologies and principles in industrial environments is known as the Industrial Internet of Things (IIoT). The IIoT concept aims to integrate various industrial devices, sensors, and actuators for collection, storage, monitoring, and process automation. Due to the complexity of IIoT environments, there is no one-size-fits-all solution. The main challenges in developing an IIoT solution are represented by the diversity of sensors and devices, connectivity, edge/fog computing, and security. This paper proposes a distributed and customized IioT (Industrial Internet of Things) framework for the interaction of things from the industrial environment. This framework is distributed on the fog nodes of the IIoT architecture proposed, and it will have the possibility to interconnect local things (with low latency) or global things (with a latency generated by the Internet network). To demonstrate the functionality of the proposed framework, it is included in the fog nodes presented in other paper. These fog nodes allow the integration of CANOpen networks into an IioT architecture. The most important advantages of the proposed architecture are its customizability and the fact that it allows decision operations to be carried out at the edge of the network to eliminate latency due to the Internet. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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21 pages, 4741 KiB

Open AccessArticle

An IoT System Proposed for Higher Education: Approaches and Challenges in Economics, Computational Linguistics, and Engineering

by Liana Luminița Boca, Elisabeta Mihaela Ciortea, Carmen Boghean, Andreea Begov-Ungur, Florin Boghean and Vasile Teodor Dădârlat

Sensors 2023, 23(14), 6272; https://doi.org/10.3390/s23146272 - 10 Jul 2023

Cited by 3 | Viewed by 1988

Abstract

The technological revolution and the evolution of technology have significantly facilitated the applicability of the IoT in various domains, such as healthcare, transportation, agriculture, retail, education, and, especially, higher education, which encompasses countless areas. Petri nets can be a useful tool to model the behavior of an IoT system. The main objective of this paper was to propose, model, and analyze a complex IoT system for higher education. The system involves the integration of IoT devices for monitoring data. An educational cloud was used as a support tool through which tracking, and control actions were implemented both internally, between the cloud and entities, and externally, between the cloud and the IoT. The system was modeled using Petri nets, which are systems with discrete events, and for simulation, we used the Visual Object Net++ package. Using this application, information was obtained in real time, and it was possible to intervene with changes even in the design phase. The diagrams were easy to read and interpret, which is an advantage for the decision-making system. The general structure of the application was based on n entities, where each entity represented a higher education field. In this paper, we discuss at least three fields: economics, computational linguistics, and engineering. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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17 pages, 427 KiB

Open AccessArticle

Data-Driven Insights through Industrial Retrofitting: An Anonymized Dataset with Machine Learning Use Cases

by Daniele Atzeni, Reshawn Ramjattan, Roberto Figliè, Giacomo Baldi and Daniele Mazzei

Sensors 2023, 23(13), 6078; https://doi.org/10.3390/s23136078 - 1 Jul 2023

Cited by 6 | Viewed by 2135

Abstract

Small and medium-sized enterprises (SMEs) often encounter practical challenges and limitations when extracting valuable insights from the data of retrofitted or brownfield equipment. The existing literature fails to reflect the full reality and potential of data-driven analysis in current SME environments. In this paper, we provide an anonymized dataset obtained from two medium-sized companies leveraging a non-invasive and scalable data-collection procedure. The dataset comprises mainly power consumption machine data collected over a period of 7 months and 1 year from two medium-sized companies. Using this dataset, we demonstrate how machine learning (ML) techniques can enable SMEs to extract useful information even in the short term, even from a small variety of data types. We develop several ML models to address various tasks, such as power consumption forecasting, item classification, next machine state prediction, and item production count forecasting. By providing this anonymized dataset and showcasing its application through various ML use cases, our paper aims to provide practical insights for SMEs seeking to leverage ML techniques with their limited data resources. The findings contribute to a better understanding of how ML can be effectively utilized in extracting actionable insights from limited datasets, offering valuable implications for SMEs in practical settings. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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18 pages, 7800 KiB

Open AccessArticle

Progressive Classifier Mechanism for Bridge Expansion Joint Health Status Monitoring System Based on Acoustic Sensors

by Xulong Zhang, Zihao Cheng, Li Du and Yuan Du

Sensors 2023, 23(11), 5090; https://doi.org/10.3390/s23115090 - 26 May 2023

Cited by 2 | Viewed by 2174

Abstract

The application of IoT (Internet of Things) technology to the health monitoring of expansion joints is of great importance in enhancing the efficiency of bridge expansion joint maintenance. In this study, a low-power, high-efficiency, end-to-cloud coordinated monitoring system analyzes acoustic signals to identify faults in bridge expansion joints. To address the issue of scarce authentic data related to bridge expansion joint failures, an expansion joint damage simulation data collection platform is established for well-annotated datasets. Based on this, a progressive two-level classifier mechanism is proposed, combining template matching based on AMPD (Automatic Peak Detection) and deep learning algorithms based on VMD (Variational Mode Decomposition), denoising, and utilizing edge and cloud computing power efficiently. The simulation-based datasets were used to test the two-level algorithm, with the first-level edge-end template matching algorithm achieving fault detection rates of 93.3% and the second-level cloud-based deep learning algorithm achieving classification accuracy of 98.4%. The proposed system in this paper has demonstrated efficient performance in monitoring the health of expansion joints, according to the aforementioned results. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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18 pages, 3111 KiB

Open AccessArticle

User QoS-Based Optimized Handover Algorithm for Wireless Networks

by Hung-Chi Chu, Chia-En Wong, Wei-Min Cheng and Hong-Cheng Lai

Sensors 2023, 23(10), 4877; https://doi.org/10.3390/s23104877 - 18 May 2023

Cited by 2 | Viewed by 2751

Abstract

Due to the development of wireless network technology, various applications relying on good network quality are widely used on mobile devices. Taking the commonly used video streaming service as an example, a network with high throughput and low packet loss rate can meet the service requirements. When the moving distance of the mobile device is greater than the signal coverage of the AP, it will trigger the handover process to connect to another AP, and cause the network to disconnect and reconnect instantaneously. However, frequently triggering the handover procedure will cause a significant drop in network performance and affect the operation of application services. In order to solve this problem, this paper proposes the OHA and OHAQR. The OHA considers whether the signal quality is good or bad, and uses the corresponding HM method to solve the problem of frequent handover procedures. The OHAQR integrates the QoS requirements of the throughput and packet loss rate into the OHA with the Q-handover score, to provide high-performance handover services with QoS. Our experimental results show that the OHA and OHAQR have 13 and 15 handovers in a high-density scenario, respectively, and are better than the other two methods. The actual throughput and packet loss rate of the OHAQR are 123 Mbps and 5%, respectively, and the network performance is better than that of other methods. The proposed method shows excellent performance in ensuring the network QoS requirements and reducing the number of handover procedures. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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21 pages, 1586 KiB

Open AccessArticle

Internet of Underground Things in Agriculture 4.0: Challenges, Applications and Perspectives

by Christophe Cariou, Laure Moiroux-Arvis, François Pinet and Jean-Pierre Chanet

Sensors 2023, 23(8), 4058; https://doi.org/10.3390/s23084058 - 17 Apr 2023

Cited by 12 | Viewed by 3737

Abstract

Internet of underground things (IoUTs) and wireless underground sensor networks (WUSNs) are new technologies particularly relevant in agriculture to measure and transmit environmental data, enabling us to optimize both crop growth and water resource management. The sensor nodes can be buried anywhere, including in the passage of vehicles, without interfering with aboveground farming activities. However, to obtain fully operational systems, several scientific and technological challenges remain to be addressed. The objective of this paper is to identify these challenges and provide an overview of the latest advances in IoUTs and WUSNs. The challenges related to the development of buried sensor nodes are first presented. The recent approaches proposed in the literature to autonomously and optimally collect the data of several buried sensor nodes, ranging from the use of ground relays, mobile robots and unmanned aerial vehicles, are next described. Finally, potential agricultural applications and future research directions are identified and discussed. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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30 pages, 2040 KiB

Open AccessArticle

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

by Yassine Yazid, Antonio Guerrero-González, Imad Ez-Zazi, Ahmed El Oualkadi and Mounir Arioua

Sensors 2022, 22(15), 5662; https://doi.org/10.3390/s22155662 - 28 Jul 2022

Cited by 6 | Viewed by 2909

Abstract

Internet of Things (IoT) landscape to cover long-range applications. The LoRa-enabled IoT devices adopt an Adaptive Data Rate-based (ADR) mechanism to assign transmission parameters such as spreading factors, transmission energy, and coding rates. Nevertheless, the energy assessment of these combinations should be considered carefully to select an accurate combination. Accordingly, the computational and transmission energy consumption trade-off should be assessed to guarantee the effectiveness of the physical parameter tuning. This paper provides comprehensive details of LoRa transceiver functioning mechanisms and provides a mathematical model for energy consumption estimation of the end devices EDs. Indeed, in order to select the optimal transmission parameters. We have modeled the LoRa energy optimization and transmission parameter selection problem as a Markov Decision Process (MDP). The dynamic system surveys the environment stats (the residual energy and channel state) and searches for the optimal actions to minimize the long-term average cost at each time slot. The proposed method has been evaluated under different scenarios and then compared to LoRaWAN default ADR in terms of energy efficiency and reliability. The numerical results have shown that our method outperforms the LoRa standard ADR mechanism since it permits the EDs to gain more energy. Besides, it enables the EDs to stand more, consequently performing more transmissions. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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28 pages, 5688 KiB

Open AccessArticle

IoT-Based Monitoring System Applied to Aeroponics Greenhouse

by Hugo A. Méndez-Guzmán, José A. Padilla-Medina, Coral Martínez-Nolasco, Juan J. Martinez-Nolasco, Alejandro I. Barranco-Gutiérrez, Luis M. Contreras-Medina and Miguel Leon-Rodriguez

Sensors 2022, 22(15), 5646; https://doi.org/10.3390/s22155646 - 28 Jul 2022

Cited by 22 | Viewed by 14002

Abstract

The inclusion of the Internet of Things (IoT) in greenhouses has become a fundamental tool for improving cultivation systems, offering information relevant to the greenhouse manager for decision making in search of optimum yield. This article presents a monitoring system applied to an aeroponic greenhouse based on an IoT architecture that provides user information on the status of the climatic variables and the appearance of the crop in addition to managing the irrigation timing and the frequency of visual inspection using an application developed for Android mobile devices called Aeroponics Monitor. The proposed IoT architecture consists of four layers: a device layer, fog layer, cloud layer and application layer. Once the information about the monitored variables is obtained by the sensors of the device layer, the fog layer processes it and transfers it to the Thingspeak and Firebase servers. In the cloud layer, Thingspeak analyzes the information from the variables monitored in the greenhouse through its IoT analytic tools to generate historical data and visualizations of their behavior, as well as an analysis of the system’s operating status. Firebase, on the other hand, is used as a database to store the results of the processing of the images taken in the fog layer for the supervision of the leaves and roots. The results of the analysis of the information of the monitored variables and of the processing of the images are presented in the developed app, with the objective of visualizing the state of the crop and to know the function of the monitoring system in the event of a possible lack of electricity or a service line failure in the fog layer and to avoid the loss of information. With the information about the temperature of the plant leaf and the relative humidity inside the greenhouse, the vapor pressure deficit (VPD) in the cloud layer is calculated; the VPD values are available on the Thingspeak server and in the developed app. Additionally, an analysis of the VPD is presented that demonstrates a water deficiency from the transplanting of the seedling to the cultivation chamber. The IoT architecture presented in this paper represents a potential tool for the study of aeroponic farming systems through IoT-assisted monitoring. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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Review

Jump to: Research

32 pages, 959 KiB

Open AccessEditor’s ChoiceReview

Smart Transportation: An Overview of Technologies and Applications

by Damilola Oladimeji, Khushi Gupta, Nuri Alperen Kose, Kubra Gundogan, Linqiang Ge and Fan Liang

Sensors 2023, 23(8), 3880; https://doi.org/10.3390/s23083880 - 11 Apr 2023

Cited by 172 | Viewed by 84949

Abstract

As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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31 pages, 3241 KiB

Open AccessEditor’s ChoiceReview

Key Challenges and Emerging Technologies in Industrial IoT Architectures: A Review

by Akseer Ali Mirani, Gustavo Velasco-Hernandez, Anshul Awasthi and Joseph Walsh

Sensors 2022, 22(15), 5836; https://doi.org/10.3390/s22155836 - 4 Aug 2022

Cited by 60 | Viewed by 13385

Abstract

The Industrial Internet of Things (IIoT) is bringing evolution with remote monitoring, intelligent analytics, and control of industrial processes. However, as the industrial world is currently in its initial stage of adopting full-stack development solutions with IIoT, there is a need to address the arising challenges. In this regard, researchers have proposed IIoT architectures based on different architectural layers and emerging technologies for the end-to-end integration of IIoT systems. In this paper, we review and compare three widely accepted IIoT reference architectures and present a state-of-the-art review of conceptual and experimental IIoT architectures from the literature. We identified scalability, interoperability, security, privacy, reliability, and low latency as the main IIoT architectural requirements and detailed how the current architectures address these challenges by using emerging technologies such as edge/fog computing, blockchain, SDN, 5G, Machine Learning, and Wireless Sensor Networks (WSN). Finally, we discuss the relation between the current challenges and emergent technologies and present some opportunities and directions for future research work. Full article

(This article belongs to the Special Issue Evolution of IoT and IIoT: Opportunities, Challenges, and Applications)

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