PostgreSQL IoT Sensor Data Processing with Analytics

This workflow automates IoT sensor data ingestion into a PostgreSQL database, processing both simulated and external sensor data with validation and analytics logging. Key nodes include Schedule Trigger, Webhook, Condition, Switch, Set, SplitOut, Postgres, HTTP Request, Aggregate, and Respond to Webhook, using the PostgreSQL API for data storage. To set up, install n8n from n8n.io for self-hosting or use cloud.n8n.io for a hosted solution. Create a PostgreSQL database with a 'dhc_sensor_data' table (columns: sensor_id, sensor_type, value, unit, location, time_stamp, quality_score, notification, batch_id, created_at). Obtain PostgreSQL credentials (host, database, user, password) and configure them in the Postgres node ('PostgreSQL Ingestion'). Set the Webhook node’s path to 'sensor-data-ingestion' with HTTPS enabled and add a custom X-API-Key header for authentication. For the HTTP Request node ('Metrics Tracker'), configure your analytics endpoint URL and API key if required. The Schedule Trigger runs every 5 minutes for simulated data. The Set node ('Simulated Sensor Data') generates random humidity sensor data for testing. Test by sending a POST request to the Webhook URL with a JSON body containing a 'sensors' array (e.g., {sensor_id, value, sensor_type, location}). Verify the Respond to Webhook node for 'success: true', checking recordsIngested and successfulIngestions. Query the PostgreSQL database to confirm inserted records. If errors occur, such as 401 (missing API key), ensure the X-API-Key header is valid. For 400 errors (invalid data), verify the sensors array format. A 500 error (database failure) indicates incorrect PostgreSQL credentials or table structure. Deploy by activating the Schedule Trigger for continuous ingestion or integrating the Webhook with IoT devices. Monitor the Analytics Logger node for executionId and recordsIngested. This setup ensures reliable, secure IoT data ingestion with real-time analytics.