MULTI-MODAL KEYLESS MULTI-SEAT IN-CAR PERSONALIZATION
In-car personalization methods/systems for applying personalized settings to car functionality and for allowing multiple passengers in a car to apply personalized settings to their individual location in the care and according to stored preferences. The methods/systems provide multi-user profile selections using one or more of: (1) key-less multi-user profile selection; (2) biometric multi-user profile selection; and/or a combination of multi-modal technologies for {key-less, biometric} multi-user profile selection. The disclosed methods/systems combine multiple available sensors to solve the complementary tasks of: (1) detecting the presence of a person, (2) performing a coarse classification of the occupants (e.g., driver vs passenger; child vs adolescent/adult), (3) seat-based localization of detected occupants, and (4) identification of a specific user.
1 . A method comprising, using available sensors in a vehicle, performing the steps of detecting the presence of an occupant in the vehicle, classifying the occupant, localizing the seat-based location of the occupant, and identifying the occupant.
2 . The method of claim 1 , wherein identifying the occupant comprises identifying the occupant in reliance on at least one biometric characteristic.
3 . The method of claim 1 , further comprising applying personalized settings based on having identified the occupant, the personalized settings being retrieved from the cloud.
4 . The method of claim 1 , wherein identifying the occupant comprises matching a profile of the occupant against an off-board database.
5 . The method of claim 1 , wherein classifying the occupant comprises determining whether the occupant is a driver or a passenger.
6 . The method of claim 1 , wherein classifying the occupant comprises determining whether the occupant is an adult or other than an adult.
7 . The method of claim 1 , wherein the available sensors include a microphone set that comprises one or more microphones and localizing the seat-based location of the occupant comprises using the microphone set to detect the occupant's speech and to identify a location from which the occupant's speech originated.
8 . The method of claim 1 , wherein the available sensors include a microphone set that comprises one or more microphones and wherein identifying the occupant comprises using the microphone set to obtain a signal representative of the occupant's speech, the method further including retrieving voice biometric data and identifying the occupant based at least in part on the voice biometric data.
9 . The method of claim 1 , wherein the available sensors include a camera set that comprises one or more cameras and identifying the occupant comprises using the camera set to acquire an image of the occupant, the method further comprising retrieving facial-recognition data and identifying the occupant based at least in part on the facial-recognition data.
10 . The method of claim 1 , wherein the available sensors include a camera set that comprises one or more cameras and localizing the seat-based location of the occupant comprises using the camera set to acquire images of seats, the method further comprising using the images to determine which seat is occupied by the occupant.
11 . The method of claim 1 , wherein the available sensors comprise a radio sensor configured to detect a communication signal from a handheld personal device, the method further comprising detecting a personal device, wherein identifying the occupant comprises identifying the occupant based at least in part on the communication signal.
12 . The method of claim 1 , wherein the available sensors comprise a seat-occupancy detector and wherein classifying the occupant comprises classifying the occupant based at least in part on data provided the seat-occupancy detector.
13 . The method of claim 1 , wherein the available sensors comprise a seat-occupancy detector and wherein localizing the seat-based location of the occupant comprises localizing the seat-based location based at least in part on data provided by the seat-occupancy detector.
14 . The method of claim 1 , wherein identifying the occupant comprises identifying a specific occupant.
15 . The method of claim 1 , wherein identifying the occupant occurs before localizing the seat-based location of the occupant.
16 . The method of claim 1 , wherein classifying the occupant comprises classifying the occupant after having localized the seat-based location of the occupant.
17 . The method of claim 1 , wherein detecting the presence of the occupant and localizing the seat-based location of the occupant occur concurrently.
18 . The method of claim 1 , wherein classifying comprises classifying the occupant into one of a plurality of roles, each of said roles having a corresponding attribute selected from the group consisting of settings, preferences, and permissions.
19 . The method of claim 1 , further comprising applying preferences, settings, or parameters associated with the occupant.
20 . The method of claim 1 , further comprising applying preferences, settings, or parameters associated with the class into which the occupant has been classified.