(5/5)

[3/3] Anomaly detection tool (crops dataset)

Automated workflow: [3/3] Anomaly detection tool (crops dataset). This workflow integrates 6 different services: stickyNote, httpRequest, code, set, stopAndError. It contains 25 nodes and follows best practices for error handling and security.

Integrations Used (2)

HTTP Request

Executeworkflow

Workflow Structure (9 nodes)

100%

Execute Workflow Trigger

Set

Image URL hardcode

Set

Variables for medoids

Http Request

Total Points in Collection

Http Request

Each Crop Counts

Set

Info About Crop Labeled Clusters

Http Request

Embed image

Http Request

Get similarity of medoids

Code

Compare scores

Node Types:

http

code

transform

trigger

Requires credentials

Prerequisites

Required Credentials (2)

HTTP Header Auth

Used by: Embed image

Docs

Qdrant

Used by: Get similarity of medoids, Total Points in Collection +1 more

Docs

Complexity

Complex

Advanced features used. Requires n8n experience.

Setup time: ~35 min

Score: 44/100

Custom Code

When to Use This Workflow

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

Time Savings

Replace repetitive manual tasks with reliable automation.

Reclaim hours every week for higher-value work.

Error Reduction

Eliminate human error from routine processes with consistent automation.

Improve accuracy and reliability across your workflows.

workflow.json

{
  "id": "G8jRDBvwsMkkMiLN",
  "meta": {
    "instanceId": "workflow-e3248bda",
    "versionId": "1.0.0",
    "createdAt": "2025-09-29T07:07:46.330806",
    "updatedAt": "2025-09-29T07:07:46.330826",
    "owner": "n8n-user",
    "license": "MIT",
    "category": "automation",
    "status": "active",
    "priority": "high",
    "environment": "production"
  },
  "name": "[3/3] Anomaly detection tool (crops dataset)",
  "tags": [
    "automation",
    "n8n",
    "production-ready",
    "excellent",
...