Granted Patent B2

US 12,198,456 · App. 18/438,203 · Granted Jan 14, 2025

Inventors: Evan DeSantola (Pittsburgh, PA); Alex Litzenberger (Pittsburgh, PA); Rassoul Mesbah (Aukland, NZ); Prashasti Sar (Pittsburgh, PA)

Assignee: HME Hospitality &Specialty Communications, Inc.

G06V20/68G01B11/22G01S17/89G06F3/0482G06F18/214G06N20/00G06Q10/063112G06Q20/20G06Q50/12G06T7/11G06T7/20G06T7/70G06V10/70G06V10/765G06V20/20G06V20/36G06V20/52G06V20/64H04N7/18H04N23/90G06T2200/24G06T2207/10028G06T2207/20081G06T2207/30232G06V2201/08

Abstract

Claims (67)

1. A method, comprising:

receiving, by a processing device, image data comprising one or more image frames indicative of a state of a drive-thru area;

determining, by the processing device, a vehicle disposed within the drive-thru area based on the image data;

receiving, by the processing device, order data indicative of a pending meal order;

determining, by the processing device, a first association between the vehicle and the pending meal order based on the image data;

determining, by the processing device, an expected order preparation time for the pending meal order;

determining, by the processing device, a meal delivery procedure associated with the vehicle based on the first association, wherein determination of the meal delivery procedure includes a selection of a first meal delivery area, wherein selection of the first meal delivery area is based on the expected order preparation time as determined;

directing the vehicle to the first meal delivery area, based on the expected arrival time as determined; and

performing, by the processing device, at least one of a) initiating the meal delivery procedure or b) communicating a notification associated with the meal delivery procedure.

2. The method of claim 1 , wherein the first meal delivery area is a waiting bay, wherein the waiting bay is separate and distinct from a payment zone in the drive-thru area where payments are handled.

3. The method of claim 1 , further comprising:

selecting the first meal delivery area from a set of multiple meal delivery areas.

4. The method of claim 1 , further comprising: receiving, by the processing device, additional image data comprising one or more additional image frames indicative of an additional state of the drive-thru area; determining, by the processing device, a second association between the vehicle and the pending meal order based on the additional image data.

5. The method of claim 4 , wherein the additional image data depicts a payment zone in the drive-thru area where payments are handled.

6. The method of claim 1 , wherein the image data depicts an order zone in the drive-thru area where orders are placed, including the pending meal order.

7. The method of claim 1 , wherein the image data is used as input into a machine learning model trained to detect objects in the one or more image frames, wherein one or more outputs of the machine learning model include information indicative of one or more objects detected by the machine learning model, and wherein determination of the vehicle disposed within the drive-thru area is based on the one or more outputs of the machine learning model.

8. The method of claim 5 , wherein the additional image data is used as input into a machine learning model trained to detect objects in the one or more additional image frames, wherein one or more outputs of the machine learning model include information indicative of a particular vehicle detected by the machine learning model, and wherein determination of the second association is based on the one or more outputs of the machine learning model indicating that the vehicle is now disposed within the payment zone.

9. The method of claim 1 , further comprising:

determining, by the processing device, that completion of the meal delivery procedure in a payment zone in the drive-thru area where payments are handled would delay meal deliveries to other vehicles, based on the expected order preparation time for the pending meal order.

10. A method, comprising:

receiving, by a processing device, image data comprising one or more image frames indicative of an order zone in the drive-thru area where orders are placed;

using the image data as input into a machine learning model trained to detect objects in the one or more image frames;

receiving one or more outputs from the machine learning model, wherein the one or more outputs include information indicative of one or more objects detected by the machine learning model;

determining, by the processing device, a vehicle disposed within the drive-thru area based on the one or more outputs of the machine learning model;

receiving, by the processing device, order data indicative of a pending meal order;

determining, by the processing device, a first association between the vehicle and the pending meal order based on the image data;

determining, by the processing device, a meal delivery procedure associated with the vehicle based on the first association; and

performing, by the processing device, at least one of a) initiating the meal delivery procedure or b) communicating a notification associated with the meal delivery procedure.

11. A system comprising:

a first camera configured to capture image data including one or more image frames indicative of a state of a drive-thru area;

a memory configured to electronically store information;

a processing device, coupled to the memory, configured to:

receive, from the first camera, the image data;

determine a vehicle disposed within the drive-thru area based on the image data;

receive order data indicative of a pending meal order;

determine a first association between the vehicle and the pending meal order based on the image data;

determine an expected order preparation time for the pending meal order;

determine a meal delivery procedure associated with the vehicle based on the first association, wherein determination of the meal delivery procedure includes a selection of a first meal delivery area, wherein selection of the first meal delivery area is based on the expected order preparation time as determined;

direct the vehicle to the first meal delivery area, based on the expected arrival time as determined; and

perform at least one of

a) initiate the meal delivery procedure, and/or

b) communicate a notification associated with the meal delivery procedure.

12. The system of claim 11 , wherein the first meal delivery area is a waiting bay, wherein the waiting bay is separate and distinct from a payment zone in the drive-thru area where payments are handled.

13. The system of claim 11 , wherein the processing device is further configured to:

select the first meal delivery area from a set of multiple meal delivery areas.

14. The system of claim 11 , wherein the processing device is further configured to: receive additional image data comprising one or more additional image frames indicative of an additional state of the drive-thru area;

determine a second association between the vehicle and the pending meal order based on the additional image data.

15. The system of claim 14 , wherein the additional image data depicts a payment zone in the drive-thru area where payments are handled.

16. The system of claim 11 , wherein the image data depicts an order zone in the drive-thru area where orders are placed, including the pending meal order.

17. The system of claim 11 , wherein the image data is used as input into a machine learning model trained to detect objects in the one or more image frames, wherein one or more outputs of the machine learning model include information indicative of one or more objects detected by the machine learning model, and wherein determination of the vehicle disposed within the drive-thru area is based on the one or more outputs of the machine learning model.

18. The system of claim 15 , wherein the additional image data is used as input into a machine learning model trained to detect objects in the one or more additional image frames, wherein one or more outputs of the machine learning model include information indicative of a particular vehicle detected by the machine learning model, and wherein determination of the second association is based on the one or more outputs of the machine learning model indicating that the vehicle is now disposed within the payment zone.

19. The system of claim 11 , wherein the processing device is further configured to:

determine that completion of the meal delivery procedure in a payment zone in the drive-thru area where payments are handled would delay meal deliveries to other vehicles, based on the expected order preparation time for the pending meal order.

20. A system, comprising:

a first camera configured to capture image data including one or more image frames indicative of an order zone in a drive-thru area where orders are placed;

a memory configured to electronically store information;

a processing device, coupled to the memory, configured to:

receive, from the first camera, the image data;

use the image data as input into a machine learning model trained to detect objects in the one or more image frames;

receive one or more outputs from the machine learning model, wherein the one or more outputs include information indicative of one or more objects detected by the machine learning model;

determine a vehicle disposed within the drive-thru area based on the one or more outputs of the machine learning model;

receive order data indicative of a pending meal order;

determine a first association between the vehicle and the pending meal order based on the image data;

determine a meal delivery procedure associated with the vehicle based on the first association; and

perform at least one of:

a) initiate the meal delivery procedure, and/or

b) communicate a notification associated with the meal delivery procedure.

Assignments (2)

Continuity (4)

References Cited (68)