Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms

Yun, Jaeseok; Ahn, Il-Yeup; Song, JaeSeung; Kim, Jae-Ho

doi:10.3390/s19204567

Cited by 18 publications

(7 citation statements)

References 35 publications

(52 reference statements)

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“…Mobius and nCube are popular oneM2M platforms for servers and devices that have been extensively researched, developed, and applied in many industries. In [31], Yun et al developed middleware software based on the nCube platform to support different sensors and actuators. Sensor values and actuator commands are transformed into oneM2M resources by the nCube platform.…”

Section: Related Workmentioning

confidence: 99%

Enhanced Interoperating Mechanism Between OneM2M and OCF Platform Based on Rules Engine and Interworking Proxy in Heterogeneous IoT Networks

Tuấn

Kim

2023

IEEE Access

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In recent years, the Internet of Things (IoT) is growing rapidly and is being applied in a variety of industries including healthcare, smart homes, and smart cities. Many standard IoT platforms are proposed to connect and communicate with IoT devices easily and securely such as oneM2M, Google Weave and Apple HomeKit. However, this makes IoT application development difficult as it requires IoT devices and applications to support multiple protocols to connect different IoT platforms. Therefore, it is necessary to provide a consistent schema to support interoperability in heterogeneous IoT networks. In this paper, we propose how to design and implement interoperating schema between two edge servers oneM2M and Open Connectivity Foundation (OCF) with heterogeneous IoT devices. Specifically, we build proxies for bridging oneM2M Mobius edge server and OCF IoTivity edge server. The sensor data is collected from various IoT devices and sent to an edge server with a compatible platform. Next, the data stored in each server will be exchanged with the other server through a proposed interworking proxy. We also use a rules engine to automatically identify registered devices to support edge server interaction within the same domain and across domains. In addition, we build a web application in each edge server to provide friendly IoT services (data visualization) to clients from different environments. In order to evaluate our system, we collect the delay time of each process in the edge servers. The results show that our proposal is completely applicable in practice.

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Section: Related Workmentioning

confidence: 99%

Enhanced Interoperating Mechanism Between OneM2M and OCF Platform Based on Rules Engine and Interworking Proxy in Heterogeneous IoT Networks

Tuấn

Kim

2023

IEEE Access

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“…IoTivity is implemented through Open Connectivity Foundation (OCF) is an IoT standard specification including the definition of connectivity, management, functions, and security [38][39][40]. The oneM2M is another popular international IoT standard that includes all required functions for operating an IoT system in largescale environments based on a high-performance machine to provide the sufficient computing and data storage [41,42]. Therefore, oneM2M is not suitable for edge computing using constrained devices.…”

Section: Related Workmentioning

confidence: 99%

Decision-making of IoT device operation based on intelligent-task offloading for improving environmental optimization

Jin

Lim

Woo

et al. 2022

Complex Intell. Syst.

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Computation offloading enables intensive computational tasks to be separated into multiple computing resources for overcoming hardware limitations. Leveraging cloud computing, edge computing can be enabled to apply not only large-scale and personalized data but also intelligent algorithms based on offloading the intelligent models to high-performance servers for working with huge volumes of data in the cloud. In this paper, we propose a getaway-centric Internet of Things (IoT) system to enable the intelligent and autonomous operation of IoT devices in edge computing. In the proposed edge computing, IoT devices are operated by a decision-making model that selects an optimal control factor from multiple intelligent services and applies it to the device. The intelligent services are provided based on offloading multiple intelligent and optimization approaches to the intelligent service engine in the cloud. Therefore, the decision-making model in the gateway is enabled to select the best solution from the candidates. Also, the proposed IoT system provides monitoring and visualization to users through device management based on resource virtualization using the gateway. Furthermore, the gateway interprets scenario profiles to interact with intelligent services dynamically and apply the optimal control factor to the actual device through the virtual resource. For implementing the improved energy optimization using the proposed IoT system, we propose two intelligent models to learn parameters of a user’s residential environment using deep learning and derive the inference models to deploy in the intelligent service engine. The inference models are used for predicting a heater energy consumption that is applied to the heater. The heater updates the environment parameters to reach the user-desired values. Moreover, based on two energy consumption values, the decision-making model brings a smaller value to operate the heater to enable reducing the energy consumption as well as providing a user-desired environment.

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“…Jeong et al [24] developed a smart city platform for the collection and analysis of data to generate insights for solving smart city interoperability issues, especially at a data level. Yun et al [25] presented an implementation work of sensing and actuation capabilities for IoT devices using the OneM2M standard-based platforms. They mainly focused their study on the importance of a well-designed middleware solution compliant with the standard, providing a best practice for other platforms.…”

Section: Related Workmentioning

confidence: 99%

Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

Troscia

Sgambelluri

Paolucci

et al. 2022

Sensors

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Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

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Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms

Cited by 18 publications

References 35 publications

Enhanced Interoperating Mechanism Between OneM2M and OCF Platform Based on Rules Engine and Interworking Proxy in Heterogeneous IoT Networks

Enhanced Interoperating Mechanism Between OneM2M and OCF Platform Based on Rules Engine and Interworking Proxy in Heterogeneous IoT Networks

Decision-making of IoT device operation based on intelligent-task offloading for improving environmental optimization

Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

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