# O3-enabled BLE Weather Station Predicting Air Quality w/ TensorFlow
#
# Windows, Linux, or Ubuntu
#
# By Kutluhan Aktar
#
# Via Nano 33 BLE, collate local weather data, build and train a TensorFlow neural network model, and run the model to predict air quality.
# 
#
# For more information:
# https://www.theamplituhedron.com/projects/O3_enabled_BLE_Weather_Station_Predicting_Air_Quality_w_TensorFlow/

import tensorflow as tf
from tensorflow import keras
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from tflite_to_c_array import hex_to_c_array
from labels import labels

# Create a class to build a neural network model after visualizing and scaling (normalizing) the local weather data collected by the Arduino Nano 33 BLE.
class Air_Quality_Level:
    def __init__(self, csv_path):
        self.inputs = []
        self.labels = []
        self.model_name = "air_quality_level"
        # Read the collated local weather data set:
        self.df = pd.read_csv(csv_path)
    # Create graphics for each requested column.
    def graphics(self, column_1, column_2, x_label, y_label):
        # Show the requested data column from the data set:
        plt.style.use("dark_background")
        plt.gcf().canvas.set_window_title('O3-enabled BLE Weather Station Predicting Air Quality')
        plt.hist2d(self.df[column_1], self.df[column_2], cmap="summer_r")
        plt.colorbar()
        plt.xlabel(x_label)
        plt.ylabel(y_label)
        plt.title(x_label)
        plt.show()
    # Visualize data before creating and training the neural network model.
    def data_visualization(self):
        # Scrutinize data columns to build a model with appropriately formatted data:
        self.graphics('Temperature', 'Ozone_Concentration', 'Temperature', 'Ozone Concentration')
        self.graphics('Altitude', 'Ozone_Concentration', 'Altitude', 'Ozone Concentration')
        self.graphics('Pressure', 'Ozone_Concentration', 'Pressure', 'Ozone Concentration')
        self.graphics('Wind Speed', 'Ozone_Concentration', 'Wind Speed', 'Ozone Concentration')
    # Scale (normalize) data to define appropriately formatted inputs.
    def scale_data_and_define_inputs(self):
        self.df["scaled_Temperature"] = self.df["Temperature"] / 100
        self.df["scaled_Altitude"] = self.df["Altitude"] / 100
        self.df["scaled_Ozone"] = self.df["Ozone_Concentration"] / 1000
        self.df["scaled_Pressure"] = self.df["Pressure"] / 100000
        self.df["scaled_Wind_Speed"] = self.df["Wind Speed"] / 30
        # Create the inputs array by utilizing the scaled variables:
        for i in range(len(self.df)):
            self.inputs.append(np.array([self.df["scaled_Temperature"][i], self.df["scaled_Altitude"][i], self.df["scaled_Ozone"][i], self.df["scaled_Pressure"][i], self.df["scaled_Wind_Speed"][i]]))
        self.inputs = np.asarray(self.inputs)
    # Assign labels for each weather data input according to the Air Quality Index (AQI) on the given date.
    def define_and_assign_labels(self):
        self.labels = labels
    # Split inputs and labels into training and test sets.
    def split_data(self):
        l = len(self.df)
        # (95%, 5%) - (training, test)
        self.train_inputs = self.inputs[0:int(l*0.95)]
        self.test_inputs = self.inputs[int(l*0.95):]
        self.train_labels = self.labels[0:int(l*0.95)]
        self.test_labels = self.labels[int(l*0.95):]
    # Build and train an artificial neural network (ANN) model to make predictions on air quality levels (classes) based on the local weather data.
    def build_and_train_model(self):
        # Build the neural network:
        self.model = keras.Sequential([
            keras.Input(shape=(5,)),
            keras.layers.Dense(128, activation='relu'),
            keras.layers.Dense(64, activation='relu'),
            keras.layers.Dense(3, activation='softmax')
        ])
        # Compile:
        self.model.compile(optimizer='adam', loss="sparse_categorical_crossentropy", metrics=['accuracy'])
        # Train:
        self.model.fit(self.train_inputs, self.train_labels, epochs=100)
        # Test the model accuracy:
        print("\n\nModel Evaluation:")
        test_loss, test_acc = self.model.evaluate(self.test_inputs, self.test_labels) 
        print("Evaluated Accuracy: ", test_acc)
    # Save the model for further usage:
    def save_model(self):
        self.model.save("model/{}.h5".format(self.model_name))        
    # Convert the TensorFlow Keras H5 model (.h5) to a TensorFlow Lite model (.tflite).
    def convert_TF_model(self, path):
        #model = tf.keras.models.load_model(path + ".h5")
        converter = tf.lite.TFLiteConverter.from_keras_model(self.model)
        #converter.optimizations = [tf.lite.Optimize.DEFAULT]
        #converter.target_spec.supported_types = [tf.float16]
        tflite_model = converter.convert()
        # Save the recently converted TensorFlow Lite model.
        with open(path + '.tflite', 'wb') as f:
            f.write(tflite_model)
        print("\r\nTensorFlow Keras H5 model converted to a TensorFlow Lite model!\r\n")
        # Convert the recently created TensorFlow Lite model to hex bytes (C array) to generate a .h file string.
        with open("model/{}.h".format(self.model_name), 'w') as file:
            file.write(hex_to_c_array(tflite_model, self.model_name))
        print("\r\nTensorFlow Lite model converted to a C header (.h) file!\r\n")
    # Run Artificial Neural Network (ANN):
    def Neural_Network(self, save):
        self.scale_data_and_define_inputs()
        self.define_and_assign_labels()
        self.split_data()
        self.build_and_train_model()
        if save:
            self.save_model()
    
# Define a new class object named 'air_quality_level':
air_quality_level = Air_Quality_Level("data/air_quality_data_set.csv")

# Visualize data columns:
air_quality_level.data_visualization()

# Artificial Neural Network (ANN):        
air_quality_level.Neural_Network(True)        
        
# Convert the TensorFlow Keras H5 model to a TensorFlow Lite model:
air_quality_level.convert_TF_model("model/{}".format(air_quality_level.model_name))
     

import numpy as np

labels = np.array([1,1,2,2,2,1,1,1,1,2,2,1,1,2,1,2,2,2,2,2,2,1,1,2,1,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,2,2,1,2,2,2,2,1,2,1,2,2,2,2,2,1,1,1,1,1,1,1,2,2,1,1,1,2,1,1,2,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,1,2,1,1,2,1,1,1,1,1,2,2,1,1,1,1,1,2,2,1,2,2,1,2,2,2,2,2,2,1,2,1,1,2,2,2,2,2,2,2,2,2,2,1,2,2,1,1,1,1,2,2,1,2,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,1,1,2,2,2,2,2,2,2,1,1,1,1,2,1,1,1,1,2,1,1,1,1,1,2,2,1,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,1,2,2,2,1,1,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,2,1,2,1,2,2,2,2,1,2,2,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,2,2,1,2,2,2,2,1,2,2,2,2,2,1,1,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,1,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,2,1,2,2,2,2,1,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,1,1,1,2,2,2,2,2,2,2,2,1,2,2,2,1,2,1,1,2,2,1,1,2,2,1,1,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,2,1,1,2,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,2,2,1,2,2,2,1,1,1,1,2,1,1,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,2,1,1,2,2,2,1,2,2,2,2,1,1,1,2,1,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,1,2,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,1,2,2,1,2,1,2,1,2,2,1,2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,1,2,2,1,1,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,2,2,2,2,2,2,2,2,2,1,1,1,2,2,2,1,2,2,2,1,2,1,1,1,1,1,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,1,1,2,1,1,1,2,2,2,2,2,2,2,2,2,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,2,2,2,1,1,1,2,2,2,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,2,2,2,1,2,1,1,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,2,2,2,2,2,2,2,1,1,2,2,2,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,1,2,2,2,1,2,2,2,2,2,2,1,1,2,2,2,1,1,2,1,1,2,2,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,2,1,2,2,1,1,2,2,1,1,2,1,2,2,2,2,1,2,2,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,1,2,2,1,2,2,2,2,1,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,2,1,1,1,1,1,2,1,2,2,2,2,2,2,1,1,1,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,1,2,2,2,2,2,1,1,1,2,0,0,0,0,0,0,2,2,2,2,0,0,0,2,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,2,2,2,2,2,2,2,2,2,2,2,2,2,0,2,2,2,2,2,2,0,0,2,2,2,2,0,0,0,0,2,2,2,0,0,2,2,2,2,0,0,2,2,2,2,0,0,0,0,2,2,0,2,2,0,0,0,0,0,0,2,2,2,0,2,2,2,2,2,2,0,0,2,2,0,2,2,2,2,2,2,2,2,2,0,0,0,2,2,2,2,0,2,2,0,0,0,2,2,0,2,2,2,0,2,2,2,2,2,2,2,2,2,0,0,0,0,2,2,2,0,2,2,2,2,2,2,2,2,2,2,0,0,2,2,2,2,0,0,0,0,2,2,2,0,0,2,0,0,2,2,2,2,2,2,0,0,0,2,2,2,2,0,0,0,0,0,2,2,2,2,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,2,2,2,2,2,0,2,2,2,2,2,2,2,2,2,2,2,2,2,0,2,0,0,2,2,2,2,2,2,0,0,2,2,2,2,2,2,0,0,0,0,0,2,2,2,2,0,2,0,2,2,0,0,0,2,0,2,2,2,0,0,2,2,2,2,2,2,2,2,2,0,0,0,0,0,0,2,2,2,2,2,2,0,2,0,0,0,0,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0,0,2,2,2,2,2,2,2,2,2,2,2,2,0,2,0,0,0,0,2,2,2,0,2,0,2,0,0,0,0,2,2,2,0,2,2,0,0,0,2,0,0,0,0,0,0,0,0,0,2,2,2,2,0,0,0,0,0,0,0,2,2,2,2,2,0,2,2,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,2,2])

#print(len(labels))

# Code from:
# https://www.digikey.com/en/maker/projects/intro-to-tinyml-part-1-training-a-model-for-arduino-in-tensorflow/8f1fc8c0b83d417ab521c48864d2a8ec
# By Shawn Hymel

# Function: Convert some hex value into an array for C programming
def hex_to_c_array(hex_data, var_name):

  c_str = ''

  # Create header guard
  c_str += '#ifndef ' + var_name.upper() + '_H\n'
  c_str += '#define ' + var_name.upper() + '_H\n\n'

  # Add array length at top of file
  c_str += '\nunsigned int ' + var_name + '_len = ' + str(len(hex_data)) + ';\n'

  # Declare C variable
  c_str += 'unsigned char ' + var_name + '[] = {'
  hex_array = []
  for i, val in enumerate(hex_data) :

    # Construct string from hex
    hex_str = format(val, '#04x')

    # Add formatting so each line stays within 80 characters
    if (i + 1) < len(hex_data):
      hex_str += ','
    if (i + 1) % 12 == 0:
      hex_str += '\n '
    hex_array.append(hex_str)

  # Add closing brace
  c_str += '\n ' + format(' '.join(hex_array)) + '\n};\n\n'

  # Close out header guard
  c_str += '#endif //' + var_name.upper() + '_H'

  return c_str

# O3-enabled BLE Weather Station Predicting Air Quality w/ TensorFlow
#
# Windows, Linux, or Ubuntu
#
# By Kutluhan Aktar
#
# Via Nano 33 BLE, collate local weather data, build and train a TensorFlow neural network model, and run the model to predict air quality.
# 
#
# For more information:
# https://www.theamplituhedron.com/projects/O3_enabled_BLE_Weather_Station_Predicting_Air_Quality_w_TensorFlow/

from bluepy import btle
from struct import unpack
from csv import writer
from time import sleep
import datetime

class air_quality:
    def __init__(self):
        # Define the Arduino Nano 33 BLE's address information:
        self.MAC_Address = "4c:f9:a9:9a:b2:da"
        self.Service_UUID_Address = "19B10000-E8F2-537E-4F6C-D104768A1214"
        self.Characteristic_UUID_Address = "19B10001-E8F2-537E-4F6C-D104768A1214"
        # Define the peripheral device:
        self.device = btle.Peripheral(self.MAC_Address)
        # Define the characteristics:
        self.characteristics = self.device.getCharacteristics()
    # Display the given service's information if required.
    def print_service(self):
        service = self.device.getServiceByUUID(btle.UUID(self.Service_UUID_Address))
        print(service.getCharacteristics())
    # Obtain the local weather data from the Arduino Nano 33 BLE. 
    def obtain_characteristics(self):
        self.air_data = []
        # Create the air quality data array:
        for data in self.characteristics:
            if(data.uuid == self.Characteristic_UUID_Address):
                #print(data.read())
                self.air_data.extend(unpack('ffiii', data.read()))
                # Add the date to the air quality data array:
                _date = datetime.datetime.now().strftime("%m-%d-%y_%H:%M:%S")
                self.air_data.append(_date)
                # Print the air quality data array:
                print(self.air_data)
        sleep(1)
    # Insert the recently generated air quality data array into the given CSV file.
    def insert_data_to_CSV(self, file_name):
        with open(file_name, "a", newline="") as f:
            # Add a new row:
            writer(f).writerow(self.air_data)
            f.close()

air_quality_data = air_quality()
#air_quality_data.print_service()

try:
    while True:
        # Get the updated characteristics and insert them into the given CSV file every 30 seconds:
        air_quality_data.obtain_characteristics()
        air_quality_data.insert_data_to_CSV("air_quality_data_set.csv")
        sleep(30)
except KeyboardInterrupt:
        # Disconnect BLE:
        air_quality_data.device.disconnect()
        print("\r\nPeripheral Disconnected!")

         /////////////////////////////////////////////  
        //     O3-enabled BLE Weather Station      //
       //   Predicting Air Quality w/ TensorFlow  //
      //             ---------------             //
     //          (Arduino Nano 33 BLE)          //           
    //             by Kutluhan Aktar           // 
   //                                         //
  /////////////////////////////////////////////

//
// Via Nano 33 BLE, collate local weather data, build and train a TensorFlow neural network model, and run the model to predict air quality.
//
// For more information:
// https://www.theamplituhedron.com/projects/O3_enabled_BLE_Weather_Station_Predicting_Air_Quality_w_TensorFlow/
//
//
// Connections
// Arduino Nano 33 BLE :  
//                                DFRobot IIC Ozone Sensor
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                BMP180 Barometric Pressure/Temperature/Altitude Sensor
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                SSD1306 OLED Display (128x64)
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                DFRobot Anemometer Kit
// A0  --------------------------- S (Yellow)
//                                5mm Green LED
// D2  --------------------------- +


// Include the required libraries.
#include <ArduinoBLE.h>
#include "DFRobot_OzoneSensor.h"
#include <Adafruit_BMP085.h>
#include <Adafruit_GFX.h>
#include <Adafruit_SSD1306.h>

// Create the BLE service:
BLEService air_quality_service("19B10000-E8F2-537E-4F6C-D104768A1214");

// Create the data characteristic and allow the remote device (central) to read and write:
BLECharacteristic airDataCharacteristic("19B10001-E8F2-537E-4F6C-D104768A1214", BLERead | BLEWrite, 20);

// Define the collect number. The collection range is 1-100: 
#define COLLECT_NUMBER   20 

// To modify the I2C address, configure the hardware IIC address by the dial switch - A0, A1 (ADDRESS_0 for [0 0]), (ADDRESS_1 for [1 0]), (ADDRESS_2 for [0 1]), (ADDRESS_3 for [1 1]).              
/*  
    The default IIC device address is ADDRESS_3: 
       ADDRESS_0               0x70  
       ADDRESS_1               0x71
       ADDRESS_2               0x72
       ADDRESS_3               0x73
*/
#define Ozone_IICAddress ADDRESS_3

// Define the IIC Ozone Sensor.
DFRobot_OzoneSensor Ozone;

// Define the timer for the IIC Ozone Sensor.
unsigned long ozone_timer = 0;
unsigned long timer = 0;

// Define the BMP180 Barometric Pressure/Temperature/Altitude Sensor.
Adafruit_BMP085 bmp;

// Define the anemometer kit's voltage signal pin (yellow).
#define  anemometer_signal A0

// Define the notification LED.
#define notification 2

// Define the SSD1306 screen settings:
#define SCREEN_WIDTH 128 // OLED display width, in pixels
#define SCREEN_HEIGHT 64 // OLED display height, in pixels
#define OLED_RESET    -1 // Reset pin # (or -1 if sharing Arduino reset pin)

Adafruit_SSD1306 display(SCREEN_WIDTH, SCREEN_HEIGHT, &Wire, OLED_RESET);

// Define monochrome graphics:
static const unsigned char PROGMEM _error [] = {
0x00, 0x00, 0x00, 0x00, 0x00, 0x3F, 0xFC, 0x00, 0x00, 0xE0, 0x07, 0x00, 0x01, 0x80, 0x01, 0x80,
0x06, 0x00, 0x00, 0x60, 0x0C, 0x00, 0x00, 0x30, 0x08, 0x01, 0x80, 0x10, 0x10, 0x03, 0xC0, 0x08,
0x30, 0x02, 0x40, 0x0C, 0x20, 0x02, 0x40, 0x04, 0x60, 0x02, 0x40, 0x06, 0x40, 0x02, 0x40, 0x02,
0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02,
0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x03, 0xC0, 0x02, 0x40, 0x01, 0x80, 0x02,
0x40, 0x00, 0x00, 0x02, 0x60, 0x00, 0x00, 0x06, 0x20, 0x01, 0x80, 0x04, 0x30, 0x03, 0xC0, 0x0C,
0x10, 0x03, 0xC0, 0x08, 0x08, 0x01, 0x80, 0x10, 0x0C, 0x00, 0x00, 0x30, 0x06, 0x00, 0x00, 0x60,
0x01, 0x80, 0x01, 0x80, 0x00, 0xE0, 0x07, 0x00, 0x00, 0x3F, 0xFC, 0x00, 0x00, 0x00, 0x00, 0x00
};
static const unsigned char PROGMEM _weather [] = {
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x02, 0x10, 0x00, 0x00,
0x02, 0x11, 0x00, 0x00, 0x01, 0x10, 0x00, 0x00, 0x01, 0x12, 0x00, 0x00, 0x10, 0xFC, 0x10, 0x00,
0x09, 0xFE, 0x60, 0x00, 0x07, 0x87, 0x80, 0x00, 0x03, 0x02, 0x00, 0x00, 0x03, 0x00, 0x7E, 0x00,
0x02, 0x00, 0xFF, 0x80, 0x02, 0x01, 0xC1, 0xC0, 0x03, 0x01, 0x80, 0xC0, 0x02, 0x1F, 0x00, 0x60,
0x04, 0x3B, 0x00, 0x60, 0x18, 0x60, 0x00, 0x60, 0x10, 0x40, 0x00, 0x70, 0x00, 0xC0, 0x00, 0x18,
0x07, 0xC0, 0x00, 0x0C, 0x0F, 0xC0, 0x00, 0x04, 0x0C, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x04,
0x18, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x0C, 0x0C, 0x00, 0x00, 0x0C, 0x0E, 0x00, 0x00, 0x38,
0x07, 0xFF, 0xFF, 0xF0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00
};

// Create a struct (data) including all air quality data parameters:
struct data {
  float _temperature;
  float _altitude;
  int ozoneConcentration;
  int _pressure;
  int wind_speed;
};

// Define the data holders: 
struct data air_Quality_Data;
float _temperature, _altitude, _real_altitude;
int ozoneConcentration, _pressure, _sea_level_pressure, wind_speed;

void setup(){
  Serial.begin(9600);
  // Wait for the serial monitor to be initialized so as to display this peripheral device's address information successfully:
  //while(!Serial);

  pinMode(notification, OUTPUT);

  // Start the timer:
  ozone_timer = millis();

  // Initialize the SSD1306 screen:
  display.begin(SSD1306_SWITCHCAPVCC, 0x3C);
  display.display();
  delay(1000);
  
  // Check the IIC Ozone Sensor connection status:
  while(!Ozone.begin(Ozone_IICAddress)){
    Serial.println("IIC Ozone Sensor is not found!");
    err_msg();
    delay(1000);
  }
  Serial.println("\nIIC Ozone Sensor is connected successfully!\n");
  
  /*   
     Set IIC Ozone Sensor mode:
       MEASURE_MODE_AUTOMATIC    // active  mode
       MEASURE_MODE_PASSIVE      // passive mode
  */
  Ozone.SetModes(MEASURE_MODE_PASSIVE);

  // Check the BMP180 Barometric Pressure/Temperature/Altitude Sensor connection status: 
  while(!bmp.begin()){
    Serial.println("BMP180 Barometric Pressure/Temperature/Altitude Sensor is not found!");
    err_msg();
    delay(1000);
  }
  Serial.println("\nBMP180 Barometric Pressure/Temperature/Altitude Sensor is connected successfully!\n");

  // Check the BLE initialization status:
  while(!BLE.begin()){
    Serial.println("BLE initialization is failed!");
    err_msg();
  }
  Serial.println("\nBLE initialization is successful!\n");
  // Print this peripheral device's address information:
  Serial.print("MAC Address: "); Serial.println(BLE.address());
  Serial.print("Service UUID Address: "); Serial.println(air_quality_service.uuid());
  Serial.print("Characteristic UUID Address: ");Serial.println(airDataCharacteristic.uuid());
  Serial.println();

  // Set the local name this peripheral advertises: 
  BLE.setLocalName("AirQuality");
  // Set the UUID for the service this peripheral advertises:
  BLE.setAdvertisedService(air_quality_service);

  // Add the given characteristic to the service:
  air_quality_service.addCharacteristic(airDataCharacteristic);

  // Add the service to the device:
  BLE.addService(air_quality_service);

  // Assign event handlers for connected, disconnected devices to this peripheral:
  BLE.setEventHandler(BLEConnected, blePeripheralConnectHandler);
  BLE.setEventHandler(BLEDisconnected, blePeripheralDisconnectHandler);

  // Set the initial value for the given characteristic: 
  airDataCharacteristic.writeValue((byte)0);

  // Start advertising:
  BLE.advertise();
  Serial.println(("Bluetooth device active, waiting for connections..."));

  display.clearDisplay();   
  display.setTextSize(2); 
  display.setTextColor(SSD1306_BLACK, SSD1306_WHITE);
  display.setCursor(0,0);
  display.println("Heating...");
  display.display();
}


void loop(){
  // Wait until the IIC Ozone Sensor heats for 3 minutes.
  while (millis() - ozone_timer < 3*60*1000){ if (millis() - timer > 1000){ timer = millis(); } }
  // Transmit the collected weather (air quality) data to Raspberry Pi over BLE every 20 seconds.
  if (millis() - timer > 20000){
    update_characteristics();
    // After updating characteristics, notify the user.
    display.clearDisplay();   
    display.drawBitmap(48, 0, _weather, 32, 32, SSD1306_WHITE);
    display.setTextSize(1); 
    display.setTextColor(SSD1306_WHITE);
    display.setCursor(0,40);
    display.println("Given BLE characteristics are updated successfully!");
    display.display();
    digitalWrite(notification, HIGH); delay(1500); digitalWrite(notification, LOW);  
    timer = millis();
  }
  
  collect_ozone_concentration();
  delay(1000);
  collect_BMP180_data();
  delay(500);
  collect_anemometer_data();
  delay(250);
  
  // Show the collected weather (air quality) data on the screen.
  show_weather_data();

  // Poll for BLE events:
  BLE.poll();
}

void collect_ozone_concentration(){
  ozoneConcentration = Ozone.ReadOzoneData(COLLECT_NUMBER);
  Serial.print("\n\nOzone Concentration => "); Serial.print(ozoneConcentration); Serial.println(" PPB");
}

void collect_BMP180_data(){
  _temperature = bmp.readTemperature();
  _pressure = bmp.readPressure();
  // Calculate altitude assuming 'standard' barometric pressure of 1013.25 millibars (101325 Pascal).
  _altitude = bmp.readAltitude();
  _sea_level_pressure = bmp.readSealevelPressure();
  // To get a more precise altitude measurement, use the current sea level pressure, which will vary with the weather conditions. 
  _real_altitude = bmp.readAltitude(101500);
  // Print the data generated by the BMP180 Barometric Pressure/Temperature/Altitude Sensor.
  Serial.print("Temperature => "); Serial.print(_temperature); Serial.println(" *C");
  Serial.print("Pressure => "); Serial.print(_pressure); Serial.println(" Pa");
  Serial.print("Altitude => "); Serial.print(_altitude); Serial.println(" meters");
  Serial.print("Pressure at sea level (calculated) => "); Serial.print(_sea_level_pressure); Serial.println(" Pa");
  Serial.print("Real Altitude => "); Serial.print(_real_altitude); Serial.println(" meters");
}

void collect_anemometer_data(){
  float outvoltage = (analogRead(A0) * (3.3 / 1023.0)) + 0.1;
  // Calculate the wind speed (level) [1 - 30] according to the output voltage: 
  wind_speed = 6 * outvoltage;
  // Print the data generated by the Anemometer Kit.
  Serial.print("Wind Speed (Level) => "); Serial.print(wind_speed);
}

void show_weather_data(){
  display.clearDisplay();   
  display.setTextSize(1); 
  display.setTextColor(SSD1306_WHITE);
  display.setCursor(0,8); 
  display.println("Ozone Con. => " + String(ozoneConcentration) + " PPB");
  display.println("Wind Speed => " + String(wind_speed));
  display.println("Temp. => " + String(_temperature) + " *C");
  display.println("Pressure => " + String(_pressure) + " Pa");
  display.println("Altitude => " + String(_altitude) + " m");
  display.display();  
}

void err_msg(){
  // Show the error message on the SSD1306 screen.
  display.clearDisplay();   
  display.drawBitmap(48, 0, _error, 32, 32, SSD1306_WHITE);
  display.setTextSize(1); 
  display.setTextColor(SSD1306_WHITE);
  display.setCursor(0,40); 
  display.println("Check the serial monitor to see the error!");
  display.display();  
}

void blePeripheralConnectHandler(BLEDevice central) {
  // Central connected event handler:
  Serial.print("Connected event, central: ");
  Serial.println(central.address());
}

void blePeripheralDisconnectHandler(BLEDevice central) {
  // Central disconnected event handler:
  Serial.print("Disconnected event, central: ");
  Serial.println(central.address());
}

void update_characteristics(){
  // Update the data characteristic with the data struct:
  air_Quality_Data._temperature = _temperature;
  air_Quality_Data._altitude = _altitude;
  air_Quality_Data.ozoneConcentration = ozoneConcentration;
  air_Quality_Data._pressure = _pressure;
  air_Quality_Data.wind_speed = wind_speed;
  airDataCharacteristic.writeValue((byte *) &air_Quality_Data, 20);
}

         /////////////////////////////////////////////  
        //     O3-enabled BLE Weather Station      //
       //   Predicting Air Quality w/ TensorFlow  //
      //             ---------------             //
     //          (Arduino Nano 33 BLE)          //           
    //             by Kutluhan Aktar           // 
   //                                         //
  /////////////////////////////////////////////

//
// Via Nano 33 BLE, collate local weather data, build and train a TensorFlow neural network model, and run the model to predict air quality.
//
// For more information:
// https://www.theamplituhedron.com/projects/O3_enabled_BLE_Weather_Station_Predicting_Air_Quality_w_TensorFlow/
//
//
// Connections
// Arduino Nano 33 BLE :  
//                                DFRobot IIC Ozone Sensor
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                BMP180 Barometric Pressure/Temperature/Altitude Sensor
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                SSD1306 OLED Display (128x64)
// A4  --------------------------- SDA
// A5  --------------------------- SCL
//                                DFRobot Anemometer Kit
// A0  --------------------------- S (Yellow)
//                                5mm Green LED
// D2  --------------------------- +
//                                Button (6x6)
// D3  --------------------------- +


// Include the required libraries.
#include "DFRobot_OzoneSensor.h"
#include <Adafruit_BMP085.h>
#include <Adafruit_GFX.h>
#include <Adafruit_SSD1306.h>

// Import the required TensorFlow modules.
#include "TensorFlowLite.h"
#include "tensorflow/lite/micro/kernels/micro_ops.h"
#include "tensorflow/lite/micro/micro_error_reporter.h"
#include "tensorflow/lite/micro/micro_interpreter.h"
#include "tensorflow/lite/micro/all_ops_resolver.h"
#include "tensorflow/lite/version.h"

// Import the converted TensorFlow Lite model.
#include "air_quality_level.h"

// TFLite globals, used for compatibility with Arduino-style sketches:
namespace {
  tflite::ErrorReporter* error_reporter = nullptr;
  const tflite::Model* model = nullptr;
  tflite::MicroInterpreter* interpreter = nullptr;
  TfLiteTensor* model_input = nullptr;
  TfLiteTensor* model_output = nullptr;

  // Create an area of memory to use for input, output, and other TensorFlow arrays.
  constexpr int kTensorArenaSize = 15 * 1024;
  uint8_t tensor_arena[kTensorArenaSize];
} // namespace

// Define the threshold value for the model outputs (results).
float threshold = 0.75;

// Define the air quality level (class) names:
String classes[] = {"Good", "Moderate", "Unhealthy"};

// Define the collect number. The collection range is 1-100: 
#define COLLECT_NUMBER   20 

// To modify the I2C address, configure the hardware IIC address by the dial switch - A0, A1 (ADDRESS_0 for [0 0]), (ADDRESS_1 for [1 0]), (ADDRESS_2 for [0 1]), (ADDRESS_3 for [1 1]).              
/*  
    The default IIC device address is ADDRESS_3: 
       ADDRESS_0               0x70  
       ADDRESS_1               0x71
       ADDRESS_2               0x72
       ADDRESS_3               0x73
*/
#define Ozone_IICAddress ADDRESS_3

// Define the IIC Ozone Sensor.
DFRobot_OzoneSensor Ozone;

// Define the timer for the IIC Ozone Sensor.
unsigned long ozone_timer = 0;
unsigned long timer = 0;

// Define the BMP180 Barometric Pressure/Temperature/Altitude Sensor.
Adafruit_BMP085 bmp;

// Define the anemometer kit's voltage signal pin (yellow).
#define  anemometer_signal A0

// Define the notification LED.
#define notification 2

// Define the model initialization button.
#define run_model 3

// Define the SSD1306 screen settings:
#define SCREEN_WIDTH 128 // OLED display width, in pixels
#define SCREEN_HEIGHT 64 // OLED display height, in pixels
#define OLED_RESET    -1 // Reset pin # (or -1 if sharing Arduino reset pin)

Adafruit_SSD1306 display(SCREEN_WIDTH, SCREEN_HEIGHT, &Wire, OLED_RESET);

// Define monochrome graphics:
static const unsigned char PROGMEM _error [] = {
0x00, 0x00, 0x00, 0x00, 0x00, 0x3F, 0xFC, 0x00, 0x00, 0xE0, 0x07, 0x00, 0x01, 0x80, 0x01, 0x80,
0x06, 0x00, 0x00, 0x60, 0x0C, 0x00, 0x00, 0x30, 0x08, 0x01, 0x80, 0x10, 0x10, 0x03, 0xC0, 0x08,
0x30, 0x02, 0x40, 0x0C, 0x20, 0x02, 0x40, 0x04, 0x60, 0x02, 0x40, 0x06, 0x40, 0x02, 0x40, 0x02,
0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02,
0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x02, 0x40, 0x03, 0xC0, 0x02, 0x40, 0x01, 0x80, 0x02,
0x40, 0x00, 0x00, 0x02, 0x60, 0x00, 0x00, 0x06, 0x20, 0x01, 0x80, 0x04, 0x30, 0x03, 0xC0, 0x0C,
0x10, 0x03, 0xC0, 0x08, 0x08, 0x01, 0x80, 0x10, 0x0C, 0x00, 0x00, 0x30, 0x06, 0x00, 0x00, 0x60,
0x01, 0x80, 0x01, 0x80, 0x00, 0xE0, 0x07, 0x00, 0x00, 0x3F, 0xFC, 0x00, 0x00, 0x00, 0x00, 0x00
};
static const unsigned char PROGMEM _good [] = {
0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x7F, 0x80, 0x00, 0x00, 0x00, 0xFF, 0xC0, 0x00, 0x00,
0x01, 0xFF, 0xC0, 0x00, 0x00, 0x03, 0xFF, 0xE0, 0x00, 0x00, 0x03, 0xFF, 0xFC, 0x00, 0x00, 0x3F,
0xFF, 0xFF, 0x00, 0x00, 0x7F, 0xFF, 0xFF, 0x00, 0x00, 0xFF, 0xFF, 0xFF, 0x80, 0x00, 0xFF, 0xFF,
0xFF, 0x80, 0x01, 0xFF, 0xFF, 0xFF, 0xC0, 0x03, 0xFF, 0xFF, 0xFF, 0xC0, 0x07, 0xFF, 0xFF, 0xFF,
0xC0, 0x0F, 0xFF, 0xFF, 0xFF, 0xC0, 0x0F, 0xFF, 0xFF, 0xFF, 0xE0, 0x0F, 0xFF, 0xFF, 0xFF, 0xF0,
0x0F, 0xFF, 0xFF, 0xFF, 0xF0, 0x0F, 0xFF, 0xFC, 0xFF, 0xF0, 0x07, 0xFF, 0xF8, 0x7F, 0xF0, 0x03,
0xF8, 0x1C, 0x7F, 0xE0, 0x01, 0xF1, 0x1C, 0xFE, 0x00, 0x00, 0x00, 0xF8, 0xBC, 0x00, 0x00, 0x00,
0x79, 0x00, 0x00, 0x00, 0x00, 0x3F, 0x00, 0x00, 0x00, 0x00, 0x3E, 0x00, 0x00, 0x00, 0x00, 0x3C,
0x00, 0x00, 0x00, 0x00, 0x3C, 0x00, 0x00, 0x00, 0x00, 0x3C, 0x00, 0x00, 0x00, 0x00, 0x3C, 0x00,
0x00, 0x00, 0x00, 0x7C, 0x00, 0x00, 0x00, 0x00, 0x7C, 0x00, 0x00, 0x00, 0x00, 0x7E, 0x00, 0x00,
0x00, 0x00, 0x7E, 0x00, 0x00, 0x00, 0x00, 0xFF, 0x00, 0x00, 0x00, 0x03, 0xFF, 0xC0, 0x00, 0x00,
0x1F, 0x7F, 0x70, 0x00, 0x00, 0x40, 0x67, 0x0C, 0x00, 0x00, 0x00, 0xC1, 0x00, 0x00, 0x00, 0x01,
0x00, 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
};
static const unsigned char PROGMEM _moderate [] = {
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0F, 0xC0, 0x00, 0x00, 0x00, 0x30, 0x30, 0x00, 0x00,
0x00, 0x40, 0x18, 0x00, 0x00, 0x00, 0xC0, 0x08, 0x00, 0x00, 0x00, 0x80, 0x04, 0x00, 0x00, 0x00,
0x80, 0x04, 0x00, 0x00, 0x70, 0x00, 0x04, 0x00, 0x03, 0x86, 0x00, 0x04, 0x00, 0x04, 0x01, 0x00,
0x04, 0x00, 0x08, 0x00, 0x80, 0x08, 0x00, 0x10, 0x00, 0x40, 0x08, 0x00, 0x10, 0x00, 0x78, 0x10,
0x00, 0x10, 0x00, 0x46, 0x00, 0x00, 0x20, 0x00, 0x41, 0x80, 0x00, 0x20, 0x00, 0x00, 0x80, 0x00,
0xE0, 0x00, 0x00, 0x40, 0x01, 0x00, 0x60, 0x00, 0x40, 0x02, 0x00, 0x18, 0x00, 0x20, 0x02, 0x00,
0x08, 0x00, 0x20, 0x00, 0x00, 0x08, 0x00, 0x20, 0x00, 0x00, 0x08, 0x00, 0x40, 0x3F, 0xFF, 0xF0,
0x00, 0x40, 0x00, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, 0x01, 0x80, 0x00, 0x00, 0x00, 0x06,
0x00, 0x00, 0x00, 0x7F, 0xF8, 0x00, 0x07, 0xFC, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00,
0x3E, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 
};
static const unsigned char PROGMEM _unhealthy [] = {
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, 0x0E, 0x78, 0x00, 0x00, 0x00, 0x7F, 0x1C,
0x00, 0x00, 0x00, 0xFF, 0xEE, 0x00, 0x00, 0x00, 0x7F, 0xE7, 0x80, 0x00, 0x00, 0x07, 0xF3, 0x80,
0x00, 0x00, 0x00, 0x78, 0x60, 0x00, 0x00, 0x00, 0x3F, 0x74, 0x00, 0x00, 0x00, 0x26, 0x7C, 0x00,
0x00, 0x00, 0x07, 0x04, 0x00, 0x00, 0x00, 0x01, 0x86, 0x00, 0x00, 0x00, 0x01, 0x86, 0x00, 0x00,
0x00, 0x01, 0x86, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0xC7, 0x80, 0x00, 0x00,
0x01, 0xC7, 0x80, 0x00, 0x00, 0x01, 0xC7, 0x80, 0x00, 0x02, 0x03, 0xC7, 0x80, 0x00, 0x02, 0x03,
0xC7, 0x80, 0x00, 0x02, 0x0B, 0xE7, 0x80, 0x00, 0x02, 0x53, 0xE7, 0x80, 0x00, 0x07, 0xFF, 0xEF,
0x80, 0x00, 0x0F, 0xFF, 0xFF, 0xE0, 0x00, 0x0F, 0xFF, 0xFF, 0xE0, 0x00, 0x08, 0x08, 0x3F, 0xE0,
0x00, 0x08, 0x08, 0x3F, 0xE0, 0x00, 0x0F, 0xFF, 0xFF, 0xE0, 0x00, 0x08, 0x08, 0x3F, 0xE0, 0x00,
0x08, 0x08, 0x3F, 0xFF, 0xF0, 0x0F, 0xFF, 0xFF, 0xE0, 0x08, 0x0F, 0xFF, 0xFF, 0xE0, 0x08, 0x1F,
0xFF, 0xFF, 0xE0, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
};

// Define the data holders: 
float _temperature, _altitude, _real_altitude;
int ozoneConcentration, _pressure, _sea_level_pressure, wind_speed;

void setup(){
  Serial.begin(9600);

  pinMode(notification, OUTPUT);
  pinMode(run_model, INPUT_PULLUP);

  // Start the timer:
  ozone_timer = millis();

  // Initialize the SSD1306 screen:
  display.begin(SSD1306_SWITCHCAPVCC, 0x3C);
  display.display();
  delay(1000);
  
  // Check the IIC Ozone Sensor connection status:
  while(!Ozone.begin(Ozone_IICAddress)){
    Serial.println("IIC Ozone Sensor is not found!");
    err_msg();
    delay(1000);
  }
  Serial.println("\nIIC Ozone Sensor is connected successfully!\n");
  
  /*   
     Set IIC Ozone Sensor mode:
       MEASURE_MODE_AUTOMATIC    // active  mode
       MEASURE_MODE_PASSIVE      // passive mode
  */
  Ozone.SetModes(MEASURE_MODE_PASSIVE);

  // Check the BMP180 Barometric Pressure/Temperature/Altitude Sensor connection status: 
  while(!bmp.begin()){
    Serial.println("BMP180 Barometric Pressure/Temperature/Altitude Sensor is not found!");
    err_msg();
    delay(1000);
  }
  Serial.println("\nBMP180 Barometric Pressure/Temperature/Altitude Sensor is connected successfully!\n");

  // TensorFlow Lite Model settings:
  
  // Set up logging (will report to Serial, even within TFLite functions).
  static tflite::MicroErrorReporter micro_error_reporter;
  error_reporter = µ_error_reporter;

  // Map the model into a usable data structure.
  model = tflite::GetModel(air_quality_level);
  if (model->version() != TFLITE_SCHEMA_VERSION) {
    error_reporter->Report("Model version does not match Schema");
    while(1);
  }

  // This pulls in all the operation implementations we need.
  // NOLINTNEXTLINE(runtime-global-variables)
  static tflite::AllOpsResolver resolver;

  // Build an interpreter to run the model.
  static tflite::MicroInterpreter static_interpreter(
    model, resolver, tensor_arena, kTensorArenaSize,
    error_reporter);
  interpreter = &static_interpreter;

  // Allocate memory from the tensor_arena for the model's tensors.
  TfLiteStatus allocate_status = interpreter->AllocateTensors();
  if (allocate_status != kTfLiteOk) {
    error_reporter->Report("AllocateTensors() failed");
    while(1);
  }

  // Assign model input and output buffers (tensors) to pointers.
  model_input = interpreter->input(0);
  model_output = interpreter->output(0);

  delay(1000);
  display.clearDisplay();   
  display.setTextSize(2); 
  display.setTextColor(SSD1306_BLACK, SSD1306_WHITE);
  display.setCursor(0,0);
  display.println("Heating...");
  display.display();
}

void loop(){
  // Wait until the IIC Ozone Sensor heats for 3 minutes.
  while (millis() - ozone_timer < 3*60*1000){ if (millis() - timer > 1000){ timer = millis(); } }

  collect_ozone_concentration();
  delay(1000);
  collect_BMP180_data();
  delay(500);
  collect_anemometer_data();
  delay(250);
  
  // Show the collected weather (air quality) data on the screen.
  show_weather_data();

 // Execute the TensorFlow Lite model to make predictions on the air quality levels (classes). 
 if(digitalRead(run_model) == LOW) run_inference_to_make_predictions();
}

void run_inference_to_make_predictions(){    
    // Scale (normalize) values (local weather data) depending on the model and copy them to the input buffer (tensor):
    model_input->data.f[0] = _temperature / 100;
    model_input->data.f[1] = _altitude / 100;
    model_input->data.f[2] = ozoneConcentration / 1000;
    model_input->data.f[3] = _pressure / 100000;
    model_input->data.f[4] = wind_speed / 30;
    
    // Run inference:
    TfLiteStatus invoke_status = interpreter->Invoke();
    if (invoke_status != kTfLiteOk) {
      error_reporter->Report("Invoke failed on the given input.");
    }

    // Read predicted y values (air quality classes) from the output buffer (tensor): 
    for(int i = 0; i<3; i++){
      if(model_output->data.f[i] >= threshold){
        // Display the detection result (class).
        display.clearDisplay(); 
        if(i == 0) display.drawBitmap(44, 0, _good, 40, 40, SSD1306_WHITE);
        if(i == 1) display.drawBitmap(44, 0, _moderate, 40, 40, SSD1306_WHITE);
        if(i == 2) display.drawBitmap(44, 0, _unhealthy, 40, 40, SSD1306_WHITE);
        // Print:
        int str_x = classes[i].length() * 11;
        display.setTextSize(2); 
        display.setTextColor(SSD1306_WHITE);
        display.setCursor((SCREEN_WIDTH - str_x) / 2, 48);
        display.println(classes[i]);
        display.display();
        digitalWrite(notification, HIGH); delay(1500); digitalWrite(notification, LOW); 
      }
    }
    // Exit and clear.
    delay(3000);

}

void collect_ozone_concentration(){
  ozoneConcentration = Ozone.ReadOzoneData(COLLECT_NUMBER);
  Serial.print("\n\nOzone Concentration => "); Serial.print(ozoneConcentration); Serial.println(" PPB");
}

void collect_BMP180_data(){
  _temperature = bmp.readTemperature();
  _pressure = bmp.readPressure();
  // Calculate altitude assuming 'standard' barometric pressure of 1013.25 millibars (101325 Pascal).
  _altitude = bmp.readAltitude();
  _sea_level_pressure = bmp.readSealevelPressure();
  // To get a more precise altitude measurement, use the current sea level pressure, which will vary with the weather conditions. 
  _real_altitude = bmp.readAltitude(101500);
  // Print the data generated by the BMP180 Barometric Pressure/Temperature/Altitude Sensor.
  Serial.print("Temperature => "); Serial.print(_temperature); Serial.println(" *C");
  Serial.print("Pressure => "); Serial.print(_pressure); Serial.println(" Pa");
  Serial.print("Altitude => "); Serial.print(_altitude); Serial.println(" meters");
  Serial.print("Pressure at sea level (calculated) => "); Serial.print(_sea_level_pressure); Serial.println(" Pa");
  Serial.print("Real Altitude => "); Serial.print(_real_altitude); Serial.println(" meters");
}

void collect_anemometer_data(){
  float outvoltage = (analogRead(A0) * (3.3 / 1023.0)) + 0.1;
  // Calculate the wind speed (level) [1 - 30] according to the output voltage: 
  wind_speed = 6 * outvoltage;
  // Print the data generated by the Anemometer Kit.
  Serial.print("Wind Speed (Level) => "); Serial.print(wind_speed);
}

void show_weather_data(){
  display.clearDisplay();   
  display.setTextSize(1); 
  display.setTextColor(SSD1306_WHITE);
  display.setCursor(0,8); 
  display.println("Ozone Con. => " + String(ozoneConcentration) + " PPB");
  display.println("Wind Speed => " + String(wind_speed));
  display.println("Temp. => " + String(_temperature) + " *C");
  display.println("Pressure => " + String(_pressure) + " Pa");
  display.println("Altitude => " + String(_altitude) + " m");
  display.display();  
}

void err_msg(){
  // Show the error message on the SSD1306 screen.
  display.clearDisplay();   
  display.drawBitmap(48, 0, _error, 32, 32, SSD1306_WHITE);
  display.setTextSize(1); 
  display.setTextColor(SSD1306_WHITE);
  display.setCursor(0,40); 
  display.println("Check the serial monitor to see the error!");
  display.display();  
}

#ifndef AIR_QUALITY_LEVEL_H
#define AIR_QUALITY_LEVEL_H


unsigned int air_quality_level_len = 38648;
unsigned char air_quality_level[] = {
 0x1c, 0x00, 0x00, 0x00, 0x54, 0x46, 0x4c, 0x33, 0x14, 0x00, 0x20, 0x00,
  0x04, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x10, 0x00, 0x14, 0x00, 0x00, 0x00,
  0x18, 0x00, 0x1c, 0x00, 0x14, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
  0x18, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0xb0, 0x00, 0x00, 0x00,
  0x20, 0x00, 0x00, 0x00, 0x58, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00,
  0x02, 0x00, 0x00, 0x00, 0x8c, 0x03, 0x00, 0x00, 0x70, 0x01, 0x00, 0x00,
  0x01, 0x00, 0x00, 0x00, 0xb4, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00,
  0xa0, 0x96, 0x00, 0x00, 0x9c, 0x96, 0x00, 0x00, 0xcc, 0x93, 0x00, 0x00,
  0x58, 0x92, 0x00, 0x00, 0xe4, 0x91, 0x00, 0x00, 0x94, 0x87, 0x00, 0x00,
  0x40, 0x07, 0x00, 0x00, 0xec, 0x03, 0x00, 0x00, 0x80, 0x96, 0x00, 0x00,
  0x7c, 0x96, 0x00, 0x00, 0x78, 0x96, 0x00, 0x00, 0x74, 0x96, 0x00, 0x00,
  0x3c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x0c, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x04, 0x00, 0x08, 0x00,
  0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00,
  0x13, 0x00, 0x00, 0x00, 0x6d, 0x69, 0x6e, 0x5f, 0x72, 0x75, 0x6e, 0x74,
  0x69, 0x6d, 0x65, 0x5f, 0x76, 0x65, 0x72, 0x73, 0x69, 0x6f, 0x6e, 0x00,
  0x9e, 0x6c, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
  0x31, 0x2e, 0x35, 0x2e, 0x30, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
  0x00, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x4d, 0x4c, 0x49, 0x52,
  0x20, 0x43, 0x6f, 0x6e, 0x76, 0x65, 0x72, 0x74, 0x65, 0x64, 0x2e, 0x00,
  0x00, 0x00, 0x0e, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0c, 0x00,
  0x10, 0x00, 0x14, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00,
  0x40, 0x00, 0x00, 0x00, 0x44, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00,
  0x58, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x94, 0x95, 0x00, 0x00,
  0x24, 0x95, 0x00, 0x00, 0xa0, 0x92, 0x00, 0x00, 0x38, 0x91, 0x00, 0x00,
  0xdc, 0x90, 0x00, 0x00, 0x88, 0x86, 0x00, 0x00, 0x34, 0x06, 0x00, 0x00,
  0xa4, 0x02, 0x00, 0x00, 0xb0, 0x01, 0x00, 0x00, 0xf8, 0x00, 0x00, 0x00,
  0x80, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
  0x01, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
  0x28, 0x02, 0x00, 0x00, 0x58, 0x01, 0x00, 0x00, 0xa4, 0x00, 0x00, 0x00,
  0x1c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e,
  0x00, 0x00, 0x0e, 0x00, 0x18, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x10, 0x00,
  0x07, 0x00, 0x14, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
  0x01, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
  0x04, 0x00, 0x00, 0x00, 0x7a, 0x6d, 0xff, 0xff, 0x00, 0x00, 0x80, 0x3f,
  0x01, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x09, 0x00, 0x00, 0x00, 0xf4, 0xfd, 0xff, 0xff, 0x19, 0x00, 0x00, 0x00,
  0x00, 0x00, 0x00, 0x19, 0x01, 0x00, 0x00, 0x00, 0x28, 0x6b, 0xff, 0xff,
  0x14, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
  0x30, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
  0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
  0xff, 0xff, 0xff, 0xff, 0x03, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
  0x49, 0x64, 0x65, 0x6e, 0x74, 0x69, 0x74, 0x79, 0x00, 0x00, 0x00, 0x00,
  0x14, 0x6b, 0xff, 0xff, 0x5e, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x08,
  0x18, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
  0x2c, 0x6b, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00,
  0x03, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00,
  0x03, 0x00, 0x00, 0x00, 0x9c, 0x6b, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00,
  0x0a, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x5c, 0x00, 0x00, 0x00,
  0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff,
  0x03, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x73, 0x65, 0x71, 0x75,
  0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e, 0x73, 0x65,
  0x5f, 0x32, 0x2f, 0x4d, 0x61, 0x74, 0x4d, 0x75, 0x6c, 0x3b, 0x73, 0x65,
  0x71, 0x75, 0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e,
  0x73, 0x65, 0x5f, 0x32, 0x2f, 0x42, 0x69, 0x61, 0x73, 0x41, 0x64, 0x64,
  0x00, 0x00, 0x00, 0x00, 0x8c, 0x6e, 0xff, 0xff, 0x00, 0x00, 0x0e, 0x00,
  0x14, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x10, 0x00,
  0x0e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x1c, 0x00, 0x00, 0x00,
  0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x32, 0xff, 0xff, 0xff,
  0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
  0x03, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00,
  0x02, 0x00, 0x00, 0x00, 0x50, 0x6c, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00,
  0x09, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00,
  0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x40, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff,
  0x40, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00, 0x73, 0x65, 0x71, 0x75,
  0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e, 0x73, 0x65,
  0x5f, 0x31, 0x2f, 0x4d, 0x61, 0x74, 0x4d, 0x75, 0x6c, 0x3b, 0x73, 0x65,
  0x71, 0x75, 0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e,
  0x73, 0x65, 0x5f, 0x31, 0x2f, 0x52, 0x65, 0x6c, 0x75, 0x3b, 0x73, 0x65,
  0x71, 0x75, 0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e,
  0x73, 0x65, 0x5f, 0x31, 0x2f, 0x42, 0x69, 0x61, 0x73, 0x41, 0x64, 0x64,
  0x00, 0x00, 0x00, 0x00, 0x58, 0x6f, 0xff, 0xff, 0x00, 0x00, 0x0e, 0x00,
  0x16, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x10, 0x00,
  0x0e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x24, 0x00, 0x00, 0x00,
  0x18, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00,
  0x08, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01,
  0x01, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
  0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x0c, 0x00, 0x10, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x04, 0x00,
  0x0c, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
  0x01, 0x00, 0x00, 0x00, 0x40, 0x6d, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00,
  0x08, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00,
  0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
  0x80, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff,
  0x80, 0x00, 0x00, 0x00, 0x46, 0x00, 0x00, 0x00, 0x73, 0x65, 0x71, 0x75,
  0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e, 0x73, 0x65,
  0x2f, 0x4d, 0x61, 0x74, 0x4d, 0x75, 0x6c, 0x3b, 0x73, 0x65, 0x71, 0x75,
  0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e, 0x73, 0x65,
  0x2f, 0x52, 0x65, 0x6c, 0x75, 0x3b, 0x73, 0x65, 0x71, 0x75, 0x65, 0x6e,
  0x74, 0x69, 0x61, 0x6c, 0x2f, 0x64, 0x65, 0x6e, 0x73, 0x65, 0x2f, 0x42,
  0x69, 0x61, 0x73, 0x41, 0x64, 0x64, 0x00, 0x00, 0x68, 0x6d, 0xff, 0xff,
  0x3a, 0x70, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00,
  0x2c, 0x54, 0x7f, 0x3f, 0xdb, 0x62, 0x6c, 0x3f, 0x60, 0x8c, 0x71, 0x3f,
  0xb0, 0x2e, 0xdf, 0x3d, 0x8c, 0xb8, 0x9a, 0x3d, 0x4e, 0xe8, 0x12, 0xbf,
  0xf4, 0x95, 0x91, 0xbe, 0xce, 0x4b, 0x28, 0xbf, 0x44, 0x1b, 0x93, 0xbe,
  0x5b, 0xdd, 0x4f, 0x3f, 0x84, 0xdc, 0xb4, 0xbf, 0x50, 0x0b, 0x9f, 0x3d,
  0x70, 0x15, 0x94, 0x3e, 0x12, 0x9b, 0x31, 0x3e, 0xad, 0xcb, 0x7e, 0xbf,
  0xd0, 0xd4, 0x35, 0x3f, 0xb0, 0xa0, 0x82, 0xbe, 0x24, 0xc7, 0xdd, 0xbd,
  0x64, 0xc9, 0xde, 0xbe, 0xd1, 0x8e, 0x2b, 0xbe, 0xa0, 0xd1, 0x4e, 0xbc,
  0x79, 0x75, 0x47, 0x3e, 0xe8, 0x26, 0x06, 0xbe, 0xfe, 0x78, 0x4a, 0x3c,
  0x9f, 0x6c, 0x74, 0xbe, 0x8a, 0x44, 0x53, 0xbe, 0xae, 0x8b, 0x8e, 0xbf,
  0xea, 0x6e, 0x8b, 0xbd, 0x0f, 0xc9, 0x84, 0x3f, 0x08, 0x65, 0x50, 0x3e,
  0x6f, 0x55, 0x96, 0xbe, 0x28, 0x15, 0x01, 0xbd, 0x7f, 0x17, 0x4b, 0xbf,
  0xf9, 0x63, 0x5b, 0xbe, 0xa0, 0x3d, 0xdd, 0x3d, 0x39, 0x3e, 0xd2, 0x3e,
  0x7e, 0x2e, 0x83, 0x3f, 0xa9, 0x09, 0x25, 0xbf, 0x70, 0x40, 0x51, 0x3d,
  0x77, 0x25, 0x14, 0xbe, 0xc5, 0xf0, 0xbc, 0xbf, 0x9a, 0x3d, 0xb0, 0xbd,
  0x22, 0x15, 0x42, 0xbe, 0xf0, 0xc5, 0x9f, 0xbe, 0x07, 0xad, 0x19, 0xbe,
  0x54, 0x4f, 0x87, 0x3f, 0x87, 0x32, 0x81, 0x3f, 0x4a, 0x1f, 0x31, 0xbe,
  0xf6, 0x0d, 0x0a, 0x3e, 0xa9, 0x51, 0xf5, 0xbe, 0xc9, 0x7f, 0xcc, 0xbd,
  0x7a, 0x4d, 0x70, 0x3e, 0x40, 0xb2, 0x17, 0xbd, 0xac, 0xe6, 0x6d, 0x3e,
  0x36, 0x80, 0x15, 0x3e, 0xd0, 0xdb, 0x11, 0xbe, 0xc8, 0xf9, 0x91, 0x3e,
  0x00, 0x01, 0x6d, 0x3e, 0x65, 0x83, 0xa7, 0xbf, 0x07, 0xff, 0x7d, 0x3e,
  0xf5, 0x7c, 0x9f, 0xbf, 0x39, 0x78, 0x84, 0xbc, 0x0a, 0x39, 0xb3, 0xbd,
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};

#endif //AIR_QUALITY_LEVEL_H