AWS IoT
开发人员指南
AWS 文档中描述的 AWS 服务或功能可能因区域而异。要查看适用于中国区域的差异,请参阅中国的 AWS 服务入门

设置您的 Raspberry Pi 和含水量传感器

将 Micro SD 卡插入 Raspberry Pi 中,连接显示器、键盘、鼠标以及以太网电缆(如果您未使用 Wi-Fi)。先不要连接电源线。

将 JST 跳线连接到含水量传感器。跳线的另一端有四根电线:

  • 绿色:I2C SCL

  • 白色:I2C SDA

  • 红色:电源 (3.5 V)

  • 黑色:接地

握住 Raspberry Pi(以太网插孔位于右侧)。以该方向握持时,可看到顶部有两排 GPIO 引脚。按照以下顺序将含水量传感器的电线连接到下排引脚。从最左侧的引脚开始,连接红色(电源)、白色 (SDA) 和绿色 (SCL) 电线。跳过一个引脚,然后连接黑色(接地)电线。有关更多信息,请参阅 Python 计算机接线

将电源线连接到 Raspberry Pi,然后将另一端插入墙壁插座以将其打开。

配置您的 Raspberry Pi

  1. Welcome to Raspberry Pi (欢迎使用 Raspberry Pi) 页面上,选择 Next (下一步)

  2. 选择您的国家/地区、语言、时区和键盘布局。选择 Next

  3. 输入 Raspberry Pi 的密码,然后选择 Next (下一步)

  4. 选择您的 Wi-Fi 网络,然后选择 Next (下一步)。如果不使用 Wi-Fi 网络,则选择 Skip (跳过)

  5. 选择 Next (下一步) 检查软件更新。完成更新后,选择 Restart (重启) 重启您的 Raspberry Pi。

在 Raspberry Pi 启动后,启用 I2C 接口。

  1. 在 Raspbian 桌面的左上角,单击 Raspberry 图标,选择 Preferences (首选项),然后选择 Raspberry Pi Configuration (Raspberry Pi 配置)

  2. Interfaces (接口) 选项卡上,对于 I2C,选择 Enable (启用)

  3. 选择 OK

Adafruit STEMMA 含水量传感器的库是为 CircuitPython 编写的。要在 Raspberry Pi 上运行它们,需要安装最新版本的 Python 3。

  1. 在命令提示符中运行以下命令来更新 Raspberry Pi 软件:

    sudo apt-get update

    sudo apt-get upgrade

  2. 运行以下命令,更新您的 Python 3 安装:

    sudo pip3 install --upgrade setuptools

  3. 运行以下命令,安装 Raspberry Pi GPIO 库:

    pip3 install RPI.GPIO

  4. 运行以下命令,安装 Adafruit Blinka 库:

    pip3 install adafruit-blinka

    有关更多信息,请参阅在 Raspberry Pi 上安装 CircuitPython 库

  5. 运行以下命令,安装 Adafruit Seesaw 库:

    sudo pip3 install adafruit-circuitpython-seesaw

  6. 运行以下命令,安装适用于 Python 的 AWS IoT 设备软件开发工具包:

    pip3 install AWSIoTPythonSDK

Raspberry Pi 现已具备所有必需的库。创建一个名为 moistureSensor.py 的文件,并将以下 Python 代码复制到该文件中:

from adafruit_seesaw.seesaw import Seesaw from AWSIoTPythonSDK.MQTTLib import AWSIoTMQTTShadowClient from board import SCL, SDA import logging import time import json import argparse import busio # Shadow JSON schema: # # { # "state": { # “desired”:{ # "moisture":<INT VALUE>, # "temp":<INT VALUE> # } # } # } # Function called when a shadow is updated def customShadowCallback_Update(payload, responseStatus, token): # Display status and data from update request if responseStatus == “timeout”: print("Update request " + token + " time out!”) if responseStatus == “accepted”: payloadDict = json.loads(payload) print("~~~~~~~~~~~~~~~~~~~~~~~”) print("Update request with token: " + token + " accepted!”) print("moisture: " + str(payloadDict[“state”][“reported”][“moisture”])) print("temperature: " + str(payloadDict[“state”][“reported”][“temp”])) print("~~~~~~~~~~~~~~~~~~~~~~~\n\n”) if responseStatus == “rejected”: print("Update request " + token + " rejected!”) # Function called when a shadow is deleted def customShadowCallback_Delete(payload, responseStatus, token): # Display status and data from delete request if responseStatus == “timeout”: print("Delete request " + token + " time out!”) if responseStatus == “accepted”: print("~~~~~~~~~~~~~~~~~~~~~~~”) print("Delete request with token: " + token + " accepted!”) print("~~~~~~~~~~~~~~~~~~~~~~~\n\n”) if responseStatus == “rejected”: print("Delete request " + token + " rejected!”) # Read in command-line parameters def parseArgs(): parser = argparse.ArgumentParser() parser.add_argument("-e", "--endpoint", action="store", required=True, dest="host", help="Your AWS IoT custom endpoint”) parser.add_argument("-r", "--rootCA", action="store", required=True, dest="rootCAPath", help="Root CA file path”) parser.add_argument("-c", "--cert", action="store", dest="certificatePath", help="Certificate file path”) parser.add_argument("-k", "--key", action="store", dest="privateKeyPath", help="Private key file path”) parser.add_argument("-p", "--port", action="store", dest="port", type=int, help="Port number override”) parser.add_argument("-n", "--thingName", action="store", dest="thingName", default="Bot", help="Targeted thing name”) parser.add_argument("-id", "--clientId", action="store", dest="clientId", default="basicShadowUpdater", help="Targeted client id”) args = parser.parse_args() return args # Configure logging # AWSIoTMQTTShadowClient writes data to the log def configureLogging(): logger = logging.getLogger(“AWSIoTPythonSDK.core”) logger.setLevel(logging.DEBUG) streamHandler = logging.StreamHandler() formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s’) streamHandler.setFormatter(formatter) logger.addHandler(streamHandler) # Parse command line arguments args = parseArgs() if not args.certificatePath or not args.privateKeyPath: parser.error("Missing credentials for authentication.”) exit(2) # If no --port argument is passed, default to 8883 if not args.port: args.port = 8883 # Init AWSIoTMQTTShadowClient myAWSIoTMQTTShadowClient = None myAWSIoTMQTTShadowClient = AWSIoTMQTTShadowClient(args.clientId) myAWSIoTMQTTShadowClient.configureEndpoint(args.host, args.port) myAWSIoTMQTTShadowClient.configureCredentials(args.rootCAPath, args.privateKeyPath, args.certificatePath) # AWSIoTMQTTShadowClient connection configuration myAWSIoTMQTTShadowClient.configureAutoReconnectBackoffTime(1, 32, 20) myAWSIoTMQTTShadowClient.configureConnectDisconnectTimeout(10) # 10 sec myAWSIoTMQTTShadowClient.configureMQTTOperationTimeout(5) # 5 sec # Initialize Raspberry Pi's I2C interface i2c_bus = busio.I2C(SCL, SDA) # Intialize SeeSaw, Adafruit's Circuit Python library ss = Seesaw(i2c_bus, addr=0x36) # Connect to AWS IoT myAWSIoTMQTTShadowClient.connect() # Create a device shadow handler, use this to update and delete shadow document deviceShadowHandler = myAWSIoTMQTTShadowClient.createShadowHandlerWithName(args.thingName, True) # Delete curent shadow JSON doc deviceShadowHandler.shadowDelete(customShadowCallback_Delete, 5) # Read data from moisture sensor and update shadow while True: # read moisture level through capacitive touch pad moistureLevel = ss.moisture_read() # read temperature from the temperature sensor temp = ss.get_temp() # Display moisture and temp readings print("Moisture Level: {}".format(moistureLevel)) print("Temperature: {}".format(temp) # Create message payload payload = {"state":{"reported":{"moisture":str(moistureLevel),"temp":str(temp)}}} # Update shadow deviceShadowHandler.shadowUpdate(json.dumps(payload), customShadowCallback_Update, 5) time.sleep(1)

将文件保存到您可以找到的位置。在命令行中运行 moistureSensor.py 及以下参数:

endpoint

自定义 AWS IoT 终端节点。

rootCA

您的 AWS IoT 根 CA 证书的完整路径。

cert

您的 AWS IoT 设备证书的完整路径。

key

您的 AWS IoT 设备证书私有密钥的完整路径。

thingName

您的事物的名称(在本例中为 RaspberryPi)。

clientId

MQTT 客户端 ID。使用 RaspberryPi

命令行应如下所示:

python3 moistureSensor.py --endpoint --rootCA ~/certs/Amazon-Root-CA-1.pem --cert ~/certs/raspberrypi.crt --key ~/certs/raspberrypi-private.key --thing-name RaspberryPi --clientId RaspberryPi

尝试触摸传感器、将其放入花盆或放入一杯水中,查看传感器对各种含水量有何反应。如果需要,可以在 MoistureSensorRule 中更改阈值。当含水量传感器的读数低于规则的 SQL 查询语句中指定的值时,AWS IoT 会向 Amazon SNS 主题发布消息。您应会收到一封包含含水量和温度数据的电子邮件。

确认收到来自 Amazon SNS 的电子邮件后,按 CTRL + C 停止 Python 程序。该 Python 程序发送的消息应该不足以产生费用,但完成后最好将其停止。