Two-dimensional code-based cooperative intelligent ordering method and system

Abstract

The invention discloses a two-dimensional code-based cooperative intelligent ordering method and system. The system comprises a mobile terminal with a two-dimensional code scanning function and a server supporting ordering and payment functions. The mobile terminal can be an intelligent mobile phone and a tablet computer. The server is used for processing ordering information, and mainly comprises a barcode module, an ordering module, a user management module, an intelligent recommendation module and a payment module; the barcode module mainly comprises two-dimensional code and verification code generation and verification functions; the ordering module is used for supporting ordering (including remote ordering) of multiple persons and voice ordering; the user management module is mainly used for automatically identifying user identities and storing user consumption information; the intelligent recommendation module is mainly used for providing big data cloud services for merchants, digging user consumption habits, tastes and the like according to user consumption records and providing personalized dish and service recommendations for users; and the payment module is mainly used for supporting transaction of cash, electronic payment (including remote payment for another) and the like.

Description

technical field [0001] The present invention relates to the technical field of information systems in the catering industry, in particular to the field of catering ordering, and specifically refers to a method and system for ordering catering based on two-dimensional codes. Background technique [0002] In the ordering mode of the traditional catering industry, each restaurant needs to print multiple paper menus, which has a limited service life and is inconvenient to replace the content, and due to the limitation of the number of pages, it cannot provide customers with sufficient information content display. In actual application, service personnel are required to verbally or manually record and convey to users, which is inefficient and error-prone. It can be seen that the traditional ordering mode wastes a lot of human and material resources. [0003] Nowadays, electronic ordering systems are becoming more and more popular, but they basically need to be equipped with spec...

AI Technical Summary

Problems solved by technology

[0002] In the ordering mode of the traditional catering industry, each restaurant needs to print multiple paper menus, the service life is limited and the content is inconvenient to replace, and due to the limitation of the number of pages, it cannot provide sufficient information content display for guests

In actual application, service personnel are required to verbally or manually record and convey to users, which is inefficient and error-prone

It can be seen that the traditional ordering mode wastes a lot of human and material resources

[0003] Now electronic ordering systems are becoming more and more popular, but they basically need to be equipped with special ordering terminals, and the cost of these ordering terminals is relatively high

Since the order is placed through the waiter, the waiter is often overwhelmed during the peak dining period, causing waiting and inconvenience to the guests

At the same time, when customers order food in a restaurant, users often cannot see all the prices they ordered in real time. They often need to check when they check out, occupying the use time of the table and reducing the efficiency of the restaurant.

Some food ordering systems support collaborative ordering through QR codes and NFC tags, etc., but usually only support local single or multiple people ordering, and cannot support remote collaborative ordering, let alone invite friends on behalf of others under the popularization of social networks. Pay and other remote payment functions

Many collaborative ordering systems cannot identify users' identities in real time, let alone provide users with personalized ordering recommendation services

Images