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device model updated to include the fixes and final columns

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khuss
2025-06-03 20:52:27 -04:00
parent 2fee8c055e
commit ab3efedc35
1 changed files with 235 additions and 135 deletions
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libs/common/src/sql/queries/fact_daily_device_aqi_score/fact_daily_device_aqi_score.sql
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@ -26,43 +26,60 @@ BEGIN
('pm10', 255, 354, 151, 200), ('pm10', 255, 354, 151, 200),
-- VOC -- VOC
('voc_value', 0, 200, 0, 50), ('voc', 0, 200, 0, 50),
('voc_value', 201, 400, 51, 100), ('voc', 201, 400, 51, 100),
('voc_value', 401, 600, 101, 150), ('voc', 401, 600, 101, 150),
('voc_value', 601, 1000, 151, 200), ('voc', 601, 1000, 151, 200),
-- CH2O -- CH2O
('ch2o_value', 0, 2, 0, 50), ('ch2o', 0, 2, 0, 50),
('ch2o_value', 2.1, 4, 51, 100), ('ch2o', 2.1, 4, 51, 100),
('ch2o_value', 4.1, 6, 101, 150), ('ch2o', 4.1, 6, 101, 150),
-- CO2 -- CO2
('co2_value', 350, 1000, 0, 50), ('co2', 350, 1000, 0, 50),
('co2_value', 1001, 1250, 51, 100), ('co2', 1001, 1250, 51, 100),
('co2_value', 1251, 1500, 101, 150), ('co2', 1251, 1500, 101, 150),
('co2_value', 1501, 2000, 151, 200) ('co2', 1501, 2000, 151, 200)
) AS v(pollutant, c_low, c_high, i_low, i_high) ) AS v(pollutant, c_low, c_high, i_low, i_high)
WHERE v.pollutant = LOWER(p_pollutant) WHERE v.pollutant = LOWER(p_pollutant)
AND concentration BETWEEN v.c_low AND v.c_high AND concentration BETWEEN v.c_low AND v.c_high
LIMIT 1; LIMIT 1;
-- Linear interpolation
RETURN ROUND(((i_high - i_low) * (concentration - c_low) / (c_high - c_low)) + i_low); RETURN ROUND(((i_high - i_low) * (concentration - c_low) / (c_high - c_low)) + i_low);
END; END;
$$ LANGUAGE plpgsql; $$ LANGUAGE plpgsql;
-- Function to convert Tuya AQI level (e.g., level_1, level_2) to numeric value
-- 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) CREATE OR REPLACE FUNCTION level_to_numeric(level_text TEXT)
RETURNS NUMERIC AS $$ RETURNS NUMERIC AS $$
BEGIN BEGIN
-- Extract the number from the string, default to NULL if not found
RETURN CAST(regexp_replace(level_text, '[^0-9]', '', 'g') AS NUMERIC); RETURN CAST(regexp_replace(level_text, '[^0-9]', '', 'g') AS NUMERIC);
EXCEPTION WHEN others THEN EXCEPTION WHEN others THEN
RETURN NULL; RETURN NULL;
END; END;
$$ LANGUAGE plpgsql; $$ LANGUAGE plpgsql;
-- CTE for device + status log + space
-- Query Pipeline Starts Here
WITH device_space AS ( WITH device_space AS (
SELECT SELECT
device.uuid AS device_id, device.uuid AS device_id,
@ -78,149 +95,160 @@ WITH device_space AS (
WHERE product.cat_name = 'hjjcy' WHERE product.cat_name = 'hjjcy'
), ),
-- Getting the hourly pollutants max min avg for each device
average_pollutants AS ( average_pollutants AS (
SELECT SELECT
event_time::date AS event_date,
date_trunc('hour', event_time) AS event_hour, date_trunc('hour', event_time) AS event_hour,
device_id, device_id,
space_id, space_id,
-- AVG READINGS -- PM1
AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
-- MIN READINGS
MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min, MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min, AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
-- MAX READINGS
MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max, 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, 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, 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, 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 MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
FROM device_space FROM device_space
GROUP BY device_id, space_id, event_hour GROUP BY device_id, space_id, event_hour, event_date
), ),
-- Fill NULLs due to missing log values
filled_pollutants AS ( filled_pollutants AS (
SELECT SELECT
*, *,
COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_filled_avg, -- AVG
COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_filled_avg, COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_avg_f,
COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_filled_avg, COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_avg_f,
COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS co2_filled_avg, COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_avg_f,
COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY device_id ORDER BY event_hour)) AS ch2o_filled_avg, 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,
COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_min_filled, -- MIN
COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_min_filled, 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(pm25_max, LAG(pm25_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm25_max_filled, COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY device_id ORDER BY event_hour)) AS voc_min_f,
COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY device_id ORDER BY event_hour)) AS pm10_max_filled 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 FROM average_pollutants
), ),
-- Calculate max, min, avg hourly AQI for each device
hourly_results AS ( hourly_results AS (
SELECT SELECT
device_id, device_id,
space_id, space_id,
event_date,
event_hour, event_hour,
pm25_filled_avg, pm1_min, pm1_avg, pm1_max,
pm10_filled_avg, pm25_min_f, pm25_avg_f, pm25_max_f,
pm25_max_filled, pm10_min_f, pm10_avg_f, pm10_max_f,
pm10_max_filled, voc_min_f, voc_avg_f, voc_max_f,
pm25_min_filled, co2_min_f, co2_avg_f, co2_max_f,
pm10_min_filled, ch2o_min_f, ch2o_avg_f, ch2o_max_f,
GREATEST( GREATEST(
calculate_aqi('pm25', pm25_filled_avg), calculate_aqi('pm25', pm25_min_f),
calculate_aqi('pm10', pm10_filled_avg) 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, ) AS hourly_avg_aqi,
GREATEST( GREATEST(
calculate_aqi('pm25', pm25_max_filled), calculate_aqi('pm25', pm25_max_f),
calculate_aqi('pm10', pm10_max_filled) calculate_aqi('pm10', pm10_max_f)
) AS hourly_max_aqi, ) AS hourly_max_aqi,
GREATEST( classify_aqi(GREATEST(
calculate_aqi('pm25', pm25_min_filled), calculate_aqi('pm25', pm25_avg_f),
calculate_aqi('pm10', pm10_min_filled) calculate_aqi('pm10', pm10_avg_f)
) AS hourly_min_aqi, )) AS aqi_category,
CASE classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
WHEN GREATEST( classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
calculate_aqi('pm25', pm25_filled_avg), classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
calculate_aqi('pm10', pm10_filled_avg) classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
) <= 50 THEN 'Good' classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
WHEN GREATEST(
calculate_aqi('pm25', pm25_filled_avg),
calculate_aqi('pm10', pm10_filled_avg)
) <= 100 THEN 'Moderate'
WHEN GREATEST(
calculate_aqi('pm25', pm25_filled_avg),
calculate_aqi('pm10', pm10_filled_avg)
) <= 150 THEN 'Unhealthy for Sensitive Groups'
WHEN GREATEST(
calculate_aqi('pm25', pm25_filled_avg),
calculate_aqi('pm10', pm10_filled_avg)
) <= 200 THEN 'Unhealthy'
WHEN GREATEST(
calculate_aqi('pm25', pm25_filled_avg),
calculate_aqi('pm10', pm10_filled_avg)
) <= 300 THEN 'Very Unhealthy'
ELSE 'Hazardous'
END AS aqi_category
FROM filled_pollutants FROM filled_pollutants
ORDER BY device_id, event_hour
), ),
-- counting how many categories/hours are there in total (in case device was disconnected could be less than 24)
daily_category_counts AS ( daily_category_counts AS (
SELECT SELECT device_id, space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
space_id,
device_id,
date_trunc('day', event_hour) AS event_day,
aqi_category,
COUNT(*) AS category_count
FROM hourly_results FROM hourly_results
GROUP BY device_id, space_id, event_day, aqi_category 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
),
-- Aggregate Total Counts per Day
daily_totals AS ( daily_totals AS (
select SELECT
device_id, device_id,
space_id, space_id,
event_day, event_date,
SUM(category_count) AS total_count SUM(category_count) AS total_count
FROM daily_category_counts FROM daily_category_counts
GROUP BY device_id, space_id, event_day where pollutant = 'aqi'
), GROUP BY device_id, space_id, event_date
-- Calculate the daily of the daily min max avg AQI values
daily_averages AS (
select
device_id,
space_id,
date_trunc('day', event_hour) AS event_day,
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi
FROM hourly_results
GROUP BY device_id, space_id, event_day
), ),
-- Pivot Categories into Columns -- Pivot Categories into Columns
@ -228,35 +256,107 @@ daily_percentages AS (
select select
dt.device_id, dt.device_id,
dt.space_id, dt.space_id,
dt.event_day, dt.event_date,
ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Good' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_percentage, -- AQI CATEGORIES
ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Moderate' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_percentage, 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.aqi_category = 'Unhealthy for Sensitive Groups' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_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.aqi_category = 'Unhealthy' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_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.aqi_category = 'Very Unhealthy' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_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.aqi_category = 'Hazardous' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_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 FROM daily_totals dt
LEFT JOIN daily_category_counts dcc LEFT JOIN daily_category_counts dcc
ON dt.device_id = dcc.device_id AND dt.event_day = dcc.event_day ON dt.device_id = dcc.device_id AND dt.event_date = dcc.event_date
GROUP BY dt.device_id, dt.space_id, dt.event_day, dt.total_count GROUP BY dt.device_id, dt.space_id, dt.event_date, dt.total_count
) ),
-- Final Output 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 SELECT
p.device_id, p.device_id,
p.space_id, p.space_id,
p.event_day, p.event_date,
p.good_percentage, 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,
p.moderate_percentage, a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
p.unhealthy_sensitive_percentage, 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,
p.unhealthy_percentage, a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
p.very_unhealthy_percentage, 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,
p.hazardous_percentage, a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
a.daily_avg_aqi, 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_max_aqi, a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
a.daily_min_aqi 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 FROM daily_percentages p
LEFT JOIN daily_averages a LEFT JOIN daily_averages a
ON p.device_id = a.device_id AND p.event_day = a.event_day ON p.device_id = a.device_id AND p.event_date = a.event_date
ORDER BY p.space_id, p.event_day; ORDER BY p.space_id, p.event_date;