I am working on a project involving an Arduino microcontroller and a Python-based AI model. My goal is to use the Arduino to read sensor data and send it to a PC via serial communication (UART) for real-time analysis.

What I have tried: I have set up the Arduino code to read sensors and use Serial.println() to output the data. On the PC side, I am attempting to use the pyserial library in Python to read these incoming strings.

The issue: However, I am struggling with data synchronization. Sometimes the Arduino sends data faster than Python reads it, leading to a buffer overflow or incomplete strings.

Here is my current code:

import serial

# Replace 'COM3' with the actual serial port name you are using.
ser = serial.Serial('COM3', 9600) 

while True:
    if ser.in_waiting > 0:
        line = ser.readline().decode('utf-8').rstrip()
        print(line)

void setup() {
  Serial.begin(9600); //  Set the serial transmission rate to 9600
}

void loop() {
  int sensorValue = analogRead(A0); // Read sensor values
  Serial.println(sensorValue);      // Transmit values ​​as strings
  delay(100);                       // Delay 100 milliseconds
}

Goal: I want to ensure the data stream is stable enough for an AI model to perform predictive analysis. Could anyone suggest a robust way to handle serial data streaming from a microcontroller to a PC for machine learning applications?