Cooking management
US-10709289-B2 · Jul 14, 2020 · US
US11317759B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11317759-B2 |
| Application number | US-202016920268-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 2, 2020 |
| Priority date | Nov 23, 2011 |
| Publication date | May 3, 2022 |
| Grant date | May 3, 2022 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A cooking management system is described that identifies a customer and orders a product for the customer based at least on current temporal data. The cooking management system identifies customers associated with previous product requests that occurred during a predetermined range of time based at least on a comparison of current temporal data with temporal data associated with the previous product requests. The cooking management system causes presentation of identifiers of the identified customers on a display. Responsive to determining that the identifier for a particular customer has been selected, the cooking management system automatically causes a cooking device to prepare a product for the particular customer based at least on customer data associated with the particular customer.
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method, comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining current temporal data; identifying in real time a plurality of customers associated with a plurality of previous product requests that occurred during a predetermined range of time based at least on a comparison of the current temporal data with temporal data associated with the plurality of previous product requests; causing presentation of identifiers of the plurality of customers on a display; determining an identifier for a particular customer has been selected; and responsive to determining that the identifier for the particular customer has been selected, automatically causing a cooking device to prepare a product for the particular customer based at least on customer data stored in a data storage device and associated with the particular customer. 2. The computer-implemented method of claim 1 , wherein identifying in real time the plurality of customers is further based at least on location information of at least one of the plurality of previous product requests, the customer, a vendor of the product, and the cooking device. 3. The computer-implemented method of claim 1 , wherein automatically causing the cooking device to prepare the product for the customer is further based at least on the current temporal data. 4. The computer-implemented method of claim 1 , wherein the predetermined range of time is a different day than the current temporal data and is based at least on at least one of the time of day of the current temporal data, the day of the week of the current temporal data, and the season of the current temporal data. 5. A computer-implemented method, comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining current temporal data; identifying in real time a customer associated with a previous product request that occurred within a predetermined range of time based at least on a comparison of the current temporal data with temporal data associated with the previous product request; and automatically requesting a product for the customer based at least on customer data stored in a data storage device and associated with the customer. 6. The computer-implemented method of claim 5 , wherein identifying in real time the plurality of customers is further based at least on location information. 7. The computer-implemented method of claim 6 , wherein the location information comprises location information of at least one of the previous product request, the customer, and a vendor of the product. 8. The computer-implemented method of claim 5 , wherein automatically requesting the product for the customer is further based at least on the current temporal data. 9. The computer-implemented method of claim 5 , wherein the predetermined range of time is a different day than the current temporal data. 10. The computer-implemented method of claim 5 , wherein the predetermined range of time is based at least on at least one of the time of day of the current temporal data, the day of the week of the current temporal data, and the season of the current temporal data. 11. The computer-implemented method of claim 5 , wherein the customer data comprises data regarding one or more previous product requests associated with the customer and wherein requesting the product for the customer is further based at least on the one or more previous product requests associated with the customer. 12. The computer-implemented method of claim 5 , wherein the customer data comprises product preference data of the customer. 13. The computer-implemented method of claim 5 , wherein the temporal data associated with the previous product request comprises data corresponding to the time at which the previous product request occurred. 14. The computer-implemented method of claim 5 , wherein the data storage device stores temporal data associated with at least one thousand previous product requests and stores customer data associated with at least one thousand customers. 15. The computer-implemented method of claim 5 , wherein the comparison of the current temporal data with the temporal data associated with the previous product request comprises a determination that the previous product request occurred within the predetermined range of time. 16. A system, comprising: a computing device in communication with one or more content data stores comprising customer data associated with at least one customer, data regarding at least one previous product request, and temporal data associated with the at least one previous product request, wherein the computing device is configured to: obtain current temporal data; identify in real time a customer associated with a previous product request of the at least one previous product request that occurred during a predetermined range of time based at least on a comparison of the current temporal data with temporal data associated with the previous product request; and automatically request a product for the customer based at least on the customer data associated with the at least one customer. 17. The system of claim 16 , wherein identifying in real time the customer is further based at least on location information of at least one of the previous product request, the customer, and a vendor of the product. 18. The system of claim 16 , automatically requesting the product for the customer is further based at least on the current temporal data. 19. The system of claim 16 , wherein the predetermined range of time is a different day than the current temporal data and is based at least on at least one of the time of day of the current temporal data, the day of the week of the current temporal data, and the season of the current temporal data. 20. A computer-readable, non-transitory storage medium having one or more computer-executable modules, the one or more computer-executable modules comprising: a first module in communication with one or more content data stores comprising customer data associated with at least one customer, data regarding at least one previous product request, and temporal data associated with the at least one previous product request, wherein the first module is configured to: obtain current temporal data; identify in real time a customer associated with a previous product request of the at least one previous product request that occurred during a predetermined range of time based at least on a comparison of the current temporal data with temporal data associated with the previous product request; and automatically request a product for the customer based at least on the customer data associated with the at least one customer. 21. The computer-readable, non-transitory storage medium of claim 20 , wherein identifying in real time the customer is further based at least on location information of at least one of the previous product request, the customer, and a vendor of the product. 22. The computer-readable, non-transitory storage medium of claim 20 , automatically requesting the product for the customer is further based at least on the current temporal data. 23. The computer-readable, non-transitory storage medium of claim 20 , wherein the predetermined range of time is a different day than the current temporal data and is based at least on at least one of the time of d
Hotels or restaurants · CPC title
Parts, details or accessories of cooking-vessels (A47J27/00 - A47J33/00 take precedence insofar as these parts, details or accessories are restricted to a particular kind of cooking-vessel provided for in a single one of these groups) · CPC title
electric · CPC title
Commerce · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.