This function takes numeric values or numeric strings and returns their median. Booleans, missing entries, invalid strings and non-finite numbers are ignored. An empty usable set returns None.

from statistics import median
import math

def median_reading(values):
    readings = []
    for value in values:
        if isinstance(value, bool):
            continue
        try:
            number = float(value)
        except (TypeError, ValueError, OverflowError):
            continue
        if math.isfinite(number):
            readings.append(number)
    return median(readings) if readings else None

assert median_reading([10, "12", None, "bad", 1000]) == 12
assert median_reading([2, 4]) == 3
assert median_reading([True, float("nan"), float("inf")]) is None
assert median_reading([]) is None
assert median_reading([0, -2, "2"]) == 0

All five assertions passed locally. A median resists isolated outliers; it does not detect whether an entire sensor is miscalibrated.