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AI agent for environmental engineers

Air Monitor Data Validation Agent

A validated data set in which every flagged reading has a code and a documented reason.

Quality controlData cleanupScience and research
See how it worksGet access
Air Monitor Data Validation Agent: what goes in, what the agent does and what you get

What it does

A monitor logs a thousand readings a day and some are spikes from a power glitch, some are drift between calibrations and some are plain gaps. This agent flags drift, spikes and gaps in the raw data and compares them to the calibration and maintenance records. It also compares to nearby monitors to see whether a spike is real or local. It proposes a validation code for each flagged period, such as valid, invalid with reason or estimated. When calibration records arrive late, it revalidates affected periods. You approve the validated data set. Edge case: a spike matching a nearby monitor's pattern is kept as a real event.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueApprovedNoNo 1 STARTS WHEN Data downloaded 2 USES A TOOL Load raw data and calibration records 3 DOES Flag spikes, flatlines, gaps and drift 4 USES A TOOL Compare flagged periods with nearby monitors 5 DOES Propose a validation code and reason for each period 6 CHECKS THE RESULT Does each invalid period have a calibration ormaintenance record that explains it? If not: mark it pending and request the record from thetechnician. Back to step 3. 7 YOU APPROVE Engineer approves the pending requests 8 USES A TOOL Load the records received and revalidate affectedperiods 9 CHECKS THE RESULT Do the codes still apply after revalidation? If not: change the codes and recheck neighboringperiods. Back to step 5. 10 YOU APPROVE Engineer approves the validated set 11 RESULT Validated data and log
Read the steps as a list
  1. Data downloaded
  2. Load raw data and calibration records
  3. Flag spikes, flatlines, gaps and drift
  4. Compare flagged periods with nearby monitors
  5. Propose a validation code and reason for each period
  6. Does each invalid period have a calibration or maintenance record that explains it?If not: mark it pending and request the record from the technician. Back to step 3.
  7. Engineer approves the pending requestsThe agent waits here for your OK.
  8. Load the records received and revalidate affected periods
  9. Do the codes still apply after revalidation?If not: change the codes and recheck neighboring periods. Back to step 5.
  10. Engineer approves the validated setThe agent waits here for your OK.
  11. Validated data and log

How it decides

Flags come from rules for range, rate of change, flatlines and drift. Codes follow the validation rules and the calibration status.

  • Change of more than 5 times the standard deviation in one step with no neighbor match: invalid spike
  • Calibration drift above the allowed limit: invalidate back to the last good check
  • Same value for 6 hours: flatline, invalid
  • Spike matched by a nearby monitor: keep as a real event

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Spike rule (default 5 standard deviations)
  • Drift limit
  • Flatline hours
  • Neighbor monitors
  • Validation code list

What keeps you in control

It always asks you first

  • The validated data set
  • Any estimated values

Hard limits

  • Never delete raw data
  • Never estimate data without approval

It stops when

  • Done: validated set approved
  • Stop: calibration records missing for the period

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensFor March, the agent flagged 41 spikes and 3 gaps in PM2.5. Nine spikes matched a neighboring monitor and were kept. A drift of 2.4 micrograms appeared after the 12 March check, but there was no record of a calibration, so the check failed and it requested the log. The record showed a bad span on 12 March. The agent invalidated 14 to 18 March. The engineer approved with 94 percent capture.

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