温度预测
温度预测
所需硬件
连接
将 LM35 传感器连接到螺栓
第 1 步:握住传感器,以便您可以读取上面写的 LM35。
第 2 步:在此位置,将传感器的引脚从左到右识别为 VCC、输出和接地。
在上图中,VCC 连接到红色线,输出连接到橙色线,Gnd 连接到棕色线。步骤 3:使用公对母线将 LM35 的 3 个引脚连接到 Bolt Wifi 模块,如下所示如下:
最终电路应如下图所示:
既然您知道多项式回归是什么,我们将使用它与 Bolt Cloud 来预测您房间的温度。
第 1 步:在“云、API 和警报”模块的“通过 VPS 连接传感器”主题中进行与“温度监视器的硬件连接”屏幕相同的连接。
Step 2: Power up the circuit and let it connect to the Bolt Cloud. (The Green LED of the Bolt should be on)
Step 3: Go to cloud.boltiot.com and create a new product. While creating the product, choose product type as Input Device and interface type as GPIO. After creating the product, select the recently created product and then click on configure icon.
Step 4: In the hardware tab, select the radio button next to the A0 pin. Give the pin the name 'temp' and save the configuration using the 'Save' icon.
Step 5: Move to the code tab, give the product code the name 'predict', and select the code type as js.
Step 6: Write the following code to plot the temperature data and run the polynomial regression algorithm on the data, and save the product configurations.
setChartLibrary('google-chart');
setChartTitle('Polynomial Regression');
setChartType('predictionGraph');
setAxisName('time_stamp', 'temp');
mul(0.0977);
plotChart('time_stamp', 'temp');
Step 7: In the products tab, select the product created and then click on the link icon. Select your Bolt device in the popup and then click the 'Done' button.
Step 8: Click on 'deploy configuration' button and then the 'view this device' icon to view the page that you have designed. Below is the screenshot of the final output.
Step 1: Connect the temperature monitoring circuit as we have done in the previous lesson -Hardware connections for temperature monitor.
Step 2: Login into the putty by entering the IP address of your digital ocean droplet.
Step 3: After successful login, create a file named conf.py which will store all the credentials related to Twilio. To create a new file type sudo nano conf.py in the terminal. After that write below code to save all the credentials in a single file.
SID = 'You can find SID in your Twilio Dashboard'
AUTH_TOKEN = 'You can find on your Twilio Dashboard'
FROM_NUMBER = 'This is the no. generated by Twilio. You can find this on your Twilio Dashboard'
TO_NUMBER = 'This is your number. Make sure you are adding +91 in beginning'
API_KEY = 'This is your Bolt Cloud accout API key'
DEVICE_ID = 'This is the ID of your Bolt device'
Note: You have to replace all the above value with your credentials. You can find the first four value in Twilio dashboard and the last two in Bolt Cloud dashboard.
We store all the credentials in a separate file since it is sensitive data which should not be shared with anyone. Hence it is a good practice to avoid using credentials in code directly. After replacing all the values, save the file using CTRL+X.
Step 4: Now create one more file named temp_sms.py. To do so you have to type sudo nano temp_sms.py in the terminal. Now we will write main code to collect the data from the Bolt and send SMS if it crosses the threshold.
The algorithm for the code can be broken down into the following steps -
Fetch the latest sensor value from the Bolt device.
Check if the sensor value is in the range specified in our min and max values.
If it is not in range, send the SMS.
Wait for 10 seconds.
Repeat from step 1.
Now we will initialize two variables which will store minimum and maximum threshold value. You can initialize any minimum and maximum integer limits to them.
minimum_limit = 300
maximum_limit = 600
mybolt = Bolt(conf.API_KEY, conf.DEVICE_ID)
sms = Sms(conf.SID, conf.AUTH_TOKEN, conf.TO_NUMBER, conf.FROM_NUMBER)
while True:
print ("Reading sensor value")
response = mybolt.analogRead('A0')
data = json.loads(response)
print("Sensor value is: " + str(data['value']))
try:
sensor_value = int(data['value'])
if sensor_value > maximum_limit or sensor_value < minimum_limit:
print("Making request to Twilio to send a SMS")
response = sms.send_sms("The Current temperature sensor value is " +str(sensor_value))
print("Response received from Twilio is: " + str(response))
print("Status of SMS at Twilio is :" + str(response.status))
except Exception as e:
print ("Error occured: Below are the details")
print (e)
time.sleep(10)
In the above code, we are fetching the data every 10sec. You can change the value but ideally, it should be good if the time interval between 2 data points is more than 10sec.
Below is the complete code:
import conf
from boltiot import Sms, Bolt
import json, time
minimum_limit = 300
maximum_limit = 600
mybolt = Bolt(conf.API_KEY, conf.DEVICE_ID)
sms = Sms(conf.SID, conf.AUTH_TOKEN, conf.TO_NUMBER, conf.FROM_NUMBER)
while True:
print ("Reading sensor value")
response = mybolt.analogRead('A0')
data = json.loads(response)
print("Sensor value is: " + str(data['value']))
try:
sensor_value = int(data['value'])
if sensor_value > maximum_limit or sensor_value < minimum_limit:
print("Making request to Twilio to send a SMS")
response = sms.send_sms("The Current temperature sensor value is " +str(sensor_value))
print("Response received from Twilio is: " + str(response))
print("Status of SMS at Twilio is :" + str(response.status))
except Exception as e:
print ("Error occured: Below are the details")
print (e)
time.sleep(10)
Note: The above "sensor_value" is the raw temperature reading, obtained from the LM35 sensor. In case you want to convert this value to the temperature in degree Celsius, use the formula:
Where sensor_value is the variable in which data obtained from the LM35 sensor is stored.
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