The workflow JSON
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{
"name": "01 Data Ingestion",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"field": "hours",
"hoursInterval": 1
}
]
}
},
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1,
"position": [
250,
300
]
},
{
"parameters": {
"jsCode": "return [\n { id: 'north-india', lat: 28.6, lon: 77.2, label: 'North India' },\n { id: 'south-india', lat: 12.9, lon: 77.6, label: 'South India' },\n { id: 'west-india', lat: 23.0, lon: 72.6, label: 'West India' },\n { id: 'east-india', lat: 22.5, lon: 88.3, label: 'East India' },\n { id: 'central-india', lat: 21.1, lon: 79.1, label: 'Central India' },\n { id: 'ne-india', lat: 26.1, lon: 91.7, label: 'NE India' }\n];"
},
"name": "Define Regions",
"type": "n8n-nodes-base.code",
"typeVersion": 1,
"position": [
450,
300
]
},
{
"parameters": {
"url": "https://api.open-meteo.com/v1/forecast",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "latitude",
"value": "={{$json.lat}}"
},
{
"name": "longitude",
"value": "={{$json.lon}}"
},
{
"name": "hourly",
"value": "temperature_2m,precipitation,windspeed_10m,relativehumidity_2m,surface_pressure,cloudcover,et0_fao_evapotranspiration"
},
{
"name": "daily",
"value": "temperature_2m_max,temperature_2m_min,precipitation_sum,windspeed_10m_max"
},
{
"name": "past_days",
"value": "30"
},
{
"name": "forecast_days",
"value": "7"
},
{
"name": "timezone",
"value": "auto"
}
]
}
},
"name": "Fetch Open-Meteo",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
650,
300
]
},
{
"parameters": {
"jsCode": "const data = $input.item.json;\nconst hourly_rows = data.hourly.time.map((time, i) => ({\n time,\n region_id: $('Define Regions').item.json.id,\n temperature_2m: data.hourly.temperature_2m[i],\n precipitation: data.hourly.precipitation[i]\n}));\nreturn { hourly_rows };"
},
"name": "Flatten Data",
"type": "n8n-nodes-base.code",
"typeVersion": 1,
"position": [
850,
300
]
},
{
"parameters": {
"method": "POST",
"url": "http://ml-service:8001/ingest",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "data",
"value": "={{$json.hourly_rows}}"
}
]
}
},
"name": "POST /ingest",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1050,
300
]
},
{
"parameters": {
"method": "POST",
"url": "http://ml-service:8001/detect",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={ \"region_id\": \"{{$('Define Regions').item.json.id}}\", \"auto_trigger\": true }"
},
"name": "POST /detect",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 3,
"position": [
1250,
300
]
},
{
"parameters": {
"jsCode": "const geojson = $input.item.json;\nconst extremes = (geojson.features || []).filter(f => f.properties.severity === 'extreme');\nreturn { trigger_alert: extremes.length > 0, extreme_count: extremes.length, geojson };"
},
"name": "Filter Extremes",
"type": "n8n-nodes-base.code",
"typeVersion": 1,
"position": [
1450,
300
]
},
{
"parameters": {
"conditions": {
"boolean": [
{
"value1": "={{$json.trigger_alert}}",
"value2": true
}
]
}
},
"name": "IF trigger_alert",
"type": "n8n-nodes-base.if",
"typeVersion": 1,
"position": [
1650,
300
]
},
{
"parameters": {
"workflowId": "ClimateGuard - 05 Alerts & Dispatch"
},
"name": "Execute Alerts Workflow",
"type": "n8n-nodes-base.executeWorkflow",
"typeVersion": 1,
"position": [
1850,
200
]
}
],
"connections": {
"Schedule Trigger": {
"main": [
[
{
"node": "Define Regions",
"type": "main",
"index": 0
}
]
]
},
"Define Regions": {
"main": [
[
{
"node": "Fetch Open-Meteo",
"type": "main",
"index": 0
}
]
]
},
"Fetch Open-Meteo": {
"main": [
[
{
"node": "Flatten Data",
"type": "main",
"index": 0
}
]
]
},
"Flatten Data": {
"main": [
[
{
"node": "POST /ingest",
"type": "main",
"index": 0
}
]
]
},
"POST /ingest": {
"main": [
[
{
"node": "POST /detect",
"type": "main",
"index": 0
}
]
]
},
"POST /detect": {
"main": [
[
{
"node": "Filter Extremes",
"type": "main",
"index": 0
}
]
]
},
"Filter Extremes": {
"main": [
[
{
"node": "IF trigger_alert",
"type": "main",
"index": 0
}
]
]
},
"IF trigger_alert": {
"main": [
[
{
"node": "Execute Alerts Workflow",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
01 Data Ingestion. Uses httpRequest. Scheduled trigger; 9 nodes.
Source: https://github.com/gurvindersingh-web/Spatiotemporal-climate-anomaly-detection-AI/blob/ebea873a39c12b1b05cb8b736f48d8717ff00d50/n8n-workflows/01-data-ingestion.json — original creator credit. Request a take-down →
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