CN111584036B - Restaurant health data management method, system and storage medium - Google Patents
Restaurant health data management method, system and storage medium Download PDFInfo
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/12—Hotels or restaurants
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
- G06V20/36—Indoor scenes
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Abstract
The invention discloses a restaurant health data management method, a system and a storage medium, wherein the restaurant health data management method comprises a data settlement process, and the data settlement process comprises the following steps: acquiring a menu list of dishes ordered by a diner; generating a bill of charge corresponding to the menu list according to the menu list; generating a health data list corresponding to the menu list according to the menu list; wherein the health data list comprises intake data for a plurality of types of food ingredients. According to the dining health data management method, system and storage medium, the bill and the health data list are provided for the diners at the same time when the diners check out every time, quantitative food ingredient intake data can be provided for the diners, and the diners can conduct health management according to the reference data.
Description
Technical Field
The invention relates to the technical field of intelligent management of restaurant health, in particular to a restaurant health data management method, a restaurant health data management system and a storage medium.
Background
With the continuous improvement of living standard, people's life is continuously improved, diet is better and better, and excessive intake of food, especially high-calorie food such as excessive intake of large fish and meat, can cause excessive intake of energy, and accumulation of daily life and month, and obesity is caused. While obesity has been considered as the hotbed for most metabolic diseases, it is extremely dangerous to health. In addition, excessive eating for a long time is easy to aggravate coronary heart disease, easy to suffer from cerebrovascular disease, easy to suffer from diabetes and seriously endanger the physical health of people. Currently, in daily life, people can only roughly estimate whether their own diet is excessive or not through weight change to draw attention, and a system capable of managing daily dining data of human beings is lacking.
Disclosure of Invention
The invention aims to: in order to overcome the defects in the prior art, the invention provides a restaurant health data management method, a restaurant health data management system and a storage medium, and aims to provide a system and a method for providing food ingredient intake data of each meal for a diner, and provide references for the diner to manage own diet health.
The technical scheme is as follows: in order to achieve the above object, the food and beverage health data management method of the present invention is applied to a food and beverage health data management system, and includes a data settlement process, wherein the data settlement process includes:
Acquiring a menu list of dishes ordered by a diner;
generating a bill of charge corresponding to the menu list according to the menu list;
Generating a health data list corresponding to the menu list according to the menu list; wherein the health data list comprises intake data for a plurality of types of food ingredients.
Further, after generating the health data list corresponding to the dish list according to the dish list, the method further comprises:
Dietary advice and/or sports advice within a set period of time after generation from the health data list.
Further, the dining personnel has an electronic form of user account, and the data settlement process further comprises:
Establishing contact with the user account according to a first operation instruction of a diner;
The method further comprises the following steps of:
Deducting a corresponding amount of fees from the user account based on the total amount of fees in the bill of fees;
pushing the bill of charge data and the health data bill data to the user account.
Further, the method also comprises a meal ordering management flow, wherein the meal ordering management flow comprises the following steps:
Acquiring a health data list in a set period of time in the user account;
Generating a recommended intake profile from the health data list over a set period of time, the recommended intake profile comprising recommended intake values corresponding to each food ingredient;
acquiring electronic menu data, wherein the electronic menu data comprises dishes, prices and food component data of the dishes which can be provided by a dining place where a diner is located;
And generating a recommended diet list according to the recommended ingestion pattern and the electronic menu data.
Further, the generating a recommended intake profile from the health data list over a set period of time includes:
Acquiring the generation time of each health data list in a set period;
calculating the residual value of each food component contained in the data list according to the generation time and the metabolic rule of each food component;
Superposing the residual values of the similar food components of all the health data lists within a set period of time to obtain a residual map of each food component in the current body of the reaction diner;
And calculating the recommended intake map according to the residual map.
Further, the calculating the recommended intake profile from the residual profile comprises:
Obtaining age data of a diner from the user account;
acquiring recommended intake values of food components corresponding to the age groups of the dining staff according to the age data;
Calculating a recommended intake value corresponding to each food component in the residual spectrum according to the residual value of the food component and the recommended intake value corresponding to the residual value;
Summarizing the recommended intake values for each food ingredient to obtain the recommended intake profile.
A dining health data management system comprising a processor and a memory;
the memory is used for storing executable programs;
The processor is used for executing the executable program to realize the restaurant health data management method.
A storage medium having stored thereon an executable program which when executed implements the dining health data management method described above.
The beneficial effects are that: the dining health data management method, the system and the storage medium can provide quantitative food ingredient intake data for the diners by providing the bill and the health data bill for the diners at the same time when the diners check out each time, so that the diners can carry out health management according to the reference data, and the dining health data management method, the system and the storage medium are suitable for carrying out health diet management on the diners who have stably eaten in occasions such as schools, unit canteens and the like.
Drawings
Fig. 1 is a schematic flow chart of a restaurant health data management method.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that the description of "first", "second", etc. in this disclosure is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implying an indication of the number of technical features being indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present invention.
Furthermore, in the following description, suffixes such as "module", "component", or "unit" for representing elements are used only for facilitating the description of the present invention, and have no specific meaning per se. Thus, "module," "component," or "unit" may be used in combination.
The restaurant health data management method shown in fig. 1 is applied to a restaurant health data management system (hereinafter referred to as a management system), and includes a data settlement process, wherein the data settlement process includes the following steps S101-S103:
step S101, acquiring a menu list of dishes ordered by a diner;
Step S102, generating a fee list corresponding to the dish list according to the dish list;
In the step, the price of each dish in the dish list can be conveniently inquired according to the dish list, and the total amount of all dishes can be calculated;
Step S103, generating a health data list corresponding to the menu list according to the menu list; wherein the health data list comprises intake data for a plurality of types of food ingredients.
In this step, the health data list may preferably further include a health intake value corresponding to each food ingredient, and an overrun value or an overrun percentage of the intake data with respect to the health intake value, so that a diner can conveniently know which food ingredients are over-standard and how much to overrun according to the overrun value or the overrun percentage data, and can conveniently control in the subsequent diet so that some food ingredients are not over-ingested for a long period of time.
In the step S103, the values of the food components corresponding to the dishes are stored in the management system, and the dishes provided in the dining hall, restaurant, etc. for providing the catering service are generally quantitatively provided, so that the content of the food components in each dish can be easily counted.
Preferably, after generating the health data list corresponding to the dish list according to the dish list in the step S103, the method further includes the following step S104:
step S104, diet advice and/or exercise advice in a set period of time after the generation of the health data list.
In this step, the management system may count the excess value or percentage of the intake data relative to the healthy intake value, determine which food components exceed the set threshold based on the excess value or percentage, and then give a diet recommendation such as: if the ingested fat exceeds the standard, the eater can be recommended to eat less meat food in a set period of time, and if the ingested cholesterol exceeds the standard, the eater can be recommended to eat less yolk, butter and other foods in the set period of time.
In the above steps S102 and S103, the form of the bill of fee and the health data list may be paper, but preferably an electronic data form is adopted, the diner has a user account in electronic form, and the diner can receive the electronic data and manage the electronic data through a mobile terminal such as a mobile phone, and based on this, the data settlement process further includes the following step S201:
step S201, establishing contact with the user account according to a first operation instruction of a diner;
in the step, a diner can make a management system establish contact with the user account in the form of code scanning and the like through the mobile terminal;
based on this, after generating the health data list corresponding to the dish list according to the dish list in the above step S103, the method further includes the following steps S301-S302:
Step S301, deducting corresponding amount of fees from the user account according to the total amount of fees in the bill of fees;
step S302, pushing the bill of charge data and the health data bill data to the user account.
In addition, the user can edit the health data list on the mobile terminal according to the actual diet condition, so that the situation that the user does not eat all the dishes and the management system counts all the food components corresponding to the dishes into the health data list to cause inaccurate data can be avoided, for example, the user can edit the number of people eating or the eating proportion of the dishes in the health data list, and after the editing is completed, the management system can adjust the data and regenerate diet suggestions and/or exercise suggestions and recalculate the exceeding value or exceeding percentage of each food component according to the data, so that the user can better adjust the follow-up diet.
Optionally, the method further includes an ordering management flow, where the ordering management flow includes the following steps S401 to S404:
Step S401, a health data list in a set period of time in the user account is obtained;
Step S402, generating a recommended intake map according to the health data list within a set period, wherein the recommended intake map comprises recommended intake values corresponding to food components;
step S403, acquiring electronic menu data, wherein the electronic menu data comprises dishes, prices and food component data of the dishes which can be provided by a dining place where a diner is located;
And step S404, generating a recommended diet list according to the recommended ingestion pattern and the electronic menu data.
Through the steps, the management system can provide accurate meal suggestions for the user, so that the meal management of the user is more visual, fatigue brought by boring data to the meal user is avoided, and the management system also has certain auxiliary meal ordering attribute, so that the user can improve the meal ordering efficiency.
Preferably, the generating the recommended intake map according to the health data list in the set period in the step S402 includes the following steps S501-S504:
Step S501, obtaining the generation time of each health data list in a set period;
Step S502, calculating the residual value of each food component contained in the data list according to the generation time and the metabolic rule of each food component;
step S503, overlapping the residual values of the similar food components of all the health data lists in a set period of time to obtain a residual map of each food component in the current body of the reaction diner;
Step S504, calculating the recommended intake map according to the residual map.
In the steps S501-S504, the metabolic rules of the human body are fully considered, and the recommended intake map is calculated, so that the result accuracy is high, the reference value is good, and the recommended diet list has a more healthy value.
Preferably, the calculating the recommended intake map according to the residual map in the step S504 includes the following steps S601-S604:
step S601, acquiring age data of a diner from the user account;
Step S602, acquiring recommended intake values of food components corresponding to the age groups of the diners according to the age data;
Step S603, calculating a recommended intake value corresponding to each food component according to the residual value of the food component in the residual map and the recommended intake value corresponding to the residual value;
step S604, summarizing the recommended intake values of the food ingredients to obtain the recommended intake map.
In the steps S601-S604, the age bracket of the user is fully considered, the recommended intake value is given according to the typical metabolic rule and other characteristics of the age bracket, and the recommended intake value is calculated according to the recommended intake value, so that the data accuracy of the calculated recommended intake map can be further improved.
Further, the generating a recommended diet list according to the recommended intake map and the electronic menu data in the step S404 includes the following steps S701-S706:
step S701, selecting a catering template, wherein the catering template comprises a plurality of vegetable grades, and each vegetable grade corresponds to a vegetable type;
In this step, the selection of the catering templates may be performed by the user through the user terminal, or may be performed by the management system itself, where typical catering templates are as follows: meat and vegetables, vegetables and soup and the like.
Step S702, classifying dishes in the electronic menu data;
in this step, if the dishes in the electronic menu data include braised pork, braised chicken nuggets, fried green vegetables and green pepper fried potatoes, the braised pork and the braised chicken nuggets can be classified into meat dishes, and the fried green vegetables and the green pepper fried potatoes can be classified into vegetable dishes.
Step S703, filling dishes in the electronic menu data to each dish grade of the catering template according to the dish types to obtain all dish combinations;
In the step, if the meal matching template is meat and vegetable, and dishes in the electronic menu data are only braised meat, stewed chicken nuggets, fried green vegetables and green pepper fried potatoes, the braised meat and the stewed chicken nuggets are respectively matched with the meat dish grade, and the fried green vegetables and the green pepper fried potatoes are respectively matched with the vegetable grade, four dish combinations can be obtained.
Step S704, calculating food ingredient data of each dish combination;
step S705, judging the matching degree of the food ingredient data of each dish combination and the recommended intake map;
In this step, the criterion of matching degree may be determined by calculating the closeness of the food component data of the dish combination to the recommended intake value of each food component in the recommended intake map.
Step S706, selecting a plurality of groups of dish combinations with highest matching degree as recommended diet lists.
Thereafter, the management system may implement one-touch ordering by interacting with the dining personnel, who select a recommended diet listing.
In the step S101, the manner of obtaining the menu list of the dishes ordered by the diner may be varied, and here, an intelligent menu list obtaining method is described by taking the occasions such as schools, unit canteens and the like as an example.
Here, the menu list is obtained by adopting an image recognition mode, so that the hardware management system comprises a camera, the software management system is internally provided with an image recognition module, the view of the camera covers the menu area of one of the menu workers in the canteen, and the camera can also cover the main active area of the menu workers, so that the camera can obtain the menu container (a common menu spoon) and the menu container (a common dinner plate) held by the workers besides the image of the menu area, wherein the menu container generally comprises a plurality of menu grids so as to be convenient for accommodating different dishes. In addition, the dish district contains the square basin that holds that a plurality of square arrays set up, and the boundary line of each dish square basin constitutes square network and separates the dish district into a plurality of district, and every district all has a serial number, has a dish square basin in every district, all holds a dish in every dish square basin, and dish name and regional serial number one-to-one and the correspondence of both are stored in management system.
Based on the above, the process of the management system obtaining the menu of the dishes ordered by the diner is as follows steps S801 to S804:
step S801, the image recognition module tracks the position of a dish-making container according to the data acquired by the camera;
In this step, the image recognition module may extract and recognize the dish-playing container in the image collected by the camera according to the shape of the dish-playing container, and after recognizing the dish-playing container, the image recognition module may learn the area number of the position of the dish-playing container (when the dish-playing container is in a certain area) according to the division of the dish area, where the dish-playing container is located, in step S801, the position of the dish-playing container refers to the area number.
Step S802, the image recognition module monitors the empty and full state of the dish-making container and the empty and full state of the dish-containing grid in the dish-containing container according to the data acquired by the camera;
In the step, the image recognition module performs extraction and recognition on the dish container, performs extraction and recognition on the dish container based on walking, and further performs further recognition on the Cheng Cai grid image in the image after extracting the image of the dish container. In this step, the image recognition module can easily recognize whether the dish-making container is empty or full according to the characteristics of the dish-making container in the empty state, so as to know whether dishes are contained in the dish-making container, and the image recognition module can recognize the empty-full state of the dish-containing grid in the dish-containing container. In order to prevent dishes from being attached to the inside of the dish beating container, the image recognition module cannot recognize that the dish beating container is in an empty state, and the inside of the dish beating container can be coated with an oleophobic layer, so that when the dumping operation is executed, the dishes in the dish beating container can be fully poured out, the attachment of greasy dirt is reduced, and the false recognition of the image recognition module is avoided.
Step 803, when the change rule of the empty and full states of the dish-making container and the change condition of the empty and full states of the dish-holding grid in the dish-holding container conform to the set rule, confirming that one effective triggering event is completed;
Specifically, in this step, the set rule is: the change rule of the empty and full states of the dish-making container is changed from empty to full to empty, and one dish containing grid in the dish containing container is changed from empty to full. Thus, the collection and conversion module 10 can determine that the staff performs the operation of loading dishes into the dish containing container, and can eliminate the operation that the staff takes up dishes and returns the dishes to the dish containing square basin, so that false detection is not caused;
Step S804, determining the information of dishes according to the position of the empty and full state change of the dish-beating container.
In the above step S803, it is confirmed that the worker has performed the operation of loading the dishes into the dish container, but has not yet confirmed what dishes are being played, so step S804 can find out the names of the dishes according to the correspondence between the area numbers and the names of the dishes by identifying the area numbers where the dish playing container is located when the state of the dish playing container is changed from empty to full.
Therefore, according to the dishes-beating operation of the dishes-beating staff, which dishes are beaten can be intelligently identified, and a dish list is generated.
The image recognition method in the steps S801-S804 has low hardware requirements for image recognition, the camera does not need to specifically shoot images of dishes, the image recognition module does not need to perform dish recognition according to the images, the image recognition module only needs to extract boundary information of each area and position information of a dish container, and recognizes empty and full information of the dish container and empty and full information of a dish containing grid in the dish containing container, so that a worker can place dishes in the dish containing grid, the recognition is accurate, a large number of image algorithms are not needed for recognition, the problem of false recognition caused by too much appearance of dishes in the traditional image recognition algorithm can be avoided, the hardware cost is saved, and the camera with high resolution is not needed.
The invention also provides a restaurant health data management system, which comprises a processor and a memory; the memory is used for storing executable programs; the processor is used for executing the executable program to realize the restaurant health data management method.
The invention also provides a storage medium, wherein the storage medium is stored with an executable program, and the executable program is executed to realize the restaurant health data management method.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (5)
1. The catering health data management method is characterized by being applied to a catering health data management system and comprising a data settlement process, wherein the data settlement process comprises the following steps of:
Acquiring a menu list of dishes ordered by a diner;
generating a bill of charge corresponding to the menu list according to the menu list;
generating a health data list corresponding to the menu list according to the menu list; wherein the health data list comprises intake data for a plurality of types of food ingredients;
the dining personnel has an electronic form of user account, and the data settlement process further comprises:
Establishing contact with the user account according to a first operation instruction of a diner;
The method further comprises the following steps of:
Deducting a corresponding amount of fees from the user account based on the total amount of fees in the bill of fees;
pushing the bill of charge data and the health data bill data to the user account;
The method also comprises a meal ordering management flow, wherein the meal ordering management flow comprises the following steps:
Acquiring a health data list in a set period of time in the user account;
Generating a recommended intake profile from the health data list over a set period of time, the recommended intake profile comprising recommended intake values corresponding to each food ingredient;
acquiring electronic menu data, wherein the electronic menu data comprises dishes, prices and food component data of the dishes which can be provided by a dining place where a diner is located;
Generating a recommended diet list according to the recommended ingestion pattern and the electronic menu data;
the generating a recommended intake map according to the health data list within a set period of time comprises:
Acquiring the generation time of each health data list in a set period;
calculating the residual value of each food component contained in the data list according to the generation time and the metabolic rule of each food component;
Superposing the residual values of the similar food components of all the health data lists within a set period of time to obtain a residual map of each food component in the current body of the reaction diner;
Calculating the recommended intake profile from the residual profile;
the generating a recommended diet manifest from the recommended intake profile and the electronic menu data comprises:
Selecting a catering template, wherein the catering template comprises a plurality of vegetable grades, and each vegetable grade corresponds to a vegetable type;
Classifying dishes in the electronic menu data;
Filling dishes in the electronic menu data to the grade of each dish of the catering template according to the types of the dishes to obtain all dish combinations;
calculating food ingredient data for each of the dish combinations;
judging the matching degree of the food ingredient data of each dish combination and the recommended intake map;
Selecting a plurality of groups of dish combinations with highest matching degree as recommended diet lists;
one-touch ordering can be achieved by the diner selecting a recommended dietary menu.
2. The dining health data management method according to claim 1, wherein after generating a health data list corresponding to the dish list according to the dish list, further comprises:
Dietary advice and/or sports advice within a set period of time after generation from the health data list.
3. Catering health data management method according to claim 1, wherein the calculating the recommended intake profile from the residual profile comprises:
Obtaining age data of a diner from the user account;
acquiring recommended intake values of food components corresponding to the age groups of the dining staff according to the age data;
Calculating a recommended intake value corresponding to each food component in the residual spectrum according to the residual value of the food component and the recommended intake value corresponding to the residual value;
Summarizing the recommended intake values for each food ingredient to obtain the recommended intake profile.
4. A restaurant health data management system, comprising a processor and a memory;
the memory is used for storing executable programs;
the processor is configured to execute the executable program to implement the dining health data management method as claimed in any one of claims 1-3.
5. A storage medium having stored thereon an executable program which when executed implements a dining health data management method as claimed in any one of claims 1-3.
Priority Applications (1)
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