Below is a simplified Python implementation to simulate the occupant detection and classification system.

python

Copy code

import time

# Define the criteria for detecting an occupant’s size

def is_alive(size):

    # Assume the occupant is alive if their size is greater than 30cm and less than 80cm

    if 30 <= size <= 80:

        return True

    return False

# Function to detect and classify an occupant

def detect_occupant(size, seat):

    start_time = time.time()

    detected = False

    # Initial detection and classification (within 20 seconds)

    while time.time() – start_time < 20:

        if is_alive(size):

            detected = True

            print(f”Occupant detected in {seat}. Classification: Alive human.”)

            break

        else:

            print(“No occupant detected.”)

            time.sleep(1)

    # If the occupant is detected, return True and seat information

    if detected:

        print(f”Occupant in {seat} is classified successfully.”)

        return True

    else:

        print(f”Failed to detect occupant in {seat}.”)

        return False

# Function to determine the location of the occupant (driver or passenger)

def determine_location(seat):

    if seat == “Driver”:

        print(“Location Determination: Driver’s Seat”)

    elif seat == “Passenger”:

        print(“Location Determination: Passenger’s Seat”)

    else:

        print(“Unknown Seat”)

# Simulate the scenario with two occupants

def main():

    # Assume size of the occupants (in cm)

    driver_size = 70  # Average size of the driver

    passenger_size = 50  # Average size of a passenger

    # Detect and classify the driver

    print(“Detecting Driver…”)

    if detect_occupant(driver_size, “Driver”):

        determine_location(“Driver”)

    # Detect and classify the passenger

    print(“\nDetecting Passenger…”)

    if detect_occupant(passenger_size, “Passenger”):

        determine_location(“Passenger”)

# Run the simulation

main()