CN111402519A - Campus dining system based on machine vision and cloud platform - Google Patents
Campus dining system based on machine vision and cloud platform Download PDFInfo
- Publication number
- CN111402519A CN111402519A CN202010163703.1A CN202010163703A CN111402519A CN 111402519 A CN111402519 A CN 111402519A CN 202010163703 A CN202010163703 A CN 202010163703A CN 111402519 A CN111402519 A CN 111402519A
- Authority
- CN
- China
- Prior art keywords
- meal
- module
- subsystem
- cloud platform
- face
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 235000012054 meals Nutrition 0.000 claims abstract description 92
- 235000011034 Rubus glaucus Nutrition 0.000 claims abstract description 30
- 235000009122 Rubus idaeus Nutrition 0.000 claims abstract description 30
- 240000007651 Rubus glaucus Species 0.000 claims abstract description 29
- 238000013500 data storage Methods 0.000 claims abstract 2
- 238000007726 management method Methods 0.000 claims abstract 2
- 230000000291 postprandial effect Effects 0.000 claims description 25
- 238000005303 weighing Methods 0.000 claims description 18
- 235000013305 food Nutrition 0.000 claims description 16
- 238000006243 chemical reaction Methods 0.000 claims description 13
- 238000005259 measurement Methods 0.000 abstract description 10
- 239000002699 waste material Substances 0.000 abstract description 7
- 230000001680 brushing effect Effects 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 7
- 235000020803 food preference Nutrition 0.000 description 5
- 230000008859 change Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 244000235659 Rubus idaeus Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
- G07G1/00—Cash registers
-
- 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
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
- G07G1/00—Cash registers
- G07G1/0009—Details of the software in the checkout register, electronic cash register [ECR] or point of sale terminal [POS]
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
- G07G1/00—Cash registers
- G07G1/0036—Checkout procedures
- G07G1/0045—Checkout procedures with a code reader for reading of an identifying code of the article to be registered, e.g. barcode reader or radio-frequency identity [RFID] reader
- G07G1/0054—Checkout procedures with a code reader for reading of an identifying code of the article to be registered, e.g. barcode reader or radio-frequency identity [RFID] reader with control of supplementary check-parameters, e.g. weight or number of articles
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
- G07G1/00—Cash registers
- G07G1/12—Cash registers electronically operated
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a campus meal system based on machine vision and a cloud platform, which comprises a meal purchasing subsystem, a meal ordering subsystem, a server and a cloud platform, wherein the meal purchasing subsystem comprises a raspberry serving main board, a meal item acquisition module, a face acquisition module, a quality measurement module, a voice broadcasting module and an L CD display module and is used for completing automatic identification, pricing and face brushing payment of purchased meal items and judging meal item collocation and quality measurement, the meal ordering subsystem comprises a raspberry serving main board, a meal item acquisition module, a face acquisition module, a quality measurement module, a voice broadcasting module and a L CD display module, the meal plate system is used for measuring the quality and judging whether waste or not when a meal plate is sent after meal, the server is used for services such as meal personnel information management, data storage, web service, account recharging and the like, and the cloud platform is used for realizing face identification.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a dining system, and specifically relates to a campus dining system based on machine vision and a cloud platform.
Background
In recent years, with the rapid development of machine vision technology and the rapid improvement of computing hardware such as graphics/image processors, more and more artificial intelligence technologies are applied and popularized. Raspberry pi, a card-style computer, was developed by the raspberry pi foundation registered in the uk, and was originally developed for the purpose of promoting computer education in poverty-stricken countries. With the continuous upgrading and upgrading of the raspberry pie, the performance is more and more powerful, and many of the work which can be completed only by a computer originally can be easily realized; moreover, the raspberry pie also has the characteristics of GPIO interface, convenience in carrying, low power consumption and the like, and is particularly suitable for research and development of products.
Along with the process of city modernization, most middle school students choose to have meals in school canteens and restaurants. At present, almost all school canteens and restaurants generally have the following phenomena: the dining time is quite centralized, the dining is crowded, and the time is wasted; food preference and waste of food.
Disclosure of Invention
Aiming at the common phenomena and even problems existing in campus dining, the invention aims to provide a campus dining system based on machine vision and a cloud platform, which can realize food identification, automatic price calculation, payment completion through face brushing, queuing time saving and labor saving; meanwhile, intelligent detection is assisted, and the problems of food preference and waste are solved. The system is simple to operate, convenient to use and high in reliability.
In order to achieve the purpose of the invention, the campus meal system based on machine vision and a cloud platform comprises a meal purchasing subsystem, a postprandial subsystem, a server and a cloud platform, wherein the meal purchasing subsystem is connected with the server and the cloud platform in a wired or wireless mode and is used for completing automatic identification, pricing and face brushing payment of meals purchased by diners and judging meal collocation and quality measurement, the postprandial subsystem is connected with the server and the cloud platform in a wired or wireless mode and is used for measuring the quality of meals sent by the diners and judging whether the meals are wasted, the meal purchasing subsystem comprises a raspberry serving mainboard, a meal collecting module, a face collecting module, a quality measuring module, a voice broadcasting module and a L CD display module, the meal collecting module is connected with the raspberry mainboard serving through a USB connecting wire, the face collecting module is connected with the serving mainboard via the USB connecting wire, the face collecting module is connected with the GPIO interface of the raspberry serving mainboard through the USB connecting wire, the quality measuring module is connected with the GPIO interface of the raspberry serving mainboard through the USB connecting wire, the face collecting module is connected with the CD playing mainboard through the USB connecting wire, the face collecting module is connected with the CD playing module through the USB connecting wire, the face collecting module is connected with the CD playing module through the USB connecting wire, the CD module, the CD playing module, the face collecting module, the CD playing module is connected with the CD playing module, the face collecting module, the CD playing module, the face collecting module is connected with the USB playing module through the USB interface of the raspberry serving mainboard, the USB playing module, the USB interface of the USB playing module.
Furthermore, the meal collection modules of the meal purchasing subsystem and the meal postprandial subsystem are high-definition (1920 x 1080), 75-degree cameras with USB interfaces.
Furthermore, the face collection modules of the meal purchasing subsystem and the meal postprandial subsystem are high-definition (1920 x 1080), 95-degree cameras with USB interfaces.
Furthermore, the mass measuring modules of the meal purchasing subsystem and the meal postprandial subsystem comprise a weighing sensor and an A/D conversion module, the weighing sensor is connected with a signal input end of the A/D conversion module, a signal output end of the A/D conversion module is connected with a signal input end of the raspberry pi main board, the A/D conversion chip is HX711, the weighing sensor is a cantilever beam type weighing sensor, and the maximum measuring range is 5 kg.
Further, the voice broadcasting modules of the meal purchasing subsystem and the meal ordering subsystem are BY 8301.
Further, the L CD display module of the meal purchasing subsystem and the meal postprandial subsystem is a 13.3-inch IPS touch display screen.
The invention has at least the following beneficial effects:
1. realizing the food identification and automatically calculating the price;
2. the face brushing payment is realized through the cloud platform;
3. identifying the type of the food, and judging whether the food is a food preference or not;
4. and judging whether the food is wasted or not according to the quality change of the food after the meal is purchased.
Drawings
Fig. 1 is a schematic general block diagram of a campus dining system based on machine vision and a cloud platform according to an embodiment of the present invention;
fig. 2 is a schematic diagram of the module structures of the meal purchasing subsystem and the postprandial subsystem according to the embodiment of the invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention will be further described in detail with reference to the accompanying drawings in the following embodiments of the invention. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
With reference to fig. 1 and 2, the campus meal system based on machine vision and a cloud platform comprises a meal purchasing subsystem, a postprandial subsystem, a server and a cloud platform, wherein the meal purchasing subsystem is connected with the server and the cloud platform in a wired or wireless mode and is used for completing automatic identification, pricing and face brushing payment of meals purchased by diners and judging meal collocation and quality measurement, the postprandial subsystem is connected with the server and the cloud platform in a wired or wireless mode and is used for measuring the quality of meals sent by the diners and judging whether the meals are wasted, the meal purchasing subsystem comprises a raspberry serving mainboard, a meal acquisition module, a face acquisition module, a quality measurement module, a voice broadcast module and a L CD display module, the meal acquisition module is connected with the raspberry mainboard serving through a USB connecting wire, the face acquisition module is connected with the raspberry serving mainboard through a USB connecting wire, the face acquisition module is connected with a GPIO interface of the raspberry serving mainboard through a USB connecting wire, the quality measurement module is connected with the GPIO of the raspberry serving mainboard through a USB connecting wire, the face acquisition module is connected with a GPIO interface of the raspberry serving mainboard through a USB connecting wire, the face acquisition module is connected with a USB interface of the raspberry serving mainboard, a USB connecting wire, a face acquisition module is connected with a CD storage module, a USB interface of the raspberry serving mainboard through a USB connecting wire, a USB interface of the raspberry serving mainboard, a USB interface of the raspberry serving server, a USB interface of the wired or a USB interface, a wired or a USB interface of the wired wiring, a wireless connection wire, a web server, a wired wiring, a face acquisition module, a wired wiring, a face acquisition module.
In this embodiment, fig. 2 is a schematic structural diagram of a module of the meal purchasing subsystem and the meal dining subsystem, wherein the meal collecting module is a camera with a USB interface, and is installed right above a meal plastic tray, a vertical distance between a lens of the camera and the plastic tray is about 50cm, and a viewing angle of the lens is 75 degrees, and the camera completely covers the periphery of the outer frame of the edge of the plastic dish, which is 15cm outward.
In this embodiment, fig. 2 is a schematic diagram of a module structure of a meal purchasing subsystem and a meal postprandial subsystem, wherein a face collecting module is a camera with a USB interface, and the camera is respectively installed right in front of the meal purchasing subsystem and the meal postprandial subsystem, when the meal purchasing subsystem and the meal postprandial subsystem are used, a vertical distance between the camera and the ground is about 160cm, so that a diner can look straight at the camera by raising the head when lowering a plastic tray to be settled or used for a meal, the face collection is facilitated, and the integrity of the face collection can be ensured when the lens viewing angle is 95 degrees.
In this embodiment, fig. 2 is a schematic diagram of a module structure of the purchasing subsystem and the postprandial subsystem, in which the mass measurement module is composed of a weighing sensor and an a/D conversion module, the mass measurement module is respectively installed on the bases of the purchasing subsystem and the postprandial subsystem, the weighing sensor is connected with a signal input end of the a/D conversion module, and a signal output end of the a/D conversion module is connected to a signal input end of the raspberry pi main board. The weighing sensor is a cantilever beam type weighing sensor, a weighing scale with the thickness of 20cm × 25cm and the thickness of 3mm is arranged on the surface right above the weighing sensor, and the weighing sensor is made of organic glass.
In this embodiment, fig. 2 is a schematic diagram of a module structure of the purchasing subsystem and the postprandial subsystem, in which the voice broadcasting module is composed of a BY8301 module and a speaker, the speaker can be respectively installed above the left side surface or the right side surface of the purchasing subsystem and the postprandial subsystem, the speaker is connected to a signal output end of the BY8301 module, and a signal control end of the BY8301 module is connected to a signal output end of the raspberry pi main board. Both the raspberry pi board and the BY8301 module can be mounted on the uppermost surface of the shopping subsystem and the post-meal subsystem.
In this embodiment, fig. 2 is a schematic diagram of a module structure of a meal purchasing subsystem and a meal postprandial subsystem, where the L CD display modules are all 13.3 inch IPS touch display screens, and are installed on the left side or the right side of the front of the meal purchasing subsystem and the meal postprandial subsystem, for example, the left side of the face capturing camera displays L CD for meal, and the right side of the face capturing camera displays L CD.
The implementation process of the campus dining system based on the machine vision and the cloud platform provided by the invention comprises the following steps:
1. initial preparation, ① establishing diner information base in the server, collecting the pictures of the diners and uploading to the cloud platform, establishing a face recognition comparison base, recharging the account of the diners, ② electrifying, respectively initializing the meal purchasing subsystem and the postprandial subsystem, and setting the unit price of the meal purchasing subsystem.
2. And paying for the purchased food. When a diner places a plastic tray containing the selected dinning articles on a tray of a quality measuring module of a ordering subsystem, the ordering subsystem starts a dinning article collecting module, the dinning article image is displayed on a display in real time, and the measured quality data is sent to a server for storage; the subsystem realizes meal identification, if no food preference condition is judged, settlement meal fees are generated, and voice reminding is performed for face brushing payment; and the face acquisition module uploads the pictures to the cloud platform, meanwhile, the face images are displayed on a display in real time, and if the comparison is successful, the meal fee is paid from the account of the related meal staff of the server.
3. And (5) returning to the dish after meals. After the meal is finished, the diner needs to place the plastic tray of the diner's own meal on the tray of the quality determination module of the postprandial subsystem, the postprandial subsystem starts the face acquisition module, uploads pictures to the cloud platform, simultaneously displays the face image in real time, and the server finds the account of the diner according to the face recognition result; starting a food acquisition module, and taking a picture of the food and uploading the picture to a server for storage; the quality measuring module compares the measured quality data with the measured quality during the meal purchase, judges whether the waste condition exists or not, and gives an alarm in a voice mode if the waste condition exists.
The raspberry group mainboard is used as a management center of a meal purchasing subsystem and a meal postprandial subsystem respectively, on one hand, the raspberry group mainboard is used for controlling and coordinately managing a meal acquisition module, a face acquisition module, a quality measurement module, a voice broadcast module and an L CD display module, on the other hand, various data are analyzed, operated and processed, on the basis of which, meal identification results, face identification results and discrimination results of food preference and waste are provided, and further, automatic checkout, related voice reminding or warning of meals are realized.
The quality measuring module is mainly used for measuring the quality of the plastic tray for containing food, and judging whether waste exists or not by calculating the change of the quality after meal purchase and meal. The mass measuring module consists of a weighing sensor and an A/D conversion module, the weighing sensor is a cantilever beam type weighing sensor, in particular to a resistance strain type pressure sensor, and has the characteristics of good stability, high sensitivity, long service life and the like, the electric sensitivity is 2mv/v, and the total error value is not more than 0.02%. The model of the A/D conversion module chip is HX711, and a 24-bit A/D converter chip developed by sea-core technology for high-precision electronic scales is internally provided with gain control and has the characteristics of quick response, high precision, strong interference resistance and low requirement on use environment.
The BY8301 is a small novel high-quality MP3 module, supports MP3 and WAV double-format files, is internally provided with an SPI-F L ASH memory and is provided with a micro USB interface, can freely change the audio content of the F L ASH BY directly connecting a computer through a data line without upper computer software, supports the operations of voice playing, pausing, song loading and unloading, song selection, volume increasing and decreasing and the like through a standard UART serial port, is provided with a 3W power amplifier, has 30-level volume adjustment and has working voltage of 3.6V-5.0V.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (6)
1. A campus dining system based on machine vision and a cloud platform is characterized in that: the system comprises a meal purchasing subsystem, a meal post-serving subsystem, a server and a cloud platform;
the food purchasing subsystem comprises a raspberry pie main board, a food collecting module, a face collecting module, a quality measuring module, a voice broadcasting module and an L CD display module;
the postprandial subsystem comprises a raspberry pie main board, a meal collection module, a face collection module, a quality determination module, a voice broadcast module and an L CD display module;
the server is used for diner information management, data storage, web service, account recharging and other services;
the cloud platform is used for realizing face recognition;
the meal purchasing subsystem is connected with the server and the cloud platform in a wired or wireless mode; the postprandial subsystem is connected with the server and the cloud platform in a wired or wireless mode.
2. The machine-vision and cloud-platform-based campus dining system of claim 1, wherein: the food acquisition modules of the food purchasing subsystem and the food post-meal subsystem are high-definition (1920 x 1080), 75-degree cameras with USB interfaces.
3. The machine-vision and cloud-platform-based campus dining system of claim 2, wherein: the face acquisition modules of the meal purchasing subsystem and the meal postprandial subsystem are high-definition (1920 x 1080), 95-degree cameras with USB interfaces.
4. The machine-vision and cloud-platform-based campus dining system of claim 3, wherein: the mass measuring modules of the meal purchasing subsystem and the meal subsystem comprise a weighing sensor and an A/D conversion module, the weighing sensor is connected with a signal input end of the A/D conversion module, a signal output end of the A/D conversion module is connected with a signal input end of the raspberry pi main board, the A/D conversion chip is HX711, the weighing sensor is a cantilever beam type weighing sensor, and the maximum measuring range is 5 kg.
5. The machine-vision and cloud-platform-based campus dining system of claim 4, wherein: the voice broadcast module of the meal purchasing subsystem and the meal sub-system is BY 8301.
6. The campus dining system based on machine vision and cloud platform as claimed in claim 5, wherein L CD display module of said meal purchasing subsystem and said meal ordering subsystem is 13.3 inch IPS touch screen.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010163703.1A CN111402519A (en) | 2020-03-10 | 2020-03-10 | Campus dining system based on machine vision and cloud platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010163703.1A CN111402519A (en) | 2020-03-10 | 2020-03-10 | Campus dining system based on machine vision and cloud platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111402519A true CN111402519A (en) | 2020-07-10 |
Family
ID=71432334
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010163703.1A Pending CN111402519A (en) | 2020-03-10 | 2020-03-10 | Campus dining system based on machine vision and cloud platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111402519A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112906513A (en) * | 2021-02-03 | 2021-06-04 | 拉扎斯网络科技（上海）有限公司 | Dining resource information processing method, device and equipment |
-
2020
- 2020-03-10 CN CN202010163703.1A patent/CN111402519A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112906513A (en) * | 2021-02-03 | 2021-06-04 | 拉扎斯网络科技（上海）有限公司 | Dining resource information processing method, device and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2022111059A1 (en) | Intelligent weighing apparatus based on computer vision technology, and intelligent weighing method | |
| US9727838B2 (en) | On-shelf tracking system | |
| CN104361698A (en) | Self-service intelligent electronic weighing settlement method and system | |
| US10948338B2 (en) | Digital product label generation using modular scale device | |
| CN112464697B (en) | Visual and gravity sensing based commodity and customer matching method and device | |
| CN109064630A (en) | Nobody weigh automatically valuation container system | |
| WO2019080674A1 (en) | Self-service checkout device, method, apparatus, medium and electronic device | |
| US20190244282A1 (en) | Computerized exchange network | |
| CN110942293A (en) | Article information processing method, device, storage medium and system | |
| CN111402519A (en) | Campus dining system based on machine vision and cloud platform | |
| CN109584479A (en) | Meal platform and system are sold in the self-service weighing of one kind | |
| CN108171502A (en) | A kind of small micro- unattended self-service vending system based on commodity image identification | |
| CN114078299A (en) | Commodity settlement method, commodity settlement device, electronic equipment and medium | |
| CN107491786B (en) | Automatic visual detection and identification method for repeated weighing behaviors of tobacco purchase | |
| CN218496241U (en) | Intelligent goods detection device | |
| CN212724252U (en) | PC scale capable of automatically identifying articles | |
| CN110706427A (en) | Intelligent network weighing, settling and dish serving device | |
| CN109584480A (en) | Meal platform and system are sold in the self-service weighing of one kind | |
| US20210272174A1 (en) | Goods purchase analysis assist system | |
| CN211555065U (en) | Intelligent network weighing, settling and dish serving device | |
| CN210666865U (en) | Digital electronic shopping guide system of intelligence AI | |
| CN209265612U (en) | Meal platform and system are sold in the self-service weighing of one kind | |
| CN102135442A (en) | Voice type object flow management auxiliary system | |
| CN109360329A (en) | A kind of interaction screen system based on gravity sensor | |
| CN100417364C (en) | Portable supersonic body height measuring device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20200710 |