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Author SHA1 Message Date
6c15ce77fe bug fix 2025-05-22 16:09:12 +03:00
30 changed files with 296 additions and 2086 deletions

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@ -1,18 +1,18 @@
import { PlatformType } from '@app/common/constants/platform-type.enum';
import { RoleType } from '@app/common/constants/role.type.enum';
import {
BadRequestException,
Injectable,
UnauthorizedException,
} from '@nestjs/common';
import { ConfigService } from '@nestjs/config';
import { JwtService } from '@nestjs/jwt';
import * as argon2 from 'argon2';
import { OAuth2Client } from 'google-auth-library';
import { UserSessionEntity } from '../../../../common/src/modules/session/entities';
import { UserSessionRepository } from '../../../../common/src/modules/session/repositories/session.repository';
import { UserRepository } from '../../../../common/src/modules/user/repositories';
import { HelperHashService } from '../../helper/services';
import { UserRepository } from '../../../../common/src/modules/user/repositories';
import { UserSessionRepository } from '../../../../common/src/modules/session/repositories/session.repository';
import { UserSessionEntity } from '../../../../common/src/modules/session/entities';
import { ConfigService } from '@nestjs/config';
import { OAuth2Client } from 'google-auth-library';
import { PlatformType } from '@app/common/constants/platform-type.enum';
import { RoleType } from '@app/common/constants/role.type.enum';
@Injectable()
export class AuthService {
@ -40,17 +40,16 @@ export class AuthService {
},
relations: ['roleType', 'project'],
});
if (!user) {
throw new BadRequestException('Invalid credentials');
}
if (
platform === PlatformType.WEB &&
[RoleType.SPACE_OWNER, RoleType.SPACE_MEMBER].includes(
user.roleType.type as RoleType,
)
(user.roleType.type === RoleType.SPACE_OWNER ||
user.roleType.type === RoleType.SPACE_MEMBER)
) {
throw new UnauthorizedException('Access denied for web platform');
}
if (!user) {
throw new BadRequestException('Invalid credentials');
}
if (!user.isUserVerified) {
throw new BadRequestException('User is not verified');

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@ -465,16 +465,7 @@ export class ControllerRoute {
'This endpoint retrieves the terms and conditions for the application.';
};
};
static WEATHER = class {
public static readonly ROUTE = 'weather';
static ACTIONS = class {
public static readonly FETCH_WEATHER_DETAILS_SUMMARY =
'Fetch Weather Details';
public static readonly FETCH_WEATHER_DETAILS_DESCRIPTION =
'This endpoint retrieves the current weather details for a specified location like temperature, humidity, etc.';
};
};
static PRIVACY_POLICY = class {
public static readonly ROUTE = 'policy';

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@ -12,7 +12,6 @@ export class RoleTypeEntity extends AbstractEntity<RoleTypeDto> {
nullable: false,
enum: Object.values(RoleType),
})
// why is this ts-type string not enum?
type: string;
@OneToMany(() => UserEntity, (inviteUser) => inviteUser.roleType, {
nullable: true,

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@ -14,7 +14,7 @@ import { AbstractEntity } from '@app/common/modules/abstract/entities/abstract.e
import { SubspaceProductAllocationDto } from '../../dtos/subspace-product-allocation.dto';
@Entity({ name: 'subspace_product_allocation' })
// @Unique(['subspace', 'product'])
@Unique(['subspace', 'product'])
export class SubspaceProductAllocationEntity extends AbstractEntity<SubspaceProductAllocationDto> {
@Column({
type: 'uuid',

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@ -25,7 +25,7 @@ export class NewTagEntity extends AbstractEntity<NewTagDto> {
name: string;
@ManyToOne(() => ProductEntity, (product) => product.newTags, {
nullable: true,
nullable: false,
onDelete: 'CASCADE',
})
public product: ProductEntity;

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@ -1,39 +0,0 @@
WITH params AS (
SELECT
$1::uuid AS space_uuid,
TO_DATE(NULLIF($2, ''), 'YYYY-MM') AS event_month
)
SELECT
sdp.space_uuid,
sdp.event_date,
sdp.good_aqi_percentage, sdp.moderate_aqi_percentage, sdp.unhealthy_sensitive_aqi_percentage, sdp.unhealthy_aqi_percentage,
sdp.very_unhealthy_aqi_percentage, sdp.hazardous_aqi_percentage,
sdp.daily_avg_aqi, sdp.daily_max_aqi, sdp.daily_min_aqi,
sdp.good_pm25_percentage, sdp.moderate_pm25_percentage, sdp.unhealthy_sensitive_pm25_percentage, sdp.unhealthy_pm25_percentage,
sdp.very_unhealthy_pm25_percentage, sdp.hazardous_pm25_percentage,
sdp.daily_avg_pm25, sdp.daily_max_pm25, sdp.daily_min_pm25,
sdp.good_pm10_percentage, sdp.moderate_pm10_percentage, sdp.unhealthy_sensitive_pm10_percentage, sdp.unhealthy_pm10_percentage,
sdp.very_unhealthy_pm10_percentage, sdp.hazardous_pm10_percentage,
sdp.daily_avg_pm10, sdp.daily_max_pm10, sdp.daily_min_pm10,
sdp.good_voc_percentage, sdp.moderate_voc_percentage, sdp.unhealthy_sensitive_voc_percentage, sdp.unhealthy_voc_percentage,
sdp.very_unhealthy_voc_percentage, sdp.hazardous_voc_percentage,
sdp.daily_avg_voc, sdp.daily_max_voc, sdp.daily_min_voc,
sdp.good_co2_percentage, sdp.moderate_co2_percentage, sdp.unhealthy_sensitive_co2_percentage, sdp.unhealthy_co2_percentage,
sdp.very_unhealthy_co2_percentage, sdp.hazardous_co2_percentage,
sdp.daily_avg_co2, sdp.daily_max_co2, sdp.daily_min_co2,
sdp.good_ch2o_percentage, sdp.moderate_ch2o_percentage, sdp.unhealthy_sensitive_ch2o_percentage, sdp.unhealthy_ch2o_percentage,
sdp.very_unhealthy_ch2o_percentage, sdp.hazardous_ch2o_percentage,
sdp.daily_avg_ch2o, sdp.daily_max_ch2o, sdp.daily_min_ch2o
FROM public."space-daily-pollutant-stats" AS sdp
CROSS JOIN params p
WHERE
(p.space_uuid IS NULL OR sdp.space_uuid = p.space_uuid)
AND (p.event_month IS NULL OR TO_CHAR(sdp.event_date, 'YYYY-MM') = TO_CHAR(p.event_month, 'YYYY-MM'))
ORDER BY sdp.space_uuid, sdp.event_date;

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@ -1,374 +0,0 @@
WITH params AS (
SELECT
TO_DATE(NULLIF($1, ''), 'YYYY-MM-DD') AS event_date,
$2::uuid AS space_id
),
-- Query Pipeline Starts Here
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;

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@ -1,367 +0,0 @@
-- 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;

View File

@ -1,155 +1,100 @@
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 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'
),
raw_absence_intervals AS (
SELECT
space_id,
device_id,
prev_time AS start_time,
event_time AS end_time
FROM presence_logs
WHERE prev_value = 'none' AND prev_time IS NOT NULL
-- 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'
),
absence_intervals AS (
SELECT
r.space_id,
r.device_id,
gs.day,
GREATEST(r.start_time, gs.day) AS start_time,
LEAST(r.end_time, gs.day + INTERVAL '1 day') AS end_time
FROM raw_absence_intervals r
CROSS JOIN LATERAL (
SELECT generate_series(
date_trunc('day', r.start_time),
date_trunc('day', r.end_time),
INTERVAL '1 day'
) AS day
) gs
WHERE GREATEST(r.start_time, gs.day) < LEAST(r.end_time, gs.day + INTERVAL '1 day')
-- 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
),
device_counts AS (
SELECT space_id, day, COUNT(DISTINCT device_id) AS device_count
FROM absence_intervals
GROUP BY 1, 2
-- 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
),
timeline AS (
SELECT
a.space_id,
a.day,
a.device_id,
a.start_time AS ts,
1 AS is_start
FROM absence_intervals a
UNION ALL
SELECT
a.space_id,
a.day,
a.device_id,
a.end_time AS ts,
0 AS is_start
FROM absence_intervals a
-- Step 5: Merge overlapping or adjacent intervals per day
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
),
ordered_events AS (
SELECT
space_id,
day,
ts,
is_start,
device_id,
SUM(CASE WHEN is_start = 1 THEN 1 ELSE -1 END)
OVER (PARTITION BY space_id, day, device_id ORDER BY ts) AS device_active
FROM timeline
-- 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
),
device_state_changes AS (
SELECT
space_id,
day,
ts,
SUM(CASE WHEN is_start = 1 THEN 1 ELSE -1 END)
OVER (PARTITION BY space_id, day ORDER BY ts) AS net_active_devices
FROM (
SELECT DISTINCT space_id, day, ts, is_start
FROM timeline
) t
),
absence_windows AS (
SELECT
dc.space_id,
dc.day,
ts AS start_time,
LEAD(ts) OVER (PARTITION BY dc.space_id, dc.day ORDER BY ts) AS end_time
FROM device_state_changes dsc
JOIN device_counts dc ON dc.space_id = dsc.space_id AND dc.day = dsc.day
WHERE net_active_devices = 0
),
empty_periods AS (
SELECT
space_id,
day,
EXTRACT(EPOCH FROM (end_time - start_time)) AS unoccupied_seconds
FROM absence_windows
WHERE end_time IS NOT NULL
),
unoccupied_summary AS (
SELECT
space_id,
day,
SUM(unoccupied_seconds) AS total_unoccupied_seconds
FROM empty_periods
GROUP BY space_id, day
),
-- Include device count even for days with 0 unoccupied time
all_days_with_devices AS (
SELECT
space_id,
DATE(event_time) AS day,
COUNT(DISTINCT device_id) AS device_count
FROM presence_logs
GROUP BY 1, 2
),
final_occupancy AS (
SELECT
d.space_id,
d.day,
d.device_count,
COALESCE(u.total_unoccupied_seconds, 0) AS unoccupied_seconds,
86400 - COALESCE(u.total_unoccupied_seconds, 0) AS occupied_seconds
FROM all_days_with_devices d
LEFT JOIN unoccupied_summary u
ON d.space_id = u.space_id AND d.day = u.day
-- Step 7: Calculate total occupied time per day (86400 - missing)
occupied_seconds_per_day AS (
SELECT
space_id,
missing_date as event_date,
86400 - total_missing_seconds AS total_occupied_seconds,
(86400 - total_missing_seconds)/86400*100 as occupancy_prct
FROM missing_seconds_per_day
)
, final_data as (
SELECT
space_id,
day,
device_count,
occupied_seconds,
ROUND(occupied_seconds / 86400.0 * 100, 2) AS occupancy_percentage
FROM final_occupancy
ORDER BY space_id, day)
-- Final Output
, final_data as (
SELECT space_id,
event_date,
total_occupied_seconds,
occupancy_prct
FROM occupied_seconds_per_day
ORDER BY 1,2
)
INSERT INTO public."space-daily-occupancy-duration" (
space_uuid,
@ -159,13 +104,13 @@ INSERT INTO public."space-daily-occupancy-duration" (
)
select space_id,
event_date,
occupied_seconds,
occupancy_percentage
total_occupied_seconds,
occupancy_prct
FROM final_data
ON CONFLICT (space_uuid, event_date) DO UPDATE
SET
occupancy_percentage = EXCLUDED.occupancy_percentage,
occupied_seconds = EXCLUDED.occupied_seconds;
occupancy_percentage = EXCLUDED.occupancy_percentage,
occupied_seconds = EXCLUDED.occupied_seconds;

View File

@ -2,163 +2,100 @@ 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,
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'
),
, 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'
)
raw_absence_intervals AS (
SELECT
space_id,
device_id,
prev_time AS start_time,
event_time AS end_time
FROM presence_logs
WHERE prev_value = 'none' AND prev_time IS NOT NULL
),
, 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'
)
absence_intervals AS (
SELECT
r.space_id,
r.device_id,
gs.day,
GREATEST(r.start_time, gs.day) AS start_time,
LEAST(r.end_time, gs.day + INTERVAL '1 day') AS end_time
FROM raw_absence_intervals r
CROSS JOIN LATERAL (
SELECT generate_series(
date_trunc('day', r.start_time),
date_trunc('day', r.end_time),
INTERVAL '1 day'
) AS day
) gs
WHERE GREATEST(r.start_time, gs.day) < LEAST(r.end_time, gs.day + INTERVAL '1 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
)
device_counts AS (
SELECT space_id, day, COUNT(DISTINCT device_id) AS device_count
FROM absence_intervals
GROUP BY 1, 2
),
, 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
)
timeline AS (
SELECT
a.space_id,
a.day,
a.device_id,
a.start_time AS ts,
1 AS is_start
FROM absence_intervals a
UNION ALL
SELECT
a.space_id,
a.day,
a.device_id,
a.end_time AS ts,
0 AS is_start
FROM absence_intervals a
),
, 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
)
ordered_events AS (
SELECT
space_id,
day,
ts,
is_start,
device_id,
SUM(CASE WHEN is_start = 1 THEN 1 ELSE -1 END)
OVER (PARTITION BY space_id, day, device_id ORDER BY ts) AS device_active
FROM timeline
),
, 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
)
device_state_changes AS (
SELECT
space_id,
day,
ts,
SUM(CASE WHEN is_start = 1 THEN 1 ELSE -1 END)
OVER (PARTITION BY space_id, day ORDER BY ts) AS net_active_devices
FROM (
SELECT DISTINCT space_id, day, ts, is_start
FROM timeline
) t
),
, occupied_seconds_per_day AS (
SELECT
space_id,
missing_date as event_date,
86400 - total_missing_seconds AS total_occupied_seconds,
(86400 - total_missing_seconds)/86400*100 as occupancy_percentage
FROM missing_seconds_per_day
)
absence_windows AS (
SELECT
dc.space_id,
dc.day,
ts AS start_time,
LEAD(ts) OVER (PARTITION BY dc.space_id, dc.day ORDER BY ts) AS end_time
FROM device_state_changes dsc
JOIN device_counts dc ON dc.space_id = dsc.space_id AND dc.day = dsc.day
WHERE net_active_devices = 0
),
empty_periods AS (
SELECT
space_id,
day,
EXTRACT(EPOCH FROM (end_time - start_time)) AS unoccupied_seconds
FROM absence_windows
WHERE end_time IS NOT NULL
),
unoccupied_summary AS (
SELECT
space_id,
day,
SUM(unoccupied_seconds) AS total_unoccupied_seconds
FROM empty_periods
GROUP BY space_id, day
),
-- Include device count even for days with 0 unoccupied time
all_days_with_devices AS (
SELECT
space_id,
DATE(event_time) AS day,
COUNT(DISTINCT device_id) AS device_count
FROM presence_logs
GROUP BY 1, 2
),
final_occupancy AS (
SELECT
d.space_id,
d.day,
d.device_count,
COALESCE(u.total_unoccupied_seconds, 0) AS unoccupied_seconds,
86400 - COALESCE(u.total_unoccupied_seconds, 0) AS occupied_seconds
FROM all_days_with_devices d
LEFT JOIN unoccupied_summary u
ON d.space_id = u.space_id AND d.day = u.day
),
final_data as(
SELECT
space_id,
day,
device_count,
occupied_seconds,
ROUND(occupied_seconds / 86400.0 * 100, 2) AS occupancy_percentage
FROM final_occupancy s
JOIN params p
ON p.space_id = s.space_id
AND p.event_date = s.event_date
ORDER BY space_id, DAY)
, final_data as (
SELECT
occupied_seconds_per_day.space_id,
occupied_seconds_per_day.event_date,
total_occupied_seconds,
occupancy_percentage
FROM occupied_seconds_per_day
JOIN params p
ON p.space_id = occupied_seconds_per_day.space_id
AND p.event_date = occupied_seconds_per_day.event_date
)
INSERT INTO public."space-daily-occupancy-duration" (
@ -168,13 +105,12 @@ INSERT INTO public."space-daily-occupancy-duration" (
occupancy_percentage
)
SELECT
space_id,
event_date,
occupied_seconds,
occupancy_percentage
space_id,
event_date,
total_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;
occupied_seconds = EXCLUDED.occupied_seconds,
occupancy_percentage = EXCLUDED.occupancy_percentage;

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@ -16,5 +16,4 @@ WITH params AS (
WHERE A.device_uuid::text = ANY(P.device_ids)
AND (P.month IS NULL
OR date_trunc('month', A.event_date) = P.month
);
)

View File

@ -12,8 +12,4 @@ 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
ORDER BY space_uuid, event_date

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@ -1,362 +0,0 @@
-- 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;

View File

@ -1,275 +0,0 @@
-- 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;

View File

@ -1,168 +1,91 @@
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 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'
),
-- Intervals when device was in 'absence' (between prev_time and event_time when value='none')
raw_absence_intervals AS (
SELECT
space_id,
device_id,
prev_time AS start_time,
event_time AS end_time
FROM presence_logs
WHERE value <> 'none'
AND prev_value = 'none'
AND prev_time IS NOT NULL
-- 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'
),
-- Split intervals that span multiple days into day-specific chunks
absence_intervals AS (
SELECT
r.space_id,
r.device_id,
GREATEST(r.start_time, gs.day::timestamp) AS start_time,
LEAST(r.end_time, (gs.day + INTERVAL '1 day' - INTERVAL '1 second')::timestamp) AS end_time
FROM raw_absence_intervals r
CROSS JOIN LATERAL (
SELECT generate_series(
date_trunc('day', r.start_time),
date_trunc('day', r.end_time),
INTERVAL '1 day'
) AS day
) gs
WHERE GREATEST(r.start_time, gs.day::timestamp) < LEAST(r.end_time, (gs.day + INTERVAL '1 day')::timestamp)
-- 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
),
-- FIXED: Count devices based on presence_logs OR absence_intervals
devices_per_day AS (
SELECT
space_id,
day,
COUNT(DISTINCT device_id) AS device_count
FROM (
-- Devices that logged events on that day
SELECT space_id, DATE(event_time) AS day, device_id
FROM presence_logs
UNION
-- Devices that had absence intervals on that day
SELECT space_id, DATE(start_time) AS day, device_id
FROM absence_intervals
) combined
GROUP BY space_id, day
-- 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
),
-- Step 5: Merge overlapping or adjacent intervals per day
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
),
-- For multi-device spaces, find all time periods when ALL devices were absent
multi_device_unoccupied AS (
WITH device_absence_per_day AS (
SELECT
a.space_id,
DATE(a.start_time) AS day,
a.device_id,
a.start_time,
a.end_time,
d.device_count
FROM absence_intervals a
JOIN devices_per_day d ON a.space_id = d.space_id AND DATE(a.start_time) = d.day
WHERE d.device_count > 1
),
-- Generate time slots for each day with multiple devices
time_ranges AS (
SELECT
space_id,
day,
day::timestamp AS range_start,
(day + INTERVAL '1 day')::timestamp AS range_end,
device_count
FROM devices_per_day
WHERE device_count > 1
),
-- Find all time periods when all devices were absent
all_devices_absent AS (
SELECT
t.space_id,
t.day,
t.range_start,
t.range_end,
t.device_count,
-- Find the latest start time of all devices' absence intervals
MAX(a.start_time) OVER (PARTITION BY t.space_id, t.day) AS max_start_time,
-- Find the earliest end time of all devices' absence intervals
MIN(a.end_time) OVER (PARTITION BY t.space_id, t.day) AS min_end_time
FROM time_ranges t
LEFT JOIN device_absence_per_day a ON
t.space_id = a.space_id AND
t.day = a.day
GROUP BY t.space_id, t.day, t.range_start, t.range_end, t.device_count, a.start_time, a.end_time
)
-- Calculate total unoccupied seconds when all devices were absent
SELECT
space_id,
day,
CASE
WHEN max_start_time IS NULL OR min_end_time IS NULL THEN 0
WHEN max_start_time >= min_end_time THEN 0
ELSE EXTRACT(EPOCH FROM (LEAST(min_end_time, range_end) - GREATEST(max_start_time, range_start)))
END AS unoccupied_seconds
FROM all_devices_absent
GROUP BY space_id, day, range_start, range_end, device_count, max_start_time, min_end_time
HAVING COUNT(*) = device_count -- Only include periods when all devices were absent
)
,
-- 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
),
-- Calculate unoccupied time for spaces with single device reporting
single_device_unoccupied AS (
SELECT
a.space_id,
DATE(a.start_time) AS day,
SUM(EXTRACT(EPOCH FROM (a.end_time - a.start_time))) AS unoccupied_seconds
FROM absence_intervals a
JOIN devices_per_day d ON a.space_id = d.space_id AND DATE(a.start_time) = d.day
WHERE d.device_count = 1
GROUP BY a.space_id, DATE(a.start_time)
)
,
-- Combine results from both single and multi-device cases
combined_unoccupied AS (
SELECT space_id, day, unoccupied_seconds FROM single_device_unoccupied
UNION ALL
SELECT space_id, day, unoccupied_seconds FROM multi_device_unoccupied
),
-- Calculate total occupied time per space per day
daily_occupancy AS (
SELECT
space_id,
day,
-- Total seconds in day (86400) minus unoccupied seconds
86400 - COALESCE(SUM(unoccupied_seconds), 0) AS occupied_seconds
FROM combined_unoccupied
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
)
-- Final result
SELECT
space_id,
day,
occupied_seconds,
-- Also include percentage for convenience
ROUND((occupied_seconds / 86400.0) * 100, 2) AS occupancy_percentage
FROM daily_occupancy
ORDER BY space_id, day;
-- Final Output
SELECT *
FROM occupied_seconds_per_day
ORDER BY 1,2;

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@ -1,18 +0,0 @@
export function calculateAQI(pm2_5: number): number {
const breakpoints = [
{ pmLow: 0.0, pmHigh: 12.0, aqiLow: 0, aqiHigh: 50 },
{ pmLow: 12.1, pmHigh: 35.4, aqiLow: 51, aqiHigh: 100 },
{ pmLow: 35.5, pmHigh: 55.4, aqiLow: 101, aqiHigh: 150 },
{ pmLow: 55.5, pmHigh: 150.4, aqiLow: 151, aqiHigh: 200 },
{ pmLow: 150.5, pmHigh: 250.4, aqiLow: 201, aqiHigh: 300 },
{ pmLow: 250.5, pmHigh: 500.4, aqiLow: 301, aqiHigh: 500 },
];
const bp = breakpoints.find((b) => pm2_5 >= b.pmLow && pm2_5 <= b.pmHigh);
if (!bp) return pm2_5 > 500.4 ? 500 : 0; // Handle out-of-range values
return Math.round(
((bp.aqiHigh - bp.aqiLow) / (bp.pmHigh - bp.pmLow)) * (pm2_5 - bp.pmLow) +
bp.aqiLow,
);
}

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@ -1,11 +0,0 @@
import { DeviceEntity } from '../modules/device/entities';
export function addSpaceUuidToDevices(
devices: DeviceEntity[],
spaceUuid: string,
): DeviceEntity[] {
return devices.map((device) => {
(device as any).spaceUuid = spaceUuid;
return device;
});
}

View File

@ -38,7 +38,6 @@ import { HealthModule } from './health/health.module';
import { winstonLoggerOptions } from '../libs/common/src/logger/services/winston.logger';
import { OccupancyModule } from './occupancy/occupancy.module';
import { WeatherModule } from './weather/weather.module';
@Module({
imports: [
ConfigModule.forRoot({
@ -80,7 +79,6 @@ import { WeatherModule } from './weather/weather.module';
PowerClampModule,
HealthModule,
OccupancyModule,
WeatherModule,
],
providers: [
{

View File

@ -23,7 +23,6 @@ import { SpaceService } from 'src/space/services';
import { SpaceRepository } from '@app/common/modules/space';
import { DeviceEntity } from '@app/common/modules/device/entities';
import { SpaceEntity } from '@app/common/modules/space/entities/space.entity';
import { addSpaceUuidToDevices } from '@app/common/util/device-utils';
@Injectable()
export class CommunityService {
@ -337,7 +336,7 @@ export class CommunityService {
visitedSpaceUuids.add(space.uuid);
if (space.devices?.length) {
allDevices.push(...addSpaceUuidToDevices(space.devices, space.uuid));
allDevices.push(...space.devices);
}
if (space.children?.length) {

View File

@ -1,5 +1,4 @@
import AuthConfig from './auth.config';
import AppConfig from './app.config';
import JwtConfig from './jwt.config';
import WeatherOpenConfig from './weather.open.config';
export default [AuthConfig, AppConfig, JwtConfig, WeatherOpenConfig];
export default [AuthConfig, AppConfig, JwtConfig];

View File

@ -1,9 +0,0 @@
import { registerAs } from '@nestjs/config';
export default registerAs(
'openweather-config',
(): Record<string, any> => ({
OPEN_WEATHER_MAP_API_KEY: process.env.OPEN_WEATHER_MAP_API_KEY,
WEATHER_API_URL: process.env.WEATHER_API_URL,
}),
);

View File

@ -67,7 +67,6 @@ import { ProjectParam } from '../dtos';
import { BatchDeviceTypeEnum } from '@app/common/constants/batch-device.enum';
import { DeviceTypeEnum } from '@app/common/constants/device-type.enum';
import { CommunityRepository } from '@app/common/modules/community/repositories';
import { addSpaceUuidToDevices } from '@app/common/util/device-utils';
@Injectable()
export class DeviceService {
@ -1787,8 +1786,7 @@ export class DeviceService {
throw new NotFoundException('Space not found');
}
const allDevices: DeviceEntity[] = [];
allDevices.push(...addSpaceUuidToDevices(space.devices, space.uuid));
const allDevices: DeviceEntity[] = [...space.devices];
// Recursive fetch function
const fetchChildren = async (parentSpace: SpaceEntity) => {
@ -1798,7 +1796,7 @@ export class DeviceService {
});
for (const child of children) {
allDevices.push(...addSpaceUuidToDevices(child.devices, child.uuid));
allDevices.push(...child.devices);
if (child.children.length > 0) {
await fetchChildren(child);
@ -1837,7 +1835,7 @@ export class DeviceService {
visitedSpaceUuids.add(space.uuid);
if (space.devices?.length) {
allDevices.push(...addSpaceUuidToDevices(space.devices, space.uuid));
allDevices.push(...space.devices);
}
if (space.children?.length) {

View File

@ -18,7 +18,6 @@ import { SpaceRepository } from '@app/common/modules/space';
import { DeviceEntity } from '@app/common/modules/device/entities';
import { SpaceEntity } from '@app/common/modules/space/entities/space.entity';
import { GetDevicesBySpaceDto } from '../dtos/device.space.dto';
import { addSpaceUuidToDevices } from '@app/common/util/device-utils';
@Injectable()
export class SpaceDeviceService {
@ -161,8 +160,7 @@ export class SpaceDeviceService {
throw new NotFoundException('Space not found');
}
const allDevices: DeviceEntity[] = [];
allDevices.push(...addSpaceUuidToDevices(space.devices, space.uuid));
const allDevices: DeviceEntity[] = [...space.devices];
// Recursive fetch function
const fetchChildren = async (parentSpace: SpaceEntity) => {
@ -172,7 +170,7 @@ export class SpaceDeviceService {
});
for (const child of children) {
allDevices.push(...addSpaceUuidToDevices(child.devices, child.uuid));
allDevices.push(...child.devices);
if (child.children.length > 0) {
await fetchChildren(child);

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@ -213,8 +213,8 @@ export class SpaceService {
{ incomingConnectionDisabled: false },
)
.leftJoinAndSelect('space.productAllocations', 'productAllocations')
// .leftJoinAndSelect('productAllocations.tags', 'tags')
// .leftJoinAndSelect('productAllocations.product', 'product')
.leftJoinAndSelect('productAllocations.tags', 'tags')
.leftJoinAndSelect('tags.product', 'tagProduct')
.leftJoinAndSelect(
'space.subspaces',
'subspaces',
@ -225,11 +225,8 @@ export class SpaceService {
'subspaces.productAllocations',
'subspaceProductAllocations',
)
// .leftJoinAndSelect('subspaceProductAllocations.tags', 'subspaceTag')
// .leftJoinAndSelect(
// 'subspaceProductAllocations.product',
// 'subspaceProduct',
// )
.leftJoinAndSelect('subspaceProductAllocations.tags', 'subspaceTags')
.leftJoinAndSelect('subspaceTags.product', 'subspaceTagProduct')
.leftJoinAndSelect('space.spaceModel', 'spaceModel')
.where('space.community_id = :communityUuid', { communityUuid })
.andWhere('space.spaceName != :orphanSpaceName', {
@ -267,7 +264,9 @@ export class SpaceService {
}),
);
}
const spaceHierarchy = this.buildSpaceHierarchy(spaces);
const transformedSpaces = spaces.map(this.transformSpace);
const spaceHierarchy = this.buildSpaceHierarchy(transformedSpaces);
return new SuccessResponseDto({
message: `Spaces in community ${communityUuid} successfully fetched in hierarchy`,
@ -327,13 +326,13 @@ export class SpaceService {
'incomingConnections.disabled = :incomingConnectionDisabled',
{ incomingConnectionDisabled: false },
)
// .leftJoinAndSelect(
// 'space.tags',
// 'tags',
// 'tags.disabled = :tagDisabled',
// { tagDisabled: false },
// )
// .leftJoinAndSelect('tags.product', 'tagProduct')
.leftJoinAndSelect(
'space.tags',
'tags',
'tags.disabled = :tagDisabled',
{ tagDisabled: false },
)
.leftJoinAndSelect('tags.product', 'tagProduct')
.leftJoinAndSelect(
'space.subspaces',
'subspaces',
@ -346,7 +345,7 @@ export class SpaceService {
'subspaceTags.disabled = :subspaceTagsDisabled',
{ subspaceTagsDisabled: false },
)
// .leftJoinAndSelect('subspaceTags.product', 'subspaceTagProduct')
.leftJoinAndSelect('subspaceTags.product', 'subspaceTagProduct')
.where('space.community_id = :communityUuid', { communityUuid })
.andWhere('space.spaceName != :orphanSpaceName', {
orphanSpaceName: ORPHAN_SPACE_NAME,

View File

@ -1 +0,0 @@
export * from './weather.controller';

View File

@ -1,28 +0,0 @@
import { Controller, Get, Query } from '@nestjs/common';
import { ApiOperation, ApiTags } from '@nestjs/swagger';
import { EnableDisableStatusEnum } from '@app/common/constants/days.enum';
import { ControllerRoute } from '@app/common/constants/controller-route'; // Assuming this is where the routes are defined
import { WeatherService } from '../services';
import { BaseResponseDto } from '@app/common/dto/base.response.dto';
import { GetWeatherDetailsDto } from '../dto/get.weather.dto';
@ApiTags('Weather Module')
@Controller({
version: EnableDisableStatusEnum.ENABLED,
path: ControllerRoute.WEATHER.ROUTE, // use the static route constant
})
export class WeatherController {
constructor(private readonly weatherService: WeatherService) {}
@Get()
@ApiOperation({
summary: ControllerRoute.WEATHER.ACTIONS.FETCH_WEATHER_DETAILS_SUMMARY,
description:
ControllerRoute.WEATHER.ACTIONS.FETCH_WEATHER_DETAILS_DESCRIPTION,
})
async fetchWeatherDetails(
@Query() query: GetWeatherDetailsDto,
): Promise<BaseResponseDto> {
return await this.weatherService.fetchWeatherDetails(query);
}
}

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@ -1,21 +0,0 @@
import { ApiProperty } from '@nestjs/swagger';
import { Type } from 'class-transformer';
import { IsNumber } from 'class-validator';
export class GetWeatherDetailsDto {
@ApiProperty({
description: 'Latitude coordinate',
example: 35.6895,
})
@IsNumber()
@Type(() => Number)
lat: number;
@ApiProperty({
description: 'Longitude coordinate',
example: 139.6917,
})
@IsNumber()
@Type(() => Number)
lon: number;
}

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@ -1 +0,0 @@
export * from './weather.service';

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@ -1,51 +0,0 @@
import { HttpException, HttpStatus, Injectable } from '@nestjs/common';
import { HttpService } from '@nestjs/axios';
import { ConfigService } from '@nestjs/config';
import { firstValueFrom } from 'rxjs';
import { GetWeatherDetailsDto } from '../dto/get.weather.dto';
import { calculateAQI } from '@app/common/util/calculate.aqi';
import { BaseResponseDto } from '@app/common/dto/base.response.dto';
import { SuccessResponseDto } from '@app/common/dto/success.response.dto';
@Injectable()
export class WeatherService {
private readonly weatherApiUrl: string;
constructor(
private readonly configService: ConfigService,
private readonly httpService: HttpService,
) {
this.weatherApiUrl = this.configService.get<string>('WEATHER_API_URL');
}
async fetchWeatherDetails(
query: GetWeatherDetailsDto,
): Promise<BaseResponseDto> {
try {
const { lat, lon } = query;
const weatherApiKey = this.configService.get<string>(
'OPEN_WEATHER_MAP_API_KEY',
);
const url = `${this.weatherApiUrl}/current.json?key=${weatherApiKey}&q=${lat},${lon}&aqi=yes`;
const response = await firstValueFrom(this.httpService.get(url));
const pm2_5 = response.data.current.air_quality.pm2_5; // Raw PM2.5 (µg/m³)
return new SuccessResponseDto({
message: `Weather details fetched successfully`,
data: {
aqi: calculateAQI(pm2_5), // Converted AQI (0-500)
temperature: response.data.current.temp_c,
humidity: response.data.current.humidity,
},
statusCode: HttpStatus.OK,
});
} catch (error) {
console.log(`Error fetching weather data: ${error}`);
throw new HttpException(
`Api can't handle these lat and lon values`,
error.response?.status || HttpStatus.INTERNAL_SERVER_ERROR,
);
}
}
}

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@ -1,12 +0,0 @@
import { Module } from '@nestjs/common';
import { ConfigModule } from '@nestjs/config';
import { HttpModule } from '@nestjs/axios'; // <-- Import this!
import { WeatherController } from './controllers';
import { WeatherService } from './services';
@Module({
imports: [ConfigModule, HttpModule],
controllers: [WeatherController],
providers: [WeatherService],
})
export class WeatherModule {}