CN114301723A - Intelligent household control system and method - Google Patents
Intelligent household control system and method Download PDFInfo
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Abstract
The application provides an intelligent home control system and method, voice information input by a user is collected through an intelligent voice module, user information and environment information are collected through a control module, then the voice information, the user information and the environment information of the user are subjected to feature extraction through a data analysis module, then behavior prediction is carried out on user behaviors according to the extracted user feature values to obtain behavior prediction, and then control commands corresponding to the behavior prediction are adopted to automatically control intelligent home equipment. So, need not the user and again manually control intelligent house for intelligent house more intelligence, great convenience of customers' life has promoted user experience.
Description
Technical Field
The application relates to the technical field of intelligent home, in particular to an intelligent home control system and method.
Background
Along with the development of the technology and the improvement of the user demand, the intelligent degree of the smart home is continuously improved, some commonly used smart homes can be accessed to the internet and can be interacted and remotely operated with devices such as a mobile terminal of a user, for example, the user can remotely control the smart homes such as an air conditioner, a refrigerator and a washing machine in the home or inquire the working state of the smart homes through a mobile phone.
However, the intelligent home of the smart home cannot be well embodied in the prior art, most smart homes are simply connected with sensors, controllers and household appliances, the control of the whole smart home system needs manual operation, and the intelligent home system does not achieve the 'intelligence' in the true sense, so that the development of the smart home is limited to a certain extent.
Disclosure of Invention
In order to solve the technical problems that the existing intelligent home is required to be operated manually and intelligentized relatively low or at least partially, the application provides an intelligent home control system and method.
In a first aspect, the present application provides an intelligent home control system, including: the intelligent voice module, the data analysis module, the control module and the intelligent household equipment;
the intelligent voice module is used for receiving voice information input by a user and sending the voice information to the data analysis module;
the control module is used for acquiring user information and environment information of the user and sending the user information and the environment information to the data analysis module;
the data analysis module is used for extracting the characteristics of the received voice information, the received user information and the received environment information to obtain a characteristic value of the user, calculating and analyzing the characteristic value to obtain a behavior prediction, and sending a control command corresponding to the behavior prediction to the control module;
the control module is further configured to forward the control command to the smart home device;
and the intelligent household equipment is used for executing corresponding operation according to the received control command.
As a possible implementation manner, the data analysis module performs feature extraction on the voice information, the user information, and the environment information by using a decision tree algorithm and a regression algorithm to obtain a feature value of the user.
As a possible implementation manner, the data analysis module performs computational analysis on the characteristic values by using a trained prediction model to obtain behavior prediction.
As a possible implementation manner, the data analysis module is further configured to perform preprocessing on the voice information, the user information, and the environment information before performing feature extraction on the received voice information, the user information, and the environment information, so as to remove information irrelevant to the user.
As a possible implementation manner, the intelligent voice module is further configured to rearrange the discordant sentences in the voice information before sending the voice information to the data analysis module.
As one possible implementation, the user information includes user physiological information and user portrait information;
the user physiological information comprises one or more of the following items of information: body temperature, heart rate, sleep time;
the user portrait information includes one or more of the following: habit, age, preferences;
the environment information includes one or more of the following: temperature, humidity, brightness.
As a possible implementation manner, the intelligent voice module is further configured to convert the voice information into a control command, and send the control command to the control module.
In a second aspect, an embodiment of the present application further provides an intelligent home control method, including:
the intelligent voice module receives voice information input by a user and sends the voice information to the data analysis module;
the control module collects the user information and the environment information of the user and sends the user information and the environment information to the data analysis module;
the data analysis module performs feature extraction on the voice information, the user information and the environment information to obtain a feature value of the user;
the data analysis module calculates and analyzes the characteristic value to obtain a behavior prediction, and sends a control command corresponding to the behavior prediction to the control module;
the control module forwards the control command to the intelligent household equipment;
and the intelligent household equipment executes corresponding operation according to the control command.
As a possible implementation manner, the data analysis module performs feature extraction on the voice information, the user information, and the environment information by using a decision tree algorithm and a regression algorithm to obtain a feature value of the user.
As a possible implementation manner, the data analysis module performs calculation analysis based on the characteristic value by using a trained prediction model to obtain behavior prediction.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages:
the application provides an intelligent home control system and method, voice information input by a user is collected through an intelligent voice module, user information and environment information are collected through a control module, then feature extraction is carried out on the voice information, the user information and the environment information of the user through a data analysis module, the behavior of the user is predicted according to the extracted user feature value, behavior prediction is obtained, and then control commands corresponding to the behavior prediction are adopted to automatically control intelligent home equipment. So, need not the user and again manually control intelligent house for intelligent house more intelligence, great convenience of customers' life has promoted user experience.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram illustrating an intelligent home control system according to an exemplary embodiment.
Fig. 2 is a signaling diagram illustrating a smart home control method according to an exemplary embodiment.
Fig. 3 is a schematic diagram illustrating a control method of a smart home control system according to an exemplary embodiment.
FIG. 4 is a schematic diagram illustrating an electronic device in accordance with an example embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
Referring to fig. 1, a schematic view of an intelligent home control system provided in an embodiment of the present application is shown in fig. 1, where the intelligent home control system may include: the intelligent voice module, the data analysis module, the control module and the intelligent household equipment. The intelligent voice module is in communication connection with the control module and the data analysis module respectively, and the control module is further in communication connection with the data analysis module and the intelligent household equipment.
The smart home devices include, but are not limited to, smart curtains, smart door locks, refrigerators, washing machines, electric cookers, air conditioners, dish washers, electric lamps, and other smart devices.
The intelligent voice module is used for receiving voice information input by a user and sending the voice information to the data analysis module.
The control module is used for collecting user information and environment information of the user and sending the user information and the environment information to the data analysis module.
The user information may include user physiological information and user portrait information.
The user physiological information includes one or more of the following: body temperature, heart rate, sleep time.
The user profile information includes one or more of the following: habit, age, preferences.
The environment information includes one or more of the following: temperature, humidity, brightness.
The data analysis module is used for extracting the characteristics of the received voice information, the user information and the environment information to obtain a characteristic value of the user, then calculating and analyzing the characteristic value to obtain a behavior prediction, and sending a control command corresponding to the behavior prediction to the control module.
And after receiving the control command sent by the intelligent analysis module, the control module is also used for forwarding the control command to the intelligent household equipment.
As an embodiment, when the control module forwards the control command to the smart home device, the control module may convert the control command into a control command recognizable by the smart home device, so as to ensure a control success rate.
As an embodiment, the control module may store communication protocols supported by each smart home, so that when the control command is forwarded to the smart home device, the communication protocols supported by the smart home device may be determined, and then the control command is converted into a format supported by the smart home device according to the communication protocols.
And the intelligent household equipment executes corresponding operation according to the received control command.
As an embodiment, functional modules such as a temperature/humidity sensor, a heart rate monitor, a sleep time monitor and the like can be built in the intelligent household equipment, so that when a user uses the intelligent household equipment, the control module can further collect user information and corresponding environmental information through the intelligent household equipment and then transmit the user information and the corresponding environmental information to the data analysis module to further analyze the user information, and therefore the intelligent life of the user can be better processed and optimized.
The application provides an intelligent home control system and method, voice information input by a user is collected through an intelligent voice module, user information and environment information are collected through a control module, then feature extraction is carried out on the voice information, the user information and the environment information of the user through a data analysis module, the behavior of the user is predicted according to the extracted user feature value, behavior prediction is obtained, and then control commands corresponding to the behavior prediction are adopted to automatically control intelligent home equipment. So, need not the user and again manually control intelligent house for intelligent house more intelligence, great convenience of customers' life has promoted user experience.
The intelligent home control system provided by the embodiment of the application can acquire user information of a user according to the intelligent home equipment and the control module, when the user returns home, the intelligent home control system can automatically match corresponding home behaviors according to the information provided by the door lock and the external environment, for example, the behaviors of turning on a lamp, intelligently cooking and turning on/off a curtain are automatically cleaned, beautiful music can be automatically played for the user according to the preference of the user, and after the user eats the food, the intelligent system can also be cleaned according to time, so that the real world interconnection is realized; wherein the user information comprises at least one of: the intelligent home equipment is subjected to linkage control according to the acquired user information, such as physiological information, hobbies and habits of the user, so that the hobbies and habits of the user are met, and the user can use the household appliance more conveniently and intelligently.
As a possible implementation manner, the control module may be a terminal with a built-in control program, where the terminal may be a mobile phone, a computer, or the like.
As a possible implementation manner, the data analysis module may perform feature extraction on the voice information, the user information, and the environment information of the user by using a decision algorithm and a regression algorithm, so as to obtain a feature value of the user.
As an example, the decision algorithm may be any one or more of decision tree ID3, C4.5, and C5.0 algorithms.
When the voice information, the user information and the environment information of the user are processed by adopting the decision tree algorithm, readable rules and decision trees can be generated by utilizing a method of approximating a discrete function value, and then the voice information, the user information and the environment information of the user are analyzed by using a decision.
The voice information, the user information and the environment information of the user can be subjected to label classification by utilizing the decision tree, and then the user decision tree is generated so as to better predict the user behavior.
As one example, the regression algorithm may employ a bayesian probability algorithm. The bayesian probability algorithm is an algorithm for classification using probability statistics, and can be represented by P (B | a) ═ P (a ∞ B)/P (a), which is based on the naive assumption that "features are independent" and by using this theorem, P (y | x1, x2.. xm) ═ P (y) P (x1, x2.. xm | y)/P (x1, x2.. xm), so that the speech information, user information, and environment information of the user are processed by the bayesian probability algorithm, and the category features of the information can be obtained, and further, the user preference, habit, and the like can be classified.
Similarly, the Bayesian probability algorithm can be used for label classification of the voice information, the user information and the environment information of the user, and the user behavior can be well predicted.
Therefore, in the embodiment of the present application, the obtained feature value of the user may be a classification feature value.
As a possible implementation mode, the data analysis module adopts a trained prediction model to calculate and analyze the characteristic value to obtain behavior prediction.
As an embodiment, the prediction model may be a neural network generated based on a recurrent neural network algorithm according to a feature value obtained by integrating a decision tree algorithm and a regression algorithm, and may perform prediction analysis on the behavior of the user based on the user feature value by performing autonomous learning.
The recurrent neural network algorithm is an artificial neural network for recursion according to input information, and is a deep learning algorithm.
In another embodiment of the present application, before performing feature extraction on the received voice information, user information, and environment information, the data analysis module may also perform preprocessing on the voice information, the user information, and the environment information, and reject information irrelevant to the user.
As an embodiment, the data analysis module may perform preprocessing such as data cleaning, data integration, data reduction, and data conversion on the voice information, the user information, and the environment information. The data cleaning is mainly used for removing useless data, filtering data and correcting, for example, removing data irrelevant to user information, such as irrelevant voice information input by a user, and the like, and is beneficial to improving the consistency, accuracy and authenticity of big data.
In another embodiment of the present application, before the intelligent voice module sends the voice information to the data analysis module, the intelligent voice module may also rearrange the discontent sentences in the voice information to improve the accuracy of the language information.
In another embodiment of the application, the intelligent voice module can also convert the received voice information into a control command and send the control command to the control module, so that the control module can forward the control command sent by the intelligent voice module to the intelligent home equipment, thereby realizing voice control of the intelligent home equipment.
As an embodiment, a science news communication voice conversion system may be built in the intelligent voice module, and the input of the user may be processed by voice information, some sentences may be typeset, converted into json data that can be understood by the intelligent home device, and sent to the control module, so as to better help the user use the device.
Referring to fig. 2, a signaling diagram of an intelligent home control method provided by the present application based on the intelligent home control system shown in fig. 1 is shown in fig. 2, where the method may include the following steps:
and S21, the intelligent voice module receives voice information input by a user and sends the voice information to the data analysis module.
And S22, the control module collects the user information and the environmental information of the user and sends the user information and the environmental information to the data analysis module.
And S23, a data analysis module performs feature extraction on the voice information, the user information and the environment information to obtain a feature value of the user.
As one embodiment, the user information includes user physiological information and user profile information;
the user physiological information comprises one or more of the following items of information: body temperature, heart rate, sleep time;
the user portrait information includes one or more of the following: habit, age, preferences;
the environment information includes one or more of the following: temperature, humidity, brightness.
And S24, calculating and analyzing the characteristic value by the data analysis module to obtain a behavior prediction, and sending a control command corresponding to the behavior prediction to the control module.
And S25, the control module forwards the control command to the intelligent household equipment.
And S26, the intelligent household equipment executes corresponding operation according to the control command.
It should be noted that, there is no specific sequence between S21 and S22, S21 may precede S22, or both steps may be performed simultaneously.
As a possible implementation manner, the data analysis module may perform feature extraction on the voice information, the user information, and the environment information by using a decision tree algorithm and a regression algorithm to obtain a feature value of the user.
As a possible implementation manner, the data analysis module may perform computational analysis based on the feature values by using a trained prediction model to obtain a behavior prediction.
In another embodiment of the present application, on the basis of the smart home control method shown in fig. 2, the smart home control method may further include: and the data analysis module is used for preprocessing the voice information, the user information and the environment information before extracting the characteristics of the received voice information, the user information and the environment information and eliminating information irrelevant to the user.
In another embodiment of the present application, on the basis of the smart home control method shown in fig. 2, the smart home control method may further include: and the intelligent voice module rearranges the unordered sentences in the voice information before sending the voice information to the data analysis module.
In another embodiment of the present application, on the basis of the smart home control method shown in fig. 2, the smart home control method may further include: the intelligent voice module can also convert the voice information into a control command and send the control command to the control module.
Referring to fig. 3, a schematic diagram of a control method of an intelligent home control system provided in an embodiment of the present application is shown.
It should be noted that fig. 3 only illustrates a refrigerator, an air conditioner, and a washing machine as the smart home device, and does not limit the smart home device in the present application.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to another embodiment of the present application.
As shown in fig. 4, the electronic device provided in this embodiment includes: at least one processor 401, memory 402, at least one network interface 403, and other user interfaces 404. The various components in the electronic device 400 are coupled together by a bus system 405. It is understood that the bus system 405 is used to enable connection communication between these components. The bus system 405 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled in the figure as the bus system 405.
The user interface 404 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, trackball, touch pad, or touch screen, among others.
It will be appreciated that memory 402 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), synchlronous SDRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 402 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 402 stores the following elements, executable units or data structures, or a subset thereof, or an expanded set thereof: an operating system 4021 and application programs 4022.
The operating system 4021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is configured to implement various basic services and process hardware-based tasks. The application programs 4022 include various application programs, such as a Media Player (Media Player), a Browser (Browser), and the like, for implementing various application services. A program for implementing the method according to the embodiment of the present invention may be included in the application 4022.
In this embodiment of the present invention, by calling a program or an instruction stored in the memory 402, specifically, a program or an instruction stored in the application 4022, the processor 401 is configured to execute the method steps provided by the method embodiments, for example, including:
the intelligent voice module receives voice information input by a user and sends the voice information to the data analysis module;
the control module collects the user information and the environment information of the user and sends the user information and the environment information to the data analysis module;
the data analysis module performs feature extraction on the voice information, the user information and the environment information to obtain a feature value of the user;
the data analysis module calculates and analyzes the characteristic value to obtain a behavior prediction, and sends a control command corresponding to the behavior prediction to the control module;
the control module forwards the control command to the intelligent household equipment;
and the intelligent household equipment executes corresponding operation according to the control command.
The method disclosed in the above embodiments of the present invention may be applied to the processor 401, or implemented by the processor 401. The processor 401 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 401. The Processor 401 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software elements in the decoding processor. The software elements may be located in ram, flash, rom, prom, or eprom, registers, among other storage media that are well known in the art. The storage medium is located in the memory 402, and the processor 401 reads the information in the memory 402 and completes the steps of the method in combination with the hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented in one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions of the present Application, or a combination thereof.
For a software implementation, the techniques herein may be implemented by means of units performing the functions herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
The embodiment of the invention also provides a storage medium (computer readable storage medium). The storage medium herein stores one or more programs. Among others, the storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, a hard disk, or a solid state disk; the memory may also comprise a combination of memories of the kind described above.
When one or more programs in the storage medium can be executed by one or more processors, the smart home control method executed on the electronic device side is realized.
The processor is used for executing the intelligent home control method program stored in the memory so as to realize the following steps of the intelligent home control method executed on the electronic equipment side:
the intelligent voice module receives voice information input by a user and sends the voice information to the data analysis module;
the control module collects the user information and the environment information of the user and sends the user information and the environment information to the data analysis module;
the data analysis module performs feature extraction on the voice information, the user information and the environment information to obtain a feature value of the user;
the data analysis module calculates and analyzes the characteristic value to obtain a behavior prediction, and sends a control command corresponding to the behavior prediction to the control module;
the control module forwards the control command to the intelligent household equipment;
and the intelligent household equipment executes corresponding operation according to the control command.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. The utility model provides an intelligence house control system which characterized in that includes: the intelligent voice module, the data analysis module, the control module and the intelligent household equipment;
the intelligent voice module is used for receiving voice information input by a user and sending the voice information to the data analysis module;
the control module is used for acquiring user information and environment information of the user and sending the user information and the environment information to the data analysis module;
the data analysis module is used for extracting the characteristics of the received voice information, the received user information and the received environment information to obtain a characteristic value of the user, calculating and analyzing the characteristic value to obtain a behavior prediction, and sending a control command corresponding to the behavior prediction to the control module;
the control module is further configured to forward the control command to the smart home device;
and the intelligent household equipment is used for executing corresponding operation according to the received control command.
2. The system of claim 1, wherein the data analysis module performs feature extraction on the speech information, the user information, and the environment information using a decision tree algorithm and a regression algorithm to obtain a feature value of the user.
3. The system of claim 1, wherein the data analysis module performs computational analysis on the feature values using a trained predictive model to obtain the behavior prediction.
4. The system of claim 1, wherein the data analysis module is further configured to pre-process the voice information, the user information, and the environment information to remove information unrelated to the user before performing feature extraction on the received voice information, the user information, and the environment information.
5. The system of claim 1, wherein the intelligent speech module is further configured to rearrange the discontent sentences in the speech message before sending the speech message to the data analysis module.
6. The system of claim 1, wherein the user information includes user physiological information and user profile information;
the user physiological information comprises one or more of the following items of information: body temperature, heart rate, sleep time;
the user portrait information includes one or more of the following: habit, age, preferences;
the environment information includes one or more of the following: temperature, humidity, brightness.
7. The system of claim 1, wherein the smart voice module is further configured to convert the voice information into a control command and send the control command to the control module.
8. The intelligent household control method is characterized by comprising the following steps:
the intelligent voice module receives voice information input by a user and sends the voice information to the data analysis module;
the control module collects the user information and the environment information of the user and sends the user information and the environment information to the data analysis module;
the data analysis module performs feature extraction on the voice information, the user information and the environment information to obtain a feature value of the user;
the data analysis module calculates and analyzes the characteristic value to obtain a behavior prediction, and sends a control command corresponding to the behavior prediction to the control module;
the control module forwards the control command to the intelligent household equipment;
and the intelligent household equipment executes corresponding operation according to the control command.
9. The method of claim 8, wherein the data analysis module performs feature extraction on the speech information, the user information and the environment information by using a decision tree algorithm and a regression algorithm to obtain a feature value of the user.
10. The method of claim 8, wherein the data analysis module performs computational analysis based on the feature values using a trained predictive model to obtain the behavior prediction.
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| CN117389348A (en) * | 2023-10-23 | 2024-01-12 | 瓦城柚木(广东)家居科技有限公司 | Temperature control method, system and storage medium of intelligent household equipment |
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