CN108171630A - Discovery method and system based on campus big data environment Students ' action trail - Google Patents
Discovery method and system based on campus big data environment Students ' action trail Download PDFInfo
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Abstract
The invention discloses a kind of discovery method based on campus big data environment Students ' action trail, including：The system data of each data system in campus environment is obtained, system data includes temporal information, location information, basic information and behavior act information；System data is started the cleaning processing and association process, form action trail model critical data；Students ' behavior initial track model is built according to action trail model critical data；Processing is modified to students ' behavior initial track model, forms students ' behavior complete trajectory model.The invention also discloses a kind of discovery systems based on campus big data environment Students ' action trail.Using the present invention, by combining data system, value and association analysis are carried out to the system data record of acquisition, students ' behavior and track are established using the time as the description for promoting dimension, it is associated with simultaneously by multi-dimensional data, the big datas technology such as logic judgment error correction, data depth excavation, realizes the description to the real behavior in track.
Description
Technical field
The present invention relates to big data technical fields more particularly to one kind to be based on campus big data environment Students ' action trail
Discovery method and a kind of discovery system based on campus big data environment Students ' action trail.
Background technology
Under the background of big data technology rapid development, data value more seems important, in MPP
(MPP) database, data mining, distributed file system (HDFS), distributed data base (hive, Hbase), cloud computing are put down
While platform, internet and expansible memory system technologies maturation and large-scale application, every profession and trade is being pursued and is being studied such as
What efficiently uses data, and available data assets is made to pass through analysis mining by enterprise or mechanism, has stronger decision edge, see clearly hair
Show power and process optimization ability to adapt to high growth rate and diversified development.
Nowadays people are in the epoch of information explosion.From pursue and find information, had evolved to screening, processing,
Analysis is a large amount of and complicated and with the stage of the exponential data increased.Many companies such as IBM, EMC, Teradata, Google etc.
Company is just using the Long-term Development Strategy of big data and cloud computing as company and new business growth point.Education sector also not example
Outside, how each university applies big data technology in campus environment, in research under campus environment relative to enterprise
The characteristics of speech, campus data, then shows as, and less but dimension is extensive for data volume, is had more in application study compared to business data
Challenge power；General enterprises rely on the data of some series, mass data are excavated using big data in application big data
Feature finds value, and in the environment in campus, the application and development of big data then needs big data builder and researcher more to note
The reasonability of molality type focuses on the adjustment of algorithm, focuses on the multi-dimensional nature of data or even sometimes for using DATA ASSOCIATION and spread out
Raw, data of science etc. is as the input of data and the input of model.
At present, the application of campus big data is broadly divided into the decision support application of big data, the analysis of user behavior custom and
Portrait description, safety and early warning, knowledge intelligent retrieval and recommendation etc..Applying for more than direction shows as studying in whole market
Stage also not really ripe application and popularization, exists simultaneously this model and application does not occur very characteristic content, based on school
The model and application that the students ' behavior track of garden data is found do not occur even more.Also without there is rationally student's row with maturation
The big data application for finding and analyzing for track.
Invention content
The technical problems to be solved by the invention are, provide a kind of based on campus big data environment Students ' action trail
Discovery method and system, the system data of acquisition can be recorded and carry out value and association analysis, establish students ' behavior and track
Using the time as the description for promoting dimension.
The technical problems to be solved by the invention also reside in, and provide a kind of based on campus big data environment Students ' behavior rail
The big datas skills such as the discovery method and system of mark, can be associated with by multi-dimensional data, logic judgment error correction, and data depth is excavated
Art realizes the description to the real behavior in track and the early warning to abnormal behaviour.
Campus big data environment Students ' action trail is based in order to solve the above technical problem, the present invention provides a kind of
Discovery method, including：Obtain campus environment in each data system system data, the system data include temporal information,
Location information, basic information and behavior act information；System data is started the cleaning processing and association process, form action trail
Model critical data；Students ' behavior initial track model is built according to action trail model critical data；It is initial to students ' behavior
Locus model is modified processing, forms students ' behavior complete trajectory model.
As the improvement of said program, the discovery method based on campus big data environment Students ' action trail, also
Including：Default students ' behavior abnormality alarming model and student group event alarm model；According to students ' behavior abnormality alarming model
And students ' behavior complete trajectory model judges whether that student's abnormal behavior event occurs；According to student group event alarm model and
Students ' behavior complete trajectory model judges whether that student's social event occurs.
As the improvement of said program, the discovery method based on campus big data environment Students ' action trail, also
Including：Students ' behavior track is extracted according to period dimension from students ' behavior complete trajectory model to be shown.
As the improvement of said program, the discovery method based on campus big data environment Students ' action trail, also
Including：Student's thermodynamic chart is built according to location information.
As the improvement of said program, the method for being modified processing to students ' behavior initial track model includes：
When different location information occurs in synchronization, then the position relationship according to front and rear event is needed, inferred position reasonability preserves just
True position；When the location information missing at a certain moment, then should occur being location information according to the deduction of other event informations；Work as something
The location information that part should occur is runed counter to practical location information, then according to front and rear event and location logic calculation position and event
Reasonability, establish event base.
Correspondingly, the present invention also provides a kind of discovery system based on campus big data environment Students ' action trail,
Including：Acquiring unit, for obtaining the system data of each data system in campus environment, the system data is believed including the time
Breath, location information, basic information and behavior act information；Data extracting unit, for being started the cleaning processing to system data and
Association process forms action trail model critical data；Initial track construction unit, for according to action trail model key number
According to structure students ' behavior initial track model；Complete trajectory construction unit, for being repaiied to students ' behavior initial track model
Positive processing, forms students ' behavior complete trajectory model.
As the improvement of said program, the discovery system based on campus big data environment Students ' action trail, also
Including：Model construction unit is alerted, for presetting students ' behavior abnormality alarming model and student group event alarm model；It is abnormal
Event-monitoring unit, for judging whether genetis method according to students ' behavior abnormality alarming model and students ' behavior complete trajectory model
Raw abnormal behavior event；Social event monitoring unit, for according to student group event alarm model and the complete rail of students ' behavior
Mark model judges whether that student's social event occurs.
As the improvement of said program, the discovery system based on campus big data environment Students ' action trail, also
Including：Display unit carries out for extracting students ' behavior track from students ' behavior complete trajectory model according to period dimension
Display.
As the improvement of said program, the discovery system based on campus big data environment Students ' action trail, also
Including：Thermodynamic chart unit, for building student's thermodynamic chart according to location information.
As the improvement of said program, the complete trajectory construction unit includes：Correcting process subelement, for student
Behavior initial track model is modified processing, specifically, when different location information occurs in synchronization, then needs before and after
The position relationship of event, inferred position reasonability preserve correct position, when the location information missing at a certain moment, then according to it
Its event information deduction should occur being location information, when the location information that certain event should occur with reality location information run counter to,
Then according to front and rear event and the reasonability of location logic calculation position and event, event base is established；Complete trajectory model construction
Unit, for building students ' behavior complete trajectory model.
Implement the present invention, have the advantages that：
The present invention by obtaining under campus environment data in each data system, perceive and cleaning initial data in crucial number
According to field, action trail model critical data is formed, while be associated with by multi-dimensional data, logic judgment error correction, data depth
The big datas technologies such as excavation, so as to describe the students ' behavior track in campus environment, and with the Perspective Analysis group track of group
Feature describes group behavior track in environment, realizes the description to the real behavior in track and the early warning to abnormal behaviour.
Description of the drawings
Fig. 1 is that the present invention is based on the first embodiment flows of the discovery method of campus big data environment Students ' action trail
Figure；
Fig. 2 is that the present invention is based on the second embodiment flows of the discovery method of campus big data environment Students ' action trail
Figure；
Fig. 3 is that the present invention is based on the first embodiment structures of the discovery system of campus big data environment Students ' action trail
Schematic diagram；
Fig. 4 is that the present invention is based on the second embodiment structures of the discovery system of campus big data environment Students ' action trail
Schematic diagram；
The schematic diagram of processing is associated in Fig. 5 present invention to system data.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, the present invention is made into one below in conjunction with attached drawing
Step ground detailed description.Only this is stated, appearance in the text of the invention or the side such as the up, down, left, right, before and after that will occur, inside and outside
Position word is not the specific restriction to the present invention only on the basis of the attached drawing of the present invention.
Referring to Fig. 1, Fig. 1 shows that the present invention is based on the of the discovery method of campus big data environment Students ' action trail
One embodiment flow chart, including：
S101 obtains the system data of each data system in campus environment.
The data system can be in card system, wireless WiFi system, wired network system, information network calling
System, access control system, dormitory duct device system, school business management system, network authentication and auditing system etc. are felt concerned about, but not limited to this
System.
Correspondingly, the system data be then the temporal information extracted from data system, location information, basic information and
Behavior act information, system that but not limited to this.Specifically, can by card system, access control system, dormitory duct device system,
Wireless WIFI systems etc. obtain location information, and the basic information of student is obtained by school business management system, by network authentication and
Auditing system records and obtains student terminal facility information (physical address and unit type).
S102, starts the cleaning processing system data and association process, forms action trail model critical data；
Quantization and standardization including data are started the cleaning processing to system data.For example, daily record data, needs to daily record
File carries out text and semantic analysis, by using the tool that the big data management platform that this project uses provides, parses daily record
Critical field forms structuring, the daily record data of standardization.
Referring to Fig. 5, it is also necessary to processing (association analysis and comparative analysis) is associated to system data, such as：
A, the internet records of wireless WIFI systems are acquired, and judge that account information whether there is according to internet records；
If b, account information is not present, using physical address information, remember if physical address exists with student account
Record is then written, and is separately deposited as there is no if；
If c, account exists, directly it is put in storage, while incremental update physical address library, safeguards that student learns work number and physics
The binding relationship of address show that student learns the correspondence of work number and physical address.
S103 builds students ' behavior initial track model according to action trail model critical data；
S104 is modified students ' behavior initial track model processing, forms students ' behavior complete trajectory model.
It should be noted that it can describe associated location information and action message according to temporal information, judge students ' behavior
Track, the analysis and track for realizing real behavior distinguish.Specifically, it is described that place is modified to students ' behavior initial track model
The method of reason includes：
When different location information occurs in synchronization, then the position relationship according to front and rear event is needed, inferred position is reasonable
Property, preserve correct position；
When the location information missing at a certain moment, then should occur being location information according to the deduction of other event informations；
When the location information that certain event should occur and reality location information run counter to, then according to front and rear event and location logic
Calculation position and the reasonability of event, establish event base.
Referring to Fig. 2, Fig. 2 shows that the present invention is based on the of the discovery method of campus big data environment Students ' action trail
Two embodiment flow charts, including：
S201 obtains the system data of each data system in campus environment.
S202, starts the cleaning processing system data and association process, forms action trail model critical data；
S203 builds students ' behavior initial track model according to action trail model critical data；
S204 is modified students ' behavior initial track model processing, forms students ' behavior complete trajectory model.
S205 presets students ' behavior abnormality alarming model and student group event alarm model；According to students ' behavior exception
Alarm model and students ' behavior complete trajectory model judge whether that student's abnormal behavior event occurs；It is accused according to student group event
Alert model and students ' behavior complete trajectory model judge whether that student's social event occurs.
In self-defined monitoring population profile or acquiescence school, row of the track using the same period as dimension is established
For with trajectory analysis model, judge student group behavior, such as：Same or similar case behavior, same or analogous location (define phase
Like range value, acquiescence is less than or equal in 100 meters) behavior；Students ' behavior exception and social event behavioural characteristic library are established, is passed through
Matching Model generates early warning to the behavior and feature database comparison of generation.The self-defined group behavior visual control, can basis
Student's build-in attribute label nationality, gender, category filter is checked with cultivating level and source of students.
Furthermore it is also possible to warning information push is carried out to students ' behavior anomalous event and student group event, including to learning
Raw abnormal behaviour event and the behavior of student group event are pushed to administrative staff, can support the modes such as public platform, short message, mail.
S206 extracts students ' behavior track from students ' behavior complete trajectory model according to period dimension and is shown.
The personal track inquiry based on period dimension can be achieved in the present invention, specifically, can pass through the students such as title, institute
Information inquires specific personal action trail path, sequentially in time, the time of the display each tracing point of student, place, work
Dynamic content.
S207 builds student's thermodynamic chart according to location information.
The present invention describes analyzed area position and student by way of showing form for geographical location based on Baidu map
Group activity and density relationship are showed using the form of thermodynamic chart, can amplify with map and visual angle is checked in diminution.Simultaneously including base
In building or divided area, student position and density are showed in a manner that bubble is subject to data markers, building floor can be refine to
And room detailed data.
Referring to Fig. 3, Fig. 3 is that the present invention is based on the of the discovery system 100 of campus big data environment Students ' action trail
One embodiment, the present invention include：
Acquiring unit 1, for obtaining the system data of each data system in campus environment.The data system can be one
Cartoon system, wireless WiFi system, wired network system, information network call center system, access control system, dormitory channel machine system
System, school business management system, network authentication and auditing system etc., system that but not limited to this.Correspondingly, the system data be then from
Temporal information, location information, basic information and the behavior act information extracted in data system, system that but not limited to this.Specifically
Ground can obtain location information by card system, access control system, dormitory duct device system, wireless WIFI systems etc., pass through school
Management system of being engaged in obtains the basic information of student, records and obtain student terminal facility information by network authentication and auditing system
(physical address and unit type).
It should be noted that acquiring unit is by using platform tools and each operation system data-interface or using JDBC etc.
Database connection mode establishes data connection, and analysis data characteristics defines the frequency acquisition of each data of acquisition platform, and monitoring is entire
Gatherer process；The startup and stopping of executable acquisition, the operations such as filling mining again, and by the data of acquisition with full dose initial data lattice
Formula deposit data warehouse (structural data is stored using Hive, hot spot data and requires storing using Hbase for arithmetic speed,
Unstructured data is stored using HDFS).
Data extracting unit 2 for being started the cleaning processing to system data and association process, forms action trail model and closes
Key data.
Quantization and standardization including data are started the cleaning processing to system data.For example, daily record data, needs to daily record
File carries out text and semantic analysis, by using the tool that the big data management platform that this project uses provides, parses daily record
Critical field forms structuring, the daily record data of standardization.
In addition, it is also necessary to processing (association analysis and comparative analysis) is associated to system data, such as：A, acquisition is wireless
The internet records of WIFI systems, and judge that account information whether there is according to internet records；If b, account information is not present,
Using physical address information, be written if physical address has record with student account, separately deposited as there is no if；If c, account
Number exist, be then directly put in storage, while incremental update physical address library, safeguard the binding relationship of student's work number and physical address,
Show that student learns the correspondence of work number and physical address.
Initial track construction unit 3, for building students ' behavior initial track mould according to action trail model critical data
Type.
Complete trajectory construction unit 4 for being modified processing to students ' behavior initial track model, forms students ' behavior
Complete trajectory model.Complete trajectory construction unit can be described associated location information and action message, sentence according to temporal information
Disconnected students ' behavior track, the analysis and track for realizing real behavior distinguish.
The complete trajectory construction unit 4 includes：
Correcting process subelement, for being modified processing to students ' behavior initial track model, specifically, when same a period of time
It carving and has showed different location information, then need the position relationship according to front and rear event, inferred position reasonability preserves correct position,
When the location information missing at a certain moment, then should occur being location information according to the deduction of other event informations, when certain event should go out
Existing location information and the location information of reality are runed counter to, then according to the reasonable of front and rear event and location logic calculation position and event
Property, establish event base；
Complete trajectory model construction subelement, for building students ' behavior complete trajectory model.
Referring to Fig. 4, Fig. 4 is that the present invention is based on the of the discovery system 100 of campus big data environment Students ' action trail
Two embodiments unlike first embodiment shown in Fig. 3, are based on campus big data environment Students ' described in the present embodiment
The discovery system 100 of action trail, further includes：
Model construction unit 5 is alerted, for presetting students ' behavior abnormality alarming model and student group event alarm model；
Anomalous event monitoring unit 6, for according to students ' behavior abnormality alarming model and students ' behavior complete trajectory model
Judge whether that student's abnormal behavior event occurs；
Social event monitoring unit 7, for according to student group event alarm model and students ' behavior complete trajectory model
Judge whether that student's social event occurs.
It should be noted that in alarm model construction unit, anomalous event monitoring unit and social event monitoring unit
With reference under, user can establish track using the same period as dimension in self-defined monitoring population profile or acquiescence school
The behavior of degree and trajectory analysis model, judge student group behavior, such as：Same or similar case behavior, same or analogous location
(defining similar range value, acquiescence is less than or equal in 100 meters) behavior；Establish students ' behavior exception and social event behavioural characteristic
By Matching Model, early warning is generated to the behavior and feature database comparison of generation for library.The self-defined group behavior visualization prison
Control according to student's build-in attribute label nationality, gender, culture level and source of students can be checked category filter.It is furthermore it is also possible to right
Students ' behavior anomalous event and student group event carry out warning information push, including to student's abnormal behaviour event and student group
The behavior of body event is pushed to administrative staff, can support the modes such as public platform, short message, mail.
Further, the discovery system based on campus big data environment Students ' action trail, further includes：Display unit
8, it is shown for extracting students ' behavior track from students ' behavior complete trajectory model according to period dimension.The present invention can
It realizes the personal track inquiry based on period dimension, specifically, specific can be inquired by student informations such as title, institutes
The action trail path of people, sequentially in time, the time of the display each tracing point of student, place, activity description.
In addition, the discovery system based on campus big data environment Students ' action trail, further includes thermodynamic chart unit
9, for building student's thermodynamic chart according to location information.The present invention for geographical location based on Baidu map by showing the side of form
Formula is described analyzed area position and student's collective exercise and density relationship, is showed using the form of thermodynamic chart, can amplified with map
Visual angle is checked with diminution.Simultaneously including based on building or divided area, student position is showed in a manner that bubble is subject to data markers
It puts and density, building floor and room detailed data can be refine to.
From the foregoing, it will be observed that the present invention by obtaining under campus environment data in each data system, perceives and cleaning original number
According to middle critical data field, action trail model critical data is formed, while be associated with by multi-dimensional data, logic judgment entangles
The big datas technology such as mistake, data depth excavation, so as to describe the students ' behavior track in campus environment, and with the visual angle of group point
Group's track characteristic is analysed, describes group behavior track in environment, realizes the description to the real behavior in track and to abnormal row
For early warning.
The above is the preferred embodiment of the present invention, it is noted that for those skilled in the art
For, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also considered as
Protection scope of the present invention.
Claims (10)
- A kind of 1. discovery method based on campus big data environment Students ' action trail, which is characterized in that including：The system data of each data system in campus environment is obtained, the system data includes temporal information, location information, basis Information and behavior act information；System data is started the cleaning processing and association process, form action trail model critical data；Students ' behavior initial track model is built according to action trail model critical data；Processing is modified to students ' behavior initial track model, forms students ' behavior complete trajectory model.
- 2. the discovery method as described in claim 1 based on campus big data environment Students ' action trail, which is characterized in that It further includes：Default students ' behavior abnormality alarming model and student group event alarm model；Judged whether that student's abnormal behavior thing occurs according to students ' behavior abnormality alarming model and students ' behavior complete trajectory model Part；Judged whether that student's social event occurs according to student group event alarm model and students ' behavior complete trajectory model.
- 3. the discovery method as described in claim 1 based on campus big data environment Students ' action trail, which is characterized in that It further includes：Students ' behavior track is extracted according to period dimension from students ' behavior complete trajectory model to be shown.
- 4. the discovery method as described in claim 1 based on campus big data environment Students ' action trail, which is characterized in that It further includes：Student's thermodynamic chart is built according to location information.
- 5. the discovery method as described in claim 1 based on campus big data environment Students ' action trail, which is characterized in that The method for being modified processing to students ' behavior initial track model includes：When different location information occurs in synchronization, then the position relationship according to front and rear event is needed, inferred position reasonability is protected Deposit correct position；When the location information missing at a certain moment, then should occur being location information according to the deduction of other event informations；When the location information of the location information that certain event should occur and reality is runed counter to, then calculated according to front and rear event and location logic Position and the reasonability of event, establish event base.
- 6. a kind of discovery system based on campus big data environment Students ' action trail, which is characterized in that including：Acquiring unit, for obtaining the system data of each data system in campus environment, the system data include temporal information, Location information, basic information and behavior act information；Data extracting unit for being started the cleaning processing to system data and association process, forms action trail model key number According to；Initial track construction unit, for building students ' behavior initial track model according to action trail model critical data；For being modified processing to students ' behavior initial track model, it is complete to form students ' behavior for complete trajectory construction unit Locus model.
- 7. the discovery system as claimed in claim 6 based on campus big data environment Students ' action trail, which is characterized in that It further includes：Model construction unit is alerted, for presetting students ' behavior abnormality alarming model and student group event alarm model；Anomalous event monitoring unit, for being according to students ' behavior abnormality alarming model and the judgement of students ' behavior complete trajectory model No generation student's abnormal behavior event；Social event monitoring unit, for being according to student group event alarm model and the judgement of students ' behavior complete trajectory model No generation student's social event.
- 8. the discovery system as claimed in claim 6 based on campus big data environment Students ' action trail, which is characterized in that It further includes：Display unit, for extracted from students ' behavior complete trajectory model according to period dimension students ' behavior track into Row display.
- 9. the discovery system as claimed in claim 6 based on campus big data environment Students ' action trail, which is characterized in that Thermodynamic chart unit is further included, for building student's thermodynamic chart according to location information.
- 10. the discovery system as claimed in claim 6 based on campus big data environment Students ' action trail, feature exist In the complete trajectory construction unit includes：Correcting process subelement, for being modified processing to students ' behavior initial track model, specifically, when synchronization goes out Different location information is showed, has then needed the position relationship according to front and rear event, inferred position reasonability preserves correct position, when certain The location information missing at one moment, then should occur being location information, should occur when certain event according to the deduction of other event informations Location information and the location information of reality are runed counter to, then according to front and rear event and the reasonability of location logic calculation position and event, Establish event base；Complete trajectory model construction subelement, for building students ' behavior complete trajectory model.
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| CN108876182A (en) * | 2018-07-02 | 2018-11-23 | 泛亚汽车技术中心有限公司 | Wisdom garden system and working method based on thermodynamic chart |
| CN109034731A (en) * | 2018-07-02 | 2018-12-18 | 泛亚汽车技术中心有限公司 | Dynamic Data Processing system and method for garden staff's benefits |
| CN109523442A (en) * | 2018-12-21 | 2019-03-26 | 广东粤众互联信息技术有限公司 | A kind of big data analysis method based on campus education system |
| CN109636688A (en) * | 2018-12-11 | 2019-04-16 | 武汉文都创新教育研究院（有限合伙） | A kind of students ' behavior analysis system based on big data |
| CN109636062A (en) * | 2018-12-25 | 2019-04-16 | 湖北工业大学 | A kind of students ' behavior analysis method and system based on big data analysis |
| CN109684514A (en) * | 2018-12-11 | 2019-04-26 | 武汉文都创新教育研究院（有限合伙） | Students ' behavior positioning system and method based on track data |
| CN110072191A (en) * | 2019-04-23 | 2019-07-30 | 安徽致远慧联电子科技有限公司 | Track analysis system and analysis method in school based on wireless technology |
| CN111163424A (en) * | 2019-12-31 | 2020-05-15 | 重庆和贯科技有限公司 | Student behavior track positioning system and method based on campus big data |
| CN111325153A (en) * | 2020-02-21 | 2020-06-23 | 青岛联合创智科技有限公司 | Student behavior characteristic intelligent analysis method based on multidimensional data |
| CN111611235A (en) * | 2020-05-27 | 2020-09-01 | 华中师范大学 | Student space-time model based on campus WiFi big data and data cleaning method |
| CN117094685A (en) * | 2023-10-18 | 2023-11-21 | 深圳市智慧建筑创新有限公司 | Intelligent campus monitoring data management system based on Internet of things technology |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108876182A (en) * | 2018-07-02 | 2018-11-23 | 泛亚汽车技术中心有限公司 | Wisdom garden system and working method based on thermodynamic chart |
| CN109034731A (en) * | 2018-07-02 | 2018-12-18 | 泛亚汽车技术中心有限公司 | Dynamic Data Processing system and method for garden staff's benefits |
| CN109636688A (en) * | 2018-12-11 | 2019-04-16 | 武汉文都创新教育研究院（有限合伙） | A kind of students ' behavior analysis system based on big data |
| CN109684514A (en) * | 2018-12-11 | 2019-04-26 | 武汉文都创新教育研究院（有限合伙） | Students ' behavior positioning system and method based on track data |
| CN109523442A (en) * | 2018-12-21 | 2019-03-26 | 广东粤众互联信息技术有限公司 | A kind of big data analysis method based on campus education system |
| CN109636062A (en) * | 2018-12-25 | 2019-04-16 | 湖北工业大学 | A kind of students ' behavior analysis method and system based on big data analysis |
| CN110072191A (en) * | 2019-04-23 | 2019-07-30 | 安徽致远慧联电子科技有限公司 | Track analysis system and analysis method in school based on wireless technology |
| CN110072191B (en) * | 2019-04-23 | 2021-01-12 | 安徽致远慧联电子科技有限公司 | Student in-school trajectory analysis system and method based on wireless technology |
| CN111163424A (en) * | 2019-12-31 | 2020-05-15 | 重庆和贯科技有限公司 | Student behavior track positioning system and method based on campus big data |
| CN111325153A (en) * | 2020-02-21 | 2020-06-23 | 青岛联合创智科技有限公司 | Student behavior characteristic intelligent analysis method based on multidimensional data |
| CN111325153B (en) * | 2020-02-21 | 2023-05-12 | 青岛联合创智科技有限公司 | Student behavior feature intelligent analysis method based on multidimensional data |
| CN111611235A (en) * | 2020-05-27 | 2020-09-01 | 华中师范大学 | Student space-time model based on campus WiFi big data and data cleaning method |
| CN117094685A (en) * | 2023-10-18 | 2023-11-21 | 深圳市智慧建筑创新有限公司 | Intelligent campus monitoring data management system based on Internet of things technology |
| CN117094685B (en) * | 2023-10-18 | 2024-01-12 | 深圳市智慧建筑创新有限公司 | Intelligent campus monitoring data management system based on Internet of things technology |
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