#define POT_PIN 32
#define DETECT_LED 2
#define CAM_LED 4

#define SAMPLES 10

float prevAvg = 0;
bool captured = false;

// ----------- Get Average -----------
float getAverage() {
  float sum = 0;
  for (int i = 0; i < SAMPLES; i++) {
    sum += analogRead(POT_PIN);
    delay(5);
  }
  return sum / SAMPLES;
}

// ----------- Get Variance -----------
float getVariance(float avg) {
  float sum = 0;
  for (int i = 0; i < SAMPLES; i++) {
    float val = analogRead(POT_PIN);
    sum += (val - avg) * (val - avg);
    delay(5);
  }
  return sum / SAMPLES;
}

void setup() {
  Serial.begin(115200);
  pinMode(DETECT_LED, OUTPUT);
  pinMode(CAM_LED, OUTPUT);
}

void loop() {

  float avg = getAverage();
  float variance = getVariance(avg);
  float rate = abs(avg - prevAvg);

  prevAvg = avg;

  // -------- ML-like Scoring --------
  float score = (0.5 * avg) + (0.3 * variance) + (0.2 * rate);

  Serial.print("Avg: "); Serial.print(avg);
  Serial.print(" | Var: "); Serial.print(variance);
  Serial.print(" | Rate: "); Serial.print(rate);
  Serial.print(" | Score: "); Serial.println(score);

  // -------- Decision Boundary --------
  if (score > 2000 && !captured) {

    digitalWrite(DETECT_LED, HIGH);
    digitalWrite(CAM_LED, HIGH);

    Serial.println("⚠ ML Model: High probability of particles");
    Serial.println("Triggering camera...");
    delay(1000);

    Serial.println("Image Captured: sample.jpg");
    Serial.println("Sending to CV system...");
    Serial.println("---------------------------");

    captured = true;
  }

  else if (score < 1500) {
    Serial.println("Water Clear (ML confidence low)");

    digitalWrite(DETECT_LED, LOW);
    digitalWrite(CAM_LED, LOW);

    captured = false;
  }

  delay(1000);
}