Associating identification information with visually captured information

Patent metadata

Field	Value
Publication number	US-12087121-B2
Application number	US-202117330825-A
Country	US
Kind code	B2
Filing date	May 26, 2021
Priority date	May 26, 2020
Publication date	Sep 10, 2024
Grant date	Sep 10, 2024

Abstract

Systems, devices, and methods for associating vehicle identification information with other visually captured information are provided. In general, a system can include a processor configured to receive an image from a camera located at a fueling station. The processor can be configured to apply an algorithm to extract various features from the image, such as a vehicle that is present in the image, facial features of a driver and/or a passenger of the vehicle, or a license plate of the vehicle. The features can be used by the processor to determine information from the features, such as the identity of the driver, the make/model of the vehicle, or an owner of the vehicle. The processor can then, based on the determined information, be configured to take a variety of actions and thereby reduce the likelihood of possible future losses associated with the vehicles or individuals present in the image.

First claim

What is claimed is:

1. A method, comprising:
receiving, by a server, a first data packet, the first data packet including image data acquired by a first sensor included within a fuel dispenser at a fueling station and a second sensor positioned in a forecourt of the fueling station, the image data depicting at least one of an individual at the fueling station and a vehicle at the fueling station;
processing, by the server, the image data to determine a plurality of regions within the image data and a feature of the at least one of the individual and a make or model of the vehicle within at least one region of the plurality of regions, the processing including evaluating the image data with a machine learning algorithm that determines the plurality of regions within the image data and determines the feature of the individual and the make or model of the vehicle within the at least one region, the machine learning algorithm trained with model image data characterizing an image of a model feature corresponding to the determined
feature of the individual or the make or model of the vehicle;
transmitting, by the server, a query to a remote database, the query including the determined feature;
receiving, by the server, a second data packet from the remote database, the second data packet including identification information corresponding to the determined feature of the individual or the make or model of the vehicle;
determining, by the server, an alert based on the identification information, the alert including an instruction executable by the fuel dispenser to control operations thereof;
providing, by the server, the alert to the fuel dispenser, which once received causes the fuel dispenser to dispense a fuel type compatible with the make or model of the vehicle; and
further comprising determining, by the server, a third alert based on the identification information, the third alert including an indication of whether the individual is a drive-off suspect, and providing, by the server, the indication for display on a computing device of an attendant of the fueling station;
wherein responsive to displaying the indication, the computing device is configured to receive an input causing an instruction to reduce a rate of fuel dispensation to be provided to the fuel dispenser.

2. The method of claim 1 , further comprising determining, by the server, a second alert based on the identification information, the second alert including second instruction executable by the fuel dispenser and providing, by the server, the second alert to the fuel dispenser, which once received by the fuel dispenser causes the fuel dispenser to disable dispensing fuel types that are incompatible with the make or model of the vehicle.

3. The method of claim 1 , wherein the image data includes a depiction of at least a portion of the vehicle, a depiction of a license plate of the vehicle, and a depiction of the individual.

4. The method of claim 3 , wherein a second determined feature includes a license plate number provided on the license plate, and a third determined feature includes a face of the individual.

5. The method of claim 4 , wherein the identification information includes a name of a registered owner of the vehicle and a registered vehicle make or/model associated with the second determined feature, the registered owner of the vehicle and the registered vehicle make or/model provided at the remote database.

6. The method of claim 5 , further comprising determining, by the server, a fourth alert comprising an indication of the presence or absence of a match between the first determined feature and the registered vehicle make or model associated with the second determined feature and providing, by the server, the fourth alert to an end user device of an attendant of the fueling station.

7. The method of claim 4 , wherein the identification information includes a name of the customer and a name of a registered owner of the vehicle associated with the second determined feature, the registered owner of the vehicle provided at the remote database.

8. A system, comprising: a processor; and a memory storing instructions configured to cause the processor to perform operations comprising: analyzing a first data packet including image data acquired by a first sensor included within a fuel dispenser at a fueling station and a second sensor positioned in a forecourt of the fueling station to determine a plurality of regions within the image data and a feature within at least one region of the plurality of regions of at least one of an individual at the fueling station and a make or model of a vehicle at the fueling station, the analyzing including evaluating the image data with a machine learning algorithm that determines the plurality of regions within the image data and determines the feature of the individual and the make or model of the vehicle within the at least one region, the machine learning algorithm trained with model image data characterizing an image of a model feature corresponding to the determined feature of the individual or the make or model of the vehicle; transmitting a query to a remote database, the query including the determined feature; determining an alert based on a second data packet received from the remote database, the alert including an instruction executable by the fuel dispenser to control operations thereof, the second data packet including identification information corresponding to the determined feature of the individual or the make or model of the vehicle; and providing the alert to the fuel dispenser, which once received cause the fuel dispenser to dispense a fuel type compatible with the make or model of the vehicle; and
further comprising determining, by the server, a third alert based on the identification information, the third alert including an indication of whether the individual is a drive-off suspect, and providing, by the server, the indication for display on a computing device of an attendant of the fueling station;
wherein responsive to displaying the indication, the computing device is configured to receive an input causing an instruction to reduce a rate of fuel dispensation to be provided to the fuel dispenser.

9. The system of claim 8 , wherein a plurality of fuel dispensers are located in a forecourt of the fueling station, and the image data depicts the forecourt of the fueling station.

10. The system of claim 8 , wherein the sensor is located at the fueling station, and the acquired image data is uniquely associated with one of a plurality of fuel dispensers at the fueling station.

11. The system of claim 8 , wherein the instructions are further configured to cause the processor to provide an indication of the alert for display on a fueling station attendant terminal.

12. The system of claim 8 , wherein the instructions are further configured to cause the processor to provide a second alert to a notification service in operable communication with law enforcement personnel.

13. A non-transitory computer program product storing instructions which, when executed by a processor forming part of at least one computing system, cause the processor to implement operations comprising: analyzing a first data packet including image data acquired by a first sensor included within a fuel dispenser at a fueling station and a second sensor positioned in a forecourt of the fueling station to determine a plurality of regions within the image data and a feature within at least one region of the plurality of regions of at least one of an individual at the fueling station and a make or model of a vehicle at the fueling station, the analyzing including evaluating th

Assignees

• Wayne Fueling Systems Llc

Inventors

• Fieglein Henry
• Singh Kalpit
• Chinnaswamy Rohith
• Hairston Hob

Classifications

• G06V2201/08

  Detecting or categorising vehicles · CPC title

• G06V20/625

  License plates · CPC title

• G06V40/161

  Detection; Localisation; Normalisation · CPC title

• G06V20/52

  Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) · CPC title

• G07F15/001

  for gas · CPC title