The protocol is the foundation of IoT technology, which plays an important role in the IoT device interworking and interoperability. The 5 G wireless communication system provides large-scale NB-IoT terminals access w...The protocol is the foundation of IoT technology, which plays an important role in the IoT device interworking and interoperability. The 5 G wireless communication system provides large-scale NB-IoT terminals access with F-RAN, and the vertical industry applications need support for the device management. As one of the most influential protocol in the IoT application, the oneM2M protocol not only has a complete architecture, but also has an interface with other IoT protocols. Therefore, to bridge the gap between the operator and industrial enterprises, the main contributions of this paper are as follows: Firstly, a general multi-protocol conversion method is proposed based on oneM2M platform where the protocol classification is used in different scenarios. Secondly, the F-RAN architecture of oneM2M platform is designed and implemented with NB-IoT device access. Thirdly, a multiplexing scheme to process the device information is proposed for interworking proxy entity(IPE), which improves the conversion efficiency for different protocols. Finally, the feasibility and efficiency of the scheme are verified.展开更多
There have been numerous works proposed to merge augmented reality/mixed reality(AR/MR)and Internet of Things(IoT)in various ways.However,they have focused on their specific target applications and have limitations on...There have been numerous works proposed to merge augmented reality/mixed reality(AR/MR)and Internet of Things(IoT)in various ways.However,they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system.This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services.The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific systems,domains,and device manufacturers.We implement the proposed architecture utilizing the open-source oneM2M-based IoT server and device platforms released by the open alliance for IoT standards(OCEAN)and Microsoft HoloLens as an MR device platform.We also suggest and demonstrate the practical use cases and discuss the advantages of the proposed architecture.展开更多
In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial domain.Due to the divergence of IoT solutions,the industry is faced with a need t...In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial domain.Due to the divergence of IoT solutions,the industry is faced with a need to apply various technologies for automation and control.This fact leads to a demand for an establishing interworking mechanism which would allow smooth interoperability between heterogeneous devices.One of the major protocols widely used today in industrial electronic devices is Modbus.However,data generated by Modbus devices cannot be understood by IoT applications using different protocols,so it should be applied in a couple with an IoT service layer platform.oneM2M,a global IoT standard,can play the role of interconnecting various protocols,as it provides flexible tools suitable for building an interworking framework for industrial services.Therefore,in this paper,we propose an interworking architecture between devices working on the Modbus protocol and an IoT platform implemented based on oneM2M standards.In the proposed architecture,we introduce the way to model Modbus data as oneM2M resources,rules to map them to each other,procedures required to establish interoperable communication,and optimization methods for this architecture.We analyze our solution and provide an evaluation by implementing it based on a solar power management use case.The results demonstrate that our model is feasible and can be applied to real case scenarios.展开更多
In social science,health care,digital therapeutics,etc.,smartphone data have played important roles to infer users’daily lives.However,smartphone data col-lection systems could not be used effectively and widely beca...In social science,health care,digital therapeutics,etc.,smartphone data have played important roles to infer users’daily lives.However,smartphone data col-lection systems could not be used effectively and widely because they did not exploit any Internet of Things(IoT)standards(e.g.,oneM2M)and class labeling methods for machine learning(ML)services.Therefore,in this paper,we propose a novel Android IoT lifelog system complying with oneM2M standards to collect various lifelog data in smartphones and provide two manual and automated class labeling methods for inference of users’daily lives.The proposed system consists of an Android IoT client application,an oneM2M-compliant IoT server,and an ML server whose high-level functional architecture was carefully designed to be open,accessible,and internation-ally recognized in accordance with the oneM2M standards.In particular,we explain implementation details of activity diagrams for the Android IoT client application,the primary component of the proposed system.Experimental results verified that this application could work with the oneM2M-compliant IoT server normally and provide corresponding class labels properly.As an application of the proposed system,we also propose motion inference based on three multi-class ML classifiers(i.e.,k nearest neighbors,Naive Bayes,and support vector machine)which were created by using only motion and location data(i.e.,acceleration force,gyroscope rate of rotation,and speed)and motion class labels(i.e.,driving,cycling,running,walking,and stil-ling).When compared with confusion matrices of the ML classifiers,the k nearest neighbors classifier outperformed the other two overall.Furthermore,we evaluated its output quality by analyzing the receiver operating characteristic(ROC)curves with area under the curve(AUC)values.The AUC values of the ROC curves for all motion classes were more than 0.9,and the macro-average and micro-average ROC curves achieved very high AUC values of 0.96 and 0.99,respectively.展开更多
Edge computing is swiftly gaining traction and is being standardised by the European Telecommunications Standards Institute(ETSI)as Multi-access Edge Computing(MEC).Simultaneously,oneM2M has been actively developing s...Edge computing is swiftly gaining traction and is being standardised by the European Telecommunications Standards Institute(ETSI)as Multi-access Edge Computing(MEC).Simultaneously,oneM2M has been actively developing standards for dynamic data management and IoT services at the edge,particularly for applications that require real-time support and security.Integrating MEC and oneM2M offers a unique opportunity to maximize their individual strengths.Therefore,this article proposes a framework that integrates MEC and oneM2M standard platforms for IoT applications,demonstrating how the synergy of these architectures can leverage the geographically distributed computing resources at base stations,enabling efficient deployment and added value for time-sensitive IoT applications.In addition,this study offers a concept of potential interworking models between oneM2M and the MEC architectures.The adoption of these standard architectures can enable various IoT edge services,such as smart city mobility and real-time analytics functions,by leveraging the oneM2M common service layer instantiated on the MEC host.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(2019PTB-017)
文摘The protocol is the foundation of IoT technology, which plays an important role in the IoT device interworking and interoperability. The 5 G wireless communication system provides large-scale NB-IoT terminals access with F-RAN, and the vertical industry applications need support for the device management. As one of the most influential protocol in the IoT application, the oneM2M protocol not only has a complete architecture, but also has an interface with other IoT protocols. Therefore, to bridge the gap between the operator and industrial enterprises, the main contributions of this paper are as follows: Firstly, a general multi-protocol conversion method is proposed based on oneM2M platform where the protocol classification is used in different scenarios. Secondly, the F-RAN architecture of oneM2M platform is designed and implemented with NB-IoT device access. Thirdly, a multiplexing scheme to process the device information is proposed for interworking proxy entity(IPE), which improves the conversion efficiency for different protocols. Finally, the feasibility and efficiency of the scheme are verified.
基金This research was supported by MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2021-2018-0-01431)the High-Potential Individuals Global Training Program(2019-0-01611)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘There have been numerous works proposed to merge augmented reality/mixed reality(AR/MR)and Internet of Things(IoT)in various ways.However,they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system.This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services.The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific systems,domains,and device manufacturers.We implement the proposed architecture utilizing the open-source oneM2M-based IoT server and device platforms released by the open alliance for IoT standards(OCEAN)and Microsoft HoloLens as an MR device platform.We also suggest and demonstrate the practical use cases and discuss the advantages of the proposed architecture.
基金the support of the Korea Research Foundation with the funding of the Ministry of Science and Information and Communication Technology(No.2018-0-88457,development of translucent solar cells and Internet of Things technology for Solar Signage).
文摘In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial domain.Due to the divergence of IoT solutions,the industry is faced with a need to apply various technologies for automation and control.This fact leads to a demand for an establishing interworking mechanism which would allow smooth interoperability between heterogeneous devices.One of the major protocols widely used today in industrial electronic devices is Modbus.However,data generated by Modbus devices cannot be understood by IoT applications using different protocols,so it should be applied in a couple with an IoT service layer platform.oneM2M,a global IoT standard,can play the role of interconnecting various protocols,as it provides flexible tools suitable for building an interworking framework for industrial services.Therefore,in this paper,we propose an interworking architecture between devices working on the Modbus protocol and an IoT platform implemented based on oneM2M standards.In the proposed architecture,we introduce the way to model Modbus data as oneM2M resources,rules to map them to each other,procedures required to establish interoperable communication,and optimization methods for this architecture.We analyze our solution and provide an evaluation by implementing it based on a solar power management use case.The results demonstrate that our model is feasible and can be applied to real case scenarios.
文摘In social science,health care,digital therapeutics,etc.,smartphone data have played important roles to infer users’daily lives.However,smartphone data col-lection systems could not be used effectively and widely because they did not exploit any Internet of Things(IoT)standards(e.g.,oneM2M)and class labeling methods for machine learning(ML)services.Therefore,in this paper,we propose a novel Android IoT lifelog system complying with oneM2M standards to collect various lifelog data in smartphones and provide two manual and automated class labeling methods for inference of users’daily lives.The proposed system consists of an Android IoT client application,an oneM2M-compliant IoT server,and an ML server whose high-level functional architecture was carefully designed to be open,accessible,and internation-ally recognized in accordance with the oneM2M standards.In particular,we explain implementation details of activity diagrams for the Android IoT client application,the primary component of the proposed system.Experimental results verified that this application could work with the oneM2M-compliant IoT server normally and provide corresponding class labels properly.As an application of the proposed system,we also propose motion inference based on three multi-class ML classifiers(i.e.,k nearest neighbors,Naive Bayes,and support vector machine)which were created by using only motion and location data(i.e.,acceleration force,gyroscope rate of rotation,and speed)and motion class labels(i.e.,driving,cycling,running,walking,and stil-ling).When compared with confusion matrices of the ML classifiers,the k nearest neighbors classifier outperformed the other two overall.Furthermore,we evaluated its output quality by analyzing the receiver operating characteristic(ROC)curves with area under the curve(AUC)values.The AUC values of the ROC curves for all motion classes were more than 0.9,and the macro-average and micro-average ROC curves achieved very high AUC values of 0.96 and 0.99,respectively.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)-Information Technology Research Center(ITRC)grant funded by the Korea government(IITP-2025-RS-2021-II211816)supported by the National Research Foundation of Korea(NRF)grant(NRF-2023R1A2C1004453)+3 种基金funded by the European Union’s HORIZON-JUSNS-2023 HE research and innovation program(6G-Path project,Grant No.101139172)the Horizon 2020 Research and Innovation Program(aerOS project,Grant No.101069732)supported by the ESTIMED project,conducted by the ETSI Specialist Task Force 685(STF 685)funded by the European Commission(EC)and the European Free Trade Association(EFTA).
文摘Edge computing is swiftly gaining traction and is being standardised by the European Telecommunications Standards Institute(ETSI)as Multi-access Edge Computing(MEC).Simultaneously,oneM2M has been actively developing standards for dynamic data management and IoT services at the edge,particularly for applications that require real-time support and security.Integrating MEC and oneM2M offers a unique opportunity to maximize their individual strengths.Therefore,this article proposes a framework that integrates MEC and oneM2M standard platforms for IoT applications,demonstrating how the synergy of these architectures can leverage the geographically distributed computing resources at base stations,enabling efficient deployment and added value for time-sensitive IoT applications.In addition,this study offers a concept of potential interworking models between oneM2M and the MEC architectures.The adoption of these standard architectures can enable various IoT edge services,such as smart city mobility and real-time analytics functions,by leveraging the oneM2M common service layer instantiated on the MEC host.
