Method for delivering a custom sandwich to a patron
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06Q-050/12
G07F-017/00
G06Q-030/06
G09B-019/00
출원번호
US-0208149
(2014-03-13)
등록번호
US-10068273
(2018-09-04)
발명자
/ 주소
Frehn, Steven
McDonald, John Lawrence
Vardakostas, Alexandros
Shapiro Hawk, Harry
출원인 / 주소
Creator, Inc.
대리인 / 주소
Harness, Dickey & Pierce, P.L.C.
인용정보
피인용 횟수 :
0인용 특허 :
50
초록▼
One variation of a method for personalizing food orders includes: from a patron, receiving a taste feedback for a first food item in a first food order submitted previously by the patron; predicting an absolute food preference of the patron from the first food order; predicting a relative taste pref
One variation of a method for personalizing food orders includes: from a patron, receiving a taste feedback for a first food item in a first food order submitted previously by the patron; predicting an absolute food preference of the patron from the first food order; predicting a relative taste preference of the patron based on the taste feedback and a recipe of the first food item; generating a taste profile of the patron based on the absolute food preference and the relative taste preference; from the patron, receiving a selection for a second food item in a new food order, the second food item different than the first food item; applying the taste profile of the patron to a recipe for the second food item to generate a personalized recipe; and submitting the personalized recipe with the new food order to a robotic food assembly apparatus.
대표청구항▼
1. A method for preparing personalized food orders, the method comprising: accessing a current ingredient configuration of a food assembly apparatus;retrieving a set of food orders previously submitted by a patron, wherein the set of food orders comprises a first food order specifying a first food i
1. A method for preparing personalized food orders, the method comprising: accessing a current ingredient configuration of a food assembly apparatus;retrieving a set of food orders previously submitted by a patron, wherein the set of food orders comprises a first food order specifying a first food item and wherein the set of food orders is stored in a database;following fulfillment of food orders in the set of food orders, calculating an absolute food preference, of the patron, based on ingredients specified for inclusion and omission in the set of food orders;calculating a relative taste preference, of the patron, defining a preference of the patron for a percentage difference between a delivered amount of a first ingredient in the first food item and a standard amount of the first ingredient specified in a standard recipe for the first food item based on the set of food orders and a set of standard recipes;generating a taste profile of the patron based on the absolute food preference and the relative taste preference;receiving, from the patron through an ordering application, a selection for a second food item in a new food order supported by the current ingredient configuration of the food assembly apparatus, wherein the second food item is different from the first food item;applying the taste profile of the patron to a standard recipe for the second food item to generate a personalized recipe that specifies a target amount of the first ingredient in the second food item based on a standard amount of the first ingredient specified in the standard recipe for the second food item and the relative taste preference; andcontrolling actuators within the food assembly apparatus to assemble the second food item according to the personalized recipe. 2. The method of claim 1, wherein: the first food item is an instance of a first food type,calculating the absolute food preference comprises correlating election of a particular ingredient for addition to the first food item in the first food order with a preference for the particular ingredient in food items of the first food type,generating the taste profile comprises specifying addition of the particular ingredient to food items of the first food type, andapplying the taste profile to the standard recipe for the second food item comprises, in response to the second food item being an instance of the first food type, specifying addition of the particular ingredient to the second food item in the personalized recipe. 3. The method of claim 2, wherein: the first food type is a hamburger, andthe particular ingredient is a hamburger topping. 4. The method of claim 1, wherein: the ordering application executes on a mobile computing device,the ordering application displays a menu of food items supported by the current ingredient configuration of the food assembly apparatus,the taste profile is stored on the mobile computing device, andthe personalized recipe is uploaded to the food assembly apparatus via a computer network. 5. The method of claim 4, further comprising: receiving an input from the patron for the first food item through the ordering application following fulfillment of the first food order,wherein the input specifies a preference of the patron for a difference between a delivered amount of a particular ingredient in the first food item and a standard amount of the particular ingredient andwherein calculating the relative taste preference is based on the input. 6. The method of claim 1, wherein calculating the relative taste preference of the patron comprises: accessing a demographic of the patron,identifying a second patron of a demographic similar to the demographic of the patron, andupdating the relative taste preference of the patron based on the relative taste preference of the second patron. 7. The method of claim 1, wherein calculating the relative taste preference of the patron comprises: extrapolating a trend in custom ingredients ordered by the patron in the set of food orders comprising the first food order; andaggregating the trend in custom ingredients ordered by the patron into the relative taste preference. 8. The method of claim 1, wherein: the first ingredient is seasoning,applying the taste profile of the patron to the standard recipe for the second food item comprises scaling the standard amount of the first ingredient specified in the standard recipe for the second food item to a target amount of seasoning based on the relative taste preference, andthe standard amount of the first ingredient specified in the standard recipe for the second food item is a preset mass of seasoning. 9. A method for preparing personalized food orders, the method comprising: receiving, from a patron through an ordering application executing on a computing device, a selection for a new food item in a new food order;retrieving a set of food orders previously submitted by the patron and feedback from the patron corresponding to food orders in the set of food orders, wherein the set of food orders and the patron feedback is stored in a database;identifying an absolute food preference, of the patron, from a trend within the set of food orders;based on the patron feedback following fulfillment of food orders in the set of food orders, identifying a relative taste preference, of the patron, comprising identifying a preference for a percentage difference between a delivered amount of a topping in a food item and a standard amount of the topping specified in a recipe for the food item;generating a taste profile of the patron based on the absolute food preference and the relative taste preference;applying the taste profile of the patron to a standard recipe for the new food item to generate a personalized recipe that specifies a target amount of the topping in the new food item based on a standard amount of the topping specified in the standard recipe for the new food item and the preference for the percentage difference; andcontrolling actuators within a food assembly apparatus to assemble the new food item according to the personalized recipe. 10. The method of claim 9, wherein: retrieving the set of food orders comprises retrieving a first food order for a first food item and a second food order for a second food item,the second food item is different from the first food item, andthe new food item in the new food order is different from the first food item and the second food item. 11. The method of claim 9, wherein: identifying the absolute food preference comprises identifying a trend in elected omission of a particular ingredient in food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to omit the particular ingredient. 12. The method of claim 9, wherein: identifying the absolute food preference further comprises identifying a trend in elected addition of a second particular ingredient in food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to add the second particular ingredient. 13. The method of claim 9, wherein: identifying the absolute food preference comprises identifying a trend in a particular meat doneness submitted with food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to specify the particular meat doneness for the new food item. 14. The method of claim 9, wherein: identifying the absolute food preference comprises identifying a trend in food item size for food items of a particular food type within the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises, in response to the new food item being of the particular food type, generating the personalized recipe to specify a size of the new food item based on the trend in food item size. 15. The method of claim 14, wherein: identifying the trend in item size comprises identifying the trend in food item size relative to time of day, andapplying the taste profile to the recipe for the new food item comprises generating the personalized recipe to specify the size of the new food item further based on a time of day that the selection for the new food item is received. 16. The method of claim 9, wherein: the topping is tomato; andthe standard amount of the topping specified in the standard recipe for the new food item is a preset thickness of tomato. 17. A system comprising: at least one processor; anda non-transitory computer-readable medium configured to store instructions for execution by the at least one processor, wherein the instructions include: receiving, from a patron through an ordering application executing on a computing device, a selection for a new food item in a new food order;retrieving a set of food orders previously submitted by the patron and feedback from the patron corresponding to food orders in the set of food orders, wherein the set of food orders and the patron feedback is stored in a database;identifying an absolute food preference, of the patron, from a trend within the set of food orders;based on the patron feedback following fulfillment of food orders in the set of food orders, identifying a relative taste preference, of the patron, comprising identifying a preference for a percentage difference between a delivered amount of a topping in a food item and a standard amount of the topping specified in a recipe for the food item;generating a taste profile of the patron based on the absolute food preference and the relative taste preference;applying the taste profile of the patron to a standard recipe for the new food item to generate a personalized recipe that specifies a target amount of the topping in the new food item based on a standard amount of the topping specified in the standard recipe for the new food item and the preference for the percentage difference; andcontrolling actuators within a food assembly apparatus to assemble the new food item according to the personalized recipe. 18. The system of claim 17, wherein: retrieving the set of food orders comprises retrieving a first food order for a first food item and a second food order for a second food item,the second food item is different from the first food item, andthe new food item in the new food order is different from the first food item and the second food item. 19. The system of claim 17, wherein: identifying the absolute food preference comprises identifying a trend in elected omission of a particular ingredient in food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to omit the particular ingredient. 20. The system of claim 17, wherein: identifying the absolute food preference further comprises identifying a trend in elected addition of a second particular ingredient in food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to add the second particular ingredient. 21. The system of claim 17, wherein: identifying the absolute food preference comprises identifying a trend in a particular meat doneness submitted with food orders in the set of food orders, andapplying the taste profile to the standard recipe for the new food item comprises generating the personalized recipe to specify the particular meat doneness for the new food item. 22. The system of claim 17, wherein: identifying the absolute food preference comprises identifying a trend in food item size for food items of a particular food type within the set of food orders,identifying the trend in item size comprises identifying the trend in food item size relative to time of day,applying the taste profile to the standard recipe for the new food item comprises, in response to the new food item being of the particular food type, generating the personalized recipe to specify a size of the new food item based on the trend in food item size, andapplying the taste profile to the recipe for the new food item comprises generating the personalized recipe to specify the size of the new food item further based on a time of day that the selection for the new food item is received.
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이 특허에 인용된 특허 (50)
Robinson Hugh (Wenham MA), Apparatus for automatic application of condiments to a sandwich.
Leary Steven G. (San Mateo CA) Benson Clark K. (Millbrae CA) Caridis Andrew A. (Foster City CA) Brown Daniel E. (San Bruno CA), Cooking a food product in a process vapor at progressively varying rates.
Flisram Dennis G. (Madison WI) Rattmann James A. (Sun Prarie WI) Skaar Gary R. (Marshall WI) Holmes Terry L. (Monona WI), Measurement of cutting edge sharpness.
Adam K. Kolawa ; Arthur Ray Hicken ; Stephen Frankini ; Skirmantas Kligys ; Emelina Gesheshyen ; Maxim Troukhan, Method and apparatus for automated selection, organization, and recommendation of items.
Caveza Martin J. (Redondo Beach CA) Chung Caleb S. (Van Nuys CA) Handy John N. (Long Beach CA) Tucker Jim I. (Manhattan Beach CA), Simulated toy hamburger maker.
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