mirror of
https://github.com/SyncrowIOT/backend.git
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Merge branch 'dev'
This commit is contained in:
faris Aljohari
+39
@@ -0,0 +1,39 @@
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WITH params AS (
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SELECT
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$1::uuid AS space_uuid,
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TO_DATE(NULLIF($2, ''), 'YYYY-MM') AS event_month
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)
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SELECT
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sdp.space_uuid,
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sdp.event_date,
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sdp.good_aqi_percentage, sdp.moderate_aqi_percentage, sdp.unhealthy_sensitive_aqi_percentage, sdp.unhealthy_aqi_percentage,
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sdp.very_unhealthy_aqi_percentage, sdp.hazardous_aqi_percentage,
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sdp.daily_avg_aqi, sdp.daily_max_aqi, sdp.daily_min_aqi,
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sdp.good_pm25_percentage, sdp.moderate_pm25_percentage, sdp.unhealthy_sensitive_pm25_percentage, sdp.unhealthy_pm25_percentage,
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sdp.very_unhealthy_pm25_percentage, sdp.hazardous_pm25_percentage,
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sdp.daily_avg_pm25, sdp.daily_max_pm25, sdp.daily_min_pm25,
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sdp.good_pm10_percentage, sdp.moderate_pm10_percentage, sdp.unhealthy_sensitive_pm10_percentage, sdp.unhealthy_pm10_percentage,
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sdp.very_unhealthy_pm10_percentage, sdp.hazardous_pm10_percentage,
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sdp.daily_avg_pm10, sdp.daily_max_pm10, sdp.daily_min_pm10,
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sdp.good_voc_percentage, sdp.moderate_voc_percentage, sdp.unhealthy_sensitive_voc_percentage, sdp.unhealthy_voc_percentage,
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sdp.very_unhealthy_voc_percentage, sdp.hazardous_voc_percentage,
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sdp.daily_avg_voc, sdp.daily_max_voc, sdp.daily_min_voc,
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sdp.good_co2_percentage, sdp.moderate_co2_percentage, sdp.unhealthy_sensitive_co2_percentage, sdp.unhealthy_co2_percentage,
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sdp.very_unhealthy_co2_percentage, sdp.hazardous_co2_percentage,
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sdp.daily_avg_co2, sdp.daily_max_co2, sdp.daily_min_co2,
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sdp.good_ch2o_percentage, sdp.moderate_ch2o_percentage, sdp.unhealthy_sensitive_ch2o_percentage, sdp.unhealthy_ch2o_percentage,
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sdp.very_unhealthy_ch2o_percentage, sdp.hazardous_ch2o_percentage,
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sdp.daily_avg_ch2o, sdp.daily_max_ch2o, sdp.daily_min_ch2o
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FROM public."space-daily-pollutant-stats" AS sdp
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CROSS JOIN params p
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WHERE
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(p.space_uuid IS NULL OR sdp.space_uuid = p.space_uuid)
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AND (p.event_month IS NULL OR TO_CHAR(sdp.event_date, 'YYYY-MM') = TO_CHAR(p.event_month, 'YYYY-MM'))
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ORDER BY sdp.space_uuid, sdp.event_date;
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+374
@@ -0,0 +1,374 @@
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WITH params AS (
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SELECT
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TO_DATE(NULLIF($1, ''), 'YYYY-MM-DD') AS event_date,
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$2::uuid AS space_id
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),
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-- Query Pipeline Starts Here
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device_space AS (
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SELECT
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device.uuid AS device_id,
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device.space_device_uuid AS space_id,
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"device-status-log".event_time::timestamp AS event_time,
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"device-status-log".code,
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"device-status-log".value
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FROM device
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LEFT JOIN "device-status-log"
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ON device.uuid = "device-status-log".device_id
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LEFT JOIN product
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ON product.uuid = device.product_device_uuid
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WHERE product.cat_name = 'hjjcy'
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),
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average_pollutants AS (
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SELECT
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event_time::date AS event_date,
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date_trunc('hour', event_time) AS event_hour,
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space_id,
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-- PM1
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MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
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AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
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MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
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-- PM25
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MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
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AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
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MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
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-- PM10
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MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
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AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
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MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
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-- VOC
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MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
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AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
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MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
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-- CH2O
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MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
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AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
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MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
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-- CO2
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MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
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AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
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MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
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FROM device_space
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GROUP BY space_id, event_hour, event_date
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),
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filled_pollutants AS (
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SELECT
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*,
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-- AVG
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COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_avg_f,
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COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_avg_f,
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COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_avg_f,
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COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_avg_f,
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COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_avg_f,
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-- MIN
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COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_min_f,
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COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_min_f,
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COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_min_f,
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COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_min_f,
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COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_min_f,
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-- MAX
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COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_max_f,
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COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_max_f,
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COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_max_f,
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COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_max_f,
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COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_max_f
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FROM average_pollutants
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),
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hourly_results AS (
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SELECT
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space_id,
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event_date,
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event_hour,
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pm1_min, pm1_avg, pm1_max,
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pm25_min_f, pm25_avg_f, pm25_max_f,
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pm10_min_f, pm10_avg_f, pm10_max_f,
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voc_min_f, voc_avg_f, voc_max_f,
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co2_min_f, co2_avg_f, co2_max_f,
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ch2o_min_f, ch2o_avg_f, ch2o_max_f,
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GREATEST(
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calculate_aqi('pm25', pm25_min_f),
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calculate_aqi('pm10', pm10_min_f)
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) AS hourly_min_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_avg_f),
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calculate_aqi('pm10', pm10_avg_f)
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) AS hourly_avg_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_max_f),
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calculate_aqi('pm10', pm10_max_f)
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) AS hourly_max_aqi,
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classify_aqi(GREATEST(
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calculate_aqi('pm25', pm25_avg_f),
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calculate_aqi('pm10', pm10_avg_f)
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)) AS aqi_category,
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classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
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classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
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classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
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classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
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classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
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FROM filled_pollutants
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),
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daily_category_counts AS (
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SELECT space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, aqi_category
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UNION ALL
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SELECT space_id, event_date, pm25_category AS category, 'pm25' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, pm25_category
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UNION ALL
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SELECT space_id, event_date, pm10_category AS category, 'pm10' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, pm10_category
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UNION ALL
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SELECT space_id, event_date, voc_category AS category, 'voc' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, voc_category
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UNION ALL
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SELECT space_id, event_date, co2_category AS category, 'co2' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, co2_category
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UNION ALL
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SELECT space_id, event_date, ch2o_category AS category, 'ch2o' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, ch2o_category
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),
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daily_totals AS (
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SELECT
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space_id,
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event_date,
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SUM(category_count) AS total_count
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FROM daily_category_counts
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where pollutant = 'aqi'
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GROUP BY space_id, event_date
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),
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-- Pivot Categories into Columns
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daily_percentages AS (
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select
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dt.space_id,
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dt.event_date,
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-- AQI CATEGORIES
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_aqi_percentage,
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-- PM25 CATEGORIES
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm25_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm25_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm25_percentage,
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||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm25_percentage,
|
||||
-- PM10 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm10_percentage,
|
||||
-- VOC CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_voc_percentage,
|
||||
-- CO2 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_co2_percentage,
|
||||
-- CH20 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_ch2o_percentage
|
||||
FROM daily_totals dt
|
||||
LEFT JOIN daily_category_counts dcc
|
||||
ON dt.space_id = dcc.space_id AND dt.event_date = dcc.event_date
|
||||
GROUP BY dt.space_id, dt.event_date, dt.total_count
|
||||
),
|
||||
|
||||
daily_averages AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
-- AQI
|
||||
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi,
|
||||
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
|
||||
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
|
||||
-- PM25
|
||||
ROUND(AVG(pm25_min_f)::numeric, 2) AS daily_min_pm25,
|
||||
ROUND(AVG(pm25_avg_f)::numeric, 2) AS daily_avg_pm25,
|
||||
ROUND(AVG(pm25_max_f)::numeric, 2) AS daily_max_pm25,
|
||||
-- PM10
|
||||
ROUND(AVG(pm10_min_f)::numeric, 2) AS daily_min_pm10,
|
||||
ROUND(AVG(pm10_avg_f)::numeric, 2) AS daily_avg_pm10,
|
||||
ROUND(AVG(pm10_max_f)::numeric, 2) AS daily_max_pm10,
|
||||
-- VOC
|
||||
ROUND(AVG(voc_min_f)::numeric, 2) AS daily_min_voc,
|
||||
ROUND(AVG(voc_avg_f)::numeric, 2) AS daily_avg_voc,
|
||||
ROUND(AVG(voc_max_f)::numeric, 2) AS daily_max_voc,
|
||||
-- CO2
|
||||
ROUND(AVG(co2_min_f)::numeric, 2) AS daily_min_co2,
|
||||
ROUND(AVG(co2_avg_f)::numeric, 2) AS daily_avg_co2,
|
||||
ROUND(AVG(co2_max_f)::numeric, 2) AS daily_max_co2,
|
||||
-- CH2O
|
||||
ROUND(AVG(ch2o_min_f)::numeric, 2) AS daily_min_ch2o,
|
||||
ROUND(AVG(ch2o_avg_f)::numeric, 2) AS daily_avg_ch2o,
|
||||
ROUND(AVG(ch2o_max_f)::numeric, 2) AS daily_max_ch2o
|
||||
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
final_data as(
|
||||
SELECT
|
||||
p.space_id,
|
||||
p.event_date,
|
||||
p.good_aqi_percentage, p.moderate_aqi_percentage, p.unhealthy_sensitive_aqi_percentage, p.unhealthy_aqi_percentage, p.very_unhealthy_aqi_percentage, p.hazardous_aqi_percentage,
|
||||
a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
|
||||
p.good_pm25_percentage, p.moderate_pm25_percentage, p.unhealthy_sensitive_pm25_percentage, p.unhealthy_pm25_percentage, p.very_unhealthy_pm25_percentage, p.hazardous_pm25_percentage,
|
||||
a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
|
||||
p.good_pm10_percentage, p.moderate_pm10_percentage, p.unhealthy_sensitive_pm10_percentage, p.unhealthy_pm10_percentage, p.very_unhealthy_pm10_percentage, p.hazardous_pm10_percentage,
|
||||
a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
|
||||
p.good_voc_percentage, p.moderate_voc_percentage, p.unhealthy_sensitive_voc_percentage, p.unhealthy_voc_percentage, p.very_unhealthy_voc_percentage, p.hazardous_voc_percentage,
|
||||
a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
|
||||
p.good_co2_percentage, p.moderate_co2_percentage, p.unhealthy_sensitive_co2_percentage, p.unhealthy_co2_percentage, p.very_unhealthy_co2_percentage, p.hazardous_co2_percentage,
|
||||
a.daily_avg_co2,a.daily_max_co2, a.daily_min_co2,
|
||||
p.good_ch2o_percentage, p.moderate_ch2o_percentage, p.unhealthy_sensitive_ch2o_percentage, p.unhealthy_ch2o_percentage, p.very_unhealthy_ch2o_percentage, p.hazardous_ch2o_percentage,
|
||||
a.daily_avg_ch2o,a.daily_max_ch2o, a.daily_min_ch2o
|
||||
FROM daily_percentages p
|
||||
LEFT JOIN daily_averages a
|
||||
ON p.space_id = a.space_id AND p.event_date = a.event_date
|
||||
ORDER BY p.space_id, p.event_date)
|
||||
|
||||
|
||||
INSERT INTO public."space-daily-pollutant-stats" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
good_aqi_percentage, moderate_aqi_percentage, unhealthy_sensitive_aqi_percentage, unhealthy_aqi_percentage, very_unhealthy_aqi_percentage, hazardous_aqi_percentage,
|
||||
daily_avg_aqi, daily_max_aqi, daily_min_aqi,
|
||||
good_pm25_percentage, moderate_pm25_percentage, unhealthy_sensitive_pm25_percentage, unhealthy_pm25_percentage, very_unhealthy_pm25_percentage, hazardous_pm25_percentage,
|
||||
daily_avg_pm25, daily_max_pm25, daily_min_pm25,
|
||||
good_pm10_percentage, moderate_pm10_percentage, unhealthy_sensitive_pm10_percentage, unhealthy_pm10_percentage, very_unhealthy_pm10_percentage, hazardous_pm10_percentage,
|
||||
daily_avg_pm10, daily_max_pm10, daily_min_pm10,
|
||||
good_voc_percentage, moderate_voc_percentage, unhealthy_sensitive_voc_percentage, unhealthy_voc_percentage, very_unhealthy_voc_percentage, hazardous_voc_percentage,
|
||||
daily_avg_voc, daily_max_voc, daily_min_voc,
|
||||
good_co2_percentage, moderate_co2_percentage, unhealthy_sensitive_co2_percentage, unhealthy_co2_percentage, very_unhealthy_co2_percentage, hazardous_co2_percentage,
|
||||
daily_avg_co2, daily_max_co2, daily_min_co2,
|
||||
good_ch2o_percentage, moderate_ch2o_percentage, unhealthy_sensitive_ch2o_percentage, unhealthy_ch2o_percentage, very_unhealthy_ch2o_percentage, hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o, daily_max_ch2o, daily_min_ch2o
|
||||
)
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
good_aqi_percentage, moderate_aqi_percentage, unhealthy_sensitive_aqi_percentage, unhealthy_aqi_percentage, very_unhealthy_aqi_percentage, hazardous_aqi_percentage,
|
||||
daily_avg_aqi, daily_max_aqi, daily_min_aqi,
|
||||
good_pm25_percentage, moderate_pm25_percentage, unhealthy_sensitive_pm25_percentage, unhealthy_pm25_percentage, very_unhealthy_pm25_percentage, hazardous_pm25_percentage,
|
||||
daily_avg_pm25, daily_max_pm25, daily_min_pm25,
|
||||
good_pm10_percentage, moderate_pm10_percentage, unhealthy_sensitive_pm10_percentage, unhealthy_pm10_percentage, very_unhealthy_pm10_percentage, hazardous_pm10_percentage,
|
||||
daily_avg_pm10, daily_max_pm10, daily_min_pm10,
|
||||
good_voc_percentage, moderate_voc_percentage, unhealthy_sensitive_voc_percentage, unhealthy_voc_percentage, very_unhealthy_voc_percentage, hazardous_voc_percentage,
|
||||
daily_avg_voc, daily_max_voc, daily_min_voc,
|
||||
good_co2_percentage, moderate_co2_percentage, unhealthy_sensitive_co2_percentage, unhealthy_co2_percentage, very_unhealthy_co2_percentage, hazardous_co2_percentage,
|
||||
daily_avg_co2, daily_max_co2, daily_min_co2,
|
||||
good_ch2o_percentage, moderate_ch2o_percentage, unhealthy_sensitive_ch2o_percentage, unhealthy_ch2o_percentage, very_unhealthy_ch2o_percentage, hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o, daily_max_ch2o, daily_min_ch2o
|
||||
FROM final_data
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
good_aqi_percentage = EXCLUDED.good_aqi_percentage,
|
||||
moderate_aqi_percentage = EXCLUDED.moderate_aqi_percentage,
|
||||
unhealthy_sensitive_aqi_percentage = EXCLUDED.unhealthy_sensitive_aqi_percentage,
|
||||
unhealthy_aqi_percentage = EXCLUDED.unhealthy_aqi_percentage,
|
||||
very_unhealthy_aqi_percentage = EXCLUDED.very_unhealthy_aqi_percentage,
|
||||
hazardous_aqi_percentage = EXCLUDED.hazardous_aqi_percentage,
|
||||
daily_avg_aqi = EXCLUDED.daily_avg_aqi,
|
||||
daily_max_aqi = EXCLUDED.daily_max_aqi,
|
||||
daily_min_aqi = EXCLUDED.daily_min_aqi,
|
||||
good_pm25_percentage = EXCLUDED.good_pm25_percentage,
|
||||
moderate_pm25_percentage = EXCLUDED.moderate_pm25_percentage,
|
||||
unhealthy_sensitive_pm25_percentage = EXCLUDED.unhealthy_sensitive_pm25_percentage,
|
||||
unhealthy_pm25_percentage = EXCLUDED.unhealthy_pm25_percentage,
|
||||
very_unhealthy_pm25_percentage = EXCLUDED.very_unhealthy_pm25_percentage,
|
||||
hazardous_pm25_percentage = EXCLUDED.hazardous_pm25_percentage,
|
||||
daily_avg_pm25 = EXCLUDED.daily_avg_pm25,
|
||||
daily_max_pm25 = EXCLUDED.daily_max_pm25,
|
||||
daily_min_pm25 = EXCLUDED.daily_min_pm25,
|
||||
good_pm10_percentage = EXCLUDED.good_pm10_percentage,
|
||||
moderate_pm10_percentage = EXCLUDED.moderate_pm10_percentage,
|
||||
unhealthy_sensitive_pm10_percentage = EXCLUDED.unhealthy_sensitive_pm10_percentage,
|
||||
unhealthy_pm10_percentage = EXCLUDED.unhealthy_pm10_percentage,
|
||||
very_unhealthy_pm10_percentage = EXCLUDED.very_unhealthy_pm10_percentage,
|
||||
hazardous_pm10_percentage = EXCLUDED.hazardous_pm10_percentage,
|
||||
daily_avg_pm10 = EXCLUDED.daily_avg_pm10,
|
||||
daily_max_pm10 = EXCLUDED.daily_max_pm10,
|
||||
daily_min_pm10 = EXCLUDED.daily_min_pm10,
|
||||
good_voc_percentage = EXCLUDED.good_voc_percentage,
|
||||
moderate_voc_percentage = EXCLUDED.moderate_voc_percentage,
|
||||
unhealthy_sensitive_voc_percentage = EXCLUDED.unhealthy_sensitive_voc_percentage,
|
||||
unhealthy_voc_percentage = EXCLUDED.unhealthy_voc_percentage,
|
||||
very_unhealthy_voc_percentage = EXCLUDED.very_unhealthy_voc_percentage,
|
||||
hazardous_voc_percentage = EXCLUDED.hazardous_voc_percentage,
|
||||
daily_avg_voc = EXCLUDED.daily_avg_voc,
|
||||
daily_max_voc = EXCLUDED.daily_max_voc,
|
||||
daily_min_voc = EXCLUDED.daily_min_voc,
|
||||
good_co2_percentage = EXCLUDED.good_co2_percentage,
|
||||
moderate_co2_percentage = EXCLUDED.moderate_co2_percentage,
|
||||
unhealthy_sensitive_co2_percentage = EXCLUDED.unhealthy_sensitive_co2_percentage,
|
||||
unhealthy_co2_percentage = EXCLUDED.unhealthy_co2_percentage,
|
||||
very_unhealthy_co2_percentage = EXCLUDED.very_unhealthy_co2_percentage,
|
||||
hazardous_co2_percentage = EXCLUDED.hazardous_co2_percentage,
|
||||
daily_avg_co2 = EXCLUDED.daily_avg_co2,
|
||||
daily_max_co2 = EXCLUDED.daily_max_co2,
|
||||
daily_min_co2 = EXCLUDED.daily_min_co2,
|
||||
good_ch2o_percentage = EXCLUDED.good_ch2o_percentage,
|
||||
moderate_ch2o_percentage = EXCLUDED.moderate_ch2o_percentage,
|
||||
unhealthy_sensitive_ch2o_percentage = EXCLUDED.unhealthy_sensitive_ch2o_percentage,
|
||||
unhealthy_ch2o_percentage = EXCLUDED.unhealthy_ch2o_percentage,
|
||||
very_unhealthy_ch2o_percentage = EXCLUDED.very_unhealthy_ch2o_percentage,
|
||||
hazardous_ch2o_percentage = EXCLUDED.hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o = EXCLUDED.daily_avg_ch2o,
|
||||
daily_max_ch2o = EXCLUDED.daily_max_ch2o,
|
||||
daily_min_ch2o = EXCLUDED.daily_min_ch2o;
|
||||
|
||||
|
||||
|
||||
+367
@@ -0,0 +1,367 @@
|
||||
-- Query Pipeline Starts Here
|
||||
WITH device_space AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_time::timestamp AS event_time,
|
||||
"device-status-log".code,
|
||||
"device-status-log".value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hjjcy'
|
||||
),
|
||||
|
||||
average_pollutants AS (
|
||||
SELECT
|
||||
event_time::date AS event_date,
|
||||
date_trunc('hour', event_time) AS event_hour,
|
||||
space_id,
|
||||
|
||||
-- PM1
|
||||
MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
|
||||
AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
|
||||
MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
|
||||
|
||||
-- PM25
|
||||
MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
|
||||
AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
|
||||
MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
|
||||
|
||||
-- PM10
|
||||
MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
|
||||
AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
|
||||
MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
|
||||
|
||||
-- VOC
|
||||
MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
|
||||
AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
|
||||
MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
|
||||
|
||||
-- CH2O
|
||||
MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
|
||||
AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
|
||||
MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
|
||||
|
||||
-- CO2
|
||||
MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
|
||||
AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
|
||||
MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
|
||||
|
||||
FROM device_space
|
||||
GROUP BY space_id, event_hour, event_date
|
||||
),
|
||||
|
||||
filled_pollutants AS (
|
||||
SELECT
|
||||
*,
|
||||
-- AVG
|
||||
COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_avg_f,
|
||||
COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_avg_f,
|
||||
COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_avg_f,
|
||||
COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_avg_f,
|
||||
COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_avg_f,
|
||||
|
||||
-- MIN
|
||||
COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_min_f,
|
||||
COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_min_f,
|
||||
COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_min_f,
|
||||
COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_min_f,
|
||||
COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_min_f,
|
||||
|
||||
-- MAX
|
||||
COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_max_f,
|
||||
COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_max_f,
|
||||
COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_max_f,
|
||||
COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_max_f,
|
||||
COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_max_f
|
||||
FROM average_pollutants
|
||||
),
|
||||
|
||||
hourly_results AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
event_hour,
|
||||
pm1_min, pm1_avg, pm1_max,
|
||||
pm25_min_f, pm25_avg_f, pm25_max_f,
|
||||
pm10_min_f, pm10_avg_f, pm10_max_f,
|
||||
voc_min_f, voc_avg_f, voc_max_f,
|
||||
co2_min_f, co2_avg_f, co2_max_f,
|
||||
ch2o_min_f, ch2o_avg_f, ch2o_max_f,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_min_f),
|
||||
calculate_aqi('pm10', pm10_min_f)
|
||||
) AS hourly_min_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
) AS hourly_avg_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_max_f),
|
||||
calculate_aqi('pm10', pm10_max_f)
|
||||
) AS hourly_max_aqi,
|
||||
|
||||
classify_aqi(GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
)) AS aqi_category,
|
||||
|
||||
classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
|
||||
classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
|
||||
classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
|
||||
classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
|
||||
classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
|
||||
|
||||
FROM filled_pollutants
|
||||
),
|
||||
|
||||
daily_category_counts AS (
|
||||
SELECT space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, aqi_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, pm25_category AS category, 'pm25' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, pm25_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, pm10_category AS category, 'pm10' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, pm10_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, voc_category AS category, 'voc' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, voc_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, co2_category AS category, 'co2' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, co2_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, ch2o_category AS category, 'ch2o' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, ch2o_category
|
||||
),
|
||||
|
||||
daily_totals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(category_count) AS total_count
|
||||
FROM daily_category_counts
|
||||
where pollutant = 'aqi'
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
-- Pivot Categories into Columns
|
||||
daily_percentages AS (
|
||||
select
|
||||
dt.space_id,
|
||||
dt.event_date,
|
||||
-- AQI CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_aqi_percentage,
|
||||
-- PM25 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm25_percentage,
|
||||
-- PM10 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm10_percentage,
|
||||
-- VOC CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_voc_percentage,
|
||||
-- CO2 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_co2_percentage,
|
||||
-- CH20 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_ch2o_percentage
|
||||
FROM daily_totals dt
|
||||
LEFT JOIN daily_category_counts dcc
|
||||
ON dt.space_id = dcc.space_id AND dt.event_date = dcc.event_date
|
||||
GROUP BY dt.space_id, dt.event_date, dt.total_count
|
||||
),
|
||||
|
||||
daily_averages AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
-- AQI
|
||||
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi,
|
||||
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
|
||||
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
|
||||
-- PM25
|
||||
ROUND(AVG(pm25_min_f)::numeric, 2) AS daily_min_pm25,
|
||||
ROUND(AVG(pm25_avg_f)::numeric, 2) AS daily_avg_pm25,
|
||||
ROUND(AVG(pm25_max_f)::numeric, 2) AS daily_max_pm25,
|
||||
-- PM10
|
||||
ROUND(AVG(pm10_min_f)::numeric, 2) AS daily_min_pm10,
|
||||
ROUND(AVG(pm10_avg_f)::numeric, 2) AS daily_avg_pm10,
|
||||
ROUND(AVG(pm10_max_f)::numeric, 2) AS daily_max_pm10,
|
||||
-- VOC
|
||||
ROUND(AVG(voc_min_f)::numeric, 2) AS daily_min_voc,
|
||||
ROUND(AVG(voc_avg_f)::numeric, 2) AS daily_avg_voc,
|
||||
ROUND(AVG(voc_max_f)::numeric, 2) AS daily_max_voc,
|
||||
-- CO2
|
||||
ROUND(AVG(co2_min_f)::numeric, 2) AS daily_min_co2,
|
||||
ROUND(AVG(co2_avg_f)::numeric, 2) AS daily_avg_co2,
|
||||
ROUND(AVG(co2_max_f)::numeric, 2) AS daily_max_co2,
|
||||
-- CH2O
|
||||
ROUND(AVG(ch2o_min_f)::numeric, 2) AS daily_min_ch2o,
|
||||
ROUND(AVG(ch2o_avg_f)::numeric, 2) AS daily_avg_ch2o,
|
||||
ROUND(AVG(ch2o_max_f)::numeric, 2) AS daily_max_ch2o
|
||||
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
final_data as(
|
||||
SELECT
|
||||
p.space_id,
|
||||
p.event_date,
|
||||
p.good_aqi_percentage, p.moderate_aqi_percentage, p.unhealthy_sensitive_aqi_percentage, p.unhealthy_aqi_percentage, p.very_unhealthy_aqi_percentage, p.hazardous_aqi_percentage,
|
||||
a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
|
||||
p.good_pm25_percentage, p.moderate_pm25_percentage, p.unhealthy_sensitive_pm25_percentage, p.unhealthy_pm25_percentage, p.very_unhealthy_pm25_percentage, p.hazardous_pm25_percentage,
|
||||
a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
|
||||
p.good_pm10_percentage, p.moderate_pm10_percentage, p.unhealthy_sensitive_pm10_percentage, p.unhealthy_pm10_percentage, p.very_unhealthy_pm10_percentage, p.hazardous_pm10_percentage,
|
||||
a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
|
||||
p.good_voc_percentage, p.moderate_voc_percentage, p.unhealthy_sensitive_voc_percentage, p.unhealthy_voc_percentage, p.very_unhealthy_voc_percentage, p.hazardous_voc_percentage,
|
||||
a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
|
||||
p.good_co2_percentage, p.moderate_co2_percentage, p.unhealthy_sensitive_co2_percentage, p.unhealthy_co2_percentage, p.very_unhealthy_co2_percentage, p.hazardous_co2_percentage,
|
||||
a.daily_avg_co2,a.daily_max_co2, a.daily_min_co2,
|
||||
p.good_ch2o_percentage, p.moderate_ch2o_percentage, p.unhealthy_sensitive_ch2o_percentage, p.unhealthy_ch2o_percentage, p.very_unhealthy_ch2o_percentage, p.hazardous_ch2o_percentage,
|
||||
a.daily_avg_ch2o,a.daily_max_ch2o, a.daily_min_ch2o
|
||||
FROM daily_percentages p
|
||||
LEFT JOIN daily_averages a
|
||||
ON p.space_id = a.space_id AND p.event_date = a.event_date
|
||||
ORDER BY p.space_id, p.event_date)
|
||||
|
||||
|
||||
INSERT INTO public."space-daily-pollutant-stats" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
good_aqi_percentage, moderate_aqi_percentage, unhealthy_sensitive_aqi_percentage, unhealthy_aqi_percentage, very_unhealthy_aqi_percentage, hazardous_aqi_percentage,
|
||||
daily_avg_aqi, daily_max_aqi, daily_min_aqi,
|
||||
good_pm25_percentage, moderate_pm25_percentage, unhealthy_sensitive_pm25_percentage, unhealthy_pm25_percentage, very_unhealthy_pm25_percentage, hazardous_pm25_percentage,
|
||||
daily_avg_pm25, daily_max_pm25, daily_min_pm25,
|
||||
good_pm10_percentage, moderate_pm10_percentage, unhealthy_sensitive_pm10_percentage, unhealthy_pm10_percentage, very_unhealthy_pm10_percentage, hazardous_pm10_percentage,
|
||||
daily_avg_pm10, daily_max_pm10, daily_min_pm10,
|
||||
good_voc_percentage, moderate_voc_percentage, unhealthy_sensitive_voc_percentage, unhealthy_voc_percentage, very_unhealthy_voc_percentage, hazardous_voc_percentage,
|
||||
daily_avg_voc, daily_max_voc, daily_min_voc,
|
||||
good_co2_percentage, moderate_co2_percentage, unhealthy_sensitive_co2_percentage, unhealthy_co2_percentage, very_unhealthy_co2_percentage, hazardous_co2_percentage,
|
||||
daily_avg_co2, daily_max_co2, daily_min_co2,
|
||||
good_ch2o_percentage, moderate_ch2o_percentage, unhealthy_sensitive_ch2o_percentage, unhealthy_ch2o_percentage, very_unhealthy_ch2o_percentage, hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o, daily_max_ch2o, daily_min_ch2o
|
||||
)
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
good_aqi_percentage, moderate_aqi_percentage, unhealthy_sensitive_aqi_percentage, unhealthy_aqi_percentage, very_unhealthy_aqi_percentage, hazardous_aqi_percentage,
|
||||
daily_avg_aqi, daily_max_aqi, daily_min_aqi,
|
||||
good_pm25_percentage, moderate_pm25_percentage, unhealthy_sensitive_pm25_percentage, unhealthy_pm25_percentage, very_unhealthy_pm25_percentage, hazardous_pm25_percentage,
|
||||
daily_avg_pm25, daily_max_pm25, daily_min_pm25,
|
||||
good_pm10_percentage, moderate_pm10_percentage, unhealthy_sensitive_pm10_percentage, unhealthy_pm10_percentage, very_unhealthy_pm10_percentage, hazardous_pm10_percentage,
|
||||
daily_avg_pm10, daily_max_pm10, daily_min_pm10,
|
||||
good_voc_percentage, moderate_voc_percentage, unhealthy_sensitive_voc_percentage, unhealthy_voc_percentage, very_unhealthy_voc_percentage, hazardous_voc_percentage,
|
||||
daily_avg_voc, daily_max_voc, daily_min_voc,
|
||||
good_co2_percentage, moderate_co2_percentage, unhealthy_sensitive_co2_percentage, unhealthy_co2_percentage, very_unhealthy_co2_percentage, hazardous_co2_percentage,
|
||||
daily_avg_co2, daily_max_co2, daily_min_co2,
|
||||
good_ch2o_percentage, moderate_ch2o_percentage, unhealthy_sensitive_ch2o_percentage, unhealthy_ch2o_percentage, very_unhealthy_ch2o_percentage, hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o, daily_max_ch2o, daily_min_ch2o
|
||||
FROM final_data
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
good_aqi_percentage = EXCLUDED.good_aqi_percentage,
|
||||
moderate_aqi_percentage = EXCLUDED.moderate_aqi_percentage,
|
||||
unhealthy_sensitive_aqi_percentage = EXCLUDED.unhealthy_sensitive_aqi_percentage,
|
||||
unhealthy_aqi_percentage = EXCLUDED.unhealthy_aqi_percentage,
|
||||
very_unhealthy_aqi_percentage = EXCLUDED.very_unhealthy_aqi_percentage,
|
||||
hazardous_aqi_percentage = EXCLUDED.hazardous_aqi_percentage,
|
||||
daily_avg_aqi = EXCLUDED.daily_avg_aqi,
|
||||
daily_max_aqi = EXCLUDED.daily_max_aqi,
|
||||
daily_min_aqi = EXCLUDED.daily_min_aqi,
|
||||
good_pm25_percentage = EXCLUDED.good_pm25_percentage,
|
||||
moderate_pm25_percentage = EXCLUDED.moderate_pm25_percentage,
|
||||
unhealthy_sensitive_pm25_percentage = EXCLUDED.unhealthy_sensitive_pm25_percentage,
|
||||
unhealthy_pm25_percentage = EXCLUDED.unhealthy_pm25_percentage,
|
||||
very_unhealthy_pm25_percentage = EXCLUDED.very_unhealthy_pm25_percentage,
|
||||
hazardous_pm25_percentage = EXCLUDED.hazardous_pm25_percentage,
|
||||
daily_avg_pm25 = EXCLUDED.daily_avg_pm25,
|
||||
daily_max_pm25 = EXCLUDED.daily_max_pm25,
|
||||
daily_min_pm25 = EXCLUDED.daily_min_pm25,
|
||||
good_pm10_percentage = EXCLUDED.good_pm10_percentage,
|
||||
moderate_pm10_percentage = EXCLUDED.moderate_pm10_percentage,
|
||||
unhealthy_sensitive_pm10_percentage = EXCLUDED.unhealthy_sensitive_pm10_percentage,
|
||||
unhealthy_pm10_percentage = EXCLUDED.unhealthy_pm10_percentage,
|
||||
very_unhealthy_pm10_percentage = EXCLUDED.very_unhealthy_pm10_percentage,
|
||||
hazardous_pm10_percentage = EXCLUDED.hazardous_pm10_percentage,
|
||||
daily_avg_pm10 = EXCLUDED.daily_avg_pm10,
|
||||
daily_max_pm10 = EXCLUDED.daily_max_pm10,
|
||||
daily_min_pm10 = EXCLUDED.daily_min_pm10,
|
||||
good_voc_percentage = EXCLUDED.good_voc_percentage,
|
||||
moderate_voc_percentage = EXCLUDED.moderate_voc_percentage,
|
||||
unhealthy_sensitive_voc_percentage = EXCLUDED.unhealthy_sensitive_voc_percentage,
|
||||
unhealthy_voc_percentage = EXCLUDED.unhealthy_voc_percentage,
|
||||
very_unhealthy_voc_percentage = EXCLUDED.very_unhealthy_voc_percentage,
|
||||
hazardous_voc_percentage = EXCLUDED.hazardous_voc_percentage,
|
||||
daily_avg_voc = EXCLUDED.daily_avg_voc,
|
||||
daily_max_voc = EXCLUDED.daily_max_voc,
|
||||
daily_min_voc = EXCLUDED.daily_min_voc,
|
||||
good_co2_percentage = EXCLUDED.good_co2_percentage,
|
||||
moderate_co2_percentage = EXCLUDED.moderate_co2_percentage,
|
||||
unhealthy_sensitive_co2_percentage = EXCLUDED.unhealthy_sensitive_co2_percentage,
|
||||
unhealthy_co2_percentage = EXCLUDED.unhealthy_co2_percentage,
|
||||
very_unhealthy_co2_percentage = EXCLUDED.very_unhealthy_co2_percentage,
|
||||
hazardous_co2_percentage = EXCLUDED.hazardous_co2_percentage,
|
||||
daily_avg_co2 = EXCLUDED.daily_avg_co2,
|
||||
daily_max_co2 = EXCLUDED.daily_max_co2,
|
||||
daily_min_co2 = EXCLUDED.daily_min_co2,
|
||||
good_ch2o_percentage = EXCLUDED.good_ch2o_percentage,
|
||||
moderate_ch2o_percentage = EXCLUDED.moderate_ch2o_percentage,
|
||||
unhealthy_sensitive_ch2o_percentage = EXCLUDED.unhealthy_sensitive_ch2o_percentage,
|
||||
unhealthy_ch2o_percentage = EXCLUDED.unhealthy_ch2o_percentage,
|
||||
very_unhealthy_ch2o_percentage = EXCLUDED.very_unhealthy_ch2o_percentage,
|
||||
hazardous_ch2o_percentage = EXCLUDED.hazardous_ch2o_percentage,
|
||||
daily_avg_ch2o = EXCLUDED.daily_avg_ch2o,
|
||||
daily_max_ch2o = EXCLUDED.daily_max_ch2o,
|
||||
daily_min_ch2o = EXCLUDED.daily_min_ch2o;
|
||||
|
||||
|
||||
+110
@@ -0,0 +1,110 @@
|
||||
WITH presence_logs AS (
|
||||
SELECT
|
||||
d.space_device_uuid AS space_id,
|
||||
l.device_id,
|
||||
l.event_time,
|
||||
l.value,
|
||||
LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time,
|
||||
LAG(l.value) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_value
|
||||
FROM device d
|
||||
JOIN "device-status-log" l ON d.uuid = l.device_id
|
||||
JOIN product p ON p.uuid = d.product_device_uuid
|
||||
WHERE l.code = 'presence_state'
|
||||
AND p.cat_name = 'hps'
|
||||
),
|
||||
|
||||
-- Intervals when device was in 'presence' (between prev_time and event_time when value='none')
|
||||
presence_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
prev_time AS start_time,
|
||||
event_time AS end_time
|
||||
FROM presence_logs
|
||||
WHERE value = 'none'
|
||||
AND prev_value = 'presence'
|
||||
AND prev_time IS NOT NULL
|
||||
),
|
||||
|
||||
-- Split intervals across days
|
||||
split_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
generate_series(
|
||||
date_trunc('day', start_time),
|
||||
date_trunc('day', end_time),
|
||||
interval '1 day'
|
||||
)::date AS event_date,
|
||||
GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
|
||||
LEAST(end_time, date_trunc('day', end_time) + interval '1 day') AS interval_end
|
||||
FROM presence_intervals
|
||||
),
|
||||
|
||||
-- Mark and group overlapping intervals per space per day
|
||||
ordered_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
interval_start,
|
||||
interval_end,
|
||||
LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
|
||||
FROM split_intervals
|
||||
),
|
||||
|
||||
grouped_intervals AS (
|
||||
SELECT *,
|
||||
SUM(CASE
|
||||
WHEN prev_end IS NULL OR interval_start > prev_end THEN 1
|
||||
ELSE 0
|
||||
END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
|
||||
FROM ordered_intervals
|
||||
),
|
||||
|
||||
-- Merge overlapping intervals per group
|
||||
merged_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
MIN(interval_start) AS merged_start,
|
||||
MAX(interval_end) AS merged_end
|
||||
FROM grouped_intervals
|
||||
GROUP BY space_id, event_date, grp
|
||||
),
|
||||
|
||||
-- Sum durations of merged intervals
|
||||
summed_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
|
||||
FROM merged_intervals
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
final_data AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
|
||||
ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
|
||||
FROM summed_intervals
|
||||
ORDER BY space_id, event_date)
|
||||
|
||||
|
||||
INSERT INTO public."space-daily-occupancy-duration" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
occupied_seconds,
|
||||
occupancy_percentage
|
||||
)
|
||||
select space_id,
|
||||
event_date,
|
||||
occupied_seconds,
|
||||
occupancy_percentage
|
||||
FROM final_data
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
occupancy_percentage = EXCLUDED.occupancy_percentage,
|
||||
occupied_seconds = EXCLUDED.occupied_seconds;
|
||||
|
||||
|
||||
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
$1::uuid AS space_uuid,
|
||||
TO_DATE(NULLIF($2, ''), 'YYYY-MM') AS event_month
|
||||
)
|
||||
|
||||
|
||||
SELECT sdo.space_uuid,
|
||||
event_date,
|
||||
occupancy_percentage,
|
||||
occupied_seconds
|
||||
FROM public."space-daily-occupancy-duration" as sdo
|
||||
JOIN params P ON true
|
||||
where (sdo.space_uuid = P.space_uuid
|
||||
OR P.event_month IS null)
|
||||
AND TO_CHAR(sdo.event_date, 'YYYY-MM') = TO_CHAR(P.event_month, 'YYYY-MM')
|
||||
ORDER BY sdo.space_uuid, sdo.event_date;
|
||||
+109
@@ -0,0 +1,109 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
TO_DATE(NULLIF($1, ''), 'YYYY-MM-DD') AS event_date,
|
||||
$2::uuid AS space_id
|
||||
),
|
||||
|
||||
presence_logs AS (
|
||||
SELECT
|
||||
d.space_device_uuid AS space_id,
|
||||
l.device_id,
|
||||
l.event_time,
|
||||
l.value,
|
||||
LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time
|
||||
FROM device d
|
||||
JOIN "device-status-log" l ON d.uuid = l.device_id
|
||||
JOIN product p ON p.uuid = d.product_device_uuid
|
||||
WHERE l.code = 'presence_state'
|
||||
AND p.cat_name = 'hps'
|
||||
),
|
||||
|
||||
presence_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
prev_time AS start_time,
|
||||
event_time AS end_time
|
||||
FROM presence_logs
|
||||
WHERE value = 'none' AND prev_time IS NOT NULL
|
||||
),
|
||||
|
||||
split_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
generate_series(
|
||||
date_trunc('day', start_time),
|
||||
date_trunc('day', end_time),
|
||||
interval '1 day'
|
||||
)::date AS event_date,
|
||||
GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
|
||||
LEAST(end_time, date_trunc('day', end_time) + INTERVAL '1 day') AS interval_end
|
||||
FROM presence_intervals
|
||||
),
|
||||
|
||||
ordered_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
interval_start,
|
||||
interval_end,
|
||||
LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
|
||||
FROM split_intervals
|
||||
),
|
||||
|
||||
grouped_intervals AS (
|
||||
SELECT *,
|
||||
SUM(CASE
|
||||
WHEN prev_end IS NULL OR interval_start > prev_end THEN 1
|
||||
ELSE 0
|
||||
END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
|
||||
FROM ordered_intervals
|
||||
),
|
||||
|
||||
merged_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
MIN(interval_start) AS merged_start,
|
||||
MAX(interval_end) AS merged_end
|
||||
FROM grouped_intervals
|
||||
GROUP BY space_id, event_date, grp
|
||||
),
|
||||
|
||||
summed_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
|
||||
FROM merged_intervals
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
final_data AS (
|
||||
SELECT
|
||||
s.space_id,
|
||||
s.event_date,
|
||||
LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
|
||||
ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
|
||||
FROM summed_intervals s
|
||||
JOIN params p
|
||||
ON p.space_id = s.space_id
|
||||
AND p.event_date = s.event_date
|
||||
)
|
||||
|
||||
INSERT INTO public."space-daily-occupancy-duration" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
occupied_seconds,
|
||||
occupancy_percentage
|
||||
)
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
occupied_seconds,
|
||||
occupancy_percentage
|
||||
FROM final_data
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
occupancy_percentage = EXCLUDED.occupancy_percentage,
|
||||
occupied_seconds = EXCLUDED.occupied_seconds;
|
||||
|
||||
+20
@@ -0,0 +1,20 @@
|
||||
-- will return the presence metrics for the days of the selected month
|
||||
WITH params AS (
|
||||
SELECT
|
||||
TO_DATE(NULLIF($2, ''), 'YYYY-MM') AS month,
|
||||
string_to_array(NULLIF($4, ''), ',') AS device_ids
|
||||
)
|
||||
|
||||
SELECT
|
||||
A.device_uuid,
|
||||
A.event_date,
|
||||
A.count_motion_detected,
|
||||
A.count_presence_detected,
|
||||
A.count_total_presence_detected
|
||||
FROM public."presence-sensor-daily-device-detection" AS A
|
||||
JOIN params P ON TRUE
|
||||
WHERE A.device_uuid::text = ANY(P.device_ids)
|
||||
AND (P.month IS NULL
|
||||
OR date_trunc('month', A.event_date) = P.month
|
||||
);
|
||||
|
||||
+21
@@ -0,0 +1,21 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
TO_DATE(NULLIF($2, ''), 'YYYY') AS year,
|
||||
string_to_array(NULLIF($4, ''), ',') AS device_ids
|
||||
)
|
||||
|
||||
SELECT
|
||||
A.device_uuid,
|
||||
TO_CHAR(date_trunc('month', A.event_date), 'YYYY-MM') AS event_month,
|
||||
SUM(A.count_motion_detected) AS total_motion_detected,
|
||||
SUM(A.count_presence_detected) AS total_presence_detected,
|
||||
SUM(A.count_total_presence_detected) AS total_overall_presence
|
||||
FROM public."presence-sensor-daily-device-detection" AS A
|
||||
JOIN params P ON TRUE
|
||||
WHERE A.device_uuid::text = ANY(P.device_ids)
|
||||
AND (
|
||||
P.year IS NULL
|
||||
OR date_trunc('year', A.event_date) = P.year
|
||||
)
|
||||
GROUP BY 1,2
|
||||
ORDER BY 1,2;
|
||||
+115
@@ -0,0 +1,115 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
TO_DATE(NULLIF($2, ''), 'YYYY-MM-DD') AS event_date,
|
||||
$4::text AS device_id
|
||||
),
|
||||
|
||||
device_logs AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.created_at,
|
||||
device.device_tuya_uuid,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_id,
|
||||
"device-status-log".event_time::timestamp,
|
||||
"device-status-log".code,
|
||||
"device-status-log".value,
|
||||
"device-status-log".log,
|
||||
LAG("device-status-log".event_time::timestamp)
|
||||
OVER (PARTITION BY device.uuid
|
||||
ORDER BY "device-status-log".event_time) AS prev_timestamp,
|
||||
LAG("device-status-log".value)
|
||||
OVER (PARTITION BY device.uuid
|
||||
ORDER BY "device-status-log".event_time) AS prev_value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
JOIN params P ON TRUE
|
||||
WHERE product.cat_name = 'hps'
|
||||
AND "device-status-log".code = 'presence_state'
|
||||
AND device.uuid::text = P.device_id
|
||||
),
|
||||
|
||||
presence_detection AS (
|
||||
SELECT *,
|
||||
CASE
|
||||
WHEN value = 'motion' AND prev_value = 'none' THEN 1 ELSE 0
|
||||
END AS motion_detected,
|
||||
CASE
|
||||
WHEN value = 'presence' AND prev_value = 'none' THEN 1 ELSE 0
|
||||
END AS presence_detected
|
||||
FROM device_logs
|
||||
),
|
||||
|
||||
presence_detection_summary AS (
|
||||
SELECT
|
||||
pd.device_id,
|
||||
d.subspace_id,
|
||||
pd.space_id,
|
||||
pd.event_time::date AS event_date,
|
||||
EXTRACT(HOUR FROM pd.event_time)::int AS event_hour,
|
||||
SUM(motion_detected) AS count_motion_detected,
|
||||
SUM(presence_detected) AS count_presence_detected,
|
||||
SUM(motion_detected + presence_detected) AS count_total_presence_detected
|
||||
FROM presence_detection pd
|
||||
LEFT JOIN device d ON d.uuid = pd.device_id
|
||||
JOIN params P ON TRUE
|
||||
AND (P.event_date IS NULL OR pd.event_time::date = P.event_date)
|
||||
GROUP BY 1, 2, 3, 4, 5
|
||||
),
|
||||
|
||||
all_dates_and_hours AS (
|
||||
SELECT device_id, subspace_id, space_id, event_date, event_hour
|
||||
FROM (
|
||||
SELECT DISTINCT device_id, subspace_id, space_id, event_date
|
||||
FROM presence_detection_summary
|
||||
) d
|
||||
CROSS JOIN generate_series(0, 23) AS event_hour
|
||||
),
|
||||
|
||||
table_final AS (
|
||||
SELECT
|
||||
adah.device_id,
|
||||
adah.event_date,
|
||||
COALESCE(pds.count_motion_detected, 0) AS count_motion_detected,
|
||||
COALESCE(pds.count_presence_detected, 0) AS count_presence_detected,
|
||||
COALESCE(pds.count_total_presence_detected, 0) AS count_total_presence_detected
|
||||
FROM all_dates_and_hours adah
|
||||
LEFT JOIN presence_detection_summary pds
|
||||
ON pds.device_id = adah.device_id
|
||||
AND pds.event_date = adah.event_date
|
||||
AND pds.event_hour = adah.event_hour
|
||||
),
|
||||
|
||||
daily_aggregates AS (
|
||||
SELECT
|
||||
device_id,
|
||||
event_date,
|
||||
SUM(count_motion_detected) AS count_motion_detected,
|
||||
SUM(count_presence_detected) AS count_presence_detected,
|
||||
SUM(count_total_presence_detected) AS count_total_presence_detected
|
||||
FROM table_final
|
||||
GROUP BY device_id, event_date
|
||||
)
|
||||
|
||||
INSERT INTO public."presence-sensor-daily-device-detection" (
|
||||
device_uuid,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
)
|
||||
SELECT
|
||||
device_id,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
FROM daily_aggregates
|
||||
ON CONFLICT (device_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
count_motion_detected = EXCLUDED.count_motion_detected,
|
||||
count_presence_detected = EXCLUDED.count_presence_detected,
|
||||
count_total_presence_detected = EXCLUDED.count_total_presence_detected;
|
||||
+15
@@ -0,0 +1,15 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
$1::uuid AS space_id,
|
||||
TO_DATE(NULLIF($2, ''), 'YYYY') AS event_year
|
||||
)
|
||||
|
||||
SELECT psdsd.*
|
||||
FROM public."presence-sensor-daily-space-detection" psdsd
|
||||
JOIN params P ON true
|
||||
WHERE psdsd.space_uuid = P.space_id
|
||||
AND (
|
||||
P.event_year IS NULL
|
||||
OR TO_CHAR(psdsd.event_date, 'YYYY') = TO_CHAR(P.event_year, 'YYYY')
|
||||
)
|
||||
ORDER BY space_uuid, event_date
|
||||
+100
@@ -0,0 +1,100 @@
|
||||
WITH device_logs AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_time::timestamp AS event_time,
|
||||
"device-status-log".value,
|
||||
LAG("device-status-log".value)
|
||||
OVER (PARTITION BY device.uuid ORDER BY "device-status-log".event_time) AS prev_value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hps'
|
||||
AND "device-status-log".code = 'presence_state'
|
||||
),
|
||||
|
||||
-- 1. All 'none' → presence or motion
|
||||
presence_transitions AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_time,
|
||||
event_time::date AS event_date,
|
||||
value
|
||||
FROM device_logs
|
||||
WHERE (value = 'motion' OR value = 'presence') AND prev_value = 'none'
|
||||
),
|
||||
|
||||
-- 2. Cluster events per space_id within 30s
|
||||
clustered_events AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_time,
|
||||
event_date,
|
||||
value,
|
||||
SUM(new_cluster_flag) OVER (PARTITION BY space_id ORDER BY event_time) AS cluster_id
|
||||
FROM (
|
||||
SELECT *,
|
||||
CASE
|
||||
WHEN event_time - LAG(event_time) OVER (PARTITION BY space_id ORDER BY event_time) > INTERVAL '30 seconds'
|
||||
THEN 1 ELSE 0
|
||||
END AS new_cluster_flag
|
||||
FROM presence_transitions
|
||||
) marked
|
||||
),
|
||||
|
||||
-- 3. Determine dominant type (motion vs presence) per cluster
|
||||
cluster_type AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
cluster_id,
|
||||
COUNT(*) FILTER (WHERE value = 'motion') AS motion_count,
|
||||
COUNT(*) FILTER (WHERE value = 'presence') AS presence_count,
|
||||
CASE
|
||||
WHEN COUNT(*) FILTER (WHERE value = 'motion') > COUNT(*) FILTER (WHERE value = 'presence') THEN 'motion'
|
||||
ELSE 'presence'
|
||||
END AS dominant_type
|
||||
FROM clustered_events
|
||||
GROUP BY space_id, event_date, cluster_id
|
||||
),
|
||||
|
||||
-- 4. Count clusters by dominant type
|
||||
summary AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
COUNT(*) FILTER (WHERE dominant_type = 'motion') AS count_motion_detected,
|
||||
COUNT(*) FILTER (WHERE dominant_type = 'presence') AS count_presence_detected,
|
||||
COUNT(*) AS count_total_presence_detected
|
||||
FROM cluster_type
|
||||
GROUP BY space_id, event_date
|
||||
)
|
||||
|
||||
-- 5. Output
|
||||
, final_table as (
|
||||
SELECT *
|
||||
FROM summary
|
||||
ORDER BY space_id, event_date)
|
||||
|
||||
|
||||
INSERT INTO public."presence-sensor-daily-space-detection" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
)
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
FROM final_table
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
count_motion_detected = EXCLUDED.count_motion_detected,
|
||||
count_presence_detected = EXCLUDED.count_presence_detected,
|
||||
count_total_presence_detected = EXCLUDED.count_total_presence_detected;
|
||||
+113
@@ -0,0 +1,113 @@
|
||||
WITH params AS (
|
||||
SELECT
|
||||
TO_DATE(NULLIF($1, ''), 'YYYY-MM-DD') AS event_date,
|
||||
$2::uuid AS space_id
|
||||
),
|
||||
|
||||
device_logs AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_time::timestamp AS event_time,
|
||||
"device-status-log".value,
|
||||
LAG("device-status-log".value)
|
||||
OVER (PARTITION BY device.uuid ORDER BY "device-status-log".event_time) AS prev_value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hps'
|
||||
AND "device-status-log".code = 'presence_state'
|
||||
),
|
||||
|
||||
-- 1. All 'none' → presence or motion
|
||||
presence_transitions AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_time,
|
||||
event_time::date AS event_date,
|
||||
value
|
||||
FROM device_logs
|
||||
WHERE (value = 'motion' OR value = 'presence') AND prev_value = 'none'
|
||||
),
|
||||
|
||||
-- 2. Cluster events per space_id within 30s
|
||||
clustered_events AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_time,
|
||||
event_date,
|
||||
value,
|
||||
SUM(new_cluster_flag) OVER (PARTITION BY space_id ORDER BY event_time) AS cluster_id
|
||||
FROM (
|
||||
SELECT *,
|
||||
CASE
|
||||
WHEN event_time - LAG(event_time) OVER (PARTITION BY space_id ORDER BY event_time) > INTERVAL '30 seconds'
|
||||
THEN 1 ELSE 0
|
||||
END AS new_cluster_flag
|
||||
FROM presence_transitions
|
||||
) marked
|
||||
),
|
||||
|
||||
-- 3. Determine dominant type (motion vs presence) per cluster
|
||||
cluster_type AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
cluster_id,
|
||||
COUNT(*) FILTER (WHERE value = 'motion') AS motion_count,
|
||||
COUNT(*) FILTER (WHERE value = 'presence') AS presence_count,
|
||||
CASE
|
||||
WHEN COUNT(*) FILTER (WHERE value = 'motion') > COUNT(*) FILTER (WHERE value = 'presence') THEN 'motion'
|
||||
ELSE 'presence'
|
||||
END AS dominant_type
|
||||
FROM clustered_events
|
||||
GROUP BY space_id, event_date, cluster_id
|
||||
),
|
||||
|
||||
-- 4. Count clusters by dominant type
|
||||
summary AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
COUNT(*) FILTER (WHERE dominant_type = 'motion') AS count_motion_detected,
|
||||
COUNT(*) FILTER (WHERE dominant_type = 'presence') AS count_presence_detected,
|
||||
COUNT(*) AS count_total_presence_detected
|
||||
FROM cluster_type
|
||||
GROUP BY space_id, event_date
|
||||
)
|
||||
|
||||
-- 5. Output
|
||||
, final_table as (
|
||||
SELECT summary.space_id,
|
||||
summary.event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
FROM summary
|
||||
JOIN params P ON true
|
||||
where summary.space_id = P.space_id
|
||||
and (P.event_date IS NULL or summary.event_date::date = P.event_date)
|
||||
ORDER BY space_id, event_date)
|
||||
|
||||
|
||||
INSERT INTO public."presence-sensor-daily-space-detection" (
|
||||
space_uuid,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
)
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
FROM final_table
|
||||
ON CONFLICT (space_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
count_motion_detected = EXCLUDED.count_motion_detected,
|
||||
count_presence_detected = EXCLUDED.count_presence_detected,
|
||||
count_total_presence_detected = EXCLUDED.count_total_presence_detected;
|
||||
+362
@@ -0,0 +1,362 @@
|
||||
-- Function to calculate AQI
|
||||
CREATE OR REPLACE FUNCTION calculate_aqi(p_pollutant TEXT, concentration NUMERIC)
|
||||
RETURNS NUMERIC AS $$
|
||||
DECLARE
|
||||
c_low NUMERIC;
|
||||
c_high NUMERIC;
|
||||
i_low INT;
|
||||
i_high INT;
|
||||
BEGIN
|
||||
SELECT v.c_low, v.c_high, v.i_low, v.i_high
|
||||
INTO c_low, c_high, i_low, i_high
|
||||
FROM (
|
||||
VALUES
|
||||
-- PM2.5
|
||||
('pm25', 0.0, 12.0, 0, 50),
|
||||
('pm25', 12.1, 35.4, 51, 100),
|
||||
('pm25', 35.5, 55.4, 101, 150),
|
||||
('pm25', 55.5, 150.4, 151, 200),
|
||||
('pm25', 150.5, 250.4, 201, 300),
|
||||
('pm25', 250.5, 500.4, 301, 500),
|
||||
|
||||
-- PM10
|
||||
('pm10', 0, 54, 0, 50),
|
||||
('pm10', 55, 154, 51, 100),
|
||||
('pm10', 155, 254, 101, 150),
|
||||
('pm10', 255, 354, 151, 200),
|
||||
|
||||
-- VOC
|
||||
('voc', 0, 200, 0, 50),
|
||||
('voc', 201, 400, 51, 100),
|
||||
('voc', 401, 600, 101, 150),
|
||||
('voc', 601, 1000, 151, 200),
|
||||
|
||||
-- CH2O
|
||||
('ch2o', 0, 2, 0, 50),
|
||||
('ch2o', 2.1, 4, 51, 100),
|
||||
('ch2o', 4.1, 6, 101, 150),
|
||||
|
||||
-- CO2
|
||||
('co2', 350, 1000, 0, 50),
|
||||
('co2', 1001, 1250, 51, 100),
|
||||
('co2', 1251, 1500, 101, 150),
|
||||
('co2', 1501, 2000, 151, 200)
|
||||
) AS v(pollutant, c_low, c_high, i_low, i_high)
|
||||
WHERE v.pollutant = LOWER(p_pollutant)
|
||||
AND concentration BETWEEN v.c_low AND v.c_high
|
||||
LIMIT 1;
|
||||
|
||||
RETURN ROUND(((i_high - i_low) * (concentration - c_low) / (c_high - c_low)) + i_low);
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
|
||||
-- Function to classify AQI
|
||||
CREATE OR REPLACE FUNCTION classify_aqi(aqi NUMERIC)
|
||||
RETURNS TEXT AS $$
|
||||
BEGIN
|
||||
RETURN CASE
|
||||
WHEN aqi BETWEEN 0 AND 50 THEN 'Good'
|
||||
WHEN aqi BETWEEN 51 AND 100 THEN 'Moderate'
|
||||
WHEN aqi BETWEEN 101 AND 150 THEN 'Unhealthy for Sensitive Groups'
|
||||
WHEN aqi BETWEEN 151 AND 200 THEN 'Unhealthy'
|
||||
WHEN aqi BETWEEN 201 AND 300 THEN 'Very Unhealthy'
|
||||
WHEN aqi >= 301 THEN 'Hazardous'
|
||||
ELSE NULL
|
||||
END;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
|
||||
-- Function to convert AQI level string to number
|
||||
CREATE OR REPLACE FUNCTION level_to_numeric(level_text TEXT)
|
||||
RETURNS NUMERIC AS $$
|
||||
BEGIN
|
||||
RETURN CAST(regexp_replace(level_text, '[^0-9]', '', 'g') AS NUMERIC);
|
||||
EXCEPTION WHEN others THEN
|
||||
RETURN NULL;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
|
||||
|
||||
-- Query Pipeline Starts Here
|
||||
WITH device_space AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_time::timestamp AS event_time,
|
||||
"device-status-log".code,
|
||||
"device-status-log".value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hjjcy'
|
||||
),
|
||||
|
||||
average_pollutants AS (
|
||||
SELECT
|
||||
event_time::date AS event_date,
|
||||
date_trunc('hour', event_time) AS event_hour,
|
||||
device_id,
|
||||
space_id,
|
||||
|
||||
-- PM1
|
||||
MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
|
||||
AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
|
||||
MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
|
||||
|
||||
-- PM25
|
||||
MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
|
||||
AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
|
||||
MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
|
||||
|
||||
-- PM10
|
||||
MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
|
||||
AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
|
||||
MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
|
||||
|
||||
-- VOC
|
||||
MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
|
||||
AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
|
||||
MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
|
||||
|
||||
-- CH2O
|
||||
MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
|
||||
AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
|
||||
MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
|
||||
|
||||
-- CO2
|
||||
MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
|
||||
AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
|
||||
MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
|
||||
|
||||
FROM device_space
|
||||
GROUP BY device_id, space_id, event_hour, event_date
|
||||
),
|
||||
|
||||
filled_pollutants AS (
|
||||
SELECT
|
||||
*,
|
||||
-- AVG
|
||||
COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_avg_f,
|
||||
COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_avg_f,
|
||||
COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_avg_f,
|
||||
COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS co2_avg_f,
|
||||
COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS ch2o_avg_f,
|
||||
|
||||
-- MIN
|
||||
COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_min_f,
|
||||
COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_min_f,
|
||||
COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_min_f,
|
||||
COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS co2_min_f,
|
||||
COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS ch2o_min_f,
|
||||
|
||||
-- MAX
|
||||
COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_max_f,
|
||||
COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_max_f,
|
||||
COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_max_f,
|
||||
COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS co2_max_f,
|
||||
COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS ch2o_max_f
|
||||
FROM average_pollutants
|
||||
),
|
||||
|
||||
hourly_results AS (
|
||||
SELECT
|
||||
device_id,
|
||||
space_id,
|
||||
event_date,
|
||||
event_hour,
|
||||
pm1_min, pm1_avg, pm1_max,
|
||||
pm25_min_f, pm25_avg_f, pm25_max_f,
|
||||
pm10_min_f, pm10_avg_f, pm10_max_f,
|
||||
voc_min_f, voc_avg_f, voc_max_f,
|
||||
co2_min_f, co2_avg_f, co2_max_f,
|
||||
ch2o_min_f, ch2o_avg_f, ch2o_max_f,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_min_f),
|
||||
calculate_aqi('pm10', pm10_min_f)
|
||||
) AS hourly_min_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
) AS hourly_avg_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_max_f),
|
||||
calculate_aqi('pm10', pm10_max_f)
|
||||
) AS hourly_max_aqi,
|
||||
|
||||
classify_aqi(GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
)) AS aqi_category,
|
||||
|
||||
classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
|
||||
classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
|
||||
classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
|
||||
classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
|
||||
classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
|
||||
|
||||
FROM filled_pollutants
|
||||
),
|
||||
|
||||
daily_category_counts AS (
|
||||
SELECT device_id, space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, aqi_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT device_id, space_id, event_date, pm25_category AS category, 'pm25' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, pm25_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT device_id, space_id, event_date, pm10_category AS category, 'pm10' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, pm10_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT device_id, space_id, event_date, voc_category AS category, 'voc' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, voc_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT device_id, space_id, event_date, co2_category AS category, 'co2' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, co2_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT device_id, space_id, event_date, ch2o_category AS category, 'ch2o' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date, ch2o_category
|
||||
),
|
||||
|
||||
daily_totals AS (
|
||||
SELECT
|
||||
device_id,
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(category_count) AS total_count
|
||||
FROM daily_category_counts
|
||||
where pollutant = 'aqi'
|
||||
GROUP BY device_id, space_id, event_date
|
||||
),
|
||||
|
||||
-- Pivot Categories into Columns
|
||||
daily_percentages AS (
|
||||
select
|
||||
dt.device_id,
|
||||
dt.space_id,
|
||||
dt.event_date,
|
||||
-- AQI CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_aqi_percentage,
|
||||
-- PM25 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm25_percentage,
|
||||
-- PM10 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm10_percentage,
|
||||
-- VOC CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_voc_percentage,
|
||||
-- CO2 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_co2_percentage,
|
||||
-- CH20 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_ch2o_percentage
|
||||
FROM daily_totals dt
|
||||
LEFT JOIN daily_category_counts dcc
|
||||
ON dt.device_id = dcc.device_id AND dt.event_date = dcc.event_date
|
||||
GROUP BY dt.device_id, dt.space_id, dt.event_date, dt.total_count
|
||||
),
|
||||
|
||||
daily_averages AS (
|
||||
SELECT
|
||||
device_id,
|
||||
space_id,
|
||||
event_date,
|
||||
-- AQI
|
||||
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi,
|
||||
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
|
||||
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
|
||||
-- PM25
|
||||
ROUND(AVG(pm25_min_f)::numeric, 2) AS daily_min_pm25,
|
||||
ROUND(AVG(pm25_avg_f)::numeric, 2) AS daily_avg_pm25,
|
||||
ROUND(AVG(pm25_max_f)::numeric, 2) AS daily_max_pm25,
|
||||
-- PM10
|
||||
ROUND(AVG(pm10_min_f)::numeric, 2) AS daily_min_pm10,
|
||||
ROUND(AVG(pm10_avg_f)::numeric, 2) AS daily_avg_pm10,
|
||||
ROUND(AVG(pm10_max_f)::numeric, 2) AS daily_max_pm10,
|
||||
-- VOC
|
||||
ROUND(AVG(voc_min_f)::numeric, 2) AS daily_min_voc,
|
||||
ROUND(AVG(voc_avg_f)::numeric, 2) AS daily_avg_voc,
|
||||
ROUND(AVG(voc_max_f)::numeric, 2) AS daily_max_voc,
|
||||
-- CO2
|
||||
ROUND(AVG(co2_min_f)::numeric, 2) AS daily_min_co2,
|
||||
ROUND(AVG(co2_avg_f)::numeric, 2) AS daily_avg_co2,
|
||||
ROUND(AVG(co2_max_f)::numeric, 2) AS daily_max_co2,
|
||||
-- CH2O
|
||||
ROUND(AVG(ch2o_min_f)::numeric, 2) AS daily_min_ch2o,
|
||||
ROUND(AVG(ch2o_avg_f)::numeric, 2) AS daily_avg_ch2o,
|
||||
ROUND(AVG(ch2o_max_f)::numeric, 2) AS daily_max_ch2o
|
||||
|
||||
FROM hourly_results
|
||||
GROUP BY device_id, space_id, event_date
|
||||
)
|
||||
SELECT
|
||||
p.device_id,
|
||||
p.space_id,
|
||||
p.event_date,
|
||||
p.good_aqi_percentage, p.moderate_aqi_percentage, p.unhealthy_sensitive_aqi_percentage, p.unhealthy_aqi_percentage, p.very_unhealthy_aqi_percentage, p.hazardous_aqi_percentage,
|
||||
a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
|
||||
p.good_pm25_percentage, p.moderate_pm25_percentage, p.unhealthy_sensitive_pm25_percentage, p.unhealthy_pm25_percentage, p.very_unhealthy_pm25_percentage, p.hazardous_pm25_percentage,
|
||||
a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
|
||||
p.good_pm10_percentage, p.moderate_pm10_percentage, p.unhealthy_sensitive_pm10_percentage, p.unhealthy_pm10_percentage, p.very_unhealthy_pm10_percentage, p.hazardous_pm10_percentage,
|
||||
a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
|
||||
p.good_voc_percentage, p.moderate_voc_percentage, p.unhealthy_sensitive_voc_percentage, p.unhealthy_voc_percentage, p.very_unhealthy_voc_percentage, p.hazardous_voc_percentage,
|
||||
a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
|
||||
p.good_co2_percentage, p.moderate_co2_percentage, p.unhealthy_sensitive_co2_percentage, p.unhealthy_co2_percentage, p.very_unhealthy_co2_percentage, p.hazardous_co2_percentage,
|
||||
a.daily_avg_co2,a.daily_max_co2, a.daily_min_co2,
|
||||
p.good_ch2o_percentage, p.moderate_ch2o_percentage, p.unhealthy_sensitive_ch2o_percentage, p.unhealthy_ch2o_percentage, p.very_unhealthy_ch2o_percentage, p.hazardous_ch2o_percentage,
|
||||
a.daily_avg_ch2o,a.daily_max_ch2o, a.daily_min_ch2o
|
||||
FROM daily_percentages p
|
||||
LEFT JOIN daily_averages a
|
||||
ON p.device_id = a.device_id AND p.event_date = a.event_date
|
||||
ORDER BY p.space_id, p.event_date;
|
||||
|
||||
|
||||
+275
@@ -0,0 +1,275 @@
|
||||
-- Query Pipeline Starts Here
|
||||
WITH device_space AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_time::timestamp AS event_time,
|
||||
"device-status-log".code,
|
||||
"device-status-log".value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hjjcy'
|
||||
),
|
||||
|
||||
average_pollutants AS (
|
||||
SELECT
|
||||
event_time::date AS event_date,
|
||||
date_trunc('hour', event_time) AS event_hour,
|
||||
space_id,
|
||||
|
||||
-- PM1
|
||||
MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
|
||||
AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
|
||||
MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
|
||||
|
||||
-- PM25
|
||||
MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
|
||||
AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
|
||||
MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
|
||||
|
||||
-- PM10
|
||||
MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
|
||||
AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
|
||||
MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
|
||||
|
||||
-- VOC
|
||||
MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
|
||||
AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
|
||||
MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
|
||||
|
||||
-- CH2O
|
||||
MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
|
||||
AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
|
||||
MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
|
||||
|
||||
-- CO2
|
||||
MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
|
||||
AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
|
||||
MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
|
||||
|
||||
FROM device_space
|
||||
GROUP BY space_id, event_hour, event_date
|
||||
),
|
||||
|
||||
filled_pollutants AS (
|
||||
SELECT
|
||||
*,
|
||||
-- AVG
|
||||
COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_avg_f,
|
||||
COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_avg_f,
|
||||
COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_avg_f,
|
||||
COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_avg_f,
|
||||
COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_avg_f,
|
||||
|
||||
-- MIN
|
||||
COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_min_f,
|
||||
COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_min_f,
|
||||
COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_min_f,
|
||||
COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_min_f,
|
||||
COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_min_f,
|
||||
|
||||
-- MAX
|
||||
COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_max_f,
|
||||
COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_max_f,
|
||||
COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_max_f,
|
||||
COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_max_f,
|
||||
COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_max_f
|
||||
FROM average_pollutants
|
||||
),
|
||||
|
||||
hourly_results AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
event_hour,
|
||||
pm1_min, pm1_avg, pm1_max,
|
||||
pm25_min_f, pm25_avg_f, pm25_max_f,
|
||||
pm10_min_f, pm10_avg_f, pm10_max_f,
|
||||
voc_min_f, voc_avg_f, voc_max_f,
|
||||
co2_min_f, co2_avg_f, co2_max_f,
|
||||
ch2o_min_f, ch2o_avg_f, ch2o_max_f,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_min_f),
|
||||
calculate_aqi('pm10', pm10_min_f)
|
||||
) AS hourly_min_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
) AS hourly_avg_aqi,
|
||||
|
||||
GREATEST(
|
||||
calculate_aqi('pm25', pm25_max_f),
|
||||
calculate_aqi('pm10', pm10_max_f)
|
||||
) AS hourly_max_aqi,
|
||||
|
||||
classify_aqi(GREATEST(
|
||||
calculate_aqi('pm25', pm25_avg_f),
|
||||
calculate_aqi('pm10', pm10_avg_f)
|
||||
)) AS aqi_category,
|
||||
|
||||
classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
|
||||
classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
|
||||
classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
|
||||
classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
|
||||
classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
|
||||
|
||||
FROM filled_pollutants
|
||||
),
|
||||
|
||||
daily_category_counts AS (
|
||||
SELECT space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, aqi_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, pm25_category AS category, 'pm25' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, pm25_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, pm10_category AS category, 'pm10' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, pm10_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, voc_category AS category, 'voc' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, voc_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, co2_category AS category, 'co2' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, co2_category
|
||||
|
||||
UNION ALL
|
||||
|
||||
SELECT space_id, event_date, ch2o_category AS category, 'ch2o' AS pollutant, COUNT(*) AS category_count
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date, ch2o_category
|
||||
),
|
||||
|
||||
daily_totals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(category_count) AS total_count
|
||||
FROM daily_category_counts
|
||||
where pollutant = 'aqi'
|
||||
GROUP BY space_id, event_date
|
||||
),
|
||||
|
||||
-- Pivot Categories into Columns
|
||||
daily_percentages AS (
|
||||
select
|
||||
dt.space_id,
|
||||
dt.event_date,
|
||||
-- AQI CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_aqi_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_aqi_percentage,
|
||||
-- PM25 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm25_percentage,
|
||||
-- PM10 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm10_percentage,
|
||||
-- VOC CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_voc_percentage,
|
||||
-- CO2 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_co2_percentage,
|
||||
-- CH20 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_ch2o_percentage
|
||||
FROM daily_totals dt
|
||||
LEFT JOIN daily_category_counts dcc
|
||||
ON dt.space_id = dcc.space_id AND dt.event_date = dcc.event_date
|
||||
GROUP BY dt.space_id, dt.event_date, dt.total_count
|
||||
),
|
||||
|
||||
daily_averages AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
-- AQI
|
||||
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi,
|
||||
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
|
||||
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
|
||||
-- PM25
|
||||
ROUND(AVG(pm25_min_f)::numeric, 2) AS daily_min_pm25,
|
||||
ROUND(AVG(pm25_avg_f)::numeric, 2) AS daily_avg_pm25,
|
||||
ROUND(AVG(pm25_max_f)::numeric, 2) AS daily_max_pm25,
|
||||
-- PM10
|
||||
ROUND(AVG(pm10_min_f)::numeric, 2) AS daily_min_pm10,
|
||||
ROUND(AVG(pm10_avg_f)::numeric, 2) AS daily_avg_pm10,
|
||||
ROUND(AVG(pm10_max_f)::numeric, 2) AS daily_max_pm10,
|
||||
-- VOC
|
||||
ROUND(AVG(voc_min_f)::numeric, 2) AS daily_min_voc,
|
||||
ROUND(AVG(voc_avg_f)::numeric, 2) AS daily_avg_voc,
|
||||
ROUND(AVG(voc_max_f)::numeric, 2) AS daily_max_voc,
|
||||
-- CO2
|
||||
ROUND(AVG(co2_min_f)::numeric, 2) AS daily_min_co2,
|
||||
ROUND(AVG(co2_avg_f)::numeric, 2) AS daily_avg_co2,
|
||||
ROUND(AVG(co2_max_f)::numeric, 2) AS daily_max_co2,
|
||||
-- CH2O
|
||||
ROUND(AVG(ch2o_min_f)::numeric, 2) AS daily_min_ch2o,
|
||||
ROUND(AVG(ch2o_avg_f)::numeric, 2) AS daily_avg_ch2o,
|
||||
ROUND(AVG(ch2o_max_f)::numeric, 2) AS daily_max_ch2o
|
||||
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date
|
||||
)
|
||||
SELECT
|
||||
p.space_id,
|
||||
p.event_date,
|
||||
p.good_aqi_percentage, p.moderate_aqi_percentage, p.unhealthy_sensitive_aqi_percentage, p.unhealthy_aqi_percentage, p.very_unhealthy_aqi_percentage, p.hazardous_aqi_percentage,
|
||||
a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
|
||||
p.good_pm25_percentage, p.moderate_pm25_percentage, p.unhealthy_sensitive_pm25_percentage, p.unhealthy_pm25_percentage, p.very_unhealthy_pm25_percentage, p.hazardous_pm25_percentage,
|
||||
a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
|
||||
p.good_pm10_percentage, p.moderate_pm10_percentage, p.unhealthy_sensitive_pm10_percentage, p.unhealthy_pm10_percentage, p.very_unhealthy_pm10_percentage, p.hazardous_pm10_percentage,
|
||||
a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
|
||||
p.good_voc_percentage, p.moderate_voc_percentage, p.unhealthy_sensitive_voc_percentage, p.unhealthy_voc_percentage, p.very_unhealthy_voc_percentage, p.hazardous_voc_percentage,
|
||||
a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
|
||||
p.good_co2_percentage, p.moderate_co2_percentage, p.unhealthy_sensitive_co2_percentage, p.unhealthy_co2_percentage, p.very_unhealthy_co2_percentage, p.hazardous_co2_percentage,
|
||||
a.daily_avg_co2,a.daily_max_co2, a.daily_min_co2,
|
||||
p.good_ch2o_percentage, p.moderate_ch2o_percentage, p.unhealthy_sensitive_ch2o_percentage, p.unhealthy_ch2o_percentage, p.very_unhealthy_ch2o_percentage, p.hazardous_ch2o_percentage,
|
||||
a.daily_avg_ch2o,a.daily_max_ch2o, a.daily_min_ch2o
|
||||
FROM daily_percentages p
|
||||
LEFT JOIN daily_averages a
|
||||
ON p.space_id = a.space_id AND p.event_date = a.event_date
|
||||
ORDER BY p.space_id, p.event_date;
|
||||
|
||||
|
||||
+77
-78
@@ -1,91 +1,90 @@
|
||||
-- Step 1: Get device presence events with previous timestamps
|
||||
WITH start_date AS (
|
||||
SELECT
|
||||
d.uuid AS device_id,
|
||||
d.space_device_uuid AS space_id,
|
||||
l.value,
|
||||
l.event_time::timestamp AS event_time,
|
||||
LAG(l.event_time::timestamp) OVER (PARTITION BY d.uuid ORDER BY l.event_time) AS prev_timestamp
|
||||
FROM device d
|
||||
LEFT JOIN "device-status-log" l
|
||||
ON d.uuid = l.device_id
|
||||
LEFT JOIN product p
|
||||
ON p.uuid = d.product_device_uuid
|
||||
WHERE p.cat_name = 'hps'
|
||||
AND l.code = 'presence_state'
|
||||
WITH presence_logs AS (
|
||||
SELECT
|
||||
d.space_device_uuid AS space_id,
|
||||
l.device_id,
|
||||
l.event_time,
|
||||
l.value,
|
||||
LAG(l.event_time) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_time,
|
||||
LAG(l.value) OVER (PARTITION BY l.device_id ORDER BY l.event_time) AS prev_value
|
||||
FROM device d
|
||||
JOIN "device-status-log" l ON d.uuid = l.device_id
|
||||
JOIN product p ON p.uuid = d.product_device_uuid
|
||||
WHERE l.code = 'presence_state'
|
||||
AND p.cat_name = 'hps'
|
||||
),
|
||||
|
||||
-- Step 2: Identify periods when device reports "none"
|
||||
device_none_periods AS (
|
||||
SELECT
|
||||
space_id,
|
||||
device_id,
|
||||
event_time AS empty_from,
|
||||
LEAD(event_time) OVER (PARTITION BY device_id ORDER BY event_time) AS empty_until
|
||||
FROM start_date
|
||||
WHERE value = 'none'
|
||||
-- Intervals when device was in 'presence' (between prev_time and event_time when value='none')
|
||||
presence_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
prev_time AS start_time,
|
||||
event_time AS end_time
|
||||
FROM presence_logs
|
||||
WHERE value = 'none'
|
||||
AND prev_value = 'presence'
|
||||
AND prev_time IS NOT NULL
|
||||
),
|
||||
|
||||
-- Step 3: Clip the "none" periods to the edges of each day
|
||||
clipped_device_none_periods AS (
|
||||
SELECT
|
||||
space_id,
|
||||
GREATEST(empty_from, DATE_TRUNC('day', empty_from)) AS clipped_from,
|
||||
LEAST(empty_until, DATE_TRUNC('day', empty_until) + INTERVAL '1 day') AS clipped_until
|
||||
FROM device_none_periods
|
||||
WHERE empty_until IS NOT NULL
|
||||
-- Split intervals across days
|
||||
split_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
generate_series(
|
||||
date_trunc('day', start_time),
|
||||
date_trunc('day', end_time),
|
||||
interval '1 day'
|
||||
)::date AS event_date,
|
||||
GREATEST(start_time, date_trunc('day', start_time)) AS interval_start,
|
||||
LEAST(end_time, date_trunc('day', end_time) + interval '1 day') AS interval_end
|
||||
FROM presence_intervals
|
||||
),
|
||||
|
||||
-- Step 4: Break multi-day periods into daily intervals
|
||||
generated_daily_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
gs::date AS day,
|
||||
GREATEST(clipped_from, gs) AS interval_start,
|
||||
LEAST(clipped_until, gs + INTERVAL '1 day') AS interval_end
|
||||
FROM clipped_device_none_periods,
|
||||
LATERAL generate_series(DATE_TRUNC('day', clipped_from), DATE_TRUNC('day', clipped_until), INTERVAL '1 day') AS gs
|
||||
-- Mark and group overlapping intervals per space per day
|
||||
ordered_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
interval_start,
|
||||
interval_end,
|
||||
LAG(interval_end) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS prev_end
|
||||
FROM split_intervals
|
||||
),
|
||||
|
||||
-- Step 5: Merge overlapping or adjacent intervals per day
|
||||
grouped_intervals AS (
|
||||
SELECT *,
|
||||
SUM(CASE
|
||||
WHEN prev_end IS NULL OR interval_start > prev_end THEN 1
|
||||
ELSE 0
|
||||
END) OVER (PARTITION BY space_id, event_date ORDER BY interval_start) AS grp
|
||||
FROM ordered_intervals
|
||||
),
|
||||
|
||||
-- Merge overlapping intervals per group
|
||||
merged_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
day,
|
||||
interval_start,
|
||||
interval_end
|
||||
FROM (
|
||||
SELECT
|
||||
space_id,
|
||||
day,
|
||||
interval_start,
|
||||
interval_end,
|
||||
LAG(interval_end) OVER (PARTITION BY space_id, day ORDER BY interval_start) AS prev_end
|
||||
FROM generated_daily_intervals
|
||||
) sub
|
||||
WHERE prev_end IS NULL OR interval_start > prev_end
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
MIN(interval_start) AS merged_start,
|
||||
MAX(interval_end) AS merged_end
|
||||
FROM grouped_intervals
|
||||
GROUP BY space_id, event_date, grp
|
||||
),
|
||||
|
||||
-- Step 6: Sum up total missing seconds (device reported "none") per day
|
||||
missing_seconds_per_day AS (
|
||||
SELECT
|
||||
space_id,
|
||||
day AS missing_date,
|
||||
SUM(EXTRACT(EPOCH FROM (interval_end - interval_start))) AS total_missing_seconds
|
||||
FROM merged_intervals
|
||||
GROUP BY space_id, day
|
||||
),
|
||||
|
||||
-- Step 7: Calculate total occupied time per day (86400 - missing)
|
||||
occupied_seconds_per_day AS (
|
||||
SELECT
|
||||
space_id,
|
||||
missing_date as date,
|
||||
86400 - total_missing_seconds AS total_occupied_seconds
|
||||
FROM missing_seconds_per_day
|
||||
-- Sum durations of merged intervals
|
||||
summed_intervals AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
SUM(EXTRACT(EPOCH FROM (merged_end - merged_start))) AS raw_occupied_seconds
|
||||
FROM merged_intervals
|
||||
GROUP BY space_id, event_date
|
||||
)
|
||||
|
||||
-- Final Output
|
||||
SELECT *
|
||||
FROM occupied_seconds_per_day
|
||||
ORDER BY 1,2;
|
||||
-- Final output with capped seconds and percentage
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
LEAST(raw_occupied_seconds, 86400) AS occupied_seconds,
|
||||
ROUND(LEAST(raw_occupied_seconds, 86400) / 86400.0 * 100, 2) AS occupancy_percentage
|
||||
FROM summed_intervals
|
||||
ORDER BY space_id, event_date;
|
||||
+106
@@ -0,0 +1,106 @@
|
||||
-- This model shows the number of times a presence was detected per hour, per day
|
||||
WITH device_logs AS (
|
||||
SELECT
|
||||
device.uuid AS device_id,
|
||||
device.created_at,
|
||||
device.device_tuya_uuid,
|
||||
device.space_device_uuid AS space_id,
|
||||
"device-status-log".event_id,
|
||||
"device-status-log".event_time::timestamp,
|
||||
"device-status-log".code,
|
||||
"device-status-log".value,
|
||||
"device-status-log".log,
|
||||
LAG("device-status-log".event_time::timestamp)
|
||||
OVER (PARTITION BY device.uuid
|
||||
ORDER BY "device-status-log".event_time) AS prev_timestamp,
|
||||
LAG("device-status-log".value)
|
||||
OVER (PARTITION BY device.uuid
|
||||
ORDER BY "device-status-log".event_time) AS prev_value
|
||||
FROM device
|
||||
LEFT JOIN "device-status-log"
|
||||
ON device.uuid = "device-status-log".device_id
|
||||
LEFT JOIN product
|
||||
ON product.uuid = device.product_device_uuid
|
||||
WHERE product.cat_name = 'hps'
|
||||
AND "device-status-log".code = 'presence_state'
|
||||
),
|
||||
|
||||
presence_detection AS (
|
||||
SELECT *,
|
||||
CASE
|
||||
WHEN value = 'motion' AND prev_value = 'none' THEN 1 ELSE 0
|
||||
END AS motion_detected,
|
||||
CASE
|
||||
WHEN value = 'presence' AND prev_value = 'none' THEN 1 ELSE 0
|
||||
END AS presence_detected
|
||||
FROM device_logs
|
||||
),
|
||||
|
||||
presence_detection_summary AS (
|
||||
SELECT
|
||||
pd.device_id,
|
||||
d.subspace_id,
|
||||
pd.space_id,
|
||||
pd.event_time::date AS event_date,
|
||||
EXTRACT(HOUR FROM pd.event_time)::int AS event_hour,
|
||||
SUM(motion_detected) AS count_motion_detected,
|
||||
SUM(presence_detected) AS count_presence_detected,
|
||||
SUM(motion_detected + presence_detected) AS count_total_presence_detected
|
||||
FROM presence_detection pd
|
||||
LEFT JOIN device d ON d.uuid = pd.device_id
|
||||
GROUP BY 1, 2, 3, 4, 5
|
||||
),
|
||||
|
||||
all_dates_and_hours AS (
|
||||
SELECT device_id, subspace_id, space_id, event_date, event_hour
|
||||
FROM (
|
||||
SELECT DISTINCT device_id, subspace_id, space_id, event_date
|
||||
FROM presence_detection_summary
|
||||
) d
|
||||
CROSS JOIN generate_series(0, 23) AS event_hour
|
||||
),
|
||||
|
||||
table_final AS (
|
||||
SELECT
|
||||
adah.device_id,
|
||||
adah.event_date,
|
||||
COALESCE(pds.count_motion_detected, 0) AS count_motion_detected,
|
||||
COALESCE(pds.count_presence_detected, 0) AS count_presence_detected,
|
||||
COALESCE(pds.count_total_presence_detected, 0) AS count_total_presence_detected
|
||||
FROM all_dates_and_hours adah
|
||||
LEFT JOIN presence_detection_summary pds
|
||||
ON pds.device_id = adah.device_id
|
||||
AND pds.event_date = adah.event_date
|
||||
AND pds.event_hour = adah.event_hour
|
||||
),
|
||||
|
||||
daily_aggregate AS (
|
||||
SELECT
|
||||
device_id,
|
||||
event_date,
|
||||
SUM(count_motion_detected) AS count_motion_detected,
|
||||
SUM(count_presence_detected) AS count_presence_detected,
|
||||
SUM(count_total_presence_detected) AS count_total_presence_detected
|
||||
FROM table_final
|
||||
GROUP BY device_id, event_date
|
||||
)
|
||||
|
||||
INSERT INTO public."presence-sensor-daily-device-detection" (
|
||||
device_uuid,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
)
|
||||
SELECT
|
||||
device_id,
|
||||
event_date,
|
||||
count_motion_detected,
|
||||
count_presence_detected,
|
||||
count_total_presence_detected
|
||||
FROM daily_aggregate
|
||||
ON CONFLICT (device_uuid, event_date) DO UPDATE
|
||||
SET
|
||||
count_motion_detected = EXCLUDED.count_motion_detected,
|
||||
count_presence_detected = EXCLUDED.count_presence_detected,
|
||||
count_total_presence_detected = EXCLUDED.count_total_presence_detected;
|
||||
Reference in New Issue
Block a user