# US 12,182,890 B2 · Contactless vehicle ordering and automation system > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,182,890 B2 - Document ID: US12182890B2 - Status: Granted - Kind: B2 - Application number: 18/450,334 - Filed: 2023-08-15 - Published: 2023-12-14 - Granted: 2024-12-31 - Earliest claimed: 2021-01-25 - Assignees: Pied Parker, Inc. - Applicants: Pied Parker, Inc. - Inventors: Gianni Rosas-Maxemin; Robert Mazzola; George Azzi; Callam Poynter; John Oglesby - Web page: https://patentgrep.com/patent/US12182890B2 ## CPC - G06Q 50/12: Hotels or restaurants - G06Q 20/12: specially adapted for electronic shopping systems - G06Q 20/18: involving self-service terminals [SST], vending machines, kiosks or multimedia terminals - G06Q 20/202: {Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR} - G06Q 20/204: {comprising interface for record bearing medium or carrier for electronic funds transfer or payment credit} - G06Q 20/206: {comprising security or operator identification provisions, e.g. password entry} - G06Q 20/4014: {Identity check for transactions} - G06Q 20/4015: {using location information} - G06Q 30/0641: {utilising user interfaces specially adapted for shopping} - G06V 20/625: {License plates} - G06V 40/172: {Classification, e.g. identification} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A computing system, includes: a non-transitory memory; processors coupled to the non-transitory memory and configured to execute instructions to perform operations including: detecting a vehicle at a first location, executing instructions local to the first location by one or more edge processors to determine vehicle specific parameters that identify the vehicle; determining the vehicle is associated with a user account stored in a computerized vehicle management system; in response to the determining that the vehicle is associated with the user account, and transmitting instruction to a first display at the first location to present a user-tailored menu generated by using the edge processors to access a machine learning computer model based on data obtaining from the user account. ## Claims ### Claim 1 A computing system, comprising: a non-transitory memory; a first display; a camera coupled to the computing system; one or more processors coupled to the non-transitory memory and configured to execute instructions to perform operations comprising: identifying a vehicle at a first location using camera data captured by one or more cameras; determining if the vehicle identified matches a user account associated with a computerized user management system; transmitting an instruction to the first display at the first location to present a default menu, if the vehicle does not match the user account; transmitting an instruction to the first display at the first location to present a user-tailored menu generated based on machine learning or behavior analysis computer model trained with data obtained from the user account, if the vehicle is determined to match the user account; updating the user-tailored menu based on a busyness of a second location; and transmitting the one or more orders to an electronic device at the second location. ### Claim 2 (depends on 1) The system of claim 1, wherein determining if the vehicle identified matches the user account, further comprises: comparing one or more user-specific parameters against a user account database included in the computerized user management system. ### Claim 3 (depends on 1) The system of claim 1, wherein the camera coupled to the computing system is an Automatic License Plate Recognition (ALPR) camera that is configured to recognize a license plate of the vehicle. ### Claim 4 (depends on 3) The system of claim 3, wherein the one or more user specific parameters comprises at least the license plate of the vehicle. ### Claim 5 (depends on 1) The system of claim 1, wherein the one or more user specific parameters includes facial features or facial geometry data. ### Claim 6 (depends on 1) The system of claim 1, wherein the user-tailored menu comprises one or more of a recommendation menu, recent orders, a loyalty and reward program in association with the user account. ### Claim 7 (depends on 1) The system of claim 1, wherein the second location comprises one or more food preparing stations. ### Claim 8 (depends on 1) The system of claim 1, wherein the user-tailored menu is further tailored based on demographic or ethnic characteristics. ### Claim 9 (depends on 1) The system of claim 1, wherein the user-tailored menu is updated based upon one or more of a customer's order history, a specific item's preparation time, time of the day, and day of the week. ### Claim 10 (depends on 1) The system of claim 1, wherein the busyness is determined by an average time of preparing an order. ### Claim 11 (depends on 1) The system of claim 1, the operations further comprising: receiving payment of one or more orders via the first display via one of the payment methods selected from the group consisting of credit card, debit card, cash, crypto currency, PAYPAL, VENMO, ZELLE, APPLE PAY, Bluetooth payment, and NFC payment. ### Claim 12 (depends on 1) The system of claim 1, wherein the one or more processors are further configured to perform operations comprising: providing instructions to direct the vehicle to a waiting zone by presenting a set of navigation instructions to the user. ### Claim 13 (depends on 1) The system of claim 1, wherein the one or more processors are further configured to perform operations comprising: transmitting a notification to the user account when the one or more orders are ready. ### Claim 14 (depends on 1) The system of claim 1, wherein the second location further comprises an auto-food maker robot, wherein the auto-food maker robot is configured to receive the one or more orders and initiate an auto-food preparation process to prepare the one or more orders. ### Claim 15 A method for vehicle drive-through ordering, comprising: identifying a vehicle at a first location using camera data captured by one or more cameras; determining if the vehicle identified matches a user account associated with a computerized user management system; transmitting an instruction to the first display at the first location to present a default menu, if the vehicle does not match the user account; transmitting an instruction to the first display at the first location to present a user-tailored menu generated based on machine learning or behavior analysis computer model trained with data obtained from the user account, if the vehicle is determined to match the user account; updating the user-tailored menu based on a busyness of a second location; and transmitting the one or more orders to an electronic device at the second location. ### Claim 16 (depends on 15) The method of claim 15, wherein the camera coupled to the computing system is an Automatic License Plate Recognition (ALPR) camera that is configured to recognize a license plate of the vehicle. ### Claim 17 (depends on 15) The method of claim 15, wherein the one or more user specific parameters comprise at least the license plate of the vehicle. ### Claim 18 (depends on 15) The method of claim 15, the method further comprising updating the user-tailored menu based on determining the user has arrived on off-peak hours. ### Claim 19 (depends on 18) The method of claim 18, the method further comprising transmitting to the user an incentive for one or more orders based on the determination that the user arrived within off-peak hours. ### Claim 20 A non-transitory, computer readable media, comprising instructions that when executed by a processor, cause the processor to perform a method for vehicle drive-through ordering, comprising: identifying a vehicle at a first location using camera data captured by one or more cameras; determining if the vehicle identified matches a user account associated with a computerized user management system; transmitting an instruction to the first display at the first location to present a default menu, if the vehicle does not match the user account; transmitting an instruction to the first display at the first location to present a user-tailored menu generated based on machine learning or behavior analysis computer model trained with data obtained from the user account, if the vehicle is determined to match the user account; updating the user-tailored menu based on a busyness of a second location; and transmitting the one or more orders to an electronic device at the second location.