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How to Ensure Reliable Data and Predictions for Skin Cancer Detection Using ESP32 and TCS3200?

Am working on an AI-powered health monitoring system using an `ESP32` and a `TCS3200` Color Sensor to analyze skin pigmentation and detect potential cancerous cells by identifying irregularities in skin color. The sensor initializes correctly, but I am encountering inconsistent data, leading to incorrect predictions about potential skin cancer.

my aim is to:

– Use machine learning to analyze color data and predict the presence of cancerous cells based on irregular pigmentation.

– Ensure reliable predictions with consistent data from the sensor.

this is my code

  1. Renuel Roberts#0000
    import machine
    import time
    from machine import Pin
    import random  # Simulating the machine learning prediction
    
    # Setup for TCS3200 Color Sensor
    S2 = Pin(15, Pin.OUT)
    S3 = Pin(2, Pin.OUT)
    out = Pin(4, Pin.IN)  # Output from sensor
    S2.off()
    S3.off()
    
    # Initialize variables
    color_data = {'red': 0, 'green': 0, 'blue': 0}
    threshold = 50  # Example threshold for detecting cancerous cells
    sensor_error = False
    
    # Simulated AI-based cancer detection (replace with an actual ML model later)
    def detect_cancerous_cells(color_data):
        # Simulating a machine learning-based prediction for cancer detection
        avg_color = (color_data['red'] + color_data['green'] + color_data['blue']) / 3
        return random.choice([True, False]) if avg_color < threshold else False
    
    def read_color():
        # Dummy function to simulate reading from the TCS3200 sensor
        # Replace with actual sensor reading logic
        return {'red': random.randint(20, 80), 'green': random.randint(20, 80), 'blue': random.randint(20, 80)}
    
    def calculate_average_color(color_data):
        # Calculate the average color value from red, green, and blue components
        return (color_data['red'] + color_data['green'] + color_data['blue']) / 3
    
    # Main loop
    while True:
        try:
            color_data = read_color()
            print("Color Data:", color_data)
    
            avg_color = calculate_average_color(color_data)
            print("Average Color Value:", avg_color)
            
            # Perform AI-based cancerous cell detection
            cancer_detected = detect_cancerous_cells(color_data)
            if cancer_detected:
                print("Warning: Potential cancerous cells detected!")
            else:
                print("Skin pigmentation is within normal range.")
    
        except OSError as e:
            print("Error reading color sensor data. Check wiring or sensor condition.")
            sensor_error = True
            break
        
        time.sleep(1)
    
  2. Renuel Roberts#0000

    How do I resolve these inconsistent data that sabotages the prediction of my code across multiple streams of data I have acquired for this project?

  3. wafa_ath#0000

    try to implement a moving average filter for sensor readings. This will smooth out fluctuations and reduce noise , check this out https://www.youtube.com/watch?v=QHWaJMncC9Q&ab_channel=VLSITechwithAnoushka

  4. Renuel Roberts#0000

    Hello @wafa_ath thanks for the video link I went through it and followed the process it worked out well, just that now some of my image data now comes out invalid

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