Machine learning interfaced with Arduino | 2024

#Arduino #MachineLearning #ArduinoArteficalIntellegence
In this video, we will interface Machine learning and Arduino on a Protes 8 professional software.
🤖 Explore the powerful combination of machine learning and Arduino! In this cutting-edge tutorial, we'll guide you through the process of interfacing machine learning algorithms with Arduino. Discover how to leverage the computational capabilities of Arduino to implement machine learning models for various applications. From image recognition to predictive analytics, unleash the potential of machine learning in your Arduino projects. Join us as we delve into the exciting world of machine learning interfaced with Arduino and unlock a new level of intelligence and automation!

Keywords: Machine learning, Arduino, machine learning interfacing, Arduino projects, artificial intelligence, predictive analytics, image recognition, intelligent automation, Arduino 2024, machine learning algorithms, computational capabilities, Arduino tutorial, machine learning applications, Arduino development, machine learning integration, Arduino machine learning projects, IoT, data analysis, intelligent decision-making, Arduino and ML, ML algorithms on Arduino, smart systems, DIY machine learning.

[makersgroup]

#include <Adafruit_Sensor.h>
#include "DHT.h"
#define DHTPIN 2 // Digital pin connected to the DHT sensor
#define DHTTYPE DHT11 // DHT 11
#include <LiquidCrystal.h>
#include<Wire.h>
LiquidCrystal lcd(13, 12, 11, 10, 9, 8);
DHT dht(DHTPIN, DHTTYPE);
int light= A0;
void setup()
{
Serial.begin(9600);
dht.begin();
delay(10);
lcd.begin(20, 4);
lcd.setCursor(0, 0);
lcd.print("Integrating");
lcd.setCursor(0, 1);
lcd.print("Machine learning");
lcd.setCursor(0, 2);
lcd.print("In Proteus simulation");
lcd.setCursor(0, 3);
lcd.print("!!!...");
delay(2000);
lcd.clear();
Serial.println("REBOOT");
}

void loop()
{
double k=analogRead(A0); // LDR reading
double h =
double t =
if (isnan(h) || isnan(t) )
{
Serial.println(F("Failed to read from DHT sensor!"));
}
double ProbablityRain=0.03743225*h - 2.21389335*t - 0.09773871*k +198.85713381876218;
lcd.setCursor(0, 0);
lcd.print("The Probablity of");
lcd.setCursor(0, 1);
lcd.print("Raining in % is ");
lcd.setCursor(0, 2);
lcd.print(ProbablityRain);
}

[milanvchristy]

i have one doubt what is the estimated time to build this project?

[mohamed.hesham]

can i get the project source code plzz ?

[CedrickJohnCALIB-OG]

do you have related articles or studies about this?

[jenildave]

This is not how you do. What about neural networks and deep learning models?