CN109544203A - A kind of user's habit record and recommended method in dining room - Google Patents
A kind of user's habit record and recommended method in dining room Download PDFInfo
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- CN109544203A CN109544203A CN201811196569.4A CN201811196569A CN109544203A CN 109544203 A CN109544203 A CN 109544203A CN 201811196569 A CN201811196569 A CN 201811196569A CN 109544203 A CN109544203 A CN 109544203A
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- customer
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- faceid
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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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0255—Targeted advertisements based on user history
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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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0268—Targeted advertisements at point-of-sale [POS]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- Entrepreneurship & Innovation (AREA)
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Abstract
A kind of user in dining room is accustomed to record and recommended method, comprising the following steps: (1) establishes cloud server and serve a dish single database；(2) FaceID of customer is recorded by face identification system；(3) purchaser record corresponding with the customer FaceID is recorded, and is uploaded in the FaceID database in cloud server；(4) customer pushes its history purchaser record to the customer, and provide the vegetable with its purchaser record same type to customer again into behind shop.The invention has the benefit that (1) this product uses face recognition technology first, each facial information into shop user is saved as into an independent FACEID, when client into shop simultaneously, we will quickly analyze the comparison that the information of user carries out high speed, the history consumer record and hobby analysis for finding out client, allow salesman that can preferably provide thoughtful, careful service for client.
Description
Technical field
The present invention relates to the users in a kind of method more particularly to a kind of dining room to be accustomed to record and recommended method.
Background technique
The arrival of mobile internet era, the most important statistics and analysis no more than big data.But for major part
For Xian Xia shops, other than a small amount of essential information of membership information, the individual for how effectively understanding each into shop user believes
Breath and into the shop frequency, more preferably careful quality service be provided, know user for the hobby and consumption data of StoreFront food product, utilization
The tools production of mobile Internet is present urgent problem to the more simple and convenient service of client.
Summary of the invention
The purpose of the present invention is to solve for the defect in the presence of Restaurant Operation, provide a kind of meal in the prior art
The user in the Room is accustomed to record with recommended method to solve the above problems.
To achieve the goals above, technical scheme is as follows:
A kind of user's habit record and recommended method in dining room, which comprises the following steps:
(1) cloud server end is established, and establishes menu database in server end beyond the clouds；
(2) customer enters shops, the FaceID of customer is recorded by face identification system, and the FaceID of customer is uploaded
To cloud server, FaceID database is established；
(3) single cross of customer's generation point is easy, then records purchaser record corresponding with the customer FaceID, and uploads cloud clothes
It is engaged in the FaceID database in device；
(4) customer is identified the FaceID of customer by face identification system, pushes it to the customer and go through again into behind shop
History purchaser record, while the vegetable in menu database being classified, and is provided and its purchaser record same type to customer
Vegetable.
A kind of user in above-mentioned dining room is accustomed to record and recommended method, which is characterized in that the purchaser record of the customer
The picture of type of merchandize, unit price, commodity including this purchase.
A kind of user in above-mentioned dining room is accustomed to record and recommended method, which is characterized in that the shops does business knot daily
Uploaded after beam shops's same day into shop flow of the people, objective monodrome, consumption total amount and male to female ratio to cloud server.
A kind of user in upper dining room is accustomed to record and recommended method, which is characterized in that foundation is connected with cloud server
Mobile client, customer is ordered dishes by mobile client by mobile phone-downloaded mobile client, after customer orders dishes,
The vegetable that cloud server automatically places an order customer pushes in the dining room computer being connected with cloud server.
A kind of user in above-mentioned dining room is accustomed to record and recommended method, which is characterized in that after fixed time period,
Cloud server counts the raw materials consumption amount in each independent dining room in the period, and raw materials consumption amount is pushed to and cloud
In the dining room computer that end server is connected.
The invention has the benefit that (1) this product uses face recognition technology first, by each into the face of shop user
Portion's information saves as an independent FACEID, when client into shop simultaneously, the information of user will quickly be carried out the ratio of high speed by we
To analysis, the history consumer record and hobby analysis of client are found out, allows salesman that can preferably provide thoughtful, careful clothes for client
Business；(2) simultaneously, system will statistically analyze all statistical data analysis of StoreFront, include into shop amount, objective monodrome, spending amount, male
Female's ratio, consumptive power analysis, age piecewise analysis, real-time passenger flow data tracking, user's history order statistics, user online order
Order, comparison analysis of user etc., and StoreFront more operational suggestion is given according to the daily data of StoreFront；(3) simultaneously cloud dining room
Mobile Internet meal ordering system, can allow client on seat barcode scanning, order, pay, not only tool statistical data, simultaneously
It allows salesman that can extract the more time out and for client provides better service.The ERP system in cloud dining room can allow storefront management work
Work becomes more preferably simple.
Specific embodiment
The effect of to make to structure feature of the invention and being reached, has a better understanding and awareness, to preferable
Embodiment cooperation detailed description, is described as follows:
A kind of user's habit record and recommended method in dining room, which comprises the following steps:
(1) cloud server end is established, and establishes menu database in server end beyond the clouds, includes in menu database
All vegetables in shops, and classifying to all vegetables, at the same establish according to sales volume number establish vegetable ranking list；
(2) customer enters shops, the FaceID of customer is recorded by face identification system, and the FaceID of customer is uploaded
To cloud server, FaceID database is established, which includes the FaceID of customer, further includes the purchase of customer
Record, and the purchaser record of customer include type of merchandize, unit price, commodity picture；
(3) single cross of customer's generation point is easy, then records purchaser record corresponding with the customer FaceID, and uploads cloud clothes
It is engaged in the FaceID database in device；
(4) customer is identified the FaceID of customer by face identification system, pushes it to the customer and go through again into behind shop
History purchaser record, while the vegetable in menu database being classified, and is provided and its purchaser record same type to customer
Vegetable.
Shops uploaded after doing business daily shops's same day into shop flow of the people, objective monodrome, consumption total amount and men and women
Ratio is to cloud server.
The mobile client being connected with cloud server is established, customer is passed through by mobile phone-downloaded mobile client
Mobile client is ordered dishes, and after customer orders dishes, the vegetable that cloud server automatically places an order customer pushes to and cloud service
In the dining room computer that device is connected.
After fixed time period, such as one week or one month, cloud server count each list in the period
The raw materials consumption amount in only dining room, and raw materials consumption amount is pushed in the dining room computer being connected with cloud server, just
It is the preparation of next cycle progress raw material in dining room.
The invention has the benefit that (1) this product uses face recognition technology first, by each into the face of shop user
Portion's information saves as an independent FACEID, when client into shop simultaneously, the information of user will quickly be carried out the ratio of high speed by we
To analysis, the history consumer record and hobby analysis of client are found out, allows salesman that can preferably provide thoughtful, careful clothes for client
Business；(2) simultaneously, system will statistically analyze all statistical data analysis of StoreFront, include into shop amount, objective monodrome, spending amount, male
Female's ratio, consumptive power analysis, age piecewise analysis, real-time passenger flow data tracking, user's history order statistics, user online order
Order, comparison analysis of user etc., and StoreFront more operational suggestion is given according to the daily data of StoreFront；(3) simultaneously cloud dining room
Mobile Internet meal ordering system, can allow client on seat barcode scanning, order, pay, not only tool statistical data, simultaneously
It allows salesman that can extract the more time out and for client provides better service.The ERP system in cloud dining room can allow storefront management work
Work becomes more preferably simple.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and what is described in the above embodiment and the description is only the present invention
Principle, various changes and improvements may be made to the invention without departing from the spirit and scope of the present invention, these variation and
Improvement is both fallen in the range of claimed invention.The present invention claims protection scope by appended claims and its
Equivalent defines.
Claims (5)
1. a kind of user in dining room is accustomed to record and recommended method, which comprises the following steps:
(1) cloud server end is established, and establishes menu database in server end beyond the clouds；
(2) customer enters shops, and the FaceID of customer is recorded by face identification system, and the FaceID of customer is uploaded to cloud
Server is held, FaceID database is established；
(3) single cross of customer's generation point is easy, then records purchaser record corresponding with the customer FaceID, and upload cloud server
In FaceID database in；
(4) customer identifies the FaceID of customer by face identification system again into behind shop, pushes the purchase of its history to the customer
Record is bought, while the vegetable in menu database being classified, and provides the vegetable with its purchaser record same type to customer.
2. a kind of user in dining room according to claim 1 is accustomed to record and recommended method, which is characterized in that the customer
Purchaser record include this time purchase type of merchandize, unit price, commodity picture.
3. a kind of user in dining room according to claim 2 is accustomed to record and recommended method, which is characterized in that the shops
Taking into shop flow of the people, objective monodrome, consumption total amount and male to female ratio to cloud for the shops same day is uploaded after daily business
Business device.
4. a kind of user in dining room according to claim 3 is accustomed to record and recommended method, which is characterized in that foundation and cloud
The mobile client that end server is connected, customer are carried out a little by mobile phone-downloaded mobile client by mobile client
Dish, after customer orders dishes, the vegetable that cloud server automatically places an order customer pushes to the dining room electricity being connected with cloud server
In brain.
5. a kind of user in dining room according to claim 4 is accustomed to record and recommended method, which is characterized in that when fixed
Between after section, cloud server counts the raw materials consumption amount in each independent dining room in the period, and by raw materials consumption
Amount pushes in the dining room computer being connected with cloud server.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811196569.4A CN109544203A (en) | 2018-10-15 | 2018-10-15 | A kind of user's habit record and recommended method in dining room |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811196569.4A CN109544203A (en) | 2018-10-15 | 2018-10-15 | A kind of user's habit record and recommended method in dining room |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109544203A true CN109544203A (en) | 2019-03-29 |
Family
ID=65843687
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811196569.4A Pending CN109544203A (en) | 2018-10-15 | 2018-10-15 | A kind of user's habit record and recommended method in dining room |
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| Country | Link |
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| CN (1) | CN109544203A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110197399A (en) * | 2019-05-22 | 2019-09-03 | 苏州工业职业技术学院 | A kind of green tea-drinking guidance system |
| CN110648194A (en) * | 2019-08-22 | 2020-01-03 | 北京梧桐车联科技有限责任公司 | Processing method and device based on shopping in driving and storage medium |
| CN111275583A (en) * | 2020-01-20 | 2020-06-12 | 上海大学 | Service method based on face recognition and database |
| CN112182365A (en) * | 2020-09-11 | 2021-01-05 | 北京三快在线科技有限公司 | Recommendation information generation method and device, electronic equipment and storage medium |
| CN112598435A (en) * | 2020-12-14 | 2021-04-02 | 珠海格力电器股份有限公司 | Restaurant recommendation method and device, storage medium and electronic device |
| CN113255596A (en) * | 2021-06-29 | 2021-08-13 | 中运科技股份有限公司 | Intelligent video image analysis system and method based on big data |
| CN114730434A (en) * | 2020-02-10 | 2022-07-08 | 松下知识产权经营株式会社 | Control method, terminal device, program, and recording medium |
-
2018
- 2018-10-15 CN CN201811196569.4A patent/CN109544203A/en active Pending
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110197399A (en) * | 2019-05-22 | 2019-09-03 | 苏州工业职业技术学院 | A kind of green tea-drinking guidance system |
| CN110648194A (en) * | 2019-08-22 | 2020-01-03 | 北京梧桐车联科技有限责任公司 | Processing method and device based on shopping in driving and storage medium |
| CN111275583A (en) * | 2020-01-20 | 2020-06-12 | 上海大学 | Service method based on face recognition and database |
| CN114730434A (en) * | 2020-02-10 | 2022-07-08 | 松下知识产权经营株式会社 | Control method, terminal device, program, and recording medium |
| CN114730447A (en) * | 2020-02-10 | 2022-07-08 | 松下知识产权经营株式会社 | Information providing method |
| CN112182365A (en) * | 2020-09-11 | 2021-01-05 | 北京三快在线科技有限公司 | Recommendation information generation method and device, electronic equipment and storage medium |
| CN112598435A (en) * | 2020-12-14 | 2021-04-02 | 珠海格力电器股份有限公司 | Restaurant recommendation method and device, storage medium and electronic device |
| CN113255596A (en) * | 2021-06-29 | 2021-08-13 | 中运科技股份有限公司 | Intelligent video image analysis system and method based on big data |
| CN113255596B (en) * | 2021-06-29 | 2021-11-02 | 中运科技股份有限公司 | Intelligent video image analysis system and method based on big data |
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| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190329 |
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| WD01 | Invention patent application deemed withdrawn after publication |