n8n Museum Microclimate Excursion Alerts (OpenAI, Jira, Slack)

Keep your museum environment in check—automated microclimate excursion alerts every 30 minutes

This n8n workflow monitors museum microclimate sensors, detects meaningful temperature and relative-humidity excursions against prior readings stored in Postgres, and—when risk is detected—uses OpenAI to produce a structured conservation-risk assessment. It then creates a Jira task, posts a Slack alert, and archives JSON evidence to Google Drive.

What this workflow does

• Runs on a 30-minute schedule to sweep configured museum zones and fetch current sensor readings via a vendor HTTP API.

• Loads prior state from Postgres for the same zones, then computes per-zone deltas for temperature and relative humidity.

• Filters for meaningful excursions using your configured RH and temperature change thresholds (only readings that exceed limits proceed).

• For each changed reading, calls OpenAI (Chat model via the “Information Extractor”) to extract a structured conservation-risk assessment including evidence and a recommended response window.

• Calculates a severity score from the AI risk output and measured deltas, assigning a route: watch, urgent, or critical.

• Depending on route, creates a Jira issue, posts to Slack, and/or uploads a JSON evidence file to Google Drive.

• Writes a fresh snapshot back to Postgres to maintain an auditable record for the next run.

Use cases

• Automatic conservation triage when museum temperature/RH drifts beyond acceptable thresholds.

• Auditable incident reporting with Google Drive JSON evidence and a persistent Postgres snapshot history.

• Operational visibility for facilities or collections teams via Slack, plus Jira tickets for tracked follow-up.

Technical details

• Integrations / credentials: Sensor vendor HTTP API, Postgres, OpenAI, Jira, Slack, Google Drive.

• n8n nodes used (as listed): if, set, code, jira, merge, slack.

• Built for n8n automation engineers and SaaS operators who need reliable, threshold-based microclimate excursion detection with AI-assisted risk extraction.