CN112051744A - Intelligent terminal, and recommendation method and system for intelligent home application - Google Patents
Intelligent terminal, and recommendation method and system for intelligent home application Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention relates to an intelligent terminal, and a recommendation method and a recommendation system for intelligent home application, and belongs to the technical field of intelligent home internet control. The recommendation method comprises the following steps: collecting current at least one condition information; storing historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; for each application device, calculating a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; further obtaining a recommended value, wherein the recommended value is positively correlated with each conditional probability; and selecting the application equipment with larger recommendation value according to the recommendation value of each application equipment, and recommending and displaying on the home page. The method can accurately recommend the application equipment without searching the application equipment by the user, so that the operation of the user is more convenient, and the experience effect is better.
Description
Technical Field
The invention relates to an intelligent terminal, and a recommendation method and a recommendation system for intelligent home application, and belongs to the technical field of intelligent home internet control.
Background
The intelligent home system is characterized in that a home is taken as a platform, facilities related to home life are integrated by utilizing a computer technology, a network communication technology, a safety precaution technology, an automatic control technology, an audio and video technology and the like, an efficient management system of home facilities and daily affairs of the home is constructed, home safety, convenience and comfortableness are improved, and environment-friendly and energy-saving living environment is realized.
The App control is one of the intelligent home control modes, and further comprises manual control, intelligent scene control, voice interaction, intelligent linkage and the like. A lot of intelligent house hardware equipment can be bound to intelligent house App usually, and the home page display page of App is fixed moreover, and the user often need just can find the equipment icon that needs the control through looking up many times, and the operation is comparatively loaded down with trivial details, and user's experience effect is not good.
Disclosure of Invention
The invention aims to provide a recommendation method of smart home application, which is used for solving the problems of complex operation and poor experience effect when the existing method is used for controlling home hardware equipment; meanwhile, a recommendation system for smart home applications is provided, so that the problems of complex operation and poor experience effect when the existing system controls home hardware equipment are solved; still provide an intelligent terminal simultaneously for solve current terminal complex operation when controlling house hardware equipment, experience the not good problem of effect.
In order to achieve the purpose, the invention provides a recommendation method of smart home application, which comprises the following steps:
collecting current at least one condition information;
storing historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, calculating a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and selecting the application equipment with larger recommendation value according to the recommendation value of each application equipment obtained in the step, and recommending and displaying on the home page.
In addition, the invention further provides an intelligent terminal, which comprises a touch screen, a wireless communication device for receiving the acquired condition information, a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the recommendation method of the intelligent home application when executing the computer program.
The beneficial effects are that: according to the method, the historical condition information is used as a sample, the recommendation value of each application device is calculated, and then the application device with the larger recommendation value is recommended, so that the control of the application device is realized.
Further, in the recommendation method for the smart home application and the smart terminal, the method for calculating the conditional probability of the application device under certain current condition information includes:
wherein, YkFor the kth application, k is 1, 2, 3, …, n; xjIs the current value of certain condition information, mukTo turn on YkWhen all are in contact with XjAn average value of the corresponding historical condition information;
to turn on YkWhen all are in contact with XjVariance, P (X), of corresponding historical condition informationj|Y＝Yk) Is YkAt XjConditional probability of (c).
Further, in the recommendation method for the smart home application and the smart terminal, in order to obtain a more accurate recommendation value, the mathematical operation is a multiplication operation or an accumulation operation after taking a logarithm.
Further, in the recommendation method for the smart home application and the smart terminal, the historical opening times of each application device are also stored, and a calculation formula of a recommendation value is as follows:
wherein, YkFor the kth application, k is 1, 2, 3, …, n; xjIs the current value of certain condition information; p (X)j|Y＝Yk) Is YkAt XjThe conditional probability of j being 1, 2, 3, …, l is the number of types of conditional information; p (Y ═ Y)k| X) as application device YkA recommended value of (d); p (Y ═ Y)k) For application of apparatus YkA priori probability of (a); m iskFor application of apparatus YkM is the total historical opening times of all the application devices.
Further, in the recommendation method for the smart home application and the smart terminal, there are various methods for selecting the application device with a larger recommendation value, including: sorting the recommended values of the application devices from large to small, and selecting a plurality of application devices with large recommended values; or setting a recommended value threshold value, and selecting the application equipment corresponding to the recommended value larger than the recommended value threshold value.
Further, in the recommendation method for the smart home application and the smart terminal, there are various methods for recommending and displaying on the home page, including: displaying a plurality of application devices with larger recommendation values on a home page; or all the application devices are displayed on the home page, and a plurality of application devices with larger recommendation values are displayed in a highlighted manner on the home page.
In addition, the invention also provides a recommendation system of the smart home application, which comprises a mobile terminal and a control terminal, wherein the mobile terminal comprises a touch screen and a wireless communication module used for communicating with the control terminal; the control terminal comprises wireless communication means for communicating with the mobile terminal and for receiving condition information, a memory, a processor and a computer program stored in said memory and executable on the processor, said processor realizing the following steps when executing said computer program:
the wireless communication device acquires the acquired current at least one condition information;
the memory stores historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, the processor calculates a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and the processor selects the application equipment with a larger recommendation value according to the recommendation values of the application equipment obtained in the steps, communicates with the mobile terminal through the control terminal, and recommends and displays on a home page of the mobile terminal.
The beneficial effects are that: according to the method, the historical condition information is used as a sample, the recommendation value of each application device is calculated, and then the application device with the larger recommendation value is recommended, so that the control of the application device is realized.
Further, the method for calculating the conditional probability of the application device under certain current condition information includes:
wherein, YkFor the kth application, k is 1, 2, 3, …, n; xjIs the current value of certain condition information, mukTo turn on YkWhen all are in contact with XjAn average value of the corresponding historical condition information;
to turn on YkWhen all are in contact with XjVariance, P (X), of corresponding historical condition informationj|Y＝Yk) Is YkAt XjConditional probability of (c).
Further, in order to obtain a more accurate recommended value, the mathematical operation is a multiplication operation or an accumulation operation after taking a logarithm.
Further, there are various methods for recommending and displaying on the home page, including: displaying a plurality of application devices with larger recommendation values on a home page; or all the application devices are displayed on the home page, and a plurality of application devices with larger recommendation values are displayed in a highlighted manner on the home page.
Drawings
FIG. 1 is a flow chart of a recommendation method for smart home applications in accordance with the present invention;
fig. 2 is a schematic diagram of home page recommendation of the smart home application of the present invention.
Detailed Description
The embodiment of the intelligent terminal comprises:
the intelligent terminal provided by the embodiment comprises a touch screen, a wireless communication device for receiving the acquired condition information, a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the recommendation method of the intelligent home application when executing the computer program. Specifically, the intelligent terminal is a terminal device which provides an operation interface for a user and controls home hardware devices, and may be terminal devices in the forms of android, ios and the like, including an intelligent home App based on electronic products such as a mobile phone and a pad.
The method for recommending the smart home application has the main idea that starting information of each application device under a historical condition is stored, the starting information under the historical condition is used as a sample, the recommended value (namely the recommended probability) of each application device which is started under the current condition information is calculated according to the current condition information, and the application device with the larger recommended value is recommended according to the size of the recommended value.
The condition information comprises environment information and time, and the environment information comprises indoor temperature, outdoor temperature, weather information, gas concentration information and illumination information; the condition information is collected through the collection module, the collection module is bound with the App of the intelligent terminal, communication connection is carried out, and the collected condition information is sent to the intelligent terminal. As other embodiments, the invention does not limit the type and the number of the condition information, and can be set as required, of course, the more the types are, the more the calculation is complicated, and the more accurate the recommendation is.
The collection module includes:
the indoor temperature acquisition module is used for acquiring indoor temperature, and specifically can be a temperature sensor arranged indoors;
the outdoor temperature acquisition module is used for acquiring outdoor temperature, and specifically can be arranged outdoors;
the weather information sensing module is used for sensing weather conditions, such as: rain or wind, and the like, and specifically may be a weather sensor disposed outdoors;
the time acquisition module is used for acquiring time information, in particular to a time service module and the like;
the gas concentration detection module is used for detecting the concentration of various gases such as carbon dioxide and the like, and is specifically a gas sensor arranged indoors;
the illumination intensity sensing module is used for sensing the indoor illumination intensity and specifically is a photosensitive sensor arranged indoors.
The specific hardware equipment, setting position and working principle of each acquisition module are the prior art, and the invention is not introduced too much. The specific implementation form of each acquisition module is not limited in the present invention, as long as the corresponding function is implemented, and each acquisition module periodically acquires and stores and records each condition information every 1 minute in this embodiment.
In order to implement the main concept of the recommendation method for smart home applications of the present invention, in this embodiment, as shown in fig. 1, a naive bayes model is used to train and test historical condition information, so as to obtain a recommendation probability under current condition information. The recommendation method of the intelligent home application comprises the following steps:
1) storing historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; and simultaneously, starting each application device once, and accumulating the starting times of each application device to obtain the starting times of each application device (the starting times are operation records of clicking a certain hardware icon on an operation interface by a user, namely the records of controlling the application device or the furniture device by clicking a certain household device ID).
The storage is real-time dynamic storage, namely, the storage is used as historical condition information to participate in subsequent calculation after the application equipment is started each time.
The home equipment comprises all home equipment capable of being intelligently controlled, such as an air conditioner, a window, an illuminating lamp, a television, a curtain, a fan, a refrigerator and the like, wherein each home equipment corresponds to a furniture equipment ID, and each furniture equipment ID corresponds to a hardware icon one to one.
The historical condition information is acquired by each acquisition module, and the specific acquisition process is introduced and is not described herein. Since the condition information is collected periodically, the condition information is the condition information whose time is closest to the time of clicking the application device.
2) The current condition information (i.e. newly generated condition data) collected by each collection module is obtained, and the current condition information obtaining is the same as the historical condition information obtaining, which is not described herein too much.
3) And establishing a recommendation model according to the historical condition information and the opening times of each application device, and obtaining a recommendation value of each application device according to the current condition information based on the recommendation model.
The specific process of establishing the recommendation model comprises the following steps: the home equipment ID is used as a sample category, and corresponding historical condition information (the condition information is divided into multi-dimensional condition information according to the type of the collected data, the number of dimensions is l, and the condition information of each dimension is standardized respectively) is used as a sample characteristic to form a piece of complete training data. And dividing all training data according to a ratio of 9:1 to respectively serve as training set data and test set data.
Training the training set data based on a naive Bayes model. The naive Bayes model includes prior probabilities and conditional probabilities, in this embodiment, the number of furniture device IDs is n, Y is the predicted furniture device, that is, the sample classes are Y respectively1,Y2,Y3…Yn(ii) a The dimension of the condition information is 6, i.e. six-dimensional condition information features, and the sample features of each dimension are respectively represented by X1、X2、X3、X4、X5、X6And (4) showing. According to the naive Bayes model principle, firstly calculating the prior probability of n sample classes, wherein the prior probability of the kth sample class is as follows:
wherein m iskThe number of sample features representing the k-th household equipment, namely YkM represents the total number of sample features of all home devices, i.e., the total historical opening times of all application devices, and P (Y ═ Y ·, where k is 1, 2, 3, …k) Representing the prior probability of the kth sample class.
Then, calculating parameters of conditional probability in a Bayesian distribution model, wherein the characteristics of each conditional sample in the Bayesian distribution model accord with normal distribution, so that the calculation formula of the conditional probability is as follows:
wherein, P (X)j|Y＝Yk) Conditional probability (i.e. Y) for the kth sample class at the sample feature of the jth dimensionkAt XjConditional probability of (c); mu.skAs a sample class of YkWhen all are in contact with XjAverage value of corresponding condition information (i.e. all of the corresponding X's)jAverage of sample features for the corresponding dimension), j ═ 1, 2, 3, 4, 5, 6;
as a sample class of YkWhen all are in contact with XjVariance of corresponding condition information (i.e., all of the variance with X)jThe variance of the sample features for the corresponding dimension).
Obtaining mu based on the trainingk、 
Then, a recommendation model is generated based on a naive Bayes principle, the recommendation model is the basis of calculating recommendation probability, so that the recommendation model is multiplied by prior probability after product operation is carried out on each conditional probability, and a specific expression is as follows:
wherein, P (Y ═ Y)k| X) is the recommended probability of the sample class k under the current condition information. Of course, as other embodiments, the recommendation model may also perform a product operation for each conditional probability, but the product operation is more accurate by multiplying the prior probability, and in the case of not needing the prior probability,the number of times each application is turned on may not be recorded. In other embodiments, the product operation may be performed by taking the logarithm of each conditional probability and accumulating the logarithms.
Testing the recommended model according to the test set data, XtestFor six-dimensional conditional information features (i.e., sample features) in the test set data, P (Y-Y)k|X＝Xtest) For the k household equipment at XtestThe recommendation probability under the sample characteristics is calculated as:
the invention does not limit the specific calculation model for establishing the recommendation model, as long as the recommendation method for the smart home application can be realized.
And obtaining a final recommendation model through training of training set data and testing of testing set data, and continuously updating the recommendation model according to dynamic storage of historical condition information.
And obtaining the recommendation probability of each application device according to the current condition information and the recommendation model, and predicting the application devices needing to be started by the user according to the recommendation probability.
3) And generating a recommendation result according to the recommendation value of each application device obtained in the step, selecting the application device with a larger recommendation value, and recommending and displaying on the home page.
In this embodiment, the recommended values of the application devices are sorted from large to small, as shown in fig. 2, the application devices with the first three recommended values are selected, and only the first three recommended application devices are displayed on the home page, and the current indoor temperature and the current outdoor temperature are also displayed. Of course, as another embodiment, a recommendation value threshold may be set, and the application devices corresponding to the recommendation values larger than the recommendation value threshold may be selected and displayed, and all the application devices may be displayed on the top page during display, and the first three application devices with larger recommendation values may be displayed in a highlighted manner on the top page. Meanwhile, the number of the furniture devices recommended to the user can be set in a user-defined mode.
The method and the device can accurately recommend the furniture equipment required by the user according to the current condition information, for example, the lighting lamp is required to be turned on when the light is dark, the air conditioner is required to be turned on when the temperature is high, the television is required to be turned on at a specific time, and the like, and the user does not need to search hardware icons, so that the user operation is simpler and more convenient, and the experience effect is better.
The embodiment of the recommendation system for the smart home application comprises the following steps:
the recommendation system for smart home applications in this embodiment is different from the above-mentioned smart terminal in that the smart terminal is an intelligent terminal integrating processing and display, and in the recommendation system for smart home applications, the control terminal processes the acquired information and displays the information in the mobile terminal, which are two independent devices capable of communicating.
Therefore, the recommendation system for the smart home application provided by the embodiment includes a mobile terminal and a control terminal, where the mobile terminal includes a touch screen and a wireless communication module for communicating with the control terminal; the control terminal comprises wireless communication means for communicating with the mobile terminal and for receiving condition information, a memory, a processor and a computer program stored in said memory and executable on the processor, said processor realizing the following steps when executing said computer program:
the wireless communication device acquires the acquired current at least one condition information;
the memory stores historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, the processor calculates a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and the processor selects the application equipment with a larger recommendation value according to the recommendation values of the application equipment obtained in the steps, communicates with the mobile terminal through the control terminal, and recommends and displays on a home page of the mobile terminal.
In this embodiment, specific steps implemented by the processor when executing the computer program are the same as the recommendation method of the smart home application in the intelligent terminal embodiment, and are not described here too much.
The embodiment of the recommendation method of the smart home application comprises the following steps:
the recommendation method for the smart home application provided by the embodiment comprises the following steps:
collecting current at least one condition information;
storing historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, calculating a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and selecting the application equipment with larger recommendation value according to the recommendation value of each application equipment obtained in the step, and recommending and displaying on the home page.
The specific implementation process of the recommendation method for the smart home application is introduced in the foregoing embodiment of the smart terminal, and is not described herein again.
Claims (10)
1. A recommendation method for smart home applications is characterized by comprising the following steps:
collecting current at least one condition information;
storing historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, calculating a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and selecting the application equipment with larger recommendation value according to the recommendation value of each application equipment obtained in the step, and recommending and displaying on the home page.
2. The recommendation method for smart home applications according to claim 1, wherein the calculation method for the conditional probability of the application device under the current certain condition information is as follows:
wherein, YkIs the kth application device; xjIs the current value of certain condition information, mukTo turn on YkWhen all are in contact with XjAn average value of the corresponding historical condition information;
to turn on YkWhen all are in contact with XjVariance, P (X), of corresponding historical condition informationj|Y＝Yk) Is YkAt XjConditional probability of (c).
3. The recommendation method for smart home applications according to claim 1 or 2, wherein the mathematical operation is a multiplication-by-multiplication operation or an accumulation operation after taking a logarithm.
4. The recommendation method for smart home applications according to claim 3, further storing the historical opening times of each application device, wherein the calculation formula of the recommendation value is as follows:
wherein, YkIs the kth application device; xjIs the current value of certain condition information; p (X)j|Y＝Yk) Is YkAt XjThe conditional probability of j being 1, 2, 3, …, l is the number of types of conditional information; p (Y ═ Y)k| X) as application device YkA recommended value of (d); p (Y ═ Y)k) For application of apparatus YkA priori probability of (a); m iskFor application of apparatus YkM is the total historical opening times of all the application devices.
5. The recommendation method of smart home applications according to claim 1, wherein selecting the application device with the larger recommendation value comprises: sorting the recommended values of the application devices from large to small, and selecting a plurality of application devices with large recommended values; or setting a recommended value threshold value, and selecting the application equipment corresponding to the recommended value larger than the recommended value threshold value.
6. The recommendation method for smart home applications according to claim 1, wherein recommending and displaying on a home page comprises: displaying a plurality of application devices with larger recommendation values on a home page; or all the application devices are displayed on the home page, and a plurality of application devices with larger recommendation values are displayed in a highlighted manner on the home page.
7. A recommendation system for smart home applications comprises a mobile terminal and a control terminal, wherein the mobile terminal comprises a touch screen and a wireless communication module used for communicating with the control terminal; the control terminal comprises wireless communication means for communicating with the mobile terminal and for receiving condition information, a memory, a processor and a computer program stored in said memory and executable on the processor, characterized in that said processor realizes the following steps when executing said computer program:
the wireless communication device acquires the acquired current at least one condition information;
the memory stores historical condition information of each application device, wherein the historical condition information comprises at least one condition information when the application device is started; the condition information comprises indoor temperature, outdoor temperature, weather information, gas concentration information, illumination information and time;
for each application device, the processor calculates a recommended value of the application device; the calculation mode of the recommended value is as follows: calculating the conditional probability of the application equipment under certain current condition information by taking the historical condition information of the application equipment as a sample; performing mathematical operation on the calculated conditional probability of the application equipment under each current condition information to obtain the recommended value, wherein the recommended value is positively correlated with each conditional probability;
and the processor selects the application equipment with a larger recommendation value according to the recommendation values of the application equipment obtained in the steps, communicates with the mobile terminal through the control terminal, and recommends and displays on a home page of the mobile terminal.
8. The recommendation system for smart home applications according to claim 7, wherein the calculation method of the conditional probability of the application device under certain current condition information is as follows:
wherein, YkFor the kth application, k is 1, 2, 3, …, n; xjIs the current value of certain condition information, mukTo turn on YkWhen all are in contact with XjAn average value of the corresponding historical condition information;
to turn on YkWhen all are in contact with XjVariance, P (X), of corresponding historical condition informationj|Y＝Yk) Is YkAt XjConditional probability of (c).
9. The recommendation system for smart home applications according to claim 7 or 8, wherein the mathematical operation is a multiplication-by-multiplication operation or a logarithm-followed-accumulation operation.
10. An intelligent terminal comprising a touch screen, a wireless communication device for receiving collected condition information, a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the recommendation method for smart home applications according to any one of claims 1 to 6 when executing the computer program.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113158027A (en) * | 2021-03-09 | 2021-07-23 | 厦门盈趣科技股份有限公司 | Intelligent device recommendation method and system and intelligent terminal |
| CN113315685A (en) * | 2021-03-09 | 2021-08-27 | 厦门盈趣科技股份有限公司 | Accelerated interaction method and system for intelligent equipment and intelligent terminal |
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