Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

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Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the IoT to enable the interconnection of anything, anywhere, and at any time in the manufacturing system context to improve the productivity, efficiency, safety, and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality-of-service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs and to present a unified assessment of the technology from a systems’ perspective, in this paper, we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation and process automation), and their characteristics. We then consider existing research efforts from the three key system aspects of control, networking, and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine communication, and software-defined networking. Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning in an I-IoT context.

A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective

Modern gas monitoring scenarios for medical diagnostics, environmental surveillance, industrial safety, and other applications demand new sensing capabilities. This Review provides analysis of development of new generation of gas sensors based on the multivariable response principles. Design criteria of these individual sensors involve a sensing material with multiresponse mechanisms to different gases and a multivariable transducer with independent outputs to recognize these different gas responses. These new sensors quantify individual components in mixtures, reject interferences, and offer more stable response over sensor arrays. Such performance is attractive when selectivity advantages of classic gas chromatography, ion mobility, and mass spectrometry instruments are canceled by requirements for no consumables, low power, low cost, and unobtrusive form factors for Internet of Things, Industrial Internet, and other applications. This Review is concluded with a perspective for future needs in fundament...

Multivariable Sensors for Ubiquitous Monitoring of Gases in the Era of Internet of Things and Industrial Internet

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. Hence, the security of IoT should start with foremost securing WSNs ahead of the other components. However, owing to the absence of a physical line-of-defense, i.e., there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: “Passive Attacks” and “Active Attacks”. Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology.

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Security of the Internet of Things: Vulnerabilities, Attacks, and Countermeasures

One of the goals of smart environments is to improve the quality of human life in terms of comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a technology for building smart environments. Security and privacy are considered key issues in any real-world smart environment based on the IoT model. The security vulnerabilities in IoT-based systems create security threats that affect smart environment applications. Thus, there is a crucial need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. This article presents a comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms. This article also provides deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT architecture. This work demonstrates that despite previous studies regarding the design and implementation of IDSs for the IoT paradigm, developing efficient, reliable and robust IDSs for IoT-based smart environments is still a crucial task. Key considerations for the development of such IDSs are introduced as a future outlook at the end of this survey.

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Intrusion detection systems for IoT-based smart environments: a survey

Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications.

https://www.mdpi.com/1424-8220/18/5/1532/pdf

Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT

We see a shift from todays Internet-of-Things(IoT) to include more industrial equipment and metrology systems, forming the Industrial Internet of Things (IIoT). However, this leads to many concerns related to confidentiality, integrity, availability, privacy and non-repudiation. Hence, there is a need to secure the IIoT in order to cater for a future with smart grids, smart metering, smart factories, smart cities, and smart manufacturing. It is therefore important to research IIoT technologies and to create order in this chaos, especially when it comes to securing communication, resilient wireless networks, protecting industrial data, and safely storing industrial intellectual property in cloud systems. This research therefore presents the challenges, needs, and requirements of industrial applications when it comes to securing IIoT systems.

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Challenges of Securing the Industrial Internet of Things Value Chain

Research in Internet-of-Things infrastructures has so far mainly been focused on connecting sensors and actuators to the Internet, while associating these devices to applications via web services. This has contributed to making the technology accessible in areas such as smart-grid, transport, health, etc. These early successes have hidden the lack of support for sensor-based applications to share information and limitations in support for applications to access sensors and actuators globally. We address these limitations in a novel open-source platform, MediaSense. MediaSense offers scalable, seamless, real-time access to global sensors and actuators via hetero- geneous network infrastructure. This paper presents a set of requirements for Internet-of-Things applications support, an overview of our architecture, and application prototypes created in order to verify the approach in a test bed with users connected from heterogeneous networks.

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MediaSense - an Internet of Things Platform for Scalable and Decentralized Context Sharing and Control

Although Internet-of-Things (IoT) is revolutionizing the IT sector, it is not mature yet as several technologies are still being offered to be candidates for supporting the backbone of this system IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is one of those promising candidate technologies to be adopted by IoT and Industrial IoT (IIoT) Attacks against RPL have shown to be possible, as the attackers utilize the unauthorized parent selection system of the RLP protocol In this work, we are proposing a methodology and architecture to detect intrusions against IIoT Especially, we are targeting to detect attacks against RPL by using genetic programming Our results indicate that the developed framework can successfully (with high accuracy, along with high true positive and low false positive rates) detect routing attacks in RPL-based Industrial IoT networks

A Central Intrusion Detection System for RPL-Based Industrial Internet of Things

The Internet of Things is predicted to consist of over 50 billion devices aiming to solve problems in most areas of our digital society. A large part of the data communicated is expected to consist ...

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Stefan Forsström

Papers

Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT

Challenges of Securing the Industrial Internet of Things Value Chain

MediaSense - an Internet of Things Platform for Scalable and Decentralized Context Sharing and Control

A Central Intrusion Detection System for RPL-Based Industrial Internet of Things

Low Delay Video Streaming on the Internet of Things Using Raspberry Pi