CN111163424A - Student behavior track positioning system and method based on campus big data - Google Patents
Student behavior track positioning system and method based on campus big data Download PDFInfo
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Abstract
The application provides a student's action orbit positioning system based on campus big data, the system includes: the data acquisition terminal is in communication connection with the data storage processing platform through the communication unit; also provided is a student behavior trajectory localization method based on campus big data, the method comprising S1: acquiring behavior data of each data system in a campus environment, wherein the behavior data comprises time information, position information and behavior action information; s2: cleaning and managing the behavior data to form behavior track model key data; s3: constructing an initial track of student behavior according to the key data; s4: and correcting the initial trajectory to form a student behavior correction trajectory. According to the invention, the behavior tracks of students are obtained by processing multi-dimensional data such as a UWB positioning system, a face recognition system, a campus card and the like in a campus environment.
Description
Technical Field
The invention relates to the field of data processing, in particular to a student behavior trajectory positioning system and method based on campus big data.
Background
Under the background of rapid development of big data technology, data value is more important, people are in the era of information explosion nowadays, information is pursued and searched, the stage of screening, processing and analyzing a large amount of complex and exponentially-increased data is developed, many companies are using big data and cloud computing as long-distance development strategies and new business growth points of the companies, the education industry is no exception, how to apply the big data technology to a campus environment to assist the safety management of students, as is well known, the safety of the students is the most important ring of the campus management, and no matter schools or parents of the students, people hope to know whether the students are in schools, on time classes, on time beddings and the like by capturing behavior information of the students. At present, the application of campus big data is mainly divided into decision support application of big data, user behavior habit analysis and portrait description, safety and early warning, intelligent knowledge retrieval and recommendation and the like. The application in the above directions is not really mature application and popularization in the research stage, and meanwhile, the model and application do not have very characteristic contents, and the model and application discovered based on the student behavior track of the campus data are not appeared. Nor do there exist big data applications for reasonable and mature student behavior trace discovery and analysis.
Therefore, a student behavior trajectory positioning system and a positioning method based on big data are needed.
Disclosure of Invention
In view of this, the present application provides a student behavior trajectory positioning system and method based on campus big data to solve the deficiencies of the prior art.
The invention provides a student behavior track positioning system based on campus big data, which is characterized in that: the method comprises the following steps: the data acquisition terminal is in communication connection with the data storage processing platform through the communication unit;
the data acquisition terminal comprises a UWB positioning tag, a UWB positioning base station and a high-definition camera, wherein the UWB positioning tag is carried by a student and used for the UWB positioning base station to identify the position, and the high-definition camera is used for acquiring image information of the student;
the communication unit comprises a first communication unit and a second communication unit, the UWB positioning base station is connected with the data storage processing platform through the first communication unit, and the high-definition camera is connected with the data storage processing platform through the second communication unit;
the data storage processing platform comprises a server, a data storage unit and a data processing unit, wherein the server is in communication connection with the first communication unit and the second communication unit and is used for receiving real-time data acquired by the data acquisition terminal, the data storage unit is in communication connection with the server, and the data processing unit is in communication connection with the server;
the data processing unit comprises an initial track generating unit and a corrected track generating unit, and the initial track generating unit and the corrected track generating unit are both in communication connection with the server.
Further, the data processing unit further comprises an abnormal event warning unit, and the abnormal event warning unit is in communication connection with the server.
Further, the data processing unit also comprises a group event alarm unit which is in communication connection with the server.
Furthermore, the data storage processing platform further comprises a display unit, and the input end of the display unit is connected with the output end of the server.
Correspondingly, the invention also provides a student behavior track positioning method based on campus big data, which is characterized by comprising the following steps: the method specifically comprises the following steps:
s1: acquiring behavior data of each data system in a campus environment, wherein the behavior data comprises time information, position information and behavior action information;
s2: cleaning and managing the behavior data to form behavior track model key data;
s3: constructing an initial track of student behavior according to the key data;
s4: and correcting the initial trajectory to form a student behavior correction trajectory.
Further, the step of correcting the initial trajectory specifically includes the following steps:
when the same student at the same time and the UWB positioning information is inconsistent with the image identification information, correcting the correct position by taking the data of the image identification information as a standard, and establishing an event library;
when the position information is lost at a certain moment, the corresponding position information is deduced according to other event information.
Further, the method also comprises the step of judging whether behavior abnormity exists according to the processing of the corrected track, if so, sending out alarm information, and if not, not sending out the alarm information.
Further, the behavior abnormity judgment comprises the step of comparing the corrected track with a preset abnormal learning behavior track, and if the ratio of inconsistent data is lower than a preset threshold value, the behavior is normal; if not, the behavior is abnormal.
Further, the method further comprises the step of comparing the corrected track with a preset student group track, if inconsistent data are lower than a preset threshold value, a group event occurs, and if not, the group event occurs and warning information is sent out.
The invention has the beneficial technical effects that: according to the invention, multidimensional data such as a UWB positioning system, a face recognition system and a campus card under a campus environment are obtained, key data fields in original data are extracted and cleaned to form behavior track model key data, and meanwhile, student behavior tracks in the campus environment are formed through big data technologies such as multidimensional data association, logic judgment error correction and data depth mining; and the campus safety early warning is realized through abnormal behavior analysis.
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The invention is further described below with reference to the following figures and examples:
fig. 1 is a block diagram of the mechanism of the present invention.
Fig. 2 is a block diagram of the first embodiment of the present invention.
FIG. 3 is a flow chart of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings in which:
the invention provides a student behavior track positioning system based on campus big data, which is characterized in that: as shown in fig. 1, includes: the data acquisition terminal is in communication connection with the data storage processing platform through the communication unit;
the data acquisition terminal comprises a UWB positioning tag, a UWB positioning base station and a high-definition camera, wherein the UWB positioning tag is carried by a student and used for the UWB positioning base station to identify the position, and the high-definition camera is used for acquiring image information of the student; the UWB positioning tags are carried by students and used as media for identity identification, and the information of the UWB positioning tags is matched with displacement identification codes of the students in the embodiment, so that the students can be accurately identified through the UWB positioning tags; the UWB positioning base station is set by the positioning accuracy of a target school and the requirements of a specific positioning place, such as a classroom, a dormitory, a playground, a dining hall, a corridor, a corner and the outside of the school, and is set by the positioning requirements of the target school, so that the action tracks of students in the school can be positioned, and basic data is provided for the subsequent track generation; the high-definition camera adopts the existing camera, and image information acquired by the high-definition camera and a background image identification system perform secondary authentication on UWB positioning, so that student positioning information is verified and corrected in multiple dimensions; meanwhile, behavior information of students is collected through a camera; the system also comprises an image recognition system, which is used for recognizing the shot image and realizing the matching of the image and the student, wherein the image recognition system adopts the existing image recognition software, such as the existing face recognition software, and the details are not repeated;
the communication unit comprises a first communication unit and a second communication unit, the UWB positioning base station is connected with the data storage processing platform through the first communication unit, and the high-definition camera is connected with the data storage processing platform through the second communication unit; the first communication unit and the second communication unit both adopt existing limited communication or wireless communication, such as Zigbee, WIFI and the like, and a person skilled in the art can select a suitable communication mode according to actual needs.
The data storage processing platform comprises a server, a data storage unit and a data processing unit, wherein the server is in communication connection with the first communication unit and the second communication unit and is used for receiving real-time data acquired by the data acquisition terminal, the data storage unit is in communication connection with the server, and the data processing unit is in communication connection with the server; the server adopts the existing server, the data storage unit adopts the existing storage medium, such as a read-only memory or a read-write memory, and the data processing unit adopts the existing singlechip or chip, such as a raspberry computer;
the data processing unit comprises an initial track generating unit and a corrected track generating unit, and the initial track generating unit and the corrected track generating unit are both in communication connection with the server.
According to the invention, multidimensional data such as a UWB positioning system, a face recognition system and a campus card under a campus environment are obtained, key data fields in original data are extracted and cleaned to form behavior track model key data, and meanwhile, student behavior tracks in the campus environment are formed through big data technologies such as multidimensional data association, logic judgment error correction and data depth mining; and the campus safety early warning is realized through abnormal behavior analysis; the student behavior tracks can also be sent to teachers and/or parents, so that the teachers and/or parents can know the behavior of students in schools in real time.
The data processing unit also comprises an abnormal event warning unit which is in communication connection with the server.
The data processing unit also comprises a group event alarm unit which is in communication connection with the server. The abnormal alarm unit and the group event alarm unit both comprise abnormal event model construction and group event model construction, and a user can establish a behavior and trajectory analysis model with a trajectory taking the same time period as a dimension under the condition of self-defining group monitoring or the condition of defaulting all students, and judge the student group behaviors, such as: the same or similar event behaviors, the same or similar position (defining similar range values, and defaulting to be less than or equal to 100 meters) behaviors; and establishing a student behavior abnormity and group event behavior characteristic library, and comparing the generated behaviors with the characteristic library through a matching model to generate early warning. The customized group behaviors are visually monitored and can be classified, screened and checked according to the inherent attribute tags of students, such as nationality, gender, culture level and origin. In addition, the early warning information can be pushed to abnormal events of student behaviors and events of student groups, the abnormal events of student behaviors and events of student groups are pushed to managers, and the modes of public numbers, short messages, mails and the like can be supported.
The data storage processing platform further comprises a display unit, and the input end of the display unit is connected with the output end of the server. According to the method and the system, personal track query based on time period dimensionality can be achieved, specifically, the specific individual behavior track path can be queried through student information such as names and colleges, and the system displays the track information of students, the activity place and the activity duration according to the time sequence.
Correspondingly, the invention also provides a student behavior track positioning method based on campus big data, which is characterized by comprising the following steps: the method specifically comprises the following steps:
s1: acquiring behavior data of each data system in a campus environment, wherein the behavior data comprises time information, position information and behavior action information; the behavior data is used for collecting student behavior information through a UWB positioning system, an image recognition system and a campus card system;
s2: cleaning and managing the behavior data to form behavior track model key data; cleaning and normalizing multi-dimensional information collected by the same student at the same time and the same place, if image equipment information, a campus card and UWB positioning information show that the same student is at the same place at the same time, cleaning the data and leaving primary information of the current time;
s3: constructing an initial track of student behavior according to the key data; constructing the behavior track of the student by taking the time dimension as a reference to form an initial behavior track;
s4: and correcting the initial trajectory to form a student behavior correction trajectory. The initial behavior track may have situations such as inconsistency of multi-dimensional information or information loss, for example, when the UWB positioning track of the student is inconsistent with the track identified by the image, the initial track of the student needs to be corrected to obtain the corrected behavior track. Through above-mentioned technical scheme, can realize the inquiry of the student action orbit based on the time dimension, the school of being convenient for is to student's management, can make things convenient for the head of a family to know student's state in real time simultaneously, effectively avoids the emergence of incident.
In this embodiment, the correcting the initial trajectory specifically includes the following steps:
when the same student at the same time and the UWB positioning information is inconsistent with the image identification information, correcting the correct position by taking the data of the image identification information as a standard, and establishing an event library; if the information is inconsistent, the system records once and pushes the record to a manager, the manager verifies the information, and the processing result is input into the system and archived;
when the position information is lost at a certain moment, the corresponding position information is deduced according to other event information. If information is lost at a certain moment, the track of the current lost information can be deduced through the tracks of the previous moment and the next moment of the lost moment.
In this embodiment, the method further includes determining whether a behavior abnormality exists according to the processing of the corrected trajectory, and if so, sending out warning information, and if not, not generating the warning information.
In this embodiment, the behavior abnormality determination includes comparing the corrected trajectory with a preset learning behavior abnormality trajectory, and if the ratio of inconsistent data is lower than a preset threshold, the behavior is normal; if not, the behavior is abnormal.
In this embodiment, the method further includes comparing the corrected trajectory with a preset student group trajectory, if the inconsistent data is lower than a preset threshold, determining that a group event occurs, and if not, generating the group event and sending out warning information.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (9)
1. The utility model provides a student's action orbit positioning system based on campus big data which characterized in that: the method comprises the following steps: the data acquisition terminal is in communication connection with the data storage processing platform through the communication unit;
the data acquisition terminal comprises a UWB positioning tag, a UWB positioning base station and a high-definition camera, wherein the UWB positioning tag is carried by a student and used for the UWB positioning base station to identify the position, and the high-definition camera is used for acquiring image information of the student;
the communication unit comprises a first communication unit and a second communication unit, the UWB positioning base station is connected with the data storage processing platform through the first communication unit, and the high-definition camera is connected with the data storage processing platform through the second communication unit;
the data storage processing platform comprises a server, a data storage unit and a data processing unit, wherein the server is in communication connection with the first communication unit and the second communication unit and is used for receiving real-time data acquired by the data acquisition terminal, the data storage unit is in communication connection with the server, and the data processing unit is in communication connection with the server;
the data processing unit comprises an initial track generating unit and a corrected track generating unit, and the initial track generating unit and the corrected track generating unit are both in communication connection with the server.
2. The campus big data based student behavior track positioning system of claim 1, wherein: the data processing unit also comprises an abnormal event warning unit which is in communication connection with the server.
3. The campus big data based student behavior track positioning system of claim 1, wherein: the data processing unit also comprises a group event alarm unit which is in communication connection with the server.
4. The campus big data based student behavior track positioning system of claim 1, wherein: the data storage processing platform further comprises a display unit, and the input end of the display unit is connected with the output end of the server.
5. A student behavior track positioning method based on campus big data is characterized by comprising the following steps: the method specifically comprises the following steps:
s1: acquiring behavior data of each data system in a campus environment, wherein the behavior data comprises time information, position information and behavior action information;
s2: cleaning and managing the behavior data to form behavior track model key data;
s3: constructing an initial track of student behavior according to the key data;
s4: and correcting the initial trajectory to form a student behavior correction trajectory.
6. The campus big data-based student behavior track positioning method as claimed in claim 5, wherein: the step of correcting the initial trajectory specifically comprises the following steps:
when the same student at the same time and the UWB positioning information is inconsistent with the image identification information, correcting the correct position by taking the data of the image identification information as a standard, and establishing an event library;
when the position information is lost at a certain moment, the corresponding position information is deduced according to other event information.
7. The campus big data-based student behavior track positioning method as claimed in claim 5, wherein: and judging whether behavior abnormity exists according to the processing of the corrected track, if so, sending out alarm information, and if not, generating no alarm information.
8. The campus big data-based student behavior track positioning method as claimed in claim 7, wherein: the behavior abnormity judgment comprises the step of comparing the corrected track with a preset learning behavior abnormity track, and if the ratio of inconsistent data is lower than a preset threshold value, the behavior is normal; if not, the behavior is abnormal.
9. The campus big data-based student behavior track positioning method as claimed in claim 5, wherein: the method further comprises the step of comparing the corrected track with a preset student group track, if inconsistent data is lower than a preset threshold value, a group event occurs, and if not, the group event occurs and warning information is sent out.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112351256A (en) * | 2020-11-04 | 2021-02-09 | 南京微研网络科技有限公司 | Smart campus management system and management method thereof |
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Application publication date: 20200515 |