Pub Date : 2025-07-25DOI: 10.1109/OJIES.2025.3592876
Angel Maureira;Sebastián Riffo;Esteban Ibáñez;Catalina González-Castaño;Marco Rivera;Cristian Guarnizo-Lemus;Abraham M. Alcaide;Carlos Restrepo
Conventional model predictive control (MPC) of power converters has been widely found in many power electronics and motor drive applications. The performance of MPC strongly depends on the precision of the converter’s physical parameters, and a mismatch of them produces a control degradation, which leads to MPC suboptimal operation. Ensuring a precise estimation of the converter’s parameters is difficult because they continuously change during the operation process due to their operating point and aging. Recently, model-free predictive control (MF-PC) has been used in motor drives and power electronics converters, especially inverters and rectifiers, to deal with the predictive control method’s dependency model. However, MF-PC proposed for dc–dc converters is an open innovation scientific field. This article proposes an MF-PC designed for second-order dc–dc converters, such as the boost, buck, buck–boost, and noninverting buck–boost converters. The presented approach uses a Kalman filter to estimate the positive and negative inductor current slopes with high accuracy and a low computational cost. The experimental results show that the proposed method is robust against parameter and model changes compared to conventional model-based solutions.
{"title":"Kalman Filter-Based Model-Free Predictive Control of Classical DC–DC Power Converters","authors":"Angel Maureira;Sebastián Riffo;Esteban Ibáñez;Catalina González-Castaño;Marco Rivera;Cristian Guarnizo-Lemus;Abraham M. Alcaide;Carlos Restrepo","doi":"10.1109/OJIES.2025.3592876","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3592876","url":null,"abstract":"Conventional model predictive control (MPC) of power converters has been widely found in many power electronics and motor drive applications. The performance of MPC strongly depends on the precision of the converter’s physical parameters, and a mismatch of them produces a control degradation, which leads to MPC suboptimal operation. Ensuring a precise estimation of the converter’s parameters is difficult because they continuously change during the operation process due to their operating point and aging. Recently, model-free predictive control (MF-PC) has been used in motor drives and power electronics converters, especially inverters and rectifiers, to deal with the predictive control method’s dependency model. However, MF-PC proposed for dc–dc converters is an open innovation scientific field. This article proposes an MF-PC designed for second-order dc–dc converters, such as the boost, buck, buck–boost, and noninverting buck–boost converters. The presented approach uses a Kalman filter to estimate the positive and negative inductor current slopes with high accuracy and a low computational cost. The experimental results show that the proposed method is robust against parameter and model changes compared to conventional model-based solutions.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1175-1187"},"PeriodicalIF":4.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11096584","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents a new transformerless switched-capacitor (SC) based five-level grid-connected inverter with inherent voltage-boosting capability. The proposed topology achieves a voltage gain factor of two without requiring an additional dc–dc boost converter or transformer, resulting in a more compact, cost-effective, and efficient design. A single SC cell is utilized to perform bidirectional capacitor charging during both positive and negative grid half cycles, thereby improving energy transfer efficiency and significantly reducing capacitor size and volume compared with the conventional topologies. The inverter employs a minimal number of components—only nine switches and one flying capacitor—while maintaining high performance. Only five switches operate at high frequency, which reduces switching losses, gate driver complexity, and electromagnetic interference. A straightforward control strategy ensures that the inverter delivers a high-quality sinusoidal current waveform to the grid and supports both active and reactive-power flow under various power factor conditions. The reliability of the proposed inverter is analyzed, and its performance is validated through detailed simulations and experimental results. A comparative study with the existing solutions highlights the advantages of the proposed topology in terms of efficiency, voltage gain, component count, and waveform quality.
{"title":"A New Reliable Switched-Capacitor-Based High Step-Up Five-Level Inverter","authors":"Milad Ghavipanjeh Marangalu;Naser Vosoughi Kurdkandi;Kourosh Khalaj Monfared;Yousef Neyshabouri;Hani Vahedi","doi":"10.1109/OJIES.2025.3590777","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3590777","url":null,"abstract":"This article presents a new transformerless switched-capacitor (SC) based five-level grid-connected inverter with inherent voltage-boosting capability. The proposed topology achieves a voltage gain factor of two without requiring an additional dc–dc boost converter or transformer, resulting in a more compact, cost-effective, and efficient design. A single SC cell is utilized to perform bidirectional capacitor charging during both positive and negative grid half cycles, thereby improving energy transfer efficiency and significantly reducing capacitor size and volume compared with the conventional topologies. The inverter employs a minimal number of components—only nine switches and one flying capacitor—while maintaining high performance. Only five switches operate at high frequency, which reduces switching losses, gate driver complexity, and electromagnetic interference. A straightforward control strategy ensures that the inverter delivers a high-quality sinusoidal current waveform to the grid and supports both active and reactive-power flow under various power factor conditions. The reliability of the proposed inverter is analyzed, and its performance is validated through detailed simulations and experimental results. A comparative study with the existing solutions highlights the advantages of the proposed topology in terms of efficiency, voltage gain, component count, and waveform quality.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1188-1209"},"PeriodicalIF":4.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11086518","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article proposes the use of a proportional–integral–derivative (PID) controller as an adaptive mechanism within the framework of the model reference adaptive system-based rotor flux (MRASF) for accurate rotor speed estimation in induction motors. The controller is designed to impose specific dynamic behaviors and performance criteria, addressing the sensitivity of MRASF dynamics to slip speed. To achieve this, a full-order transfer function of the MRASF is employed to systematically derive the PID parameters using compensation and pole placement techniques. The proposed control strategy ensures that the estimated rotor speed closely follows the desired performance across various operating conditions. The effectiveness of the MRASF–PID design is validated through both simulation and experimental testing under open-loop voltage/frequency control of the induction machine, confirming the successful realization of the targeted dynamic and steady-state performance.
{"title":"Design and Implementation of PID Adaptation Mechanism for MRAS-Based Speed Estimation of Induction Machine","authors":"Mohamed Amine Fnaiech;Mohamed Trabelsi;Ayman Al-Khazraji;Maamar Taleb;Hani Vahedi","doi":"10.1109/OJIES.2025.3587055","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3587055","url":null,"abstract":"This article proposes the use of a proportional–integral–derivative (PID) controller as an adaptive mechanism within the framework of the model reference adaptive system-based rotor flux (MRASF) for accurate rotor speed estimation in induction motors. The controller is designed to impose specific dynamic behaviors and performance criteria, addressing the sensitivity of MRASF dynamics to slip speed. To achieve this, a full-order transfer function of the MRASF is employed to systematically derive the PID parameters using compensation and pole placement techniques. The proposed control strategy ensures that the estimated rotor speed closely follows the desired performance across various operating conditions. The effectiveness of the MRASF–PID design is validated through both simulation and experimental testing under open-loop voltage/frequency control of the induction machine, confirming the successful realization of the targeted dynamic and steady-state performance.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1090-1100"},"PeriodicalIF":5.2,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11074712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-03DOI: 10.1109/OJIES.2025.3585749
D. del Giudice;A. Dolara;J. D. Bastidas-Rodriguez;G. Spagnuolo;A. M. Brambilla;F. Bizzarri
Mismatched operating conditions occur very frequently in photovoltaic arrays, especially in urban installations or those that are commonly referred to as agrivoltaic. Mismatches are not only due to partial shading, but also to modules’ construction tolerances and installation mistakes, to maintenance operations, to a different effect of aging on modules, to an uneven distribution of dust, pollution, and snow on the module surfaces. The simulation of photovoltaic arrays operating in mismatched conditions is required in many applications, from plant design to model-based control, from monitoring and diagnosis up to the implementation of a digital twin. Some applications require not only an extreme granularity level (even at the single cell or fractions of it) but also a very fast computation compatible with real-time applications, running on embedded processors. This article introduces a new approach to the simulation of mismatched photovoltaic arrays based on isomorphism. The approach exploits similarities among subsections of the array to minimize the number of nonlinear equations modeling it. The lower the simulation accuracy required, the smaller the rank of the system of equations to solve. The application examples proposed in the article, concerning a PV array affected by a partial shading by nearby objects that changes during the day and a faulty PV field made up of half-cut modules, allow one to quantify the reduction in model complexity and the consequent computation time granted by the proposed technique as a function of the desired accuracy of the simulation results.
{"title":"Isomorphism-Based Fast Simulation of Mismatched Photovoltaic Arrays","authors":"D. del Giudice;A. Dolara;J. D. Bastidas-Rodriguez;G. Spagnuolo;A. M. Brambilla;F. Bizzarri","doi":"10.1109/OJIES.2025.3585749","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3585749","url":null,"abstract":"Mismatched operating conditions occur very frequently in photovoltaic arrays, especially in urban installations or those that are commonly referred to as agrivoltaic. Mismatches are not only due to partial shading, but also to modules’ construction tolerances and installation mistakes, to maintenance operations, to a different effect of aging on modules, to an uneven distribution of dust, pollution, and snow on the module surfaces. The simulation of photovoltaic arrays operating in mismatched conditions is required in many applications, from plant design to model-based control, from monitoring and diagnosis up to the implementation of a digital twin. Some applications require not only an extreme granularity level (even at the single cell or fractions of it) but also a very fast computation compatible with real-time applications, running on embedded processors. This article introduces a new approach to the simulation of mismatched photovoltaic arrays based on isomorphism. The approach exploits similarities among subsections of the array to minimize the number of nonlinear equations modeling it. The lower the simulation accuracy required, the smaller the rank of the system of equations to solve. The application examples proposed in the article, concerning a PV array affected by a partial shading by nearby objects that changes during the day and a faulty PV field made up of half-cut modules, allow one to quantify the reduction in model complexity and the consequent computation time granted by the proposed technique as a function of the desired accuracy of the simulation results.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1075-1089"},"PeriodicalIF":5.2,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11068156","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-02DOI: 10.1109/OJIES.2025.3585439
Joao Dinis;José Alberto;Antonio J. Marques Cardoso
This article introduces the implementation of an adaptive termination impedance alongside a corresponding control algorithm designed for resonant arrays in inductive wireless power transfer systems for vehicle charging applications. The integration of an adaptive termination impedance in the final cell of the array significantly improves both energy transfer between the transmitter array and the receiver. By employing the proposed algorithm, which estimates the receiver’s position relative to the array through voltage and current measurement in the first cell directly connected to the power source, the need for additional position sensors is eliminated. Moreover, this innovative approach not only reduces the number of components but also lowers system cost and complexity, while allowing the system to be modular, as the proposed method works for any number of array cells. The effectiveness of the proposed solution has been validated through comprehensive simulations and experimental testing.
{"title":"Optimization of Resonant Arrays for Dynamic Wireless Power Transfer Using Adaptive Termination","authors":"Joao Dinis;José Alberto;Antonio J. Marques Cardoso","doi":"10.1109/OJIES.2025.3585439","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3585439","url":null,"abstract":"This article introduces the implementation of an adaptive termination impedance alongside a corresponding control algorithm designed for resonant arrays in inductive wireless power transfer systems for vehicle charging applications. The integration of an adaptive termination impedance in the final cell of the array significantly improves both energy transfer between the transmitter array and the receiver. By employing the proposed algorithm, which estimates the receiver’s position relative to the array through voltage and current measurement in the first cell directly connected to the power source, the need for additional position sensors is eliminated. Moreover, this innovative approach not only reduces the number of components but also lowers system cost and complexity, while allowing the system to be modular, as the proposed method works for any number of array cells. The effectiveness of the proposed solution has been validated through comprehensive simulations and experimental testing.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1066-1074"},"PeriodicalIF":5.2,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11066279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-30DOI: 10.1109/OJIES.2025.3526497
{"title":"IEEE Industrial Electronics Society Information","authors":"","doi":"10.1109/OJIES.2025.3526497","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3526497","url":null,"abstract":"","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"C3-C3"},"PeriodicalIF":5.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11059357","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-30DOI: 10.1109/OJIES.2025.3526495
{"title":"IEEE Open Journal of the Industrial Electronics Society Publication Information","authors":"","doi":"10.1109/OJIES.2025.3526495","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3526495","url":null,"abstract":"","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"C2-C2"},"PeriodicalIF":5.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11059354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-30DOI: 10.1109/OJIES.2025.3526493
{"title":"IEEE Open Journal of the Industrial Electronics Society Instructions for Authors","authors":"","doi":"10.1109/OJIES.2025.3526493","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3526493","url":null,"abstract":"","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"C4-C4"},"PeriodicalIF":5.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11059356","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-23DOI: 10.1109/OJIES.2025.3582482
Francesco Ferracuti;Riccardo Felicetti;Luca Cavanini;Patrick Schweitzer;Andrea Monteriù
This article presents a method to detect and classify series arc faults affecting domestic AC electrical circuits by the analysis of electric current time series data, based on the HYDRA (HYbrid Dictionary-Rocket Architecture) algorithm, a fast dictionary method for time series classification employing competing convolutional kernels. The key novel contributions are twofold: Competing convolutional kernels are suitable to effectively extract features representing an effective set of arc fault detection indicators, and the classification performed in this way is feasible to be executed in real time. The proposed method is validated using a public database, where data from 13 different types of loads is collected according to the IEC 62606 standard. To reduce inference time and optimize the algorithm for embedded control units, a feature reduction strategy is employed. The effectiveness of the proposed method is demonstrated through experimental tests conducted under both arcing and non-arcing conditions and across different load types. Moreover, its accuracy is also tested in case of transients caused by operational changes in common electrical appliances. Achieved results show a detection accuracy of approximately 99%, with appliance classification performance around 98%, with inference times ranging from 2.8 to 172.0 ms while executing the algorithm on an ARM Cortex-based board.
{"title":"Real-Time Series Arc Fault Detection and Appliances Classification in AC Networks Based on Competing Convolutional Kernels","authors":"Francesco Ferracuti;Riccardo Felicetti;Luca Cavanini;Patrick Schweitzer;Andrea Monteriù","doi":"10.1109/OJIES.2025.3582482","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3582482","url":null,"abstract":"This article presents a method to detect and classify series arc faults affecting domestic AC electrical circuits by the analysis of electric current time series data, based on the HYDRA (HYbrid Dictionary-Rocket Architecture) algorithm, a fast dictionary method for time series classification employing competing convolutional kernels. The key novel contributions are twofold: Competing convolutional kernels are suitable to effectively extract features representing an effective set of arc fault detection indicators, and the classification performed in this way is feasible to be executed in real time. The proposed method is validated using a public database, where data from 13 different types of loads is collected according to the IEC 62606 standard. To reduce inference time and optimize the algorithm for embedded control units, a feature reduction strategy is employed. The effectiveness of the proposed method is demonstrated through experimental tests conducted under both arcing and non-arcing conditions and across different load types. Moreover, its accuracy is also tested in case of transients caused by operational changes in common electrical appliances. Achieved results show a detection accuracy of approximately 99%, with appliance classification performance around 98%, with inference times ranging from 2.8 to 172.0 ms while executing the algorithm on an ARM Cortex-based board.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1050-1065"},"PeriodicalIF":5.2,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11048510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-19DOI: 10.1109/OJIES.2025.3581076
Carlos Resende;João Oliveira;Filipe Sousa;Waldir Moreira;Luis Almeida Sousa
Internet of Things (IoT) driven digitalization is shifting data processing to the edge, reducing the burden of constant cloud communication. Advances in resource-constrained microcontroller-based IoT devices that interact with the environment, such as in cyber-physical production systems, enable them to assist in computation offloading, extending edge computing into the so-called far-edge that includes such devices. However, updating these devices often requires manual interventions, full firmware updates, or proprietary tools, leading to potential application downtime. To fully leverage far-edge enhanced computing capabilities, it is crucial to integrate far-edge devices with cloud orchestration tools, streamlining service management and deployment along the cloud to the far-edge continuum. Current approaches overlook these devices’ computing power and their potential to host services, supporting IoT continuum orchestration only from the cloud to the edge. This article introduces far-edge IoT device management (FITA), the first platform that integrates far-edge devices into Kubernetes-based infrastructures. FITA provides a far-edge container-like solution compliant with the open container initiative. It extends Kubernetes to support service deployment on heterogeneous far-edge devices seamlessly and provides a method for creating virtual representations of far-edge devices to expose their unique capabilities to the Kubernetes scheduler. Our evaluation shows a mean deployment time on clusters with 500 services and 100 devices of around 600 ms, and a device registration time of around 1080 ms, with CPU and memory consumption of around 23 milicores and 1500 MB, respectively. Overall, FITA improves service continuity, deployment speed, and application resilience, supporting the future of the IoT, particularly in industry.
{"title":"Improving Far-Edge Device Management in IoT Applications Using Kubernetes","authors":"Carlos Resende;João Oliveira;Filipe Sousa;Waldir Moreira;Luis Almeida Sousa","doi":"10.1109/OJIES.2025.3581076","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3581076","url":null,"abstract":"Internet of Things (IoT) driven digitalization is shifting data processing to the edge, reducing the burden of constant cloud communication. Advances in resource-constrained microcontroller-based IoT devices that interact with the environment, such as in cyber-physical production systems, enable them to assist in computation offloading, extending edge computing into the so-called far-edge that includes such devices. However, updating these devices often requires manual interventions, full firmware updates, or proprietary tools, leading to potential application downtime. To fully leverage far-edge enhanced computing capabilities, it is crucial to integrate far-edge devices with cloud orchestration tools, streamlining service management and deployment along the cloud to the far-edge continuum. Current approaches overlook these devices’ computing power and their potential to host services, supporting IoT continuum orchestration only from the cloud to the edge. This article introduces far-edge IoT device management (FITA), the first platform that integrates far-edge devices into Kubernetes-based infrastructures. FITA provides a far-edge container-like solution compliant with the open container initiative. It extends Kubernetes to support service deployment on heterogeneous far-edge devices seamlessly and provides a method for creating virtual representations of far-edge devices to expose their unique capabilities to the Kubernetes scheduler. Our evaluation shows a mean deployment time on clusters with 500 services and 100 devices of around 600 ms, and a device registration time of around 1080 ms, with CPU and memory consumption of around 23 milicores and 1500 MB, respectively. Overall, FITA improves service continuity, deployment speed, and application resilience, supporting the future of the IoT, particularly in industry.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1027-1049"},"PeriodicalIF":5.2,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11044429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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