US 12,493,900 B2
Image-based parking recognition and navigation
Gianni Rosas-Maxemin, Sacramento, CA (US); Robert Mazzola, Sacramento, CA (US); Francisco Sandoval, Sacramento, CA (US); Callam Poynter, Sacramento, CA (US); and Noah Kindler, Palo Alto, CA (US)
Assigned to Pied Parker, Inc., Sacramento, CA (US)
Filed by Pied Parker, Inc., Sacramento, CA (US)
Filed on Nov. 14, 2023, as Appl. No. 18/509,248.
Application 18/509,248 is a continuation of application No. 16/730,999, filed on Dec. 30, 2019, granted, now 11,816,709.
Claims priority of provisional application 62/840,999, filed on Apr. 30, 2019.
Claims priority of provisional application 62/786,006, filed on Dec. 28, 2018.
Prior Publication US 2024/0086982 A1, Mar. 14, 2024
Int. Cl. G06Q 50/40 (2024.01); G06N 20/00 (2019.01); G06Q 30/0283 (2023.01)
CPC G06Q 30/0284 (2013.01) [G06N 20/00 (2019.01); G06Q 50/40 (2024.01)] 19 Claims
OG exemplary drawing
 
1. A computerized vehicle management system, comprising:
a non-transitory memory; and
one or more processors coupled to the non-transitory memory and configured to execute instructions to perform operations comprising:
receiving a request for an available parking space for a vehicle from a user device associated with the vehicle, the request including user preferences for the available parking space at a first location within a geographic area;
transmitting a prompt to a user account associated with the user device to verify a parking fee transaction, the prompt including price and hours information associated with a service at the available parking space; wherein the price and hours information are based on vehicle specific parameters and user preferences stored in the vehicle-user account;
capturing, using one or more cameras, first image data associated with the vehicle;
providing the image data associated with the vehicle to a computer vision machine learning model running on a processor located proximate to the available parking space to determine vehicle specific parameters associated with the vehicle;
determining:
i) if a user account identified by the vehicle specific parameters determined by the computer vision machine learning model matches a vehicle-user account stored in the computerized vehicle management system by comparing the vehicle specific parameters associated with the vehicle against a vehicle-user account database included in the computerized vehicle management system, the vehicle specific parameters including a license plate and at least one other parameter other than the license plate; and
ii) that the first location is within proximity to the user device associated with the vehicle based on short-range wireless communication between the user device and an access control mechanism; and
responsive to determining both i) and ii), transmitting instructions to the access control mechanism at the geographic area to permit access to the first location by the vehicle.