CN104092775A - Intelligent household electrical appliance self-learning method and system - Google Patents
Intelligent household electrical appliance self-learning method and system Download PDFInfo
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Abstract
The invention provides an intelligent household electrical appliance self-learning method. The method comprises the steps of sending identity recognition information and an API of a household electrical appliance to a network server, inquiring whether the matched identity recognition information and using historical information exist or not, building an entry of the identity recognition information when it is determined that no matched identity recognition information exists, and conducting statistical learning on using habits of a user according to all API states of using the household electrical appliance. The invention further provides an intelligent household electrical appliance self-learning system. By the utilization of the intelligent household electrical appliance self-learning method and system, due to the analysis and recording of configuration information of the household electrical appliance, the setting time of the user is shortened, workloads of the user are reduced, and the household electrical appliance can automatically set and initially work according to the habits of the user.
Description
Technical field
The present invention relates to household electrical appliances control technology field, relate in particular to a kind of intelligent appliance self-learning method and system.
Background technology
Each user has the use habit of oneself when using specific household electrical appliances, such as, certain user uses air-conditioning custom to be arranged on 25 degree, and opens dehumidification function; Use television habits to see one, central authorities, brightness is set to 80, volume is set to 50; Use roller washing machine, custom is transferred to 25 degree washings, and washing time is 50 minutes, and washing mode is soft pattern.If user wants to allow a home appliance reach the use habit of oneself, current method normally, user need to use plenty of time household electrical appliances to be set to the mode of operation that oneself needs or the setting of custom, or even while changing to the home appliance of a same model, still need to repeat to arrange work.And, while reopening household electrical appliances, for household electrical appliances with automatic Memory function not, need to reset at every turn.
Summary of the invention
In view of the above problems, the invention provides a kind of a kind of intelligent appliance self-learning method and system that overcomes the problems referred to above or address the above problem at least partly.
The invention provides a kind of intelligent appliance self-learning method, the method comprises:
The identity identification information of transmission home appliance and API information are to the webserver.
Thereby the identity identification information whether this webserver inquiry has coupling determines whether the use historical information of this home appliance, wherein, the identity identification information of home appliance and corresponding user use historical information by pre-stored.And
When determining the identity identification information that there is no coupling, according to all API states of this home appliance of use, user's use habit is carried out to statistical learning.
The present invention also provides a kind of intelligent appliance self learning system, comprises user terminal, the webserver and a plurality of home appliance, and each home appliance all communicates to connect with this webserver, and this webserver comprises:
Memory cell, the identity identification information of pre-stored a plurality of home appliances and corresponding user use historical information.
Operation historical record unit, thus for the identity identification information whether identity identification information that sends according to this home appliance and API have coupling in this memory cell inquiry, determine whether to have the use historical information of this home appliance.
Use habit unit, when the use historical information of this home appliance is not determined in this operation historical record unit, for according to using all API states of this home appliance to carry out statistical learning to user's use habit.
A kind of intelligent appliance self learning system provided by the invention and method, by to the analysis of the configuration information of home appliance and record, user is signed in to after different home appliances by user terminal anywhere by unique account, user's use habit of remembering and learn to obtain by server, automatically corresponding device setting is completed to configuration and the initialization for user habit, user's setup times and work have been greatly reduced, and access to your account can be across distinct device type, the household electrical appliances of same type different model are used, thereby complete according to user habit Lookup protocol and initialization.
Accompanying drawing explanation
Fig. 1 is the hardware structure schematic diagram of the intelligent appliance self learning system in embodiment of the present invention;
Fig. 2 is the high-level schematic functional block diagram of the intelligent appliance self learning system in embodiment of the present invention;
Fig. 3 is the schematic flow sheet of the intelligent appliance self-learning method in embodiment of the present invention;
Fig. 4 carries out the sub-process schematic diagram of statistical learning to user's use habit in embodiment of the present invention.
Label declaration:
Intelligent appliance self learning system 10
User terminal 11
The webserver 12
Operation historical record unit 120
Language scripts storehouse 121
Memory cell 122
Log in control unit 123
Use habit unit 124
Configuration item is set up module 125
Configuration writes control module 126
Use statistics custom analytic unit 127
Home appliance 13
Api interface converting unit 14
Large data analysis system 20
Embodiment
By describing technology contents of the present invention, structural feature in detail, being realized object and effect, below in conjunction with execution mode and coordinate accompanying drawing to be explained in detail.
API: application programming interfaces (API:Application Program Interface) are the set of a group of definition, program and agreement, realize the intercommunication mutually between computer software by api interface.A major function of API is to provide general utility functions collection.Programmer passes through to use api function developing application, thereby can avoid writing useless program, to alleviate programmed tasks.API is also a kind of middleware simultaneously, for various different platforms provide data sharing.
Please refer to Fig. 1, is the hardware structure schematic diagram of the intelligent appliance self learning system in embodiment of the present invention, and this system 10 comprises user terminal 11, the webserver 12 and a plurality of home appliance 13.Wherein, each home appliance 13 is all by network and 12 communication connections of this webserver.This communication connection mode can be wifi, infrared, bluetooth, 3G, 4G, cable broadband etc.In the present embodiment, this webserver 12 is cloud server.
Please refer to Fig. 2, in the present embodiment, this system 10 also comprises api interface converting unit 14, is connected between this webserver 12 and home appliance 13.This webserver 12 comprises operation historical record unit 120, language scripts storehouse 121, memory cell 122, logs in control unit 123, use habit unit 124 and use habit statistical analysis unit 127.
Wherein, this language scripts storehouse 121 is for storing multiple initialization language, and every kind of initialization language is the bottom machine language that a kind of home appliance is used, for example, and C++, java, perl, C# etc.This api interface converting unit 14 is for the conversion to api interface by the action of configuration unification of hardware and software according to the corresponding initialization language in language scripts storehouse 121.Particularly, this home appliance 13 can be sent to this api interface converting unit 14 by the configuration information of hardware or software (as used function and relative parameters setting), this api interface converting unit is obtained corresponding initialization language configuration information be converted to API configuration information and be uploaded in the webserver 12 from language scripts storehouse 121, this webserver 12 can be sent to API configuration information this api interface converting unit 14, API configuration information is converted to the configuration of the hardware and software mating with this home appliance 13 and is downloaded by home appliance 13 according to the opriginal language obtaining.
This user terminal 11 is communicated and is connected with a home appliance 13 by network, and in the present embodiment, this user terminal 11 is NFC equipment, by NFC, is communicated and is connected with this home appliance 13.Further, this user terminal 11 has unique for identifying the account information of identity, and this home appliance 13 can pre-stored one or more account information, and by determine whether to allow this user terminal 11 to log in connection to the checking of account information.When account information is passed through checking, this user terminal 11 establishes a communications link with this home appliance 13, and this home appliance 13 sends and logs in request to this webserver 12, and this logs in the account information of having carried this home appliance 13 in request, the account information that this user terminal 11 is used.Pre-stored a plurality of account information in the memory cell 122 of this webserver 12.And, the control unit 123 that logs in of this webserver 12 is verified logging in the account information of carrying in request according to a plurality of account information of memory cell 122 storages, and when being verified, this logs in the account information of carrying in request and mates with an account information of memory cell 122 storages, establish a communications link with this home appliance 13, feed back one simultaneously and log in successful signal to this home appliance 13.
When this home appliance 13 is successfully connected with this webserver 12, receive the successful signal of logging in of this feedback, by this api interface converting unit 14, send identity identification information and the api interface of self, to notify identity identification information and the spendable api interface of these webserver 12 these home appliances 13.Wherein, this identity identification information can be the classification (as air-conditioning, refrigerator, washing machine etc.) of home appliance, can also be the model of home appliance.
Identity identification information and the corresponding user of this memory cell 122 is also pre-stored a plurality of home appliances use historical information, and wherein, this user uses historical information can comprise the parameter configuration, user's use habit information etc. of this home appliance.Further, this memory cell 122 is divided into a plurality of other storage areas of level, as first order classification storage area, second level classification storage area ..., and the plurality of other storage area of level is tree.Every one-level storage area is for storing different configuration informations.For example, the classification (as refrigerator, washing machine etc.) of first order classification storage area for storing home appliance, second level classification storage area is used for storing other model of each household appliances (as the refrigerator of the refrigerator of RTS2006 model, RTS2016 model), third level classification storage area is for storing the basic function (as the refrigerator of RTS2006 model has the function that refrigerates automatic temperature-control, refrigeration zoned temperature control, the refrigerator of RTS2016 model has the function of digital temperature adjustment, refrigeration zoned temperature control) of each household electrical appliances model.
When this webserver 12 receives identity identification information that this home appliance 13 sends and spendable api interface, thereby the use historical information that the identity identification information whether with coupling determines whether this home appliance 13 is inquired about in this operation historical record unit 120 in memory cell 122.If no, this use habit unit 124 is according to using all API states of home appliance 13 to carry out statistical learning to user's use habit.
By take identity identification information, as household electrical appliances model as example, the statistical learning theory of user's use habit is illustrated below.
This use habit unit 124 comprises that configuration item is set up module 125 and configuration information writes control module 126.When definite this home appliance 13 is not used historical information in the webserver 12, this configuration item is set up module 125 and is set up model entrance, and sends request to this home appliance 13 feedback one API.After this home appliance 13 receives this API and sends request, send api interface that this home appliance supports to this webserver 12.For example, the API of certain model air-conditioning support has refrigerating/heating/ventilation to select that (Configuration Values is 0/1/2,0 representative refrigeration, 1 representative heats, and 2 representatives are ventilated), temperature setting (configuration scope 16 to 30), sweep up and down wind (Configuration Values 0/1,0 representative is closed, and 1 representative is opened), wind (Configuration Values 0/1,0 representative is closed, and 1 representative is opened) is swept in left and right, plasma wind function (Configuration Values 0/1,0 representative is closed, and 1 representative is opened), dehumidification function (Configuration Values 0/1,0 representative is closed, and 1 representative is opened).
The configuration of this webserver 12 writes control module 126 and sets up all API configuration items according to the identity information of this home appliance 13, and after user finishes using, this home appliance 13 can also send to this webserver 12 by current all API states.The configuration of this webserver 12 writes control module 126 these API state informations is stored in corresponding API configuration item.For example, this use habit statistical analysis unit 127 determines that the classification of these home appliances 13 is that washing machine, model are QRS2055, and sets up corresponding API configuration item, and this API state can comprise the water level, temperature, rinsing time of washing machine etc.User finishes using after this home appliance 13 and sends shutdown command, and this home appliance 13 sent to current all API states in this webserver 13 before this shutdown command of response.This configuration writes control module 126 the API state information receiving is stored in the API configuration item of setting up in advance accordingly.Thereby, as mentioned above, the record of completing user use habit, configuration information.
When definite this home appliance 13 has the historical information of use in the webserver 12, the operation historical record unit 120 of this webserver 12 obtains corresponding use historical information to form corresponding API configuration information from this memory cell 122, and sends initialization request and API configuration information to this home appliance 13.When this home appliance 13 receives this initialization request and API configuration information, according to this API configuration information, complete the initialization after start, according to the corresponding function of API configuration information configuration home appliance, be parameter, user can directly use the home appliance that meets own use habit.
Further, user uses home appliance and sends shutdown command, and this home appliance 13 sent to the webserver 12 by current all API states before this shutdown command of response, then this this shutdown command shutdown of home appliance 13 responses.The operation historical record unit 120 of this webserver 12 stores the API state information receiving in memory cell 122 into, and corresponding with this use habit historical data.In the present embodiment, the rerun user habit API configuration of this use habit statistical analysis unit 127, and by the configuration information update newly calculating in corresponding API configuration item.
Particularly, according to API state information computing user habit API, configuration comprises statistical model, study mould and memory pattern to this use habit statistical analysis unit 127.Wherein, statistical model refers to that use habit statistical analysis unit 127 counting users carry out maximum operations on the same equipment, and operation maximum be provided as start time initial setting up.Memory pattern refers to the API configuration before using operation historical record unit 120 to record each home appliance 13 closes, and can automatically restore to the operative configuration of last start while once starting shooting on this home appliance.Mode of learning refers to the division of operations weights of use habit statistical analysis unit 127 counting users on the same equipment, and nearest operation weights are higher, and operation weights more of a specified duration are lower, after weights are cumulative, obtains final configuration information.
In the present embodiment, this system also comprises large data analysis system 20, this operation historical record unit 120 is sent to this large data analysis system 20 by the historical record of all operations, for other any large data analysis application based on user's operation, be used as such as the large data analysis of individual's medical treatment, the large data analysis of individual psychology state, personal lifestyle is accustomed to large data analysis etc.
Referring to Fig. 3, is the schematic flow sheet of the intelligent appliance self-learning method in embodiment of the present invention, and the method comprises:
Step S30, this user terminal 11 logs in a home appliance 13, thereby establishes a communications link with this webserver 12.
This user terminal 11 has unique for identifying the account information of identity, and this home appliance 13 can pre-stored one or more account information, and by determine whether to allow this user terminal 11 to log in connection to the checking of account information.When account information is passed through checking, this user terminal 11 establishes a communications link with this home appliance 13, and this home appliance 13 sends and logs in request to this webserver 12, and this logs in the account information of having carried this home appliance 13 in request, the account information that this user terminal 11 is used.Pre-stored a plurality of account information in the memory cell 122 of this webserver 12.And, the control unit 123 that logs in of this webserver 12 is verified logging in the account information of carrying in request according to a plurality of account information of memory cell 122 storages, and when being verified, this logs in the account information of carrying in request and mates with an account information of memory cell 122 storages, establish a communications link with this home appliance 13, feed back one simultaneously and log in successful signal to this home appliance 13.
Step S31, this home appliance 13 sends identity identification information and the api interface of self by this api interface converting unit 14, to notify identity identification information and the spendable api interface of these webserver 12 these home appliances 13.
Wherein, this identity identification information can be the classification (as air-conditioning, refrigerator, washing machine etc.) of home appliance, can also be the model of home appliance.
Step S32, thus the use historical information that the identity identification information whether with coupling determines whether this home appliance 13 is inquired about in this operation historical record unit 120 in memory cell 122.If no, enter step S33, otherwise, enter step S34.
Identity identification information and the corresponding user of this memory cell 122 is pre-stored a plurality of home appliances use historical information, and wherein, this user uses historical information can comprise the parameter configuration, user's use habit information etc. of this home appliance.Further, this memory cell 122 is divided into a plurality of other storage areas of level, as first order classification storage area, second level classification storage area ..., and the plurality of other storage area of level is tree.Every one-level storage area is for storing different configuration informations.For example, the classification (as refrigerator, washing machine etc.) of first order classification storage area for storing home appliance, second level classification storage area is used for storing other model of each household appliances (as the refrigerator of the refrigerator of RTS2006 model, RTS2016 model), third level classification storage area is for storing the basic function (as the refrigerator of RTS2006 model has the function that refrigerates automatic temperature-control, refrigeration zoned temperature control, the refrigerator of RTS2016 model has the function of digital temperature adjustment, refrigeration zoned temperature control) of each household electrical appliances model.
Step S33, this use habit unit 124 is according to using all API states of home appliance 13 to carry out statistical learning to user's use habit.Then, flow process finishes.
Wherein, 124 couples of users' of this use habit unit use habit is carried out statistical learning and is comprised following sub-step:
Sub-step S330, this configuration item is set up module 135 and is set up model entrance, and sends request to this home appliance 13 feedback one API.
Sub-step S331, the API that this home appliance 13 sends this home appliance support is to this webserver 12.
For example, the API of certain model air-conditioning support has refrigerating/heating/ventilation to select that (Configuration Values is 0/1/2,0 representative refrigeration, 1 representative heats, and 2 representatives are ventilated), temperature setting (configuration scope 16 to 30), sweep up and down wind (Configuration Values 0/1,0 representative is closed, and 1 representative is opened), wind (Configuration Values 0/1,0 representative is closed, and 1 representative is opened) is swept in left and right, plasma wind function (Configuration Values 0/1,0 representative is closed, and 1 representative is opened), dehumidification function (Configuration Values 0/1,0 representative is closed, and 1 representative is opened).
Sub-step S332, this configuration writes control module 126 and sets up all API configuration items according to the identity information of this home appliance 13.
Sub-step S333, after user finishes using, this home appliance 13 sends to this webserver 12 by current all API states, and this configuration writes control module 126 the API state information receiving is stored in the API configuration item of setting up in advance accordingly.
Step S34, this operation historical record unit 120 obtains corresponding use historical information to form corresponding API configuration information from this memory cell 122, and sends initialization request and API configuration information to this home appliance 13.
Step S35, this home appliance 13 completes the initialization after start according to the API configuration information receiving, and according to the corresponding function of API configuration information configuration home appliance, is parameter, and user can directly use the home appliance that meets own use habit.
Step S36, user uses home appliance and sends shutdown command, and this home appliance 13 sent to the webserver 12 by current all API states before this shutdown command of response, then this this shutdown command shutdown of home appliance 13 responses.
Step S37, this operation historical record unit 120 stores the API state information receiving in memory cell 122 into, and corresponding with this use habit historical data.
In the present embodiment, the rerun user habit API configuration of this use habit statistical analysis unit 127, and by the configuration information update newly calculating in corresponding API configuration item.
Further, this operation historical record unit 120 is sent to this large data analysis system 20 by the historical record of all operations, for other any large data analysis application based on user's operation, be used as such as the large data analysis of individual's medical treatment, the large data analysis of individual psychology state, personal lifestyle is accustomed to large data analysis etc.
A kind of intelligent appliance self learning system provided by the invention and method, by to the analysis of the configuration information of home appliance and record, user is signed in to after different home appliances by user terminal anywhere by unique account, user's use habit of remembering and learn to obtain by server, automatically corresponding device setting is completed to configuration and the initialization for user habit, user's setup times and work have been greatly reduced, and access to your account can be across distinct device type, the household electrical appliances of same type different model are used, thereby complete according to user habit Lookup protocol and initialization.
The foregoing is only embodiments of the invention; not thereby limit the scope of the claims of the present invention; every equivalent structure or conversion of equivalent flow process that utilizes specification of the present invention and accompanying drawing content to do; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.
Claims (17)
1. an intelligent appliance self-learning method, is characterized in that, described method comprises:
The identity identification information of transmission home appliance and API information are to the webserver;
Thereby the identity identification information whether described webserver inquiry has coupling determines whether the use historical information of described home appliance, wherein, the identity identification information of home appliance and corresponding user use historical information by pre-stored; And
When determining the identity identification information that there is no coupling, according to all API states of the described home appliance of use, user's use habit is carried out to statistical learning.
2. intelligent appliance self-learning method as claimed in claim 1, is characterized in that, " identity identification information of transmission home appliance and API information are to the webserver " also comprises before:
Thereby user is logged in home appliance and establishes a communications link with the webserver for identifying the account information of identity by a user terminal input.
3. intelligent appliance self-learning method as claimed in claim 2, is characterized in that, thereby the account information that described user identifies identity by a user terminal input user logs in home appliance, comprises with the step that the webserver establishes a communications link:
User is by described user terminal input account information and be sent to described home appliance the account information of described input is verified to determine whether to allow described user terminal to log in connection according to pre-stored account information by network;
When the account information of described input is passed through checking, described user terminal and described home appliance establish a communications link, and the request that logs in of carrying described account information by described home appliance transmission is to the described webserver;
Described network server is verified the described account information of carrying in request that logs according to pre-stored a plurality of account information;
When described while logging in the account information of carrying in request by checking and described home appliance establish a communications link.
4. intelligent appliance self-learning method as claimed in claim 1, is characterized in that, " according to using all API states of described home appliance to carry out statistical learning to user's use habit " comprising:
Set up the entrance corresponding with described identity identification information, and to described home appliance, feed back an API and send request;
Send the API of described home appliance support to the described webserver;
According to the identity identification information of described home appliance, set up all API configuration items; And
To use the current API state of described home appliance to send to the described webserver, and corresponding being saved in the API configuration item of setting up in advance.
5. intelligent appliance self-learning method as claimed in claim 1, it is characterized in that, when defining the identity identification information of coupling, obtain corresponding use historical information to form corresponding API configuration information, and send initialization request and API configuration information to described home appliance;
According to described API configuration information, complete the opening initialization of home appliance, and according to described API configuration information configuration.
6. intelligent appliance self-learning method as claimed in claim 5, is characterized in that, also comprises:
After current API state being sent to the webserver after using described home appliance to finish, shut down; And
By the API state information receiving and the corresponding preservation of use habit historical data.
7. intelligent appliance self-learning method as claimed in claim 6, is characterized in that, also comprises:
According to the current API state that uses described home appliance to finish rear generation, recalculate computing user habit API configuration, and by the configuration information update newly calculating in corresponding API configuration item.
8. an intelligent appliance self learning system, comprises user terminal, the webserver and a plurality of home appliance, and each home appliance all communicates to connect with the described webserver, it is characterized in that, the described webserver comprises:
Memory cell, the identity identification information of pre-stored a plurality of home appliances and corresponding user use historical information;
Operation historical record unit, thus for the identity identification information whether identity identification information that sends according to described home appliance and API have coupling in described memory cell inquiry, determine whether to have the use historical information of described home appliance;
Use habit unit, when the use historical information there is no described home appliance is determined in described operation historical record unit for according to using the API state of described home appliance to carry out statistical learning to user's use habit.
9. intelligent appliance self learning system as claimed in claim 8, it is characterized in that, thereby user logs in described home appliance by account information and establishes a communications link with the described webserver on a user terminal, and by described home appliance, send the identity identification information of described home appliance and API to the described webserver when successful connection.
10. intelligent appliance self learning system as claimed in claim 9, it is characterized in that, user is by described user terminal input account information and be sent to described home appliance the account information of described input is verified to determine whether to allow described user terminal to log in connection according to pre-stored account information by network, when the account information of described input is passed through checking, described user terminal and described home appliance establish a communications link, and the request that logs in of carrying described account information by described home appliance transmission is to the described webserver;
Described network server also comprises and logs in control unit, for logging in the account information that request carries and verify described according to the pre-stored a plurality of account information of described memory cell, and when described in log in the account information of carrying in request when verifying and described home appliance establishes a communications link.
11. intelligent appliance self learning systems as claimed in claim 10, is characterized in that, described mobile terminal is NFC equipment, by NFC, send described account information to described home appliance.
12. intelligent appliance self learning systems as claimed in claim 8, is characterized in that, described use habit unit comprises:
Configuration item is set up module, for setting up the entrance corresponding with described identity identification information, and to described home appliance, feeds back an API and sends request, and feeds back the API of its support to trigger described home appliance;
Configuration writes control module, according to the identity identification information of described home appliance, sets up all API configuration items, will use the current API state information of described home appliance feedback to store in corresponding API configuration item.
13. intelligent appliance self learning systems as claimed in claim 8, it is characterized in that, when defining the identity identification information of coupling, described operation historical record unit obtains corresponding use historical information to form corresponding API configuration information from described memory cell, and sending initialization request and API configuration information to described home appliance, described home appliance completes opening initialization and configuration according to described API configuration information.
14. intelligent appliance self learning systems as claimed in claim 13, it is characterized in that, described operation historical record unit also stores memory cell into for current all API state informations that the described home appliance of the use receiving is fed back, and corresponding with described use habit historical data.
15. intelligent appliance self learning systems as claimed in claim 14, it is characterized in that, the described webserver also comprises use habit statistical analysis unit, for recalculate user habit API configuration according to the current API state that uses described home appliance to finish rear generation, and by the configuration information update newly calculating in corresponding API configuration item.
16. intelligent appliance self learning systems as claimed in claim 8, it is characterized in that, described system also comprises api interface converting unit, the described webserver also comprises for storing the language scripts storehouse of multiple initialization language, and described api interface converting unit is for mutually changing described API information and described configuration information according to the corresponding initialization language in language scripts storehouse.
17. intelligent appliance self learning systems as claimed in claim 8, is characterized in that, also comprise large data analysis system, use historical information, and described user history information is carried out to large data analysis application for receiving the user of described webserver transmission.
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| CN108173722A (en) * | 2017-12-26 | 2018-06-15 | 北京康力优蓝机器人科技有限公司 | A kind of smart home device automatic operation method |
| CN109076101A (en) * | 2017-12-29 | 2018-12-21 | 深圳市大疆创新科技有限公司 | Cloud platform control method, equipment and computer readable storage medium |
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| CN111338264A (en) * | 2020-03-24 | 2020-06-26 | 珠海格力电器股份有限公司 | Method for automatically setting parameters of electric appliance and electric appliance |
| CN111338264B (en) * | 2020-03-24 | 2021-04-27 | 珠海格力电器股份有限公司 | Method for automatically setting parameters of electric appliance and electric appliance |
| CN111665735A (en) * | 2020-06-26 | 2020-09-15 | 深圳全景空间工业有限公司 | Intelligent household control system |
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