IP Library Patent Application 16887530
Patent Application
App. No. 16/887,530

HYBRID NEURAL NETWORK SYSTEM FOR TRANSPORTATION SYSTEM OPTIMIZATION

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Quick Facts
Patent No.
US None
App. No.
16/887,530
Abstract

A hybrid neural network system for transportation system optimization includes a hybrid neural network. The hybrid neural network includes a first neural network that predicts a localized effect on a transportation system through analysis of social medial data sourced from a plurality of social media data sources. The hybrid neural network further includes a second neural network that optimizes an operating state of the transportation system based on the predicted localized effect.

Claims (40)

1 . A hybrid neural network system for transportation system optimization, the hybrid neural network system comprising a hybrid neural network, including:

a first neural network that predicts a localized effect on a transportation system through analysis of social medial data sourced from a plurality of social media data sources; and

a second neural network that optimizes an operating state of the transportation system based on the predicted localized effect.

2 . The hybrid neural network system of claim 1 wherein at least one of the first neural network and the second neural network is a convolutional neural network.

3 . The hybrid neural network system of claim 1 wherein the second neural network is to optimize an in-vehicle rider experience state.

4 . The hybrid neural network system of claim 1 wherein the first neural network identifies a set of vehicles contributing to the localized effect based on correlation of vehicle location and an area of the localized effect.

5 . The hybrid neural network system of claim 1 wherein the second neural network is to optimize a routing state of the transportation system for vehicles proximal to a location of the localized effect.

6 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of the predicting and optimizing based on keywords in the social media data indicative of an outcome of a transportation system optimization action.

7 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on social media posts or social media feeds.

8 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on ratings derived from the social media data.

9 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on like or dislike activity detected in the social media data.

10 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on indications of relationships in the social media data.

11 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on user behavior detected in the social media data.

12 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on discussion threads or chats in the social media data.

13 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on photographs in the social media data.

14 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on traffic-affecting information in the social media data.

15 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based on an indication of a specific individual at a location in the social media data.

16 . The hybrid neural network system of claim 1 wherein the specific individual is a celebrity.

17 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based a presence of a rare or transient phenomena at a location in the social media data.

18 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based a commerce-related event at a location in the social media data.

19 . The hybrid neural network system of claim 1 wherein the hybrid neural network is trained for at least one of predicting and optimizing based an entertainment event at a location in the social media data.

20 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes traffic conditions or weather conditions.

21 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes entertainment options.

22 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes risk-related conditions.

23 . The hybrid neural network system of claim 22 wherein the risk-related conditions include crowds gathering for potentially dangerous reasons.

24 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes commerce-related conditions.

25 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes goal-related conditions.

26 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes estimates of attendance at an event.

27 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes predictions of attendance at an event.

28 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes modes of transportation.

29 . The hybrid neural network system of claim 28 wherein the modes of transportation include car traffic.

30 . The hybrid neural network system of claim 28 wherein the modes of transportation include public transportation options.

31 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes hash tags.

32 . The hybrid neural network system of claim 1 wherein the social media data analyzed to predict a localized effect on a transportation system includes trending of topics.

33 . The hybrid neural network system of claim 1 wherein an outcome of a transportation system optimization action is at least one of: reducing fuel consumption; reducing traffic congestion; reduced pollution; and bad weather avoidance.

34 . The hybrid neural network system of claim 1 wherein an operating state of the transportation system being optimized includes an in-vehicle state.

35 . The hybrid neural network system of claim 1 wherein an operating state of the transportation system being optimized includes a routing state.

36 . The hybrid neural network system of claim 35 wherein the routing state is for an individual vehicle.

37 . The hybrid neural network system of claim 35 wherein the routing state is for a set of vehicles.

38 . The hybrid neural network system of claim 1 wherein an operating state of the transportation system being optimized includes a user-experience state.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 2, 2022
From: STRONG FORCE INTELLECTUAL CAPITAL, LLC
To: STRONG FORCE TP PORTFOLIO 2022, LLC
Reel/Frame 061960/0235 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 8, 2020
From: CELLA, CHARLES HOWARD
To: STRONG FORCE INTELLECTUAL CAPITAL, LLC
Reel/Frame 053714/0389 →