MET has a collection of survey data provided by the Norwegian road administration. This data is primarily sampled from a selection of fjords in Sunnmøre in regards to the 'ferry-less' E39 road plan.
The data is stored in a common network common dataform (netCDF) format, which enables multidimensional variables. It is a widely used data format for scientific data. Every .nc file has a myriad of variables, all of which has descriptive meta-data.
Since it is difficult to publish multi-dimensional data through MQTT, some compromises have been made. For example, the measurement of salinity is stored and accessed with regards to both time and depth. I.e to get a value for salinity, depth and time must be provided. Time can be provided through timestamp, but depth has to be set to a static variable. In this case the depth is set to be always 5 meters.
The script called XarrayBuouData.py fetches every .nc file on MET buoy data section of E39 and parses through all variables and stores their keys in an array. A separate function handles connection and publishing through MQTT. Below is a code-snippet which shows how to select and publish a variable.
json_data = json.dumps(kwargs, indent=2)if 'adcp' in locationname:
publishMqtt(json_data,'acdcp')
elif 'aquadopp' in locationname:
publishMqtt(json_data,'aquadopp')
elif 'ctd' in locationname:
publishMqtt(json_data, 'ctd')
elif 'raw_wind' in locationname:
publishMqtt(json_data, 'raw')
elif 'wave' in locationname:
publishMqtt(json_data, 'wave')
elif 'wind' in locationname:
publishMqtt(json_data, 'wind')The 'adcp', 'aquadopp' and other tags makes sure the data gets sent to the correct data converter on Thingsboard.