| name | n8n-photo-report |
| description | Automate construction photo report generation using n8n with AI-powered image analysis. |
| homepage | https://datadrivenconstruction.io |
| metadata | {"openclaw":{"emoji":"🔧","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":"[Truncated]"}}} |
n8n Photo Report Automation
Business Case
Site photos require organization, analysis, and reporting. This workflow automates photo collection, AI analysis, and report generation.
Workflow Overview
[Photo Upload] → [AI Analysis] → [Categorization] → [Report Generation] → [Distribution]
n8n Workflow Configuration
1. Photo Input Triggers
{
"nodes": [
{
"name": "Photo Webhook",
"type": "n8n-nodes-base.webhook",
"parameters": {
"httpMethod": "POST",
"path": "photo-upload",
"options": {
"binaryData": true
}
}
},
{
"name": "Watch Dropbox Folder",
"type": "n8n-nodes-base.dropbox",
"parameters": {
"operation": "listFolder",
"path": "/SitePhotos/{{$today}}"
}
}
]
}
2. AI Image Analysis
{
"name": "Analyze with Claude Vision",
"type": "n8n-nodes-base.httpRequest",
"parameters": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"x-api-key": "={{$env.ANTHROPIC_API_KEY}}",
"anthropic-version": "2023-06-01"
},
"body": {
"model": "claude-3-5-sonnet-20241022",
"max_tokens": 1024,
"messages": [{
"role": "user",
"content": [
{
"type"
3. Categorize and Store
{
"nodes": [
{
"name": "Parse AI Response",
"type": "n8n-nodes-base.code",
"parameters": {
"jsCode": "const response = JSON.parse($json.content[0].text);\n\nreturn [{\n json: {\n filename: $('Photo Webhook').first().json.filename,\n timestamp: new Date().toISOString(),\n activity: response.work_activity,\n completion: response.completion_status,\n safety_issues: response.safety_concerns,\n weather: response.weather,\n category: response.work_activity.includes('concrete') ? 'CONCRETE' :\n response.work_activity.includes('steel') ? 'STEEL' :\n response.work_activity.includes('mep') ? 'MEP' : 'GENERAL'\n }\n}];"
}
},
{
"name": "Store in Airtable",
"type": "n8n-nodes-base.airtable",
"parameters": {
"operation": "create",
"table": "Site Photos",
"fields": {
"Filename"
4. Generate Photo Report
{
"nodes": [
{
"name": "Schedule Report",
"type": "n8n-nodes-base.scheduleTrigger",
"parameters": {
"rule": {"interval": [{"field": "cronExpression", "expression": "0 18 * * 1-5"}]}
}
},
{
"name": "Get Today Photos",
"type": "n8n-nodes-base.airtable",
"parameters": {
"operation": "list",
"table": "Site Photos",
"filterByFormula"
5. Distribution
{
"name": "Send Report Email",
"type": "n8n-nodes-base.emailSend",
"parameters": {
"toEmail": "={{$env.PHOTO_REPORT_RECIPIENTS}}",
"subject": "Site Photo Report - {{$json.date}} ({{$json.total_photos}} photos)",
"html": "<h2>Daily Photo Report</h2><p>Total Photos: {{$json.total_photos}}</p><h3>Safety Issues: {{$json.safety_count}}</h3>{{#if $json.safety_issues.length}}<ul>{{#each $json.safety_issues}}<li>{{photo}}: {{issue}}</li>{{/each}}</ul>{{/if}}"
}
}
Python Helper
import requests
import base64
def upload_photo_to_workflow(image_path: str, webhook_url: str, metadata: dict):
"""Upload photo to n8n workflow."""
with open(image_path, 'rb') as f:
image_data = base64.b64encode(f.read()).decode()
payload = {
'filename': image_path.split('/')[-1],
'image_data': image_data,
'project_id': metadata.get('project_id'),
'location': metadata.get('location'),
'captured_by': metadata.get('captured_by')
}
response = requests.post(webhook_url, json=payload)
return response.json()
def batch_upload_photos(photo_paths: list, webhook_url: str, project_id: str):
"""Batch upload multiple photos."""
results = []
for path in photo_paths:
result = upload_photo_to_workflow(path, webhook_url, {'project_id': project_id})
results.append(result)
return results
Quick Start
- Import workflow to n8n
- Configure API keys:
ANTHROPIC_API_KEY for Claude Vision- Airtable credentials
- Email configuration
- Create Airtable base with "Site Photos" table
- Test with sample photo upload
Resources
