Automated preparation and dispensation of food and beverage products
In one embodiment, the present disclosure includes a cloud based management system controlling a plurality of automated food production systems residing at different locations. A machine learning algorithm may be used to modify recipe data to customize recipes.
1. A system comprising:
one or more servers;
a plurality of automated food production systems, residing at different locations, controlled by a cloud based management system executing on at least one server of the one or more servers, the automated food production systems comprising at least one a robotic arm assembly and a plurality of software controlled hardware components coupled to the at least one server for performing food preparation tasks, wherein the automated food production systems are peripherals of the cloud based management system independently configured by the cloud based management system to produce different food items based on different recipes, wherein the recipes are stored in the cloud based management system and not stored in the automated food production systems; and
a machine learning algorithm, executing on at least one server of the one or more servers, the machine learning algorithm accessing a set of data for one or more users of the plurality of automated food production systems and generating, for particular users, recipe data,
wherein, in response to a request from a user received in the cloud based management system, the cloud based management system translates the recipe data into instructions executable by particular software controlled hardware components in at least one automated food production system to produce a food item.
2. The system as recited in claim 1 , wherein the machine learning algorithm makes a modification to an existing recipe.
3. The system as recited in claim 2 , wherein the modification is based on an input from a user adjusting an amount of one or more ingredients.
4. The system as recited in claim 1 , wherein the recipe data comprises ingredient data for at least one ingredient of a plurality of ingredients of a particular recipe.
5. The system as recited in claim 1 , wherein the set of data for one or more users is received from orders submitted to one or more of the plurality of automated food production systems.
6. The system as recited in claim 1 , wherein the plurality of automated food production systems form kiosks.
7. The system as recited in claim 6 , wherein the automated food production systems further comprise a server.
8. A method comprising:
receiving a request from a user in a cloud based management system executing on at least one server of one or more servers, the cloud based management system controlling a plurality of automated food production systems residing at different locations, the automated food production systems comprising at least one a robotic arm assembly and a plurality of software controlled hardware components coupled to the at least one server for performing food preparation tasks, wherein the automated food production systems are peripherals of the cloud based management system independently configured by the cloud based management system to produce different food items based on different recipes, wherein the recipes are stored in the cloud based management system and not stored in the automated food production systems;
accessing, by a machine learning algorithm executing on at least one server of the one or more servers, a set of data for one or more users of the plurality of automated food production systems;
generating, by a machine learning algorithm, recipe data for the user; and;
translating, by the cloud based management system, the recipe data into instructions executable by particular software controlled hardware components in at least one automated food production system to produce a food item.
9. The method of claim 8 , wherein the machine learning algorithm makes a modification to an existing recipe.
10. The method of claim 9 , wherein the modification is based on an input from a user adjusting an amount of one or more ingredients.
11. The method of claim 8 , wherein the recipe data comprises ingredient data for at least one ingredient of a plurality of ingredients of a particular recipe.
12. The method of claim 8 , wherein the set of data for one or more users is received from orders submitted to one or more of the plurality of automated food production systems.
13. The method of claim 8 , wherein the automated food production systems further comprise a server.
14. A non-transitory computer readable storage medium having computer code thereon, the computer code executable to:
receiving a request from a user in a cloud based management system executing on at least one server of one or more servers, the cloud based management system controlling a plurality of automated food production systems residing at different locations, the automated food production systems comprising at least one a robotic arm assembly and a plurality of software controlled hardware components coupled to the at least one server for performing food preparation tasks, wherein the automated food production systems are peripherals of the cloud based management system independently configured by the cloud based management system to produce different food items based on different recipes, wherein the recipes are stored in the cloud based management system and not stored in the automated food production systems;
accessing, by a machine learning algorithm executing on at least one server of the one or more servers, a set of data for one or more users of the plurality of automated food production systems;
generating, by a machine learning algorithm, recipe data for the user; and;
translating, by the cloud based management system, the recipe data into instructions executable by particular software controlled hardware components in at least one automated food production system to produce a food item.
15. The non-transitory computer readable storage medium of claim 14 , wherein the machine learning algorithm makes a modification to an existing recipe.
16. The non-transitory computer readable storage medium of claim 15 , wherein the modification is based on an input from a user adjusting an amount of one or more ingredients.
17. The non-transitory computer readable storage medium of claim 14 , wherein the recipe data comprises ingredient data for at least one ingredient of a plurality of ingredients of a particular recipe.
18. The non-transitory computer readable storage medium of claim 14 , wherein the set of data for one or more users is received from orders submitted to one or more of the plurality of automated food production systems.
19. The non-transitory computer readable storage medium of claim 14 , wherein the automated food production systems further comprise a server.