CN114170544A

CN114170544A - Data transmission method and system based on intelligent health data effective confirmation

Info

Publication number: CN114170544A
Application number: CN202111306676.XA
Authority: CN
Inventors: 周士刚; 谢丽娜; 宋琛; 莫朝枫
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-11-05
Filing date: 2021-11-05
Publication date: 2022-03-11

Abstract

The invention provides a data transmission method and a data transmission system based on intelligent health data effective confirmation, and relates to the technical field of data processing. In the invention, each health monitoring video is subjected to effectiveness analysis processing to obtain a corresponding video frame effectiveness confirmation result, wherein the video frame effectiveness confirmation result is used for representing the effective degree of the health monitoring video frame in the corresponding health monitoring video for reflecting the health state detection of the corresponding health monitoring user; determining whether effectiveness analysis processing needs to be carried out again based on the video frame effectiveness confirmation result corresponding to each health monitoring video; and for each health monitoring video, if the health monitoring video needs to be subjected to effectiveness analysis processing again, transmitting the health monitoring video to a video processing server to perform effectiveness analysis processing again. Based on the method, the problem of poor health monitoring effect in the prior art can be solved.

Description

Data transmission method and system based on intelligent health data effective confirmation

Technical Field

The invention relates to the technical field of data processing, in particular to a data transmission method and system based on intelligent health data effective confirmation.

Background

With the continuous development of computer technology and internet technology, the precision of data processing technology is higher and higher, and the corresponding application range is wider and wider. For example, health monitoring may be applied. In order to realize timely and effective monitoring of the health of the user, the user can purchase or configure a response detection device in a common mode. However, the inventors have found that, in the prior art, there is a problem that the detection result obtained is not highly likely due to problems such as the irregularity of the detection operation of the user, and thus the effect of health monitoring is not good.

Disclosure of Invention

In view of the above, the present invention provides a data transmission method and system based on smart health data effective confirmation to solve the problem of poor health monitoring effect in the prior art.

In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:

a data transmission method based on intelligent health data effective confirmation is applied to a health data processing server, the health data processing server is in communication connection with a plurality of health data acquisition devices, and the data transmission method based on intelligent health data effective confirmation comprises the following steps:

aiming at each health monitoring video in a plurality of health monitoring videos corresponding to a plurality of health monitoring users acquired by a plurality of health data acquisition devices, carrying out effectiveness analysis processing on the health monitoring videos included in the health monitoring videos to obtain a video frame effectiveness confirmation result corresponding to the health monitoring videos, wherein each health data acquisition device is used for acquiring the detection action of the corresponding health monitoring user during health state detection to obtain the corresponding health monitoring video, each health monitoring video comprises a plurality of frames of health monitoring video frames, and the video frame effectiveness confirmation result is used for representing the effectiveness degree of the health monitoring video frames in the corresponding health monitoring videos for reflecting the health state detection carried out by the corresponding health monitoring user;

determining whether each health monitoring video needs to be subjected to effectiveness analysis again based on the video frame effectiveness confirmation result corresponding to each health monitoring video;

and aiming at each health monitoring video in the health monitoring videos, if the health monitoring video needs to be subjected to effectiveness analysis processing again, transmitting the health monitoring video to a video processing server in communication connection, wherein the video processing server is used for performing effectiveness analysis processing on the received health monitoring video again so as to determine the effectiveness degree of health state detection performed by a health monitoring user corresponding to the health monitoring video again.

In some preferred embodiments, in the above data transmission method based on intelligent health data validity confirmation, the step of determining whether it is necessary to perform validity analysis processing again on each health monitoring video based on the video frame validity confirmation result corresponding to each health monitoring video includes:

determining a video frame validity confirmation standard result, wherein the video frame validity confirmation standard result is used for representing the standard validity degree of health state detection performed by a health monitoring user;

for each health monitoring video in the plurality of health monitoring videos, determining the magnitude relation between the effective degree of the video frame validity confirmation result representation corresponding to the health monitoring video and the standard effective degree of the video frame validity confirmation standard result representation;

for each health monitoring video in the health monitoring videos, if the effective degree of the video frame validity confirmation result representation corresponding to the health monitoring video is greater than or equal to the standard effective degree of the video frame validity confirmation standard result representation, determining that validity analysis processing does not need to be carried out on the health monitoring video again;

and for each health monitoring video in the health monitoring videos, if the effective degree of the video frame validity confirmation result representation corresponding to the health monitoring video is smaller than the standard effective degree of the video frame validity confirmation standard result representation, determining that the health monitoring video needs to be subjected to validity analysis again.

In some preferred embodiments, in the above data transmission method based on smart health data validity confirmation, the step of determining a result of the video frame validity confirmation criterion includes:

obtaining a preset video frame validity confirmation initial result;

calculating the average value of the effective degrees represented by the plurality of video frame effectiveness confirmation results corresponding to the plurality of health monitoring videos to obtain the corresponding effective degree average value;

and updating the initial effectiveness degree represented by the initial result of the video frame effectiveness confirmation based on the average value of the effectiveness degrees to obtain a corresponding standard effectiveness degree, so as to determine a standard result of the video frame effectiveness confirmation based on the standard effectiveness degree.

In some preferred embodiments, in the above method for transmitting data based on intelligent health data validity confirmation, the step of updating the initial validity degree represented by the initial result of video frame validity confirmation based on the mean value of validity degrees to obtain a corresponding standard validity degree, so as to determine a standard result of video frame validity confirmation based on the standard validity degree includes:

determining a relative magnitude relation between the effective degree mean value and the initial effective degree represented by the video frame effectiveness confirmation initial result;

if the mean value of the effectiveness degrees is determined to be larger than or equal to the initial effectiveness degree represented by the video frame effectiveness confirmation initial result, increasing the initial effectiveness degree to obtain a corresponding standard effectiveness degree so as to determine a video frame effectiveness confirmation standard result based on the standard effectiveness degree;

and if the mean value of the effective degrees is smaller than the initial effective degree represented by the video frame effectiveness confirmation initial result, reducing the initial effective degree to obtain a corresponding standard effective degree so as to determine a video frame effectiveness confirmation standard result based on the standard effective degree.

In some preferred embodiments, in the data transmission method based on smart health data validity confirmation, if it is determined that validity analysis processing needs to be performed on each of the plurality of health monitoring videos, the step of transmitting the health monitoring video to a video processing server connected to a communication link includes:

for each health monitoring video in the plurality of health monitoring videos, if it is determined that the health monitoring video needs to be subjected to effectiveness analysis again, determining the health monitoring video as a health monitoring video to be transmitted, counting the number of the health monitoring videos to be transmitted to obtain a corresponding video counting number, and determining the size between the video counting number and a preset video counting number threshold;

if the video statistic number is smaller than the video statistic number threshold, directly transmitting all the health monitoring videos to be transmitted to a video processing server in communication connection;

if the video statistic number is greater than or equal to the video statistic number threshold, determining video similarity degree values among a plurality of to-be-transmitted health monitoring videos, and performing clustering processing on the plurality of to-be-transmitted health monitoring videos based on the video similarity degree values among the plurality of to-be-transmitted health monitoring videos to obtain at least one monitoring video clustering set corresponding to the plurality of to-be-transmitted health monitoring videos, wherein each monitoring video clustering set in the at least one monitoring video clustering set comprises at least one to-be-transmitted health monitoring video;

and determining transmission priority information corresponding to each monitoring video cluster set in the at least one monitoring video cluster set, and sequentially transmitting the health monitoring videos to be transmitted, which are included in each monitoring video cluster set, to the video processing server based on the transmission priority information corresponding to each monitoring video cluster set.

In some preferred embodiments, in the above data transmission method based on smart health data valid confirmation, if the video statistics number is greater than or equal to the video statistics number threshold, determining video similarity values between a plurality of health monitoring videos to be transmitted, and performing clustering processing on the plurality of health monitoring videos to be transmitted based on the video similarity values between the plurality of health monitoring videos to be transmitted to obtain at least one monitoring video clustering set corresponding to the plurality of health monitoring videos to be transmitted, the method includes:

if the video statistic number is greater than or equal to the video statistic number threshold, calculating an effective degree similarity value between effective degrees represented by the video frame effectiveness confirmation results corresponding to the two health monitoring videos to be transmitted aiming at each two health monitoring videos to be transmitted, and determining the effective degree similarity value as a video similarity value between the two health monitoring videos to be transmitted;

and clustering the plurality of health monitoring videos to be transmitted based on the video similarity degree value between every two health monitoring videos to be transmitted to obtain at least one monitoring video clustering set corresponding to the plurality of health monitoring videos to be transmitted.

In some preferred embodiments, in the above data transmission method based on smart health data effective validation, the step of determining, for each of the at least one monitoring video cluster set, transmission priority information corresponding to the monitoring video cluster set, and sequentially transmitting the health monitoring video to be transmitted included in each of the monitoring video cluster sets to the video processing server based on the transmission priority information corresponding to each of the monitoring video cluster sets includes:

for each monitoring video cluster set in the at least one monitoring video cluster set, performing mean value calculation based on the effective degrees of the video frame effectiveness confirmation result representations corresponding to the health monitoring videos to be transmitted included in the monitoring video cluster set to obtain an effective degree mean value corresponding to the monitoring video cluster set;

and determining transmission priority information corresponding to each monitoring video cluster set based on the size relation between the effective degree average values corresponding to each monitoring video cluster set in the at least one monitoring video cluster set, and sequentially transmitting the health monitoring videos to be transmitted, which are included in each monitoring video cluster set, to the video processing server based on the transmission priority information corresponding to each monitoring video cluster set.

The embodiment of the invention also provides a data transmission system based on intelligent health data effective confirmation, which is applied to a health data processing server, wherein the health data processing server is in communication connection with a plurality of health data acquisition devices, and the data transmission system based on intelligent health data effective confirmation comprises:

an effectiveness analysis processing module, configured to, for each of a plurality of health monitoring videos corresponding to a plurality of health monitoring users acquired by the plurality of health data acquisition devices, analyzing the effectiveness of the health monitoring video to obtain the result of confirming the effectiveness of the video frame corresponding to the health monitoring video, wherein each health data acquisition device is used for acquiring the detection action of the corresponding health monitoring user in the health state detection to obtain the corresponding health monitoring video, each health monitoring video comprises a plurality of frames of health monitoring video frames, the video frame validity confirmation result is used for representing the validity degree of the health monitoring video frame in the corresponding health monitoring video for reflecting the health state detection of the corresponding health monitoring user;

the effectiveness analysis processing confirming module is used for determining whether effectiveness analysis processing needs to be carried out on each health monitoring video again or not based on the video frame effectiveness confirming result corresponding to each health monitoring video;

and the effectiveness analysis reprocessing module is used for transmitting the health monitoring video to a video processing server in communication connection if the health monitoring video needs to be subjected to effectiveness analysis processing again aiming at each health monitoring video in the health monitoring videos, wherein the video processing server is used for carrying out effectiveness analysis processing on the received health monitoring video again so as to determine the effectiveness degree of health state detection carried out by the health monitoring user corresponding to the health monitoring video again.

In some preferred embodiments, in the data transmission system based on smart health data validation, the validation parsing module is specifically configured to:

In some preferred embodiments, in the data transmission system based on smart health data validation, the validity analysis reprocessing module is specifically configured to:

According to the data transmission method and system based on intelligent health data effective confirmation, after the effectiveness analysis processing is carried out on each acquired health monitoring video to obtain the corresponding video frame effectiveness confirmation result, whether the effectiveness analysis processing needs to be carried out on each health monitoring video again can be determined based on the video frame effectiveness confirmation result corresponding to each health monitoring video, and the health monitoring video needing to be subjected to the effectiveness analysis processing again can be transmitted to a video processing server in communication connection to be subjected to the effectiveness analysis processing again, so that the effectiveness degree of health state detection carried out by a corresponding health monitoring user is determined again, the reliability of the finally determined effectiveness degree is guaranteed, and the problem that the health monitoring effect is poor in the prior art is solved.

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

Fig. 1 is a block diagram of a health data processing server according to an embodiment of the present invention.

Fig. 2 is a flowchart illustrating steps included in a data transmission method based on smart health data validation according to an embodiment of the present invention.

Fig. 3 is a block diagram illustrating modules included in a data transmission system based on smart health data validation according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, an embodiment of the present invention provides a health data processing server. Wherein the health data processing server may include a memory and a processor.

In particular, in one particular implementation, the memory and the processor are electrically connected, directly or indirectly, to enable data transfer or interaction. For example, they may be electrically connected to each other via one or more communication buses or signal lines. The memory can have stored therein at least one software function (computer program) in the form of software or firmware. The processor may be configured to execute the executable computer program stored in the memory, so as to implement the data transmission method based on intelligent health data validation provided by the embodiment of the present invention.

Alternatively, in a specific implementation, the Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), a System on Chip (SoC), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components.

With reference to fig. 2, an embodiment of the present invention further provides a data transmission method based on smart health data validation, which can be applied to the health data processing server. The method steps defined by the relevant flow of the intelligent health data effective confirmation-based data transmission method can be realized by the health data processing server, and the health data processing server is in communication connection with a plurality of health data acquisition devices. The specific process shown in FIG. 2 will be described in detail below.

Step S100, aiming at each health monitoring video of a plurality of health monitoring videos corresponding to a plurality of health monitoring users acquired by a plurality of health data acquisition devices, carrying out validity analysis processing on the health monitoring videos included in the health monitoring videos to obtain a video frame validity confirmation result corresponding to the health monitoring videos.

In the embodiment of the present invention, the health data processing server may perform, for each of the obtained plurality of health monitoring videos corresponding to the plurality of health monitoring users acquired by the plurality of health data acquisition devices, validity analysis processing on the health monitoring videos included in the health monitoring videos, so as to obtain a video frame validity confirmation result corresponding to the health monitoring videos. Each health data acquisition device is used for acquiring the detection action of the corresponding health monitoring user in the health state detection to obtain the corresponding health monitoring video, each health monitoring video comprises a plurality of frames of health monitoring video frames, and the video frame validity confirmation result is used for representing the validity degree of the health monitoring video frames in the corresponding health monitoring video for reflecting the health state detection of the corresponding health monitoring user.

Step S200, determining whether each health monitoring video needs to be subjected to effectiveness analysis again or not based on the video frame effectiveness confirmation result corresponding to each health monitoring video.

In the embodiment of the present invention, the health data processing server may determine whether it is necessary to perform effectiveness analysis processing on each of the health monitoring videos again based on a result of determining the effectiveness of the video frame corresponding to each of the health monitoring videos.

Step S300, aiming at each health monitoring video in the health monitoring videos, if the health monitoring video needs to be subjected to effectiveness analysis processing again, the health monitoring video is transmitted to a video processing server in communication connection.

In the embodiment of the present invention, the health data processing server may transmit, for each of the plurality of health monitoring videos, the health monitoring video to a video processing server in communication connection if it is determined that the health monitoring video needs to be subjected to effectiveness analysis again. The video processing server is used for carrying out effectiveness analysis processing on the received health monitoring video again so as to determine the effectiveness degree of health state detection carried out by the health monitoring user corresponding to the health monitoring video again.

Based on the data transmission method, after the effectiveness analysis processing is performed on each acquired health monitoring video to obtain the corresponding video frame effectiveness confirmation result, whether the effectiveness analysis processing needs to be performed on each health monitoring video again can be determined based on the video frame effectiveness confirmation result corresponding to each health monitoring video, and for the health monitoring video needing to be subjected to the effectiveness analysis processing again, the health monitoring video can be transmitted to a video processing server in communication connection to be subjected to the effectiveness analysis processing again, so that the effectiveness degree of the health state detection performed by the corresponding health monitoring user is determined again, the reliability of the finally determined effectiveness degree is guaranteed, and the problem that the effect of health monitoring in the prior art is poor is solved.

Optionally, in a specific implementation manner, the step S100 may include the following step S110, step S120, and step S130, which are described in detail below.

Step S110, obtaining health monitoring videos collected by a plurality of health data collecting devices, and obtaining a plurality of health monitoring videos corresponding to a plurality of corresponding health monitoring users.

In the embodiment of the present invention, the health data processing server may obtain the health monitoring videos acquired by the plurality of health data acquisition devices, and obtain a plurality of health monitoring videos corresponding to a plurality of health monitoring users corresponding to the plurality of health data acquisition devices. Each health data acquisition device is used for acquiring the detection action of the corresponding health monitoring user in the health state detection to obtain the corresponding health monitoring video, and each health monitoring video comprises a plurality of frames of health monitoring video frames of the corresponding health monitoring user.

Step S120, determining video correlation relation information among the plurality of health monitoring videos.

In an embodiment of the present invention, the health data processing server may determine video correlation information between the plurality of health monitoring videos. The video correlation relation information is used for representing the correlation degree among the plurality of health monitoring videos.

Step S130, for each health monitoring video in the plurality of health monitoring videos, performing validity analysis processing on the health monitoring video included in the health monitoring video based on the video correlation relationship information, and obtaining a video frame validity confirmation result corresponding to the health monitoring video.

In the embodiment of the present invention, the health data processing server may perform, for each health monitoring video in the plurality of health monitoring videos, validity analysis processing on the health monitoring video included in the health monitoring video based on the video correlation relationship information, so as to obtain a video frame validity confirmation result corresponding to the health monitoring video. And the video frame validity confirmation result is used for representing the valid degree of the health monitoring video frame in the corresponding health monitoring video for reflecting the health state detection of the corresponding health monitoring user.

Based on the above steps S110, S120, and S130, after obtaining a plurality of health monitoring videos corresponding to a plurality of health monitoring users corresponding to a plurality of health data acquisition devices, video correlation relationship information among the plurality of health monitoring videos may be determined, and then, for each health monitoring video, the health monitoring video included in the health monitoring video is subjected to validity analysis processing based on the video correlation relationship information, so as to obtain a video frame validity confirmation result corresponding to the health monitoring video.

Optionally, in a specific implementation manner, the step S110 may include the following steps:

firstly, judging whether monitoring video sending request information sent by each health data acquisition device is received or not aiming at each health data acquisition device in the plurality of health data acquisition devices;

secondly, for each health data acquisition device in the plurality of health data acquisition devices, if the monitoring video sending request information sent by the health data acquisition device is received, generating corresponding monitoring video sending confirmation information, and sending the monitoring video sending confirmation information to the health data acquisition device, wherein the health data acquisition device sends the currently acquired health monitoring video to the health data processing server based on the monitoring video sending confirmation information;

then, the currently acquired health monitoring videos sent by each health data acquisition device based on the monitoring video sending confirmation information are respectively acquired, and a plurality of health monitoring videos corresponding to a plurality of health monitoring users corresponding to the plurality of health data acquisition devices are acquired.

Optionally, in a specific implementation manner, the step of determining, for each health data acquisition device of the plurality of health data acquisition devices, whether monitoring video transmission request information sent by the health data acquisition device is received may include the following steps:

firstly, judging whether monitoring video acquisition request information sent by each health data acquisition device is received or not aiming at each health data acquisition device in the plurality of health data acquisition devices;

secondly, for each health data acquisition device in the plurality of health data acquisition devices, performing request verification processing on the monitoring video acquisition request information sent by the health data acquisition device, and generating corresponding monitoring video acquisition confirmation information after the request verification is passed;

then, for each health data acquisition device in the plurality of health data acquisition devices, sending monitoring video acquisition confirmation information corresponding to the health data acquisition device, wherein the health data acquisition device is used for acquiring a corresponding health monitoring video based on a detection action of a health monitoring user corresponding to the monitoring video acquisition confirmation information during health state detection;

and finally, aiming at each health data acquisition equipment in the plurality of health data acquisition equipment, after the corresponding monitoring video acquisition confirmation information is sent to the health data acquisition equipment, judging whether monitoring video sending request information sent by the health data acquisition equipment is received or not.

Optionally, in a specific implementation manner, the step of obtaining the health monitoring videos acquired by the health data acquisition devices to obtain a plurality of health monitoring videos corresponding to a plurality of health monitoring users corresponding to the plurality of health data acquisition devices may further include the following steps:

firstly, aiming at each health data acquisition equipment in the plurality of health data acquisition equipment, after corresponding monitoring video acquisition confirmation information is sent to the health data acquisition equipment, timing processing is carried out to obtain a target waiting duration corresponding to the health data acquisition equipment;

secondly, for each health data acquisition device in the plurality of health data acquisition devices, if the target waiting time corresponding to the health data acquisition device is greater than or equal to a preset target waiting time threshold value and monitoring video sending request information sent by the health data acquisition device is not received, generating corresponding monitoring video obtaining notification information, sending the monitoring video obtaining notification information to the health data acquisition device, and controlling the health data acquisition device to send the currently acquired health monitoring video to the health data processing server.

Optionally, in a specific implementation manner, the step S120 may include the following steps:

firstly, for every two health monitoring videos in the plurality of health monitoring videos, calculating the similarity between the two health monitoring videos to obtain the video similarity (such as the similarity between corresponding video frames) corresponding to the two health monitoring videos;

secondly, calculating the similarity between two health monitoring users corresponding to the two health monitoring videos aiming at every two health monitoring videos in the plurality of health monitoring videos to obtain the user similarity corresponding to the two health monitoring videos;

then, for every two health monitoring videos in the plurality of health monitoring videos, similarity fusion calculation is carried out based on the video similarity and the user similarity corresponding to the two health monitoring videos, and video correlation relationship information corresponding to the two health monitoring videos is obtained.

Optionally, in a specific implementation manner, the step of calculating, for each two health monitoring videos in the plurality of health monitoring videos, a similarity between the two health monitoring videos to obtain video similarities corresponding to the two health monitoring videos may include the following steps:

firstly, regarding each health monitoring video in the plurality of health monitoring videos, taking the health monitoring video as a first health monitoring video, and sequentially taking each other health monitoring video as a second health monitoring video corresponding to the first health monitoring video;

secondly, calculating the video frame similarity between each frame of the health monitoring video frame and each frame of the health monitoring video frame in the current second health monitoring video aiming at each frame of the health monitoring video frame in the first health monitoring video, carrying out mean value calculation to obtain the corresponding first video frame similarity mean value, carrying out mean value calculation to the first video frame similarity mean value corresponding to each frame of the health monitoring video frame in the first health monitoring video to obtain the second video frame similarity mean value between the first health monitoring video and the current second health monitoring video,

then, calculating a sum of the second video frame similarity mean values between the first health monitoring video and each corresponding second health monitoring video to obtain a similarity mean value sum value corresponding to the first health monitoring video, and normalizing the second video frame similarity mean values between the first health monitoring video and each corresponding second health monitoring video based on the similarity mean value sum value to obtain a similarity normalized value between the first health monitoring video and each corresponding second health monitoring video;

and finally, for every two health monitoring videos in the plurality of health monitoring videos, when the two health monitoring videos are respectively used as the first health monitoring video and the second health monitoring video which correspond to each other, the obtained two similarity normalization values are subjected to fusion processing, and the video similarity corresponding to the two health monitoring videos is obtained.

Optionally, in a specific implementation manner, the step of calculating, for each two health monitoring videos in the plurality of health monitoring videos, a similarity between two health monitoring users corresponding to the two health monitoring videos to obtain a user similarity corresponding to the two health monitoring videos may include the following steps:

secondly, calculating the user identity correlation degree information between the first health monitoring video and two health monitoring users corresponding to the second health monitoring video (such as determining the identity correlation degree based on the distance degree of the user positions), and calculates the action correlation degree information of the two corresponding health monitoring users in the first health monitoring video and the second health monitoring video corresponding to the first health monitoring video and the second health monitoring video (i.e. performing action recognition on the monitoring video, and then performing similarity calculation based on the action recognition result to obtain the action correlation degree information), and, and performing fusion processing (weighted summation) on the user identity correlation degree information and the action correlation degree information between the first health monitoring video and two health monitoring users corresponding to the second health monitoring video which corresponds to the first health monitoring video at present to obtain the user similarity between the first health monitoring video and the second health monitoring video which corresponds to the first health monitoring video at present.

Optionally, in a specific implementation manner, the step of performing similarity fusion calculation on two health surveillance videos of the plurality of health surveillance videos based on the video similarity and the user similarity corresponding to the two health surveillance videos to obtain video correlation information corresponding to the two health surveillance videos may include the following steps:

firstly, for every two health monitoring videos in the plurality of health monitoring videos, performing mean value calculation on the video similarity and the user similarity corresponding to the two health monitoring videos to obtain video correlation relationship information corresponding to the two health monitoring videos.

Optionally, in a specific implementation manner, the step S130 may include the following steps:

firstly, aiming at each health monitoring video in the plurality of health monitoring videos, screening out at least one target health monitoring video frame (as a representative) from a plurality of health monitoring video frames included in the health monitoring video;

secondly, aiming at each health monitoring video in the plurality of health monitoring videos, performing action identification processing on a target health monitoring video frame corresponding to the health monitoring video to obtain action characteristic information corresponding to the health monitoring video, and performing characteristic similarity calculation on the action characteristic information and pre-configured reference action characteristic information (such as characteristic information of standard action for corresponding detection) to obtain characteristic similarity corresponding to the health monitoring video;

then, for each health monitoring video in the plurality of health monitoring videos, based on the video correlation information and the feature similarity corresponding to the health monitoring video, obtaining a video frame validity confirmation result corresponding to the health monitoring video.

Optionally, in a specific implementation manner, the step of, for each health monitoring video of the plurality of health monitoring videos, screening out at least one target health monitoring video frame from a plurality of health monitoring video frames included in the health monitoring video may include the following steps:

firstly, acquiring a first health monitoring video frame (which may be any one frame or any multiple frames, etc.) and a reference health monitoring video frame of the first health monitoring video frame from a plurality of health monitoring video frames included in the health monitoring video, wherein the reference health monitoring video frame is a health monitoring video frame whose frame timing interval with the corresponding first health monitoring video frame is smaller than a first frame timing interval threshold;

secondly, performing video frame content saturation calculation processing on the first health monitoring video frame based on the pixel values of the pixel points of the first health monitoring video frame to obtain video frame content saturation corresponding to the first health monitoring video frame, and performing video frame content saturation calculation processing on the reference health monitoring video frame based on the pixel values of the pixel points of the reference health monitoring video frame to obtain video frame content saturation of the reference health monitoring video frame;

then, based on the video frame content saturation of the first health monitoring video frame and the video frame content saturation of the reference health monitoring video frame, screening and checking the first health monitoring video frame, and if the first health monitoring video frame passes the screening and checking, taking the first health monitoring video frame as a target health monitoring video frame.

Optionally, in a specific implementation manner, the step of performing screening verification on the first health monitoring video frame based on the video frame content saturation of the first health monitoring video frame and the video frame content saturation of the reference health monitoring video frame may include the following steps:

firstly, calculating the saturation mean value of the video frame content saturation of the reference health monitoring video frame and the video frame content saturation of the first health monitoring video frame;

secondly, determining the maximum video frame content saturation from the video frame content saturation of the first health monitoring video frame and the video frame content saturation of the reference health monitoring video frame;

then, if the difference between the maximum video frame content saturation and the saturation mean is greater than or equal to a saturation threshold, it is determined that the first health surveillance video frame passes the screening verification, and if the difference between the maximum video frame content saturation and the saturation mean is less than the saturation threshold, it is determined that the first health surveillance video frame does not pass the screening verification.

Optionally, in a specific implementation manner, the step of performing video frame content saturation calculation processing on the first health monitoring video frame based on the pixel value of the pixel point of the first health monitoring video frame to obtain the video frame content saturation of the first health monitoring video frame may include the following steps:

firstly, acquiring a plurality of frames of related health monitoring video frames of a first health monitoring video frame from the plurality of frames of health monitoring video frames, and calculating a pixel value representative coefficient of the first health monitoring video frame based on a pixel value of a pixel point of each frame of related health monitoring video frame and a pixel value of a pixel point of the first health monitoring video frame, wherein the related health monitoring video frame is a health monitoring video frame of which the frame time sequence interval between the related health monitoring video frame and the corresponding first health monitoring video frame is smaller than a second frame time sequence interval threshold value;

secondly, acquiring adjacent health monitoring video frames of the first health monitoring video frame from the plurality of health monitoring video frames, wherein the adjacent health monitoring video frames comprise a target number of health monitoring video frames with a frame time sequence of the first health monitoring video frame in the plurality of health monitoring video frames;

then, calculating a pixel value representative coefficient change value of the first health monitoring video frame based on the pixel value representative coefficient of the first health monitoring video frame and the pixel value representative coefficient of each health monitoring video frame in the adjacent health monitoring video frames;

and finally, carrying out weighted summation calculation on the pixel value representative coefficient and the pixel value representative coefficient change value to obtain the video frame content saturation of the first health monitoring video frame.

Optionally, in a specific implementation manner, the step of calculating a pixel value representative coefficient of the first health surveillance video frame based on the pixel value of the pixel point of each frame-associated health surveillance video frame and the pixel value of the pixel point of the first health surveillance video frame may include the following steps:

firstly, calculating the pixel value of a pixel point of a first health monitoring video frame to carry out square sum calculation to obtain the pixel value initial representative coefficient of the first health monitoring video frame, and carrying out square sum calculation to the pixel value of the pixel point of each frame related to the health monitoring video frame to obtain the pixel value initial representative coefficient of each frame related to the health monitoring video frame;

and secondly, performing mean value calculation on the pixel value initial representative coefficient of the first health monitoring video frame and the pixel value initial representative coefficients of the related health monitoring video frames of the frames to obtain the pixel value representative coefficient of the first health monitoring video frame.

Optionally, in a specific implementation manner, the step of calculating a pixel value representative coefficient change value of the first health surveillance video frame based on the pixel value representative coefficient of the first health surveillance video frame and the pixel value representative coefficient of each of the adjacent health surveillance video frames may include the following steps:

firstly, calculating the sum of pixel value representative coefficients between the pixel value representative coefficients of each frame of the adjacent health monitoring video frames, secondly, calculating the difference between the sum of the pixel value representative coefficients and the target number multiple of the pixel value representative coefficients of the first health monitoring video frame, and taking the maximum value between the difference and a preset reference value as the pixel value representative coefficient change value of the first health monitoring video frame.

Optionally, in a specific implementation manner, the step of obtaining, for each health monitoring video in the plurality of health monitoring videos, a video frame validity confirmation result corresponding to the health monitoring video based on the video correlation information and the feature similarity corresponding to the health monitoring video may include the following steps:

firstly, aiming at each health monitoring video in the plurality of health monitoring videos, determining the relative size relationship between the feature similarity corresponding to the health monitoring video and a pre-configured feature similarity threshold value, and when the feature similarity is greater than or equal to the feature similarity threshold, taking the feature similarity as a video frame validity confirmation result corresponding to the health monitoring video, and, when the feature similarity is smaller than the feature similarity threshold, determining a validity confirmation coefficient between the health monitoring video and each other health monitoring video based on video correlation information between the health monitoring video and each other health monitoring video, the validity confirmation coefficient and the video correlation relation information have positive correlation, and the sum of the validity confirmation coefficients of other health monitoring videos is 1;

secondly, for each health monitoring video in the health monitoring videos, based on the validity confirmation coefficient between the health monitoring video and each other health monitoring video, carrying out weighted summation calculation on the feature similarity corresponding to each other health monitoring video to obtain a feature similarity reference value corresponding to the health monitoring video, and determining the relative magnitude relation between the feature similarity reference value and the feature similarity threshold value;

then, for each health monitoring video in the health monitoring videos, if the feature similarity reference value corresponding to the health monitoring video is greater than or equal to the feature similarity threshold value, taking the feature similarity corresponding to the health monitoring video as a video frame validity confirmation result corresponding to the health monitoring video, if the feature similarity reference value corresponding to the health monitoring video is smaller than the feature similarity threshold (indicating that the action is generally not standard, i.e. the precision requirement of the detection action may not be very high), updating the feature similarity based on the feature similarity reference value to obtain a corresponding new feature similarity, and the new feature similarity is used as a video frame validity confirmation result corresponding to the health monitoring video, wherein the new feature similarity has a negative correlation with the feature similarity reference value.

Optionally, in a specific implementation manner, the step S200 may include the following steps:

firstly, determining a video frame validity confirmation standard result, wherein the video frame validity confirmation standard result is used for representing the standard validity degree of health state detection performed by a health monitoring user (namely, used as reference comparison);

secondly, for each health monitoring video in the plurality of health monitoring videos, determining the magnitude relation between the effective degree of the video frame validity confirmation result representation corresponding to the health monitoring video and the standard effective degree of the video frame validity confirmation standard result representation;

then, for each health monitoring video in the health monitoring videos, if the effective degree represented by the video frame effectiveness confirmation result corresponding to the health monitoring video is greater than or equal to the standard effective degree represented by the video frame effectiveness confirmation standard result, determining that the health monitoring video does not need to be subjected to effectiveness analysis again;

finally, for each health monitoring video in the health monitoring videos, if the effectiveness degree of the video frame effectiveness confirmation result representation corresponding to the health monitoring video is smaller than the standard effectiveness degree of the video frame effectiveness confirmation standard result representation, it is determined that the health monitoring video needs to be subjected to effectiveness analysis again.

Optionally, in a specific implementation manner, the step of determining a result of the video frame validity confirmation criterion may include the following steps:

firstly, acquiring a preset video frame validity confirmation initial result;

secondly, calculating the average value of the effective degrees represented by a plurality of video frame effectiveness confirmation results corresponding to the plurality of health monitoring videos to obtain the corresponding average value of the effective degrees;

then, updating the initial effectiveness degree represented by the initial result of the video frame effectiveness confirmation based on the average value of the effectiveness degrees to obtain a corresponding standard effectiveness degree, so as to determine a standard result of the video frame effectiveness confirmation based on the standard effectiveness degree.

Optionally, in a specific implementation manner, the step of updating the initial effectiveness degree represented by the initial result of video frame effectiveness confirmation based on the average value of the effectiveness degrees to obtain a corresponding standard effectiveness degree, so as to determine a standard result of video frame effectiveness confirmation based on the standard effectiveness degree may include the following steps:

firstly, determining a relative size relation between the effective degree mean value and the initial effective degree represented by the video frame effectiveness confirmation initial result;

secondly, if the mean value of the effectiveness degrees is determined to be larger than or equal to the initial effectiveness degree represented by the video frame effectiveness confirmation initial result, increasing the initial effectiveness degree to obtain a corresponding standard effectiveness degree so as to determine a video frame effectiveness confirmation standard result based on the standard effectiveness degree;

and then, if the mean value of the effectiveness degrees is determined to be smaller than the initial effectiveness degree represented by the initial result of the video frame effectiveness confirmation, reducing the initial effectiveness degree to obtain a corresponding standard effectiveness degree, so as to determine the standard result of the video frame effectiveness confirmation based on the standard effectiveness degree.

Optionally, in a specific implementation manner, the step S300 may include the following steps:

firstly, aiming at each health monitoring video in the plurality of health monitoring videos, if the health monitoring video needs to be subjected to effectiveness analysis processing again, determining the health monitoring video as a health monitoring video to be transmitted, counting the number of the health monitoring videos to be transmitted to obtain a corresponding video counting number, and determining the size between the video counting number and a preset video counting number threshold;

secondly, if the video statistic number is smaller than the video statistic number threshold, directly transmitting all the health monitoring videos to be transmitted to a video processing server in communication connection;

then, if the video statistics number is greater than or equal to the video statistics number threshold, determining video similarity degree values among a plurality of health monitoring videos to be transmitted, and performing clustering processing on the plurality of health monitoring videos to be transmitted based on the video similarity degree values among the plurality of health monitoring videos to be transmitted to obtain at least one monitoring video clustering set corresponding to the plurality of health monitoring videos to be transmitted, wherein each monitoring video clustering set in the at least one monitoring video clustering set comprises at least one health monitoring video to be transmitted;

and finally, determining transmission priority information corresponding to each monitoring video cluster set in the at least one monitoring video cluster set, and sequentially transmitting the health monitoring videos to be transmitted, which are included in each monitoring video cluster set, to the video processing based on the transmission priority information corresponding to each monitoring video cluster set.

Optionally, in a specific implementation manner, if the video statistics number is greater than or equal to the video statistics number threshold, determining video similarity values between multiple to-be-transmitted health monitoring videos, and performing clustering processing on the multiple to-be-transmitted health monitoring videos based on the video similarity values between the multiple to-be-transmitted health monitoring videos to obtain at least one monitoring video clustering set corresponding to the multiple to-be-transmitted health monitoring videos may include the following steps:

firstly, if the video statistic number is greater than or equal to the video statistic number threshold, calculating an effective degree similarity value between effective degrees represented by the video frame effectiveness confirmation results corresponding to two to-be-transmitted health monitoring videos aiming at each two to-be-transmitted health monitoring videos in the plurality of to-be-transmitted health monitoring videos, and determining the effective degree similarity value as a video similarity value between the two to-be-transmitted health monitoring videos;

secondly, clustering the plurality of health monitoring videos to be transmitted based on the video similarity degree value between every two health monitoring videos to be transmitted to obtain at least one monitoring video clustering set corresponding to the plurality of health monitoring videos to be transmitted.

Optionally, in a specific implementation manner, the step of determining, for each monitoring video cluster set in the at least one monitoring video cluster set, transmission priority information corresponding to the monitoring video cluster set, and sequentially transmitting the health monitoring videos to be transmitted, which are included in each monitoring video cluster set, to the video processing server based on the transmission priority information corresponding to each monitoring video cluster set may include the following steps:

firstly, for each monitoring video cluster set in at least one monitoring video cluster set, carrying out mean value calculation on the effective degrees represented by the video frame effectiveness confirmation results corresponding to the health monitoring videos to be transmitted included in the monitoring video cluster set to obtain an effective degree mean value corresponding to the monitoring video cluster set;

secondly, determining transmission priority information corresponding to each monitoring video cluster set based on a size relation between effective degree average values corresponding to each monitoring video cluster set in the at least one monitoring video cluster set (for example, the smaller the effective degree average value is, the higher the corresponding transmission priority information is), and sequentially transmitting the health monitoring videos to be transmitted, which are included in each monitoring video cluster set, to the video processing server based on the transmission priority information corresponding to each monitoring video cluster set.

With reference to fig. 3, an embodiment of the present invention further provides a data transmission system based on smart health data validation, which can be applied to the health data processing server. The data transmission system based on the intelligent health data effective confirmation can comprise the following modules:

Optionally, in a specific implementation manner, the validity analysis processing confirmation module in the embodiment is specifically configured to:

Optionally, in a specific implementation manner, the validity analysis reprocessing module in the foregoing embodiment is specifically configured to:

In summary, according to the data transmission method and system based on intelligent health data effective validation provided by the invention, after the effectiveness analysis processing is performed on each acquired health monitoring video to obtain the corresponding video frame effectiveness validation result, whether the effectiveness analysis processing needs to be performed on each health monitoring video again can be determined based on the video frame effectiveness validation result corresponding to each health monitoring video, and for the health monitoring video which needs to be performed with the effectiveness analysis processing again, the health monitoring video can be transmitted to the video processing server in communication connection to perform the effectiveness analysis processing again, so that the effectiveness degree of the health state detection performed by the corresponding health monitoring user is determined again, the reliability of the finally determined effectiveness degree is ensured, and the problem of poor health monitoring effect in the prior art is solved.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A data transmission method based on intelligent health data effective confirmation is applied to a health data processing server, the health data processing server is in communication connection with a plurality of health data acquisition devices, and the data transmission method based on intelligent health data effective confirmation comprises the following steps:

2. The method as claimed in claim 1, wherein the step of determining whether to perform the validity analysis process again on each of the health surveillance videos based on the video frame validity confirmation result corresponding to each of the health surveillance videos comprises:

3. The method of claim 2, wherein the step of determining the result of the video frame validity determination criteria comprises:

obtaining a preset video frame validity confirmation initial result;

4. The method as claimed in claim 3, wherein the step of updating the initial validity degree represented by the initial result of video frame validity confirmation based on the mean value of validity degrees to obtain a corresponding standard validity degree, so as to determine the standard result of video frame validity confirmation based on the standard validity degree comprises:

5. The method according to any one of claims 1 to 4, wherein the step of transmitting the health monitoring video to a video processing server in communication connection if it is determined that the health monitoring video needs to be further processed for validity analysis for each of the plurality of health monitoring videos comprises:

6. The method according to claim 5, wherein if the video statistics number is greater than or equal to the video statistics number threshold, determining video similarity values between a plurality of to-be-transmitted health surveillance videos, and performing clustering processing on the plurality of to-be-transmitted health surveillance videos based on the video similarity values between the plurality of to-be-transmitted health surveillance videos to obtain at least one surveillance video clustering set corresponding to the plurality of to-be-transmitted health surveillance videos, includes:

7. The method as claimed in claim 5, wherein the step of determining, for each of the at least one surveillance video cluster set, transmission priority information corresponding to the surveillance video cluster set, and sequentially transmitting the health surveillance video to be transmitted included in each of the surveillance video cluster sets to the video processing server based on the transmission priority information corresponding to each of the surveillance video cluster sets comprises:

8. The utility model provides a data transmission system based on wisdom healthy data is valid to be confirmed which characterized in that is applied to healthy data processing server, healthy data processing server communication connection has a plurality of healthy data acquisition equipment, data transmission system based on wisdom healthy data is valid to be confirmed includes:

9. The data transmission system according to claim 8, wherein the validity analysis processing confirmation module is specifically configured to:

10. The data transmission system according to claim 8, wherein the validity analysis reprocessing module is specifically configured to: