CN106330970A - Mobile learning monitoring method and system - Google Patents
Mobile learning monitoring method and system Download PDFInfo
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- CN106330970A CN106330970A CN201610935162.3A CN201610935162A CN106330970A CN 106330970 A CN106330970 A CN 106330970A CN 201610935162 A CN201610935162 A CN 201610935162A CN 106330970 A CN106330970 A CN 106330970A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
- H04N7/185—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source from a mobile camera, e.g. for remote control
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- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- General Engineering & Computer Science (AREA)
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Abstract
The invention provides a monitoring method and system based on mobile learning. The method includes the steps that effective identity information and human face information of a user are matched with register information in a background server in the user authentication process of mobile learning, if the effective identity information and human face information are consistent with the register information, authentication is successfully, and otherwise, monitoring is triggered; monitoring is conducted in the learning process of mobile learning, human face images are periodically shot by means of the camera function of a mobile terminal for identity comparison judgment, monitoring continues if the identity is consistent with the image, and warning is triggered if the identity is not consistent with the image; warning feedback processing of mobile learning is conducted according to the number of times of warning triggering. The human face images are obtained through the intelligent mobile terminal, perceptual authentication is conducted in the authentication process, and non-perceptual learning process monitoring is achieved in the learning process.
Description
Technical field
The invention belongs to Mobile solution field, particularly relate to a kind of mobile learning monitoring method and system.
Technical background
Mobile learning on the basis of Digital Learning by effectively combine mobile calculation technique bring learner at any time with
The brand-new experience of ground study.Mobile learning is considered as the learning model in a kind of future, or perhaps following study is indispensable
A kind of learning model.
In recent years, even enterprise of more and more school, network schools was all in the skill using mobile learning to improve student, employee
Energy.The evaluation of the learning effect of student at present generally uses the numbers such as the learning materials to student are downloaded, experience is shared, login times
Analyze study habit and the study initiative understanding student according to statistics.But in this process, it is impossible to judge to use account to step on
Whether whether land is student self, not to mention be student in whole learning process.Therefore, at tradition mobile learning
Basis use image recognition analysis technology, it is possible to ensure further the verity of student's identity information, it is ensured that learning process is held
Continuous effectiveness, can improve student's learning effect further.
Summary of the invention
It is an object of the invention to provide a kind of mobile learning monitoring method and system, during mobile learning, user learns
The monitoring of habit process, uses effective identity information to combine with face information including debarkation authentication process, uses noninductive during study
Know that timing acquisition user's face information is machine-processed to carry out process monitoring and relevant warning information feedback processing, thus provide
A kind of monitor user's effectiveness of identity in learning process.
A kind of mobile learning monitoring system, including: user authentication logs in, learning process monitors and alerts feedback processing.
Described verification process logs in having needed for system user initiates user's Sign-On authentication in the study incipient stage
The effect biological characteristic authentication information such as authentification of message and face；
Described effective information certification includes: the information such as identity card, student's identity card, employee ID are sent to background server data base and enter
Row certification.
Further, the biological information certifications such as described face include: utilize intelligence intelligent terminal's photographic head shooting people
Face image, and send images to server database and carry out the biometric matches processes such as face.
Described learning process monitoring is used for the facial image of timing acquisition learner in learning process and mates
Process.
Further, the facial image in above-mentioned learning process obtains mode is that intelligent terminal's photographic head carries out unaware timing
Shooting photo.
Further, the described unaware BR photo in above-mentioned learning process is the flash lamp being not turned on photographic head
In the case of, do not show that photographic head calls the style of shooting at interface.
Further, in above-mentioned learning process face coupling use based on face characteristic extract on the basis of coupling.
Preferably, above-mentioned face characteristic coupling completes intelligent terminal.
Described alarm feedback processing is to occur the processing mode under abnormal conditions in verification process and learning process.
Further, the alarming processing in verification process described above is that the authentication information frequency of failure exceedes restriction threshold value, moves back
Go out verification process, terminate study.
Described threshold value is usually arranged as 3 times.
Further, the abnormal conditions in learning process described above do not have learner face in processing the image including identifying
Direct picture and do not have facial image, carries out relevant information storage the prompt alarms such as abnormal image.
Described does not has learner face direct picture face, is non-learner front face image for image recognition.
Described does not has facial image, for not comprising facial image in image recognition result.
Further, in above-mentioned learning process, described abnormal image information storage includes storing non-frontal facial image and figure
As the time obtained.
Further, in above-mentioned learning process, described prompt alarm includes the dialog box prompting alerting number of times, and transfinites
Alarm afterwards also exits learning process.
A kind of based on mobile learning monitoring method, comprise the following steps:
Step 101. study application initializes, and monitoring initializes.
Step 102. is called certification and is logged in setting.
The passport NO. inputs such as step 103. identity card/student's identity card.
Step 104. calls intelligent terminal's photographic head shooting facial image.
Certificate information and facial image are sent to far-end server by step 105..
Authentication result is fed back by step 106. far-end server, and feedback information includes whether certification student is legal, if
For legal student simultaneously by its intelligent terminal that facial image feature and image send in background server.
Step 107. intelligent terminal's Learning-memory behavior module judges whether certification success, if certification successfully goes to step 108,
Otherwise go to step 1071.
Step 1071. judges whether authentification failure number of times transfinites, and goes to step 103 without transfiniting, and otherwise goes to step
1072。
Step 1072. points out the warning information of authentification failure, goes to step 1073.
Step 1073. exits certification, terminates study, closes application.
Step 108. recalls learning stuff, starts study.
Intelligent terminal's photographic head shooting photo is called in step 109. timing.
Step 110. is captured face characteristic in intelligent terminal side extraction step 109.
The face characteristic that the face characteristic extracted and server provide is contrasted, if study by step 111.
Person, goes to step 116, otherwise goes to step 112.
Step 112. preserves photo in intelligent terminal side.
Step 113. learns interface intelligent terminal and ejects alarm prompt frame.
Step 114. judges the number of times of alarm prompt, if it exceeds limit number of times to go to step 1141, otherwise goes to step 115.
Step 1141. uploads the information such as the human face photo of shooting, alarm time, alarm number of times to background server, turns
1142。
Step 1142. exits study and closes application.
Step 115. uploads the information such as captured human face photo, alarm time, alarm number of times to background server.
Step 116. judges whether learning process terminates, if it has not ended, turn 109, otherwise turns 117.
Step 117. is uploaded learning process and be recorded server, and exits study, closes application.
The present invention has following effective effect:
The mode that the effective identity information of user and human face image information are mated with log-on message in server when learning certification adds
With certification, after certification success, facial image and the characteristics of image thereof of backstage learning person are delivered to intelligent terminal.In study
During, utilize intelligent terminal's BR photo, and carry out mating judging at the photo captured by the extraction of intelligent terminal side
Whether learner there are abnormal conditions, under normal circumstances, the backed off after random learning system learnt, reach one in abnormal conditions
The backed off after random learning process of fixed limit degree, and will alarm upload server backed off after random system.
Accompanying drawing explanation
Fig. 1 is the system architecture diagram of the present invention；
Fig. 2 embodiment of the present invention flow chart.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below technical scheme in the present invention carry out clearly
Chu, it is fully described by, it is clear that described embodiment is a part of embodiment of the present invention rather than whole embodiments.Based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under not making creative work premise
Embodiment, broadly falls into the scope of protection of the invention.
As it is shown in figure 1, the mobile learning monitoring system that the present invention provides, including: the user authentication module of mobile learning, moves
The learning process monitoring module of dynamic study and the alarm feedback module of mobile learning.
The user authentication module of described mobile learning, for using the face of effective identity information and mobile terminal shooting
Information combines and realizes matching with log-on message in background server；
The learning process monitoring module of described mobile learning, it is achieved unaware BR facial image, carries out identity comparison
Judge；
The alarm feedback module of described mobile learning is used for alarming processing and the feedback of system.
The operation principle of described mobile learning monitoring system is: during verification process, user Sign-On authentication is provided needed for have
The effect biological information such as authentification of message and face, and by these information and the log-on message comparison in server；If certification
Success, then system is controlled by Learning-memory behavior module, if authentification failure, failure information is supplied to alarm feedback mould by system
Block, is fed back the reason of failure by alarm module.Learning-memory behavior module monitors learning process in real time, and timing is clapped in this process
Take the photograph user's face information to compare with log-on message, if relatively success, continue monitoring, otherwise failure information is passed to
Alarm module.In alarm module, add up login authentication module and the alarm cause of Learning-memory behavior module and whether alarm number of times reaches
To the threshold value set, if it exceeds the threshold, terminate learning process after prompting reason.
Fig. 2 is the flow chart of a kind of monitoring method based on mobile learning of the embodiment of the present invention, as in figure 2 it is shown, the present invention
The monitoring method of mobile learning comprise the following steps:
Step 101. study application initializes, and monitoring initializes.
Step 102. learns application call certification log-in interface.
The passport NO. inputs such as step 103. identity card/student's identity card.
Step 104. calls intelligent terminal's photographic head shooting facial image.
Specifically, prompting application user, shoot frontal one image, face image to the left, face image to the right with
And bow face image and look up the multi-angle face images such as face image.
Certificate information and facial image are sent to background server by step 105..
Specifically, the information that captured photo and user are inputted is sent to background user number by the application of intelligent terminal
According to storehouse.
Authentication result is fed back by step 106. far-end server, and feedback information includes whether certification student is legal, if
For legal student simultaneously by its intelligent terminal that facial image feature and image send in background server.
Step 107. intelligent terminal's Learning-memory behavior module judges whether certification success, if certification successfully goes to step 108,
Otherwise go to step 1071.
Step 1071. judges whether authentification failure number of times transfinites, and goes to step 103 without transfiniting, and otherwise goes to step
1072。
Specifically, if authentification failure number of times exceedes preferentially is set to last time.
Specifically, authentification failure number of times transfinites and includes face authentication failure and identity information authentification failure.
Step 1072. points out the warning information of authentification failure, goes to step 1073.
Step 1073. exits certification, terminates study, closes application.
Step 108. recalls learning stuff, starts study.
Intelligent terminal's photographic head shooting photo is called in step 109. timing.
Specifically, the time cycle of set intervalometer is the random number less than 1 minute.
Step 110. is captured face characteristic in intelligent terminal side extraction step 109.
The face characteristic that the face characteristic extracted and server provide is contrasted, if study by step 111.
Person, goes to step 116, otherwise goes to step 112.
Step 112. preserves photo in intelligent terminal side.
Step 113. learns interface intelligent terminal and ejects alarm prompt frame.
Step 114. judges the number of times of alarm prompt, if it exceeds limit number of times to go to step 1141, otherwise goes to step 115.
Step 1141. uploads the information such as the human face photo of shooting, alarm time, alarm number of times to background server, turns
1142。
Step 1142. exits study and closes application.
Step 115. uploads the information such as captured human face photo, alarm time, alarm number of times to background server.
Step 116. judges whether learning process terminates, if it has not ended, turn 109, otherwise turns 117.
Step 117. is uploaded learning process and be recorded server, and exits study, closes application.
Last it is noted that above example is only in order to illustrate technical scheme, it is not intended to limit；Although
With reference to previous embodiment, the present invention is described in detail, it will be understood by those within the art that: it still may be used
So that the technical scheme described in foregoing embodiments to be modified, or wherein portion of techniques feature is carried out equivalent；
And these amendment or replace, do not make appropriate technical solution essence depart from various embodiments of the present invention technical scheme spirit and
Scope.
Claims (5)
1. a monitoring system based on mobile learning, it is characterised in that including: the user authentication module of mobile learning, mobile
The learning process monitoring module of study and the alarm feedback module of mobile learning；
The user authentication module of described mobile learning, for using the face information of effective identity information and mobile terminal shooting
Combine and realize matching with log-on message in background server；
The learning process monitoring module of described mobile learning, it is achieved unaware BR facial image, carries out identity comparison
Judge；
The alarm feedback module of described mobile learning is used for alarming processing and the feedback of system.
Monitoring system based on mobile learning the most according to claim 1, it is characterised in that described user authentication module
The information used includes effective identity information and face information, log-on message in server；
Described effective identity information is the most certified information, polytype including identity information, student's identity card, student's card etc.
A kind of；
Described face information is study application call mobile intelligent terminal photographic head, and it is captured to point out user to be authenticated
Facial image；
The acquisition methods of the face information of described verification process is for calling captured by intelligent mobile terminal；
Described server info certification is the human face photo and certification personnel couple in background data base shot by mobile terminal
Answer front, left surface, right flank, look up and overlook facial image and carry out similarity system design.
The monitoring system of mobile learning the most according to claim 1, it is characterised in that described learning process monitoring module is real
Now include that unaware BR photo, photo face characteristic extract, human face similarity compares；
Described unaware BR photo is a length of when being to use is less than random timer in 1 minute；
It is to call mobile terminal camera to carry out backstage and take pictures that described unaware is taken pictures, and does not show interface of taking pictures, it is not necessary to open
Open flash of light；
It is to complete face characteristic at mobile intelligent terminal to extract that described photo face characteristic extracts；
Described human face similarity compares and carries out with lineup's face image of the student returned from server for the photo of BR
Similarity system design.
The monitoring system of mobile learning the most according to claim 1, it is characterised in that described alarm feedback module includes
Authentification failure alarming processing, learning process face alignment failure alarming processing；
Described authentification failure alarming processing exceedes threshold value by the interpretation frequency of failure and i.e. thinks failure, is fed back to by failure information
User；
It is photo learning person captured by mobile terminal in learning process that described learning process face alignment unsuccessfully alerts
Face image with storage learner photo inconsistent time prompt alarm, and alarm transfinite backed off after random study application.
5. a monitoring method based on mobile learning, it is characterised in that comprise the following steps:
Step 101. study application initializes, and monitoring initializes；
Step 102. is called certification and is logged in setting；
The passport NO. inputs such as step 103. identity card/student's identity card；
Step 104. calls intelligent terminal's photographic head shooting facial image；
Certificate information and facial image are sent to far-end server by step 105.；
Authentication result is fed back by step 106. far-end server, and feedback information includes whether certification student is legal, if conjunction
Science of law person is simultaneously by its intelligent terminal that facial image feature and image send in background server；
Step 107. intelligent terminal's Learning-memory behavior module judges whether certification success, if certification successfully goes to step 108, otherwise
Go to step 1071；
Step 1071. judges whether authentification failure number of times transfinites, and goes to step 103 without transfiniting, and otherwise goes to step 1072；
Step 1072. points out the warning information of authentification failure, goes to step 1073；
Step 1073. exits certification, terminates study, closes application；
Step 108. recalls learning stuff, starts study；
Intelligent terminal's photographic head shooting photo is called in step 109. timing；
Step 110. is captured face characteristic in intelligent terminal side extraction step 109；
The face characteristic that the face characteristic extracted and server provide is contrasted by step 111., if learner, turns
Step 116, otherwise goes to step 112；
Step 112. preserves photo in intelligent terminal side；
Step 113. learns interface intelligent terminal and ejects alarm prompt frame；
Step 114. judges the number of times of alarm prompt, if it exceeds limit number of times to go to step 1141, otherwise goes to step 115；
Step 1141. uploads the information such as the human face photo of shooting, alarm time, alarm number of times to background server, turns 1142；
Step 1142. exits study and closes application；
Step 115. uploads the information such as captured human face photo, alarm time, alarm number of times to background server；
Step 116. judges whether learning process terminates, if it has not ended, turn 109, otherwise turns 117；
Step 117. is uploaded learning process and be recorded server, and exits study, closes application.
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| CN201610935162.3A CN106330970A (en) | 2016-11-01 | 2016-11-01 | Mobile learning monitoring method and system |
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| CN107317846A (en) * | 2017-06-07 | 2017-11-03 | 上海储翔信息科技有限公司 | Vehicle management system based on cloud platform |
| CN109785692A (en) * | 2019-01-22 | 2019-05-21 | 合肥状元郎电子科技有限公司 | A kind of Digital Teaching display systems |
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| CN111324879A (en) * | 2020-02-18 | 2020-06-23 | 支付宝(杭州)信息技术有限公司 | Login state control method, device and equipment |
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| CN112417415A (en) * | 2020-12-07 | 2021-02-26 | 江汉大学 | Interactive education identity recognition method, storage medium and system |
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