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On April 28, 2023 at 4:56:13 PM +0200, Gravatar Mathieu Ronkes Agerbeek:
  • Updated description of Water quality data from Talkpool sensor from

    # Introduction Talkpool installed water quality sensors measuring temperature, conductivity, pH and turbidity in recipients receiving wast water from construction sites to be able to monitor the influence of waste water from construction sites on water quality in those recipients. Sensors are installed both upstream and downstream from the discharge point to be able to measure the effect of the waste water. The sensors publish their data using a MQTT queue. The SCOREwater platform is subscribed to this MQTT queue and stores the data in its time series database as it comes in. Using a database view the data is converted to the WaterQualityObserved Smart Data Model before being published using different API's. For a record to be published a location of the sensor and a scale and offset factor is needed to be able to convert the incoming raw data to actual conductivity, pH and turbidity information. # Contents of the data Data are being harmonized using FIWARE [Smart Data Models](https://www.fiware.org/smart-data-models/). Data regarding water quality can be harmonized using the WaterQualityObserved data model The data in this dataset provide the following elements from this data model: * id - identifier of the sensors * recordingTimetamp - timestamp of the measurement * location - GPS location of the sensor, GeoJSON with WGS84/EPSG:4326 coordinate * temperature - temperature in degrees Celsius * conductivity - * ph - * turbidity
    to
    # Introduction Talkpool installed water quality sensors measuring temperature, conductivity, pH and turbidity in recipients receiving waste water from construction sites to be able to monitor the influence of waste water from construction sites on water quality in those recipients. Sensors are installed both upstream and downstream from the discharge point to be able to measure the effect of the waste water. The sensors publish their data using a MQTT queue. The SCOREwater platform is subscribed to this MQTT queue and stores the data in its time series database as it comes in. Using a database view the data is converted to the WaterQualityObserved Smart Data Model before being published using different API's. For a record to be published a location of the sensor and a scale and offset factor is needed to be able to convert the incoming raw data to actual conductivity, pH and turbidity information. # Contents of the data Data are being harmonized using FIWARE [Smart Data Models](https://www.fiware.org/smart-data-models/). Data regarding water quality can be harmonized using the WaterQualityObserved data model The data in this dataset provide the following elements from this data model: * id - identifier of the sensors * recordingTimetamp - timestamp of the measurement * location - GPS location of the sensor, GeoJSON with WGS84/EPSG:4326 coordinate * temperature - temperature in degrees Celsius * conductivity - * ph - * turbidity