An Ontology-driven ECHONET Lite Adaptation Layer for Smart Homes

Pham, Van Cu; Lim, Yuto; Sgorbissa, Antonio; Tan, Yasuo

doi:10.2197/ipsjjip.27.360

Cited by 9 publications

(2 citation statements)

References 13 publications

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“…The data model for the ELWA, namely Device Description, is located above the Management Platform layer. In [10], an ontology-based data model was introduced at the Home Gateway layer. The proposed data model supports the ECHONET device objects specification (release K) and ambient assisted living platform [11].…”

Section: Related Workmentioning

confidence: 99%

Automated Data Model Generation From Textual Specifications: A Case Study of ECHONET Lite Specification

Pham,

Linh,

et al. 2023

IEEE Access

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Section: Related Workmentioning

confidence: 99%

Automated Data Model Generation From Textual Specifications: A Case Study of ECHONET Lite Specification

Pham,

Linh,

et al. 2023

IEEE Access

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“…In Ref. [24], an adaptation layer that provides the network abstraction for the ECHONET Lite protocol has been implemented (Fig. 3 (b)).…”

Section: Managementmentioning

confidence: 99%

IoT Area Network Simulator For Network Dataset Generation

Pham

Matsuo

Pho

et al. 2020

Journal of Information Processing

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With the development of information and communication technology (ICT), smart home technologies are expecting to be a potential solution for the population aging problem. Smart home simulators and testbeds have been introduced to provide materials for researchers in the field of ambient assisted living to develop and evaluate their solutions. Since simulators reduce costs in terms of money and time, researchers are utilizing simulators to expand services to enhance user comfort, save energy, and detect abnormal behaviors in daily living activities, etc. However, available smart home simulators seem to focus on the operational aspects of simulated devices and environments. The network communication aspects have not been fulfilled so far. Following the development of the Internet of Things, smart home networks are more complex, and users in the smart home are ordinary people without knowledge about network management. Therefore, intelligent operation, administration, and maintenance (OAM) services for smart homes are desired. This paper proposes a smart home network simulator to generate a network dataset of a home network, which is essential to develop machine learning technologies for providing intelligent OAM services in smart homes. The simulator is implemented based on ECHONET Lite, a leading smart home protocol in Japan.

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