
    Given sensor data from vehicle components where each pair contains two related measurements, find the component pair with the lowest combined risk factor (calculated as the product of its measurements) to identify the least critical maintenance concern. The sensor pairs could represent various component health indicators like (tire pressure, wear level), (engine temperature, oil level), or (brake pad thickness, usage count), and finding the minimum product will help prioritize maintenance tasks by identifying the least urgent issue.
    

    
def min_product_tuple(list1):
    """
    Given sensor data from vehicle components where each pair contains two related measurements, find the component pair with the lowest combined risk factor (calculated as the product of its measurements) to identify the least critical maintenance concern. The sensor pairs could represent various component health indicators like (tire pressure, wear level), (engine temperature, oil level), or (brake pad thickness, usage count), and finding the minimum product will help prioritize maintenance tasks by identifying the least urgent issue.
    

    """
def min_product_tuple(list1):
    """
    Given sensor data from vehicle components where each pair contains two related measurements, find the component pair with the lowest combined risk factor (calculated as the product of its measurements) to identify the least critical maintenance concern. The sensor pairs could represent various component health indicators like (tire pressure, wear level), (engine temperature, oil level), or (brake pad thickness, usage count), and finding the minimum product will help prioritize maintenance tasks by identifying the least urgent issue.
    

    """
    result_min = min([abs(x * y) for (x, y) in list1])
    return result_min