Abstract: A method for the determination of a physical property parameter of a seat passenger includes getting a reading of at least two parameters from an occupancy sensor; plotting a probability vector which shows, for each value of the physical property, the probability to cause the readings of the at least two parameters; and correlating the physical property parameter to the range of values of the probability vector with the highest probabilities.

Abstract: A method for classifying an occupancy status of a vehicle seat includes associating a filtered class to a specific seat occupancy status based on a plurality of successive readings of at least one parameter value of a seat occupancy sensor, including the steps of: 1) determining an actual value of a first parameter of the seat sensor and associating an actual class to the actual value of the first parameter; 2) storing the actual class in a buffer, and deleting the oldest stored class; 3) plotting a confidence parameter indicative of the reliability of the actual class; 4) setting an updated filtered class to equal (i) an average of the classes stored in the buffer, if the confidence parameter is smaller than a first confidence threshold value, or (ii) the previously determined filter class, if the confidence parameter is greater than or equal to the first confidence threshold value.

Abstract: A method for the classification of an occupancy status of a vehicle seat, where occupancy profiles from an occupancy sensor are recorded and evaluated and the classification of the actual occupancy status is determined. The method includes, when the system power is turned off, storing the last determined class and the last recorded profile into a non-volatile memory; when the system power is turned on, comparing the first recorded profile with the profile stored into the non-volatile memory; and if the likeness of the first recorded profile and the profile stored in the non-volatile memory exceeds a specific threshold, setting the actual class to equal the class stored into the non-volatile memory.

Abstract: A method for the classification of an occupancy status of a vehicle seat, where occupancy profiles from an occupancy sensor are recorded and evaluated and the classification of the actual occupancy status is determined. The method includes, when the system power is turned off, storing the last determined class and the last recorded profile into a non-volatile memory; when the system power is turned on, comparing the first recorded profile with the profile stored into the non-volatile memory; and if the likeness of the first recorded profile and the profile stored in the non-volatile memory exceeds a specific threshold, setting the actual class to equal the class stored into the non-volatile memory.

Abstract: A method for the determination of a physical property parameter of a seat passenger includes getting a reading of at least two parameters from an occupancy sensor; plotting a probability vector which shows, for each value of the physical property, the probability to cause the readings of the at least two parameters; and correlating the physical property parameter to the range of values of the probability vector with the highest probabilities.

Abstract: A method for classifying an occupancy status of a vehicle seat includes associating a filtered class to a specific seat occupancy status based on a plurality of successive readings of at least one parameter value of a seat occupancy sensor, including the steps of: 1) determining an actual value of a first parameter of the seat sensor and associating an actual class to the actual value of the first parameter; 2) storing the actual class in a buffer, and deleting the oldest stored class; 3) plotting a confidence parameter indicative of the reliability of the actual class; 4) setting an updated filtered class to equal (i) an average of the classes stored in the buffer, if the confidence parameter is smaller than a first confidence threshold value, or (ii) the previously determined filter class, if the confidence parameter is greater than or equal to the first confidence threshold value.