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Air Quality Observations – IQR Outlier Flags
x402
Air Quality Observations – IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Applies interquartile range (IQR) outlier detection to a batch of air quality observation records and returns a flag for each row indicating whether it is an outlier.
Price / call$0.01
Success—
StatusUnknown
How this service works
Air quality observations - IQR outlier flags: IQR outlier flags for Air quality observations. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded iqr outlier flags report.
Output
Returns a report per submitted row indicating whether each record is flagged as an IQR outlier for the chosen field (pm25 or humidity_percent), based purely on local descriptive statistics computed over the supplied dataset. No external enrichment or forecasting is applied.
Example use cases
Detecting rogue sensor spikes in PM2.5 data
“I have a week of PM2.5 readings from 30 air quality stations and I think a few sensors are misbehaving. Can you run IQR outlier flagging on the pm25 field across all rows and tell me which readings are flagged as outliers?”
Humidity anomaly audit before a report
“Before I submit our monthly environmental report, can you check this batch of humidity_percent readings from our monitoring stations for any statistical outliers using IQR? Here are the 80 rows with station, date, and humidity values.”
Automated QA pass on ingested sensor data
“We just ingested a fresh batch of air quality observations from our field stations — can you run an IQR outlier check on the pm25 values for all 150 rows and return which row IDs are flagged so I can quarantine them before analysis?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-air-quality-observations-outliers?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local IQR-based outlier detection on a bounded batch (up to 200 rows) of air quality observations without requiring external enrichment, forecasting, or ML inference. It is ideal for data QA pipelines, pre-report validation passes, and sensor-data health checks where a simple statistical flagging approach is sufficient and cost must stay low ($0.01 per call).
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds batch limit
- Missing required fields (row_id, station, date, pm25, humidity_percent) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- Invalid field enum value (must be 'pm25' or 'humidity_percent') — error
- All values null for chosen field — IQR computation undefined
- Payment not included or insufficient — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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