scholarly journals Automatic Configuration of OPC UA for Industrial Internet of Things Environments

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 600 ◽  
Author(s):  
Jose Miguel Gutierrez-Guerrero ◽  
Juan Antonio Holgado-Terriza
Keyword(s):  
Internet Of Things ◽  
Data Exchange ◽  
Software Systems ◽  
Industrial Internet Of Things ◽  
Human Errors ◽  
Industrial Systems ◽  
Modbus Protocol ◽  
Industrial Internet ◽  
Ethernet Network ◽  
Ole For Process Control

Software technologies play an increasingly significant role in industrial environments, especially for the adoption of Industrial Internet of Things (IIoT). In this context, the application of mechanisms for the auto-configuration of industrial systems may be relevant for reducing human errors and costs in terms of time and money, improving the maintenance and the quality control. OPC UA (OLE for Process Control Unified Architecture) systems are usually integrated into an industrial system to provide a standard way for setting a secure and reliable data exchange between industrial devices of multiple vendors and software systems. In this paper, a novel mechanism for the auto-configuration of OPC UA systems is proposed from an initial setup of industrial devices interconnected to a basic Ethernet network. The auto-configuration of the OPC UA is self-managed over the TCP/IP protocol. This mechanism allows automating the configuration process of the OPC UA server automatically from the programmable logic controller (PLC) devices connected to a basic Ethernet network. Once the PLC devices are identified, they exchange information directly with OPC using a Modbus protocol over the same Ethernet network. To test the feasibility of this approach, a case study is prepared and evaluated.

scholarly journals Distributed Watchdogs Based on Blockchain for Securing Industrial Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4393
Author(s):  
JongHyup Lee ◽  
Taekyoung Kwon
Keyword(s):  
Internet Of Things ◽  
Software Protection ◽  
Industrial Internet Of Things ◽  
Industrial Systems ◽  
Industrial Internet ◽  
Unique Identity ◽  
Protection Mechanisms ◽  
Software Updates ◽  
Detailed Specification ◽  
Industrial Environments

The Industrial Internet of Things (IIoT) could enhance automation and analytics in industrial environments. Despite the promising benefits of IIoT, securely managing software updates is a challenging problem for those critical applications. This is due to at least the intrinsic lack of software protection mechanisms in legacy industrial systems. In this paper, to address the challenges in building a secure software supply chain for industrial environments, we propose a new approach that leverages distributed watchdogs with blockchain systems in protecting software supply chains. For this purpose, we bind every entity with a unique identity in the blockchain and employ the blockchain as a delegated authenticator by mapping every reporting action to a non-fungible token transfer. Moreover, we present a detailed specification to clearly define the behavior of systems and to apply model checking.

scholarly journals Security standard compliance and continuous verification for Industrial Internet of Things

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092273 ◽  
Author(s):  
Ani Bicaku ◽  
Markus Tauber ◽  
Jerker Delsing
Keyword(s):  
Internet Of Things ◽  
Best Practice ◽  
Automatic Monitoring ◽  
Industrial Internet Of Things ◽  
Industrial Systems ◽  
Best Practice Guidelines ◽  
Industrial Internet ◽  
Security Standard ◽  
Compliance Verification ◽  
Security Compliance

Due to globalization and digitalization of industrial systems, standard compliance is gaining more attention. In order to stay competitive and remain in business, different sectors within industry are required to comply with multiple regulations. Compliance aims to fulfill regulations by including all measures imposed by laws and standards. Every device, application, or service implements several technologies at many levels, and standards support interoperability across them. They help to create global markets for industries and enable networked development in order to be successful and sustainable. This work highlights the importance of standard compliance and continuous verification in industrial Internet of Things and implements an automatic monitoring and standard compliance verification framework. In this work, we focus on security, safety, and organizational aspects of industrial Internet of Things. We identify a number of standards and best practice guidelines, which are used to extract security, safety, and organizational measurable indicator points. In addition, a metric model is provided that forms the basis for the necessary information needed for compliance verification, including requirements, standards, and metrics. Also, we present the prototype of the monitoring and standard compliance verification framework used to show the security compliance of an industrial Internet of Things use case.

Secure Data Exchange in Industrial Internet of Things

2021 ◽  
Author(s):  
Anna Sukiasyan ◽  
Hasmik Badikyan ◽  
Tiago Pedrosa ◽  
Paulo Leitão
Keyword(s):  
Internet Of Things ◽  
Data Exchange ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Secure Data

scholarly journals Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4807 ◽  
Author(s):  
Rabeea Basir ◽  
Saad Qaisar ◽  
Mudassar Ali ◽  
Monther Aldwairi ◽  
Muhammad Ikram Ashraf ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Data Exchange ◽  
Fog Computing ◽  
Building Blocks ◽  
Smart Devices ◽  
Industrial Internet Of Things ◽  
Computing Architecture ◽  
Research Challenges ◽  
Industrial Internet

Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a comprehensive review of methods and techniques in fog computing. Our focus is on fog infrastructure and protocols in the context of IIoT applications. This article has two main research areas: In the first half, we discuss the history of industrial revolution, application areas of IIoT followed by key enabling technologies that act as building blocks for industrial transformation. In the second half, we focus on fog computing, providing solutions to critical challenges and as an enabler for IIoT application domains. Finally, open research challenges are discussed to enlighten fog computing aspects in different fields and technologies.

scholarly journals Reliability Evaluation Model Of Industrial Internet Of Things Systems

2020 ◽  
Vol 1 (1) ◽  
pp. 22-24
Author(s):  
Dong-Seong Kim
Keyword(s):  
Internet Of Things ◽  
Performance Indicator ◽  
Evaluation Model ◽  
Industrial Internet Of Things ◽  
Research Issues ◽  
Industrial Systems ◽  
Performance Accuracy ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Robust Systems

The Industrial Internet of Things (IIoT) allows digitizing manufacturing processes and increasing the digital connectivity of smart factory and industrial systems. The reliability of a system is considered as a key performance indicator that defines how accurately and perfectly the system works. Ensuring reliability in industrial IoT exposes several challenges as well as promising opportunities for advancing technologies and systematic designs such as algorithms, architectures, and devices. It depends on several factors, for example, ensuring performance, accuracy, stability, and availability. This article provides a systematic model for evaluating the reliability of IIoT systems. This model enables elucidate several open research issues regarding designing the reliable and robust systems.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

2020 ◽  
pp. 7-12
Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский
Keyword(s):  
Internet Of Things ◽  
Data Acquisition ◽  
Predictive Analytics ◽  
Actual State ◽  
Monitoring And Control ◽  
Industrial Internet Of Things ◽  
Machining Time ◽  
Industrial Internet ◽  
Acquisition Device ◽  
Data Acquisition Device

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

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