51 research outputs found

    Interoperability middleware for IIoT gateways based on international standard ontologies and standardized digital representation

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    Recent advances in the areas of microelectronics, information technology, and communication protocols have made the development of smaller devices with greater processing capacity and lower energy consumption. This context contributed to the growing number of physical devices in industrial environments which are interconnected and communicate via the internet, enabling concepts such as Industry 4.0 and the Industrial Internet of Things (IIoT). These nodes have different sensors and actuators that monitor and control environment data. Several companies develop these devices, including diverse communication protocols, data structures, and IoT platforms, which leads to interoperability issues. In IoT scenarios, interoperability is the ability of two systems to communicate and share services. Therefore, communication problems can make it unfeasible to use heterogeneous devices, increasing the project’s financial cost and development time. In an industry, interoperability is related to different aspects, such as physical communication, divergent device communication protocols, and syntactical problems, referring to the distinct data structure. Developing a new standard for solving these matters may bring interoperability-related drawbacks rather than effectively solving these issues. Therefore, to mitigate interoperability problems in industrial applications, this work proposes the development of an interoperability middleware for Edge-enabled IIoT gateways based on international standards. The middleware is responsible for translating communication protocols, updating data from simulations or physical nodes to the assets’ digital representations, and storing data locally or remotely. The middleware adopts the IEEE industrial standard ontologies combined with assets’ standardized digital models. As a case study, a simulation replicates the production of a nutrient solution for agriculture, controlled by IIoT nodes. The use case consists of three devices, each equipped with at least five sensors or actuators, communicating in different communication protocols and exchanging data using diverse structures. The performance of the proposed middleware and its proposed translations algorithms were evaluated, obtaining satisfactory results for mitigating interoperable in industrial applications.Devido a recentes avanços nas áreas de microeletrônica, tecnologia da informação, e protocolos de comunicação tornaram possível o desenvolvimento de dispositivos cada vez menores com maior capacidade de processamento e menor consumo energético. Esse contexto contribuiu para o crescente nú- mero desses dispositivos na industria que estão interligados via internet, viabilizando conceitos como Indústria 4.0 e Internet das Coisas Industrial (IIoT). Esses nós possuem diferentes sensores e atuadores que monitoram e controlam os dados do ambiente. Esses equipamentos são desenvolvidos por diferentes empresas, incluindo protocolos de comunicação, estruturas de dados e plataformas de IoT distintos, acarretando em problemas de interoperabilidade. Em cenários de IoT, interoperabilidade, é a capacidade de sistemas se comunicarem e compartilharem serviços. Portanto, esses problemas podem inviabilizar o uso de dispositivos heterogêneos, aumentando o custo financeiro do projeto e seu tempo de desenvolvimento. Na indústria, interoperabilidade se divide em diferentes aspectos, como comunicação e problemas sintáticos, referentes à estrutura de dados distinta. O desenvolvimento de um padrão industrial pode trazer mais desvantagens relacionadas à interoperabilidade, em vez de resolver esses problemas. Portanto, para mitigar problemas relacionados a intoperabilidade industrial, este trabalho propõe o desenvolvimento de um middleware de interoperável para gateways IIoT baseado em padrões internacionais e ontologias. O middleware é responsável por traduzir diferentes protocolos de comunicação, atualizar os dados dos ativos industriais por meio de suas representações digitais, esses armazenados localmente ou remotamente. O middleware adota os padrões ontológicos industriais da IEEE combinadas com modelos digitais padronizados de ativos industriais. Como estudo de caso, são realizadas simulações para a produção de uma solução nutritiva para agricultura, controlada por nós IIoT. O processo utiliza três dispositivos, cada um equipado com pelo menos cinco sensores ou atuadores, por meio de diferentes protocolos de comunicação e estruturas de dados. O desempenho do middleware proposto e seus algoritmos de tradução foram avaliados e apresentados no final do trabalho, os quais resultados foram satisfatórios para mitigar a interoperabilidade em aplicações industriais

    Real-Time Performance of Industrial IoT Communication Technologies: A Review

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    With the growing need for automation and the ongoing merge of OT and IT, industrial networks have to transport a high amount of heterogeneous data with mixed criticality such as control traffic, sensor data, and configuration messages. Current advances in IT technologies furthermore enable a new set of automation scenarios under the roof of Industry 4.0 and IIoT where industrial networks now have to meet new requirements in flexibility and reliability. The necessary real-time guarantees will place significant demands on the networks. In this paper, we identify IIoT use cases and infer real-time requirements along several axes before bridging the gap between real-time network technologies and the identified scenarios. We review real-time networking technologies and present peer-reviewed works from the past 5 years for industrial environments. We investigate how these can be applied to controllers, systems, and embedded devices. Finally, we discuss open challenges for real-time communication technologies to enable the identified scenarios. The review shows academic interest in the field of real-time communication technologies but also highlights a lack of a fixed set of standards important for trust in safety and reliability, especially where wireless technologies are concerned.Comment: IEEE Internet of Things Journal 2023 | Journal article DOI: 10.1109/JIOT.2023.333250

    Smart industrial IoT monitoring and control system based on UAV and cloud computing applied to a concrete plant

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    Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besides quantifying production and helping to make decisions. UAVs are a highly consistent technological platform for efficient and cost-effective data collection and event monitoring. The industrial Internet of things (IIoT) sends data from systems that monitor and control the physical world to data processing systems that cloud computing has shown to be important tools for meeting processing requirements. In fog computing, the IoT gateway links different objects to the internet. It can operate as a joint interface for different networks and support different communication protocols. A great deal of effort has been put into developing UAVs and multi-UAV systems. This paper introduces a smart IIoT monitoring and control system based on an unmanned aerial vehicle that uses cloud computing services and exploits fog computing as the bridge between IIoT layers. Its novelty lies in the fact that the UAV is automatically integrated into an industrial control system through an IoT gateway platform, while UAV photos are systematically and instantly computed and analyzed in the cloud. Visual supervision of the plant by drones and cloud services is integrated in real-time into the control loop of the industrial control system. As a proof of concept, the platform was used in a case study in an industrial concrete plant. The results obtained clearly illustrate the feasibility of the proposed platform in providing a reliable and efficient system for UAV remote control to improve product quality and reduce waste. For this, we studied the communication latency between the different IIoT layers in different IoT gateways.The authors would like to thank the Seneca Foundation as also FRUMECAR S.L., for their support and the opportunity to implement and test the proposed approach on their facilities. This work was partially supported by FRUMECAR S.L. and Seneca Foundation's "Murcia Regional Scientific Excellence Research Program" (Murcia Science and Technology Agency-19895/GERM/15)

    Common Educational Teleoperation Platform for Robotics Utilizing Digital Twins

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    The erratic modern world introduces challenges to all sectors of societies and potentially introduces additional inequality. One possibility to decrease the educational inequality is to provide remote access to facilities that enable learning and training. A similar approach of remote resource usage can be utilized in resource-poor situations where the required equipment is available at other premises. The concept of Industry 5.0 (i5.0) focuses on a human-centric approach, enabling technologies to concentrate on human–machine interaction and emphasizing the importance of societal values. This paper introduces a novel robotics teleoperation platform supported by the i5.0. The platform reduces inequality and allows usage and learning of robotics remotely independently of time and location. The platform is based on digital twins with bi-directional data transmission between the physical and digital counterparts. The proposed system allows teleoperation, remote programming, and near real-time monitoring of controlled robots, robot time scheduling, and social interaction between users. The system design and implementation are described in detail, followed by experimental results

    Specification and Prototyping for Design of a Control System for Proton Computer Tomography.

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    Proton Computer Tomography (pCT) is a new imaging modality. It based on proton with matter interaction. Treatment with protons is used already against cancer, as it offers the possibility to give a high dose to the tumour, while at the same time deposit a very low dose to the surrounding tissue. Imaging with protons improves the accuracy of the dose planning. However, there are no commercial pCT scanners available in the market today. At the Department of Physics and Technology at the University of Bergen, a new generation of a Digital Tracking Calorimeter (DTC) is designed. It is a significant part of the pCT system. It is a highly complex device designed with 41 layers of ALPIDEs, a Monotholitic Active Pixel Sensor. It is more than 4000 ALPIDEs in the design, and they will be read out and controlled by 41 custom readout units. A control system is required, both to configure the system and to monitor vital health parameters such as temperatures, current and voltages during operation. During this thesis, prototyping has been done to find the best solution. At the time of writing, the DTC is still under development, so the work covers tests of communication protocols and prototyping of a monitoring system with randomly generated data. Various options of communication protocols for the pCT control system has been tested in this thesis.The work of this thesis has shown that the best option for the pCT control system will be the use of OPC UA communication protocol as it is a standard industrial protocol of communication. An OPC UA information model for the pCT has been developed. The XML design file has been imported to a commercial SDK.Master's Thesis in PhysicsPHYS399MAMN-PHY

    Developing web-based digital twin of assembly lines for industrial cyber-physical systems

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    Modern manufacturing relies heavily on digital technologies, and the recent changes in the manufacturing environment are the reflection of the advancements in information and communication technologies. Web-based Digital Twin (WDT) will constitute the future of manufacturing giving a greater potential of process/product data interaction, where Digital Twin functions on a web browser and connects to its Physical Twin to exchange data. To this end, the research work on WDT is still in the first stages. Therefore, the current paper presents a framework for developing WDT taking into account the possibility of utilising WDT for education, research and industrial applications. A case study adopted from a mini-scale assembly line is used to illustrate the proposed concept

    Development and Evaluation of a Publish/Subscribe IoT Data Sharing Model with LoRaWAN

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    Publish/subscribe architectures are becoming very common for many IoT environments such as power grid, manufacturing and factory automation. In these architectures, many different communication standards and middleware can be supported to ensure interoperability. One of the widely used publish/subscribe protocol is MQTT where a broker acts among publishers and subscribers to relay data on certain topics. While MQTT can be easily setup on cloud environments to perform research experiments, its large-scale and quick deployment for IoT environments with a widely used wireless MAC layer protocol such as LoRaWAN has not been thoroughly tested. Therefore, in this paper we develop and present a simulation framework in NS-3 to offer MQTT-based on publish/subscribe architecture that can also support LoRaWAN communication standard. To this end, we utilize NS-3's LoRaWAN library and integrate it with a broker that connects to other types of publishers/subscribers. We enable unicast capability from the broker to LoRaWAN end-devices while supporting multiple topics at the broker. We tested several scenarios under this IoT architecture to demonstrate its feasibility while assessing the performance at scale

    A MEC-IIoT intelligent threat detector based on machine learning boosted tree algorithms

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    In recent years, new management methods have appeared that mark the beginning of a new industrial revolution called Industry 4.0 or the Industrial Internet of Things (IIoT). IIoT brings together new emerging technologies, such as the Internet of Things (IoT), Deep Learning (DL) and Machine Learning (ML), that contribute to new applications, industrial processes and efficiency management in factories. This combination of new technologies and contexts is paired with Multi-access Edge Computing (MEC) to reduce costs through the virtualisation of networks and services. As these new paradigms increase in growth, so does the number of threats and vulnerabilities, making IIoT a very desirable target for cybercriminals. In addition, IIoT devices have certain intrinsic limitations, especially due to their limited resources, and this makes it impossible, in many cases, to detect attacks by using solutions designed for other paradigms. So it is necessary to design, implement and evaluate new solutions or adapt existing ones. Therefore, this paper proposes an intelligent threat detector based on boosted tree algorithms. Such detectors have been implemented and evaluated in an environment specifically designed to test IIoT deployments. In this way, we can learn how these algorithms, which have been successful in multiple contexts, behave in a paradigm with known constraints. The results obtained in the study show that our intelligent threat detector achieves a mean efficiency of between 95%–99% in the F1 Score metric, indicating that it is a good option for implementation in these scenarios
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