CN113596849B - Wireless communication channel dynamic allocation method and system for smart home - Google Patents
Wireless communication channel dynamic allocation method and system for smart home Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
- H04W16/10—Dynamic resource partitioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
According to the method and the system for dynamically distributing the wireless communication channels of the smart home, feature fusion is carried out on various scene tracks to obtain the global feature description track of the smart home control data, sample identification can be carried out on the track to be processed, when a preset sample is identified, the preset sample track is selected from the track to be processed, the communication track motion state is determined according to the sample track, and dynamic distribution is carried out on the sample track, the communication track motion state and the global feature description track, so that communication track motion is carried out on the smart home control data. The intelligent home control data distribution method has the advantages that the intelligent home control data distribution principle is reminded in real time in the intelligent home control data distribution process, the triggered error data are reminded, the probability of error occurrence of the intelligent home control data is reduced, unreasonable distribution paths caused by related communication description labels, communication classification models or key description contents are avoided, and therefore intelligent home control data distribution efficiency is improved.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a method and a system for dynamically distributing wireless communication channels of intelligent home.
Background
The channel dynamic allocation is to optimally configure channel resources through channel quality criteria and traffic parameters. Through reasonable distribution of wireless communication data of the intelligent home, the transmission rate of related communication data can be improved, and therefore cost is effectively reduced.
However, in the process of allocating transmission tracks for relevant communication data, there is a case where the allocation of transmission tracks for relevant communication data is inaccurate, which may result in that relevant communication data cannot be accurately transmitted.
Disclosure of Invention
In view of the above, the application provides a method and a system for dynamically allocating wireless communication channels of smart home.
In a first aspect, a method for dynamically allocating a wireless communication channel of an intelligent home is provided, where the method includes:
acquiring various scene tracks near intelligent home control data;
feature fusion is carried out on the plurality of scene tracks to obtain a global feature description track of the intelligent home control data;
sample identification is carried out on a track to be processed so as to identify whether the track to be processed contains a preset sample or not, the track to be processed comprises at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks for controlling data movement of the intelligent home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content;
When the track to be processed is identified to contain the preset sample, selecting the preset sample track from the track to be processed, and determining a communication track motion state matched with a scene to which the intelligent home control data belong according to the sample track;
and dynamically distributing the sample track, the communication track motion state and the global feature description track to perform communication track motion on intelligent home control data.
Further, before selecting the preset sample track from the tracks to be processed and determining the motion state of the communication track adapted to the scene according to the sample track, the method further includes:
judging whether a scene to which the intelligent home control data belongs meets the communication track movement condition or not through a preset data template according to a sample identification result of the track to be processed and at least one of the content attribute and the transmission state of the intelligent home control data;
when the scene to which the intelligent home control data belongs is determined to meet the communication track motion condition, triggering and executing a program for selecting the preset sample track from the tracks to be processed, and determining the communication track motion state adapted to the scene according to the sample track.
Further, the sample recognition of the track to be processed includes:
and taking the track to be processed as the input of a track simulation drawing thread, and identifying whether the track to be processed contains the preset sample or not through the track simulation drawing thread, wherein the track simulation drawing thread is obtained by configuring a plurality of sample tracks containing the preset sample.
Further, the selecting the preset sample track from the tracks to be processed includes:
determining at least one candidate track containing the preset sample from the tracks to be processed;
determining the credibility of the preset samples contained in each candidate track;
and selecting the sample track from the at least one candidate track based on the credibility of the preset sample contained in each candidate track.
Further, the selecting the sample track from the at least one candidate track based on the reliability of the preset sample contained in each candidate track includes:
if the preset samples contained in the at least one candidate track are the same samples, determining a sample candidate track with the highest reliability of the contained preset samples from the at least one candidate track, selecting a partial region track where the preset samples are located in the sample candidate track, and determining the sample track based on the selected track;
If the preset samples contained in the at least one candidate track are different from each other, determining a candidate track with the reliability of the contained preset samples larger than a reliability preset vector from the at least one candidate track, selecting a part of area tracks where the preset samples are located in the determined candidate track, and determining the sample track based on the selected tracks;
and if the at least one candidate track comprises i first candidate tracks and j second candidate tracks, screening a first candidate track with the largest credibility of the preset samples from the i first candidate tracks, screening a second candidate track with the credibility larger than the preset vector of credibility of the preset samples from the j second candidate tracks, respectively selecting partial area tracks where the preset samples are located in the screened first candidate tracks and the second candidate tracks, determining the sample tracks based on the selected tracks, wherein the preset samples contained in the i first candidate tracks are the same samples, the j second candidate tracks refer to the preset samples which are different from each other except the i first candidate tracks, and i and j are positive integers.
Further, the determining a sample trajectory based on the selected trajectory includes:
and preprocessing the selected track to obtain the sample track, wherein the preprocessing comprises at least one of expanding processing and reinforcing processing.
Further, determining, according to the sample track, a communication track motion state adapted to a scene to which the smart home control data belongs, including at least one of the following modes:
if the sample track contains a communication description tag, determining content attribute warning data matched with the communication description tag, and determining the motion state of the communication track according to the content attribute warning data matched with the communication description tag;
if the sample track contains a communication classification model, determining error warning data matched with the communication classification model, and determining the motion state of the communication track according to the error warning data matched with the communication classification model;
and if the sample track contains key descriptive contents, determining key descriptive content warning data adapted to the key descriptive contents, and determining the motion state of the communication track according to the key descriptive content warning data.
Further, the determining content attribute warning data adapted to the communication description tag includes:
determining the type of the communication description tag;
and determining content attribute warning data adapted to the communication description tag from the one-to-one correspondence of the cached communication description tags of various types and the content attribute warning data based on the type of the communication description tag.
Further, the dynamically assigning the sample trajectory, the communication trajectory motion state, and the global feature description trajectory includes:
iterating the communication track motion state in a preset interval range of the sample track;
and dynamically distributing the sample track iteration with the communication track motion state on the global feature description track, or dynamically distributing the sample track with the communication track motion state and the global feature description track.
In a second aspect, a wireless communication channel dynamic allocation system for smart home is provided, including a data acquisition end and a data processing terminal, where the data acquisition end is in communication connection with the data processing terminal, and the data processing terminal is specifically configured to:
Acquiring various scene tracks near intelligent home control data;
feature fusion is carried out on the plurality of scene tracks to obtain a global feature description track of the intelligent home control data;
sample identification is carried out on a track to be processed so as to identify whether the track to be processed contains a preset sample or not, the track to be processed comprises at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks for controlling data movement of the intelligent home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content;
when the track to be processed is identified to contain the preset sample, selecting the preset sample track from the track to be processed, and determining a communication track motion state matched with a scene to which the intelligent home control data belong according to the sample track;
and dynamically distributing the sample track, the communication track motion state and the global feature description track to perform communication track motion on intelligent home control data.
According to the wireless communication channel dynamic allocation method and system for the smart home, after various scene tracks near the smart home control data are acquired, not only can feature fusion be conducted on the various scene tracks to obtain the global feature description track of the smart home control data, but also sample identification can be conducted on the track to be processed to identify whether the sample track contains preset samples such as communication description labels, communication classification models or key description contents, when the sample track to be processed is identified to contain the preset samples, the preset sample track can be selected from the track to be processed, the communication track motion state matched with the scene to which the smart home control data belong is determined according to the sample track, and dynamic allocation is conducted on the sample track, the communication track motion state and the global feature description track to conduct communication track motion on the smart home control data. Therefore, the intelligent home control data distribution principle can be reminded in real time in the intelligent home control data distribution process, error data which can be triggered are reminded, the probability of errors of the intelligent home control data is reduced, and unreasonable distribution paths caused by related communication description labels, communication classification models or key description contents are avoided, so that the intelligent home control data distribution efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for dynamically allocating wireless communication channels of smart home according to an embodiment of the present application.
Fig. 2 is a block diagram of a device for dynamically allocating wireless communication channels of smart home according to an embodiment of the present application.
Fig. 3 is a schematic diagram of a wireless communication channel dynamic allocation system for smart home according to an embodiment of the present application.
Detailed Description
In order to better understand the above technical solutions, the following detailed description of the technical solutions of the present application is made by using the accompanying drawings and specific embodiments, and it should be understood that the specific features of the embodiments and the embodiments of the present application are detailed descriptions of the technical solutions of the present application, and not limiting the technical solutions of the present application, and the technical features of the embodiments and the embodiments of the present application may be combined with each other without conflict.
Referring to fig. 1, a method for dynamically allocating a wireless communication channel of an intelligent home is shown, which may include the following steps 100-500.
Step 100, acquiring various scene tracks near the intelligent home control data.
Illustratively, a variety of scene trajectories are used to characterize a variety of transmission channels.
And 200, carrying out feature fusion on the various scene tracks to obtain a global feature description track of the intelligent home control data.
Illustratively, the global feature description track is used to characterize important features of a variety of scene tracks.
Step 300, sample identification is performed on the track to be processed to identify whether the track to be processed contains a preset sample or not.
The track to be processed includes at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks of control data movement of the smart home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content.
Step 400, when the fact that the track to be processed contains the preset sample is identified, selecting the preset sample track from the track to be processed, and determining a communication track motion state matched with a scene to which the intelligent home control data belong according to the sample track.
The communication track motion state is used for representing the motion state of relevant communication data in a sample track selected in advance in the track to be processed.
And 500, dynamically distributing the sample track, the communication track motion state and the global feature description track to perform communication track motion on intelligent home control data.
Exemplary, the communication track motion is used for representing the transmission state of the smart home control data.
It may be understood that, when the technical solutions described in the above steps 100-500 are executed, after obtaining multiple scene tracks near the smart home control data, not only feature fusion may be performed on the multiple scene tracks to obtain a global feature description track of the smart home control data, but also sample recognition may be performed on the track to be processed to identify whether the sample track contains a preset sample such as a communication description tag, a communication classification model or a key description content, and when the sample track to be processed is identified to contain the preset sample, the preset sample track may be selected from the track to be processed, and a communication track motion state adapted to the scene to which the smart home control data belongs is determined according to the sample track, and dynamic allocation is performed on the sample track, the communication track motion state and the global feature description track to perform communication track motion on the smart home control data. Therefore, the intelligent home control data distribution principle can be reminded in real time in the intelligent home control data distribution process, error data which can be triggered are reminded, the probability of errors of the intelligent home control data is reduced, and unreasonable distribution paths caused by related communication description labels, communication classification models or key description contents are avoided, so that the intelligent home control data distribution efficiency is improved.
Based on the above basis, the pre-set sample track is selected from the tracks to be processed, and the technical scheme described in the following step q1 and step q2 can be further included before the communication track motion state adapted to the scene is determined according to the sample track.
And q1, judging whether a scene to which the intelligent home control data belongs meets the communication track movement condition or not through a preset data template according to the sample identification result of the track to be processed and at least one of the content attribute and the transmission state of the intelligent home control data.
And q2, triggering and executing a program for selecting the preset sample track from the tracks to be processed and determining the motion state of the communication track adapted to the scene according to the sample track when the scene to which the intelligent home control data belongs is determined to meet the motion condition of the communication track.
It can be understood that when the technical solutions described in the above steps q1 and q2 are executed, the preset sample track is selected from the tracks to be processed, and when the sample track is used, the problem of judgment error caused by multiple conditions of content attribute and transmission state is improved, so that the motion state of the communication track adapted to the scene can be accurately determined.
In an alternative embodiment, the inventor finds that when the sample is identified for the track to be processed, there is a problem that the calculation of the track simulation drawing thread is wrong, so that it is difficult to accurately identify the sample, and in order to improve the technical problem, the step of identifying the sample for the track to be processed described in step 300 may specifically include the following technical scheme described in step w 1.
And step w1, taking the track to be processed as the input of a track simulation drawing thread, and identifying whether the track to be processed contains the preset sample or not through the track simulation drawing thread, wherein the track simulation drawing thread is obtained by configuring a plurality of sample tracks containing the preset sample.
It can be appreciated that when the technical scheme described in the step w1 is executed, the problem of calculation errors of the trace simulation drawing thread is solved when the sample identification is performed on the trace to be processed, so that the sample identification can be accurately performed.
In an alternative embodiment, the inventor finds that when the preset sample track is selected from the tracks to be processed, there is a problem that each candidate track is inaccurate, so that it is difficult to accurately select the preset sample track, and in order to improve the technical problem, the step of selecting the preset sample track from the tracks to be processed described in step 400 may specifically include the following technical solutions described in steps e 1-e 3.
And e1, determining at least one candidate track containing the preset sample from the tracks to be processed.
And e2, determining the credibility of the preset samples contained in each candidate track.
And e3, selecting the sample track from the at least one candidate track based on the credibility of the preset sample contained in each candidate track.
It can be appreciated that when the technical solutions described in the above steps e1 to e3 are executed, the problem of inaccuracy of each candidate track is avoided when the preset sample track is selected from the tracks to be processed, so that the preset sample track can be accurately selected.
In an alternative embodiment, the inventor finds that when the sample track is selected from the at least one candidate track based on the reliability of the preset sample contained in each candidate track, there are a plurality of candidate tracks that cause an inaccurate sample track problem, so that it is difficult to accurately select the sample track, and in order to improve the technical problem, the step of selecting the sample track from the at least one candidate track based on the reliability of the preset sample contained in each candidate track described in the step e3 may specifically include the technical scheme described in the following steps e 31-e 33.
And e31, if the preset samples contained in the at least one candidate track are the same samples, determining a sample candidate track with the highest reliability of the contained preset samples from the at least one candidate track, selecting a partial region track where the preset samples are located in the sample candidate track, and determining the sample track based on the selected track.
And e32, if the preset samples contained in the at least one candidate track are different from each other, determining a candidate track with the reliability of the contained preset samples larger than the reliability preset vector from the at least one candidate track, selecting a partial area track where the preset samples are located in the determined candidate track, and determining the sample track based on the selected track.
And e33, if the at least one candidate track includes i first candidate tracks and j second candidate tracks, selecting a first candidate track with the highest reliability of the preset samples from the i first candidate tracks, selecting a second candidate track with the reliability greater than the reliability preset vector from the j second candidate tracks, selecting partial area tracks where the preset samples are located from the selected first candidate tracks and the second candidate tracks, respectively, determining the sample tracks based on the selected tracks, wherein the preset samples contained in the i first candidate tracks are the same samples, the j second candidate tracks refer to two different candidate tracks of the preset samples which are except the i first candidate tracks, and i and j are positive integers.
It can be appreciated that when the technical solutions described in the above steps e 31-e 33 are executed, based on the reliability of the preset sample included in each candidate track, when the sample track is selected from the at least one candidate track, the problem that the sample track is inaccurate due to multiple candidate tracks is improved, so that the sample track can be accurately selected.
In an alternative embodiment, the inventor finds that when the trace is selected, there is a problem that the trace is not accurately preprocessed, so that it is difficult to accurately determine the sample trace, and in order to improve the technical problem, the step of determining the sample trace based on the selected trace described in the step e32 may specifically include a technical scheme described in the following step r 1.
And r1, preprocessing the selected track to obtain the sample track, wherein the preprocessing comprises at least one of expanding processing and reinforcing processing.
It can be appreciated that when the technical scheme described in the step r1 is executed, the problem that the preprocessing of the trace is inaccurate is solved based on the selected trace, so that the sample trace can be accurately determined.
In an alternative embodiment, determining, according to the sample track, a communication track motion state adapted to a scene to which the smart home control data belongs, where the communication track motion state includes at least one of the following steps, and may specifically include a technical scheme described in the following steps t1 to t 3.
And step t1, if the sample track contains a communication description tag, determining content attribute warning data matched with the communication description tag, and determining the motion state of the communication track according to the content attribute warning data matched with the communication description tag.
And t2, if the sample track contains a communication classification model, determining error warning data matched with the communication classification model, and determining the motion state of the communication track according to the error warning data matched with the communication classification model.
And step t3, if the sample track contains key descriptive contents, determining key descriptive content warning data adapted to the key descriptive contents, and determining the communication track motion state according to the key descriptive content warning data.
It can be understood that when the technical solution described in the above steps t1 to t3 is executed, the accuracy of the communication track motion state is improved by precisely determining the content attribute warning data adapted to the communication description tag.
In an alternative embodiment, the inventor finds that when determining the content attribute warning data adapted to the communication description tag, there is a problem that the type of the communication description tag is unreliable, so that it is difficult to reliably determine the content attribute warning data adapted to the communication description tag, and in order to improve the technical problem, the step of determining the content attribute warning data adapted to the communication description tag described in step t1 may specifically include the following technical solutions described in step t11 and step t 12.
Step t11, determining the type of the communication description tag.
And step t12, determining the content attribute warning data matched with the communication description tag from the one-to-one correspondence relationship between the cached communication description tags of various types and the content attribute warning data based on the types of the communication description tags.
It can be understood that when the technical solutions described in the above steps t11 and t12 are executed, the problem that the kind of the communication description tag is unreliable is improved when the content attribute warning data adapted to the communication description tag is determined, so that the content attribute warning data adapted to the communication description tag can be reliably determined.
In an alternative embodiment, the inventor finds that when the sample track, the communication track motion state and the global feature description track are dynamically allocated, there is a problem that a preset interval range is inaccurate, so that it is difficult to accurately perform dynamic allocation, and in order to improve the technical problem, the step of dynamically allocating the sample track, the communication track motion state and the global feature description track described in step 500 may specifically include the technical schemes described in the following steps y1 and y 2.
And step y1, iterating the motion state of the communication track in a preset interval range of the sample track.
And step y2, dynamically distributing the sample track iterated with the communication track motion state on the global feature description track, or dynamically distributing the sample track iterated with the communication track motion state and the global feature description track.
It can be understood that when the technical schemes described in the above steps y1 and y2 are executed, the problem of inaccurate preset interval range is solved when the sample track, the communication track motion state and the global feature description track are dynamically allocated, so that the dynamic allocation can be accurately performed.
Based on the above basis, the method can further comprise the following technical schemes described in step a1 and step a2 before the preset sample track is selected from the tracks to be processed and the communication track motion state adapted to the scene is determined according to the sample track,
and a step a1 of determining whether the intelligent home control data has started the communication track movement performance.
And a step a2 of triggering and executing a program for selecting the preset sample track from the tracks to be processed and determining the communication track motion state adapted to the scene according to the sample track if the communication track motion performance is started by the intelligent home control data.
It can be appreciated that when the technical solutions described in the above steps a1 and a2 are executed, the integrity of the program of the communication track motion state adapted to the associated scene is improved by completely determining whether the smart home control data has started the communication track motion performance.
Based on the above basis, before determining whether the smart home control data has started the communication track movement performance, the following technical schemes described in step s1 and step s2 may be further included.
Step s1, acquiring a distribution mode of the intelligent home control data, if the distribution mode of the intelligent home control data meets a mode preset vector, starting the communication track motion performance to acquire the distribution mode of the intelligent home control data, and if the distribution mode of the intelligent home control data meets the mode preset vector, starting the communication track motion performance.
Step s2, or when a user opening operation on the communication track movement performance is identified, opening the communication track movement performance.
It can be understood that, when the technical schemes described in the step s1 and the step s2 are executed, the accuracy of the motion performance of the communication track is improved by a distribution mode.
On the basis of the foregoing, please refer to fig. 2 in combination, there is provided a device 200 for dynamically allocating wireless communication channels of smart home, which is applied to a data processing terminal, and the device includes:
the control data acquisition module 210 is configured to acquire multiple scene tracks near the smart home control data;
the description track fusion module 220 is configured to perform feature fusion on the multiple scene tracks to obtain a global feature description track of the smart home control data;
the sample recognition module 230 is configured to perform sample recognition on a track to be processed, so as to recognize whether the track to be processed contains a preset sample, where the track to be processed includes at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks of control data motion of the smart home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content;
the motion state determining module 240 is configured to, when it is identified that the to-be-processed track includes the preset sample, select the preset sample track from the to-be-processed tracks, and determine a motion state of a communication track adapted to a scene to which the smart home control data belongs according to the sample track;
The track motion distribution module 250 is configured to dynamically distribute the sample track, the communication track motion state, and the global feature description track, so as to perform communication track motion on smart home control data.
On the basis of the above, referring to fig. 3 in combination, a system 300 for dynamically allocating wireless communication channels of smart home is shown, which includes a processor 310 and a memory 320 in communication with each other, where the processor 310 is configured to read and execute a computer program from the memory 320 to implement the above method.
On the basis of the above, there is also provided a computer readable storage medium on which a computer program stored which, when run, implements the above method.
In summary, based on the above scheme, after acquiring multiple scene tracks near the smart home control data, not only can feature fusion be performed on the multiple scene tracks to obtain a global feature description track of the smart home control data, but also sample recognition can be performed on the track to be processed to identify whether the sample track contains a preset sample such as a communication description tag, a communication classification model or key description content, when the sample track to be processed is identified to contain the preset sample, the preset sample track can be selected from the track to be processed, and a communication track motion state adapted to the scene to which the smart home control data belongs is determined according to the sample track, and the sample track, the communication track motion state and the global feature description track are dynamically allocated to perform communication track motion on the smart home control data. Therefore, the intelligent home control data distribution principle can be reminded in real time in the intelligent home control data distribution process, error data which can be triggered are reminded, the probability of errors of the intelligent home control data is reduced, and unreasonable distribution paths caused by related communication description labels, communication classification models or key description contents are avoided, so that the intelligent home control data distribution efficiency is improved.
It should be appreciated that the systems and modules thereof shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may then be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system of the present application and its modules may be implemented not only with hardware circuitry such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also with software executed by various types of processors, for example, and with a combination of the above hardware circuitry and software (e.g., firmware).
It should be noted that, the advantages that may be generated by different embodiments may be different, and in different embodiments, the advantages that may be generated may be any one or a combination of several of the above, or any other possible advantages that may be obtained.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements and adaptations of the application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within the present disclosure, and therefore, such modifications, improvements, and adaptations are intended to be within the spirit and scope of the exemplary embodiments of the present disclosure.
Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the application may be combined as suitable.
Furthermore, those skilled in the art will appreciate that the various aspects of the application are illustrated and described in the context of a number of patentable categories or circumstances, including any novel and useful procedures, machines, products, or materials, or any novel and useful modifications thereof. Accordingly, aspects of the application may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the application may take the form of a computer product, comprising computer-readable program code, embodied in one or more computer-readable media.
The computer storage medium may contain a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take on a variety of forms, including electro-magnetic, optical, etc., or any suitable combination thereof. A computer storage medium may be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.
The computer program code necessary for operation of portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C ++, c#, vb net, python, etc., a conventional programming language such as C language, visual Basic, fortran 2003, perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, ruby and Groovy, or other programming languages, etc. The program code may execute entirely on the user's computer or as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or the use of services such as software as a service (SaaS) in a cloud computing environment.
Furthermore, the order in which the elements and sequences are presented, the use of numerical letters, or other designations are used in the application is not intended to limit the sequence of the processes and methods unless specifically recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of example, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the application. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in order to simplify the description of the present disclosure and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are required by the subject application. Indeed, less than all of the features of a single embodiment disclosed above.
In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the numbers allow for adaptive variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations in some embodiments for use in determining the breadth of the range, in particular embodiments, the numerical values set forth herein are as precisely as possible.
Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited herein is hereby incorporated by reference in its entirety. Except for the application history file that is inconsistent or conflicting with this disclosure, the file (currently or later attached to this disclosure) that limits the broadest scope of the claims of this disclosure is also excluded. It is noted that the description, definition, and/or use of the term in the appended claims controls the description, definition, and/or use of the term in this application if there is a discrepancy or conflict between the description, definition, and/or use of the term in the appended claims.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the application. Thus, by way of example, and not limitation, alternative configurations of embodiments of the application may be considered in keeping with the teachings of the application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly described and depicted herein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (8)
1. A method for dynamically allocating a wireless communication channel of an intelligent home, the method comprising:
acquiring various scene tracks near intelligent home control data;
feature fusion is carried out on the plurality of scene tracks to obtain a global feature description track of the intelligent home control data;
sample identification is carried out on a track to be processed so as to identify whether the track to be processed contains a preset sample or not, the track to be processed comprises at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks for controlling data movement of the intelligent home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content;
when the track to be processed is identified to contain the preset sample, selecting the preset sample track from the track to be processed, and determining a communication track motion state matched with a scene to which the intelligent home control data belong according to the sample track;
dynamically distributing the sample track, the communication track motion state and the global feature description track to perform communication track motion on intelligent home control data;
The selecting the preset sample track from the tracks to be processed comprises the following steps:
determining at least one candidate track containing the preset sample from the tracks to be processed;
determining the credibility of the preset samples contained in each candidate track;
selecting the sample track from at least one candidate track based on the credibility of the preset sample contained in each candidate track;
the selecting the sample track from the at least one candidate track based on the credibility of the preset sample contained in each candidate track comprises the following steps:
if the preset samples contained in the at least one candidate track are the same samples, determining a sample candidate track with the highest reliability of the contained preset samples from the at least one candidate track, selecting a partial region track where the preset samples are located in the sample candidate track, and determining the sample track based on the selected track;
if the preset samples contained in the at least one candidate track are different from each other, determining a candidate track with the reliability of the contained preset samples larger than a reliability preset vector from the at least one candidate track, selecting a part of area tracks where the preset samples are located in the determined candidate track, and determining the sample track based on the selected tracks;
And if the at least one candidate track comprises i first candidate tracks and j second candidate tracks, screening a first candidate track with the largest credibility of the preset samples from the i first candidate tracks, screening a second candidate track with the credibility larger than the preset vector of credibility of the preset samples from the j second candidate tracks, respectively selecting partial area tracks where the preset samples are located in the screened first candidate tracks and the second candidate tracks, determining the sample tracks based on the selected tracks, wherein the preset samples contained in the i first candidate tracks are the same samples, the j second candidate tracks refer to the preset samples which are different from each other except the i first candidate tracks, and i and j are positive integers.
2. The method according to claim 1, wherein before selecting the preset sample track from the tracks to be processed and determining the communication track motion state adapted to the scene according to the sample track, the method further comprises:
judging whether a scene to which the intelligent home control data belongs meets the communication track movement condition or not through a preset data template according to a sample identification result of the track to be processed and at least one of the content attribute and the transmission state of the intelligent home control data;
When the scene to which the intelligent home control data belongs is determined to meet the communication track motion condition, triggering and executing a program for selecting the preset sample track from the tracks to be processed, and determining the communication track motion state adapted to the scene according to the sample track.
3. The method of claim 1, wherein the sample recognition of the trajectory to be processed comprises:
and taking the track to be processed as the input of a track simulation drawing thread, and identifying whether the track to be processed contains the preset sample or not through the track simulation drawing thread, wherein the track simulation drawing thread is obtained by configuring a plurality of sample tracks containing the preset sample.
4. The method of claim 1, wherein the determining a sample trajectory based on the selected trajectory comprises:
and preprocessing the selected track to obtain the sample track, wherein the preprocessing comprises at least one of expanding processing and reinforcing processing.
5. The method of claim 1, wherein determining a communication track motion state adapted to a scene to which the smart home control data belongs from the sample track comprises at least one of:
If the sample track contains a communication description tag, determining content attribute warning data matched with the communication description tag, and determining the motion state of the communication track according to the content attribute warning data matched with the communication description tag;
if the sample track contains a communication classification model, determining error warning data matched with the communication classification model, and determining the motion state of the communication track according to the error warning data matched with the communication classification model;
and if the sample track contains key descriptive contents, determining key descriptive content warning data adapted to the key descriptive contents, and determining the motion state of the communication track according to the key descriptive content warning data.
6. The method of claim 5, wherein said determining content attribute alert data adapted to the communication description tag comprises:
determining the type of the communication description tag;
and determining content attribute warning data adapted to the communication description tag from the one-to-one correspondence of the cached communication description tags of various types and the content attribute warning data based on the type of the communication description tag.
7. The method of claim 1, wherein the dynamically assigning the sample trajectory, the communication trajectory motion state, and the global feature description trajectory comprises:
iterating the communication track motion state in a preset interval range of the sample track;
and dynamically distributing the sample track iteration with the communication track motion state on the global feature description track, or dynamically distributing the sample track with the communication track motion state and the global feature description track.
8. The utility model provides a wireless communication channel dynamic distribution system of intelligent house which characterized in that includes data acquisition end and data processing terminal, data acquisition end with data processing terminal communication connection, data processing terminal specifically is used for:
acquiring various scene tracks near intelligent home control data;
feature fusion is carried out on the plurality of scene tracks to obtain a global feature description track of the intelligent home control data;
sample identification is carried out on a track to be processed so as to identify whether the track to be processed contains a preset sample or not, the track to be processed comprises at least one of the global feature description track and a plurality of specific tracks, the plurality of specific tracks are tracks for controlling data movement of the intelligent home control data, and the preset sample is at least one of a communication description tag, a communication classification model and key description content;
When the track to be processed is identified to contain the preset sample, selecting the preset sample track from the track to be processed, and determining a communication track motion state matched with a scene to which the intelligent home control data belong according to the sample track;
dynamically distributing the sample track, the communication track motion state and the global feature description track to perform communication track motion on intelligent home control data;
the selecting the preset sample track from the tracks to be processed comprises the following steps:
determining at least one candidate track containing the preset sample from the tracks to be processed;
determining the credibility of the preset samples contained in each candidate track;
selecting the sample track from at least one candidate track based on the credibility of the preset sample contained in each candidate track;
the selecting the sample track from the at least one candidate track based on the credibility of the preset sample contained in each candidate track comprises the following steps:
if the preset samples contained in the at least one candidate track are the same samples, determining a sample candidate track with the highest reliability of the contained preset samples from the at least one candidate track, selecting a partial region track where the preset samples are located in the sample candidate track, and determining the sample track based on the selected track;
If the preset samples contained in the at least one candidate track are different from each other, determining a candidate track with the reliability of the contained preset samples larger than a reliability preset vector from the at least one candidate track, selecting a part of area tracks where the preset samples are located in the determined candidate track, and determining the sample track based on the selected tracks;
and if the at least one candidate track comprises i first candidate tracks and j second candidate tracks, screening a first candidate track with the largest credibility of the preset samples from the i first candidate tracks, screening a second candidate track with the credibility larger than the preset vector of credibility of the preset samples from the j second candidate tracks, respectively selecting partial area tracks where the preset samples are located in the screened first candidate tracks and the second candidate tracks, determining the sample tracks based on the selected tracks, wherein the preset samples contained in the i first candidate tracks are the same samples, the j second candidate tracks refer to the preset samples which are different from each other except the i first candidate tracks, and i and j are positive integers.
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