330 lines
15 KiB
Python
330 lines
15 KiB
Python
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import time
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import random
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import requests
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from datetime import datetime
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# 添加InfluxDB配置
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INFLUXDB_URL = 'http://8.134.11.76:8086'
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INFLUXDB_TOKEN = 'KuTa5ZsqoHIhi2IglOO06zExUYw1_mJ6K0mcA9X1y6O6CJDog3_Cgr8mUw1SwpuCCKRElqxa6wAhrrhsYPytkg=='
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INFLUXDB_ORG = 'gzlg'
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INFLUXDB_BUCKET = 'gzlg'
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# 配置设备ID：设置为0则自动注册，设置为1000~1999则固定使用该ID
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CONFIG_DEVICE_ID = 1003
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# 分配的设备ID（初始为None，注册后更新）
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assigned_device_id = None
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# 相位计数器
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phase_counter = 0
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def get_next_device_id():
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"""从InfluxDB查询已注册的设备ID，并返回下一个可用的ID"""
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try:
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# 查询InfluxDB中已存在的设备ID
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query = '''
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from(bucket: "{}")
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|> range(start: -365d)
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|> filter(fn: (r) => r["_measurement"] == "device_data")
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|> keep(columns: ["deviceId"])
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|> distinct(column: "deviceId")
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|> sort()
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'''.format(INFLUXDB_BUCKET)
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url = f"{INFLUXDB_URL}/api/v2/query?org={INFLUXDB_ORG}"
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headers = {
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"Authorization": f"Token {INFLUXDB_TOKEN}",
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"Content-Type": "application/json"
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}
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data = {
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"query": query
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}
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response = requests.post(url, headers=headers, json=data)
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print(f"🔍 InfluxDB查询响应状态: {response.status_code}")
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if response.status_code == 200:
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print(f"🔍 InfluxDB查询响应内容: {response.text}")
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# 解析响应数据
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device_ids = []
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lines = response.text.strip().split('\n')
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for line in lines:
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if line and not line.startswith('#') and 'deviceId' not in line:
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try:
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# 解析CSV格式的响应数据
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# 格式类似于: ,_result,0,1001,1001
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parts = line.split(',')
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if len(parts) >= 5:
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# deviceId在第4个位置（索引3）
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device_id_str = parts[3].strip()
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if device_id_str:
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device_id = int(device_id_str)
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if 1000 <= device_id <= 1999: # 只考虑1000-1999范围内的设备ID
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device_ids.append(device_id)
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print(f"📱 发现设备ID: {device_id}")
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except (ValueError, IndexError) as e:
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# 忽略解析错误的行
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print(f"⚠️ 忽略无法解析的行: {line}")
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continue
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# 对设备ID进行排序
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device_ids.sort()
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# 找到下一个可用的ID
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next_id = 1001
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for device_id in device_ids:
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if device_id == next_id:
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next_id += 1
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elif device_id > next_id:
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break
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# 确保ID在有效范围内
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if next_id > 1999:
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next_id = 1001 # 如果超出范围，从头开始
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print(f"📊 查询到已注册设备: {device_ids}")
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print(f"🆕 分配新设备ID: {next_id}")
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return next_id
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else:
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print(f"❌ 查询InfluxDB失败: {response.status_code} - {response.text}")
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# 如果查询失败，返回默认ID
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return 1001
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except Exception as e:
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print(f"❌ 查询设备ID时出错: {e}")
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import traceback
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traceback.print_exc()
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# 如果查询失败，返回默认ID
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return 1001
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def register_device():
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"""注册设备并获取设备ID"""
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global assigned_device_id
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# 检查配置的设备ID
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if CONFIG_DEVICE_ID == 0:
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# 自动注册模式
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try:
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# 获取下一个可用的设备ID
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next_device_id = get_next_device_id()
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assigned_device_id = next_device_id
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print(f"✅ 设备注册成功! 设备ID: {assigned_device_id} (0x{assigned_device_id:04X})")
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return True
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except Exception as e:
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print(f"❌ 注册过程中发生错误: {e}")
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return False
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elif 1000 <= CONFIG_DEVICE_ID <= 1999:
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# 固定设备ID模式
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assigned_device_id = CONFIG_DEVICE_ID
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print(f"✅ 使用固定设备ID: {assigned_device_id} (0x{assigned_device_id:04X})")
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return True
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else:
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# 配置的设备ID无效
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print(f"❌ 配置的设备ID {CONFIG_DEVICE_ID} 无效，请设置为0（自动注册）或1000~1999之间的值")
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return False
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def save_data_to_influxdb(protocol_id, data_value):
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"""保存日常数据到InfluxDB"""
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try:
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# 根据协议ID确定字段名
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field_mapping = {
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1: "heartRate",
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2: "breathingRate",
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13: "personDetected",
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14: "humanActivity",
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15: "humanDistance", # 人体距离 (cm)
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16: "humanPosition", # 人体方位 (cm)
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17: "sleepState" # 睡眠状态
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}
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if protocol_id in field_mapping:
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field_name = field_mapping[protocol_id]
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# 创建数据点 - 使用 "daily_data" 作为测量值名称
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data_point = {
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"measurement": "daily_data", # 改为 daily_data 以区分日常数据
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"tags": {
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"deviceId": assigned_device_id,
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"dataType": "daily" # 标识这是日常数据
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},
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"time": datetime.utcnow().isoformat() + "Z",
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"fields": {}
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}
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# 对特定字段进行数值处理
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if protocol_id in [1, 2]: # 心率和呼吸频率需要除以10
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data_point["fields"][field_name] = float(data_value) / 10.0
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elif protocol_id in [13, 14]: # 人检/活动数据，确保是整数0或1
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# 强制转换为整数，确保只有0或1
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data_point["fields"][field_name] = int(data_value)
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if data_point["fields"][field_name] not in [0, 1]:
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print(f"⚠️ 警告: 人检/活动数据值异常: {data_value}, 强制转换为: {data_point['fields'][field_name]}")
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elif protocol_id == 15: # 人体距离，范围0-65535
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data_point["fields"][field_name] = int(data_value)
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elif protocol_id == 16: # 人体方位，可以是正负值
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data_point["fields"][field_name] = int(data_value)
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elif protocol_id == 17: # 睡眠状态，使用预定义值
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data_point["fields"][field_name] = int(data_value)
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else:
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data_point["fields"][field_name] = data_value
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# 发送数据到InfluxDB
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url = f"{INFLUXDB_URL}/api/v2/write?org={INFLUXDB_ORG}&bucket={INFLUXDB_BUCKET}"
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headers = {
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"Authorization": f"Token {INFLUXDB_TOKEN}",
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"Content-Type": "text/plain; charset=utf-8"
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}
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# 构造行协议格式的数据，明确指定数据类型
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if protocol_id in [13, 14, 15, 16, 17]:
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# 对于人检/活动/距离/位置/睡眠状态数据，使用整数格式
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line_protocol = f"daily_data,deviceId={assigned_device_id},dataType=daily {field_name}={int(data_point['fields'][field_name])}i"
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else:
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# 对于其他数据，使用浮点数格式
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line_protocol = f"daily_data,deviceId={assigned_device_id},dataType=daily {field_name}={data_point['fields'][field_name]}"
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response = requests.post(url, headers=headers, data=line_protocol)
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if response.status_code == 204:
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print(f"✅ 日常数据已保存到InfluxDB设备{assigned_device_id}上: {field_name}={data_point['fields'][field_name]}")
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else:
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print(f"❌ 保存日常数据到InfluxDB失败: {response.status_code} - {response.text}")
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else:
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print(f"⚠️ 未知的协议ID: {protocol_id}")
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except Exception as e:
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print(f"❌ 保存日常数据到InfluxDB时出错: {e}")
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import traceback
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traceback.print_exc()
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def save_sleep_data_to_influxdb(sleep_data):
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"""保存睡眠数据到InfluxDB"""
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try:
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# 构造睡眠数据的行协议格式 - 使用 "sleep_data" 作为测量值名称
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line_protocol = f"sleep_data,deviceId={assigned_device_id},dataType=sleep "
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# 按顺序添加各个字段
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fields = []
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fields.append(f"sleepQualityScore={int(sleep_data['sleepQualityScore'])}i") # 1B 睡眠质量评分 (0~100)
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fields.append(f"totalSleepDuration={int(sleep_data['totalSleepDuration'])}i") # 2B 睡眠总时长 (0~65535 分钟)
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fields.append(f"awakeDurationRatio={int(sleep_data['awakeDurationRatio'])}i") # 1B 清醒时长占比 (0~100)
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fields.append(f"lightSleepRatio={int(sleep_data['lightSleepRatio'])}i") # 1B 浅睡时长占比 (0~100)
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fields.append(f"deepSleepRatio={int(sleep_data['deepSleepRatio'])}i") # 1B 深睡时长占比 (0~100)
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fields.append(f"outOfBedDuration={int(sleep_data['outOfBedDuration'])}i") # 1B 离床时长 (0~255)
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fields.append(f"outOfBedCount={int(sleep_data['outOfBedCount'])}i") # 1B 离床次数 (0~255)
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fields.append(f"turnCount={int(sleep_data['turnCount'])}i") # 1B 翻身次数 (0~255)
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fields.append(f"avgBreathingRate={int(sleep_data['avgBreathingRate'])}i") # 1B 平均呼吸 (0~25)
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fields.append(f"avgHeartRate={int(sleep_data['avgHeartRate'])}i") # 1B 平均心跳 (0~100)
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fields.append(f"apneaCount={int(sleep_data['apneaCount'])}i") # 1B 呼吸暂停次数 (0~10)
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line_protocol += ",".join(fields)
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# 发送数据到InfluxDB
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url = f"{INFLUXDB_URL}/api/v2/write?org={INFLUXDB_ORG}&bucket={INFLUXDB_BUCKET}"
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headers = {
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"Authorization": f"Token {INFLUXDB_TOKEN}",
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"Content-Type": "text/plain; charset=utf-8"
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}
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response = requests.post(url, headers=headers, data=line_protocol)
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if response.status_code == 204:
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print(f"✅ 睡眠数据已保存到InfluxDB设备{assigned_device_id}上")
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else:
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print(f"❌ 保存睡眠数据到InfluxDB失败: {response.status_code} - {response.text}")
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except Exception as e:
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print(f"❌ 保存睡眠数据到InfluxDB时出错: {e}")
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import traceback
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traceback.print_exc()
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def generate_random_sleep_data():
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"""生成随机睡眠数据用于测试"""
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sleep_data = {
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"sleepQualityScore": random.randint(0, 100), # 1B 睡眠质量评分 (0~100)
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"totalSleepDuration": random.randint(0, 65535), # 2B 睡眠总时长 (0~65535 分钟)
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"awakeDurationRatio": random.randint(0, 100), # 1B 清醒时长占比 (0~100)
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"lightSleepRatio": random.randint(0, 100), # 1B 浅睡时长占比 (0~100)
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"deepSleepRatio": random.randint(0, 100), # 1B 深睡时长占比 (0~100)
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"outOfBedDuration": random.randint(0, 255), # 1B 离床时长 (0~255)
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"outOfBedCount": random.randint(0, 255), # 1B 离床次数 (0~255)
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"turnCount": random.randint(0, 255), # 1B 翻身次数 (0~255)
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"avgBreathingRate": random.randint(0, 25), # 1B 平均呼吸 (0~25)
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"avgHeartRate": random.randint(0, 100), # 1B 平均心跳 (0~100)
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"apneaCount": random.randint(0, 10), # 1B 呼吸暂停次数 (0~10)
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}
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# 确保比例字段总和为100
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total_ratio = sleep_data["awakeDurationRatio"] + sleep_data["lightSleepRatio"] + sleep_data["deepSleepRatio"]
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if total_ratio != 100:
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# 调整浅睡时长占比以确保总和为100
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adjustment = 100 - total_ratio
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sleep_data["lightSleepRatio"] = max(0, min(100, sleep_data["lightSleepRatio"] + adjustment))
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# 再次检查总和
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total_ratio = sleep_data["awakeDurationRatio"] + sleep_data["lightSleepRatio"] + sleep_data["deepSleepRatio"]
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if total_ratio != 100:
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# 如果仍然不是100，则最后一次调整浅睡占比
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sleep_data["lightSleepRatio"] += (100 - total_ratio)
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sleep_data["lightSleepRatio"] = max(0, min(100, sleep_data["lightSleepRatio"]))
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return sleep_data
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def main():
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global assigned_device_id
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try:
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# 第一步：注册设备获取设备ID
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if not register_device():
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print("❌ 设备注册失败，程序退出")
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return
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print(f"🎯 开始使用设备ID {assigned_device_id} 发送数据...")
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# 启动时立即发送一次睡眠数据
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print("⏰ 启动时生成并发送睡眠数据...")
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initial_sleep_data = generate_random_sleep_data()
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save_sleep_data_to_influxdb(initial_sleep_data)
|
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|
|
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|
|
# 记录上次发送睡眠数据的时间
|
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|
last_sleep_data_time = time.time()
|
|||
|
|
|
|||
|
|
# 第二步：开始发送数据
|
|||
|
|
while True:
|
|||
|
|
# 初始化数据值
|
|||
|
|
data_value = 0
|
|||
|
|
|
|||
|
|
# 发送其他数据
|
|||
|
|
protocol_id = random.choice([1, 2, 13, 14, 15, 16, 17]) # 1=心跳, 2=呼吸, 13=检测到人, 14=人体活动, 15=人体距离, 16=人体方位, 17=睡眠状态
|
|||
|
|
|
|||
|
|
if protocol_id == 1: # 心跳
|
|||
|
|
data_value = random.randint(600, 1000)
|
|||
|
|
elif protocol_id == 2: # 呼吸
|
|||
|
|
data_value = random.randint(120, 200)
|
|||
|
|
elif protocol_id == 13: # 检测到人（1检测到，0未检测到）
|
|||
|
|
data_value = random.choice([1])
|
|||
|
|
elif protocol_id == 14: # 人体活动（1活动，0静止）
|
|||
|
|
data_value = random.choice([0])
|
|||
|
|
elif protocol_id == 15: # 人体距离 (cm)，范围0-65535
|
|||
|
|
data_value = random.randint(0, 65535)
|
|||
|
|
elif protocol_id == 16: # 人体方位 (cm)，可以有正负值
|
|||
|
|
data_value = random.randint(-32768, 32767)
|
|||
|
|
elif protocol_id == 17: # 睡眠状态 (0x00=深睡, 0x01=浅睡, 0x02=清醒, 0x03=无)
|
|||
|
|
data_value = random.choice([0, 1, 2, 3])
|
|||
|
|
|
|||
|
|
# 直接发送数据到InfluxDB
|
|||
|
|
save_data_to_influxdb(protocol_id, data_value)
|
|||
|
|
|
|||
|
|
# 每隔一段时间（例如30分钟）发送一次睡眠数据
|
|||
|
|
current_time = time.time()
|
|||
|
|
if current_time - last_sleep_data_time >= 1800: # 30分钟 = 1800秒
|
|||
|
|
print("⏰ 生成并发送睡眠数据...")
|
|||
|
|
sleep_data = generate_random_sleep_data()
|
|||
|
|
save_sleep_data_to_influxdb(sleep_data)
|
|||
|
|
last_sleep_data_time = current_time
|
|||
|
|
|
|||
|
|
# 设置发送间隔
|
|||
|
|
time.sleep(0.4) # 每0.4秒发送一次数据
|
|||
|
|
|
|||
|
|
except KeyboardInterrupt:
|
|||
|
|
print(f"\n🛑 设备 {assigned_device_id} 发送端已停止")
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"❌ 发生错误: {e}")
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
main()
|