Towards Automated Generation of Data Models for the ECHONET Lite Protocol
Van Cu Pham, Yasuo Tan · 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) · 2021
Providing data models is essential for any protocol or standard to achieve cooperation with other ecosystems. This paper proposes a solution to save human efforts from tedious, repetitive, and easy-to-make mistake tasks when creating data models from the standardized ECHONET device objects. The proposed solution was able to generate data models such as device description for the ECHONET Lite web API, thing description schemes for the ECHONET Lite-Web of things integration, and the SAREF extended ontology for ECHONET Lite. Other data models and open API documents for each data model could be easily generated by simply adding more conversion rules. Generated data models have matched the requirements of human-generated data models. This solution is utilizing in a workflow to create the data model for the ECHONET Lite web API.