A key state detector for a vehicle collects a sequence of battery voltage samples and applies a time-domain to frequency-domain transform (TFT) to the collected samples. The results of the TFT are then applied to an artificial neural network (ANN) to determine if they represent a key-on or key-off state. The ANN is trained based on data collected from the vehicle and is periodically retrained so that the detection of key-on and key-off states conforms to the particular vehicle and tracks the aging of vehicle components.