US 12,248,317 B2
Neural net-based use of perceptrons to mimic human senses associated with a vehicle occupant
Charles Howard Cella, Pembroke, MA (US)
Assigned to Strong Force TP Portfolio 2022, LLC, Fort Lauderdale, FL (US)
Filed by STRONG FORCE TP PORTFOLIO 2022, LLC, Fort Lauderdale, FL (US)
Filed on Dec. 22, 2023, as Appl. No. 18/395,073.
Application 18/395,073 is a continuation of application No. 17/977,550, filed on Oct. 31, 2022.
Application 17/977,550 is a continuation of application No. 16/887,557, filed on May 29, 2020.
Application 16/887,557 is a continuation of application No. 16/803,220, filed on Feb. 27, 2020.
Application 16/803,220 is a continuation of application No. PCT/US2019/053857, filed on Sep. 30, 2019.
Claims priority of provisional application 62/739,335, filed on Sep. 30, 2018.
Prior Publication US 2024/0142970 A1, May 2, 2024
Int. Cl. G06V 20/59 (2022.01); B60W 40/08 (2012.01); G01C 21/34 (2006.01); G01C 21/36 (2006.01); G05B 13/02 (2006.01); G05D 1/00 (2006.01); G05D 1/224 (2024.01); G05D 1/225 (2024.01); G05D 1/226 (2024.01); G05D 1/227 (2024.01); G05D 1/228 (2024.01); G05D 1/229 (2024.01); G05D 1/24 (2024.01); G05D 1/646 (2024.01); G05D 1/69 (2024.01); G05D 1/692 (2024.01); G05D 1/81 (2024.01); G06F 40/40 (2020.01); G06N 3/04 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06N 3/086 (2023.01); G06N 20/00 (2019.01); G06Q 30/0208 (2023.01); G06Q 50/18 (2012.01); G06Q 50/40 (2024.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/64 (2022.01); G07C 5/00 (2006.01); G07C 5/02 (2006.01); G07C 5/08 (2006.01); G10L 15/16 (2006.01); G10L 25/63 (2013.01); G06N 3/02 (2006.01); G06Q 30/02 (2023.01); G06Q 50/00 (2012.01)
CPC G05D 1/0022 (2013.01) [B60W 40/08 (2013.01); G01C 21/3438 (2013.01); G01C 21/3461 (2013.01); G01C 21/3469 (2013.01); G01C 21/3617 (2013.01); G05B 13/027 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G05D 1/0287 (2013.01); G05D 1/224 (2024.01); G05D 1/225 (2024.01); G05D 1/226 (2024.01); G05D 1/227 (2024.01); G05D 1/228 (2024.01); G05D 1/229 (2024.01); G05D 1/24 (2024.01); G05D 1/646 (2024.01); G05D 1/69 (2024.01); G05D 1/692 (2024.01); G05D 1/81 (2024.01); G06F 40/40 (2020.01); G06N 3/0418 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06N 3/086 (2013.01); G06N 20/00 (2019.01); G06Q 30/0208 (2013.01); G06Q 50/188 (2013.01); G06Q 50/40 (2024.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/59 (2022.01); G06V 20/597 (2022.01); G06V 20/64 (2022.01); G07C 5/006 (2013.01); G07C 5/008 (2013.01); G07C 5/02 (2013.01); G07C 5/08 (2013.01); G07C 5/0808 (2013.01); G07C 5/0816 (2013.01); G07C 5/0866 (2013.01); G07C 5/0891 (2013.01); G10L 15/16 (2013.01); G10L 25/63 (2013.01); B60W 2040/0881 (2013.01); G06N 3/02 (2013.01); G06Q 30/0281 (2013.01); G06Q 50/01 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A system for operating a vehicle based on an emotional state of a rider, the system comprising:
an artificial intelligence system for processing a sensory input from a wearable device in the vehicle to determine a state of the rider in the vehicle and optimizing an operating parameter of the vehicle to improve the state of the rider, wherein the artificial intelligence system is configured to execute a genetic algorithm to generate mutations from an initial operating state of the vehicle to determine at least one optimized vehicle operating state, wherein the at least one optimized vehicle operating state is optimized to improve the state of the rider,
the artificial intelligence system including a neural net with one or more perceptrons to mimic human senses to facilitate determining the state of the rider based on an extent to which at least one of the senses of the rider is stimulated, wherein the artificial intelligence system is to indicate a change in the state of the rider through recognition of patterns of emotional state indicative wearable sensor data of the rider in the vehicle;
a vehicle control system to control an operation of the vehicle by adjusting a plurality of vehicle operating parameters; and
a feedback loop through which the indication of the change in the state of the rider is communicated between the vehicle control system and the artificial intelligence system, wherein the vehicle control system adjusts at least one of the plurality of vehicle operating parameters responsive to the indication of the change to achieve the at least one optimized vehicle operating state.