Anomaly detection tool for crops dataset

• Detect anomalies in crop images for agricultural monitoring.
• Identify unknown crop types using image analysis.
• Enhance crop management strategies with data-driven insights.

Receive an image URL input through a trigger. Embed the image using a specialized model to generate vectors. Query a Qdrant database to compare the image vectors against known crop data. Analyze similarity scores to determine if the image is anomalous or matches known crops.

1. 1
   Import the workflow template into your n8n instance.
2. 2
   Configure the necessary credentials for Qdrant and Voyage AI.
3. 3
   Set up the Execute Workflow Trigger to receive image URLs.
4. 4
   Test the workflow with sample crop images to ensure functionality.