MQTT物联网数据采集全栈方案

原创于 2025-10-23 09:20:53 发布 · 178 阅读

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CC 4.0 BY-SA版权

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#python #vscode #算法 #flask #后端 #前端

MQTT服务器搭建与数据接收

使用paho-mqtt库实现MQTT服务器订阅功能，接收NBIoT模组上报的数据。NBIoT模组通常以JSON格式上报传感器数据。

import paho.mqtt.client as mqtt
import json

# MQTT配置
MQTT_BROKER = "localhost"
MQTT_PORT = 1883
MQTT_TOPIC = "sensor/data"

def on_connect(client, userdata, flags, rc):
    print("Connected with result code "+str(rc))
    client.subscribe(MQTT_TOPIC)

def on_message(client, userdata, msg):
    try:
        data = json.loads(msg.payload.decode())
        print(f"Received data: {data}")
        # 调用数据库存储函数
        save_to_database(data)
    except Exception as e:
        print(f"Error processing message: {e}")

client = mqtt.Client()
client.on_connect = on_connect
client.on_message = on_message
client.connect(MQTT_BROKER, MQTT_PORT, 60)
client.loop_forever()

数据库存储实现

使用SQLite或MySQL存储传感器数据，这里以SQLite为例。

import sqlite3
from datetime import datetime

def init_db():
    conn = sqlite3.connect('sensor_data.db')
    cursor = conn.cursor()
    cursor.execute('''
        CREATE TABLE IF NOT EXISTS sensor_readings (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            device_id TEXT,
            temperature REAL,
            power REAL,
            timestamp DATETIME
        )
    ''')
    conn.commit()
    conn.close()

def save_to_database(data):
    conn = sqlite3.connect('sensor_data.db')
    cursor = conn.cursor()
    cursor.execute('''
        INSERT INTO sensor_readings (device_id, temperature, power, timestamp)
        VALUES (?, ?, ?, ?)
    ''', (data['device_id'], data['temp'], data['power'], datetime.now()))
    conn.commit()
    conn.close()

Web服务实现

使用Flask创建REST API供前端调用。

from flask import Flask, jsonify
import sqlite3

app = Flask(__name__)

@app.route('/api/sensor_data', methods=['GET'])
def get_sensor_data():
    conn = sqlite3.connect('sensor_data.db')
    cursor = conn.cursor()
    cursor.execute('SELECT * FROM sensor_readings ORDER BY timestamp DESC LIMIT 100')
    rows = cursor.fetchall()
    conn.close()
    
    data = [{
        'id': row[0],
        'device_id': row[1],
        'temperature': row[2],
        'power': row[3],
        'timestamp': row[4]
    } for row in rows]
    
    return jsonify(data)

if __name__ == '__main__':
    init_db()
    app.run(host='0.0.0.0', port=5000)

WebSocket实时推送

使用Flask-SocketIO实现实时数据推送。

from flask_socketio import SocketIO, emit

socketio = SocketIO(app, cors_allowed_origins="*")

# 修改on_message函数加入WebSocket推送
def on_message(client, userdata, msg):
    try:
        data = json.loads(msg.payload.decode())
        print(f"Received data: {data}")
        save_to_database(data)
        socketio.emit('new_data', data)  # 推送新数据到所有客户端
    except Exception as e:
        print(f"Error processing message: {e}")

@socketio.on('connect')
def handle_connect():
    print('Client connected')

小程序端实现

小程序使用WebSocket连接后端服务。

// 小程序端代码
const socket = wx.connectSocket({
  url: 'ws://your-server-ip:5000'
})

socket.onMessage((res) => {
  const data = JSON.parse(res.data)
  console.log('Received new data:', data)
  // 更新页面数据
  this.setData({
    temperature: data.temperature,
    power: data.power
  })
})

完整系统部署

启动MQTT服务：mosquitto -v
运行Python脚本：python main.py（整合所有代码）
部署Flask应用：可使用Gunicorn或uWSGI
配置Nginx反向代理WebSocket连接
小程序端配置合法域名

数据可视化增强

使用ECharts或Chart.js实现数据可视化。

// 小程序端图表实现
import * as echarts from '../../ec-canvas/echarts'

function initChart(canvas, width, height) {
  const chart = echarts.init(canvas, null, {
    width: width,
    height: height
  })
  canvas.setChart(chart)
  
  const option = {
    xAxis: {
      type: 'category',
      data: ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
    },
    yAxis: {
      type: 'value'
    },
    series: [{
      data: [820, 932, 901, 934, 1290, 1330, 1320],
      type: 'line'
    }]
  }
  
  chart.setOption(option)
  return chart
}