US 12,243,270 B2
Dynamic image-based parking management systems and methods of operation thereof
Gianni Rosas-Maxemin, Sacramento, CA (US); George Azzi, Sacramento, CA (US); Callam Poynter, Sacramento, CA (US); and Robert Mazzola, Sacramento, CA (US)
Assigned to PIED PARKER, INC., Sacramento, CA (US)
Filed by PIED PARKER, INC., Sacramento, CA (US)
Filed on Oct. 4, 2021, as Appl. No. 17/493,795.
Claims priority of provisional application 63/087,872, filed on Oct. 5, 2020.
Prior Publication US 2022/0108474 A1, Apr. 7, 2022
Int. Cl. G06T 7/80 (2017.01); G06T 7/70 (2017.01); G06V 20/52 (2022.01); H04N 23/60 (2023.01); H04N 23/661 (2023.01); H04N 23/80 (2023.01)
CPC G06T 7/80 (2017.01) [G06T 7/70 (2017.01); G06V 20/52 (2022.01); H04N 23/64 (2023.01); H04N 23/661 (2023.01); H04N 23/80 (2023.01); G06T 2207/30264 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A method of operating a camera-based parking management system, comprising:
activating an AI-enabled camera covering a staging area responsive to detecting a vehicle;
capturing a first snapshot of the staging area using the AI-enabled camera;
transmitting the first snapshot to an edge processor coupled to the AI-enabled camera to identify one or more objects shown in the first snapshot;
determining that first object observed in the first snapshot is not capable of being identified with a predefined degree of certainty based on a machine learning model;
responsive to the determining:
identifying first one or more characteristics about the environmental conditions surrounding the first object that potentially reduce an identification accuracy of one or more vehicle-specific parameters; and
identifying second one or more characteristics about the first snapshot that potentially reduce the identification accuracy of one or more vehicle-specific parameters; and
automatically adjusting one or more settings of the AI-enabled camera to capture a second snapshot based on identifying the first one or more characteristics about the environmental conditions surrounding the first object;
automatically adjusting one or more settings of the processing of images captured by the AI-enabled camera based on identifying the second one or more characteristics about the first snapshot;
wherein the second one or more characteristics about the first snapshot include a resolution of the snapshot, network availability based on the time of day, and a network speed of a network connection between the AI-enabled camera and the edge processor;
capturing the second snapshot of the staging area using the AI-enabled camera;
determining the first object observed in the first snapshot is capable of being identified with the predefined degree of certainty based on the machine learning model; and
adjusting the machine learning model based on the adjustment of the settings of the AI-enabled camera and settings of the processing of images captured by the AI-enabled camera.