使用Bolt和LM35传感器构建温度监测系统电路

描述

目标：

创建有助于实现以下目标的设备：

• 虽然允许制造商将药片的温度保持在 -40 到 -30 摄氏度之间，但药片的温度不得一次保持在 -33 到 -30 度之间超过 20 分钟。
• 此外，制造商应记录用于生产片剂的冷却室何时打开。

项目目标：

Capstone 项目的目标如下。

A. 使用 Bolt 和 LM35 传感器构建温度监测系统电路。

• LM35 的 VCC 引脚连接到 Bolt Wifi 模块的 5v。（白线）
• LM35 的输出引脚连接到 Bolt Wifi 模块的 A0（interwetten与威廉的赔率体系 输入引脚）。（灰线）
• LM35 的 GND 引脚连接到 Gnd。（紫线）

 

B. 在 Bolt Cloud 上创建一个产品，以监控来自 LM35 的数据，并将其链接到您的 Bolt。

 

 

C. 编写产品代码，对 Bolt 发送的数据运行多项式回归算法。

带着这个目标，奈杰尔先生成功地满足了政府设定的第一个条件。使用预测数据，只要图表预测温度将保持在 -33 和 -30 摄氏度范围内超过 20 分钟，他就能够及早采取行动。

 

 

代码 ：

setChartLibrary('google-chart');
setChartTitle('Polynomial Regression');
setChartType('predictionGraph');
setAxisName('time_stamp','temp');
mul(0.0977);
plotChart('time_stamp','temp');

D. 将温度监测电路保持在冰箱内，关闭冰箱门，让系统记录温度读数约 2 小时。

 

 

E. 使用您在 2 小时内收到的读数，设置冰箱内温度的界限。

 

F. 编写一个 Python 代码，每 10 秒获取一次温度数据，如果温度超出您在目标“E”中确定的温度阈值，则发送电子邮件警报。

打开ubuntu服务器。

创建一个文件来存储凭据：

sudo nano email_conf.py

输入以下代码。

MAILGUN_API_KEY = 'This is the private API key which you can find on your Mailgun Dashboard' 
SANDBOX_URL= 'You can find this on your Mailgun Dashboard' 
SENDER_EMAIL = 'This would be test@your SANDBOX_URL'
RECIPIENT_EMAIL = 'Enter your Email ID Here'
API_KEY = 'This is your Bolt Cloud account API key'
DEVICE_ID = 'This is the ID of your Bolt device'
FRAME_SIZE = 10
MUL_FACTOR = 6

创建主代码文件：

sudo nano capstone_project.py

输入以下代码。

import email_conf, json, time, math, statistics
from boltiot import Email, Bolt

max_limit = 52
min_limit = -52

while True:
    response = mybolt.analogRead('A0')
    data = json.loads(response)
    if data['success'] != 1:
        print("There was an error while retriving the data.")
        print("This is the error:"+data['value'])
        time.sleep(10)
        continue

    print ("This is the value "+data['value'])
    sensor_value=0
    try:
        sensor_value = int(data['value'])
        if sensor_value > max_limit or sensor_value < min_limit:
            print("Making request to Mailgun to send an email")
            temperature = (100*sensor_value)/1024
            response = mailer.send_email("Alert!!", "The temperature of the refrigerator is " +str(temperature))
            response_text = json.loads(response.text)
            print("Response received from Mailgun is: " + str(response_text['message']))
    except e:
        print("There was an error while parsing the response: ",e)
        continue

G. 修改 Python 代码，同时进行 Z 分数分析，并在检测到异常时打印“有人打开冰箱门”这一行。

H. 调整 Z-score 分析代码，当有人打开冰箱门时，它会检测到异常。

最终代码：

import email_conf, json, time, math, statistics
from boltiot import Email, Bolt

max_limit = 52
min_limit = -52

def compute_bounds(history_data,frame_size,factor):
    if len(history_data)        return None

    if len(history_data)>frame_size :
        del history_data[0:len(history_data)-frame_size]
    Mn=statistics.mean(history_data)
    Variance=0
    for data in history_data :
        Variance += math.pow((data-Mn),2)
    Zn = factor * math.sqrt(Variance / frame_size)
    High_bound = history_data[frame_size-1]+Zn
    Low_bound = history_data[frame_size-1]-Zn
    return [High_bound,Low_bound]

mybolt = Bolt(email_conf.API_KEY, email_conf.DEVICE_ID)
mailer = Email(email_conf.MAILGUN_API_KEY, email_conf.SANDBOX_URL, email_conf.SENDER_EMAIL, email_conf.RECIPIENT_EMAIL)
history_data=[]

while True:
    response = mybolt.analogRead('A0')
    data = json.loads(response)
    if data['success'] != 1:
        print("There was an error while retriving the data.")
        print("This is the error:"+data['value'])
        time.sleep(10)
        continue

    print ("This is the value "+data['value'])
    sensor_value=0
    try:
        sensor_value = int(data['value'])
        if sensor_value > max_limit or sensor_value < min_limit:
            print("Making request to Mailgun to send an email")
            temperature = (100*sensor_value)/1024
            response = mailer.send_email("Alert!!", "The temperature of the refrigerator is " +str(temperature))
            response_text = json.loads(response.text)
            print("Response received from Mailgun is: " + str(response_text['message']))
    except e:
        print("There was an error while parsing the response: ",e)
        continue

    bound = compute_bounds(history_data,email_conf.FRAME_SIZE,email_conf.MUL_FACTOR)
    if not bound:
        required_data_count=email_conf.FRAME_SIZE-len(history_data)
        print("Not enough data to compute Z-score. Need ",required_data_count," more data points")
        history_data.append(int(data['value']))
        time.sleep(10)
        continue

    try:
        if sensor_value > bound[0] or sensor_value < bound[1]:
            print ("Someone has opened the refrigerator door.")
        history_data.append(sensor_value);
    except Exception as e:
        print ("Error",e)
    time.sleep(10)

输出：

运行代码：

sudo python3 capstone_project.py