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