CN114462981A - College student identification method and system based on Internet of things and readable storage medium - Google Patents
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Abstract
The invention discloses a college student identification method, a college student identification system and a readable storage medium based on the Internet of things, wherein the method comprises the following steps: acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data; identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range; identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range; and after the user data information is subjected to screening processing, extracting stored data as first data. According to the method and the system, the data of the user can be collected based on the Internet of things for analysis, the type of the colleges to which the identity matching information corresponding to the user belongs can be analyzed by utilizing the path, the age and the parking time, the annual statistics can be carried out on the colleges by utilizing the table visualization, and the identity attribution of the colleges is clearly shown.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to a college student identification method and system based on the Internet of things and a readable storage medium.
Background
The internet of things, namely the internet connected with everything, is an extended and expanded network on the basis of the internet, various information sensing devices are combined with the network to form a huge network, and the interconnection and the intercommunication of people, machines and things at any time and any place are realized.
At the present stage, the method becomes a popular research direction based on the internet of things and big data analysis, and the colleges and universities are open, so that the identities of the colleges and universities are identified, and the learning tracks of the colleges and universities are recorded in the form of years, months and days, so that the method becomes a research direction for the data analysis of the colleges and universities.
Disclosure of Invention
In view of the foregoing problems, an object of the present invention is to provide a college identification method and system based on the internet of things, and a readable storage medium, which can analyze data collected by a user based on the internet of things, analyze the college type of identity matching information corresponding to the user by using a path, an age, and a parking time, and clearly show the identity affiliation of the college.
The invention provides a college student identification method based on the Internet of things, which comprises the following steps:
acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range;
identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range;
and after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the user based on the first data, wherein the school information is subjected to identity information matching so as to finish the identification of the colleges and universities.
In this scheme, the obtaining of the user data information, where the user data information includes user path data and user internet of things data, specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
In this scheme, the age data in the user data information is identified, and the users whose age data is not within the preset age threshold range are rejected, specifically including:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
In the scheme, for the college students in different age groups, the age attributes of the college students are annotated in advance, and the school identity attribution information corresponding to the college students is directly identified based on the annotation information.
In this scheme, the identifying and removing the path records in the path data within the non-preset campus range, and identifying the name of the school to which the current path belongs based on the path records within the preset campus range specifically include:
extracting user data with the age data within the preset age threshold range as second data;
identifying the path data of the corresponding user based on the second data, and further eliminating the path data which is not located in a preset campus range to obtain a college path corresponding to the user;
and identifying the type of the colleges and universities which the user approaches based on the college path, and identifying the school name of each college and universities.
In this scheme, treat after user data information does the screening process, extract the data that exist and regard as first data, based on first data identification user school information carry out identity information matching, in order to accomplish college student's discernment specifically includes:
slicing according to preset time based on the first data, and identifying the staying time of each user in different schools within the preset time;
recording the residence time, extracting the school with the longest residence time in a single day as the calendar matching data, and further acquiring the weekly schedule, the monthly schedule and the annual schedule.
And performing merging operation based on the chronology, and extracting the school with the largest school occurrence frequency sequence corresponding to the calendar matching data as the identity matching information corresponding to the user.
The second aspect of the present invention further provides an internet of things-based college student identification system, which includes a memory and a processor, wherein the memory includes an internet of things-based college student identification method program, and when the processor executes the internet of things-based college student identification method program, the following steps are implemented:
acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range;
identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range;
and after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the user based on the first data, wherein the school information is subjected to identity information matching so as to finish the identification of the colleges and universities.
In this scheme, the obtaining of the user data information, where the user data information includes user path data and user internet of things data, specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
In this scheme, the age data in the user data information is identified, and the users whose age data is not within the preset age threshold range are rejected, specifically including:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
In the scheme, for the college students in different age groups, the age attributes of the college students are annotated in advance, and the school identity attribution information corresponding to the college students is directly identified based on the annotation information.
In this scheme, the identifying and removing the path records in the path data within the non-preset campus range, and identifying the name of the school to which the current path belongs based on the path records within the preset campus range specifically include:
extracting user data with the age data within the preset age threshold range as second data;
identifying the path data of the corresponding user based on the second data, and further eliminating the path data which is not located in a preset campus range to obtain a college path corresponding to the user;
and identifying the type of the colleges and universities which the user approaches based on the college path, and identifying the name of the school of each college and university.
In this scheme, treat after user data information does the screening process, extract the data that exist and regard as first data, based on first data identification user school information carry out identity information matching, in order to accomplish college student's discernment specifically includes:
slicing according to preset time based on the first data, and identifying the staying time of each user in different schools within the preset time;
recording the residence time, extracting the school with the longest residence time in a single day as the calendar matching data, and further acquiring the weekly schedule, the monthly schedule and the annual schedule.
And performing merging operation based on the chronology, and extracting the school with the largest school occurrence frequency sequence corresponding to the calendar matching data as the identity matching information corresponding to the user.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a college identification method based on the internet of things of a machine, and when the program of the college identification method based on the internet of things is executed by a processor, the steps of the college identification method based on the internet of things as described in any one of the above are implemented.
The college student identification method, the college student identification system and the readable storage medium based on the Internet of things can analyze data of users collected based on the Internet of things, analyze the college types of identity matching information corresponding to the users by using paths, ages and parking time, perform annual statistics on the college students by using table visualization, and clearly show the identity affiliation of the college students.
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Fig. 1 shows a flow chart of a college student identification method based on the internet of things of the invention;
fig. 2 shows a block diagram of an internet of things-based college student identification system of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flowchart of a college student identification method based on the internet of things.
As shown in fig. 1, the application discloses a college student identification method based on the internet of things, which comprises the following steps:
s102, acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
s104, identifying age data in the user data information, and rejecting users of which the age data is not within a preset age threshold range;
s106, identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying the name of a school to which the current path belongs based on the path records in the preset campus range;
and S108, after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the school information of the user based on the first data to perform identity information matching so as to finish the identification of colleges and universities.
It should be noted that, in this embodiment, a mobile device carried by a college student may access an internet of things, and further may obtain the user data information corresponding to the college student, and based on the extraction of the user path data and the user internet of things card data, the user path data is used to identify a path of a current user in a preset college, the internet of things card data is used to identify an identification when the current user accesses the internet of things, further, data that is not in a preset college range in the user path data is deleted, the age data in the user data information may also be extracted, users that do not conform to the age threshold range in the college are also removed to retain the remaining to-be-processed college student data, and after the user data information is screened, the to-be-processed college student data is extracted as the first data, and then identifying the type of the colleges and universities to which the current user belongs based on the first data to perform matching so as to finish the identity identification of the colleges and universities of the current user.
According to the embodiment of the present invention, the obtaining of the user data information, where the user data information includes user path data and user internet of things card data, specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
It should be noted that, in this embodiment, in view of the above mobile device capable of accessing the internet of things, the mobile device is in communication connection to obtain the user data information corresponding to the user wearing the mobile device, and further distinguish data types to obtain the user path data, the internet of things card data, the age data, and the like, and the user path data, the internet of things card data, the age data, and the like are visualized in a table form to enhance display.
According to the embodiment of the present invention, the identifying age data in the user data information and rejecting users whose age data is not within a preset age threshold specifically includes:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
It should be noted that, by determining the age value based on the age data, and because the general age distribution of high school students has stability, the age threshold range may be obtained by clustering with respect to the age limit ranges corresponding to different schools, for example, the age distribution of the school a is limited to "18-28" years, the age distribution of the school B is "18-22" years, and the age distribution of the school C is "16-32", so that the obtained age threshold range may be "16-32" years, and users whose age value identified in the high school internet of things is not within the age threshold range may be rejected, so as to reduce the data processing amount, improve the data processing capability, and synchronously reject other information together with rejected users who do not meet the requirements for age.
According to the embodiment of the invention, for the college students in the cross-age group, the age attributes of the college students are annotated in advance, and the school identity attribution information of the college students is directly identified based on the annotation information.
It should be noted that, in this embodiment, although the general senior citizen age distribution has stability, it does not exclude that some students in special age groups read, and for the students in these special age groups, they will annotate their age attributes when entering school, so that the identity of their senior citizens can be directly identified based on the annotation information, and then the school identity attribution information can be identified.
According to the embodiment of the present invention, the identifying and removing the path records in the path data, which are not within the preset campus range, and identifying the name of the school to which the current path belongs based on the path records within the preset campus range specifically include:
extracting user data with the age data within the preset age threshold range as second data;
identifying the path data of the corresponding user based on the second data, and further eliminating the path data which is not located in a preset campus range to obtain a college path corresponding to the user;
and identifying the type of the colleges and universities which the user approaches based on the college path, and identifying the school name of each college and universities.
It should be noted that after classifying ages, the user data whose age data is within the preset age threshold range is extracted to serve as the second data, and further, the path data recorded by the user in the second data is classified, and the path records not within the preset campus range are removed to obtain the route of the colleges and universities corresponding to the user in the second data, so that the type of the colleges and universities passed by each user and the name of the colleges and universities can be identified.
According to the embodiment of the present invention, after the user data information is subjected to the screening processing, the stored data is extracted as the first data, and the school information of the user is identified based on the first data to perform identity information matching, so as to complete the college and university identification, specifically including:
slicing according to preset time based on the first data, and identifying the staying time of each user in different schools within the preset time;
recording the residence time, extracting the school with the longest residence time in a single day as the calendar matching data, and further acquiring the weekly schedule, the monthly schedule and the annual schedule.
And performing merging operation based on the chronology, and extracting the school with the largest school occurrence frequency sequence corresponding to the calendar matching data as the identity matching information corresponding to the user.
It should be noted that after the user data information is subjected to age and path screening, the remaining data is extracted as the first data, the preset time is selected as day and night, the first data is further sliced according to day and night, the staying time of the user in different schools in each time period is obtained and recorded, the school with the longest staying time in a single day is extracted as the day and table matching data of the user, so as to obtain the week table matching data, month table matching data and chronology matching data of the user, further, a merging operation is performed based on the chronology matching data, the school with the highest occurrence frequency ranking corresponding to the day table matching data is analyzed as the identity matching information corresponding to the user, for example, a student D goes in and out of three colleges, but after the chronology matching data is integrated, since it was found that A, B and C colleges and universities were "118", "20" and "12", respectively, student D was judged to be a college student at school A.
It is worth mentioning that the method further comprises identifying social security data of the user to complete the screening of the user data information.
It should be noted that, as the students do not pay the social security in the learning stage, the students can screen users by using the social security as a feature factor, and extract and reserve user groups which are not paid in the social security among the users identified in the college range, so as to further reduce the operation amount.
It is worth mentioning that the method further comprises identifying the doctor identity factor in the social security payment data to expand the student user group.
It should be noted that, in the actual operation process of domestic colleges and universities, social security is mostly not paid for the principal and the master, but social security is paid for the doctor, so that when the user is screened, the doctor identity factor in the social security payment data can be extracted to be reserved, and the screening mechanism is perfected.
It is worth mentioning that the method further comprises the step of extracting preset library browsing user data to perform cross analysis so as to screen out the target group.
It should be noted that, for college students, provinces, urban galleries and large bookstores are located in frequently-visited places, so that users identified in the range of college students can be cross-analyzed with the user group visiting the library to extract the cross group, thereby further narrowing the screening range.
It is worth mentioning that the method also comprises the steps of calling an external database to match the user signature data, and carrying out identity study and judgment to judge the colleges and universities of the current user.
It should be noted that, for colleges and universities, articles need to be published in the web or various academic magazines, so the web database or the academic magazines and the newspapers can be called to track the user signature data, and when the users matched with the current colleges and universities are the same, the identity of the colleges and universities of the current users and the corresponding schools can be directly obtained.
It is worth mentioning that the method further comprises extracting the volunteer activity data for auxiliary screening.
It should be noted that, for college students, the principal force of the young volunteers in each city, organization or group is the principle force, so that the volunteer activity data can be extracted for auxiliary analysis, and meanwhile, the screened college student users can also perfect the identity label information of the college student users.
Fig. 2 shows a block diagram of an internet of things-based college student identification system of the present invention.
As shown in fig. 2, the invention discloses a college student identification system based on the internet of things, which comprises a memory and a processor, wherein the memory comprises a college student identification method program based on the internet of things, and the college student identification method program based on the internet of things realizes the following steps when being executed by the processor:
acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range;
identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range;
and after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the user based on the first data, wherein the school information is subjected to identity information matching so as to finish the identification of the colleges and universities.
It should be noted that, in this embodiment, a mobile device carried by a college student may access an internet of things, and further may obtain the user data information corresponding to the college student, and based on the extraction of the user path data and the user internet of things card data, the user path data is used to identify a path of a current user in a preset college, the internet of things card data is used to identify an identification when the current user accesses the internet of things, further, data that is not in a preset college range in the user path data is deleted, the age data in the user data information may also be extracted, users that do not conform to the age threshold range in the college are also removed to retain the remaining to-be-processed student data of the college, and after the user data information is screened, the to-be-processed student data of the college is extracted as the first data, and then identifying the type of the colleges and universities to which the current user belongs based on the first data to perform matching so as to finish the identity identification of the colleges and universities of the current user.
According to the embodiment of the present invention, the acquiring user data information, where the user data information includes user path data and user internet of things data, specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
It should be noted that, in this embodiment, in view of the above mobile device capable of accessing the internet of things, the mobile device is in communication connection to obtain the user data information corresponding to the user wearing the mobile device, and further distinguish data types to obtain the user path data, the internet of things card data, the age data, and the like, and the user path data, the internet of things card data, the age data, and the like are visualized in a table form to enhance display.
According to the embodiment of the present invention, the identifying age data in the user data information and rejecting users whose age data is not within a preset age threshold specifically includes:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
It should be noted that, since the age number value is determined based on the age data, and the general age distribution of the colleges has stability, the age threshold range may be obtained by clustering the age limit ranges corresponding to different schools, for example, the age distribution of the school a is limited to "18-28" years, the age distribution of the school B is "18-22" years, and the age distribution of the school C is "16-32", so that the obtained age threshold range may be "16-32" years, and users whose age number value is not within the age threshold range, which are identified in the college internet of things system, may be culled to reduce the data processing amount, improve the data processing capability, and simultaneously, for culled users who do not meet the age requirement, other information may also be culled.
According to the embodiment of the invention, for the college students in the cross-age group, the age attributes of the college students are annotated in advance, and the school identity attribution information of the college students is directly identified based on the annotation information.
It should be noted that, in this embodiment, although the general senior citizen age distribution has stability, it does not exclude that some students in special age groups read, and for the students in these special age groups, they will annotate their age attributes when entering school, so that the identity of their senior citizens can be directly identified based on the annotation information, and then the school identity attribution information can be identified.
According to the embodiment of the present invention, the identifying and removing the path records in the path data, which are not within the preset campus range, and identifying the name of the school to which the current path belongs based on the path records within the preset campus range specifically include:
extracting user data with the age data within the preset age threshold range as second data;
identifying the path data of the corresponding user based on the second data, and further eliminating the path data which is not located in a preset campus range to obtain a college path corresponding to the user;
and identifying the type of the colleges and universities which the user approaches based on the college path, and identifying the name of the school of each college and university.
It should be noted that after classifying ages, the user data whose age data is within the preset age threshold range is extracted to serve as the second data, and further, the path data recorded by the user in the second data is classified, and the path records not within the preset campus range are removed to obtain the route of the colleges and universities corresponding to the user in the second data, so that the type of the colleges and universities passed by each user and the name of the colleges and universities can be identified.
According to the embodiment of the present invention, after the user data information is subjected to the screening processing, the stored data is extracted as the first data, and the school information of the user is identified based on the first data to perform identity information matching, so as to complete the college and university identification, specifically including:
slicing according to preset time based on the first data, and identifying the staying time of each user in different schools within the preset time;
recording the residence time, extracting the school with the longest residence time in a single day as the calendar matching data, and further acquiring the weekly schedule, the monthly schedule and the annual schedule.
And performing merging operation based on the chronology, and extracting the school with the largest school occurrence frequency sequence corresponding to the calendar matching data as the identity matching information corresponding to the user.
It should be noted that after the user data information is subjected to age and path screening, the remaining data is extracted as the first data, the preset time is selected as day and night, the first data is further sliced according to day and night, the staying time of the user in different schools in each time period is obtained and recorded, the school with the longest staying time in a single day is extracted as the day and table matching data of the user, so as to obtain the week table matching data, month table matching data and chronology matching data of the user, further, a merging operation is performed based on the chronology matching data, the school with the highest occurrence frequency ranking corresponding to the day table matching data is analyzed as the identity matching information corresponding to the user, for example, a student D goes in and out of three colleges, but after the chronology matching data is integrated, since it was found that A, B and C colleges and universities were "118", "20" and "12", respectively, student D was judged to be a college student at school A.
It is worth mentioning that the method further comprises identifying social security data of the user to complete the screening of the user data information.
It should be noted that, because the students do not pay the social security in the learning stage, the students can screen users by using the presence or absence of the social security as a characteristic factor, and extract and reserve user groups which are identified in the college scope and do not pay the social security, so as to further reduce the calculation amount.
It is worth mentioning that the method further comprises identifying the doctor identity factor in the social security payment data to expand the student user group.
It should be noted that, in the actual operation process of domestic colleges and universities, social security is mostly not paid for the principal and the master, but social security is paid for the doctor, so that when the user is screened, the doctor identity factor in the social security payment data can be extracted to be reserved, and the screening mechanism is perfected.
It is worth mentioning that the method further comprises the step of extracting preset library browsing user data to perform cross analysis so as to screen out the target group.
It should be noted that, for college students, provinces, urban galleries and large bookstores are located in frequently-visited places, so that users identified in the range of college students can be cross-analyzed with the user group visiting the library to extract the cross group, thereby further narrowing the screening range.
It is worth mentioning that the method also comprises the steps of calling an external database to match the user signature data, and carrying out identity study and judgment to judge the colleges and universities of the current user.
It should be noted that, for colleges and universities, articles need to be published in the known network or various academic magazines, so the known network database or the academic magazines and the newspapers can be called to track the user signature data, and when the users matched with the same identity in the range of the current colleges and universities are matched, the identity of the current colleges and the corresponding schools can be directly obtained.
It is worth mentioning that the method further comprises extracting the volunteer activity data for auxiliary screening.
It should be noted that, for college students, the principal force of the young volunteers in each city, organization or group is the principle force, so that the volunteer activity data can be extracted for auxiliary analysis, and meanwhile, the screened college student users can also perfect the identity label information of the college student users.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a college identification method based on the internet of things of a machine, and when the program of the college identification method based on the internet of things is executed by a processor, the steps of the college identification method based on the internet of things as described in any one of the above are implemented.
The college student identification method, the college student identification system and the readable storage medium based on the Internet of things can analyze data of users collected based on the Internet of things, analyze the college types of identity matching information corresponding to the users by using paths, ages and parking time, perform annual statistics on the college students by using table visualization, and clearly show the identity affiliation of the college students.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
Claims (10)
1. A college student identification method based on the Internet of things is characterized by comprising the following steps:
acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range;
identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range;
and after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the user based on the first data, wherein the school information is subjected to identity information matching so as to finish the identification of the colleges and universities.
2. The internet of things-based college student identification method according to claim 1, wherein the obtaining of the user data information includes user path data and user internet of things card data, and specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
3. The internet of things-based college student identification method according to claim 2, wherein the identifying age data in the user data information and eliminating users whose age data is not within a preset age threshold range specifically comprises:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
4. The Internet of things-based college student identification method according to claim 3, wherein for the college students across age groups, the age attributes of the college students are annotated in advance, and the school identity attribution information of the college students is directly identified based on the annotation information.
5. The internet of things-based college student identification method according to claim 3, wherein the identifying and removing path records in the path data that are not within a preset campus range, and identifying a school name to which a current path belongs based on the path records within the preset campus range specifically comprises:
extracting user data with the age data within the preset age threshold range as second data;
identifying the path data of the corresponding user based on the second data, and further eliminating the path data which is not located in a preset campus range to obtain a college path corresponding to the user;
and identifying the type of the colleges and universities which the user approaches based on the college path, and identifying the school name of each college and universities.
6. The internet of things-based college and university student identification method according to claim 1, wherein after the user data information is subjected to screening processing, stored data is extracted as first data, and the school information of the user is identified based on the first data to perform identity information matching, so as to complete the college and university identification, specifically comprising:
slicing according to preset time based on the first data, and identifying the staying time of each user in different schools within the preset time;
recording the retention time, extracting the school with the longest retention time in a single day as the calendar matching data, and further acquiring a week table, a month table and an annual table;
and performing merging operation based on the chronology, and extracting the school with the largest school occurrence frequency sequence corresponding to the calendar matching data as the identity matching information corresponding to the user.
7. The college student identification system based on the Internet of things is characterized by comprising a memory and a processor, wherein the memory comprises a college student identification method program based on the Internet of things, and the college student identification method program based on the Internet of things realizes the following steps when being executed by the processor:
acquiring user data information, wherein the user data information comprises user path data and user Internet of things card data;
identifying age data in the user data information, and rejecting users whose age data is not within a preset age threshold range;
identifying and eliminating path records in the path data, wherein the path records are not in a preset campus range, and identifying a school name to which a current path belongs based on the path records in the preset campus range;
and after the user data information is subjected to screening processing, extracting stored data as first data, and identifying the user based on the first data, wherein the school information is subjected to identity information matching so as to finish the identification of the colleges and universities.
8. The internet of things-based college student identification system according to claim 7, wherein the user data information is obtained, wherein the user data information includes user path data and user internet of things card data, and specifically includes:
establishing communication connection with Internet of things equipment worn by a user to read data so as to obtain user data information;
and distinguishing data types based on the user data information, and visualizing the data types in a preset table form, wherein the user data information comprises the user path data, the Internet of things card data and the age data.
9. The internet of things-based college student identification system according to claim 8, wherein the identifying of the age data in the user data information and the eliminating of the users whose age data is not within a preset age threshold range specifically comprises:
performing quantitative value judgment on the age data corresponding to each user based on the obtained user data information, wherein,
aiming at different age limit ranges corresponding to different preset school proofreads, carrying out age clustering based on different preset schools to obtain a preset age threshold range;
and removing users which are not in the preset age threshold range in the user data information, and synchronously removing other information of the users in the visual table.
10. A computer-readable storage medium, wherein the computer-readable storage medium includes a program of a method for identifying college students based on the internet of things, and when the program of the method for identifying college students based on the internet of things is executed by a processor, the steps of the method for identifying college students based on the internet of things according to any one of claims 1 to 6 are implemented.
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