CN106055894A - Behavior analysis method and system based on artificial intelligence - Google Patents
Behavior analysis method and system based on artificial intelligence Download PDFInfo
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Abstract
The invention provides a behavior analysis method and system based on artificial intelligence, and is applied to developing good habits of children. The system comprises an information acquisition module used for acquiring real-time state information of a user to be analyzed; and a behavior processing analysis module used for performing analysis processing on the real-time state information so as to determine a fatigue degree and a focus degree of the user to be analyze. The real-time state information comprises behavior information and environment information. The processing analysis module comprises a preprocessing submodule used for performing detection and extraction processing on the behavior information to obtain feature behavior information and a determining analysis submodule used for performing comparison analysis with a standard behavior model according to the feature behavior information so as to determine the fatigue degree and the concentration degree of the user to be analyzed. According to the invention, based on the artificial intelligence and big data analysis, behavior information of bad learning habits of children is analyzed, the bad habits are rectified through guiding education of parents, the learning concentration power and automatic learning capability of the children are improved, and finally, the children can develop goods habits.
Description
Technical field
The present invention relates to the field of information processing of Internet of Things, particularly relate to a kind of for child custom based on artificial intelligence
The behavior analysis system and method for energy.
Background technology
Society, the educational problem of child has become as one of most concerned topic of the heads of a family.In general, 5-12 year
Age bracket be child cultivate study habit, improve be absorbed in power critical period, good attention and study habit, to its become
Length will have conclusive effect.Therefore, the study habit that child is good how is cultivated so that it is body and mind is developed in a healthy way always
It is the head of a family and topic that teachers are concerned about the most.The most active is the nature of Most of children.But, if do not use restraint and
Cultivating, children's study will be brought certain negative effect by these nature.
In reality, the heads of a family often because busy work, usually do not have the too many time to accompany child at one's side；And
The self-control of child itself is poor, it is impossible to focus on for a long time, and in the course of time, bad study habit will be formed,
Thus badly influence the school grade of child.Even if the head of a family can find time, accompany child at one's side in real time, teach also
Correct the study habit of child, but get off the most easily to encourage inertia and the psychological inversion thereof of child for a long time, affect child equally
Mental health.
Further, child is in the body development phase, and incorrect sitting posture the most easily causes textured bone, hunchback, torticollis oblique
Depending on and the problem such as visual deterioration, this to produce greatest injury equally for the physiology of child.
How while ensureing the physical and mental health of child, behavior during children for learning is analyzed, guides child to entangle
The worst study habit, finally picking up good habits of study has become as the head of a family and urgently to be resolved hurrily one of teacher asks
Topic.
Summary of the invention
The shortcoming of prior art in view of the above, it is an object of the invention to provide a kind of behavior based on artificial intelligence
Analyze system and method, well learn habit for solve prior art is the most effectively cultivated child, form good
Breezy used problem.
For achieving the above object and other relevant purposes, the present invention provides a kind of behavior analysis system based on artificial intelligence
System, including: information acquisition module, for gathering the real time status information of user to be analyzed；Behavior Treatment Analysis module, for right
Described real time status information is analyzed processing, thus judges the mental status of described user to be analyzed.
In one embodiment of the invention, described real time status information includes: behavioural information and environmental information；Wherein, institute
State behavioural information and include facial expression information and limbs behavioural information；The mental status of described user to be analyzed includes: fatigue strength
And focus.
In one embodiment of the invention, described information acquisition module includes video equipment and audio frequency apparatus, wherein, described
Video equipment is for gathering the video format of described user to be analyzed and/or the real-time described behavioural information of picture format；Institute
State audio frequency apparatus for gathering the described environmental information of the audio format of described user's local environment to be analyzed.
In one embodiment of the invention, described Treatment Analysis module includes pretreatment submodule and discriminatory analysis submodule
Block；Described pretreatment submodule, for detecting and at extraction the described behavioural information of video format and/or picture format
Reason, obtains characteristic behavior information；Described discriminatory analysis submodule, for processing described in acquisition according to described pretreatment submodule
Characteristic behavior information, compares analysis with criterion behavior model, thus judges that the fatigue strength of described user to be analyzed is with special
Note degree.
In one embodiment of the invention, described criterion behavior model is different for different users described to be analyzed
, it is that the long-term behavioural information to described user to be analyzed carries out Adaptive matching and formed.
In one embodiment of the invention, described characteristic behavior information includes eye information, muscle movement and lip expression.
In one embodiment of the invention, described information acquisition module and described pretreatment submodule are positioned at described to be analyzed
User side, described discriminatory analysis submodule is positioned at high in the clouds；Lead between described pretreatment submodule and described discriminatory analysis submodule
Cross communication to carry out data transmission；Or, described pretreatment submodule and described discriminatory analysis submodule are located on high in the clouds,
Carried out data transmission by communication between described information acquisition module and described pretreatment submodule.
In one embodiment of the invention, described behavior analysis system also include respectively with described behavior Treatment Analysis module
The report feedback module connected by wireless network with described information acquisition module, described report feedback module is for according to described
Behavior Treatment Analysis module analysis judges the mental status of the user described to be analyzed obtained, and sums up and obtains behavior analysis report,
And report that described user to be analyzed makes corresponding information to feed back according to described behavior analysis.
In one embodiment of the invention, the mode of described information feedback includes: directly feedback and indirect feedback；Wherein,
Described direct feedback includes: by wireless network, feedack is sent directly to described information acquisition module；Described indirectly
Feedback includes: via described behavior Treatment Analysis module, feedack is indirectly fed back to described information by wireless network and adopts
Collection module.
In one embodiment of the invention, the described video equipment of described information acquisition module for by play video or
The mode of image reminds described user to be analyzed；The described audio frequency apparatus of described information acquisition module is for by playing voice
Mode reminds described user to be analyzed；Described information acquisition module also includes for reminding by the way of vibration described to be analyzed
The vibration prompt equipment of user.
The invention also discloses a kind of behavior analysis method based on artificial intelligence, including: gather the reality of user to be analyzed
Time status information；Analyze and process the described real time status information of described user to be analyzed, thus judge described user's to be analyzed
The mental status.
In one embodiment of the invention, described real time status information includes: behavioural information and environmental information；Wherein, institute
State behavioural information and include facial expression information and limbs behavioural information；The mental status of described user to be analyzed include fatigue strength and
Focus.
In one embodiment of the invention, the described real time status information of the described user to be analyzed of described analyzing and processing, from
And judge that the described fatigue strength of user to be analyzed and the step of focus include: described behavioural information is detected and at extraction
Reason, obtains characteristic behavior information；Described characteristic behavior information and criterion behavior model are compared analysis, thus judges institute
State fatigue strength and the focus of user to be analyzed；Wherein, described criterion behavior model is long-term to described user to be analyzed
The Adaptive matching of behavioural information and formed.
In one embodiment of the invention, described behavior analysis method also includes: according to judge obtain described to be analyzed
The mental status of user, sums up and obtains behavior analysis report；And according to the report of described behavior analysis, described user to be analyzed is done
Go out corresponding information feedback.
As it has been described above, a kind of based on artificial intelligence behavior analysis system and method for the present invention, it is based on artificial intelligence
Behavior analysis system with big data analysis.The user to be analyzed of the present invention is primarily directed in child, for cultivating child's
Good study habit.The activities such as child can use the present invention to learn in the case of insusceptibly, amusement, the reality of child
Time status information (behavioural information and environmental information) collected and be uploaded to server or the cloud processing platform in high in the clouds, carry out behavior
The data of information are by integration of classifying further, thus judge fatigue strength and the focus of child；And it is final in remote platform shape
The behavior analysis becoming complete is reported, obtains the firsthand information the most intuitively.Reporting according to behavior analysis, the head of a family or teacher can be with
Time understand the current state information of child everywhere, can offer information in good time to children's behavior feedback.Further, the letter that the present invention uses
Breath acquisition module integrates sound, optical, electrical and vibrations, the information collected can be carried out pretreatment, complete information in child side
Feedback function, this automatic entrusted management model makes this system more convenient and hommization.It is contemplated that practise for children's study
Used offer one remotely forms correction system, by the guiding education of the head of a family, corrects the study habit that child is bad, improves child
Study be absorbed in power and independent learning ability, the good habit finally realizing child is formed.
Accompanying drawing explanation
Fig. 1 is shown as the principle signal of a kind of behavior analysis system based on artificial intelligence disclosed in the embodiment of the present invention
Figure.
Fig. 2 is shown as the structural representation of a kind of behavior analysis system based on artificial intelligence disclosed in the embodiment of the present invention
Figure.
Fig. 3 is shown as the schematic diagram of learning curve disclosed in the embodiment of the present invention.
Fig. 4 is shown as the information transmission of a kind of behavior analysis system based on artificial intelligence disclosed in the embodiment of the present invention and shows
It is intended to.
Fig. 5 is shown as the flow process signal of a kind of behavior analysis method based on artificial intelligence disclosed in the embodiment of the present invention
Figure.
Element numbers explanation
110 information acquisition modules
120 Treatment Analysis modules
121 pretreatment submodules
122 discriminatory analysis submodules
130 report feedback modules
S10～S40 step
Detailed description of the invention
Below by way of specific instantiation, embodiments of the present invention being described, those skilled in the art can be by this specification
Disclosed content understands other advantages and effect of the present invention easily.The present invention can also be by the most different concrete realities
The mode of executing is carried out or applies, the every details in this specification can also based on different viewpoints and application, without departing from
Various modification or change is carried out under the spirit of the present invention.It should be noted that, in the case of not conflicting, following example and enforcement
Feature in example can be mutually combined.
Refer to accompanying drawing.It should be noted that the diagram provided in following example illustrates this most in a schematic way
Bright basic conception, the most graphic in component count time only display with relevant assembly in the present invention rather than is implemented according to reality,
Shape and size are drawn, and during its actual enforcement, the kenel of each assembly, quantity and ratio can be a kind of random change, and its assembly
Layout kenel is likely to increasingly complex.
The invention discloses a kind of behavior analysis system based on artificial intelligence and big data analysis and behavior analysis method,
For cultivating the good study habit of child.The present invention carries FPGA (Field-Programmable Gate Array, scene
Programmable gate array) or data algorithm processor, the cloud such as DSP (Digital Signal Processing, data signal process)
The big data of network such as process calculate platform and process view data, and by being accustomed to child, behavior is analyzed and finds,
In conjunction with individual variation, judge its fatigue conditions and message focus from children's behavior, compare with the custom of top student,
Then comparison analysing content is supplied to father and mother or teacher, it is simple to they understand child's present case in time, and child is imposed pipe
Religion and guiding, be of value to and cultivate the study habit that child is good, correct bad learning state, improve learning efficiency, finally support
Become good study habit.
Embodiment 1
As shown in Fig. 1 and Fig. 2, present embodiment discloses a kind of behavior analysis system based on artificial intelligence and include: information
Acquisition module 110, Treatment Analysis module 120 and report feedback module 130.Wherein,
Described information acquisition module 110 is positioned at user side to be analyzed, i.e. child side, for gathering the real-time status letter of child
Breath.Wherein, real time status information includes but not limited to the behavioural information of environmental information and child.Behavioural information includes but does not limits
In: facial expression information and limbs behavioural information.
Further, the information acquisition module 110 of the present embodiment includes but not limited to video equipment, audio frequency apparatus, vibration
Equipment and other photoelectricity auxiliary equipments that can realize guiding intervention purpose.
Wherein, video equipment is for gathering the video format of child and/or the real-time behavioural information of picture format.Preferably
Ground, video equipment is photographic head.Photographic head can be directly anchored to optimal collection position, it is possible to is mounted in the rotating shaft of motor,
Photographic head is facilitated to rotate to look for the optimal shooting angle of face neatly.
Audio frequency apparatus is for gathering the real-time environmental voice information of the audio format of child's local environment.
Treatment Analysis module 120 is for being analyzed processing to the real time status information of child, thus judges child's
The mental status.Wherein, the mental status includes but not limited to fatigue strength and focus.Treatment Analysis module 120 is based primarily upon face
And behavior Intellectual Analysis Technology, by the face in locking video and behavior image, in conjunction with the attention time in biomedicine
Curve, utilizes associated picture treatment technology loading algorithm, and face information such as facial expression, muscle movement, lip reading etc. are carried out intelligence
Can analyze, it is judged that the mental status and degree of fatigue.All data of this module gained are uploaded to high in the clouds, through further youngster
Virgin acquired behavior analysis and discovery, the physical fatigue situation to child, learn focus, Optimal Learning curve etc. is analyzed,
Thus judge fatigue strength and the focus of child.
Treatment Analysis module 120 includes pretreatment submodule 121 and discriminatory analysis submodule 122.Wherein,
Pretreatment submodule 121 detects for the real time status information gathering information acquisition module 110 and extracts,
Obtain corresponding characteristic behavior information.For example, for the video format gathered by photographic head and/or the row of picture format
For information.Pretreatment submodule 121 both can be the arm processor of integrated specific function, it is also possible to be integrated with SoC
The FPGA of (System on Chip, system level chip) kernel and dsp processor.Pretreatment submodule 121 first has to locking
Face area in the behavioural information of video format and/or picture format, cuts facial expression, action and human eye information etc.
Cut and arrange with fragmentation, it is achieved preliminary to described behavioural information is extracted and classification, processes and obtains characteristic behavior information.Wherein,
Characteristic behavior information includes but not limited to eye information (frequency of wink), muscle movement and lip expression etc..
Pretreatment submodule 121 both can be located at child side, it is possible to is positioned at high in the clouds.Due to information acquisition module 110 collection
The data of real time status information include video format, picture format and audio format, and data volume is the biggest, therefore.For
The consideration of network data transmission, is preferably arranged at child side by pretreatment submodule 121.
Discriminatory analysis submodule 122, for processing the characteristic behavior information obtained, with number according to pretreatment submodule 121
Compare analysis according to the criterion behavior data in storehouse or criterion behavior model, obtain the slight change of face, thus to child
Fatigue strength and focus make corresponding judgement.Due to the fatigue strength of child and the judgement of focus and analysis, data process
Measure bigger, therefore, it is judged that analyze submodule 122 and be arranged at high in the clouds, based on cloud treatment technology, characteristic behavior information is carried out
Big Data Management Analysis and algorithm load.
When pretreatment submodule 121 is positioned at child side, between pretreatment submodule 121 and discriminatory analysis submodule 122
Carried out data transmission by communication.When pretreatment submodule 121 is positioned at high in the clouds, information acquisition module 110 is with pre-
Process and carried out data transmission by communication between submodule 121.Wherein, the communication bag in the present embodiment
Include but be not limited to: radio-frequency technique, infrared technique, WiFi technology, Bluetooth technology and and ZigBee technology.
Discriminatory analysis submodule 122 can for the existing big data such as the common behavioural habits of child carry out Treatment Analysis and
Algorithm loads, and draws the characteristics such as fatigue criterion value, liveness, frequency of wink, behavior attitude, and training obtains standard further
Behavior model or criterion behavior data, for comparing with the characteristic behavior information acquired in pretreatment submodule 121.Judge
Analyzing submodule 122 the characteristic behavior information received to be loaded in criterion behavior model, data can be according to characteristic behavior information
Difference enter different property field, through Multilevel method data through simple aspect ratio to after the most exportable analyze knot
Really；And more complicated data are through quantification treatment, then by the behavior comparison of multilamellar algorithm structure, reject wrong demarcation special
Levy, data are reprocessed, finally exports analysis result.
And, it is contemplated that the diversity of child to be analyzed, criterion behavior model needs to be mated by adaptive learning to treat
Analyze child's.By for a long time to big data mining and the analysis of behavioural habits and discovery, this model can according to and reality
The gap of model, constantly stores new quantity of information and updates data with existing, forms the criterion behavior module more mated.Pass through
Constantly being trained, evolve and self study, criterion behavior model can map out practical situation more faithfully.
In the present embodiment, in order to show the behavior state during children for learning more easily, add displaying youngster
The learning curve of virgin learning quality, as shown in Figure 3.And further, the characteristic quantity of Optimal Learning curvilinear correlation is stored in mark
In quasi-behavior model.Wherein, the study in learning curve is absorbed in coefficient S mainly by fatigue data, liveness, frequency of wink, behavior
The information such as attitude obtain through comprehensive assessment.Learning curve shown in Fig. 3, its abscissa is time t, and vertical coordinate is absorbed in system for study
Number S, in conjunction with biomedical correlation theory, study is absorbed in the highest, and it is the biggest that coefficient S value is absorbed in the study in figure.Optimal Learning is bent
Line 1 reflects that child can keep the attention of one period of long period during study, and monitors learning curve 2 and show
Child now learns attention and is difficult to concentrate.In view of the difference between child's individuality, the reflection of Optimal Learning curve is to be analyzed
The optimum state of child.
Report feedback module 130, is positioned at remote terminal side, obtains for analyzing judgement according to behavior Treatment Analysis module 120
The fatigue strength of the child obtained and focus, sum up and obtain behavior analysis report, and according to behavior analysis report, child is made phase
The information feedback answered.Report feedback module 130 is adopted with Treatment Analysis module 120 (discriminatory analysis submodule 122) and information respectively
Collection module 110 by between carried out data transmission by communication.Wherein, the communication bag in the present embodiment
Include but be not limited to: radio-frequency technique, infrared technique, WiFi technology, Bluetooth technology and and ZigBee technology.
Described report feedback module 130 is the application software by being arranged on remote terminal or APP realizes.Its
In, remote terminal includes memorizer, Memory Controller, one or more processor (CPU), interface circuit, RF (radio frequency) electricity
Road, voicefrequency circuit, speaker, mike, input/output (I/O) subsystem, display screen, other outputs or control equipment, and
Outside port.These assemblies are communicated by one or more communication bus or holding wire.Remote terminal is electronic equipment, bag
Include but be not limited to notebook computer, computer, panel computer, smart mobile phone, multimedia player, personal digital assistant (PDA) etc.
Deng, it is also possible to include wherein two or multinomial combination.Should be appreciated that the remote terminal enumerated in the present embodiment is that electronics sets
A standby example, the assembly of this equipment can have more or less of assembly than provide in diagram, or have different
Assembly configures.
The data received from Treatment Analysis module 120 (discriminatory analysis submodule 122) are carried out by report feedback module 130
Reprocessing, carries out careful analysis to the present case of child to be analyzed, ultimately forms based on chart, and explanatory note is auxiliary tool
The behavior analysis report having personal customization style feeds back to terminal use (father and mother or teacher).Further, if remote terminal is put down
The function of platform extends further, then information acquisition module 110 gathers original video format and/or picture format
The environmental information of behavioural information and audio format can be with simultaneous display in the display of the man-machine interaction panel of remote terminal platform
On screen.
Report feedback module 130 also can make corresponding information feedback for behavior analysis report.This information feedback is permissible
It is to be automatically reminded to, it is also possible to be artificial feedback.It is automatically reminded to be the state according to child to be analyzed, directly acts on information gathering
Module 110, send the sound of information acquisition module 110 storage inside, optical, electrical or vibration information to reach to remind purpose to hair of children.Example
As, in the real time status information gathered, child successive learning 45 minutes, then send information acquisition module to hair of children
The acoustic information of 110 storage inside " reaches 45 minutes with eye, need to have a rest 10 minutes ".Artificial feedback is user's root of remote terminal
The modes such as according to particular situation, selection sends voice, plays music or sends light transformation, module vibration command.Such as, adopt
Collect to the eyes of real time status information display child be not absorbed in books, father and mother or teacher and reminded by remote speech
Virgin " study of should focusing on ".The pattern of feedack is the most versatile and flexible, such as video frequency output, voice output, language
Sound input etc..This remote terminal platform can be mobile phone terminal or other can carry out the touch screen of wireless network connection, terminal
User (father and mother or teacher) can manually or speech recognition system come to its operate.This process simplify system complexity,
Improve man-machine interaction experience further.
Further, as shown in Figure 4, the mode of information feedback includes directly feeding back or indirect feedback:
Directly feedback is directly to be fed back to by wireless network by feedack (voice, video or other command informations)
Information acquisition module 110.This feedback system makes the data transmission of whole behavior analysis system form a closed loop.
Indirect feedback is to be divided via process by wireless network by feedack (voice, video or other command informations)
Analysis module 120 feeds back to information acquisition module 110.
Information acquisition module 110 is different according to the instruction received, and reaches by the way of playing voice, video or vibrations
To the purpose reminding child.Wherein, the video equipment of information acquisition module 110 is for carrying by the way of playing video or image
Wake up child；The audio frequency apparatus of information acquisition module 110 is for reminding child by the way of playing voice；Information acquisition module
The vibratory equipment of 110 is for reminding child by the way of vibration.
Additionally, for the innovative part highlighting the present invention, not by proposed by the invention with solution in the present embodiment
The module introducing that technical problem relation is the closest, but this is not intended that in the present embodiment the module that there is not other.
Embodiment 2
Present embodiment discloses a kind of behavior analysis method based on artificial intelligence for cultivating child's good habit, as
Shown in Fig. 5, including:
Step S10, gathers the real time status information of user to be analyzed (child)；
Real time status information includes but not limited to the behavioural information of environmental information and child.Behavioural information includes but does not limits
In: facial expression information and limbs behavioural information.
Step S20, the real time status information of analyzing and processing child, thus judge the mental status of child, and wherein, spirit shape
State includes but not limited to fatigue strength and focus.Specifically include:
Detection and extract real time status information, obtains corresponding characteristic behavior information:
Face area in locking real time status information, to facial expression, action, human eye information etc. carries out cutting and fragment
Change and arrange, it is achieved preliminary to behavioural information is extracted and classification, processes and obtains characteristic behavior information.
According to the criterion behavior data in data base or criterion behavior model, characteristic behavior information is compared analysis, from
And judge fatigue strength and the focus of child:
Carry out Treatment Analysis and algorithm for existing big data such as the common behavioural habits of child load, and show that standard is tired
Labor value, liveness, frequency of wink, the characteristic such as behavior attitude, training obtains criterion behavior model or criterion behavior further
Data, compare with characteristic behavior information.Characteristic behavior information is after being loaded into criterion behavior model, and data can be according to feature row
Enter different property field for the difference of information, through Multilevel method data through simple aspect ratio to after the most exportable
Analysis result；And more complicated data are through quantification treatment, then by the behavior comparison of multilamellar algorithm structure, reject wrong
Demarcate feature, data are reprocessed, finally exports analysis result.Wherein, criterion behavior model or criterion behavior data be for
Carry out Treatment Analysis and the algorithm of the existing big data such as the common behavioural habits of child load, and draw fatigue criterion value, liveness,
Frequency of wink, the characteristic such as behavior attitude, training obtains further.Further, for different children, criterion behavior model
Also need to mate child's to be analyzed by adaptive learning.
Step S30, according to judging the fatigue strength of child and the focus that obtain, sums up and obtains behavior analysis report:
According to judging the fatigue strength of child and the focus that obtain, carry out careful analysis, ultimately form based on chart, literary composition
The behavior analysis with personal customization style that word explanation is auxiliary is reported for end user query.
Step S40, makes corresponding information according to behavior analysis report to child and feeds back:
Reporting according to behavior analysis, automatic or artificial makes corresponding information feedback to child, to reach to remind or refer to
Lead the effect of children's behavior.
The step of above method divides, and is intended merely to describe clear, it is achieved time can merge into a step or to certain
A little steps split, and are decomposed into multiple step, as long as comprising identical logical relation, all in the protection domain of this patent；
To adding inessential amendment in algorithm or in flow process or introducing inessential design, but do not change its algorithm and stream
The core design of journey is all in the protection domain of this patent.
Further, it is seen that, the present embodiment is embodiment of the method corresponding to those in the first embodiment, and the present embodiment can be with
One embodiment is worked in coordination enforcement.The relevant technical details mentioned in first embodiment is the most effective, in order to
Reduce and repeat, repeat no more here.Correspondingly, the relevant technical details mentioned in the present embodiment is also applicable in first embodiment
In.
In sum, a kind of behavior analysis system and method for the present invention, based on artificial intelligence and big data analysis
Behavior analysis system.The user to be analyzed of the present invention is primarily directed in child, for cultivating the good study habit of child.Youngster
The activities such as child can use the present invention to learn in the case of insusceptibly, amusement, the real time status information (behavior of child
Information and environmental information) collected and be uploaded to server or the cloud processing platform in high in the clouds, the data carrying out behavioural information are entered
One step ground classification is integrated, thus judges fatigue strength and the focus of child；And finally form complete behavior at remote platform and divide
Analysis report, obtains the firsthand information the most intuitively.Reporting according to behavior analysis, the head of a family or teacher can understand child whenever and wherever possible
Current state information, can offer information in good time to children's behavior feedback.Further, the information acquisition module collection that the present invention uses
Sound, optical, electrical and vibrations be integrated, the information collected can be carried out pretreatment, complete information feedback function in child side, this
Automatically entrusted management model makes this system more convenient and hommization.It is contemplated that provide a kind of long-range for children's study custom
Form correction system, by the guiding education of the head of a family, correct the study habit that child is bad, improve the study of child be absorbed in power with
Independent learning ability, the good habit finally realizing child is formed.So, the present invention effectively overcomes of the prior art all
Shortcoming and have high industrial utilization.
The principle of above-described embodiment only illustrative present invention and effect thereof, not for limiting the present invention.Any ripe
Above-described embodiment all can be modified under the spirit and the scope of the present invention or change by the personage knowing this technology.Cause
This, have usually intellectual such as complete with institute under technological thought without departing from disclosed spirit in art
All equivalences become are modified or change, and must be contained by the claim of the present invention.
Claims (14)
1. a behavior analysis system based on artificial intelligence, it is characterised in that including:
Information acquisition module, for gathering the real time status information of user to be analyzed；
Behavior Treatment Analysis module, for described real time status information is analyzed process, thus judges described use to be analyzed
The mental status at family.
Behavior analysis system based on artificial intelligence the most according to claim 1, it is characterised in that:
Described real time status information includes: behavioural information and environmental information；Wherein, described behavioural information includes facial expression information
With limbs behavioural information；
The mental status of described user to be analyzed includes: fatigue strength and focus.
Behavior analysis system based on artificial intelligence the most according to claim 2, it is characterised in that: described information gathering mould
Block includes video equipment and audio frequency apparatus, wherein, described video equipment for gather described user to be analyzed video format and/
Or the real-time described behavioural information of picture format；Described audio frequency apparatus is for gathering the sound of described user's local environment to be analyzed
Frequently the described environmental information of form.
Behavior analysis system based on artificial intelligence the most according to claim 2, it is characterised in that: described Treatment Analysis mould
Block includes pretreatment submodule and discriminatory analysis submodule；
Described pretreatment submodule, for detecting the described behavioural information of video format and/or picture format and extract
Process, obtain characteristic behavior information；
Described discriminatory analysis submodule, for processing the described characteristic behavior information obtained according to described pretreatment submodule, with
Criterion behavior model compares analysis, thus judges fatigue strength and the focus of described user to be analyzed.
Behavior analysis system based on artificial intelligence the most according to claim 4, it is characterised in that: described criterion behavior mould
Type is different for different users described to be analyzed, and it is that the long-term behavioural information to described user to be analyzed is carried out certainly
Adapt to coupling and formed.
Behavior analysis system based on artificial intelligence the most according to claim 4, it is characterised in that: described characteristic behavior is believed
Breath includes eye information, muscle movement and lip expression.
Behavior analysis system based on artificial intelligence the most according to claim 4, it is characterised in that:
Described information acquisition module and described pretreatment submodule are positioned at described user side to be analyzed, described discriminatory analysis submodule
It is positioned at high in the clouds；Data biography is carried out by communication between described pretreatment submodule and described discriminatory analysis submodule
Defeated；
Or, described pretreatment submodule and described discriminatory analysis submodule are located on high in the clouds, and described information acquisition module is with described
Carried out data transmission by communication between pretreatment submodule.
Behavior analysis system based on artificial intelligence the most according to claim 1, it is characterised in that: described behavior analysis system
System also includes anti-with the report that described behavior Treatment Analysis module and described information acquisition module are connected by wireless network respectively
Feedback module, described report feedback module is for the use described to be analyzed judging to obtain according to described behavior Treatment Analysis module analysis
The mental status at family, sums up and obtains behavior analysis report, and make described user to be analyzed according to the report of described behavior analysis
Corresponding information feedback.
Behavior analysis system based on artificial intelligence the most according to claim 8, it is characterised in that: described information feedback
Mode includes: directly feedback and indirect feedback；Wherein,
Described direct feedback includes: by wireless network, feedack is sent directly to described information acquisition module；
Described indirect feedback includes: by feedack by wireless network via described behavior Treatment Analysis module indirect feedback
To described information acquisition module.
Behavior analysis system based on artificial intelligence the most according to claim 9, it is characterised in that:
The described video equipment of described information acquisition module is described to be analyzed for reminding by the way of playing video or image
User；
The described audio frequency apparatus of described information acquisition module is for reminding described user to be analyzed by the way of playing voice；
Described information acquisition module also includes the vibration prompt equipment for reminding described user to be analyzed by the way of vibration.
11. 1 kinds of behavior analysis methods based on artificial intelligence, it is characterised in that: including:
Gather the real time status information of user to be analyzed；
Analyze and process the described real time status information of described user to be analyzed, thus judge the spiritual shape of described user to be analyzed
State.
12. behavior analysis methods based on artificial intelligence according to claim 11, it is characterised in that:
Described real time status information includes: behavioural information and environmental information；Wherein, described behavioural information includes facial expression information
With limbs behavioural information；
The mental status of described user to be analyzed includes fatigue strength and focus.
13. behavior analysis methods based on artificial intelligence according to claim 12, it is characterised in that: described analyzing and processing
The described real time status information of described user to be analyzed, thus judge fatigue strength and the step of focus of described user to be analyzed
Including:
Described behavioural information is detected and extraction process, obtains characteristic behavior information；
Described characteristic behavior information and criterion behavior model are compared analysis, thus judges that described user's to be analyzed is tired
Lao Du and focus；Wherein, described criterion behavior model is the self adaptation of the long-term behavioural information to described user to be analyzed
Mate and formed.
14. behavior analysis methods based on artificial intelligence according to claim 11, it is characterised in that: described behavior analysis
Method also includes: according to the mental status of the user described to be analyzed that judgement obtains, and sums up and obtains behavior analysis report；And according to
Described user to be analyzed is made corresponding information feedback by the report of described behavior analysis.
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