Route_OptimizationUsingAPI.py

import requests
import json

# Function to get real-time traffic data from TomTom API
def get_real_time_traffic_data(start_point, end_point):
    API_KEY = 'YOUR_TOMTOM_API_KEY'  # Replace with your TomTom API Key
    url = f"https://api.tomtom.com/traffic/services/4/flowSegmentData/relative0/10/json?key={API_KEY}&point={start_point['lat']},{start_point['lon']}"
    response = requests.get(url)
    if response.status_code == 200:
        traffic_data = response.json()
        return traffic_data
    else:
        print(f"Error fetching traffic data: {response.status_code}")
        return None

# Function to get route data from Google Maps Directions API
def get_route_data(start_point, end_point):
    API_KEY = 'YOUR_GOOGLE_MAPS_API_KEY'  # Replace with your Google Maps API Key
    url = f"https://maps.googleapis.com/maps/api/directions/json?origin={start_point}&destination={end_point}&key={API_KEY}"
    response = requests.get(url)
    if response.status_code == 200:
        route_data = response.json()
        return route_data
    else:
        print(f"Error fetching route data: {response.status_code}")
        return None

# Function to get air quality and weather data from AQICN API
def get_weather_data(city):
    API_KEY = 'YOUR_AQICN_API_KEY'  # Replace with your AQICN API Key
    url = f"https://api.waqi.info/feed/{city}/?token={API_KEY}"
    response = requests.get(url)
    if response.status_code == 200:
        weather_data = response.json()
        return weather_data
    else:
        print(f"Error fetching weather data: {response.status_code}")
        return None

# Function to calculate vehicle emissions based on distance and vehicle efficiency
def calculate_emissions(distance, fuel_efficiency, emission_factor):
    emissions = (distance / fuel_efficiency) * emission_factor
    return emissions

# Main function for user input and routing optimization
def main():
    # Get user input for vehicle details and route
    start_point = {
        "lat": float(input("Enter start point latitude: ")),
        "lon": float(input("Enter start point longitude: "))
    }
    end_point = {
        "lat": float(input("Enter end point latitude: ")),
        "lon": float(input("Enter end point longitude: "))
    }
    city = input("Enter your city for weather and air quality data: ")
    vehicle_type = input("Enter vehicle type (gas/electric): ")
    fuel_efficiency = float(input("Enter fuel efficiency (km per litre): "))
    emission_factor = 2.31  # gCO2 per litre (standard for gasoline vehicles)

    # Fetch real-time traffic data
    traffic_data = get_real_time_traffic_data(start_point, end_point)
    if traffic_data:
        print("Traffic data fetched successfully.")

    # Fetch route data
    route_data = get_route_data(f"{start_point['lat']},{start_point['lon']}", f"{end_point['lat']},{end_point['lon']}")
    if route_data:
        print("Route data fetched successfully.")
        routes = route_data.get('routes', [])
        if routes:
            route = routes[0]
            distance = route['legs'][0]['distance']['value'] / 1000  # Convert meters to kilometers
            print(f"Route distance: {distance} km")
        else:
            print("No routes found.")
            return

    # Fetch weather and air quality data
    weather_data = get_weather_data(city)
    if weather_data:
        print(f"Weather data: {weather_data['data']['aqi']} AQI")

    # Calculate emissions for the route
    emissions = calculate_emissions(distance, fuel_efficiency, emission_factor)
    print(f"Estimated CO2 emissions for the route: {emissions} grams")

if __name__ == "__main__":
    main()