MRA is a data file that describes the contents of “APPENDIX Detailed Requirements for ECHONET Device objects” in JSON format.
Please refer to the release notes for supported devices. MRAs are provided as JSON data, and a tool (MRAViewer) for viewing the contents of MRAs with a Web browser is available from Kanagawa Institute of Technology (KAIT). The Device Descriptions (DDs) of the ECHONET Lite Web APIs are created using MRA. This translation is done by using a tool (eDataModelsGen) provided by Japan Advanced Institute of Science and Technology (JAIST), which can automatically generate DDs from MRAs.
MRA Data version 1.3.0 (zipped) | MRA_en_v1.3.0.zip [zip 192KB] |
Release note version 1.3.0 (pdf) | MRA_releasenote_en_v1.3.0.pdf [PDF 128KB] |
Guidebook version 1.2.0 (pdf) | MRA_guidebook_en_v1.2.0.pdf [PDF 232KB] |
MRAViewer <provided by KAIT> | Link to GitHub |
MRA2DD convertor tool (eDataModelsGen) <provide by JAIST> |
Link to GitHub |
“APPENDIX Detailed Requirements for ECHONET Device objects” are defined as detailed specifications for the property structure of the specified classes for each device. In order to implement a program that operates a device or a controller, the developer usually extracts the necessary commands and parameters from the specifications published in PDF format, translates them into the messages on the ECHONET Lite communication stack, and codes them manually. In this case, the developer writes the necessary code by following the values in the property table with his eyes, which not only takes a lot of man-hours but also creates a situation where mistakes can easily occur. In order to avoid this situation, a format suitable for handling the contents of device object specifications electronically instead of manually allow the developer to build a more efficient coding environment.
We plan to update the MRA data when we update the DD. With your comments and feedback, we will continue to improve MRA to the data that is easier to use and more valuable.
This MRA was developed as part of a joint research project between KAIT, JAIST, and the ECHONET Consortium. We received many supports from Professor Isshiki of KAIT, Vice President Tan of JAIST, and other researchers throughout the development of the MRA. We would like to express our deepest gratitude to them.