Floor Plan Indoor Air Quality monitoring

(soon interactive)

Features

• Air Quality rendering
• Easy configuration and setup
• Interactive rooms
• Detailed charts of IAQ history.

Short description

Monitoring indoor air quality through floor plan visualization in Grafana using Flux query language allows for gaining valuable insights into the air quality of different areas within a building. By integrating sensors and data collection points throughout the building, Grafana can display real-time and historical air quality data on a floor plan layout. This enables users to easily identify areas with poor air quality and take appropriate actions to improve it, such as adjusting ventilation systems or implementing air purifiers. Overall, this approach enhances indoor air quality management and contributes to creating healthier and more comfortable environments for occupants.

The plugin finds rooms in the provided floor plan SVG by looking for prefix of room: (example: room:Living room) and in the future walls with the prefix of wall: (example: wall:south-east).

Public Dashboard Example

https://iaq.innorenew.eu/grafana/public-dashboards/535d826acc744109b4d64a68654ee262?orgId=1&refresh=5s

Required Data Example (CSV)

#group,false,false,false,false,false,true
#datatype,string,long,string,dateTime:RFC3339,string,string
#default,_result,,,,,
,result,table,_field,_time,_value,sensor_id
,,0,RH,2024-06-03T07:06:00Z,59.89,411
,,0,abs_humidity,2024-06-03T07:06:00Z,12.41,411
,,0,co2,2024-06-03T07:06:00Z,500.48,411
,,0,dew_point,2024-06-03T07:06:00Z,14.96,411
,,0,luminance,2024-06-03T07:06:00Z,40.43,411
,,0,temperature,2024-06-03T07:06:00Z,23.19,411
,,0,voc_eq_co2,2024-06-03T07:06:00Z,577.68,411
,,0,voc_index,2024-06-03T07:06:00Z,577.68,411
,,1,RH,2024-06-03T07:06:00Z,53.0938,ir-00
,,1,abs_humidity,2024-06-03T07:06:00Z,12.3588,ir-00
,,1,co2,2024-06-03T07:06:00Z,504.1678,ir-00
,,1,dew_point,2024-06-03T07:06:00Z,15.0008,ir-00
,,1,luminance,2024-06-03T07:06:00Z,297.5616,ir-00
,,1,temperature,2024-06-03T07:06:00Z,25.2382,ir-00
,,1,turned_on,2024-06-03T07:06:00Z,17091208,ir-00
,,1,voc_acc,2024-06-03T07:06:00Z,NULL,ir-00
,,1,voc_eq_co2,2024-06-03T07:06:00Z,665,ir-00
,,1,voc_index,2024-06-03T07:06:00Z,665,ir-00
,,2,RH,2024-06-03T07:06:00Z,47.0603,ir-01
,,2,abs_humidity,2024-06-03T07:06:00Z,11.5456,ir-01
,,2,co2,2024-06-03T07:06:00Z,419.7745,ir-01
,,2,dew_point,2024-06-03T07:06:00Z,13.9951,ir-01
,,2,luminance,2024-06-03T07:06:00Z,16.1856,ir-01
,,2,temperature,2024-06-03T07:06:00Z,26.1782,ir-01
,,2,turned_on,2024-06-03T07:06:00Z,19316144,ir-01
,,2,voc_acc,2024-06-03T07:06:00Z,NULL,ir-01
,,2,voc_eq_co2,2024-06-03T07:06:00Z,488,ir-01
,,2,voc_index,2024-06-03T07:06:00Z,488,ir-01
,,3,RH,2024-06-03T07:06:00Z,47.2755,ir-02
,,3,abs_humidity,2024-06-03T07:06:00Z,11.1204,ir-02
,,3,co2,2024-06-03T07:06:00Z,425.1092,ir-02
,,3,dew_point,2024-06-03T07:06:00Z,13.3786,ir-02
,,3,luminance,2024-06-03T07:06:00Z,0,ir-02
,,3,temperature,2024-06-03T07:06:00Z,25.4251,ir-02
,,3,turned_on,2024-06-03T07:06:00Z,12344016,ir-02
,,3,voc_acc,2024-06-03T07:06:00Z,NULL,ir-02
,,3,voc_eq_co2,2024-06-03T07:06:00Z,698,ir-02
,,3,voc_index,2024-06-03T07:06:00Z,698,ir-02
,,4,RH,2024-06-03T07:06:00Z,57.1145,ir-03
,,4,abs_humidity,2024-06-03T07:06:00Z,12.2462,ir-03
,,4,co2,2024-06-03T07:06:00Z,474.4346,ir-03
,,4,dew_point,2024-06-03T07:06:00Z,14.7826,ir-03
,,4,luminance,2024-06-03T07:06:00Z,36.288,ir-03
,,4,temperature,2024-06-03T07:06:00Z,23.7829,ir-03
,,4,turned_on,2024-06-03T07:06:00Z,1522037,ir-03
,,4,voc_acc,2024-06-03T07:06:00Z,NULL,ir-03
,,4,voc_eq_co2,2024-06-03T07:06:00Z,540,ir-03
,,4,voc_index,2024-06-03T07:06:00Z,540,ir-03
,,5,RH,2024-06-03T07:06:00Z,56.2478,ir-04
,,5,abs_humidity,2024-06-03T07:06:00Z,11.8319,ir-04
,,5,co2,2024-06-03T07:06:00Z,676.0902,ir-04
,,5,dew_point,2024-06-03T07:06:00Z,14.2318,ir-04
,,5,luminance,2024-06-03T07:06:00Z,26.8416,ir-04
,,5,temperature,2024-06-03T07:06:00Z,23.4464,ir-04
,,5,turned_on,2024-06-03T07:06:00Z,5754636,ir-04
,,5,voc_acc,2024-06-03T07:06:00Z,NULL,ir-04
,,5,voc_eq_co2,2024-06-03T07:06:00Z,431,ir-04
,,5,voc_index,2024-06-03T07:06:00Z,431,ir-04
,,6,RH,2024-06-03T07:06:00Z,63.9078,ir-06
,,6,abs_humidity,2024-06-03T07:06:00Z,12.1686,ir-06
,,6,co2,2024-06-03T07:06:00Z,431.7405,ir-06
,,6,dew_point,2024-06-03T07:06:00Z,14.5753,ir-06
,,6,luminance,2024-06-03T07:06:00Z,3.2832,ir-06
,,6,temperature,2024-06-03T07:06:00Z,21.708,ir-06
,,6,turned_on,2024-06-03T07:06:00Z,23495992,ir-06
,,6,voc_acc,2024-06-03T07:06:00Z,NULL,ir-06
,,6,voc_eq_co2,2024-06-03T07:06:00Z,457,ir-06
,,6,voc_index,2024-06-03T07:06:00Z,457,ir-06
,,7,RH,2024-06-03T07:06:00Z,57.4838,ir-07
,,7,abs_humidity,2024-06-03T07:06:00Z,11.7847,ir-07
,,7,co2,2024-06-03T07:06:00Z,433.5116,ir-07
,,7,dew_point,2024-06-03T07:06:00Z,14.1465,ir-07
,,7,luminance,2024-06-03T07:06:00Z,5.3568,ir-07
,,7,temperature,2024-06-03T07:06:00Z,22.9951,ir-07
,,7,turned_on,2024-06-03T07:06:00Z,19316228,ir-07
,,7,voc_acc,2024-06-03T07:06:00Z,NULL,ir-07
,,7,voc_eq_co2,2024-06-03T07:06:00Z,464,ir-07
,,7,voc_index,2024-06-03T07:06:00Z,464,ir-07

Data should be grouped as

<sensor_id, <_field, _time, _value, sensor_id>>

A flux example query would be

from(bucket: "iaq")
  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
  |> filter(fn: (r) => r["_measurement"] == "iaq_data")
  |> map(fn: (r) => ({r with _value: string(v:r._value)}))
  |> truncateTimeColumn(unit: 2m)
  |> last()
  |> group(columns: ["sensor_id"])
  |> drop(columns: ["_start", "_stop", "_measurement", "building"])

Sample Floor plan SVG Data

https://github.com/InnoRenew-CoE/grafana-floor-panel/blob/main/floor_plan.svg

Note:

The plugin is not yet signed and is not available through the grafana store.