Granted Patent B1

US 12,393,176 · App. 18/638,258 · Granted Aug 19, 2025

Inventors: Christopher Clinton Chappell (Lincoln, CA); Rodney Daniel Sparks (Antelope, CA); Josh David Schumacher (Sacramento, CA); Joseph Allen Steele, III (Plumas Lake, CA)

Assignee: Quick Quack Car Wash Holdings, LLC

G05B19/4155G05B2219/31229

Abstract

Claims (42)

1. An apparatus for initiating a command for an equipment controller, the apparatus comprising:

at least a processor; and

a memory communicatively connected to the at least processor, wherein the memory contains instructions configuring the at least processor to:

receive a structured data package from a primary controller, wherein the structured data package comprises a configuration category and a malfunction datum, wherein the malfunction datum comprises an indication that a malfunction is at an increased chance of occurring;

identify an equipment command as a function of the structured data package, wherein identifying the equipment command comprises:

classifying the configuration category into an implementation category;

and identifying the equipment command as a function of the implementation category;

initiate the equipment command by transmitting the equipment command to an equipment controller, wherein the equipment controller comprises car wash tunnel equipment; and

after initiating the equipment command, transmitting an unstructured signal comprising a sensor output associated with the car wash tunnel equipment to the primary controller;

wherein the equipment command configures the equipment controller to utilize a function of equipment associated with the equipment controller.

2. The apparatus of claim 1 , wherein the processor is a component of a first secondary controller, wherein the structured data package comprises data originating from a second secondary controller.

3. The apparatus of claim 1 , wherein the memory contains instructions configuring the at least processor to identify the equipment command using a rule based engine.

4. The apparatus of claim 1 , wherein the memory contains instructions configuring the at least processor to identify the equipment command by:

training an equipment command machine learning model on a training dataset including a plurality of example structured data packages as inputs correlated to a plurality of example equipment commands as outputs; and

generating the equipment command as a function of the structured data packages using the trained equipment command machine learning model.

5. The apparatus of claim 1 , wherein the memory contains instructions configuring the at least processor to identify the equipment command by receiving an equipment command user input from the user.

6. The apparatus of claim 1 , wherein the memory contains instructions configuring the at least processor to transmit unstructured data indicating an operational status of the equipment to the primary controller.

7. The apparatus of claim 1 , wherein the equipment comprises equipment at a vehicle care site.

8. The apparatus of claim 1 , wherein classifying the configuration category into an implementation category comprises:

training an implementation classifier on a training dataset including a plurality of example configuration categories as inputs correlated to a plurality of example implementation categories as outputs; and

generating the implementation category as a function of the configuration category using the trained implementation classifier.

9. The apparatus of claim 1 , wherein the structured data package comprises a target parameter value.

10. The apparatus of claim 1 , wherein the indication that a malfunction is at an increased chance of occurring is within a car wash system.

11. A method of initiating a command for an equipment controller, the method comprising:

using at least a processor, receiving a structured data package from a primary controller, wherein the structured data package comprises a configuration category and a malfunction datum, wherein the malfunction datum comprises an indication that a malfunction is at an increased chance of occurring;

using at least a processor, identifying an equipment command as a function of the structured data package, wherein identifying the equipment command comprises classifying the configuration category into an implementation category, and identifying the equipment command as a function of the implementation category;

using at least a processor, initiating the equipment command by transmitting the equipment command to an equipment controller, wherein the equipment controller comprises car wash tunnel equipment; and

using at least a processor, after initiating the equipment command, transmitting an unstructured signal comprising a sensor output associated with the car wash tunnel equipment to the primary controller;

wherein the equipment command configures the equipment controller to utilize a function of equipment associated with the equipment controller.

12. The method of claim 11 , wherein the at least processor is a component of a first secondary controller, wherein the structured data package comprises data originating from a second secondary controller.

13. The method of claim 11 , wherein the equipment command is identified using a rule based engine.

14. The method of claim 11 , wherein the equipment command is identified by:

training an equipment command machine learning model on a training dataset including a plurality of example structured data packages as inputs correlated to a plurality of example equipment commands as outputs; and

generating the equipment command as a function of the structured data packages using the trained equipment command machine learning model.

15. The method of claim 11 , wherein the equipment command is identified by receiving an equipment command user input from the user.

16. The method of claim 11 , further comprising transmitting to the primary controller unstructured data indicating an operational status of the equipment to the primary controller.

17. The method of claim 11 , wherein the equipment comprises equipment at a vehicle care site.

18. The method of claim 11 , wherein classifying the configuration category into an implementation category comprises:

training an implementation classifier on a training dataset including a plurality of example configuration categories as inputs correlated to a plurality of example implementation categories as outputs; and

generating the implementation category as a function of the configuration category using the trained implementation classifier.

19. The method of claim 11 , wherein the structured data package comprises a target parameter value.

20. The method of claim 11 , wherein the indication that a malfunction is at an increased chance of occurring is within a car wash system.

Assignments (2)

References Cited (12)