초록 ▼

System for determining the occupancy of a seat in a vehicle using pattern recognition technologies and techniques that apply to any combination of transducers that provide information about seat occupancy, for example, weight sensors, capacitive sensors, inductive sensors, ultrasonic, optical, elect

System for determining the occupancy of a seat in a vehicle using pattern recognition technologies and techniques that apply to any combination of transducers that provide information about seat occupancy, for example, weight sensors, capacitive sensors, inductive sensors, ultrasonic, optical, electromagnetic, motion, infrared and radar sensors. A processor is coupled to the transducers for receiving data therefrom and processes the data to obtain an output indicative of the seat's current occupancy state. A combination neural network is resident in the processor and is created from data sets, each representing a different occupancy state of the seat and being formed from data from the transducers while the seat is in that occupancy state. The combination neural network produces the output indicative of the current occupancy state of the seat upon inputting a data set representing the current occupancy state of the seat and being formed from data from the transducers.

대표청구항 ▼

1. A vehicle including a system for determining the occupancy state of a seat in the vehicle occupied by an occupying item, the system comprising:a plurality of transducers arranged in the vehicle, each of said transducers providing data relating to the occupancy state of the seat; and processor mea

1. A vehicle including a system for determining the occupancy state of a seat in the vehicle occupied by an occupying item, the system comprising:a plurality of transducers arranged in the vehicle, each of said transducers providing data relating to the occupancy state of the seat; and processor means coupled to said transducers for receiving the data from said transducers and processing the data to obtain an output indicative of the current occupancy state of the seat, said processor means comprising a trained combination neural network created from a plurality of data sets, each of said data sets representing a different occupancy state of the seat and being formed from data from said transducers while the seat is in that occupancy state, said combination neural network producing the output indicative of the current occupancy state of the seat upon inputting a data set representing the current occupancy state of the seat and being formed from data from at least some of said transducers.