How to efficiently stream sensor data from Arduino to Python for real-time AI analysis? [duplicate]
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?
