5bbd5a6e5d
- Fix datasource: bucket=smartcity, token=my-super-token, org=digitribe - Fix dashboard queries: filter by topic tag instead of _measurement (all data in measurement 'mqtt_consumer', type in tag 'topic') - Fix field names: temperature_c→temperature_celsius, luminosity→brightness_lux - Update dashboard to v3 with 15 panels (airquality, traffic, parking, weather, noise, light) - Update TODO.md and session_resume Tested: PM2.5 ✅, Temperature ✅, Vehicle Count ✅ via Grafana API
173 lines
8.4 KiB
JSON
173 lines
8.4 KiB
JSON
{
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"annotations": {"list": []},
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"editable": true,
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"fiscalYearStartMonth": 0,
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"graphTooltip": 0,
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"id": null,
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"links": [],
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"panels": [
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{
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"title": "Air Quality — PM2.5 (µg/m³)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/airquality/)\n |> filter(fn: (r) => r[\"_field\"] == \"pm25_ugm3\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 0}
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},
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{
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"title": "Air Quality — NO2 (µg/m³)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/airquality/)\n |> filter(fn: (r) => r[\"_field\"] == \"no2_ugm3\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 0}
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},
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{
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"title": "Temperature (°C)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"temperature_celsius\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 8}
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},
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{
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"title": "Humidity (%)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"humidity_percent\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 8}
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},
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{
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"title": "Wind Speed (km/h)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"wind_speed_kmh\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 16}
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},
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{
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"title": "Rain (mm)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"rain_mm\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 16}
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},
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{
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"title": "Traffic — Vehicle Count",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/traffic/)\n |> filter(fn: (r) => r[\"_field\"] == \"vehicle_count\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 24}
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},
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{
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"title": "Traffic — Avg Speed (km/h)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/traffic/)\n |> filter(fn: (r) => r[\"_field\"] == \"average_speed_kmh\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 24}
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},
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{
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"title": "Parking — Available Spots",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/parking/)\n |> filter(fn: (r) => r[\"_field\"] == \"available_spots\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 32}
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},
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{
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"title": "Parking — Occupancy (%)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/parking/)\n |> filter(fn: (r) => r[\"_field\"] == \"occupancy_percent\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 32}
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},
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{
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"title": "Noise Level (dB)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/noise/)\n |> filter(fn: (r) => r[\"_field\"] == \"noise_level_db\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 40}
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},
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{
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"title": "Light — Brightness (lux)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/light/)\n |> filter(fn: (r) => r[\"_field\"] == \"brightness_lux\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 40}
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},
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{
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"title": "UV Index",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"uv_index\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 48}
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},
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{
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"title": "Pressure (hPa)",
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"type": "timeseries",
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"datasource": {"type": "influxdb", "name": "Influxdb-v2"},
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"targets": [
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{
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"query": "from(bucket:\"smartcity\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"topic\"] =~ /smartcity\\/weather/)\n |> filter(fn: (r) => r[\"_field\"] == \"pressure_hpa\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")"
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}
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],
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 48}
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}
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],
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"schemaVersion": 36,
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"style": "dark",
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"tags": ["smartcity", "martinique", "iot"],
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"templating": {"list": []},
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"time": {"from": "now-1h", "to": "now"},
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"title": "Smart City Digital Twin — Martinique",
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"uid": "smartcity-martinique-v2",
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"version": 2
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}
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