A whole-process intelligent management and display system for labor education practice

Abstract

The application relates to a full-process intelligent management and display system for labor education practice, which comprises a mobile phone APP end and a PC end; the mobile phone APP end comprises: a labor practice activity module for processing related businesses of a labor education course; a lost and found module for realizing lost and found and a search notice, and performing information publishing and keyword searching; a personal panel module for displaying and processing personal information and part of associated data for users; an interactive function module for realizing a like, comment and collection function; the PC end comprises: a background management subsystem for realizing management of user information, health areas, tasks and activities; a visual display subsystem for visually displaying a campus health condition and a three-dimensional map of the whole campus, and marking a position with an unqualified health condition on the map in a point marking mode. Compared with the prior art, the application has the advantages of intelligent management efficiency, clear visual display, simple operation and easy maintenance.

Description

TECHNICAL FIELD

[0001] The present application relates to an information management system, in particular to a full-process intelligent management and display system for labor education practice. BACKGROUND

[0002] Labor education and education digitization are major events in China that are being comprehensively strengthened and vigorously promoted. To build an education system that comprehensively cultivates morality, intelligence, body, and labor, major universities actively carry out labor education activities, set up labor education courses, and integrate them into talent training programs, forming a labor education curriculum system that is comprehensive, practical, open, and targeted. Through research, it was found that there were three systemic problems in the early stages of course offering: (1) inconvenient management: labor education courses have various forms, but most of the work is manually managed, lacking intelligent software and digital information management; (2) lack of display: there is no instant display platform, and information is displayed through offline or online communication software, lacking intelligent software for unified display; (3) inconvenient practice achievement acceptance: there is no unified acceptance portal and no effective achievement evaluation system. However, there are currently no related intelligent management and display products on the market that can effectively solve these problems.

[0003] To respond to the call of the state and the school, and actively integrate software development technology into the management of labor education, we can use wisdom and efficiency to manage labor education practice. For some labor education practice projects carried out by schools, to address the problems of inconvenient management, lack of display, and inconvenient practice achievement acceptance, we can use relevant software development technology and digital visualization technology to invent a full-process intelligent management and display system for labor education practice to empower the management innovation of labor education practice and become a technical problem that needs to be solved. SUMMARY

[0004] The purpose of the present application is to overcome the shortcomings of the prior art and provide a full-process intelligent management and display system for labor education practice.

[0005] The purpose of the present application can be achieved through the following technical solutions:

[0006] According to one aspect of the present application, a full-process intelligent management and display system for labor education practice is provided, including a mobile phone APP end and a PC end.

[0007] The mobile phone APP end includes:

[0008] A labor practice activity module for processing related business of labor education courses;

[0009] A lost and found module for implementing lost and found and search notices, and information publishing and keyword search;

[0010] Personal panel module, for displaying and processing personal information and part of the associated data to the user;

[0011] Interactive function module, for realizing the functions of like, comment and collection;

[0012] The PC terminal comprises:

[0013] Background management subsystem, for realizing user information management, health area management, task management and activity management;

[0014] Visual display subsystem, for visually displaying the campus health condition and the three-dimensional map of the whole campus, and marking the position of unqualified health condition on the map in the form of points.

[0015] As a preferred technical solution, the user information management is used for adding, deleting, modifying and inquiring the college, class, student number and name information of the user.

[0016] As a preferred technical solution, the health area management is used for adding, deleting, modifying and inquiring the building and classroom information required to be cleaned and inspected.

[0017] As a preferred technical solution, the task management comprises a cleaning task management submodule and an inspection task management submodule.

[0018] As a preferred technical solution, the cleaning task management submodule adopts a classroom-class cleaning task matching algorithm, which uses the greedy algorithm idea to locally find the optimal solution, i.e. the class with the most class times in each classroom is taken as the local optimal solution, and the global optimal solution is formed by summarizing.

[0019] As a preferred technical solution, the specific process of the classroom-class cleaning task matching algorithm is as follows:

[0020] Step 1: Construct a classroom-class-class time table;

[0021] Step 1.1: Obtain the site timetable excel file, and read the classroom-class class-related information from the excel file to construct a classroom-class matching table;

[0022] Step 1.2: Extract the class times of each class in the corresponding classroom, and generate a classroom-class-class time table R-C-N=<classroom, class, class time> in descending order of class times; if the table is empty, the algorithm ends, otherwise go to step 1;

[0023] Step 2: Perform the first round of classroom-class cleaning task matching to generate an optimal matching table and a pending list;

[0024] Step 2.1 For each classroom, use a greedy strategy to obtain the class with the maximum number of lessons in the classroom-class-lesson table R-C-N, and store it in the R-C-Nmax = <classroom, class, maximum number of lessons> list; if the maximum number of lessons of a classroom is greater than 0, assign the task of cleaning the classroom to the class with the maximum number of lessons in that classroom, if there are multiple different classes with the maximum number of lessons in that classroom, randomly select one class from these classes with the same maximum number of lessons to assign to the classroom, mark the classroom and class as matched, and store the matched classroom-class in the optimal matching table OptimalMatching = <classroom, class, maximum number of lessons>; at the same time, if the marked class exists in other unmarked classrooms in the R-C-Nmax table, delete the class and update the maximum number of lessons of the classroom and its corresponding class;

[0025] Step 2.2 Take the difference set of table OptimalMatching from table R-C-N, and store it in the pending list PendingList = <classroom, class, number of lessons>;

[0026] Step 2.3 If the pending list PendingList is empty, the algorithm ends, otherwise go to step 3;

[0027] Step 3: Perform the second round of classroom-class cleaning task matching, and generate a suboptimal matching table;

[0028] Step 3.1 According to the distribution of school areas, disciplines and professional buildings, set up a mapping table between the area (A), class (C), building (B) and classroom list (RL), map the class (C) through the area (A), and the mapping relationship is recorded as A = f(C); map the area (A) through the building (B), and the mapping relationship is recorded as B = f(A); map the building (B) through the classroom list (RL), and the mapping relationship is recorded as RL = f(B); map the classroom list (RL) through the classroom (R), and the mapping relationship is recorded as R = random(RL);

[0029] Step 3.2 Match the class (C) in the pending list PendingList to the classroom R through the mapping relationship constructed in the previous step, and store it in the suboptimal matching table SuboptimalMatching = <classroom, class, number of lessons>;

[0030] Step 4: Summarize and generate a classroom-class cleaning task matching table;

[0031] The optimal matching table generated in step 2 and the suboptimal matching table generated in step 3 are summarized to generate a classroom-class cleaning task matching table and output.

[0032] As a preferred technical solution, the inspection task management submodule adopts an inspection task optimal allocation algorithm to realize semi-autonomous selection and automatic allocation of inspection tasks.

[0033] As a preferred technical solution, the inspection task optimal allocation algorithm has the following specific process:

[0034] Step 1: Initialize algorithm-related parameters, including setting the number of classrooms to be inspected by a single inspector checkCount and setting the inspection date range checkDate;

[0035] Step 2: Obtain the table of all buildings to be cleaned, denoted as roomList = <Building, List, roomCount>, where the table item Building represents a building, the table item List represents a list of classrooms, and the table item roomCount represents the number of classrooms to be inspected;

[0036] Step 3: Build a selected task and generate a building selected task table denoted as B-T = <Building, Task>, where the table item Building represents a building and the table item Task represents a selected task table stored in an array. For each Building in the roomList table, compare its roomCount with checkCount and generate the building selected task table B-T according to the following conditions:

[0037] Step 3.1 If the roomCount of a certain Building is less than or equal to checkCount, set the number of inspection tasks for that building limit to 1 and add the roomCount to the selected task table Task to generate the B-T item and store it in the B-T table;

[0038] Step 3.2 If roomCount > checkCount, set remainder = roomCount % checkCount and Set the length of the array Task to limit, and each item in the array has a value of checkCount;

[0039] Step 3.2.1 If remainder >= limit, make the following judgment: if Then, the value of each item in Task is added by remainder / limit, and remainder%limit items in Task are randomly selected and added by 1 respectively, to generate B-T items and add them to B-T table; if Then, the length of array Task is set to limit+1, and the item is set to remainder, and B-T items are generated and stored in B-T table;

[0040] Step 3.2.2 If remainder<limit, randomly select remainder positions in Task table, and add 1 to the value of each item in the corresponding position respectively, to generate B-T items and store them in B-T table;

[0041] Step 4: Construct the inspection task, generate the inspection task table, denoted as B-D-C=<Building, Date, CheckRoom>, wherein the table item Building represents the building, the table item Date represents the inspection date, and the table item CheckRoom represents the inspection classroom table;

[0042] Step 4.1 For each inspector, voluntarily select the inspection date Date from the selectable inspection date range, and select the building Building from the B-T table;

[0043] Step 4.2 According to the mapping relationship in the B-T table, the system automatically randomly allocates one table item in array Task to the inspector, and the value in the table item is used as the table length of the inspection classroom table of the inspector;

[0044] Step 4.3 Match the selected building Building in roomList, and select value adjacent classrooms from the classroom list List corresponding to Building to generate the inspection classroom table CheckRoom, thereby generating the inspection task table B-D-C.

[0045] As a preferred technical solution, the activity management includes an activity information auditing submodule and an activity project acceptance management submodule.

[0046] As a preferred technical solution, the visual display subsystem adopts Echarts visualization technology and Gaode map SDK to visually display data.

[0047] As a preferred technical solution, the system further includes a database subsystem, which designs corresponding entity classes according to the object-oriented idea, generates corresponding database tables from the entity classes, and reflects the relationship between objects through the relationship between data tables; wherein the database logical structure design is based on the E-R diagram of the database.

[0048] Compared with the prior art, the application adopts front and rear end separation development mode, has low coupling degree and high maintainability, the rear end is developed based on serverless platform light service, can realize zero operation and maintenance, can be elastically expanded in performance, greatly meets the operation and maintenance and server performance needs of product; has excellent characteristics of intelligent management efficiency, visual display clarity, simple operation, easy maintenance, safety and reliability and the like. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 It is system architecture diagram of the application;

[0050] Figure 2 It is structure schematic view of the system of the application;

[0051] Figure 3 It is system E-R diagram of the database subsystem of the application;

[0052] Figure 4 It is schematic view of the inspector information management interface of the application;

[0053] Figure 5 It is schematic view of the health area management interface of the application;

[0054] Figure 6 It is schematic view of the visual display interface of the application;

[0055] Figure 7 It is classroom-class cleaning task matching algorithm flow chart of the application;

[0056] Figure 8 It is optimal allocation algorithm flow chart of the inspection task of the application;

[0057] Figure 9 It is schematic view of the mobile phone APP end publishing function module of the application;

[0058] Figure 10 It is schematic view of the mobile phone APP end activity page creation of the application;

[0059] Figure 11 It is schematic view of the mobile phone APP end health inspection publishing page of the application;

[0060] Figure 12 It is schematic view of the mobile phone APP end home page of the application.

[0061] Figure 13 It is schematic view of the mobile phone APP end interaction function related interface of the application. DETAILED DESCRIPTION

[0062] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the protection scope of the present application.

[0063] The whole-process intelligent management and display system for labor education practice designed and implemented by the present application is provided with a mobile phone APP end and a PC end. The mobile phone APP end mainly has a labor practice activity module, a lost and found module, a personal panel module, and an interactive function module. The PC end can be divided into a background management and a visual display two subsystems and corresponding functions of each subsystem. The present application is based on a Serverless development platform, adopts the current mainstream framework, including Express, Vue and Uni-App front-end and back-end framework and Apache Echarts, MongoDB and Redis technology, and has the advantages of intelligent management efficiency, visual display clarity, simple operation, easy maintenance, safety and reliability.

[0064] 1. System architecture design

[0065] As shown in Figure 1 , the whole-process intelligent management and display system for labor education practice of the present application is based on a light service platform, uses the Express framework to build the back-end, uses the Vue, Echarts and Uni-App technology to build the front-end, and calls the MongoDB, Redis integrated by the light service platform for data storage and caching. The system adopts a front-end and back-end separation development mode, and the two ends communicate through the HTTPS protocol.

[0066] 2. System function design

[0067] As shown in Figure 2 , the function design of the whole-process intelligent management and display system for labor education practice of the present application is divided into a PC end and a mobile phone APP end, and the two ends complement each other and jointly complete the functions of the whole-process intelligent management and display system for labor education practice.

[0068] The APP of mobile phone is mainly for teachers and students, which is divided into four function modules, namely, the module of labor practice activities, the module of lost and found, the module of personal panel, and the module of interactive function. Among them, the module of labor practice activities is responsible for handling the related business of labor education courses, including the functions of health cleaning inspection and supervision, labor education activities, and credit settlement. The function of health cleaning inspection and supervision is designed for the campus health labor education practice project, which abstracts the project into three behaviors of cleaning, inspection, and supervision, and designs the functions around them. The function of labor education activities abstracts the process of ordinary labor education practice activities into six steps of activity publishing, auditing, signing up, activity check-in, project completion, and credit settlement, and combines the system to realize digital and intelligent management. The module of lost and found mainly includes two businesses of lost and found and missing notice, which can realize the functions of information publishing and keyword search. The module of personal panel mainly shows and processes the personal information and part of the related data of users. The module of interactive function can realize the functions of liking, commenting, and collecting, and can be reused as a component in each of the above modules.

[0069] The PC terminal is mainly for managers and students, which is divided into two subsystems of background management and visual display and several functions corresponding to each subsystem. Among them, the background management subsystem is divided into four modules of user information management, health area management, task management, and activity management, which correspond to each management function and basically meet the needs of daily management of the system. The visual display subsystem uses related visualization technology to intuitively display the campus health situation, including the display of campus health situation, trend chart, and health situation of each building, as well as the three-dimensional map of the entire campus, which marks the location of unqualified health situation on the map in the form of point markers.

[0070] 3. Database design

[0071] According to the system function design, the basic entities and entity relationships of the whole-process intelligent management and display system of labor education practice are determined, so as to determine the database required for the design of each function of the system. According to the object-oriented idea, the corresponding entity class is designed, and the corresponding database table is generated by the entity class. The relationship between the data tables reflects the relationship between the objects. The system designs a total of 14 data tables, and the light service provides a simple and easy-to-use database function based on mongoDB. In the database table, mongoDB automatically generates the _id field as the primary key of each table. In the code, only through inspirecloud.db can the relevant operation be carried out, for example, the table can be obtained through await inspirecloud.db.table('myTable'), all records can be queried through await myTable.where().find(), records can be saved through await myTable.save(items), records can be deleted through await myTable.delete(items), etc.

[0072] 3.1 Database E-R diagram design

[0073] Through the previous system function design, it can be known that the external entities involved in the whole-process intelligent management and display system of labor education practice are users and administrators. The database table is designed based on these two cores. Table 1 shows the tables in the database of the whole-process intelligent management and display system of labor education practice and their related descriptions. Each table complements each other, and based on the system function, the system E-R diagram as shown in Figure 3 is obtained.

[0074] Table 1

[0075]

[0076]

[0077] 3.2 Database logical structure design

[0078] The database logical structure design is based on the E-R diagram of the database. Due to the limitation of the length, only the Users table will be analyzed. The Users table stores the personal information of the user, including login information, email, cleaning and inspection information, college, class information, activity information, credits, and integrity. As an external entity, the functions of the system revolve around the user, and the data revolves around the user, so the logical structure design of the Users table is particularly important.

[0079] 4. Main function implementation of the system

[0080] The whole-process intelligent management and display system for labor education practice is a double-end system including PC end and mobile phone APP end, and the main functions of each end are as follows.

[0081] 4.1 User information management and health area management function

[0082] The user information management and health area management are mainly realized by relying on the background management subsystem of the PC end, and can perform add, delete, modify and query operations on the information of the user's college, class, student number and name, and the building and classroom that need to be cleaned and inspected, basically meeting the daily management needs, among which the inspector information and health area management are for the campus health labor education practice project. The inspector information management interface is as shown in Figure 4 , and the health area management interface is as shown in Figure 5 .

[0083] 4.2 Visualization display function

[0084] The visualization display function is mainly realized by relying on the visualization display subsystem of the PC end, and uses Echarts visualization technology and Gaode map SDK to visualize the data, and the interface is as shown in Figure 6 . In the figure, the top bar is the overview, trend chart and health condition data of each building of the campus health condition; the left bar is the real-time health inspection data, the middle part is the three-dimensional map of the campus, and the places with unqualified health conditions are marked on the map in the form of point markers; the right bar is the completion situation of cleaning and inspection.

[0085] 4.3 Task management function

[0086] For the campus health labor education practice, the task management function mainly designs cleaning tasks and inspection tasks, and is realized by relying on the PC end and mobile phone APP end two-end system.

[0087] 4.3.1 Cleaning task

[0088] For the health responsibility system of one class and one classroom, in view of the problems of large workload caused by manual allocation of cleaning tasks, and long distance and inconvenience caused by mismatching of classroom allocation and object class arrangement, a classroom-class cleaning task matching algorithm is designed and implemented, and the algorithm flow is as shown in Figure 7 . The algorithm uses the greedy algorithm idea to find the local optimal solution, that is, the class with the most class times in each classroom is taken as the local optimal solution, and the global matching optimal solution is formed by summarizing.

[0089] The basic steps of the classroom-class cleaning task matching algorithm are as follows:

[0090] Step 1: Construct the classroom-class-class times table.

[0091] Step 1.1 Obtain the site schedule excel file and read the classroom-class related information from the file to build a classroom-class matching table.

[0092] Step 1.2 Extract the number of classes in the corresponding classroom, and generate a classroom-class-class number table R-C-N=<classroom, class, class number> in descending order of class number. If the table is empty, the algorithm ends, otherwise go to step 2.

[0093] Step 2: Perform the first round of classroom-class cleaning task matching to generate the optimal matching table and pending list.

[0094] Step 2.1 For each classroom, use the greedy strategy to get the class with the most class number from the classroom-class-class number table R-C-N, and store it in the R-C-Nmax=<classroom, class, maximum class number> list. If the maximum class number of a classroom is greater than 0, assign the task of cleaning the classroom to the class with the most class number in that classroom. If there are multiple different classes with the most class number in the classroom, randomly select one class from these classes with the same maximum number of classes and assign it to the classroom. Mark the classroom and class as matched, and store the matched classroom-class in the optimal matching table OptimalMatching=<classroom, class, maximum class number>. At the same time, if the marked class exists in the R-C-Nmax table of other unmarked classrooms, delete the class and update the maximum class number and its corresponding class of the classroom.

[0095] Step 2.2 Take the difference set of table R-C-N from table OptimalMatching, and store the difference set in the pending list PendingList=<classroom, class, class number>.

[0096] Step 2.3 If the pending list PendingList is empty, the algorithm ends, otherwise go to step 3.

[0097] Step 3: Perform the second round of classroom-class cleaning task matching to generate the sub-optimal matching table

[0098] Step 3.1 According to the distribution of disciplines and professional majors in the school area and the geographical location of the building, set up a mapping table between the area (A), class (C), building (B), and classroom list (RL). Map the class (C) to the area (A), and the mapping relationship is A=f(C); Map the area (A) to the building (B), and the mapping relationship is B=f(A); Map the building (B) to the classroom list (RL), and the mapping relationship is RL=f(B); Map the classroom list (RL) to the classroom (R), and the mapping relationship is R=random(RL).

[0099] Step 3.2 Match the classes (C) in the PendingList with the classrooms R through the mapping relationship constructed in the previous step, and store them in the SuboptimalMatching table = <classroom, class, number of classes>.

[0100] Step 4: Summarize the generated classroom-class cleaning task matching table

[0101] Summarize the optimal matching table optimalMatching generated in step 2 and the suboptimal matching table SuboptimalMatching generated in step 3 to generate a classroom-class cleaning task matching table and output. At this point, the classroom-class cleaning task matching is complete, and the algorithm ends.

[0102] 4.3.2 Inspection task

[0103] An optimal allocation algorithm for inspection tasks is designed for health inspectors, which realizes semi-automatic selection and automatic allocation of inspection tasks, and effectively solves the problem of reasonable allocation of inspection tasks. The detailed process of the optimal allocation algorithm for inspection tasks is shown in Figure 8 .

[0104] The steps of the optimal allocation algorithm for inspection tasks are:

[0105] Step 1: Initialize the algorithm-related parameters, including setting the number of inspection classrooms for a single inspector checkCount and setting the inspection date range checkDate and other parameters.

[0106] Step 2: Get the table of all buildings that need to be cleaned, denoted as roomList = <Building, List, roomCount>, where the table item Building represents the building, the table item List represents the classroom list, and the table item roomCount represents the number of inspection classrooms,

[0107] Step 3: Build the candidate task and generate the building candidate task table, denoted as B-T = <Building, Task>, where the table item Building represents the building, and the table item Task represents the candidate task table and is stored in an array. For each Building in the roomList table, compare its roomCount with checkCount, and generate the building candidate task table B-T according to the following conditions:

[0108] Step 3.1 If the roomCount of a Building is less than or equal to checkCount, then the limit of the Building is set to 1, and the roomCount is added to the Task table, and the B-T item is generated and stored in the B-T table.

[0109] Step 3.2 If the roomCount is greater than checkCount, then remainder = roomCount % checkCount and The length of the Task array is set to limit, and each item in the array is set to checkCount.

[0110] Step 3.2.1 If remainder is greater than or equal to limit, then the following judgment is made: if The value of each item in Task is added by remainder / limit, and remainder % limit table items are randomly selected in Task and added by 1, and the B-T item is generated and added to the B-T table; if The length of the Task array is set to limit + 1, and the item is set to remainder, and the B-T item is generated and stored in the B-T table.

[0111] Step 3.2.2 If remainder is less than limit, then remainder positions are randomly selected in the Task table, and the values of the corresponding positions are added by 1, and the B-T item is generated and stored in the B-T table.

[0112] Step 4: Construct the inspection task, generate the inspection task table, denoted as B-D-C = <Building, Date, CheckRoom>, where the Building table item represents the building, the Date table item represents the inspection date, and the CheckRoom table item represents the inspection classroom table.

[0113] Step 4.1 For each inspector, voluntarily select the inspection date Date from the available inspection date range, and select the building Building from the B-T table.

[0114] Step 4.2 According to the mapping relationship in the B-T table, the system automatically allocates an item in the Task array to the inspector, and the value in the item is used as the length of the inspection classroom table for the inspector.

[0115] Step 4.3 matches the selected building Building in the roomList, and generates a check room table CheckRoom by selecting value adjacent classrooms from the corresponding classroom list List in Building, thereby generating a check task table B-D-C, and the algorithm ends.

[0116] 4.4 Release function

[0117] The release function is mainly implemented through the mobile phone APP, which contains the main function modules of labor education practice: cleaning check-in, health inspection, volunteer activities, score ranking, activity creation, lost and found, and its interface is as shown in Figure 9 In the modules of each release function in the figure, if picture uploading is performed, the built-in file storage API of the light service is called.

[0118] The "activity creation" in Figure 9 contains information such as the activity cover, activity name, activity introduction, registration time, activity time, activity location, and activity number of an activity, which can completely abstract a labor education practice activity, and its page is as shown in Figure 10 The page uses flex layout, flex-direction is set to column, and justify-content is set to space-around, so that the page is arranged neatly and orderly, the timestamp uses the built-in component of Uni-App, and the current time can be obtained by clicking the start time. After the activity is created, the time range is verified by the front and back ends to determine whether it can be signed up or the activity can be performed, the front end judges the time range before the page is rendered through the Uni-App page life cycle function onLoad, and disables the join activity button at the interface level, and the back end verification prohibits joining the activity at the service level, which can prevent xss attacks. Such design and implementation not only saves the back-end overhead but also improves the security of the system and the responsiveness of the page.

[0119] The "health inspection" in Figure 9 contains selection tasks, location buttons, health status state buttons, health status detailed descriptions, and picture uploading, which can completely evaluate the health status, and its health inspection release page is as shown in Figure 11The page is used to assign the health inspection task by the system, and different building and classroom options are provided for each inspector. The health status of each classroom has three states for the inspector to choose from, which are excellent, qualified and unqualified. Detailed description and uploading of on-site pictures can be used as evidence, and the current coordinate position information is uploaded for visual processing by the visualization display subsystem. For the health status, if the inspector chooses excellent or qualified, the picture can be selected, and the description cannot be selected. If the unqualified is selected, both the description and the picture need to be selected, otherwise, it will not be uploaded. The control and change of the state of each option is realized by the watch function in the Vue framework. Before changing one option state, the state of other options is changed at the same time, and the page is synchronously displayed in response.

[0120] 4.5 Information display function

[0121] The information display function is realized by relying on the mobile APP end, mainly used for the display of information flow. The front-end technologies such as waterfall flow, horizontal long list, lazy loading and Layout layout are used to fully and orderly display the activity information, health inspection and cleaning information, lost and found information and the like. At the same time, the front-end and back-end performance are taken into account. The mobile APP end undertakes most of the information display functions, and the home page thereof is as shown in Figure 12 .

[0122] 4.6 Interaction function

[0123] The full-process intelligent management and display system of labor education practice sets the interaction function in the mobile APP end, mainly including the like, comment and collection functions, which are provided to the labor practice activity module and the lost and found module as an independent reusable function component to provide better user experience. The comment data in the interaction function is stored in a flat data structure in the database. When the front-end sends a request, the back-end returns the JSON tree data to the front-end by converting the flat data. The data conversion is realized by using the Map storage method, and the corresponding relationship is realized by _id and reply. _id is the unique identifier of each comment, and reply is the _id of the reply comment. According to the corresponding relationship, the Map reading verification operation is performed during traversal, and one layer of loop can complete the flat data to tree, which has good performance. In the interaction function, an activity object is the root node of the tree, any direct comment of the activity object is the first layer node of the tree, and the existing comment information is the child node of the corresponding comment node. In the related interface of the interaction function, Figure 13 a detail page of a volunteer activity in the labor practice activity module is shown, and the bottom thereof is the interaction function component, including the like, comment and collection functions.

[0124] 5. Main features and advantages of the present application:

[0125] The whole-process intelligent management and display system of labor education practice is set for the administrative personnel, teachers and students in the campus, and has a mobile APP end and a PC end, and the characteristics mainly include: (1) the whole-process intelligent management of labor education practice is realized through software development technology and visualization technology; (2) the examination and evaluation of labor education practice are standardized through digital technology; and (3) the intelligent management of the campus health labor education practice is deeply developed.

[0126] The system adopts a front-end and back-end separation development mode, has low coupling degree and high maintainability, the back end is developed based on a serverless platform light service, can realize zero operation and maintenance, can be elastically scaled in performance, greatly meets the operation and maintenance and server performance needs of the product, has excellent characteristics of intelligent management efficiency, clear visual display, simple operation, easy maintenance, safety and reliability and the like.

[0127] Compared with the traditional labor education practice management mode, the system has certain advantages, as shown in Table 2.

[0128] Table 2

[0129]

[0130] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this, any skilled person in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A fully intelligent management and display system for labor education practices, characterized in that, Including mobile app and PC platforms; The mobile app includes: The Labor Practice Activities module is used to handle business related to labor education courses; The lost and found module is used to publish lost and found items and issue lost and found notices, as well as to publish information and conduct keyword searches; The personal panel module is used to display and process personal information and some related data for users. The interactive functionality module is used to enable likes, comments, and favorites. The PC terminal includes: The back-end management subsystem is used to manage user information, hygiene areas, tasks, and activities. The visualization subsystem is used to intuitively display the campus sanitation status and a 3D map of the entire campus, marking the locations on the map where sanitation is substandard using point markers; The task management includes a cleaning task management submodule and an inspection task management submodule. The cleaning task management submodule adopts a classroom-class cleaning task matching algorithm. This algorithm uses the greedy algorithm idea to find the local optimal solution, that is, to count the class with the most classes in each classroom as the local optimal solution, and summarize them to form the global matching optimal solution. The specific process of the classroom-classroom cleaning task matching algorithm is as follows: Step 1: Create a classroom-class-number of classes table; Step 1.1 Obtain the venue timetable Excel file, and read the classroom-class teaching information from the Excel file to build a classroom-class matching table; Step 1.2 Extract the number of classes for each class in the corresponding classroom, and generate a classroom-class-class number of classes table RCN = <classroom, class, number of classes> by sorting the number of classes in descending order; if the table is empty, the algorithm ends, otherwise proceed to step 2; Step 2: Perform the first round of classroom-classroom cleaning task matching to generate an optimal matching table and a pending list; Step 2.1 For each classroom, a greedy strategy is used to retrieve the class with the most classes in each classroom from the classroom-class-class count table RCN, and store it in the RC-Nmax = <classroom, class, maximum number of classes> list; if the maximum number of classes in a classroom is greater than 0, the task of cleaning the classroom is assigned to the class with the most classes in that classroom; if there are multiple different classes with the most classes in a classroom, a class is randomly selected from these classes with the same maximum number of classes and assigned to the classroom, and the classroom and class are marked as matched, and the matched classroom-class is stored in the OptimalMatching = <classroom, class, maximum number of classes> table; at the same time, if the marked class exists in other unmarked classrooms in the RC-Nmax table, the class is deleted and the maximum number of classes in the classroom and its corresponding class are updated; Step 2.2 Obtain the difference between the table RCN and the table OptimalMatching, and store the difference in the pending list PendingList = <classroom, class, number of classes>; Step 2.3 If the pending list PendingList is empty, the algorithm ends; otherwise, proceed to step 3. Step 3: Perform the second round of classroom-classroom cleaning task matching to generate a suboptimal matching table; Step 3.1 Based on the distribution of academic disciplines and building locations within the school area, set up a mapping table between area (A), class (C), building (B), and classroom list (RL). Mapping from class (C) to area (A) is denoted as A = f(C); mapping from area (A) to building (B) is denoted as B = f(A); mapping from building (B) to classroom list (RL) is denoted as RL = f(B); mapping from classroom list (RL) to classroom (R) is denoted as R = random(RL). Step 3.2 Match the class (C) in the pending list to the classroom R through the mapping relationship constructed in the previous step, and store it in the suboptimal matching table SuboptimalMatching=<classroom, class, number of classes>; Step 4: Compile and generate a classroom-classroom cleaning task matching table; The optimal matching table (optimalMatching) generated in step 2 and the suboptimal matching table (SuboptimalMatching) generated in step 3 are combined to generate and output a classroom-classroom cleaning task matching table. The inspection task management submodule adopts the inspection task optimal allocation algorithm to realize semi-autonomous selection and automatic allocation of inspection tasks.

2. The intelligent management and display system for the entire process of labor education practice according to claim 1, characterized in that, The aforementioned user information management and hygiene area management are used to perform add, delete, modify, and query operations on users' colleges, classes, student IDs, names, and the buildings and classrooms that need to be cleaned and inspected.

3. The intelligent management and display system for the entire process of labor education practice according to claim 1, characterized in that, The specific process of the optimal task allocation algorithm is as follows: Step 1: Initialize algorithm-related parameters, including setting the number of classrooms to be inspected by a single inspector (checkCount) and setting the inspection date range (checkDate); Step 2: Obtain a list of all classrooms in all buildings that need cleaning, denoted as roomList =<Building,List,roomCount> The table entry Building represents the building, List represents the list of classrooms, and roomCount represents the number of classrooms checked. Step 3: Construct candidate tasks and generate a building candidate task table, denoted as BT=<Building,Task> The table `Building` represents a building, and the table `Task` represents a list of candidate tasks, stored in an array. For each building in the `roomList` table, its `roomCount` is compared with its `checkCount`, and a candidate task list `BT` is generated based on the following conditions: Step 3.1 If the roomCount of a building is less than or equal to the checkCount, then set the limit of the number of check tasks for that building to 1, add the roomCount to the Task list, generate a BT item and store it in the BT table. Step 3.2 If roomCount > checkCount, then let remainder = roomCount % checkCount and Set the length of the array Task to limit, and the value of each item in the array to checkCount; Step 3.2.1 If remainder ≥ limit, then perform the following judgment: If Then, add `remainder / limit` to the value of each item in the Task, and randomly select `remainder%limit` items in the Task and add them with 1 to each, generating BT items and adding them to the BT table; if Then set the length of the array Task to limit+1, set the item to remainder, and generate a BT item and store it in the BT table; Step 3.2.2 If remainder < limit, randomly select remainder positions in the Task table, increment the values of the corresponding entries by 1 respectively, generate B-T items and store them in the B-T table; Step 4: Construct inspection tasks, generate an inspection task table, denoted as B-D-C = <Building, Date, CheckRoom>, where the entry Building represents the building number, the entry Date represents the inspection date, and the entry CheckRoom represents the inspection classroom list; Step 4.1 For each inspector, voluntarily select the inspection date Date from the range of selectable inspection dates, and select the building Building from the B-T table; Step 4.2 According to the mapping relationship in the B-T table, the system automatically randomly assigns an entry in the array Task to the inspector, and uses the value value in this entry as the length of the inspector's inspection classroom list; Step 4.3 Match the selected building Building in the roomList, and select value adjacent classrooms from the corresponding classroom list List in Building to generate the inspection classroom list CheckRoom, thus generating the inspection task table B-D-C.

4. The intelligent management and display system for the entire process of labor education practice according to claim 1, characterized in that, The activity management mentioned above includes an activity information review sub-module and an activity project acceptance management sub-module.

5. The intelligent management and display system for the entire process of labor education practice according to claim 1, characterized in that, The visualization display subsystem uses Echarts visualization technology and the Amap SDK to visualize the data.

6. The intelligent management and display system for the entire process of labor education practice according to claim 1, characterized in that, The system also includes a database subsystem. According to the object-oriented concept, corresponding entity classes are designed, database tables are generated from the entity classes, and the relationships between the data tables reflect the relationships between objects; among which the database logical structure design is based on the E-R diagram of the database.

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