TOMOMITSU ASANO This workflow corresponds to n8n.io template #11909 — we link there as the canonical source.
This workflow follows the Agent → Gmail recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "IoT Sensor Data Aggregation with AI-Powered Anomaly Detection",
"nodes": [
{
"id": "sticky-overview",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-352,
96
],
"parameters": {
"width": 400,
"height": 664,
"content": "## IoT Sensor Data Aggregation with AI-Powered Anomaly Detection\n\n### Overview\nReal-time IoT sensor monitoring system that collects data via MQTT, processes with AI for anomaly detection, and triggers smart alerts.\n\n### Key Features\n- **MQTT Integration**: Real-time sensor data ingestion\n- **AI Agent Analysis**: Dynamic anomaly detection with reasoning\n- **Multi-Threshold Alerts**: Critical/Warning/Info levels\n- **Data Fingerprinting**: SHA256 deduplication\n- **Historical Logging**: Google Sheets archiving\n\n### Required Credentials\n- MQTT Broker credentials\n- OpenAI API key\n- Slack Bot Token\n- Google Sheets OAuth\n- Gmail OAuth\n\n### Trigger Options\n1. MQTT real-time sensor data\n2. Scheduled batch processing\n3. Manual webhook trigger"
},
"typeVersion": 1
},
{
"id": "sticky-step1",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
112,
624
],
"parameters": {
"color": 7,
"width": 280,
"height": 140,
"content": "### Step 1: Data Ingestion\nMultiple trigger sources for flexibility:\n- MQTT for real-time IoT data\n- Schedule for batch processing\n- Webhook for manual triggers"
},
"typeVersion": 1
},
{
"id": "sticky-step2",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
608,
608
],
"parameters": {
"color": 7,
"width": 280,
"height": 156,
"content": "### Step 2: Data Processing\n- Parse sensor payload\n- Add timestamps & metadata\n- Generate content hash for deduplication\n- Filter duplicate readings"
},
"typeVersion": 1
},
{
"id": "sticky-step3",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1312,
688
],
"parameters": {
"color": 7,
"width": 280,
"height": 172,
"content": "### Step 3: AI Analysis\nAI Agent analyzes sensor data to:\n- Detect anomalies dynamically\n- Provide reasoning for decisions\n- Classify severity levels\n- Suggest corrective actions"
},
"typeVersion": 1
},
{
"id": "sticky-step4",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
2000,
736
],
"parameters": {
"color": 7,
"width": 280,
"height": 140,
"content": "### Step 4: Alert & Archive\n- Route alerts by severity\n- Critical \u2192 Email + Slack\n- Warning \u2192 Slack only\n- Log all data to Sheets"
},
"typeVersion": 1
},
{
"id": "mqtt-trigger",
"name": "MQTT Sensor Trigger",
"type": "n8n-nodes-base.mqttTrigger",
"position": [
112,
304
],
"parameters": {
"topics": "sensors/+/data",
"options": {}
},
"typeVersion": 1
},
{
"id": "schedule-trigger",
"name": "Batch Process Schedule",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
112,
480
],
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 15
}
]
}
},
"typeVersion": 1.2
},
{
"id": "merge-triggers",
"name": "Merge Triggers",
"type": "n8n-nodes-base.merge",
"position": [
352,
384
],
"parameters": {
"mode": "chooseBranch"
},
"typeVersion": 3
},
{
"id": "set-sensor-config",
"name": "Define Sensor Thresholds",
"type": "n8n-nodes-base.set",
"position": [
560,
384
],
"parameters": {
"mode": "raw",
"options": {},
"jsonOutput": "{\n \"thresholds\": {\n \"temperature\": {\"min\": -10, \"max\": 50, \"unit\": \"C\"},\n \"humidity\": {\"min\": 20, \"max\": 90, \"unit\": \"%\"},\n \"pressure\": {\"min\": 950, \"max\": 1050, \"unit\": \"hPa\"},\n \"co2\": {\"min\": 400, \"max\": 2000, \"unit\": \"ppm\"}\n },\n \"alertConfig\": {\n \"criticalChannel\": \"#iot-critical\",\n \"warningChannel\": \"#iot-alerts\",\n \"emailRecipients\": \"user@example.com\"\n }\n}"
},
"typeVersion": 3.4
},
{
"id": "parse-sensor-data",
"name": "Parse Sensor Payload",
"type": "n8n-nodes-base.code",
"position": [
752,
384
],
"parameters": {
"jsCode": "const items = $input.all();\nconst thresholds = $('Define Sensor Thresholds').first().json.thresholds;\nconst results = [];\n\nfor (const item of items) {\n let sensorData;\n try {\n sensorData = typeof item.json.message === 'string' \n ? JSON.parse(item.json.message) \n : item.json;\n } catch (e) {\n sensorData = item.json;\n }\n \n const now = new Date();\n const reading = {\n sensorId: sensorData.sensorId || sensorData.topic?.split('/')[1] || 'unknown',\n location: sensorData.location || 'Main Facility',\n timestamp: now.toISOString(),\n readings: {\n temperature: sensorData.temperature ?? null,\n humidity: sensorData.humidity ?? null,\n pressure: sensorData.pressure ?? null,\n co2: sensorData.co2 ?? null\n },\n metadata: {\n receivedAt: now.toISOString(),\n source: item.json.topic || 'batch',\n thresholds: thresholds\n }\n };\n \n results.push({ json: reading });\n}\n\nreturn results;"
},
"typeVersion": 2
},
{
"id": "generate-hash",
"name": "Generate Data Fingerprint",
"type": "n8n-nodes-base.crypto",
"position": [
960,
384
],
"parameters": {
"type": "SHA256",
"value": "={{ $json.sensorId + '-' + $json.timestamp + '-' + JSON.stringify($json.readings) }}",
"dataPropertyName": "dataHash"
},
"typeVersion": 1
},
{
"id": "remove-duplicates",
"name": "Remove Duplicate Readings",
"type": "n8n-nodes-base.removeDuplicates",
"position": [
1152,
384
],
"parameters": {
"compare": "selectedFields",
"options": {},
"fieldsToCompare": "dataHash"
},
"typeVersion": 1
},
{
"id": "ai-agent",
"name": "AI Anomaly Detector",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1344,
384
],
"parameters": {
"text": "=Analyze this IoT sensor reading and determine if there are any anomalies:\n\nSensor ID: {{ $json.sensorId }}\nLocation: {{ $json.location }}\nTimestamp: {{ $json.timestamp }}\n\nReadings:\n- Temperature: {{ $json.readings.temperature }}\u00b0C (Normal: {{ $json.metadata.thresholds.temperature.min }} to {{ $json.metadata.thresholds.temperature.max }})\n- Humidity: {{ $json.readings.humidity }}% (Normal: {{ $json.metadata.thresholds.humidity.min }} to {{ $json.metadata.thresholds.humidity.max }})\n- CO2: {{ $json.readings.co2 }} ppm (Normal: {{ $json.metadata.thresholds.co2.min }} to {{ $json.metadata.thresholds.co2.max }})\n\nProvide your analysis in this exact JSON format:\n{\n \"hasAnomaly\": true/false,\n \"severity\": \"critical\"/\"warning\"/\"normal\",\n \"anomalies\": [\"list of detected issues\"],\n \"reasoning\": \"explanation of your analysis\",\n \"recommendation\": \"suggested action\"\n}",
"options": {
"systemMessage": "You are an IoT monitoring expert. Analyze sensor data and detect anomalies based on the provided thresholds. Be precise and provide actionable recommendations. Always respond in valid JSON format."
}
},
"typeVersion": 1.7
},
{
"id": "parse-ai-response",
"name": "Parse AI Analysis",
"type": "n8n-nodes-base.code",
"position": [
1600,
384
],
"parameters": {
"jsCode": "const item = $input.first();\nconst originalData = $('Remove Duplicate Readings').first().json;\n\nlet aiAnalysis;\ntry {\n const responseText = item.json.output || item.json.text || '';\n const jsonMatch = responseText.match(/\\{[\\s\\S]*\\}/);\n aiAnalysis = jsonMatch ? JSON.parse(jsonMatch[0]) : {\n hasAnomaly: false,\n severity: 'normal',\n anomalies: [],\n reasoning: 'Unable to parse AI response',\n recommendation: 'Manual review required'\n };\n} catch (e) {\n aiAnalysis = {\n hasAnomaly: false,\n severity: 'normal',\n anomalies: [],\n reasoning: 'Parse error: ' + e.message,\n recommendation: 'Manual review required'\n };\n}\n\nreturn [{\n json: {\n ...originalData,\n analysis: aiAnalysis,\n alertLevel: aiAnalysis.severity,\n requiresAlert: aiAnalysis.hasAnomaly && aiAnalysis.severity !== 'normal'\n }\n}];"
},
"typeVersion": 2
},
{
"id": "switch-severity",
"name": "Route by Severity",
"type": "n8n-nodes-base.switch",
"position": [
1808,
384
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "Critical",
"conditions": {
"options": {
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "critical",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.alertLevel }}",
"rightValue": "critical"
}
]
},
"renameOutput": true
},
{
"outputKey": "Warning",
"conditions": {
"options": {
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "warning",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.alertLevel }}",
"rightValue": "warning"
}
]
},
"renameOutput": true
}
]
},
"options": {
"fallbackOutput": "extra"
}
},
"typeVersion": 3.2
},
{
"id": "send-critical-email",
"name": "Send Critical Email",
"type": "n8n-nodes-base.gmail",
"position": [
2080,
208
],
"parameters": {
"sendTo": "={{ $('Define Sensor Thresholds').first().json.alertConfig.emailRecipients }}",
"message": "=CRITICAL IoT SENSOR ALERT\n\nSensor: {{ $json.sensorId }}\nLocation: {{ $json.location }}\nTime: {{ $json.timestamp }}\n\nReadings:\n- Temperature: {{ $json.readings.temperature }}\u00b0C\n- Humidity: {{ $json.readings.humidity }}%\n- CO2: {{ $json.readings.co2 }} ppm\n\nAI Analysis:\n{{ $json.analysis.reasoning }}\n\nDetected Issues:\n{{ $json.analysis.anomalies.join('\\n- ') }}\n\nRecommendation:\n{{ $json.analysis.recommendation }}",
"options": {},
"subject": "=CRITICAL IoT Alert: {{ $json.sensorId }} - {{ $json.analysis.anomalies[0] || 'Anomaly Detected' }}"
},
"typeVersion": 2.1
},
{
"id": "send-critical-slack",
"name": "Slack Critical Alert",
"type": "n8n-nodes-base.slack",
"position": [
2080,
368
],
"parameters": {
"text": "=\ud83d\udea8 *CRITICAL IoT ALERT*\n\n*Sensor:* {{ $json.sensorId }}\n*Location:* {{ $json.location }}\n\n*Readings:*\n\u2022 Temperature: {{ $json.readings.temperature }}\u00b0C\n\u2022 Humidity: {{ $json.readings.humidity }}%\n\u2022 CO2: {{ $json.readings.co2 }} ppm\n\n*AI Analysis:* {{ $json.analysis.reasoning }}\n*Recommendation:* {{ $json.analysis.recommendation }}",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "name",
"value": "#iot-critical"
},
"otherOptions": {}
},
"typeVersion": 2.2
},
{
"id": "send-warning-slack",
"name": "Slack Warning Alert",
"type": "n8n-nodes-base.slack",
"position": [
2080,
528
],
"parameters": {
"text": "=\u26a0\ufe0f *IoT Warning*\n\n*Sensor:* {{ $json.sensorId }} | *Location:* {{ $json.location }}\n*Issue:* {{ $json.analysis.anomalies[0] || 'Threshold approaching' }}\n*Recommendation:* {{ $json.analysis.recommendation }}",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "name",
"value": "#iot-alerts"
},
"otherOptions": {}
},
"typeVersion": 2.2
},
{
"id": "merge-alerts",
"name": "Merge Alert Outputs",
"type": "n8n-nodes-base.merge",
"position": [
2336,
384
],
"parameters": {},
"typeVersion": 3
},
{
"id": "log-to-sheets",
"name": "Archive to Google Sheets",
"type": "n8n-nodes-base.googleSheets",
"position": [
2512,
384
],
"parameters": {
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": ""
},
"documentId": {
"__rl": true,
"mode": "list",
"value": ""
}
},
"typeVersion": 4.5
},
{
"id": "openai-model",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1344,
544
],
"parameters": {
"model": "gpt-4o-mini",
"options": {
"temperature": 0.3
}
},
"typeVersion": 1.2
}
],
"settings": {
"executionOrder": "v1"
},
"connections": {
"Merge Triggers": {
"main": [
[
{
"node": "Define Sensor Thresholds",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Anomaly Detector",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Parse AI Analysis": {
"main": [
[
{
"node": "Route by Severity",
"type": "main",
"index": 0
}
]
]
},
"Route by Severity": {
"main": [
[
{
"node": "Send Critical Email",
"type": "main",
"index": 0
},
{
"node": "Slack Critical Alert",
"type": "main",
"index": 0
}
],
[
{
"node": "Slack Warning Alert",
"type": "main",
"index": 0
}
],
[
{
"node": "Merge Alert Outputs",
"type": "main",
"index": 0
}
]
]
},
"AI Anomaly Detector": {
"main": [
[
{
"node": "Parse AI Analysis",
"type": "main",
"index": 0
}
]
]
},
"MQTT Sensor Trigger": {
"main": [
[
{
"node": "Merge Triggers",
"type": "main",
"index": 0
}
]
]
},
"Merge Alert Outputs": {
"main": [
[
{
"node": "Archive to Google Sheets",
"type": "main",
"index": 0
}
]
]
},
"Send Critical Email": {
"main": [
[
{
"node": "Merge Alert Outputs",
"type": "main",
"index": 0
}
]
]
},
"Slack Warning Alert": {
"main": [
[
{
"node": "Merge Alert Outputs",
"type": "main",
"index": 0
}
]
]
},
"Parse Sensor Payload": {
"main": [
[
{
"node": "Generate Data Fingerprint",
"type": "main",
"index": 0
}
]
]
},
"Slack Critical Alert": {
"main": [
[
{
"node": "Merge Alert Outputs",
"type": "main",
"index": 0
}
]
]
},
"Batch Process Schedule": {
"main": [
[
{
"node": "Merge Triggers",
"type": "main",
"index": 1
}
]
]
},
"Define Sensor Thresholds": {
"main": [
[
{
"node": "Parse Sensor Payload",
"type": "main",
"index": 0
}
]
]
},
"Generate Data Fingerprint": {
"main": [
[
{
"node": "Remove Duplicate Readings",
"type": "main",
"index": 0
}
]
]
},
"Remove Duplicate Readings": {
"main": [
[
{
"node": "AI Anomaly Detector",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
{ "name": "IoT Sensor Data Aggregation with AI-Powered Anomaly Detection", "nodes": [ { "parameters": { "content": "## How it works\nThis workflow monitors IoT sensors in real-time. It ingests data via MQTT or a schedule, normalizes the format, and removes duplicates using data…
Source: https://n8n.io/workflows/11909/ — original creator credit. Request a take-down →
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