| 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)] | 15 Claims |

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1. A system for transportation, comprising:
a vehicle interface to interface with a vehicle occupied by a rider; and
a hybrid neural network, including:
a first neural network to process a sensor input corresponding to the rider to determine an emotional state of the rider;
a second neural network to classify social media data sourced from a plurality of social media sources and as being indicative of an effect on the system for transportation, wherein the social media data indicates at least one of an interest of the rider or a transportation objective of the rider, and
a third neural network to analyze the classified social media data and optimize at least one operating parameter of the vehicle to improve the emotional state of the rider, wherein the analysis of the classified social media data by the third neural network includes determining a value for the at least one operating parameter that is likely to improve the emotional state of the rider based on at least one of a model or a rule, wherein the at least one of the model or the rule includes a weighting for the at least one operating parameter, and wherein the optimization of the at least one operating parameter includes using the vehicle interface for at least one of:
adjustment of a routing plan of the vehicle to include passing a point of interest to the rider, or
selecting entertainment content from entertainment options including at least one of: movies, games, or advertising content,
wherein the third neural network is configured to optimize the at least one operating parameter of the vehicle in part by varying the at least one operating parameter to vary a cortisol level of the rider based on a time of day.
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