Remote IOT Sensor monitoring via MQTT and InfluxDB
工作流概述
这是一个包含6个节点的中等工作流,主要用于自动化处理各种任务。
工作流源代码
{
"id": "6pOGYw5O3iOY1Gc6",
"meta": {
"instanceId": "7221598654c32899e94731aab144bdcd338735c2ac218dc0873131caa0be0ef8",
"templateCredsSetupCompleted": true
},
"name": "Remote IOT Sensor monitoring via MQTT and InfluxDB",
"tags": [],
"nodes": [
{
"id": "4997f226-f236-4d27-bea4-904744d9ff07",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-700,
-360
],
"parameters": {
"width": 340,
"height": 120,
"content": "MQTT trigger subscribed to a topic called wokwi-weather via a Mosquitto MQTT broker. The trigger receives the temperature and humidity payloads from a DHT22 sensor connected to a remote ESP32 microcontroller "
},
"typeVersion": 1
},
{
"id": "9d4f1da6-fda3-4312-a6b1-bd0ac499dde7",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-240,
-360
],
"parameters": {
"height": 100,
"content": "Javascript code to extract the temperature and humidity values to ensure correct JSON format for the database"
},
"typeVersion": 1
},
{
"id": "d8f01dba-5019-457e-8c1a-99c802282fdf",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
140,
-360
],
"parameters": {
"width": 260,
"height": 120,
"content": "HTTP request node posts temperature and humidity data from the DHT22 sensor to the InfluxDB data bucket running on a local host http://localhost:8086"
},
"typeVersion": 1
},
{
"id": "020858a6-7771-4322-8eb6-b83e99b3563d",
"name": "Remote Sensor MQTT Trigger",
"type": "n8n-nodes-base.mqttTrigger",
"position": [
-580,
-220
],
"parameters": {
"topics": "wokwi-weather",
"options": {}
},
"credentials": {
"mqtt": {
"id": "xtd75tjk1hKlQOba",
"name": "MQTT account"
}
},
"typeVersion": 1
},
{
"id": "51e6f59f-9b93-4121-8db4-7f47b929fdf5",
"name": "Data ingest to InfluxDB bucket",
"type": "n8n-nodes-base.httpRequest",
"position": [
200,
-220
],
"parameters": {
"url": "http://localhost:8086/api/v2/write?orgID=<Organization ID>&bucket=<InfluxDB bucket name>&precision=s",
"body": "={{ $json.payload }}",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "raw",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Token <API Token value generated in InfluxDB>"
}
]
}
},
"notesInFlow": true,
"typeVersion": 4.2
},
{
"id": "6abe1212-b128-492f-b485-401a4315fcbc",
"name": "Payload data preparation node",
"type": "n8n-nodes-base.code",
"position": [
-180,
-220
],
"parameters": {
"jsCode": "// Try to parse the incoming message as JSON
let data;
try {
data = JSON.parse($json.message); // $json.message is expected to be a JSON string
} catch (e) {
// If parsing fails, throw an error
throw new Error(\"Invalid JSON in MQTT message\");
}
// Get the topic from the input, or use a default value
const topic = $json.topic || \"unknown-topic\";
// Make sure humidity and temp are numbers
if (typeof data.humidity !== \"number\" || typeof data.temp !== \"number\") {
throw new Error(\"Missing or invalid humidity/temp in MQTT message\");
}
// Create a formatted string like: \"topic_name humidity=45,temp=22\"
const line = `${topic} humidity=${data.humidity},temp=${data.temp}`;
// Return the result in the expected format
return [
{
json: {
payload: line
}
}
];"
},
"typeVersion": 2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "d1311dca-5edf-4f14-86b9-629937cd3416",
"connections": {
"Remote Sensor MQTT Trigger": {
"main": [
[
{
"node": "Payload data preparation node",
"type": "main",
"index": 0
}
]
]
},
"Payload data preparation node": {
"main": [
[
{
"node": "Data ingest to InfluxDB bucket",
"type": "main",
"index": 0
}
]
]
}
}
}
功能特点
- 自动检测新邮件
- AI智能内容分析
- 自定义分类规则
- 批量处理能力
- 详细的处理日志
技术分析
节点类型及作用
- Stickynote
- Mqtttrigger
- Httprequest
- Code
复杂度评估
配置难度:
维护难度:
扩展性:
实施指南
前置条件
- 有效的Gmail账户
- n8n平台访问权限
- Google API凭证
- AI分类服务订阅
配置步骤
- 在n8n中导入工作流JSON文件
- 配置Gmail节点的认证信息
- 设置AI分类器的API密钥
- 自定义分类规则和标签映射
- 测试工作流执行
- 配置定时触发器(可选)
关键参数
| 参数名称 | 默认值 | 说明 |
|---|---|---|
| maxEmails | 50 | 单次处理的最大邮件数量 |
| confidenceThreshold | 0.8 | 分类置信度阈值 |
| autoLabel | true | 是否自动添加标签 |
最佳实践
优化建议
- 定期更新AI分类模型以提高准确性
- 根据邮件量调整处理批次大小
- 设置合理的分类置信度阈值
- 定期清理过期的分类规则
安全注意事项
- 妥善保管API密钥和认证信息
- 限制工作流的访问权限
- 定期审查处理日志
- 启用双因素认证保护Gmail账户
性能优化
- 使用增量处理减少重复工作
- 缓存频繁访问的数据
- 并行处理多个邮件分类任务
- 监控系统资源使用情况
故障排除
常见问题
邮件未被正确分类
检查AI分类器的置信度阈值设置,适当降低阈值或更新训练数据。
Gmail认证失败
确认Google API凭证有效且具有正确的权限范围,重新进行OAuth授权。
调试技巧
- 启用详细日志记录查看每个步骤的执行情况
- 使用测试邮件验证分类逻辑
- 检查网络连接和API服务状态
- 逐步执行工作流定位问题节点
错误处理
工作流包含以下错误处理机制:
- 网络超时自动重试(最多3次)
- API错误记录和告警
- 处理失败邮件的隔离机制
- 异常情况下的回滚操作