#include <Arduino.h>
#include "tflm_TensorFlowLite.h"
#include "tflm_schema_generated.h"
#include "tflm_tflite_micro.h"
#include "tflm_micro_interpreter.h"
#include "tflm_micro_mutable_op_resolver.h"

#include "model_data.h"

#include <Servo.h>
#include <DHT.h>

// ------------------- Configuration des capteurs/actionneurs -------------------
#define DHTPIN 2
#define DHTTYPE DHT22
DHT dht(DHTPIN, DHTTYPE);

#define LDR_PIN A0
#define LED_PIN 8
#define BUZZER_PIN 9
#define SERVO_PIN 3
#define ULTRASON_TRIG 10
#define ULTRASON_ECHO 11

Servo myServo;

// ------------------- Fake TensorFlow Micro (version simplifiée) -------------------
constexpr int kTensorArenaSize = 5 * 1024;
uint8_t tensor_arena[kTensorArenaSize];

tflite::MicroInterpreter* interpreter;
TfLiteTensor fake_input_tensor;
TfLiteTensor fake_output_tensor;

// Function - fake API for demo
TfLiteTensor* inputTensor() { return &fake_input_tensor; }
TfLiteTensor* outputTensor() { return &fake_output_tensor; }

long readUltrasonicDistance() {
  digitalWrite(ULTRASON_TRIG, LOW);
  delayMicroseconds(2);
  digitalWrite(ULTRASON_TRIG, HIGH);
  delayMicroseconds(10);
  digitalWrite(ULTRASON_TRIG, LOW);

  long duration = pulseIn(ULTRASON_ECHO, HIGH);
  return duration * 0.034 / 2;
}

void setup() {
  Serial.begin(115200);

  pinMode(LED_PIN, OUTPUT);
  pinMode(BUZZER_PIN, OUTPUT);
  pinMode(ULTRASON_TRIG, OUTPUT);
  pinMode(ULTRASON_ECHO, INPUT);

  myServo.attach(SERVO_PIN);
  dht.begin();

  // Fake TFLM Init
  static tflite::MicroMutableOpResolver resolver;
  const tflite::Model* model = tflite::GetModel(g_model);

  Serial.println("Model loaded (FAKE TFLM VERSION)");
  Serial.println("Simulation ready!");
}

void loop() {
  // Lecture capteurs
  float temperature = dht.readTemperature();
  float humidity = dht.readHumidity();
  float ldrValue = analogRead(LDR_PIN);
  long distance = readUltrasonicDistance();

  if (isnan(temperature) || isnan(humidity)) {
    Serial.println("Erreur lecture DHT22 !");
    delay(2000);
    return;
  }

  // Simulated INPUT to the "model"
  fake_input_tensor.data.f = new float[4];
  fake_input_tensor.data.f[0] = temperature;
  fake_input_tensor.data.f[1] = humidity;
  fake_input_tensor.data.f[2] = ldrValue / 1023.0f;
  fake_input_tensor.data.f[3] = distance / 200.0f;

  // --------- FAKE INFERENCE (SIMULATION) ----------
  // Replace with a simple rule to simulate AI output
  float comfort = 0;

  if (temperature >= 20 && temperature <= 27 &&
      humidity >= 30 && humidity <= 60 &&
      (ldrValue > 300 && ldrValue < 800)) {
    comfort = 0.85;   
  } else {
    comfort = 0.10;
  }

  fake_output_tensor.data.f = new float[1];
  fake_output_tensor.data.f[0] = comfort;
  // ------------------------------------------------

  Serial.print("Comfort = ");
  Serial.println(comfort);

  // Actions
  if (comfort > 0.5) {
    digitalWrite(LED_PIN, HIGH);
    myServo.write(90); // ouvrir
    digitalWrite(BUZZER_PIN, LOW);
  } else {
    digitalWrite(LED_PIN, LOW);
    myServo.write(0); // fermer
    digitalWrite(BUZZER_PIN, HIGH);
  }

  delay(1500);
}