Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.
The term "plurality" means two or more unless otherwise specified.
In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.
In the embodiment of the disclosure, the cloud server may be configured with a big data learning model, so that the user air conditioner usage behavior learning result information corresponding to the user identity information can be obtained and stored through big data learning, and when the air conditioner is awakened by the user voice, the user identity information can be matched with the user voiceprint identification information of the user, so that the user air conditioner usage behavior learning result information after the big data learning matched with the user identity information can be obtained, and the corresponding air conditioner control instruction information can be generated to control the operation of the air conditioner, thereby realizing voice recognition of the user identity information, and automatically controlling the air conditioner according to the user air conditioner usage behavior, improving the intelligence of air conditioner control, and also improving user experience.
In the embodiment of the disclosure, the air conditioner is an air conditioner with a voice function, namely, the air conditioner carries a voice module, so that a voice platform module can be arranged in the cloud server, voice signaling interaction can be performed with the air conditioner, voice management and the like, and a big data learning model can be arranged in the cloud server, so that the user air conditioner can learn the use behavior to obtain corresponding learning result information, and therefore, the cloud server can further comprise the data platform module. Simultaneously, along with the development of air conditioner intelligent technology, still can air conditioner control platform module in the high in the clouds server, can carry out remote control and management to the air conditioner, consequently, in this embodiment of this disclosure, the device that is used for pronunciation air conditioner control in the high in the clouds server can include a plurality of platform modules, and these platform modules can be virtual function module, also can specifically be server equipment to, can communicate between the platform module, realize pronunciation air conditioner control.
Fig. 1 is a schematic flowchart of a control method for a voice air conditioner according to an embodiment of the present disclosure. As shown in fig. 1, the process of voice air-conditioning control includes:
step 101: and receiving a current user voice awakening instruction sent by the air conditioner.
In the embodiment of the disclosure, the air conditioner has a voice function, and therefore, after the user sends the voice awakening instruction, the voice module in the air conditioner can send the received current user voice awakening instruction to the cloud server, so that the cloud server can receive the current user voice awakening instruction sent by the air conditioner.
Wherein, included the pronunciation platform module in the cloud server, for example: and (2) an Artificial Intelligence (AI) platform device, so that the voice platform module receives a current user voice awakening instruction sent by the air conditioner.
Step 102: and analyzing the voice awakening instruction of the current user to obtain voiceprint identification information of the current user, and determining identity information of the current user matched with the voiceprint identification information of the current user.
The cloud server can pre-store the corresponding relation between the user voiceprint identification information and the user identity information. In some embodiments, the voice platform module in the cloud server may store a correspondence between the user voiceprint identification information and the user identity information.
The user identity information and the user voice information can be obtained in advance, and the user voice information is analyzed to obtain the user voiceprint identification information, so that the corresponding relation between the user voiceprint identification information and the user identity information can be configured and stored. In some embodiments, user identity information and user voice information sent by a terminal configured with a voiceprint registration application APP can be received and analyzed to obtain user voiceprint identification information; and the corresponding relation between the user voiceprint identification information and the user identity information is configured and stored, so that the current user identity information matched with the current user voiceprint identification information is determined according to the corresponding relation.
For example: the user inputs user identity information through a terminal configured with a voiceprint registration application APP, and the method comprises the following steps: one or more information of name, age, sex, etc., and also can input user voice information, so that the user voice information can be analyzed to obtain the voiceprint identification voiceFlag information of the user, and thus, after registration and authentication, the corresponding relation between the voiceprint identification information of the user and the identity information of the user can be configured and stored.
The corresponding relation between the user voiceprint identification information and the user identity information is stored in the cloud server, so that the current user identity information matched with the current user voiceprint identification information can be determined according to the corresponding relation. For example: the voice AI platform can determine the current user identity information matched with the voiceprint identification information of the current user according to the stored corresponding relation.
Step 103: and under the condition that the current user air conditioner use behavior learning result information matched with the current user identity information is obtained, generating current air conditioner control instruction information according to the current user air conditioner use behavior learning result information.
The cloud server can be configured with a big data learning model to learn the use behavior of the air conditioner of the user to obtain corresponding learning result information, so that in some embodiments, a big data platform module in the cloud server can obtain the operation mode sample information of the air conditioner in a set area where the user is located, and obtain the air conditioner equipment sample information, the temperature sample information and the wind speed sample information which are matched with a set time period of the user; according to the operation mode sample information, the air conditioner equipment sample information, the temperature sample information and the wind speed sample information, big data learning is carried out, and learning result information of the using behaviors of the air conditioner of a user is obtained; and storing the corresponding relation between the user identity information and the user air conditioner use behavior learning result information.
In this embodiment, the learning result information of the big data learning model configured in the cloud server is the learning result information of the user air conditioner usage behavior, and may include: one or more of air conditioner operation mode information, air conditioner target temperature information, air conditioner operation wind speed information, etc., and thus, the learning samples of the big data learning model that may be obtained may include: one or more of operation mode sample information, temperature sample information, and wind speed sample information.
In some embodiments, the step of obtaining the operation mode of each air conditioner in the set area where the user is located may be performed by setting a circular area corresponding to the radius as the set area where the user is located at the center of the position where any user is located, and includes: and performing big data analysis on the operation mode sample information to obtain air conditioner operation mode information in the user air conditioner use behavior learning result information matched with the user identity information. Certainly, in some embodiments, the target temperature information and the operating wind speed information of each air conditioner in the set area where the user is located may also be obtained as the temperature sample information and the wind speed sample information, so that the target temperature information and the operating wind speed information in the user air conditioner usage behavior learning result information matched with the user identity information may be obtained by performing big data analysis.
In some embodiments, the air conditioner sample information, the temperature sample information, and the wind speed sample information that match the set time period of the user may be obtained, including: and obtaining air conditioning equipment sample information, temperature sample information and wind speed sample information corresponding to each interval time according to the interval data of the user accumulated time. For example: the time is divided into 24 time intervals, and the specific time intervals are as follows: (0, 1], (1, 2], (2, 3] … … (23, 24), the corresponding time markers can be 1, 2, 3 … … 24 respectively, thus, the current time identifier corresponding to the current startup time of the user is determined, and then according to the current time identifier and the air conditioning equipment information, searching in the corresponding relation between the stored time identification and the air conditioner temperature and wind speed index information, if the current air conditioner temperature and wind speed index information corresponding to the current time identification is searched, and no manual intervention action exists, corresponding temperature sample information and wind speed sample information can be obtained, if a manual intervention action is taken, the target temperature and the running wind speed of the air conditioner after the manual intervention action are updated and stored as the corresponding current air conditioner temperature and wind speed index information, so that the corresponding temperature sample information and wind speed sample information are obtained.
If the current air conditioner temperature and wind speed index information corresponding to the current time identifier is not found, the air conditioner temperature and wind speed index information corresponding to the time identifier closest to the current time identifier can be found, and if the air conditioner temperature and wind speed index information can be found without manual intervention, the found air conditioner temperature and wind speed index information can be determined to be the current air conditioner temperature and wind speed index information, so that corresponding temperature sample information and wind speed sample information are obtained. Of course, if there is a manual intervention action, the current air-conditioning temperature and wind speed index information may be updated and stored according to the target temperature and the operating wind speed of the air conditioner after the manual intervention action, so as to obtain the corresponding temperature sample information and wind speed sample information.
If the air conditioner temperature and wind speed index information corresponding to the time identifier closest to the current time identifier is not searched, the received target temperature information and the air conditioner running wind speed information which are reported by the air conditioner latest are determined as the current air conditioner temperature and wind speed index information, and therefore the corresponding temperature sample information and the corresponding wind speed sample information are obtained.
For example: the current starting time of the user is 9:40, the corresponding time identifier can be 10, if the current time identifier 10 is found in the corresponding relation between the stored time identifier and the air conditioner temperature and wind speed index information, at the moment, if a manual intervention action (the user changes the target temperature or the running wind speed), the current time identifier 10 can be updated and stored as the corresponding current air conditioner temperature and wind speed index information according to the target temperature and the running wind speed of the air conditioner after the manual intervention action, and therefore the corresponding temperature sample information and the corresponding wind speed sample information are obtained. If the current time identifier 10 is not found in the corresponding relationship between the stored time identifiers and the air conditioner temperature and wind speed index information, but the air conditioner temperature and wind speed index information corresponding to the closest time identifier 11 is found, and no manual intervention action exists, the found air conditioner temperature and wind speed index information can be determined as the current air conditioner temperature and wind speed index information. If the time marks 9, 10 and 11 are not found, the received target temperature information and the air conditioner running wind speed information which are reported by the air conditioner latest can be determined as the current air conditioner temperature and wind speed index information and stored.
It is thus clear that, in this embodiment of the disclosure, the cloud server, or, the data platform module accessible big data model in the cloud server obtains and keeps the corresponding relation between user identity information and the user air conditioner use behavior learning result information, and wherein, the user air conditioner uses the behavior learning result information to include: one, two or more of air conditioner operation mode information, target temperature information, and operation wind speed information, etc.
In this way, if the current user air conditioner usage behavior learning result information matched with the current user identity information is obtained according to the correspondence between the stored user identity information and the user air conditioner usage behavior learning result information, the current air conditioner control instruction information may be generated according to one, two or more of the air conditioner operation mode information, the target temperature information, the operation wind speed information, and the like in the current user air conditioner usage behavior learning result information.
In some embodiments, the cloud server may include an air conditioner control platform module, for example: the air conditioner control platform module can acquire state data information reported by an air conditioner, can issue control instruction information of the air conditioner and the like, and can control and manage the air conditioner, so that when the data platform module in the cloud server or the cloud server finds current user air conditioner use behavior learning result information matched with current user identity information, the current user air conditioner use behavior learning result information can be sent to the air conditioner control platform module in the cloud server, and therefore the air conditioner control platform module can perform compatible processing on the current user air conditioner use behavior learning result information according to an air conditioner protocol to generate the current air conditioner control instruction information.
Step 104: and sending the current air conditioner control instruction information to the air conditioner to control the operation of the air conditioner.
The cloud server can send the current air conditioner control instruction information to the air conditioner to control the operation of the air conditioner. In some embodiments, the air conditioning platform module may directly communicate with the air conditioner, so that the air conditioning platform module may send the current air conditioning control instruction information to the air conditioner to control the operation of the air conditioner.
In some embodiments, the air conditioner may belong to a smart device in a smart home system, and the smart home system may be controlled by an Internet of Things (IoT) platform module, and therefore, the cloud server may further include: the IoT platform module can send the current air-conditioning control instruction information to the IoT platform module after the air-conditioning control platform module generates the current air-conditioning control instruction information, so that the IoT platform module sends the current air-conditioning control instruction information to the air conditioner according to the agreed communication mode to control the operation of the air conditioner. Or after the air-conditioning control platform module generates the current air-conditioning control instruction information, the current air-conditioning control instruction information can be sent to the voice platform module according to the communication mode of the protocol, and the voice platform module generates the current corresponding voice control instruction according to the current air-conditioning control instruction information and sends the current voice control instruction to the IoT platform module, so that the IoT platform module sends the current voice control instruction to the air conditioner according to the communication mode of the protocol to control the operation of the air conditioner.
Therefore, in this embodiment, the cloud server may be configured with a big data learning model, so that the user air conditioner usage behavior learning result information after big data learning corresponding to the user identity information can be obtained through big data learning and stored, and therefore, when the air conditioner is awakened by the user voice, the user identity information can be matched with the user voiceprint identification information of the user, so that the user air conditioner usage behavior learning result information matched with the user identity information can be obtained, and corresponding air conditioner control instruction information can be generated to control the operation of the air conditioner, so that the user identity information is recognized by voice, the air conditioner is automatically controlled according to the user air conditioner usage behavior, the intelligence of air conditioner control is improved, and the user experience is also improved.
Of course, in the corresponding relationship between the user identity information stored in the cloud server or the data platform module in the cloud server and the user air conditioner use behavior learning result information, if the current user identity information is not found, the current user identity information may be put into a configured big data model for big data learning, that is, the operation mode sample information, the air conditioner sample information, the temperature sample information, and the wind speed sample information corresponding to the current user identity information are obtained, and the big data learning is performed to obtain a corresponding learning result, so that when the current user identity information is found again, the corresponding current user air conditioner use behavior learning result information may be obtained.
The cloud server controls the air conditioner to run according to the current air conditioner control instruction information, and then the air conditioner can report the running state information, so that the cloud server can receive the running state information reported by the air conditioner; therefore, current operation playing information is generated according to the current user identity information and the operation state information; and sending the current running playing information to the air conditioner for broadcasting.
In some embodiments, the voice platform module in the cloud server may receive the running state information reported by the air conditioner; therefore, current operation playing information is generated according to the current user identity information and the operation state information; and send the current operation broadcast information to the air conditioner and report, for example: and (3) playing: "xx children, air conditioner on, and you set your usual xx wind speed, xx mode, xx temperature".
It can be seen that an apparatus for voice air-conditioning control can be constructed according to the above-described process for voice air-conditioning control. The device for controlling the voice air conditioner can be applied to a cloud server.
Fig. 2 is a schematic structural diagram of a voice air conditioner control device according to an embodiment of the present disclosure. As shown in fig. 2, the control apparatus for voice air conditioner includes:voice platform module 100,data platform module 200 and air conditioningcontrol platform module 300.
Thevoice platform module 100 is configured to receive a current user voice wake-up instruction sent by an air conditioner; and analyzing the voice awakening instruction of the current user to obtain voiceprint identification information of the current user, and determining identity information of the current user matched with the voiceprint identification information of the current user.
And thedata platform module 200 is configured to send the current user air conditioner usage behavior learning result information under the condition that the current user air conditioner usage behavior learning result information matched with the current user identity information is obtained.
And the air conditionercontrol platform module 300 is configured to generate current air conditioner control instruction information according to the received current user air conditioner usage behavior learning result information, and send the current air conditioner control instruction information to the air conditioner to control the operation of the air conditioner.
In some embodiments, thevoice platform module 100 is further configured to receive user identity information and user voice information sent by a terminal configured with a voiceprint registration application APP, and analyze the user voice information to obtain user voiceprint identification information; and configuring and storing the corresponding relation between the user voiceprint identification information and the user identity information.
In some embodiments, thedata platform module 200 is further configured to obtain operation mode sample information of an air conditioner in a set area where a user is located, and obtain air conditioner device sample information, temperature sample information, and wind speed sample information that are matched with a set time period of the user; according to the operation mode sample information, the air conditioner equipment sample information, the temperature sample information and the wind speed sample information, big data learning is carried out, and learning result information of the using behaviors of the air conditioner of a user is obtained; and storing the corresponding relation between the user identity information and the user air conditioner use behavior learning result information.
In some embodiments, thevoice platform module 300 is further configured to receive the running state information reported by the air conditioner; generating current operation playing information according to the current user identity information and the operation state information; and sending the current running playing information to the air conditioner for broadcasting.
Of course, in the embodiment of the present disclosure, each platform module used in the voice air conditioner may be a virtual functional module, and may also be specifically a server device, for example: thespeech platform module 100 may include: a voice AI platform device;data platform module 200 may include: a data platform device; the climatecontrol platform module 300 may include: air conditioning servers, and the like.
The following operation flows are integrated into a specific embodiment to illustrate a voice air-conditioning control process performed by the voice air-conditioning control device according to the embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a voice air-conditioning control device according to an embodiment of the present disclosure. As shown in fig. 3, the method for controlling a voice air conditioner applied to a cloud server may include: voiceAI platform device 310,data platform device 320,air conditioning server 330, andIOT platform device 340.
The voiceAI platform device 310, thedata platform device 320, and theair conditioner server 330 may communicate with each other, and the voiceAI platform device 310 and theair conditioner server 330 may also communicate with theIOT platform device 340, respectively.
Moreover, the voiceAI platform device 310 stores the corresponding relationship between the user voiceprint identification information and the user identity information. Thedata platform device 320 is configured with a big data model, and stores the corresponding relationship between the user identity information and the user air conditioner use behavior learning result information.
Fig. 4 is a signaling flow diagram of a user voice air conditioner control method according to an embodiment of the present disclosure. The process for the voice air conditioner controlling device to control the voice air conditioner may be as shown in fig. 4, and includes:
step 401: and the voice AI platform equipment receives a current user voice awakening instruction sent by the air conditioner.
Step 402: and the voice AI platform equipment analyzes the voice awakening instruction of the current user to obtain the voiceprint identification information of the current user.
Step 403: and the voice AI platform equipment determines the current user identity information matched with the current user voiceprint identification information according to the corresponding relation between the stored user voiceprint identification information and the user identity information.
Step 404: and the data platform equipment acquires the identity information of the current user.
Step 405: is the data platform device determine whether the current user identity information is found in the correspondence between the stored user identity information and the user air conditioner usage behavior learning result information? If yes, go to step 406, otherwise, go to step 407.
Step 406: and the data platform equipment acquires the current user air conditioner use behavior learning result information matched with the current user identity information and sends the current user air conditioner use behavior learning result information to the air conditioner server.
Step 407: the data platform equipment acquires sample information corresponding to the current user identity information, and performs big data learning to obtain learning result information of the user air conditioner use behavior; and storing the corresponding relation between the user identity information and the user air conditioner use behavior learning result information.
Step 408: and the air conditioner server performs protocol compatibility processing on the current user air conditioner use behavior learning result information to generate current air conditioner control instruction information.
Step 409: and the air conditioner server returns the current air conditioner control instruction information to the voice AI platform equipment.
Step 410: and the voice AI platform equipment sends the current air conditioner control instruction information to the air conditioner through the IOT platform equipment.
Step 411: the air conditioner operates according to the current air conditioner control instruction information, and reports the operation state information to the voice AI platform equipment.
Step 412: and the voice AI platform equipment generates current operation playing information according to the current user identity information and the operation state information and sends the current operation playing information to the air conditioner.
Step 413: and the air conditioner broadcasts according to the current operation playing information.
It can be seen that, in this embodiment, the apparatus for controlling a voice air conditioner may be configured with a big data learning model, so that the user air conditioner usage behavior learning result information corresponding to the user identity information may be obtained through big data learning and stored, so that when the air conditioner is woken up by the user voice, the apparatus for controlling a voice air conditioner may match the user identity information through the voiceprint identification information of the user, so that the user air conditioner usage behavior learning result information matching the user identity information may be obtained, and the corresponding air conditioner control instruction information may be generated to control the operation of the air conditioner, thereby implementing voice recognition of the user identity information, and automatically controlling the air conditioner according to the user air conditioner usage behavior, improving intelligence of air conditioner control, and also improving user experience.
The embodiment of the present disclosure provides a device for controlling a voice air conditioner, which is structurally shown in fig. 5 and includes:
a processor (processor)1000 and a memory (memory)1001, and may further include a Communication Interface (Communication Interface)1002 and abus 1003. Theprocessor 1000, thecommunication interface 1002, and thememory 1001 may communicate with each other through thebus 1003.Communication interface 1002 may be used for the transfer of information. Theprocessor 1000 may call logic instructions in thememory 1001 to perform the method for voice air-conditioning control of the above-described embodiment.
In addition, the logic instructions in thememory 1001 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products.
Thememory 1001 is a computer readable storage medium and can be used for storing software programs, computer executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. Theprocessor 1000 executes functional applications and data processing by executing program instructions/modules stored in thememory 1001, that is, implements the method for voice air-conditioning control in the above-described method embodiment.
Thememory 1001 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. Further, thememory 1001 may include a high-speed random access memory and may also include a nonvolatile memory.
The embodiment of the present disclosure provides a control device for a voice air conditioner, including: a processor and a memory storing program instructions, the processor configured to, upon execution of the program instructions, perform a method for voice air conditioning control.
The embodiment of the disclosure provides a cloud server, including the above-mentioned voice air conditioner controlling means that is used for.
The disclosed embodiments provide a storage medium storing program instructions that, when executed, perform the method for voice air conditioning control as described above.
The disclosed embodiments provide a computer program product comprising a computer program stored on a storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the above-described method for voice air-conditioning control.
The storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes, and may also be a transient storage medium.
The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the disclosed embodiments includes the full ambit of the claims, as well as all available equivalents of the claims. As used in this application, although the terms "first," "second," etc. may be used in this application to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, unless the meaning of the description changes, so long as all occurrences of the "first element" are renamed consistently and all occurrences of the "second element" are renamed consistently. The first and second elements are both elements, but may not be the same element. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.