CN113688170A

CN113688170A - Campus management method, device, equipment and storage medium

Info

Publication number: CN113688170A
Application number: CN202110961344.9A
Authority: CN
Inventors: 成晨; 郝若晶; 韩玉辉; 程新洲; 张亚南; 肖天; 高洁; 张涛; 赫欣; 贾玉玮
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2021-08-20
Filing date: 2021-08-20
Publication date: 2021-11-23

Abstract

The embodiment of the disclosure provides a campus management method, a campus management device, campus management equipment and a campus management storage medium, relates to the technical field of smart campuses and aims to solve the problem that big data are not combined to perform full-chain management on students in the prior art. The method specifically comprises the following steps: acquiring educational administration data and network data of a user; cleaning, normalizing, converging and marking the network data of the user to obtain processed data; performing fusion processing and analysis processing on the processed data and the educational administration data to obtain multi-aspect supervision data; and analyzing the multi-aspect supervision data to obtain an analysis result, and executing corresponding processing according to the analysis result.

Description

Campus management method, device, equipment and storage medium

Technical Field

The present disclosure relates to the field of smart campus technologies, and in particular, to a campus management method, device, equipment, and storage medium.

Background

With the trend of mobile internet, the combination of various industries and networks is becoming more extensive. After the network is combined with campus management, the intelligent management and service level of the school can be improved, and students can live and learn more conveniently and quickly at school.

However, the conventional campus management system has the following problems. Such as: single data source, incomplete problem processing chain, etc. Therefore, how to combine big data is crucial to students in full chain management.

Disclosure of Invention

The disclosure provides a campus management method, a campus management device, campus management equipment and a campus management storage medium, and aims to solve the problem that in the prior art, big data are not combined to perform full-chain management on students.

In order to achieve the purpose, the technical scheme adopted by the disclosure is as follows:

in a first aspect, the present disclosure provides a campus management method, including the following steps: the campus management device acquires educational administration data and network data of a user; cleaning, normalizing, converging and marking the network data of the user to obtain processed data; performing fusion processing and analysis processing on the processed data and the educational administration data to obtain multi-aspect supervision data; and analyzing the multi-aspect supervision data to obtain an analysis result, and executing corresponding processing according to the analysis result.

Based on the technical scheme provided by the disclosure, the campus management device analyzes according to the network data and the educational administration data of the user to obtain more precise supervision data, and analyzes the supervision data, so that bad habits of the user corresponding to part of abnormal data are timely followed up. More refined management is achieved, and a full-link automatic closed loop is formed. Meanwhile, the labor management cost is further reduced.

In a second aspect, the present disclosure provides a campus management apparatus, including an obtaining module and a processing module; the acquisition module is configured to acquire educational administration data and network data of a user; the processing module is configured to perform cleaning processing, normalization processing, convergence processing and marking processing on the network data of the user to obtain processed data; the processing module is also configured to perform fusion processing and analysis processing on the processing data and the educational administration data to obtain multi-aspect supervision data; and the processing module is also configured to analyze the multi-aspect supervision data to obtain an analysis result and execute corresponding processing according to the analysis result.

In a third aspect, a campus management device is provided, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute instructions to implement the campus management method as provided in the first aspect above.

In a fourth aspect, the invention provides a computer-readable storage medium comprising instructions. The instructions, when executed on the computer, cause the computer to perform the campus management method as provided above in the first aspect.

In a fifth aspect, the present invention provides a computer program product for causing a computer to perform the campus management method as provided in the first aspect when the computer program product runs on the computer.

It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with the processor of the access network device or may be packaged separately from the processor of the access network device, which is not limited in the present invention.

Reference may be made to the detailed description of the first aspect for the description of the second to fifth aspects of the invention; in addition, for the beneficial effects described in the second aspect to the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not described here.

In the present invention, the above names do not limit the devices or the functional modules themselves, and in actual implementation, the devices or the functional modules may appear by other names. Insofar as the functions of the respective devices or functional blocks are similar to those of the present invention, they are within the scope of the claims of the present invention and their equivalents.

These and other aspects of the invention will be more readily apparent from the following description.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.

Fig. 1 is a schematic diagram of a communication system in accordance with an embodiment of the present disclosure;

FIG. 2 is a flow chart illustrating a campus management method according to an embodiment of the present disclosure;

FIG. 3 is a second flowchart illustrating a campus management method according to another embodiment of the disclosure;

FIG. 4 is a schematic diagram of a campus management model according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram illustrating an application of a campus management model according to an embodiment of the present disclosure;

FIG. 6 is a third flowchart illustrating a campus management method according to an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of a night homing management system according to an embodiment of the present disclosure;

FIG. 8 is a schematic structural diagram of a night homing management system, according to an embodiment of the present disclosure;

FIG. 9 is a schematic diagram of a campus management device according to an embodiment of the present disclosure;

fig. 10 is a schematic structural diagram of a campus management device according to an embodiment of the present disclosure;

fig. 11 is a schematic structural diagram of a computer program product of a campus management method according to an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first" and "second" are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first" and "second" are not limited in number or execution order.

Based on the background technology, the embodiment of the application provides a campus management method. The method comprises the steps of obtaining educational administration data and network data of a user, processing the network data of the user to obtain processed data, fusing and analyzing the processed data and the educational administration data to obtain multi-aspect supervision data, and analyzing the supervision data to execute corresponding processing. Compared with the prior art, the method and the system are simple in calculation, and meanwhile, the network data and the educational administration data of the user are combined to perform full-chain management on the user, so that the intelligent service level is improved.

Next, a brief description will be given of an implementation environment related to the present disclosure.

Referring to fig. 1, fig. 1 is a schematic diagram illustrating a communication system according to an example embodiment. The system comprises an access network device 10 and a user terminal 20. Wherein the access network device 10 and the user terminal 20 may be interconnected and communicate through a network.

In some embodiments, the access network device 10 may be configured to obtain network data of a target user, determine a mobility index of the user, and so on. Specifically, the Access network device 10 may be an Access Point (AP), an evolved Node Base Station (eNB), or a Base Station in the 5Generation Mobile Communication Technology (5G) network, which is not limited in this embodiment.

The user terminal 20 may be a mobile phone, a tablet computer, a notebook computer, a desktop computer, a portable computer, etc., which is not limited in this disclosure. The user terminal 20 is shown in fig. 1 as a mobile phone.

It will be appreciated by those skilled in the art that the above-described communication system is merely exemplary and that other existing or future communication systems, as may be suitable for use with the present disclosure, are intended to be included within the scope of the present disclosure and are hereby incorporated by reference.

The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by one of ordinary skill in the art from the embodiments disclosed herein without making any creative effort, shall fall within the scope of protection of the present disclosure.

Fig. 2 is a flow diagram illustrating a campus management method according to an example embodiment. The method can be applied to the system shown in fig. 1, and as shown in fig. 2, the method comprises steps 21-24.

And step 21, the campus management device acquires educational administration data and network data of the user.

The campus management device may be the terminal 10 in the communication system, or may be the base station 20 in the communication system.

Educational administration data is used to characterize all data related to the life of a user (e.g., a student). The data mainly comprises static data, and the static data comprises the following components: student's academic information, such as: class, grade, specialty of the student; the class course arrangement is used for acquiring the attendance condition of students; student performance, such as: public class score, professional class score, age ranking, professional ranking, number of hung disciplines, hung science score, etc.; student award schooling data; student learning aid data; student's learning aid loan data, etc.

The network data comprises 5G data, 2G/3G/4G data and Internet of things data. The 5G data and the 2G/3G/4G data may be obtained by collecting an Object Storage Service (OSS) domain data XDR ticket. The XDR ticket comprises a single interface ticket and a special ticket, wherein the single interface ticket is generated by analyzing data in a certain specific interface, and the special ticket is generated by performing multi-interface association or secondary processing according to specific requirements. And for the single interface ticket, dividing the single interface ticket into each interface ticket according to the difference of the interfaces. Specifically, the network data in the present disclosure may be Interface (IUCS) data for transmitting a circuit domain between a radio network controller and a core network, interface (S1MME) data for transmitting session management and mobility management information, and interface (S1UHTTP) data for transmitting a user data service.

The IUCS interface may obtain call data for the user. In the IUCS interface, SpecFlag 1 indicates data called by the user, and CallDropFlag 1 indicates data called successfully by the user. The present disclosure keeps a record of CallDropFlag ═ 1, and deletes the data for SpecFlag ═ 1. For an example, see table 1 for data in the IUCS interface.

TABLE 1

Imsi
	Imei
Imsisdn
	Starting time
End time
	Calling/called party
Base station cell identity

The S1UHTTP interface can obtain the internet data of the user. For an example, see table 2 for data in the S1UHTTP interface.

TABLE 2

Imsi
	Imei
Imsisdn
	Starting time
End time
	Class of APP
Name of APP
	Upstream flow
Downstream traffic
	Base station cell identity

For example, see table 3 for data in the S1MME interface.

TABLE 3

Imsi
	Imei
Imsisdn
	Starting time
End time
	Base station cell identity

And step 22, the campus management device performs cleaning processing, normalization processing, aggregation processing and marking processing on the network data of the user to obtain processed data.

In the embodiment of the disclosure, the campus management device analyzes the network data of the user to obtain the processed data. The processing data comprises basic data, intermediate data, data indexes and data labels.

Referring to fig. 2, as shown in fig. 3, in the step 22, performing a cleaning process, a normalization process, a convergence process, and a labeling process on the network data of the user, and obtaining processed data may include:

step 221, the campus management device performs cleaning processing and normalization processing on the network data of the user to obtain basic data.

In the embodiment of the present disclosure, the campus management device inputs the acquired network data of the user into the campus management model for processing, so as to obtain the basic data.

Specifically, as shown in fig. 4, an input layer of the campus management model acquires network data of a user, and a data analysis layer analyzes the acquired network data of the user to obtain analysis data; and then, the data buffer layer performs data cleaning and data normalization on the analyzed data, and performs multi-dimensional correlation analysis according to the time latitude and the geographical latitude after the data cleaning and normalization so as to obtain basic data. The input layer of the campus management model can acquire the network data of the user in batch or in real time; the data buffer layer can analyze the data in a timing analysis mode or a streaming analysis mode; the associated data for the data buffer layer to perform association analysis includes a terminal library, a cause value, an engineering parameter, a user attribute table, an IP address library, a service information table, a Deep Packet Inspection feature library (DPI), and the like.

And step 222, the campus management device performs convergence processing on the basic data to obtain theme data.

In the embodiment of the disclosure, the basic data are aggregated according to different classifications to obtain the subject data. The theme data comprises user theme data, network theme data, terminal theme data, service theme data and the like.

Specifically, with reference to fig. 4, the campus management device performs aggregation processing on the basic data through a data aggregation layer in the campus management model to obtain the subject data.

And 223, the campus management device performs label marking on the subject data to obtain marked data, and obtains processed data according to the basic data, the subject data and the marked data.

In the embodiment of the disclosure, the subject data is labeled according to the attribute thereof, so as to obtain labeled data. Wherein the marking data comprises user tags, terminal preferences, location preferences, application preferences, lap preferences, network element tags, scene tags, and the like. The process data includes basic data, topic data, and tag data.

Specifically, with reference to fig. 4, the campus management device tags the topic data through the data mart layer in the campus management model to obtain a tagged result, packages the tagged result, the topic data, and the basic data to generate processed data, and outputs the processed data.

Optionally, in conjunction with fig. 4, the campus management model further includes a storage layer and a metadata standard layer. The storage mode of the storage layer comprises column storage and distributed storage, and the storage data comprises cold data and hot data. And the metadata standard layer is used for recording all files of the data processing process, wherein the metadata standard layer comprises a metadata standard library, a metadata application, a metadata storage and metadata basic management.

The technical scheme provided by the steps at least has the following beneficial effects: the campus management model can analyze the network data of the user to obtain a processing result, and the campus management model is applied to various campus management according to the processing result, so that the labor management cost can be greatly reduced, and the management time is saved.

And step 23, the campus management device performs fusion processing and analysis processing on the processed data and the educational administration data to obtain multi-aspect supervision data.

In the embodiment of the disclosure, the campus management device performs data fusion on the processing data, the educational administration data and the user identifier, and performs data analysis based on the fused data to obtain multi-aspect supervision data.

For example, referring to fig. 5, network data of a user of a terminal is input into the campus management model shown in fig. 4 to obtain processed data, and the processed data and educational administration data of other terminals are subjected to data fusion and data analysis to obtain various supervision data.

Further, the multiple aspects of supervision include: night homing supervision, attendance supervision, newborn collective outgoing supervision, game addiction supervision, video addiction supervision and consumption level supervision.

Specifically, the night returning supervision, the attendance supervision, the game addiction supervision and the video addiction supervision are all used for evaluating related bad habits through network data of users (such as students), assisting school parties and instructors to intervene according to the bad habits of the students, and facilitating early correction.

The newborn collective outgoing supervision is used for assisting school parties and instructors to manage outgoing activities and holidays of students through student group distribution thermodynamic diagrams, school-out gathering monitoring, student urban/urban outgoing analysis and outgoing intention assessment.

The consumption level supervision is used for constructing a student consumption level evaluation system and providing a certain basis for the judgment of high consumption groups and poor students, thereby providing a certain basis for 'non-inductive' issuing of learning-aid money and poor-poverty assistance and personalized student subsidy.

Wherein, the night homing supervision is mainly realized by the following statistical data, and mainly comprises: the method comprises the following steps of carrying out sectional statistics on night homing statistical data, school leaving statistical data during the course, the geographical position of a night homing student, school leaving time and the number of people of the school leaving student at night and day, and the number of people leaving the school at night and day and the number of people leaving the school for a long time in a preset time period; student group supervision of special attributes.

The game addiction supervision is realized by the following statistical data, and mainly comprises the following steps: game enthusiasm of each class, network credit index and comparison between the network credit index and the average index of the whole school are used for guiding the instructor to carry out student behavior deviation evaluation; counting the number of students playing games and the duration within a preset time period; analyzing the popularity of the game application program; the number of students accessing the network loan application program, the frequency and the application program type; student group supervision of special attributes.

Video addiction supervision is mainly realized by the following statistical data, and the video addiction supervision method mainly comprises the following steps: video enthusiasm of each class, network credit index and comparison between the network credit index and the average index of the whole school are used for guiding the instructor to carry out student behavior deviation evaluation; counting the number of students watching the video at a fixed time within a preset time period and counting the time; analyzing the popularity of the video application program; the number of students accessing the network loan application program, the frequency and the application program type; student group supervision of special attributes.

The newborn collective outgoing supervision is mainly realized by the following statistical data, and mainly comprises the following steps: the thermodynamic diagrams of the whole school and the student groups of all classes are distributed, and the thermodynamic diagrams in the current day and the seven days are supported to be displayed; analyzing the number of the students going out in the city within a preset time period, wherein the analyzing comprises various scenes of leaving school, leaving school for two hours and leaving school for four hours, and analyzing the number of the students leaving school in real time on the same day and the moving range; analyzing urban and outdoor trips within a preset time period, wherein the urban and outdoor trips comprise an intra-province trip scene and a trans-province trip scene; long distance travel intentions and plans for students; the method aims at the big new students or other special student groups, continuously monitors the collective travel behaviors, displays the collective travel destinations, the gathering time and the number of people, and provides support for the safety management of students.

Consumption level supervision is mainly achieved by the following statistical data, which mainly include: the communication fee of students and the price of the held terminal are analyzed, and various brands and model distributions are held; the number of people in each interval of the current day payment times and the shopping duration is displayed in a distributed manner; the payment times, the number of online shopping people and the time length of fixed time length in a preset time period; the heat analysis of the hot spot finance type and shopping type APP is used; student group supervision of special attributes.

And 24, analyzing the multi-aspect supervision data by the campus management device to obtain an analysis result, and executing corresponding processing according to the analysis result.

In the embodiment of the disclosure, after the supervision data is obtained, the supervision data is analyzed, if the analysis result meets the threshold, monitoring is performed according to a normal monitoring flow, and if the analysis result does not meet the threshold, user behavior intervention is performed by adopting a related management method.

Further, referring to fig. 2, as shown in fig. 6, when the monitoring data is night unsure monitoring data, step 24 analyzes the multi-aspect monitoring data to obtain an analysis result, and performs corresponding processing according to the analysis result, including:

and 241, determining the danger level of the user by the campus management device according to the night homing data of the user and the static data in the educational administration data.

Specifically, the output data of the campus management device can be applied to a plurality of aspects, such as: a network planning scenario, a user profile scenario, a cell profile scenario, a user group analysis scenario, a terminal analysis scenario, and a service analysis scenario, among others.

When the supervision data of the campus management device is used in the night homing scene, as shown in fig. 7, the campus management device inputs night homing data into a night homing determination module in a night homing management system, the night homing determination module determines whether the night homing is present, then determines whether the same user is in the night homing before the previous day according to the previous day night homing determination module, the previous day night homing determination module inputs the output result of the previous day night homing determination module and the output result of the night homing determination module into a determination frame to determine whether the night homing lasts for two days, and after the two days of night homing are determined, the determination result and static data in the educational data are input into a danger level determination module of the user to determine the danger level of the user.

Illustratively, whether a user (such as a student) stays at night or not is judged in real time, and after the user is judged to stay at night or not, whether the student stays at night or not is judged in combination with the condition that the student stays at night in the previous day or not. After the students are determined not to be in the home at night, the danger levels of the students are determined through a danger level determination module of the user by combining static attributes (such as whether to hang up, whether to leave a class, whether to be three red students and the like) in the educational administration data.

In step 242, the campus management device executes corresponding processing when the risk level of the user is greater than a threshold.

Illustratively, when the danger level of a user (such as a student) is larger than a threshold value, the system automatically informs the student and the instructor through the short message/voice gateway. When the number of students with the danger levels larger than the threshold reaches a certain threshold, a class meeting notice is automatically sent, and the counselor is enabled to conduct unified management and evacuation.

With reference to FIG. 7, after the user's risk level is greater than a threshold, the tutor and the user themselves are notified; and if the number of the users with the danger levels of the users larger than the threshold exceeds the limit value, informing the instructor, the user and the users in the whole shift.

The technical scheme provided by the steps at least has the following beneficial effects: according to the monitored night unsure data and static data, the danger level of the user can be directly determined, and therefore corresponding processing is executed. Therefore, the user behavior is quantified in a data form, and the method is more objective and realizes effective supervision.

Optionally, when the output data of the campus management device is used in a night homing scene in campus management, as shown in fig. 8, the campus management device inputs night homing supervision data to a night homing determination module in the night homing management system, the night homing determination module determines whether the data is returned at night, then inputs the night homing supervision data of the week to the night homing determination module of the week to determine the night homing condition of the week, and then inputs the night homing condition of the week to the night homing statistics module of the week to be summarized by the personal latitude, the class latitude and the full school latitude, so as to obtain the night homing statistics data of the week. Finally, the night statistics of the week are notified to the professor, the instructor and the user.

The technical scheme provided by the steps at least has the following beneficial effects: and analyzing according to the network data and the educational administration data of the user to obtain more detailed supervision data, and analyzing the supervision data so as to timely follow up the bad habits of the user corresponding to part of the abnormal data. More refined management is achieved, and a full-link automatic closed loop is formed. Meanwhile, the labor management cost is further reduced.

The foregoing describes the scheme provided by the embodiments of the present disclosure, primarily from a methodological perspective. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

Fig. 9 is a schematic structural diagram illustrating a campus management device according to an exemplary embodiment, where the campus management device may be used to execute the campus management method shown in fig. 2. As an implementation manner, the apparatus may include an acquisition module 91 and a processing module 92.

An obtaining module 91 configured to obtain educational administration data and network data of a user; for example, in conjunction with fig. 2, the obtaining module 91 may be configured to perform step 21.

The processing module 92 is configured to perform cleaning processing, normalization processing, aggregation processing and marking processing on the network data of the user to obtain processed data; for example, in conjunction with fig. 2, processing module 92 may be used to perform step 22.

The processing module 92 is further configured to perform fusion processing and analysis processing on the processing data and the educational administration data to obtain multi-aspect supervision data; for example, in conjunction with fig. 2, processing module 92 may be used to perform step 23.

The processing module 92 is further configured to analyze the multi-aspect supervision data to obtain an analysis result, and perform corresponding processing according to the analysis result. For example, in conjunction with fig. 2, processing module 92 may be used to perform step 24.

Optionally, the processing module 92 is further configured to perform cleaning processing and normalization processing on the network data of the user to obtain basic data; for example, in conjunction with fig. 6, the processing module 92 may be configured to perform step 221.

The processing module 92 is further configured to perform aggregation processing on the basic data to obtain theme data; for example, in conjunction with fig. 6, the processing module 92 may be used to perform step 222.

The processing module 92 is further configured to tag the subject data to obtain tagged data, and obtain processed data according to the basic data, the subject data, and the tagged data. For example, in conjunction with FIG. 6, processing module 92 may be used to perform step 223.

Optionally, the multiple aspects of supervision include: night homing supervision, attendance supervision, newborn collective outgoing supervision, game addiction supervision, video addiction supervision and consumption level supervision.

Optionally, the processing module 92 is further configured to determine a danger level of the user according to static data in the night non-homing data and the educational administration data of the user; for example, in conjunction with fig. 6, the processing module 92 may be configured to perform step 241.

The processing module 92 is further configured to execute a corresponding process when the risk level of the user is greater than a threshold. For example, in conjunction with fig. 6, processing module 92 may be used to perform step 242.

Of course, the campus management apparatus provided in the embodiment of the present invention includes but is not limited to the above modules, and for example, the campus management apparatus may further include a storage module 93. The storage module 93 may be configured to store program codes of the write campus management apparatus, and may also be configured to store data generated by the write campus management apparatus during operation, such as data in a write request.

Fig. 10 is a schematic structural diagram of a campus management device according to an embodiment of the present invention, and as shown in fig. 10, the campus management device may include: at least one processor 101, a memory 102, a communication interface 103, and a communication bus 104.

The following specifically describes each component of the campus management device with reference to fig. 10:

the processor 101 is a control center of the campus management device, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 101 is a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present invention, such as: one or more DSPs, or one or more Field Programmable Gate Arrays (FPGAs).

In particular implementations, processor 101 may include one or more CPUs such as CPU0 and CPU1 shown in fig. 10 for one embodiment. Also, as an example, the campus management device may include a plurality of processors, such as the processor 101 and the processor 1010 shown in fig. 10. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).

The Memory 102 may be a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 102 may be self-contained and coupled to the processor 101 via a communication bus 104. The memory 102 may also be integrated with the processor 101.

In a particular implementation, the memory 102 is used for storing data and software programs for implementing the present invention. The processor 101 may perform various functions of the air conditioner by running or executing software programs stored in the memory 102 and calling data stored in the memory 102.

The communication interface 103 is a device such as any transceiver, and is used for communicating with other devices or communication Networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a user terminal, and a cloud. The communication interface 103 may include an acquisition unit implementing an acquisition function and a transmission unit implementing a transmission function.

The communication bus 104 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 10, but this is not intended to represent only one bus or type of bus.

As an example, in conjunction with fig. 9, the processing module 92 in the campus management device implements the same function as the processor 101 in fig. 10, and the storage module 93 implements the same function as the memory 102 in fig. 10.

Another embodiment of the present invention further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the method shown in the above method embodiment.

In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.

Fig. 11 schematically illustrates a conceptual partial view of a computer program product comprising a computer program for executing a computer process on a computing device provided by an embodiment of the invention.

In one embodiment, the computer program product is provided using a signal bearing medium 1110. The signal bearing medium 1110 may include one or more program instructions that, when executed by one or more processors, may provide the functions or portions of the functions described above with respect to fig. 2. Thus, for example, referring to the embodiment shown in FIG. 2, one or more features of steps 21-24 may be undertaken by one or more instructions associated with the signal bearing medium 1110. Further, the program instructions in FIG. 11 also describe example instructions.

In some examples, signal bearing medium 1110 may include a computer readable medium 1111, such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like.

In some implementations, the signal bearing medium 1110 may include a computer recordable medium 1112 such as, but not limited to, a memory, a read/write (R/W) CD, a R/W DVD, and so forth.

In some implementations, the signal bearing medium 1110 may include a communication medium 1113 such as, but not limited to, a digital and/or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).

The signal bearing medium 1110 may be communicated by a wireless form of communication medium 1113, such as a wireless communication medium conforming to the IEEE 802.111 standard or other transmission protocol. The one or more program instructions may be, for example, computer-executable instructions or logic-implementing instructions.

In some examples, a data writing device, such as that described with respect to fig. 2, may be configured to provide various operations, functions, or actions in response to one or more program instructions via computer-readable medium 1111, computer-recordable medium 1112, and/or communication medium 1113.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete the above-described full-classification part or part of the functions.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. The purpose of the scheme of the embodiment can be realized by selecting a part of or a whole classification part unit according to actual needs.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be substantially implemented as a part contributing to the prior art, or a whole classification part or a part of the technical solutions may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute the whole classification part or a part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions within the technical scope of the present invention are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for campus management, comprising:

acquiring educational administration data and network data of a user;

cleaning, normalizing, converging and marking the network data of the user to obtain processed data;

performing fusion processing and analysis processing on the processing data and the educational administration data to obtain multi-aspect supervision data;

and analyzing the multi-aspect supervision data to obtain an analysis result, and executing corresponding processing according to the analysis result.

2. The method of claim 1, wherein the performing a cleaning process, a normalization process, a convergence process, and a labeling process on the network data to obtain processed data comprises:

cleaning and normalizing the network data of the user to obtain basic data;

converging the basic data to obtain theme data;

and performing label marking on the subject data to obtain marked data, and obtaining processed data according to the basic data, the subject data and the marked data.

3. The method of claim 1, wherein the multifaceted surveillance comprises: night homing supervision, attendance supervision, newborn collective outgoing supervision, game addiction supervision, video addiction supervision and consumption level supervision.

4. The method according to claim 3, wherein the supervision data is night non-homing supervision data, the multi-aspect supervision data is analyzed to obtain an analysis result, and corresponding processing is performed according to the analysis result, and the method comprises the following steps:

determining the danger level of the user according to the night homing data of the user and static data in the educational administration data;

and when the danger level of the user is greater than a threshold value, executing corresponding processing.

5. An apparatus for campus management, comprising:

the acquisition module is configured to acquire educational administration data and network data of a user;

the processing module is configured to perform cleaning processing, normalization processing, convergence processing and marking processing on the network data of the user to obtain processed data;

the processing module is also configured to perform fusion processing and analysis processing on the processing data and the educational administration data to obtain multi-aspect supervision data;

the processing module is also configured to analyze the multi-aspect supervision data to obtain an analysis result, and execute corresponding processing according to the analysis result.

6. The apparatus of claim 5,

the processing module is also configured to perform cleaning processing and normalization processing on the network data of the user to obtain basic data;

the processing module is further configured to perform aggregation processing on the basic data to obtain subject data;

the processing module is further configured to label the subject data to obtain labeled data, and obtain processed data according to the basic data, the subject data and the labeled data.

7. The apparatus of claim 5, wherein the multifaceted surveillance comprises: night homing supervision, attendance supervision, newborn collective outgoing supervision, game addiction supervision, video addiction supervision and consumption level supervision.

8. The apparatus of claim 7,

the processing module is further configured to determine a danger level of a user according to static data in the night homing data and the educational administration data of the user;

the processing module is further configured to execute corresponding processing when the danger level of the user is greater than a threshold value.

9. A campus management device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of campus management of any of claims 1-4.

10. A computer-readable storage medium having instructions stored thereon, wherein the instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method for campus management as recited in any one of claims 1-4.