Self-Commissioning Industrial IoT-Systems in Process Automation: A Reference Architecture

Koziolek, Heiko; Burger, Andreas; Doppelhamer, Jens

doi:10.1109/icsa.2018.00029

Cited by 23 publications

(16 citation statements)

References 12 publications

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“…We claim that our proposal is useful for supporting engineering activities potentially for all IoT application domains, including the field of Industrial Internet of Things (IIoT) systems [31]. As identified by Koziolek and colleagues [32], distributed control systems are currently evolving towards IIoT. However, the initial network configuration, applicationspecific device configuration, and integration with other devices are cumbersome and laborious nowadays.…”

Section: Introductionmentioning

confidence: 95%

Towards the adoption of OMG standards in the development of SOA-based IoT systems

Costa

Pires

Delicato

2020

Journal of Systems and Software

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A common feature of the Internet of Things (IoT) is the high heterogeneity, regarding network protocols, data formats, hardware and software platforms. Aiming to deal with such a degree of heterogeneity, several frameworks have applied the Model-Driven Development (MDD) to build IoT applications. On the software architecture viewpoint, the literature has shown that the Service-Oriented Architecture (SOA) is a promising style to address the interoperability of entities composing these solutions. Some features of IoT make it challenging to analyze the impact of design decisions on the SOAbased IoT applications behavior. Thus, it is a key requirement to simulate the model to verify whether the system performs as expected before its implementation. Although the literature has identified that the SOA style is suitable for addressing the interoperability, existing modelling languages do not consider SOA elements as first-class citizens when designing IoT applications. Furthermore, although existing MDD frameworks provide modeling languages comprising well-defined syntax, they lack execution semantics, thus, are not suitable for model execution and analysis. This work aims at addressing these issues by introducing IoTDraw. The framework provides a fully OMG-compliant executable modeling language for SOA-based IoT systems; thus, its specifications can be implemented by any tool implementing OMG standards. Keywords-internet of things, application, model-driven development, service-oriented architecture given rise to the recent paradigm known as Sensor-Cloud or Cloud of Things, which aims to make the most of both technologies. IoT-generated data that requires a lot of processing or long-term storage can be sent to the cloud, which in turn extends its service portfolio to encompass sensing and actuation capabilities. Cloud platforms follow a service-based resource provisioning model. Cloud platforms providing infrastructure for IoT systems naturally adopt the services approach (e.g., [17], [18]). In a recent survey that investigated middleware technologies for Cloud of Things [19], the authors have identified that SOA is the main architectural style in CoT-based Middleware, due to is capability of promoting interoperability and reusability in IoT systems. 1.1 Issues in designing MDD & SOA-based IoT Systems Any DSL must provide a coherent set of concepts related to the domain of interest [8]. That is, the DSL must be expressive, aiming to allow the precise identification of multiple aspects regarding the application domain. Otherwise, if the DSL lacks essential elements of the underlying domain, the models may be at least ambiguous, or the modelers may not be able to represent all components of the applications. Although the literature has identified the suitability of the SOA style for addressing the interoperability in the IoT domain, to the best of our knowledge, there is no DSL tailored for the modeling of SOA-based IoT applications. SOA is a proven architectural pattern, with a well-known set of concepts. Existing DSLs ...

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Section: Introductionmentioning

confidence: 95%

Towards the adoption of OMG standards in the development of SOA-based IoT systems

Costa

Pires

Delicato

2020

Journal of Systems and Software

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“…Last, the software architecture community has recently come up with a reference architecture for fast self-commissioning of for industrial IoT-systems in process automation [15]. Although commissioning times could be reduced to a few seconds across vendor products, they rely on the assumption that all vendors conform to standardized models such as PLCOpen on every layer (c.f.…”

Section: Related Workmentioning

confidence: 99%

A Conceptual Architecture for Enabling Future Self-Adaptive Service Systems

Burzlaff

Bartelt

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Dynamic integration methods for unknown data sources and services at system design time are currently primarily driven by technological standards. Hence, little emphasis is being placed on integration methods. However, the combination of heterogeneous data sources and services offered by devices across domains is hard to standardize. In this paper, we will shed light on the interplay of self-adaptive system architectures as well as bottom-up, incremental integration methods relying on formal knowledge bases. An incremental integration method has direct influences on both the system architecture itself and the way these systems are engineered and operated during design and runtime. Our findings are evaluated in the context of a case study that uses an adapted bus architecture including two tool prototypes. In addition, we illustrate conceptually how control loops such as MAPE-K can be enriched with machine-readable integration knowledge.

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“…In order to cope up with the Industry 4.0 many industries are adopting newer cutting edge technologies such as Machine learning, Deep neural networks, Block chain and Internet of Things. The IoT has found its applications in all walks of life from agriculture [1], Energy [2]- [3], Industrial Automation [4], Medical [5]- [6], Transportation, Smart city, logistics and in all possible domains [7]- [9].…”

Section: A Generalmentioning

confidence: 99%

Wireless Monitoring Of Industrial Drives Using Internet Of Things Technology (Iot)

Kaliappan,

Ponkarthika,

Gowrishankar

et al. 2019

IJEAT

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Electrical motors and drives consumes about 45% of the power generation. However, if the electrical machines are not maintained properly the drives consumes about 5% to 10 % of excess power which affects the productivity and revenue. Continuous monitoring of critical parameters of the drives is crucial for an industry which continuously operates large number of electrical drives. Before the advent of Internet of Things (IoT) technology, monitoring of the machine parameters were carried out using Supervisory Control and Data Acquisition (SCADA), which can store data temporarily, after which that data will be overwritten by more recent data. Also the online monitoring of the machine is not feasible. In the IoT technology the data collected can be safely stored in the Cloud and retrieved whenever needed. Moreover the data collected can be easy integrated through any platform to any application, which benefits the end user by cutting down huge investment costs. In the presented work, the machine parameters like current, voltage, speed and number of working hours of the machine, temperature are measured using the sensors for continuous monitoring. The data is collected and processed using microcontroller and transferred to a remote server wirelessly using Message Queuing Telemetry Transport (MQTT) protocol. The received data is then sent to the telegram server. Any deviation from the safe operating conditions is reported to the server and control room through chatbot in telegram mobile app for immediate action

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Self-Commissioning Industrial IoT-Systems in Process Automation: A Reference Architecture

Cited by 23 publications

References 12 publications

Towards the adoption of OMG standards in the development of SOA-based IoT systems

Towards the adoption of OMG standards in the development of SOA-based IoT systems

A Conceptual Architecture for Enabling Future Self-Adaptive Service Systems

Wireless Monitoring Of Industrial Drives Using Internet Of Things Technology (Iot)

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