
    Develop an algorithm to analyze public transit vehicle sensor data sequences where each reading is either 0 (normal) or 1 (abnormal), and determine how many possible sequences of 2n readings would indicate balanced vehicle wear by having the same number of abnormal readings in the first n measurements as in the last n measurements of the day.
    

    
def count_binary_seq(n):
    """
    Develop an algorithm to analyze public transit vehicle sensor data sequences where each reading is either 0 (normal) or 1 (abnormal), and determine how many possible sequences of 2n readings would indicate balanced vehicle wear by having the same number of abnormal readings in the first n measurements as in the last n measurements of the day.
    

    """
def count_binary_seq(n):
    """
    Develop an algorithm to analyze public transit vehicle sensor data sequences where each reading is either 0 (normal) or 1 (abnormal), and determine how many possible sequences of 2n readings would indicate balanced vehicle wear by having the same number of abnormal readings in the first n measurements as in the last n measurements of the day.
    

    """
    nCr = 1
    res = 1
    for r in range(1, n + 1):
        nCr = nCr * (n + 1 - r) / r
        res += nCr * nCr
    return res