CN111680964A - Real-time class attendance checking method and system - Google Patents
Real-time class attendance checking method and system Download PDFInfo
- Publication number
- CN111680964A CN111680964A CN202010402926.9A CN202010402926A CN111680964A CN 111680964 A CN111680964 A CN 111680964A CN 202010402926 A CN202010402926 A CN 202010402926A CN 111680964 A CN111680964 A CN 111680964A
- Authority
- CN
- China
- Prior art keywords
- attendance
- information
- real
- classroom
- class
- 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
Images
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
- G06Q10/1091—Recording time for administrative or management purposes
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Educational Technology (AREA)
- Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- General Health & Medical Sciences (AREA)
- Economics (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Multimedia (AREA)
- Human Computer Interaction (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a real-time class attendance method and a real-time class attendance system, which comprise the following steps: creating an attendance table; reading attendance information in an attendance table; according to the real-time class attendance method, the attendance of students in a classroom is performed according to the attendance information in the attendance table, the attendance efficiency is high, the occupation of class time is reduced, the attendance accuracy is high, and the student congestion is avoided.
Description
Technical Field
The invention relates to the technical field of classroom attendance systems, in particular to a classroom real-time attendance method and a classroom real-time attendance system.
Background
With the release of the national standard "overall framework of smart campus", the planning and design of smart campus becomes a key project for campus construction. The classroom attendance is an important component of school teaching management and student evaluation, and along with the improvement and development of the level of the internet of things technology, artificial intelligence and mobile communication technology, the classroom attendance is more developed towards intellectualization and accuracy.
At present, two main class attendance modes in a campus exist, namely a traditional attendance mode and a biological identification attendance mode. The traditional attendance checking mode comprises roll attendance checking and attendance checking through a campus card, the roll attendance checking mode is still the most common attendance checking means in colleges and universities, and the roll attendance checking mode is not limited by sites and can directly check on-site student information according to a roll book. The campus card attendance solves the problem that roll calling takes classroom time, but the mode has the loophole of student attendance checking because students can take the campus card of others to check attendance. Biological identification's attendance mode includes fingerprint attendance and face identification attendance, and these modes have effectively solved the drawback that traditional attendance mode was instead of attendance, but this kind of mode receives equipment hardware's influence, and the identification ability is too slow, and is especially after class the student more, and the attendance signs and moves back and takes place phenomenon such as crowding easily, has the potential safety hazard consequently.
Disclosure of Invention
In view of the above, the present invention is directed to a real-time class attendance method and system, which solve all or one of the problems in the background art.
Based on the purpose, the invention provides a real-time class attendance method, which comprises the following steps:
creating an attendance table;
reading attendance information in an attendance table;
and checking attendance according to the attendance information to obtain an attendance result.
Optionally, the reading of the attendance information in the attendance table includes:
and reading a student-class relation table, a class-course relation table, student information, class information and course information in the attendance table.
Optionally, attendance is performed according to the attendance information, and the attendance result obtaining includes:
acquiring face information in a classroom;
and comparing the attendance information with the face information to obtain an attendance result.
Optionally, the acquiring the face information in the classroom includes:
collecting a face photo in a classroom;
and identifying student information corresponding to the face photos.
Optionally, the obtaining of the face information in the classroom is realized based on a deep learning convolutional neural network.
A real-time class attendance system comprises:
the creation module is used for creating an attendance table;
the reading module is used for reading attendance information in the attendance meter;
and the attendance module is used for checking attendance according to the attendance information to obtain an attendance result.
Optionally, the attendance module includes:
the acquisition unit is used for acquiring the face information in the classroom;
and the comparison unit is used for comparing the attendance information with the face information to obtain an attendance result.
Optionally, the obtaining unit includes:
the acquisition subunit is used for acquiring a face photo in the classroom;
and the identification subunit is used for identifying the student information corresponding to the face picture.
From the above, the real-time class attendance method and system provided by the invention have the advantages that the attendance of students in a classroom is carried out according to the attendance information in the attendance table, the attendance efficiency is high, the occupation of class time is reduced, the attendance accuracy is high, and the student congestion is avoided.
Drawings
In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only one or more embodiments of the present specification, and that other drawings may be obtained by those skilled in the art without inventive effort from these drawings.
FIG. 1 is a schematic flow chart of real-time class attendance of the present invention;
fig. 2 is a schematic flow chart of the invention for checking attendance according to attendance information to obtain an attendance result;
FIG. 3 is a schematic view of a process for acquiring face information in a classroom according to the present invention;
fig. 4 is a schematic structural diagram of the real-time class attendance system of the invention;
fig. 5 is a schematic structural diagram of the attendance checking module of the invention;
fig. 6 is a schematic structural diagram of an acquisition unit according to the present invention.
100, creating a module; 200. a reading module; 300. an attendance module; 310. an acquisition unit; 320. a comparison unit; 311. a collecting subunit; 312. a subunit is identified.
Detailed Description
To make the objects, technical solutions and advantages of the present disclosure more apparent, the present disclosure is further described in detail below with reference to specific embodiments.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in one or more embodiments of the specification is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
The invention provides a real-time class attendance method, which comprises the following steps:
s100, creating an attendance table.
The user establishes an attendance table in the database, wherein the information of the attendance table can comprise course information, student information, class time, classroom and the like.
And S200, reading attendance information in the attendance table.
The attendance list comprises related attendance information, after a user creates the attendance list, the system reads the information contained in the attendance list, the attendance information can comprise class time information, and when the preset class time is reached, attendance checking is started.
And S300, checking attendance according to the attendance information to obtain an attendance result.
The attendance information comprises student information, students in the classroom are subjected to attendance judgment one by one according to the student information, and attendance data are stored in the database, so that the attendance information can be conveniently checked by a background.
For example, attendance can be performed at the time points of the beginning and the ending of a course, and meanwhile, a plurality of time points can be randomly selected from the course for attendance, so that the attendance result of students can be accurately obtained, and the inaccurate attendance result caused by the fact that the students leave the course midway is avoided.
In conclusion, the real-time class attendance method disclosed by the invention has the advantages that the attendance of students in a classroom is carried out according to the attendance information in the attendance table, the attendance efficiency is high, the occupation of class time is reduced, the attendance accuracy is high, and the student congestion is avoided.
In some optional embodiments, the step S200 includes:
and reading a student-class relation table, a class-course relation table, student information, class information and course information in the attendance table.
The attendance table can comprise a student-class relation table, a class-course relation table, student information, class information and course information, each class is provided with a plurality of different students, the student information corresponds to the class information, the course arrangement information of each class is independent, the course information corresponds to the class information, the student information comprises names, photos, student cards, contact ways and other information of the students, the class information can comprise information of teachers in any class, instructors, affiliated colleges and the like, and the course information can comprise time information of the courses, teachers in any class, places, classes and the like.
In some optional embodiments, the step S300 includes:
s310, obtaining face information in the classroom.
The face information of the students in the classroom is acquired, and the face photos of the students can be acquired by adopting a camera.
And S320, comparing the attendance information with the face information to obtain an attendance result.
The attendance information comprises information of corresponding students, the acquired face information is compared with the attendance information one by one, whether the face information is matched with the attendance information or not is judged, if all the students arrive, the acquired face information is matched with the attendance information, and if part of the students are absent, the information of the absent students in the attendance information cannot be matched with the acquired face information.
In some optional embodiments, the acquiring the face information in the classroom includes:
s311, acquiring a human face photo in the classroom.
The camera is used for collecting the face photos in the classroom, for example, the face photos can be collected for multiple times, and the photos which are most easily recognized are selected for recognition.
And S312, identifying student information corresponding to the face photos.
According to the collected face photo, the student information corresponding to the photo is identified, so that the face photo and the student information in the attendance table can be conveniently compared one by one.
In some optional embodiments, the obtaining of the face information in the classroom is implemented based on a deep learning convolutional neural network.
Corresponding to the embodiment of the method, the invention also provides a real-time class attendance system, which comprises:
the creation module 100 is used for creating an attendance table;
the reading module 200 is used for reading attendance information in the attendance table;
and the attendance module 300 is used for checking attendance according to the attendance information to obtain an attendance result.
For example, the system can adopt Python development language, the Python is mainly applied to the fields of Web service design, big data, artificial intelligence and the like, the system has the main advantages of high development efficiency, strong expandability, cross-platform, portability and the like, and the design requirements of the system are met. In addition, a third-party software development kit based on Python is used in the development process, and the third-party software development kit comprises a flash used for building a Web server of the system; PyQt5 is used to build the client of the system; OpenCV is used for processing image videos in the system; tensoflow is used for developing a computer vision model, building a deep learning model and completing human face detection and recognition tasks; mysqlclient is used to manage, access, query and update Mysql databases.
For example, the system can be provided with a model layer, a controller layer, a view layer and a network communication layer, wherein the model layer is mainly a database of the system and is used for storing and updating attendance information.
The controller layer mainly comprises server application software and a target detection and identification model, and the functions of the server application software comprise system communication configuration, data service processing and scheduling among all the modules of the system. The target detection and identification model is a core module of the real-time class attendance system, is realized based on a deep learning convolutional neural network, and mainly has the functions of face detection and face identification. Whether students are absent from the class is identified through detection.
The view layer mainly comprises an image acquisition system and a client, wherein monitoring equipment in a classroom is used as the image acquisition system, the client is designed by adopting an application program interface, then a graphical user interface is designed in a teaching management system, and the functions of the system are called through the application program interface.
The network communication layer mainly comprises a communication unit used for storing data, uploading cloud data, regulating and controlling a background and the like.
In some optional embodiments, the attendance module 300 includes:
an acquisition unit 310, configured to acquire face information in a classroom;
and the comparison unit 320 is configured to compare the attendance information with the face information to obtain an attendance result.
In some optional embodiments, the obtaining unit 310 includes:
the collecting subunit 311 is used for collecting the face photos in the classroom;
and the identifying subunit 312 is configured to identify student information corresponding to the face picture.
It should be noted that the method of one or more embodiments of the present disclosure may be performed by a single device, such as a computer or server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the devices may perform only one or more steps of the method of one or more embodiments of the present disclosure, and the devices may interact with each other to complete the method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the modules may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
The apparatus of the foregoing embodiment is used to implement the corresponding method in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the spirit of the present disclosure, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present description as described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures, for simplicity of illustration and discussion, and so as not to obscure one or more embodiments of the disclosure. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the understanding of one or more embodiments of the present description, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the one or more embodiments of the present description are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that one or more embodiments of the disclosure can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of one or more embodiments of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (8)
1. A real-time class attendance method is characterized by comprising the following steps:
creating an attendance table;
reading attendance information in an attendance table;
and checking attendance according to the attendance information to obtain an attendance result.
2. The real-time class attendance method of claim 1, wherein the reading of the attendance information in the attendance table comprises:
and reading a student-class relation table, a class-course relation table, student information, class information and course information in the attendance table.
3. The real-time class attendance method of claim 2, wherein the attendance is performed according to the attendance information, and the obtaining of the attendance result comprises:
acquiring face information in a classroom;
and comparing the attendance information with the face information to obtain an attendance result.
4. The real-time class attendance method of claim 3, wherein the acquiring of the face information in the classroom comprises:
collecting a face photo in a classroom;
and identifying student information corresponding to the face photos.
5. The real-time class attendance method of claim 3, wherein the obtaining of the face information in the classroom is implemented based on a deep learning convolutional neural network.
6. The utility model provides a real-time attendance system in classroom which characterized in that includes:
the system comprises a creating module (100) used for creating an attendance table;
the reading module (200) is used for reading attendance information in the attendance table;
and the attendance module (300) is used for checking attendance according to the attendance information to obtain an attendance result.
7. The real-time class attendance system of claim 6, wherein the attendance module (300) comprises:
an acquisition unit (310) for acquiring face information in a classroom;
and the comparison unit (320) is used for comparing the attendance information with the face information to obtain an attendance result.
8. The classroom real-time attendance system as claimed in claim 7, wherein the acquiring unit (310) comprises:
the acquisition subunit (311) is used for acquiring a face photo in a classroom;
and the identification subunit (312) is used for identifying the student information corresponding to the face picture.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010402926.9A CN111680964A (en) | 2020-05-13 | 2020-05-13 | Real-time class attendance checking method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010402926.9A CN111680964A (en) | 2020-05-13 | 2020-05-13 | Real-time class attendance checking method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111680964A true CN111680964A (en) | 2020-09-18 |
Family
ID=72433960
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010402926.9A Pending CN111680964A (en) | 2020-05-13 | 2020-05-13 | Real-time class attendance checking method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111680964A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112395950A (en) * | 2020-10-22 | 2021-02-23 | 浙江蓝鸽科技有限公司 | Classroom intelligent attendance checking method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109598809A (en) * | 2018-12-05 | 2019-04-09 | 上海创视通软件技术有限公司 | A kind of check class attendance method and system based on recognition of face |
| CN110033403A (en) * | 2019-04-22 | 2019-07-19 | 重庆工商职业学院 | A kind of unaware check class attendance method and system |
-
2020
- 2020-05-13 CN CN202010402926.9A patent/CN111680964A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109598809A (en) * | 2018-12-05 | 2019-04-09 | 上海创视通软件技术有限公司 | A kind of check class attendance method and system based on recognition of face |
| CN110033403A (en) * | 2019-04-22 | 2019-07-19 | 重庆工商职业学院 | A kind of unaware check class attendance method and system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112395950A (en) * | 2020-10-22 | 2021-02-23 | 浙江蓝鸽科技有限公司 | Classroom intelligent attendance checking method and system |
| CN112395950B (en) * | 2020-10-22 | 2023-12-19 | 浙江蓝鸽科技有限公司 | Classroom intelligent attendance checking method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108347490A (en) | A kind of campus application apparatus and system based on biological identification technology | |
| CN110162599A (en) | Personnel recruitment and interview method, apparatus and computer readable storage medium | |
| CN111238466A (en) | Indoor navigation method, device, medium and terminal equipment | |
| CN108765610A (en) | Attendance management method for work transmission line scene | |
| CN111382633A (en) | Classroom attendance management method, device, terminal and computer readable storage medium | |
| CN111814587A (en) | Human behavior detection method, teacher behavior detection method, and related system and device | |
| CN111382655A (en) | Hand-lifting behavior identification method and device and electronic equipment | |
| CN111598899A (en) | Image processing method, image processing apparatus, and computer-readable storage medium | |
| CN113920540A (en) | Knowledge distillation-based pedestrian re-identification method, device, equipment and storage medium | |
| CN111680964A (en) | Real-time class attendance checking method and system | |
| Al-Muhaidhri et al. | Smart attendance system using face recognition | |
| CN110378261B (en) | Student identification method and device | |
| CN111639879A (en) | Intelligent security personnel information management method, device and system, storage medium and server | |
| CN107945353B (en) | Self-service tour guide system based on deep learning | |
| CN213072720U (en) | Intelligent classroom course arrangement and distribution system | |
| CN111738884A (en) | Student behavior diagnosis and management method based on intelligent campus student position information | |
| CN113824874A (en) | Auxiliary shooting method and device, electronic equipment and storage medium | |
| Abdalkarim et al. | A Literature Review on Smart Attendance Systems | |
| CN113850196A (en) | Conference monitoring device, conference monitoring equipment and conference monitoring storage medium based on artificial intelligence | |
| CN208112665U (en) | A kind of campus application apparatus based on biological identification technology | |
| CN113807150A (en) | Data processing method, attitude prediction method, data processing device, attitude prediction device, and storage medium | |
| CN110765953A (en) | Multimedia teaching teacher sign-in monitoring method and system | |
| Babatunde et al. | Mobile Based Student Attendance System Using Geo-Fencing With Timing and Face Recognition | |
| Himel et al. | Face-App: A real-time face recognition e-attendance system for digital learning | |
| CN111860357B (en) | Attendance rate calculating method and device based on living body identification, terminal and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200918 |