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Method and apparatus for Cognition enabled Discernment Specialist for Restaurant food order Disclosure Number: IPCOM000248873D
Publication Date: 2017-Jan-19

Publishing Venue

The Prior Art Database


The industry trend is emerging towards "Cognitive models" enabled via a Big Data platform. Such models termed as "Cognitive entities" are aimed to remember the past, interact with humans, continuously learn and refine the responses for future. The machines are becoming intelligent and finding the smarter way to serve humans. A cognitive assistant can continue the conversation with leads by interacting with humans in a more natural way. In this invention publication, we propose a cognitive system for food ordering and natural language assistant for the people which will serve as a guide to an individual or group of individuals at the time of placing food order in hotels. The cognitive food ordering system will take inputs from various static and dynamic platforms and frame the conversations accordingly as detailed later.

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Method and apparatus for Cognition enabled Discernment Specialist for Restaurant food order

Summary :

When we go to the restaurant, first big question in the mind is what food to order, food ordering in the restaurant is very challenging task

when you are with large quorum with everybody having their own choices and constraints. Many a time’s people don’t know the famous dishes

in the area or in that restaurant. This confuses even more while ordering the food. Some information technology organisations are working on

ordering food online which generally has a huge list of menu card which creates confusion even more while selecting food.

Cognitive Discernment Specialist for Restaurant (CDSR) will serve as an assistant and advisor while food ordering and considers number

of people, nature of the people, their purpose of gathering, health history and suggests best available food for the people-set. This will provide the

detailed insights of the menu card considering all provided constraints in more natural way.

This proposed system takes the natural language inputs and detects the probable purpose and type of the lunch/dinner and suggest food

accordingly. For example, if user provides "Hey.!! This is office party for person XXX's birthday" Then the CDSR manipulates the inputs and

suggest a cake with other food items. If people count change is detected, then CE recomputes the suggestions and pops up "Hey, as YYY left,

this new set of orders will be best suited for you.." . Paired smart monitoring devices like micro cameras are used to detect the people using face

recognition or similar techniques, uniquely identify the person and personality insights database provides the likes-dislikes of the person, food

habits and preferences based on unique mapping mechanisms like mobile number or unique identification number. The priority engine takes the

patterns from databases and suggests the best food for the set of people. Internet connected APIs provides the information about the famous food

in the area and also fetches the menu card of the restaurant where the users are. Also fetches feedback provided on internet for the dishes in that

restaurant and considers them while making a selection.

IoT enablement and integration to health database of users leads to consideration of health related factors while placing order. For

example, if a guy on table is diabetic, then considering this health circumstances, CDSR will suggest not to order sweet dishes. Or if somebody

from the group has an allergy for some specific food content, then CDSR will restrict the group from ordering food which contains the allergenic


Extension of this invention to smart tables and integration of tablet computers in restaurant table will provide the suggestion and displays

customized, priority based menus on the table top itself which helps in deciding the dishes and assist users as a companion.

Novelty of the solution:

The novelty of this solution is to provide a metho...