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1
Dangat, Prof M. T. "Industrial Internet of Things (IIOT)." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (March 31, 2024): 2721–26. http://dx.doi.org/10.22214/ijraset.2024.59103.
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Abstract: Industrial Internet of Things (IOT) is a part of IOT (Internet of Things) technology that has provided an opportunity to build powerful industrial system and applications by using different I0T devices like sensors, actuators, Resistance Temperature Detectors, pH analyzers, Level Transmitters, RFIDs, wireless and mobile devices. High-speed internet has given a new hike in development of IOT devices, as it makes remote access facility at ease. Various IOT applications and systems have been developed and deployed in recent years. To understand the development of IOТ technology, this study addresses IIOT concepts through a systematic review of various white papers, research papers and online database.Abstract: Industrial Internet of Things (IOT) is a part of IOT (Internet of Things) technology that has provided an opportunity to build powerful industrial system and applications by using different I0T devices like sensors, actuators, Resistance Temperature Detectors, pH analyzers, Level Transmitters, RFIDs, wireless and mobile devices. High-speed internet has given a new hike in development of IOT devices, as it makes remote access facility at ease. Various IOT applications and systems have been developed and deployed in recent years. To understand the development of IOТ technology, this study addresses IIOT concepts through a systematic review of various white papers, research papers and online database.
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Madugula, Lavanya. "Applications of IoT in Manufacturing: Issues and Challenges." Journal of Advanced Research in Embedded System 8, no. 1&2 (July 29, 2021): 3–7. http://dx.doi.org/10.24321/2395.3802.202101.
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The Internet of Things (IoT) is the global network of inter-related physical devices such as sensors, objects, computing devices, mechanical instruments, smart applications and human resources that are becoming an essential part of the internet. These devices are the sources of data which provide abundant information in manufacturing processes. In an industrial environment, the Industrial Internet of Things (IIoT) plays a pivotal role in manufacturing. IIoT is the transformation of manufacturing process by making the industries more efficient, productive, and smarter. In order to survive, withstand in the market place and gain competitive advantage, the manufacturers are initiating to leverage IIoT technologies and data analytics. With globalization, global competitive pressures are challenging industries and manufacturing companies to manage the gaps in the workforce skills, drive out inefficiencies from the existing systems and enhance their business opportunities. The world is plunging into an era of data inter-connectivity and companies are able to enhance their production after adapting new technologies. In this context, this paper provides an understanding of the concept of IIoT and smart manufacturing. Further, the paper discusses in detail the issues concerning different applications of IoT in the industrial sector; and presents the challenges encountered in an IoT-based Industrial Data Management System (IDMS), which can manage the huge industrial data, support online monitoring and control smart manufacturing.
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Farooq, Muhammad Shoaib, Muhammad Abdullah, Shamyla Riaz, Atif Alvi, Furqan Rustam, Miguel Angel López Flores, Juan Castanedo Galán, Md Abdus Samad, and Imran Ashraf. "A Survey on the Role of Industrial IoT in Manufacturing for Implementation of Smart Industry." Sensors 23, no. 21 (November 3, 2023): 8958. http://dx.doi.org/10.3390/s23218958.
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The Internet of Things (IoT) is an innovative technology that presents effective and attractive solutions to revolutionize various domains. Numerous solutions based on the IoT have been designed to automate industries, manufacturing units, and production houses to mitigate human involvement in hazardous operations. Owing to the large number of publications in the IoT paradigm, in particular those focusing on industrial IoT (IIoT), a comprehensive survey is significantly important to provide insights into recent developments. This survey presents the workings of the IoT-based smart industry and its major components and proposes the state-of-the-art network infrastructure, including structured layers of IIoT architecture, IIoT network topologies, protocols, and devices. Furthermore, the relationship between IoT-based industries and key technologies is analyzed, including big data storage, cloud computing, and data analytics. A detailed discussion of IIoT-based application domains, smartphone application solutions, and sensor- and device-based IIoT applications developed for the management of the smart industry is also presented. Consequently, IIoT-based security attacks and their relevant countermeasures are highlighted. By analyzing the essential components, their security risks, and available solutions, future research directions regarding the implementation of IIoT are outlined. Finally, a comprehensive discussion of open research challenges and issues related to the smart industry is also presented.
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Caesarendra, Wahyu, Bobby Pappachan, Tomi Wijaya, Daryl Lee, Tegoeh Tjahjowidodo, David Then, and Omey Manyar. "An AWS Machine Learning-Based Indirect Monitoring Method for Deburring in Aerospace Industries Towards Industry 4.0." Applied Sciences 8, no. 11 (November 5, 2018): 2165. http://dx.doi.org/10.3390/app8112165.
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The number of studies on the Internet of Things (IoT) has grown significantly in the past decade and has been applied in various fields. The IoT term sounds like it is specifically for computer science but it has actually been widely applied in the engineering field, especially in industrial applications, e.g., manufacturing processes. The number of published papers in the IoT has also increased significantly, addressing various applications. A particular application of the IoT in these industries has brought in a new term, the so-called Industrial IoT (IIoT). This paper concisely reviews the IoT from the perspective of industrial applications, in particular, the major pillars in order to build an IoT application, i.e., architectural and cloud computing. This enabled readers to understand the concept of the IIoT and to identify the starting point. A case study of the Amazon Web Services Machine Learning (AML) platform for the chamfer length prediction of deburring processes is presented. An experimental setup of the deburring process and steps that must be taken to apply AML practically are also presented.
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Gaber, Tarek, Joseph B. Awotunde, Sakinat O. Folorunso, Sunday A. Ajagbe, and Esraa Eldesouky. "Industrial Internet of Things Intrusion Detection Method Using Machine Learning and Optimization Techniques." Wireless Communications and Mobile Computing 2023 (April 30, 2023): 1–15. http://dx.doi.org/10.1155/2023/3939895.
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The emergence of the Internet of Things (IoT) has witnessed immense growth globally with the use of various devices found in home, transportation, healthcare, and industry. The deployment and implementation of the IoT paradigm in industrial settings lead to the architectural changes of Industrial Automation and Control Systems (IACS) plus the countless connectivity of industrial systems. This resulted in what is referred to as the Industrial Internet of Things (IIoT), which removes the barrier of connecting IACS to isolated conventional ICT platforms. In recent times, the IoT has started hacking our personal lives and not only our world, thus creating a platform for impending IoT cyberattacks. The widespread use of the IoT has created a rich platform for possible IoT cyberattacks. Machine learning (ML) algorithms have been driven solutions to secure wireless communication in IIoT-based systems, and their use in solving various cybersecurity challenges. Therefore, this paper proposes a novel intrusion detection model based on the Particle Swarm Optimization (PSO) and Bat algorithm (BA) for feature selection, and the Random Forest (RF) classifier for the classification of malicious behaviors in IIoT-based network traffic. An IIoT-based cybersecurity dataset, WUSTL-IIOT-2021 Dataset, was used to evaluate the performance of the proposed model using accuracy, recall, precision, and F1-score. The results of the two feature selection were compared to identify the most promising one. The results were compared with other recent state-of-the-art ML and multiobjective algorithms, and the results showed better performance. The RF along with BA classifier had proved to be the best classifier.
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Arora, Jyoti, Pooja Kherwa, and Meena Tushir. "A comprehensive survey on the significance of industrial Internet of Things, energy management and big data analytics." Journal of Information and Optimization Sciences 45, no. 2 (2024): 247–56. http://dx.doi.org/10.47974/jios-1544.
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The adaptive worldwide network architecture made up of web-enabled, objects connected through internet generally defines the concept of Internet of Things (IoT). In today’s world, IoT is contributing towards the transformation of the traditional industries to the smart industries by integrating the concept of IoT based energy management system into the analytics-based information system of the industries. Manufacturing businesses have concluded that by providing a digital identity to their tangible resources through IoT-based solutions, they can gain higher clarity into their processes and massively improve them. To estimate and analyze the developments in this field, this paper conducts an in-depth survey on the significance of big data analytics and energy management in shaping the progress of the Industrial Internet of Things (IIoT). It briefs the components related to the building blocks of the IoT, its application in various domains, benefits and the major challenges faced for building IoT technologies. This review present cutting-edge research on how IoT technology adoption might propel the transformation of industrial companies that are energy-efficient and environmentally sustainable.
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Li, Keng, Yu Zhang, Yong Huang, Zhiwei Tian, and Ziqin Sang. "Framework and Capability of Industrial IoT Infrastructure for Smart Manufacturing." Standards 3, no. 1 (January 3, 2023): 1–18. http://dx.doi.org/10.3390/standards3010001.
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The Internet of Things (IoT) and smart manufacturing (SM) are mutually reinforcing. The establishment of IoT-based common facilities for SM is the premise of building SM system. Industrial IoT (IIoT) infrastructure for SM refers to common facilities based on IoT that support SM in industries or sectors, and plays a dominant role and faces severe challenges in the intelligence of SM. The infrastructure is independent of the products and production process in a specific factory. This paper develops conceptual and capability frameworks of IIoT infrastructure from a unified perspective of IIoT-related SM industries. These frameworks reflect relationships between IIoT and SM with in-depth relationships among basic facilities of IIoT infrastructure and lay the foundation of SM. In this paper the common characteristics and high-level requirements with respect to the different IoT layers of IIoT infrastructure are analyzed, and the capability framework and relevant capabilities of IIoT infrastructure are summarized according to the characteristics and requirements. In order to help service providers implement their systems to meet the needs of SM, the existing and newly developed IIoT infrastructure are integrated partially or in whole according to the intelligence level, so as to provide technical guidance for stakeholders to apply emerging ICTs to SM.
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Vijayakumaran, C., B. Muthusenthil, and B. Manickavasagam. "A reliable next generation cyber security architecture for industrial internet of things environment." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (February 1, 2020): 387. http://dx.doi.org/10.11591/ijece.v10i1.pp387-395.
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Architectural changes are happening in the modern industries due to the adaption and the deployment of ‘Internet of Things (IoT)’ for monitoring and controlling various devices remotely from the external world. The most predominant place where the IoT technology makes the most sense is the industrial automation processes in smart industries (Industry 4.0). In this paper, a reliable ‘Next Generation Cyber Security Architecture (NCSA)’ is presented for Industrial IoT (IIoT) environment that detects and thwarts cybersecurity threats and vulnerabilities. It helps to automate the processes of exchanging real-time critical information between devices without any human intervention. It proposes an analytical framework that can be used to protect entities and network traffics involved in the IIoT wireless communication. It incorporates an automated cyber-defense authentication mechanism that detects and prevents security attacks when a network session has been established. The defense mechanism accomplishes the required level of security protection in the network by generating an identity token which is cryptographically encrypted and verified by a virtual gateway system. The proposed NCSA improves security in the IIoT environment and reduces operational management cost.
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C. Sailaja. "Industrial Internet of Things – An Overview." December 2022 4, no. 4 (December 30, 2022): 257–71. http://dx.doi.org/10.36548/jismac.2022.4.003.
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Internet of Things (IoT) is a network of intelligent objects (smart sensors) that are connected and accessible to the Internet through devices such as routers to exchange data. Many useful applications can be developed using IoT. IoT has brought a change in such a way that everything around us can be turned into smart devices e.g., smart cars, smart homes, smart parking, smart cities etc., thereby connecting human, machine & things seamlessly. The advent of cheaper processing power, communication cost and some marketing have created the IoT of today. When the principles of IoT are applied to Industries, it is termed as Industrial IoT. Smart sensors and Industrial Internet of Things (IIoT) are modern tools which drive Industry 4.0. The use of smart sensors and IIoT have a positive impact in enhancing the quality & value of products and improve efficiency. The combination of smart sensors with its processing & networking capabilities help in transferring the process data to the centralized database for further analysis. Thus, digitalization has helped industry to reimage the business with the transformation brought about by IIoT. This paper discusses some of the applications of IIoT such as Remote Monitoring & Service, AI & ML based predictive analysis and Closed loop Digital twin using IoT sensors.
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Alshahrani, Hani, Attiya Khan, Muhammad Rizwan, Mana Saleh Al Reshan, Adel Sulaiman, and Asadullah Shaikh. "Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network." Sustainability 15, no. 11 (June 2, 2023): 9001. http://dx.doi.org/10.3390/su15119001.
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The Industrial Internet of Things (IIoT) refers to the employment of the Internet of Things in industrial management, where a substantial number of machines and devices are linked and synchronized with the help of software programs and third platforms to improve the overall productivity. The acquisition of the industrial IoT provides benefits that range from automation and optimization to eliminating manual processes and improving overall efficiencies, but security remains to be forethought. The absence of reliable security mechanisms and the magnitude of security features are significant obstacles to enhancing IIoT security. Over the last few years, alarming attacks have been witnessed utilizing the vulnerabilities of the IIoT network devices. Moreover, the attackers can also sink deep into the network by using the relationships amidst the vulnerabilities. Such network security threats cause industries and businesses to suffer financial losses, reputational damage, and theft of important information. This paper proposes an SDN-based framework using machine learning techniques for intrusion detection in an industrial IoT environment. SDN is an approach that enables the network to be centrally and intelligently controlled through software applications. In our framework, the SDN controller employs a machine-learning algorithm to monitor the behavior of industrial IoT devices and networks by analyzing traffic flow data and ultimately determining the flow rules for SDN switches. We use SVM and Decision Tree classification models to analyze our framework’s network intrusion and attack detection performance. The results indicate that the proposed framework can detect attacks in industrial IoT networks and devices with an accuracy of 99.7%.
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Yangui, Sami. "A Panorama of Cloud Platforms for IoT Applications Across Industries." Sensors 20, no. 9 (May 9, 2020): 2701. http://dx.doi.org/10.3390/s20092701.
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Internet of Things (IoT) applications can play a critical role in business and industry. Industrial IoT (IIoT) refers to the use of IoT technologies in manufacturing. Enabling IIoT applications in cloud environments requires the design of appropriate IIoT Platform as-a-Service (IIoT PaaS) to support and ease their provisioning (i.e., development, deployment and management). This paper critically reviews the IIoT PaaS architectures proposed so far in the relevant literature. It only surveys the architectures that are suitable for IIoT applications provisioning and it excludes regular IoT solutions from its scope. The evaluation is based on a set of well-defined architectural requirements. It also introduces and discusses the future challenges and the research directions. The critical review discusses the PaaS solutions that focus on the whole spectrum of IoT verticals and also the ones dealing with specific IoT verticals. Existing limitations are identified and hints are provided on how to tackle them. As critical research directions, the mechanisms that enable the secure provisioning, and IIoT PaaS interaction with virtualized IoT Infrastructure as-a-Service (IaaS) and fog computing layer are discussed.
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Lampropoulos, Georgios, Kerstin Siakas, and Theofylaktos Anastasiadis. "Internet of Things in the Context of Industry 4.0: An Overview." International Journal of Entrepreneurial Knowledge 7, no. 1 (June 1, 2019): 4–19. http://dx.doi.org/10.2478/ijek-2019-0001.
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Abstract Due to successive technological advancements, developments and innovations, the global industrial landscape has drastically transformed over the last years. The fourth industrial revolution (Industry 4.0) aims at transforming traditional industries into intelligent ones by incorporating innovative technologies. Industry 4.0 enables physical assets to be integrated into intertwined digital and physical processes thus creating smart factories and intelligent manufacturing environments. Internet of Things (IoT) is a rapidly growing technology that has drastically contributed to the Industry 4.0 realization. IoT pursues to pervade our everyday environment and its objects, linking the physical to the digital world and allowing people and “things” to be connected anytime, anywhere, with anything and anyone ideally using any network and service. IoT is regarded as a dynamic and global network of interconnected “things” uniquely addressable, based on standard and interoperable communication protocols and with self-configuring capabilities. Despite still being at an early development, adoption and implementation stage, Industry 4.0 and IoT can provide a multitude of contemporary solutions, applications and services. Hence, they can improve life quality and yield significant personal, professional and economic opportunities and benefits in the near future. This study scrutinizes IoT in the Industry 4.0 context. More specifically, it presents related studies, describes the IoT concept and explores some of the numerous IoT application domains. Moreover, it presents and analyzes the concept of Industry 4.0 and the benefits it offers as well as the relevant key technologies (e.g. industrial internet of things (IIoT), cyber-physical systems (CPSs), cloud computing, big data and advanced data analytics). Furthermore, it describes the concept of intelligent manufacturing and highlights the main IoT and Industry 4.0 challenges and open research issues. Finally, the need for innovation in the industrial domain and the impact and benefits that IoT and Industry 4.0 provide to everyday life and industries is described.
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Abosata, Nasr, Saba Al-Rubaye, Gokhan Inalhan, and Christos Emmanouilidis. "Internet of Things for System Integrity: A Comprehensive Survey on Security, Attacks and Countermeasures for Industrial Applications." Sensors 21, no. 11 (May 24, 2021): 3654. http://dx.doi.org/10.3390/s21113654.
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The growth of the Internet of Things (IoT) offers numerous opportunities for developing industrial applications such as smart grids, smart cities, smart manufacturers, etc. By utilising these opportunities, businesses engage in creating the Industrial Internet of Things (IIoT). IoT is vulnerable to hacks and, therefore, requires various techniques to achieve the level of security required. Furthermore, the wider implementation of IIoT causes an even greater security risk than its benefits. To provide a roadmap for researchers, this survey discusses the integrity of industrial IoT systems and highlights the existing security approaches for the most significant industrial applications. This paper mainly classifies the attacks and possible security solutions regarding IoT layers architecture. Consequently, each attack is connected to one or more layers of the architecture accompanied by a literature analysis on the various IoT security countermeasures. It further provides a critical analysis of the existing IoT/IIoT solutions based on different security mechanisms, including communications protocols, networking, cryptography and intrusion detection systems. Additionally, there is a discussion of the emerging tools and simulations used for testing and evaluating security mechanisms in IoT applications. Last, this survey outlines several other relevant research issues and challenges for IoT/IIoT security.
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Sreedharan, Radhika. "Dealing with applications in Industrial IoT." International Conference on Information Science and Technology Innovation (ICoSTEC) 2, no. 1 (March 5, 2023): 122–26. http://dx.doi.org/10.35842/icostec.v2i1.49.
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Industrial Internet of Things (IIoT) also known as Industry 4.0, consists of industries that utilize IoTs to facilitate logistics, manufacturing, transportation, oil and gas, energy/utilities, mining and metals, aviation, and others. Though a lot of companies have proceeded into a lot of areas utilizing IIoT, its applicability in a lot of is still not explored and remains unpredictable. Its evolution is similar to that of the Internet in the early 90s, where it initially appeared and slowly gained momentum in the 20th century to almost becoming and indispensable aspect of human life in the 21st century. Robotics and control are already a part of most of the manufacturing companies, however, when it comes to real-time applications in manufacturing, IIoT may not come to the rescue. Another aspect that separates the internet and IIoT is that the internet is based on the bet effort delivery model which is acceptable for e-commerce and man-machine interactions. However, failures in an IIoT scenario such as air-traffic monitoring, automated manufacturing can have serious consequences. Industry 4.0 is an initiative taken up by industries to use IoT in industries and many such initiatives have been taken up by different companies and countries. For example, GE has already invested $1billion to improve its asset performance and business operation by using IIoT services. Germany has started an initiative called “Industry 4.0”, a strategic initiative that brought together leaders from private and public sectors as well as from academia to create a detailed plan of action for incorporating digital technologies into German industries. Other countries such as Italy, Netherlands, and France have invested in setting up smart factories and industries. China has also started a project called “Made in China 2025” to integrate digital technologies and industrialization. A major hindrance in adopting IIoT is that the smart devices often speak different “languages” that existing industrial automation software uses, which creates a communication gap, and hence standardization is necessary. Overcoming such bottlenecks and adopting IIoT can help automate the production techniques, for instance, manufacturers could increase their productivity by a margin of 30%. The capabilities of IIoT can be explored in areas such as sensor driven computing, industrial analytics, and intelligent machine applications. The main aim of this topic is to explain various applications inf IoT in industries.
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Sadeghizadeh, Hamze, Amir Hossein Davaie Markazi, and Saeed Shavvalpour. "Investigating the Relationship between Governance and Key Processes of the Iran IoT Innovation System." Sensors 22, no. 2 (January 14, 2022): 652. http://dx.doi.org/10.3390/s22020652.
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Despite the emergence of unique opportunities for social-industrial growth and development resulting from the use of the Internet of Things (IoT), lack of a well-posed IoT governance will cause serious threats on personal privacy, public safety, industrial security, and dubious data gathering by unauthorized entities. Furthermore, adopting a systemic governance approach, particularly for the IoT innovation system, requires a precise clarification on the concept and scope of IoT governance. In this study, by employing the Structural Equation Modeling (SEM) approach, the role of governance in the Iran IoT innovation system is investigated. Contacting respondents across the seven industries, including Information and Communication Technology (ICT), Healthcare, Transportation, Oil and Gas, Energy, Agriculture, and Banking over the course of three months, the authors performed statistical analysis on 319 fulfilled questionnaires using SPPS and Smart PLS software. Findings show that all IoT-related TIS processes have been affected by IoT governance functions. The main result of this study is the proposition of particular governance functions, including policy-making, regulation, facilitation, and service provision with more notable impact on the indicators of the key processes in the IoT-based TIS.
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Kant, Daniel, Andreas Johannsen, and Reiner Creutzburg. "Analysis of IoT Security Risks based on the exposure of the MQTT Protocol." Electronic Imaging 2021, no. 3 (June 18, 2021): 96–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-096.
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Due to the tremendous growth of Internet of Things (IoT) applications - e.g. smart homes, smart grids, smart factories – and the emerging integration into industrial systems, the cyber threat landscape for IoT and IIoT applications is rapidly evolving. Security by Design principles are still widely neglected in the design of IoT devices and protocols. For consumer IoT, the privacy of the applicant can be compromised when devices are inappropriately secured. With regard to Industrial IoT, the usage of insecure IIoT protocols such as MQTT can have a severe impact on the industrial environment such as failure or impairment of production systems. We evaluate the prevalence of exposed IoT and IIoT devices related to the protocol MQTT by means of the search engine Shodan. The approach, design and results of our analysis are summarized in this paper.
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Shevtsov, Vadim, and Nikita Kasimovsky. "Threat and Vulnerability Analysis of IoT and IIoT Concepts." NBI Technologies, no. 3 (March 2021): 28–35. http://dx.doi.org/10.15688/nbit.jvolsu.2020.3.5.
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IoT and IIoT are new information technologies. They are very efficient solutions for home, industry and infrastructure. A lot of complex processes can be implemented using this systems. The popularity of the industrial Internet of things is steadily growing along with the development of the Internet of things. Both of these approaches involve the exchange of data over the Internet, use of common hardware platforms and are managed by using specialized software, and this leads to an increase in the number of common vulnerabilities and possible attacks on industrial facilities. The Frost & Sullivan report shows that industrial and IT infrastructures are becoming more transparent. First of all, this is due to the development of the Industrial 4.0 standard and the refusal to isolate industrial facilities, which entails common vulnerabilities, the use of security services based on the SaaS model for industrial facilities, as well as the use of hardware devices that a potential attacker can access quite easily. But very actual problems of IoT and IIoT are information security. Many of this systems are critical and little error can stop the entire system. This is not hard for hackers because that complex system has sensitive components usually. For example simple router can have a lot of vulnerabilities. There an attacker takes a root easily in every system. To solve the problem successfully it is recommended to use complex security actions. These are secure configurations of network devices, using safe devices and protocols, regular audit, using backups, using actual politics of information security.
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Raimundo, Ricardo Jorge, and Albérico Travassos Rosário. "Cybersecurity in the Internet of Things in Industrial Management." Applied Sciences 12, no. 3 (February 2, 2022): 1598. http://dx.doi.org/10.3390/app12031598.
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Nowadays, people live amidst the smart home domain, while there are business opportunities in industrial smart cities and healthcare. However, there are concerns about security. Security is central for IoT systems to protect sensitive data and infrastructure, whilst security issues have become increasingly expensive, in particular in Industrial Internet of Things (IIoT) domains. Nonetheless, there are some key challenges for dealing with those security issues in IoT domains: Applications operate in distributed environments such as Blockchain, varied smart objects are used, and sensors are limited, as far as machine resources are concerned. In this way, traditional security does not fit in IoT systems. The issue of cybersecurity has become paramount to the Internet of Things (IoT) and the Industrial Internet of Things (IIoT) in mitigating cybersecurity risk for organizations and end users. New cybersecurity technologies/applications present improvements for IoT security management. Nevertheless, there is a gap in the effectiveness of IoT cyber risk solutions. This review article discusses the literature trends around opportunities and threats in cybersecurity for IIoT, by reviewing 70 key articles discovered from a profound Scopus literature survey. It aims to present the current debate around the issue of IIoT rather than suggesting any particular technical solutions to solve network security problems.
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Dwivedi, Sanjeev Kumar, Priyadarshini Roy, Chinky Karda, Shalini Agrawal, and Ruhul Amin. "Blockchain-Based Internet of Things and Industrial IoT: A Comprehensive Survey." Security and Communication Networks 2021 (August 23, 2021): 1–21. http://dx.doi.org/10.1155/2021/7142048.
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Industry 4.0 connects the latest technologies such as cloud computing, Internet of things (IoT), machine learning and artificial intelligence (ML/AI), and blockchain to provide more automation in the industrial process and also bridges the gap between the physical and digital worlds through the cyber-physical system. The inherent feature of IoT devices creates the industry to smart industry (referred to as industrial IoT, i.e., IIoT) through its data-driven decision policies. However, several challenges such as decentralization, security and privacy vulnerability, single point of failure (SPOF), and trust issues exist in the IoT system. Blockchain is one of the promising technologies that can bring about opportunities for addressing the challenges of IoT systems. In this article, we have investigated the integration of IoT with blockchain technology and provided an in-depth study of the blockchain-enabled IoT and IIoT systems. The state-of-the-art research is categorized into data storage and management technique, big data and cloud computing technique (finance and data auditing), and industrial sectors (supply chain, energy, and healthcare sector). The insightful discussion based on the different categories is also presented in the paper. In particular, first, we introduce the IoT and IIoT and then discuss the need for smart contracts in IoT and IIoT systems. Next, we concentrate on the convergence of blockchain and IoT with state-of-the-art research. In addition, this article also provides the open and future research directions towards this era with the highlighted observations.
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Bynagari, Naresh Babu. "Industrial Application of Internet of Things." Asia Pacific Journal of Energy and Environment 3, no. 2 (December 31, 2016): 75–82. http://dx.doi.org/10.18034/apjee.v3i2.576.
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‘Industrial application of Internet of Things deals with the application of Internet of things to produce industrial services. It analyzed how industries can carry out multiple services with function remotely using IoT-connected devices. The several benefits and drawbacks to the application of IoT services were also investigated. The IoT is a network of connected systems and smart devices that use encoded networks like sensors, processors, and interactive hardware to receive, send and store data. The utilization of IoT for industrial functions will significantly improve industrial output, and in the future, more industries will come to apply IoT devices and systems for greater efficiency.
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Essop, Ismael, José C. Ribeiro, Maria Papaioannou, Georgios Zachos, Georgios Mantas, and Jonathan Rodriguez. "Generating Datasets for Anomaly-Based Intrusion Detection Systems in IoT and Industrial IoT Networks." Sensors 21, no. 4 (February 23, 2021): 1528. http://dx.doi.org/10.3390/s21041528.
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Over the past few years, we have witnessed the emergence of Internet of Things (IoT) and Industrial IoT networks that bring significant benefits to citizens, society, and industry. However, their heterogeneous and resource-constrained nature makes them vulnerable to a wide range of threats. Therefore, there is an urgent need for novel security mechanisms such as accurate and efficient anomaly-based intrusion detection systems (AIDSs) to be developed before these networks reach their full potential. Nevertheless, there is a lack of up-to-date, representative, and well-structured IoT/IIoT-specific datasets which are publicly available and constitute benchmark datasets for training and evaluating machine learning models used in AIDSs for IoT/IIoT networks. Contribution to filling this research gap is the main target of our recent research work and thus, we focus on the generation of new labelled IoT/IIoT-specific datasets by utilising the Cooja simulator. To the best of our knowledge, this is the first time that the Cooja simulator is used, in a systematic way, to generate comprehensive IoT/IIoT datasets. In this paper, we present the approach that we followed to generate an initial set of benign and malicious IoT/IIoT datasets. The generated IIoT-specific information was captured from the Contiki plugin “powertrace” and the Cooja tool “Radio messages”.
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Hazra, Abhishek, Mainak Adhikari, Tarachand Amgoth, and Satish Narayana Srirama. "A Comprehensive Survey on Interoperability for IIoT: Taxonomy, Standards, and Future Directions." ACM Computing Surveys 55, no. 1 (January 31, 2023): 1–35. http://dx.doi.org/10.1145/3485130.
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In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within the industry domain. Hence, the enactment of IoT in the industry magnifies effective optimization, authority, and data-driven judgment. However, this field undergoes several interoperable issues, including large numbers of heterogeneous IoT gadgets, tools, software, sensing, and processing components, joining through the Internet, despite the deficiency of communication protocols and standards. Recently, various interoperable protocols, platforms, standards, and technologies are enhanced and altered according to the specifications of the applicability in industrial applications. However, there are no recent survey papers that primarily examine various interoperability issues that Industrial IoT (IIoT) faces. In this review, we investigate the conventional and recent developments of relevant state-of-the-art IIoT technologies, frameworks, and solutions for facilitating interoperability between different IIoT components. We also discuss several interoperable IIoT standards, protocols, and models for digitizing the industrial revolution. Finally, we conclude this survey with an inherent discussion of open challenges and directions for future research.
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Te Chen, Ming. "A Secure Group Data Encryption Scheme in Intelligent Manufacturing Systems for IIoT." International Journal of Software Innovation 10, no. 1 (January 1, 2022): 1–12. http://dx.doi.org/10.4018/ijsi.312577.
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In recent years, there are many industries that imported intelligent systems to help them make the intelligent factory and get product record analysis to evaluate product rate. These intelligent systems could generate product records, store them to the on-line database, and provide product rate analysis from these records. Due to the rapid development of internet of things (IoT), the stockholder can construct its own smart factory with the smart intelligent system to develop its own industrial internet of things (IIoT) architecture. With the help of IIoT, the smart intelligence system can collect data information with IoT sensors embedded into each machine in the production line. However, there are some security issues arising between smart intelligent systems and IoT devices. In addition, the authors also discovered that there are fewer methodologies to talk about the data security during the machine transmitting its censored data to the other machines under the same network environment.
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Alotaibi, Bandar. "A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing Opportunities." Sensors 23, no. 17 (August 28, 2023): 7470. http://dx.doi.org/10.3390/s23177470.
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The Industrial Internet of Things (IIoT) paradigm is a key research area derived from the Internet of Things (IoT). The emergence of IIoT has enabled a revolution in manufacturing and production, through the employment of various embedded sensing devices connected by an IoT network, along with a collection of enabling technologies, such as artificial intelligence (AI) and edge/fog computing. One of the unrivaled characteristics of IIoT is the inter-connectivity provided to industries; however, this characteristic might open the door for cyber-criminals to launch various attacks. In fact, one of the major challenges hindering the prevalent adoption of the IIoT paradigm is IoT security. Inevitably, there has been an inevitable increase in research proposals over the last decade to overcome these security concerns. To obtain an overview of this research area, conducting a literature survey of the published research is necessary, eliciting the various security requirements and their considerations. This paper provides a literature survey of IIoT security, focused on the period from 2017 to 2023. We identify IIoT security threats and classify them into three categories, based on the IIoT layer they exploit to launch these attacks. Additionally, we characterize the security requirements that these attacks violate. Finally, we highlight how emerging technologies, such as AI and edge/fog computing, can be adopted to address security concerns and enhance IIoT security.
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Sim, Sungho, and Hanyong Choi. "A study on the service discovery support method in the IoT environments." International Journal of Electrical Engineering & Education 57, no. 1 (December 5, 2018): 85–96. http://dx.doi.org/10.1177/0020720918813824.
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The fourth Industrial Revolution is rapidly growing due to the development of ICT and the need for organic linkage in the industry. The Internet of Things (IoT), in which objects and objects from active relationships such as sensing, networking and mutual cooperation without human intervention is the core technology of the fourth Industrial Revolution, which can be linked to various industrial fields. As the IoT environment spreads, IoT devices are continuously increasing in various industries. IoT devices connected to the Internet are as different as each application environment. Many information is derived from the interaction between an IoT device and a device or between a human and an IoT device, as well as devices that provide simple data such as sensing. This paper proposes a support method to enable extended service search when users search for services using information generated in IoT environment. The existing service discovery method focuses on the method by which the user selects the service based on the simple service information disclosed by the service provider. In order to solve the problem of existing service discovery method, this study proposed a support method that enables users to search service discovery flexibly even when using existing methods in service discovery in IoT environment. The proposed method provides a user-centered service search environment construction through a search method using user IoT information which was not considered in the existing service search. This makes up for the problem of service availability and provider-oriented service discovery through the establishment of a user service discovery environment.
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Alasmary, Hisham. "RDAF-IIoT: Reliable Device-Access Framework for the Industrial Internet of Things." Mathematics 11, no. 12 (June 15, 2023): 2710. http://dx.doi.org/10.3390/math11122710.
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The Internet of Things (IoT) has experienced significant growth and is now a fundamental part of the next-generation Internet. Alongside improving daily life, IoT devices generate and collect vast amounts of data that can be leveraged by AI-enabled big data analytics for diverse applications. However, due to the machine-to-machine communication inherent in IoT, ensuring data security and privacy is crucial to mitigate various malicious cyber attacks, including man-in-the-middle, impersonation, and data poisoning attacks. Nevertheless, designing an efficient and adaptable IoT security framework poses challenges due to the limited computational and communication power of IoT devices, as well as their wide-ranging variety. To address these challenges, this paper proposes an Access Key Agreement (AKA) scheme called the “Reliable Device-Access Framework for the Industrial IoT (RDAF-IIoT)”. RDAF-IIoT verifies the user’s authenticity before granting access to real-time information from IIoT devices deployed in an industrial plant. Once authenticated at the gateway node, the user and IIoT device establish a session key for future encrypted communication. The security of the proposed RDAF-IIoT is validated using a random oracle model, while the Scyther tool is employed to assess its resilience against various security attacks. Performance evaluations demonstrate that the proposed scheme requires lower computational and communication costs compared to related security frameworks while providing enhanced security features.
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W.D. Madhuka Priyashan and Navod Neranjan Thilakarathne. "IIoT Framework for SME level Injection Molding Industry in the Context of Industry 4.0." International Journal of Engineering and Management Research 10, no. 6 (December 16, 2020): 61–68. http://dx.doi.org/10.31033/ijemr.10.6.9.
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The Internet of Things (IoT) is a hype topic for nearly a decade now. Broadly growing, millions of devices get direct access to the Internet provides plenty of applications such as smart homes or mobile health management. This trend can also be found in the industry where IoT components hardened for these environments are introduced, called Industrial IoT (IIoT) devices which can be either sensors or actors, as well as mobile equipment such as smartphones, tablets, and smart glasses. Consequently, mobile communication becomes universal in smart factories. IIoT devices provide massive data on temperature, pressure, machine states, etc. But still, most of the SME level industries in the Asian region are new to these technological advancements. They still operate their facilities ith conventional setups without absorbing the new opportunities which are presented by IoT.
In the plastic injection molding industry, process parameters perform a significant role in the quality of the output product. During the manufacturing process, these process parameters have to deal with various factors such as quality and type of materials, requirement tolerance levels of the output product, Environmental conditions like temperature and humidity, etc. Injection molding has been a challenging process for many SME level manufacturers to produce products while meeting the quality requirements at the lowest cost. Most of them are unable to reach the global market in the injection molding industry due to the non-availability of the proper methods to determine the process parameters for injection molding. During production, quality characteristics may differ due to drifting or shifting of processing conditions caused by machine wear, environmental change, or operator fatigue. By determining the optimal process parameter settings productivity and quality will increase while reducing the cost of production.
In this paper, we suggest an Industrial IoT framework that can develop for small- and medium-sized enterprises (SMEs) level industries to optimize their production facility. With the presented framework SME level industries can start to inherit IoT devices into their production floor to manage and monitor production parameters in real-time while improving the quality of the production.
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Bader, Jawhara, and Anna Lito Michala. "Searchable Encryption with Access Control in Industrial Internet of Things (IIoT)." Wireless Communications and Mobile Computing 2021 (May 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/5555362.
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The technological advancements in the Internet of Things (IoT) and related technologies lead to revolutionary advancements in many sectors. One of these sectors, is the industrial sector red that leverages IoT technologies forming the Industrial Internet of Things (IIoT). IIoT has the potential to enhance the manufacturing process by improving the quality, trace-ability, and integrity of the industrial processes. The enhancement of the manufacturing process is achieved by deploying IoT devices (sensors) across the manufacturing facilities; therefore, monitoring systems are required to collect (from multiple locations) and analyse the data, most likely in the cloud. As a result, IIoT monitoring systems should be secure, preserve the privacy, and provide real-time responses for critical decision-making. In this review, we identified a gap in the state-of-the-art of secure IIoT and propose a set of criteria for secure and privacy preserving IIoT systems to enhance efficiency and deliver better IIoT applications.
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Cabrini, Fábio Henrique, Filippo Valiante Filho, Pedro Rito, Albérico Barros Filho, Susana Sargento, Augusto Venâncio Neto, and Sergio Takeo Kofuji. "Enabling the Industrial Internet of Things to Cloud Continuum in a Real City Environment." Sensors 21, no. 22 (November 19, 2021): 7707. http://dx.doi.org/10.3390/s21227707.
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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.
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Surya, P., Asuman Suenbuel, and Arockia Selvakumar Arockia Doss. "Industrial Internet of Things - Control of Industry Simulation Through Different Protocols." Journal of Physics: Conference Series 2115, no. 1 (November 1, 2021): 012011. http://dx.doi.org/10.1088/1742-6596/2115/1/012011.
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Abstract In past few years there is a great demand for internet of things (IoT), It has become an important part of smart technologies. There have been many researches going-on in internet of things in both academics and industries. IoT using in industries is also known as Industrial Internet of Things (IIoT). Where smart sensors are used along with IoT are used. This research work is done to identify the best protocol for high-speed data transmission with no loss of data to prevent command lag between mobile controller and industry. In this research a soda filling Industry simulation with 3 different plants was controlled through a mobile application through different protocols with 4 different features of data transfer. The time of data sending and receiving from application and ESP32 controller are stored in a log. The speed of data transfer of all different protocols is compared. From the final result, ThingSpeak is an optimum protocol for this application which is 36% faster than HTTP in single data transfer and 39% faster than MQTT in continuous data transfer.
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Dangana, Muhammad, Shuja Ansari, Qammer H. Abbasi, Sajjad Hussain, and Muhammad Ali Imran. "Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights." Sensors 21, no. 16 (August 5, 2021): 5284. http://dx.doi.org/10.3390/s21165284.
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The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications.
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Varga, Pal, Jozsef Peto, Attila Franko, David Balla, David Haja, Ferenc Janky, Gabor Soos, Daniel Ficzere, Markosz Maliosz, and Laszlo Toka. "5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps." Sensors 20, no. 3 (February 4, 2020): 828. http://dx.doi.org/10.3390/s20030828.
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Industrial IoT has special communication requirements, including high reliability, low latency, flexibility, and security. These are instinctively provided by the 5G mobile technology, making it a successful candidate for supporting Industrial IoT (IIoT) scenarios. The aim of this paper is to identify current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains. The methodology of the paper follows the steps of surveying state-of-the art, comparing results to identify further challenges, and drawing conclusions as lessons learned for each research domain. These areas include IIoT applications and their requirements; mobile edge cloud; back-end performance tuning; network function virtualization; and security, blockchains for IIoT, Artificial Intelligence support for 5G, and private campus networks. Beside surveying the current challenges and solutions, the paper aims to provide meaningful comparisons for each of these areas (in relation to 5G-enabled IIoT) to draw conclusions on current research gaps.
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Devi Kotha, Harika, and V. Mnssvkr Gupta. "IoT Application, A Survey." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 891. http://dx.doi.org/10.14419/ijet.v7i2.7.11089.
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Internet of Things ( IoT ) , where physical systems are connected over network to exchange information among themselves and with their surroundings. IoT helps in developing most powerful industrial systems. It finds its various applications in house hold, agriculture, and in various industrial systems. In an effort to understand the growth of IoT , this paper reviews current research trends of IoT , key technologies, and its major applications, and identifies key challenges of IoT. This paper mainly summarizes the applications of IoT in industries
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Ijiga, Owoicho E., Reza Malekian, and Uche A. K. Chude-Okonkwo. "Enabling Emergent Configurations in the Industrial Internet of Things for Oil and Gas Explorations: A Survey." Electronics 9, no. 8 (August 14, 2020): 1306. http://dx.doi.org/10.3390/electronics9081306.
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Several heterogeneous, intelligent, and distributed devices can be connected to interact with one another over the Internet in what is termed internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for enhancing the production of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). Emergent configuration (EC) is a technology that can be adopted to enhance the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this paper, a survey of the concept of IoT is presented in addition to a review of IIoT systems. The application of ubiquitous computing-aided software define networking (SDN)-based EC architecture is propounded for enhancing the throughput of oil and gas production in the maritime ecosystems by managing the exploration process especially in emergency situations that involve anthropogenic oil and gas spillages.
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Rup, Clément, and Eddy Bajic. "Green and Sustainable Industrial Internet of Things Systems Leveraging Wake-Up Radio to Enable On-Demand IoT Communication." Sustainability 16, no. 3 (January 30, 2024): 1160. http://dx.doi.org/10.3390/su16031160.
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The industrial Internet of things (IIoT) is a major lever in Industry 4.0 development, where reducing the carbon footprint and energy consumption has become crucial for modern companies. Today’s IIoT device infrastructure wastes large amounts of energy on wireless communication, limiting device lifetime and increasing power consumption and battery requirements. Communication capabilities seriously affect the responsiveness and availability of autonomous IoT devices when collecting data and retrieving commands to/from higher-level applications. Thus, the objective of optimizing communication remains paramount; in addition to typical optimization methods, such as algorithms and protocols, a new concept is emerging, known as wake-up radio (WuR). WuR provides novel on-demand radio communication schemes that can increase device efficiency. By expanding the lifespan of IoT devices while maintaining high reactivity and communication performance, the WuR approach paves the way for a “place-and-forget” IoT device deployment methodology that combines a small carbon footprint with an extended lifetime and highly responsive functionality. WuR technology, when applied to IoT devices, facilitates green IIoT, thereby enabling the emergence of a novel on-demand IoT (OD-IoT) concept. This article presents an analysis of the state-of-the-art WuR technology within the green IoT paradigm and details the OD-IoT concept. Furthermore, this review provides an overview of WuR applications and their impact on the IIoT, including relevant industry use cases. Finally, we describe our experimental performance evaluation of a WuR-enabled device that is commercially available off the shelf. Specifically, we focused on the communication range and energy consumption, successfully demonstrating the applicability of WuR and the strong potential that it has and the benefits that it offers for sustainable IIoT systems.
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Ahmad, Usman, Junaid Chaudhary, Mudassar Ahmad, and Amjad Ali Naz. "Survey on Internet of Things (IoT) for Different Industry Environments." Annals of Emerging Technologies in Computing 3, no. 3 (July 1, 2019): 28–43. http://dx.doi.org/10.33166/aetic.2019.03.004.
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Internet of Things (IoT) provides an opportunity to build powerful applications and computing systems by using wireless communication and radio frequency identification (RFID), mobile, wired and wireless sensor device. In recent years several IoT applications have been developed for industrial use. To comprehend the IoT development, this survey paper provides a precise review of current research on IoT technologies. This study provides IoT applications regarding industries and categorizes the research challenges, issues, and developments. This survey contributes in providing the current state-of-the-art information regarding industrial IoT.
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Bhardwaj, Akashdeep, Keshav Kaushik, Salil Bharany, Ateeq Ur Rehman, Yu-Chen Hu, Elsayed Tag Eldin, and Nivin A. Ghamry. "IIoT: Traffic Data Flow Analysis and Modeling Experiment for Smart IoT Devices." Sustainability 14, no. 21 (November 7, 2022): 14645. http://dx.doi.org/10.3390/su142114645.
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The Internet of Things (IoT) has redefined several aspects of our daily lives, including automation and control of the living environment, innovative healthcare services, and much more. Digital IoT devices and sensors, when integrated with home appliances, industrial systems, and online services in the physical world, have brought intense, disruptive changes in our lives. The industry and home users have widely embraced these ‘things’ on the Internet or IoT. However, the innate, intrinsic repercussions regarding security and data privacy are not evaluated. Security applies to Industrial IoT (IIoT) is in its infancy stage. Techniques from security and privacy research promise to address broad security goals, but attacks continue to emerge in industrial devices. This research explores the vulnerabilities of IIoT ecosystems not just as individual nodes but as the integrated infrastructure of digital and physical systems interacting with the domains. The authors propose a unique threat model framework to analyze the attacks on IIoT application environments. The authors identified sensitive data flows inside the IIoT devices to determine privacy risks at the application level and explored the device exchanges at the physical level. Both these risks lead to insecure ecosystems. The authors also performed a security analysis of physical domains to digital domains.
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Wójcicki, Krzysztof, Marta Biegańska, Beata Paliwoda, and Justyna Górna. "Internet of Things in Industry: Research Profiling, Application, Challenges and Opportunities—A Review." Energies 15, no. 5 (February 28, 2022): 1806. http://dx.doi.org/10.3390/en15051806.
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The fourth industrial revolution taking place in the industrial sector is related to the increasing digitization and linkage of goods, products, value chains and business models. Industry 4.0 is based on the global connection of people, things and machines. By connecting devices and sensors to the internet, we are entering a new era of data analysis, connectivity and automation. This gives great opportunities for innovation and progress, previously unattainable in such a dimension. The term Internet of Things (IoT) has spread along with the vision of a world instrumented with intelligent inputs and outputs able to communicate with each other through internet data and technologies. IoT is being implemented in various areas of the modern economy, for example, healthcare, quality control, logistics, energy, agriculture and production. The Industrial Internet of Things (IIoT) blazes the trail to a better understanding of the manufacturing process, thus enabling efficient and sustainable production. The paper explains the concepts of IoT, IIoT and Industry 4.0. It highlights the accompanying opportunities, threats and challenges related to their implementation. Additionally, it presents an outline of computing architecture in IoT and related energy consumption issues. Moreover, it provides examples of application and IIoT research profiling.
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Koulamas, Christos, and Mihai T. Lazarescu. "Real-Time Sensor Networks and Systems for the Industrial IoT: What Next?" Sensors 20, no. 18 (September 4, 2020): 5023. http://dx.doi.org/10.3390/s20185023.
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The Industrial Internet of Things (Industrial IoT—IIoT) is the emerging core backbone construct for the various cyber-physical systems constituting one of the principal dimensions of the 4th Industrial Revolution [...]
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Cao, Keyan, and Chuang Zheng. "TBRm: A Time Representation Method for Industrial Knowledge Graph." Applied Sciences 12, no. 22 (November 8, 2022): 11316. http://dx.doi.org/10.3390/app122211316.
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With the development of the artificial intelligence industry, Knowledge Graph (KG), as a concise and intuitive data presentation form, has received extensive attention and research from both academia and industry in recent years. At the same time, developments in the Internet of Things (IoT) have empowered modern industries to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). Using knowledge graphs (KG) to process data from the Industrial Internet of Things (IIoT) is a research field worthy of attention, but most of the researched knowledge graph technologies are mainly concentrated in the field of static knowledge graphs, which are composed of triples. In fact, many graphs also contain some dynamic information, such as time changes at points and time changes at edges; such knowledge graphs are called Temporal Knowledge Graphs (TKGs). We consider the temporal knowledge graph based on the projection and change of space. In order to combine the temporal information, we propose a new representation of the temporal knowledge graph, namely TBRm, which increases the temporal dimension of the translational distance model and utilizes relational predicates in time add representation in time dimension. We evaluate the proposed method on knowledge graph completion tasks using four benchmark datasets. Experiments demonstrate the effectiveness of TBRm representation in the temporal dimension. At the same time, it is also practiced on a network security data set of the Industrial Internet of Things. The practical results prove that the TBRm method can achieve good performance in terms of the degree of harm to IIoT network security.
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Guérineau, Benjamin-Julia, Kousay Samir, Marvin Richrath, Kristin Paetzold, and Joaquin Montero. "Aspects of Body Metrics Data Management in the Long Term for the European Fitness Industry." Proceedings of the Design Society: International Conference on Engineering Design 1, no. 1 (July 2019): 2051–60. http://dx.doi.org/10.1017/dsi.2019.211.
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AbstractThe dawn of the fourth industrial revolution, mostly known through the German initiative “Industrie 4.0”, builds on a set of technologies emerging from software and information and communication technologies (ICT); paired with the growth of the Internet-of-Things (IoT), the so-called “smart products” are expanding on the market. These smart products integrate data collection and processing capacities. Additionally, the collected data have their own lifecycle, and can be classified as sensitive data. In that sense, companies developing hardware products may need support to step in “smart products” development. Digital transformation strategy is a possible overall support for companies. However, regarding smart product development and IoT data management, no studies to date have addressed formalized guidelines to support companies. This article proposes a set of guidelines focusing on IoT data management to support hardware companies in their transformation towards smart products. The proposed guidelines are exemplified on a fitness industry case which is using wearable devices collecting body metrics, considered as sensitive data.
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Ungurean, Ioan, and Nicoleta Cristina Gaitan. "A Software Architecture for the Industrial Internet of Things—A Conceptual Model." Sensors 20, no. 19 (September 30, 2020): 5603. http://dx.doi.org/10.3390/s20195603.
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The Internet of Things (IoT) is an emerging concept that has revolutionized the use of new technologies in everyday life. The economic impact of IoT becoming very important, and it began to be used in the industrial environment under the name of the Industrial Internet of Things (IIoT) concept, which is a sub-domain of IoT. The IIoT changes the way industrial processes are controlled and monitored, increasing operating efficiency. This article proposes a software architecture for IIoT that has a low degree of abstraction compared to the reference architectures presented in the literature. The architecture is organized on four-layer and it integrates the latest concepts related to fog and edge computing. These concepts are activated through the use of fog/edge/gateway nodes, where the processing of data acquired from things is performed and it is the place where things interact with each other in the virtual environment. The main contributions of this paper are the proposal and description of a complete IIoT software architecture, the use of a unified address space, and the use of the computing platform based on SoC (System on Chip) with specialized co-processors in order to be able to execute in real-time certain time-critical operations specific to the industrial environment.
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Islam, Mahbubul, Hossain Jamil, Samiul Pranto, Rupak Das, Al Amin, and Arshia Khan. "Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols." Sensors 24, no. 8 (April 14, 2024): 2509. http://dx.doi.org/10.3390/s24082509.
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The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.
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Todoli-Ferrandis, David, Javier Silvestre-Blanes, Víctor Sempere-Payá, and Salvador Santonja-Climent. "Polling Mechanisms for Industrial IoT Applications in Long-Range Wide-Area Networks." Future Internet 16, no. 4 (April 12, 2024): 130. http://dx.doi.org/10.3390/fi16040130.
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LoRaWAN is a low-power wide-area network (LPWAN) technology that is well suited for industrial IoT (IIoT) applications. One of the challenges of using LoRaWAN for IIoT is the need to collect data from a large number of devices. Polling is a common way to collect data from devices, but it can be inefficient for LoRaWANs, which are designed for low data rates and long battery life. LoRaWAN devices operating in two specific modes can receive messages from a gateway even when they are not sending data themselves. This allows the gateway to send commands to devices at any time, without having to wait for them to check for messages. This paper proposes various polling mechanisms for industrial IoT applications in LoRaWANs and presents specific considerations for designing efficient polling mechanisms in the context of industrial IoT applications leveraging LoRaWAN technology.
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Bhuvaneswari, K. "IoT Based Industrial Information Gathering." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (August 31, 2018): 856–62. http://dx.doi.org/10.31142/ijtsrd15935.
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Deshpande, Sujit N., and Rashmi M. Jogdand. "A Survey on Internet of Things (IoT), Industrial IoT (IIoT) and Industry 4.0." International Journal of Computer Applications 175, no. 27 (October 15, 2020): 20–27. http://dx.doi.org/10.5120/ijca2020920790.
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Huang, Hongyang, Mohammed Dauwed, Morched Derbali, Imran Khan, Sun Li, Kai Chen, and Sangsoon Lim. "An Optimized Approach for Industrial IoT Based on Edge Computing." Wireless Communications and Mobile Computing 2022 (July 9, 2022): 1–15. http://dx.doi.org/10.1155/2022/3918207.
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial time by using the Benders decomposition technique and cutting plane approximation. To ensure the nonincreasing character of the Benders upper limit, a local branching method was also added to improve the convergence. Simulation results indicated that the proposed method is superior to the existing method and has better overall performance.
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Peixoto, João Alvarez, André Borin Soares, and Vitor Macedo Ochôa. "Internet das Coisas Industrial: um ensaio de protocolos IoT para manufatura industrial." Revista Eletrônica Científica da UERGS 8, no. 3 (December 23, 2022): 178–87. http://dx.doi.org/10.21674/2448-0479.83.178-187.
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Em meio às mudanças no mercado de bens e consumo, provocadas pela transformação digital, exige-se que as máquinas de manufaturas sejam mais interativas entre si e com os painéis de monitoramento em nuvem. As conexões via internet das coisas (IoT) promovem este grau de interação e mobilidade desejados. Contudo, o ambiente industrial reivindica melhor confiabilidade e segurança, visto que a Internet das Coisas Industrial (IIoT) apresenta-se com protocolos e plataformas para este fim. Portanto, conhecer as características de protocolos e plataformas, ante a manufatura, adquire importância. O objetivo deste estudo é caracterizar as funcionalidades dos protocolos MQTT, HTTP e CoAP como uma aplicação de manufatura industrial, com painel de monitoramento nas plataformas Adafruit.IO, Tago.IO e Thinger.IO. É proposto um método para a realização de estudos semelhantes, em sistemas de manufatura interativa, com uso de protocolos e plataformas IIoT. Como forma de conexão da máquina com a internet, é utilizado o módulo ESP8266 NodeMCU. Na aplicação, as plataformas IIoT obtiveram resultados muito semelhantes, podendo ser a elas atribuídas o mesmo grau de importância para o estudo. Os protocolos diferenciaram-se, sendo o protocolo MQTT o que melhor respondeu às funcionalidades do sistema de manufatura proposto, ao oferecer sua comunicação assíncrona, sem necessidade de que os equipamentos estejam constantemente interagindo. Já o protocolo HTTP apresentou melhores recursos em APIs, mas sua conexão síncrona demanda uma boa rede de dados em internet. Por fim, o protocolo CoAP apresentou documentação insuficiente para acesso às plataformas e bibliotecas para uso em módulos microcontroladores.
Palavras-chave: Protocolos; IIoT; plataformas; redes; indústria 4.0; programação.
Abstract
Industrial Internet of Things: a trial of IoT protocols for industrial manufacturing
Changes in the goods and consumption market, caused by digital transformation, require manufacturing machines to be more interactive, with each other and with cloud monitoring panels. Connections via the Internet of Things (IoT) promote this desired degree of interaction and mobility, but the industrial environment demands increased reliability and security. The Industrial Internet of Things (IIoT) presents itself with protocols and platforms for this purpose. Knowing the characteristics of protocols and platforms, facing the desired manufacturing, becomes important. The objective of this study is to characterize the functionalities of the MQTT, HTTP and CoAP protocols in an industrial manufacturing application, with a monitoring panel on the Adafruit.IO, Tago.IO and Thinger.IO platforms. A method is proposed for carrying out similar studies in interactive manufacturing systems, using IIoT protocols and platforms. As a way of connecting the machine to the internet, the ESP8266 NodeMCU module is used. In the developed application, the IIoT platforms obtained very similar results, and they can be attributed the same degree of importance for the study. In the evaluation of the protocols, the MQTT protocol was the one that best met the functionalities of the proposed manufacturing system, providing its asynchronous communication, which does not requires the equipment to be constantly interacting. The HTTP protocol has better features in APIs, but its synchronous connection demands a good data network on the internet. The CoAP protocol presented insufficient documentation available for access to platforms and libraries, for use in microcontroller modules.
Keywords: Protocols; IIoT; platforms; networks; industry 4.0; programming.
Resumen
Internet Industrial de las Cosas: un ensayo de protocolos IoT para la fabricación industrial
En medio de los cambios en el mercado de bienes y de consumo provocados por la transformación digital, se requiere que las máquinas de fabricación sean más interactivas, tanto entre sí como con los paneles de control en la nube. Las conexiones dela Internet de las Cosas (IoT) promueven este grado deseado de interacción y movilidad, pero el entorno industrial exige una mayor fiabilidad y seguridad. La Internet Industrial de las Cosas (IIoT) se presenta con protocolos y plataformas para este fin. Conocer las características de los protocolos y las plataformas relacionados a la fabricación cobra importancia. El objetivo de este estudio es caracterizar las funcionalidades de los protocolos MQTT, HTTP y CoAP en una aplicación de fabricación industrial, con panel de control en las plataformas Adafruit.IO, Tago.IO y Thinger.IO. Se propone un método para realizar estudios similares, en sistemas de fabricación interactivos, utilizando protocolos y plataformas IIoT. Como forma de conectar la máquina a internet, se utiliza el módulo ESP8266 NodeMCU. En la aplicación, las plataformas IIoT obtuvieron resultados muy similares, pudiendo asignarles el mismo grado de importancia para el estudio. Los protocolos, en cambio, se mostraron diferentes, siendo el MQTT el que mejor respondió a las funcionalidades del sistema de fabricación propuesto, ofreciendo su comunicación asíncrona, no requiriendo que los equipos estén constantemente interactuando. El protocolo HTTP presentaba mejores recursos en las API, pero su conexión sincrónica exige una buena red de datos de internet. Por último, el protocolo CoAP presentó una documentación insuficiente para el acceso a las plataformas y bibliotecas, para su uso en módulos de microcontroladores.
Palabras clave: Protocolos; IIoT; plataformas; redes; industria 4.0; programa.
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Wong, Kok-Seng, and Myung Ho Kim. "Privacy Protection for Data-Driven Smart Manufacturing Systems." International Journal of Web Services Research 14, no. 3 (July 2017): 17–32. http://dx.doi.org/10.4018/ijwsr.2017070102.
Full textAbstract:
The Industrial Internet of Things (IIoT) is a new industrial ecosystem that combines intelligent and autonomous machines, advanced predictive analytics, and machine-human collaboration to improve productivity, efficiency and reliability. The integration of industry and IoT creates various attack surfaces and new opportunities for data breaches. In the IIoT context, it will often be the case that data is considered sensitive. This is because data will encapsulate various aspects of industrial operation, including highly sensitive information about products, business strategies, and companies. The transition to more open network architectures and data sharing of IoT poses challenges in manufacturing and industrial markets. The loss of sensitive information can lead to significant business loss and cause reputational damage. In this paper, the authors discuss emerging issues that are related to IIoT data sharing, investigate possible technological solutions to hide sensitive information and discuss some privacy management techniques in smart manufacturing systems.
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Ma, Jinnan, Xuekui Shangguan, and Ying Zhang. "IoT Security Review: A Case Study of IIoT, IoV, and Smart Home." Wireless Communications and Mobile Computing 2022 (August 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6360553.
Full textAbstract:
The Internet of Things (IoT) acts as a tremendous network that is constructed by fusing diverse sensors. IoT can achieve the interconnection of individuals, things, and machines at any place and time and improve the function performance of network applications. However, the security of IoT has always been a major problem that may limit the application perspective of IoT technologies. Nowadays, industrial IOT (IIoT), Internet of vehicles (IoV), and smart home have become the three primary emerging perspectives of the current IoT studies, and it is necessary to systematically highlight the security analysis of these three types of scenarios. Hence, in this paper, guided by the three major IoT application scenarios, i.e., IIoT, IoV, and smart home, we sum up the development status of IoT security technologies, analyzed corresponding technical difficulties, and discussed several future outlook of challenges and development trends for the IoT technology.