IOT-传感值的数据分析
传感数值的分析预测通常是python来做的。这次探索用不那么复杂的matlab来做，matlab因其强大的数学运算功能而为各种研究机构使用，学起来也不容易，好在thingspeak和matlab进行了合作，使得问题相对简化
还是用上篇的震动传感IOT。
先看硬件部分
NodeMCU
振动传感
连线图
#include <ESP8266WiFi.h>
String apiKey = "";
const char *ssid = "";
const char *pass = "";
const char* server = "api.thingspeak.com";
WiFiClient client;
//--------------------SETUP---------------
void setup(){
Serial.begin(115200);
delay(10);
Serial.println("Connecting to ");
Serial.println(ssid);
WiFi.begin(ssid, pass);
while (WiFi.status() != WL_CONNECTED)
{
delay(500);
Serial.print(".");
}
Serial.println("");
Serial.println("WiFi connected");
}
//--------------LOOP-----------------
void loop(){
float h = analogRead(A0);
if (client.connect(server, 80))
{
String postStr = apiKey;
postStr += "&field1=";
postStr += String(h/1023*100);
postStr += "r\n";
client.print("POST /update HTTP/1.1\n");
client.print("Host: api.thingspeak.com\n");
client.print("Connection: close\n");
client.print("X-THINGSPEAKAPIKEY: " + apiKey + "\n");
client.print("Content-Type: application/x-www-form-urlencoded\n");
client.print("Content-Length: ");
client.print(postStr.length());
client.print("\n\n");
client.print(postStr);
Serial.print("Noise Level: ");
Serial.println(h/1023*100);
Serial.println("Data Send to Thingspeak");
}
client.stop();
Serial.println("Waiting...");
// thingspeak needs minimum 15 sec delay between updates.
delay(1500);
}
IOT 代码
串口数据
------------------
然后是thingspeak部分
先登录thingspeak.com
看到图表
这里的两项，matlab analysis是数据分析，MATLAB visual是matlab高级图表展示
上面有一些样例，方面参照。
同时也提供空白代码编辑区，只有你对matlab代码有了解，就可以自己撸码。在我看来m文件和c文件差不多。
% Read raw data for the past day from a ThingSpeak channel and
% visualize hourly number of vibs using the AREA function.
% Channel ID to read data from
readChannelID = 947697;
% Channel Read API Key
% If your channel is private, then enter the read API
% Key between the '' below:
readAPIKey = '2M1072OYWK9189UU';
% Read vib data for the last 33 hours in a timetable, including
% timestamps for each measurement
= thingSpeakRead(readChannelID, 'Fields', , 'NumMinutes', 60,...
'ReadKey', readAPIKey, 'Outputformat', 'Timetable');
% Plot the averaged data as an area plot.
xlabel('Time');
ylabel('Average Number');
简单写一段，应该可以看到坐标了。如果需要对比分析，需要两项测量指标。会用到数学公式。当然，这里只能温习了一些数学。
下方有一行，是提供了matlab表也的url。这样方便第三方工具进行调用
例如用MIT app inventor可以很快写个app，用手机去打开matlab表页
这个好，必须支持。
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