Amazon Iot物联网终端之廿六 采用AmazonIoT SDK for Python测试一个温度云监测的项目。

1. 项目介绍
这个项目是用于远程温度监测的项目，通过开发板采集温度传感器的温度数据，并通过订阅MQTT topic来上传到云端账号。对应于amazon开通一个和aws lambda驱动的语音入口UI，可以对这Amazon Echo说话，fetch temperature（取得温度），Echo音箱就会按照程序的编制取得对应的温度数据并用语音播报。
这个过程采用了MQTT订阅服务，在树莓派上测试过的，这个是在米尔板子上搭建了一个python环境并移植过来的。不过，目前echo只能支持英文，不能支持中文，所以只好用来测试。
这里的温度传感器数据采用虚拟数据，没有实际采集，因为暂时手头没有合适的独立温度传感器模块，相比树莓派，这个开发板还可以直接支持ADC采集的传感器，因此选择更多，可以用adafruit_BBIO.GPIO的ADC设置来采集。
在树莓派上的程序，需要下载amazon网站生成的公共证书CA，私有证书CA，和publicCA共3个CA，才能正确执行。这个部分属于AWS开发的过程。
2、简述AWS开发

• 登录AWS Console: https://aws.amazon.com/
  

• Navigate to AWS IoT
  

然后选择, “Create a Thing”.创建“CableTracer”.
然后创建证书， Certificate，下载所述public key, private key, 和certificate。并和这个项目关联。创建成功如下所示。
然后编制Lambda function，进入https://console.aws.amazon.com ，开始按步骤设置。
转到 https://developer.amazon.com/public/solutions/alexa/alexa-skills-kit
逐个设置

3. 开发板编程，

3.1 云端的node.js处理程序参考如下，主要是安全验证后，进行语音的识别和转换，

function onIntent(intentRequest, session )是其中的事件处理，对应于request，进行handle，

function buildSpeechletResponses()时生成语音模块的应答。

var awsIot = require('aws-iot-device-sdk');

var config = require("./config");

var deviceName = "CableTracer";      

var mqtt_config = {

    "keyPath": config.privateKey,

    "certPath": config.certificate,

    "caPath": config.rootCA,

    "host": config.host,

    "port": 8883,

    "clientId": "Lambda-" + deviceName,  //+ "-Lambda-" + (new Date().getTime()),

    "region":"us-east-1",

    "debug":true

};

var ctx = null;

var client = null;

// Route the incoming request based on type (LaunchRequest, IntentRequest, etc.) The JSON body of the request is provided in the event parameter.

exports.handler = function (event, context) {

    try {

        console.log("event.session.application.applicationId=" + event.session.application.applicationId);

        ctx = context;

        if (event.session.application.applicationId ！== app_id) {

             ctx.fail("Invalid Application ID");

         }

        client = awsIot.device(mqtt_config);

        client.on("connect",function(){

            console.log("Connected to AWS IoT");

//            callback();

        });

        if (event.session.new) {

            onSessionStarted({requestId: event.request.requestId}, event.session);

        }

        if (event.request.type === "LaunchRequest") {

            onLaunch(event.request, event.session);

        }  else if (event.request.type === "IntentRequest") {

            onIntent(event.request, event.session);

        } else if (event.request.type === "SessionEndedRequest") {

            onSessionEnded(event.request, event.session);

            ctx.succeed();

        }

    } catch (e) {

        console.log("EXCEPTION in handler:  " + e);

        ctx.fail("Exception: " + e);

    }

};

/**

* Called when the session starts.

*/

function onSessionStarted(sessionStartedRequest, session) {

    console.log("onSessionStarted requestId=" + sessionStartedRequest.requestId + ", sessionId=" + session.sessionId);

}

/**

* Called when the user launches the skill without specifying what they want.

*/

function onLaunch(launchRequest, session, callback) {

    console.log("onLaunch requestId=" + launchRequest.requestId + ", sessionId=" + session.sessionId);

    // Dispatch to your skill's launch.

    getWelcomeResponse(callback);

}

/**

* Called when the user specifies an intent for this skill.

*/

function onIntent(intentRequest, session ) {                  //, callback) {

    console.log("onIntent requestId=" + intentRequest.requestId + ", sessionId=" + session.sessionId);

    var intent = intentRequest.intent,

    intentName = intentRequest.intent.name;

    console.log("REQUEST to string =" + JSON.stringify(intentRequest));

    var callback = null;

    // Dispatch to your skill's intent handlers

    if ("Turn" === intentName) {

        doTurnIntent(intent, session);

    } else if ("Fetch" === intentName) {

        doFetchIntent(intent, session);

    } else if ("HelpIntent" === intentName) {

        getWelcomeResponse();

    } else {

        throw "Invalid intent";

    }

}

/**

* Called when the user ends the session.

* Is not called when the skill returns shouldEndSession=true.

*/

function onSessionEnded(sessionEndedRequest, session) {

    console.log("onSessionEnded requestId=" + sessionEndedRequest.requestId + ", sessionId=" + session.sessionId);

    // Add cleanup logic here

}

// --------------- Functions that control the skill's behavior -----------------------

function getWelcomeResponse() {

    // If we wanted to initialize the session to have some attributes we could add those here.

    var sessionAttributes = {};

    var cardTitle = "Welcome";

    var speechOutput = "Welcome to the Cable Tracer . ";

    var shouldEndSession = false;

    ctx.succeed(buildResponse(sessionAttributes, buildSpeechletResponse(cardTitle, speechOutput, repromptText, shouldEndSession)));

}

/**

*  handles GO intent.

*/

function doTurnIntent(intent, session, callback) {

// OnGoing code for Turn based on

//  mqttPublish() The codes send data to thingShadow, connection AWS IoT

}

function doFetchIntent(intent, session, callback) {

// OnGoing code for Turn based on

//  mqttPublish() The codes send data to thingShadow, connection AWS IoT

}

function mqttPublish(intent, sessionAttributes, cardTitle, speechOutput, repromptText, shouldEndSession)

{

    var strIntent = JSON.stringify(intent);

    console.log("mqttPublish:  INTENT text = " + strIntent);

//    client.publish("cabletracer", strIntent, false);

    client.publish(config.topic, strIntent, false);

    client.end();

    client.on("close", (function () {

        console.log("MQTT CLIENT CLOSE - thinks it's done, successfully. ");

        ctx.succeed(buildResponse(sessionAttributes, buildSpeechletResponse(cardTitle, speechOutput, repromptText, shouldEndSession)));

    }));

    client.on("error", (function (err, granted) {

        console.log("MQTT CLIENT ERROR！  " + err);

    }));

}

// --------------- Helpers that build all of the responses -----------------------

function buildSpeechletResponse(title, output, repromptText, shouldEndSession) {

    return {

        outputSpeech: {

            type: "PlainText",

            text: output

        },

        card: {

            type: "Simple",

            title: title,

            content: output

        },

        reprompt: {

            outputSpeech: {

                type: "PlainText",

                text: repromptText

            }

        },

        shouldEndSession: shouldEndSession

    }

}

function buildResponse(sessionAttributes, speechletResponse) {

    return {

        version: "1.0",

        sessionAttributes: sessionAttributes,

        response: speechletResponse

    }

}"""python C

3.2 实际的开发板上的程序，命名为aws.py,运行时为

python aws.py则启动了本程序。本ASK没有通过amazon的认证，所以还没有发布到amazon app store，只能在用本账户登录的Echo音箱，或者echosim.io网站上模拟测试，是语音交互的方式。

python语言交互性较好，不需要更多注释，可以直接读懂，

其中，

def do_fetch(voltage, current, temperature):

是其中关键的读取GPIO的函数，读出的数据作为publish的信息发布到MQTT的云端去。

ablot_cert,[size=1.4]      

"""python Cable Tracer running on Raspberry Pi"""

import adafruit_BBIO.GPIO as GPIO

import paho.mqtt.client as mqtt

import json, math, time, sys, ssl

import logging, logging.handlers, traceback

cert_path = "/Home/certs/"

host = "/a1enbuzxyq4gt0.iot.us-east-1.amazonaws.com"

topic = "$aws/things/CableTracer/shadow/update"

root_cert = cert_path + "184db63325-public.pem"

cert_file = cert_path + "184db63325-certificate.pem.crt"

key_file = cert_path + "184db63325-private.pem.key"

globalmessage = ""  # to send status back to MQTT -- voltage, current, temperature.

api = local_connect()

logger = logging.getLogger('cabletracer')

def do_turn(data):  #   {"name":"TurnIntent","slots":{"Onoff":{"name":"Onoff","value":"on"}}}

    Onoff = str(data["slots"]["Onoff"]["value"])

    logger.info("Onoff = " + onoff)

    global globalmessage

    if Onoff == "on":

        globalmessage = "Turn On"

        print globalmessage

        cabletracer_onoff = TRUE

    elif task == "off":

        globalmessage = "Turn Off"

        print globalmessage

        cabletracer_onoff = FALSE

def do_fetch(voltage, current, temperature):

    """

Seting Pin in analogIn and read data with analogue shield, since GPIO in Raspberry can only read digital LOW and digital HIGH

    """

    voltage = 1.0

    current = 1.0

    temperature =20

    # voltage = GPIO.analogIn(9)

    # current = GPIO.analogIn(10)

    # temperature = rpi.analogIn(11)   

    return voltage, current, temperature

def logger_init():

    logger.setLevel(logging.DEBUG)

    log_file_size = 1024 * 1024 * 1  # 1 MB

    formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(process)d - %(name)s : %(message)s')

    fh = logging.handlers.RotatingFileHandler('logs/echodronectl.log', maxBytes=log_file_size, backupCount=5)

    fh.setFormatter(formatter)

    sh = logging.StreamHandler(sys.stdout)

    sh.setFormatter(formatter)

    logger.addHandler(fh)

    logger.addHandler(sh)

    logger.info('******************************************')

    logger.info('Starting up...')

logger_init()

logger.info('setting up mqtt client')

client = mqtt.Client(client_id="echodronectl.py")

logger.info('completed setting up mqtt client')

client.on_connect = on_connect

client.on_message = on_message

client.on_log = on_log

client.tls_set(root_cert,

               certfile = cert_file,

               keyfile = key_file,

               tls_version=ssl.PROTOCOL_TLSv1_2,

               ciphers=None)

client.connect(host, 8883, 60)

#client.loop_forever()

run = True

while run:

    client.loop()

    do_fetch()

    do_turn()

    time.sleep(1)

    try:

        mypayload = '''{

        "Voltage": %s,

        "Current": %s,

        "Temperature": %s

        }''' % (voltage, current, temperature,cabletracer_onoff, globalmessage)

        client.publish(topic, mypayload)

    except (TypeError):

        pass

4、关于AWS开发是相对比较复杂的，对于其他的云端服务就相对容易得多。用简单API就可以实现，还可以在后台看到数据的历史记录。如果有时间，可以作为额外的对比内容。

lz这个项目介绍完了嘛?

也写了太多了，而且小编也催交作业了，近期不往下续写了，因为最近1个月要做其他的项目了。不过，围绕定制开发平台的测试才刚出发，还会把这个项目继续做下去的。

也写了太多了，而且小编也催交作业了，近期不往下续写了，因为最近1个月要做其他的项目了。不过，围绕定制开发平台的测试才刚出发，还会把这个项目继续做下去的。

看到论坛那些伪大神和马后炮我也是挺无奈的，实在看不下去，本身同根生，何必还要收费?大多数散户都没跑赢庄家，在这里我免费分享点个人多年珍藏的指标，互相交流，整体还是很实用。并且我的空间会分享每日大盘策略及荐股。欢迎交流！如果你觉得有问题，直接拉黑就行了。筘筘：201 925 567 验证113