Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976183
Ryan Kurte, Z. Salcic, K. Wang
This paper presents DSF-IoT, a novel distributed approach enabling a future decentralised Internet of Things (IoT). DSF-IoT is designed to address key challenges in the IoT, providing a novel secure and efficient specification for the description of IoT services and their data, as well as novel mechanisms for consistent dynamic and contextually relevant service discovery and interaction. Distributed technologies provide an alternative to existing centralised and firmly capitalised models for service provision, removing the requirements for trusted vendor infrastructure and simplifying the deployment of IoT devices, while end-to-end trust, authenticity, and confidentiality ensure user interactions and data are secure-by-default. DSF-IoT is demonstrated through the development of a network of demonstration devices, and evaluated against existing frameworks for IoT service specification and discovery.
{"title":"A Specification for a Decentralised Internet of Things","authors":"Ryan Kurte, Z. Salcic, K. Wang","doi":"10.1109/INDIN51773.2022.9976183","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976183","url":null,"abstract":"This paper presents DSF-IoT, a novel distributed approach enabling a future decentralised Internet of Things (IoT). DSF-IoT is designed to address key challenges in the IoT, providing a novel secure and efficient specification for the description of IoT services and their data, as well as novel mechanisms for consistent dynamic and contextually relevant service discovery and interaction. Distributed technologies provide an alternative to existing centralised and firmly capitalised models for service provision, removing the requirements for trusted vendor infrastructure and simplifying the deployment of IoT devices, while end-to-end trust, authenticity, and confidentiality ensure user interactions and data are secure-by-default. DSF-IoT is demonstrated through the development of a network of demonstration devices, and evaluated against existing frameworks for IoT service specification and discovery.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123600877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/indin51773.2022.9976178
Marc Brunninghaus, Carsten Rocker
{"title":"Low-Code Development in Worker Assistance Systems: Improving Flexibility and Adaptability","authors":"Marc Brunninghaus, Carsten Rocker","doi":"10.1109/indin51773.2022.9976178","DOIUrl":"https://doi.org/10.1109/indin51773.2022.9976178","url":null,"abstract":"","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115062939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976148
Laurin Prenzel, Simon Hofmann, S. Steinhorst
Dynamic reconfiguration is a core contributor to the flexibility and agility of future industrial control systems. Verification and validation can provide some confidence in the success of a reconfiguration, yet unexpected external events or bugs can always lead to the abortion of the reconfiguration process. This can threaten the real-time behavior and must be anticipated. In this paper, we extend existing real-time models of dynamic reconfiguration to incorporate safe rollback scenarios that allow a disruption-free reversal of the reconfiguration process, thus providing fault-tolerance. We introduce the concept of a point of no return, after which a rollback is no longer feasible. We demonstrate in two example systems how the ordering of operations can affect the length of the rollback sequence and optimize the ordering of operations in two stages to find a sequence that offers a maximal fault-tolerance, while minimizing the real-time disruption. The results indicate that while considering potential failure modes requires additional overhead, it can provide fault-tolerance that promotes the further application of dynamic reconfiguration in practical applications. This may lead to higher agility and resilience in industrial control systems of the future.
{"title":"Rollback Sequences for Dynamic Reconfiguration of IEC 61499","authors":"Laurin Prenzel, Simon Hofmann, S. Steinhorst","doi":"10.1109/INDIN51773.2022.9976148","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976148","url":null,"abstract":"Dynamic reconfiguration is a core contributor to the flexibility and agility of future industrial control systems. Verification and validation can provide some confidence in the success of a reconfiguration, yet unexpected external events or bugs can always lead to the abortion of the reconfiguration process. This can threaten the real-time behavior and must be anticipated. In this paper, we extend existing real-time models of dynamic reconfiguration to incorporate safe rollback scenarios that allow a disruption-free reversal of the reconfiguration process, thus providing fault-tolerance. We introduce the concept of a point of no return, after which a rollback is no longer feasible. We demonstrate in two example systems how the ordering of operations can affect the length of the rollback sequence and optimize the ordering of operations in two stages to find a sequence that offers a maximal fault-tolerance, while minimizing the real-time disruption. The results indicate that while considering potential failure modes requires additional overhead, it can provide fault-tolerance that promotes the further application of dynamic reconfiguration in practical applications. This may lead to higher agility and resilience in industrial control systems of the future.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134429644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976152
Hongwei Li, D. Chasaki
Most of the recent high-profile attacks targeting cyber-physical systems (CPS) started with lengthy reconnaissance periods that enabled attackers to gain in-depth understanding of the victim’s environment. To simulate these stealthy attacks, several covert channel tools have been published and proven effective in their ability to blend into existing CPS communication streams and have the capability for data exfiltration and command injection.In this paper, we report a novel machine learning feature engineering and data processing pipeline for the detection of covert channel attacks on CPS systems with real-time detection throughput. The system also operates at the network layer without requiring physical system domain-specific state modeling, such as voltage levels in a power generation system. We not only demonstrate the effectiveness of using TCP payload entropy as engineered features and the technique of grouping information into network flows, but also pitch the proposed detector against scenarios employing advanced evasion tactics, and still achieve above 99% detection performance.
{"title":"Network-Based Machine Learning Detection of Covert Channel Attacks on Cyber-Physical Systems","authors":"Hongwei Li, D. Chasaki","doi":"10.1109/INDIN51773.2022.9976152","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976152","url":null,"abstract":"Most of the recent high-profile attacks targeting cyber-physical systems (CPS) started with lengthy reconnaissance periods that enabled attackers to gain in-depth understanding of the victim’s environment. To simulate these stealthy attacks, several covert channel tools have been published and proven effective in their ability to blend into existing CPS communication streams and have the capability for data exfiltration and command injection.In this paper, we report a novel machine learning feature engineering and data processing pipeline for the detection of covert channel attacks on CPS systems with real-time detection throughput. The system also operates at the network layer without requiring physical system domain-specific state modeling, such as voltage levels in a power generation system. We not only demonstrate the effectiveness of using TCP payload entropy as engineered features and the technique of grouping information into network flows, but also pitch the proposed detector against scenarios employing advanced evasion tactics, and still achieve above 99% detection performance.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132856945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976102
Kamal Rsetam, M. Al-Rawi, Z. Cao
A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its estimation error. Finally, the tracking performance is examined by carrying out several simulations on robotic systems with compliant actuators as an application example of the high order systems. In addition, the comparative study is conducted between the proposed SMC method with RESO and a feedback linearization control (FLC) with a full-order ESO to confirm the estimation and tracking performance of the proposed scheme.
{"title":"Robust Continuous Sliding Mode Controller for Uncertain Canonical Brunovsky Systems Using Reduced Order Extended State Observer","authors":"Kamal Rsetam, M. Al-Rawi, Z. Cao","doi":"10.1109/INDIN51773.2022.9976102","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976102","url":null,"abstract":"A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its estimation error. Finally, the tracking performance is examined by carrying out several simulations on robotic systems with compliant actuators as an application example of the high order systems. In addition, the comparative study is conducted between the proposed SMC method with RESO and a feedback linearization control (FLC) with a full-order ESO to confirm the estimation and tracking performance of the proposed scheme.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130940576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976161
S. Zhou, Zhili Michelle Chen, J. Huang, Heping Pan
The statistics for a window of an engineering observation is called running window quantity. Running intra-covariance is a special case of running inter-covariance, when two variables are the same. The inter-covariance minus the geometric average of respected intra-covariances is called the pure inter-covariance. It gives you a cleaner association analysis compared with the running Pearson analysis. The normalization of covariance to standard deviation is called the Pearson correlation coefficient. The covariance for the region above or below the average is called semi-covariance (upper or down). Here we present a pure inter running semi-covariance, an accurate ReLU (Rectified Linear Unit) way of measuring the inter-non-linear correlation between variables excluding the intra-non-linear components. Our framework is applied to successfully analyze the association between war factors and the gold response. The result of our analyses of the 12 years after the 2007 Mortgage crisis on the war equipment companies' stock versus the gold suggests that stocks from different regions have a slightly different impact on the gold value that reflects the overall peaceful economic prosperities.
{"title":"War Economy Analysis after Mortgage Crisis on Stock and Gold with Semi-Stock and Gold with Semi--Covariance Covariance Covariance","authors":"S. Zhou, Zhili Michelle Chen, J. Huang, Heping Pan","doi":"10.1109/INDIN51773.2022.9976161","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976161","url":null,"abstract":"The statistics for a window of an engineering observation is called running window quantity. Running intra-covariance is a special case of running inter-covariance, when two variables are the same. The inter-covariance minus the geometric average of respected intra-covariances is called the pure inter-covariance. It gives you a cleaner association analysis compared with the running Pearson analysis. The normalization of covariance to standard deviation is called the Pearson correlation coefficient. The covariance for the region above or below the average is called semi-covariance (upper or down). Here we present a pure inter running semi-covariance, an accurate ReLU (Rectified Linear Unit) way of measuring the inter-non-linear correlation between variables excluding the intra-non-linear components. Our framework is applied to successfully analyze the association between war factors and the gold response. The result of our analyses of the 12 years after the 2007 Mortgage crisis on the war equipment companies' stock versus the gold suggests that stocks from different regions have a slightly different impact on the gold value that reflects the overall peaceful economic prosperities.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130238941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976077
Jifeng Sun, Yinghe Qing, Chang Liu, Jianwu Lin
The stock price’s highly unstable fluctuation pattern makes learning efficient representation challenging to model the stock movement. The common deep learning often overfits after a few epochs of training and performs poorly in the validation set because the optimization objective is insufficient to characterize the stock adequately. In this paper, we propose Self-FTS, a self-supervised learning framework for financial time series representation, to learn the underlying representation and use in stock trading, affected by the fact that self-supervised learning is a promising technique for learning representation for extracting high dimensional features from unlabeled financial data to overcome the bias caused by handcrafted features. Specifically, we design several auxiliary tasks to generate samples with pseudo labels from the A-share stock price data sets and build a weight-sharing feature extraction backbone combined with a classification head to learn the pseudo labels based on the samples. Finally, We evaluate the learned representations extracted from the backbone by fine-tuning data sets labelled with stock returns to build an investment portfolio. Experimental analysis results on the Chinese stock market data show that our method significantly improves the stock trend forecasting performances and the actual investment income through backtesting compared to the current SOTA method, which strongly demonstrates our effective approach.
{"title":"Self-FTS: A Self-Supervised Learning Method for Financial Time Series Representation in Stock Intraday Trading","authors":"Jifeng Sun, Yinghe Qing, Chang Liu, Jianwu Lin","doi":"10.1109/INDIN51773.2022.9976077","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976077","url":null,"abstract":"The stock price’s highly unstable fluctuation pattern makes learning efficient representation challenging to model the stock movement. The common deep learning often overfits after a few epochs of training and performs poorly in the validation set because the optimization objective is insufficient to characterize the stock adequately. In this paper, we propose Self-FTS, a self-supervised learning framework for financial time series representation, to learn the underlying representation and use in stock trading, affected by the fact that self-supervised learning is a promising technique for learning representation for extracting high dimensional features from unlabeled financial data to overcome the bias caused by handcrafted features. Specifically, we design several auxiliary tasks to generate samples with pseudo labels from the A-share stock price data sets and build a weight-sharing feature extraction backbone combined with a classification head to learn the pseudo labels based on the samples. Finally, We evaluate the learned representations extracted from the backbone by fine-tuning data sets labelled with stock returns to build an investment portfolio. Experimental analysis results on the Chinese stock market data show that our method significantly improves the stock trend forecasting performances and the actual investment income through backtesting compared to the current SOTA method, which strongly demonstrates our effective approach.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116509319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976138
Kai-yu Tsang, Zuneera Umair, U. Qureshi, I. Zwetsloot
The food industry has been facing extreme shortages of food as a result of higher consumption due to increasing population. One of the key reasons of food shortages is inadequate water supply to the crops and plants. Usually farmers setup a schedule to supply water without assessing the real-time condition of the plants, which leads to wasting water in substantial quantities. As a result, plants are sometimes under watered or over watered. In this paper, we propose an IoT based watering system for plants that uses a microcontroller, a soil moisture sensor, an environmental temperature sensor, and a humidity sensor to assess favourable conditions of a plant’s growth. We propose 4 different experimental setups including regular watering schedules setups and modified watering schedule setups for both indoor and outdoor settings. We observe that watering the plants by a modified schedule based on the plants condition, the growth increases by using minimum amount of water. We further apply regression analysis on different variables in our system to observe the factors that have a direct effect on the growth of the plant. Based on our data analysis, environmental temperature plays the most important part in the growth of a plant along with adequate water supply.
{"title":"An IoT-based Optimized Watering System for Plants","authors":"Kai-yu Tsang, Zuneera Umair, U. Qureshi, I. Zwetsloot","doi":"10.1109/INDIN51773.2022.9976138","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976138","url":null,"abstract":"The food industry has been facing extreme shortages of food as a result of higher consumption due to increasing population. One of the key reasons of food shortages is inadequate water supply to the crops and plants. Usually farmers setup a schedule to supply water without assessing the real-time condition of the plants, which leads to wasting water in substantial quantities. As a result, plants are sometimes under watered or over watered. In this paper, we propose an IoT based watering system for plants that uses a microcontroller, a soil moisture sensor, an environmental temperature sensor, and a humidity sensor to assess favourable conditions of a plant’s growth. We propose 4 different experimental setups including regular watering schedules setups and modified watering schedule setups for both indoor and outdoor settings. We observe that watering the plants by a modified schedule based on the plants condition, the growth increases by using minimum amount of water. We further apply regression analysis on different variables in our system to observe the factors that have a direct effect on the growth of the plant. Based on our data analysis, environmental temperature plays the most important part in the growth of a plant along with adequate water supply.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126960962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976096
S. Biffl, S. Kropatschek, Elmar Kiesling, Kristof Meixner, A. Lüder
During the ramp-up of a production system, complex and difficult to resolve product quality issues often result in tedious experimentation and costly delays. A particular challenge in this context is insufficient guidance for operators on how to resolve issues and adapt their actions to a new production context. Failure Mode and Effects Analysis (FMEA) can help to identify and address likely causes of production quality issues. However, FMEA models are typically (i) isolated from engineering domain models on product, process and resource (PPR) concerns, and (ii) not actionable for operators. This paper introduces the FMEA-to-Operation (F2O) approach to reduce the risk of ramp-up delays and recurring quality issues by integrating the required domain knowledge for model-driven, machine skill-centric, and actionable process FMEA. The F2O approach (i) validates likely root causes of a production quality issue by linking these causes to engineering reality in a graph database, and (ii) derives operation checklists with prioritized countermeasures. In a feasibility study on a real-world welding cell for car parts, we evaluated the effectiveness and efficiency of the F2O approach. Results indicate that the F2O approach is feasible and effective, and provides operators with actionable, context-specific guidelines that are well grounded in engineering models.
{"title":"Risk-Driven Derivation of Operation Checklists from Multi-Disciplinary Engineering Knowledge","authors":"S. Biffl, S. Kropatschek, Elmar Kiesling, Kristof Meixner, A. Lüder","doi":"10.1109/INDIN51773.2022.9976096","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976096","url":null,"abstract":"During the ramp-up of a production system, complex and difficult to resolve product quality issues often result in tedious experimentation and costly delays. A particular challenge in this context is insufficient guidance for operators on how to resolve issues and adapt their actions to a new production context. Failure Mode and Effects Analysis (FMEA) can help to identify and address likely causes of production quality issues. However, FMEA models are typically (i) isolated from engineering domain models on product, process and resource (PPR) concerns, and (ii) not actionable for operators. This paper introduces the FMEA-to-Operation (F2O) approach to reduce the risk of ramp-up delays and recurring quality issues by integrating the required domain knowledge for model-driven, machine skill-centric, and actionable process FMEA. The F2O approach (i) validates likely root causes of a production quality issue by linking these causes to engineering reality in a graph database, and (ii) derives operation checklists with prioritized countermeasures. In a feasibility study on a real-world welding cell for car parts, we evaluated the effectiveness and efficiency of the F2O approach. Results indicate that the F2O approach is feasible and effective, and provides operators with actionable, context-specific guidelines that are well grounded in engineering models.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125412496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1109/INDIN51773.2022.9976153
Nico Braunisch, Sven Schlesinger, R. Lehmann
New approaches are regularly developed, but their implementation in existing environments is a challenge, and Industry 4.0 is not different. In this paper, we present our approach towards a modular and adaptable gateway to retrofit brownfield installation for use in the context of Industrial IoT. The aim is to close the gap between existing operational technology installation and modern IT infrastructure. To fulfil time constraints and flexibility requirements, a highly decoupled architecture employing a streaming platform is proposed. For the data to be useful for downstream processes, it is annotated with means of Industry 4.0 modelling standards. The loosely coupled gateway presented by us is intended to help make existing installations Industry 4.0 capable without having to re-engineer them directly.
{"title":"Adaptive Industrial IoT gateway using kafka streaming platform","authors":"Nico Braunisch, Sven Schlesinger, R. Lehmann","doi":"10.1109/INDIN51773.2022.9976153","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976153","url":null,"abstract":"New approaches are regularly developed, but their implementation in existing environments is a challenge, and Industry 4.0 is not different. In this paper, we present our approach towards a modular and adaptable gateway to retrofit brownfield installation for use in the context of Industrial IoT. The aim is to close the gap between existing operational technology installation and modern IT infrastructure. To fulfil time constraints and flexibility requirements, a highly decoupled architecture employing a streaming platform is proposed. For the data to be useful for downstream processes, it is annotated with means of Industry 4.0 modelling standards. The loosely coupled gateway presented by us is intended to help make existing installations Industry 4.0 capable without having to re-engineer them directly.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127837078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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