CN110553354A - Control method and device of intelligent equipment - Google Patents

Control method and device of intelligent equipment Download PDF

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Publication number
CN110553354A
CN110553354A CN201810564690.1A CN201810564690A CN110553354A CN 110553354 A CN110553354 A CN 110553354A CN 201810564690 A CN201810564690 A CN 201810564690A CN 110553354 A CN110553354 A CN 110553354A
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CN
China
Prior art keywords
control
intelligent equipment
intelligent
control parameters
smart
Prior art date
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CN201810564690.1A
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Chinese (zh)
Inventor
陈翀
肖龙
连圆圆
秦萍
万会
冯德兵
马诗蓉
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珠海格力电器股份有限公司
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Priority to CN201810564690.1A priority Critical patent/CN110553354A/en
Publication of CN110553354A publication Critical patent/CN110553354A/en

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Classifications

    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/50Control or safety arrangements characterised by user interfaces or communication
    • F24F11/52Indication arrangements, e.g. displays
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/50Control or safety arrangements characterised by user interfaces or communication
    • F24F11/56Remote control
    • F24F11/58Remote control using Internet communication
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24HEATING; RANGES; VENTILATING
    • F24FAIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00Control or safety arrangements
    • F24F11/62Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63Electronic processing
    • F24F11/64Electronic processing using pre-stored data

Abstract

the invention relates to a control method and a device of intelligent equipment, wherein the method comprises the following steps: acquiring environmental data; determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is mutually linked intelligent equipment; and performing linkage control on the intelligent equipment according to the control parameters. According to the technical scheme, the control parameters of the intelligent equipment are determined through the acquired environment data, so that linkage control over the intelligent equipment is achieved, compared with a control mode of single intelligent equipment, indoor air condition adjusting means are enriched, the use efficiency of the intelligent equipment is improved, and meanwhile comfort level experience of a user is improved.

Description

Control method and device of intelligent equipment

Technical Field

The invention relates to the technical field of intelligent equipment, in particular to a control method and a control device of intelligent equipment.

Background

Air conditioning is an apparatus that provides treated air directly to an enclosed space, room or area. The treatment of the air includes changing the temperature, humidity, cleanliness and other parameters of the air.

at present, the air conditioner is an essential household electrical appliance in daily life, and the importance degree of the air conditioner is self-evident particularly in summer. However, through research, it is found that although the air conditioner has a remarkable function in indoor air conditioning, users tend to ventilate more naturally in the same temperature environment compared with the sealed environment when the air conditioner is operated, so that the users feel more comfortable, and diseases such as cold and air conditioning diseases caused by long-time air blowing can be avoided.

Because the air conditioner is adjusted according to the indoor air condition, so when outdoor temperature is lower, originally when can adjusting the indoor air condition through windowing, the air conditioner is still in operation according to the indoor air condition, has not only caused the waste of electric power energy like this, has also reduced user's comfortable nature experience simultaneously.

Disclosure of Invention

in order to overcome the problems in the related art at least to a certain extent, the invention provides a control method and a control device of an intelligent device.

according to a first aspect of an embodiment of the present invention, there is provided a method for controlling an intelligent device, including:

acquiring environmental data;

determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is mutually linked intelligent equipment;

and performing linkage control on the intelligent equipment according to the control parameters.

Preferably, the determining the control parameter of the smart device according to the environment data includes:

When the intelligent equipment is determined to need linkage, a preset control parameter determination model is adopted, the control parameters of the intelligent equipment are determined according to the environment data, and the input and the output of the control parameter determination model are the environment data and the control parameters respectively.

Preferably, the control method of the intelligent device further includes:

And judging whether the intelligent equipment needs to be linked or not according to the environment data by adopting a preset judgment model.

preferably, the control parameter determination model is an artificial neural network model.

Preferably, the decision model is a decision tree model.

Preferably, the control method of the intelligent device further includes:

Acquiring monitoring data, and sending the monitoring data to a mobile terminal so as to display the monitoring data on the mobile terminal, wherein the monitoring data comprises at least one of the following items: environmental data, control parameters and running state information of the intelligent equipment after being controlled.

Preferably, the control method of the intelligent device further includes:

And receiving a control instruction sent by the mobile terminal, wherein the control instruction is generated by the mobile terminal according to the control operation of a user, and the control operation is generated by the user according to the monitoring data displayed on the mobile terminal.

Preferably, the smart device comprises at least: air conditioners and windows.

Preferably, the smart device further comprises at least one of:

Fresh air machine, air purifier, dehumidifier, humidifier.

according to a second aspect of the embodiments of the present invention, there is provided a control apparatus for an intelligent device, including:

the acquisition module is used for acquiring environmental data;

The determining module is used for determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is mutually linked intelligent equipment;

And the control module is used for carrying out linkage control on the intelligent equipment according to the control parameters.

Preferably, the apparatus is located in a linkage controlled smart device, or in a remote server, or in a central processor of a smart device.

The technical scheme provided by the embodiment of the invention can have the following beneficial effects:

The control parameters of the intelligent equipment are determined through the acquired environmental data, so that linkage control over the intelligent equipment is realized.

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 invention, as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

FIG. 1 is a flow chart illustrating a method of controlling a smart device in accordance with an exemplary embodiment;

FIG. 2 is a flow chart illustrating a method of controlling a smart device in accordance with another exemplary embodiment;

FIG. 3 is a flow chart illustrating a method of controlling a smart device in accordance with another exemplary embodiment;

FIG. 4 is a schematic diagram of a decision tree model shown in accordance with an exemplary embodiment;

FIG. 5 is a schematic diagram of an artificial neural network model shown in accordance with an exemplary embodiment;

FIG. 6 is a schematic block diagram illustrating a control apparatus of a smart device in accordance with an exemplary embodiment;

fig. 7 is a schematic block diagram illustrating a control apparatus of an intelligent device according to another exemplary 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 invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.

Fig. 1 is a flowchart illustrating a control method of a smart device according to an exemplary embodiment, as shown in fig. 1, the method including the steps of:

step S11, acquiring environmental data;

Step S12, determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is intelligent equipment which is mutually linked;

and step S13, carrying out linkage control on the intelligent equipment according to the control parameters.

it should be noted that the environmental data includes, but is not limited to: indoor and outdoor temperature and humidity data, wind speed, wind direction, rainfall, PM2.5 value, oxygen content, formaldehyde content and the like.

in step S11, the acquiring of the environment data includes: obtaining indoor environment data and obtaining outdoor environment data. Wherein the content of the first and second substances,

For obtaining indoor environment data, various sensors may be arranged indoors to obtain indoor temperature and humidity, for example, indoor air speed is obtained through indoor temperature and humidity sensors, indoor oxygen content is obtained through indoor oxygen concentration sensors, and the like. Or, sensors of the existing intelligent equipment can be directly multiplexed, for example, an air conditioner is generally provided with a temperature and humidity sensor, a wind speed sensor, a wind direction sensor and the like; the air purifier is generally provided with a humidity sensor, a formaldehyde content sensor, a PM2.5 content sensor and the like; humidifiers generally have a humidity sensor or the like.

for obtaining the outdoor environment data, the outdoor environment data sent by the cloud platform can be received, for example, the outdoor weather real-time data sent by a weather bureau is received; alternatively, the outdoor environment data may be searched from the internet, or may be acquired by arranging various sensors, for example, acquiring outdoor temperature and humidity by an outdoor temperature and humidity sensor, acquiring outdoor wind speed by an outdoor wind speed sensor, and acquiring outdoor rainfall by an outdoor rainfall sensor.

It is understood that the smart devices in steps S12 and S13 are mutually linked smart devices controlled by the same central processing unit, or are mutually linked smart devices controlled by the same remote server in the same local area network, or are mutually linked smart devices controlled by any one of the smart devices (for example, an air conditioner is used as a main controller, and a humidifier, a dehumidifier, an air purifier, a fresh air blower, a window, etc. are simultaneously controlled).

It should be noted that the intelligent device includes: smart appliances and smart home devices, wherein the smart appliances include but are not limited to: an air conditioner, an air purifier, a fresh air machine, an exhaust fan, a dehumidifier, a humidifier, a dust removal robot, and the like; the smart home devices include but are not limited to: smart windows, smart doors, smart curtains, smart home alarms, and the like.

preferably, the smart device comprises at least: air conditioners and windows.

The control to the window can be realized through the linkage control device of the window, whether the window is opened or not and the opening angle are detected, and the window can be opened or closed through the window magnetic switch of the window. The structure and operation principle of the window belong to the prior art, and are not described herein.

it can be understood that, compare pure window or air conditioner control mode among the correlation technique, the air conditioner that this embodiment provided and the coordinated control mode of window have richened indoor air conditioning's means, can improve user's comfort level and experience, also can reduce the energy resource consumption that the air conditioner brought simultaneously, reduce the user because of the cold that blows the air conditioner for a long time, the emergence of air conditioner disease.

Preferably, the smart device further comprises at least one of:

Fresh air machine, air purifier, dehumidifier, humidifier.

it can be understood that if windowing, must have the air quality problem, so if on the basis of air conditioner and window control, in addition to the coordinated control to other smart machines, can further improve user's comfort level and experience. For example: under the windy condition of outdoor cloudy day, can control and open the window and cool down the ventilation, but this moment if there is dust, pollen, catkin or air quality not good in the air, if can the simultaneous control air purifier open, can realize the accurate regulation to the indoor air situation, further improve user's comfort level and experience.

In step S13, performing linkage control on the smart device according to the control parameter may be: starting a humidifier, an air purifier and the like while starting the air conditioner; or, when the air conditioner is closed, the humidifier is closed, the air purifier is opened, the window is opened, and the like; alternatively, simply to close the window; or, simply to turn on the air conditioner.

it is understood that the control parameters of the smart device include, but are not limited to: the air conditioner comprises a window opening degree (for example, 90 degrees, 45 degrees, 30 degrees and the like), a window opening mode (an upper suspension mode, a lower suspension mode, a side-hung mode and the like), an air conditioner working mode (for example, opening, closing, dormancy, heating, refrigerating, dehumidifying, air supplying and the like), an air conditioner working state (for example, three-stage wind speed, downward wind direction, 26 ℃ and the like), an air purifier working mode (for example, opening, closing, formaldehyde removing, pollen removing, PM2.5 removing, strong wind silence, peaceful sleep and the like), an air purifier working state (for example, strong sterilization, formaldehyde removing, three-stage wind speed, 70% relative humidity RH), a humidifier working mode (for example, opening, closing, dormancy, 70% relative humidity RH and the like), a dehumidifier working mode (for example, opening, closing, automatic drainage, clothes drying, high wind speed and the like).

According to the technical scheme, the control parameter of the intelligent device is determined through the acquired environment data, so that linkage control over the intelligent device is achieved, compared with a control mode of a single intelligent device, the control method of the intelligent device enriches means for adjusting the indoor air condition, improves the use efficiency of the intelligent device, and meanwhile improves comfort level experience of a user.

preferably, the determining the control parameter of the smart device according to the environment data includes:

When the intelligent equipment is determined to need linkage, a preset control parameter determination model is adopted, the control parameters of the intelligent equipment are determined according to the environment data, and the input and the output of the control parameter determination model are the environment data and the control parameters respectively.

Preferably, the control parameter determination model is an artificial neural network model.

The input data of the artificial neural network model is data obtained by performing linear processing such as normalization on environmental data, nonlinear processing such as logarithmic transformation, square root transformation, and cubic root on the environmental data, and performing data exception processing.

The artificial neural network model includes, but is not limited to: a supervised learning network model, an unsupervised learning network model, a mixed learning network model, an associative learning network model and an optimal learning network.

It can be understood that the air quality problem exists due to the windowing ventilation, and the model is determined through the preset control parameters, such as an artificial neural network model, so that the linked intelligent equipment works efficiently, energy-saving and orderly, the service efficiency of the intelligent equipment is improved, and meanwhile, the intelligent decision is realized for a user, such as when to use, how large the power is to be opened and the like.

preferably, the control method of the intelligent device further includes:

And judging whether the intelligent equipment needs to be linked or not according to the environment data by adopting a preset judgment model.

Preferably, the decision model is a decision tree model.

It can be understood that, when the control parameter is obtained to control the window by determining a model, such as an artificial neural network model, by a preset control parameter, a deviation occurs. If the weather conditions are storm, severe haze and the like, the windowing cannot be performed in the weather conditions, but because the artificial neural network model has randomness, the output result is likely to be small-amplitude windowing, but the output result is unsafe. The embodiment provides a control algorithm of a decision tree model and an artificial neural network model, the extreme weather conditions are screened out through the decision tree model, and then the corresponding environment data is input into the artificial neural network model to obtain the control parameters of the intelligent device, so that the condition that the artificial neural network model outputs windowing control parameters to control windowing under the extreme weather conditions is avoided, and the reliability and the safety of the system are greatly improved.

preferably, the control method of the intelligent device further includes:

Acquiring monitoring data, and sending the monitoring data to a mobile terminal so as to display the monitoring data on the mobile terminal, wherein the monitoring data comprises at least one of the following items: environmental data, control parameters and running state information of the intelligent equipment after being controlled.

It can be understood that, the monitoring data is sent to the mobile terminal, so that the user can monitor the indoor and outdoor air conditions and the running states of the intelligent devices through the mobile terminal, the user experience can be improved, and meanwhile, the user can rapidly position faults when the intelligent devices cannot work normally.

preferably, the control method of the intelligent device further includes:

And receiving a control instruction sent by the mobile terminal, wherein the control instruction is generated by the mobile terminal according to the control operation of a user, and the control operation is generated by the user according to the monitoring data displayed on the mobile terminal.

It can be understood that, due to individual differences, the control method for the intelligent device provided in this embodiment does not satisfy every user in terms of adjustment of the indoor air condition, and the user feeds back the own requirements (for example, an expected wind speed value, a wind direction value, and a temperature and humidity value) to the preset control parameter model through the mobile terminal according to the monitoring data displayed on the mobile terminal, so that the preset parameter model corrects the output control parameters, and the comfort experience of the user can be improved.

Fig. 2 is a flowchart illustrating a control method of a smart device according to another exemplary embodiment, as shown in fig. 2, the method including the steps of:

step S21, acquiring environmental data;

The environmental data includes, but is not limited to: indoor and outdoor temperature and humidity data, wind speed, wind direction, rainfall, PM2.5 value, oxygen content, formaldehyde content and the like.

Step S22, processing the environmental data;

The processing of the environment data includes but is not limited to: and performing linear processing such as normalization and nonlinear processing such as logarithmic transformation, square root transformation and cubic root on the environmental data, and removing abnormal data.

Step S23, judging whether the intelligent equipment needs to be linked or not according to the processed environmental data by adopting a preset judgment model; if yes, executing the step S24, otherwise, jumping to the step S26;

Taking the decision model as a decision tree model and the intelligent device including an air-conditioning-related household appliance as an example, as shown in fig. 4, a first decision point of the decision tree model is: judging whether the current air quality condition is good (according to the PM2.5 value judgment), if so, judging that the intelligent equipment does not need linkage; otherwise, entering a second decision point: judging whether the current weather condition is good (judging according to wind speed and rainfall), if so, judging that the intelligent equipment does not need linkage; otherwise, a third decision point is entered: judging whether the current outdoor temperature is high, if so, judging that the intelligent equipment does not need linkage, and jumping to the step S26; otherwise, the intelligent device is judged to need linkage, and step S24 is executed.

Assume that the currently acquired environmental data is: the outdoor wind speed is three-level, the south wind, the temperature is 20 ℃, the relative humidity is 40% RH, the rainfall is 0 mm, the value of PM2.5 is 35, according to the decision tree model shown in FIG. 4, at the first decision point, because the value of PM2.5 is 35, the current air quality state is output to be good, and then the second decision point is entered; in the second decision point, the current weather condition is good because the outdoor wind speed is three levels and the rainfall is 0 mm, and then the current weather condition enters a third decision point; at the third decision point, since the outdoor temperature is 20 ℃, it is determined that the intelligent device needs to be linked because the output outdoor temperature is not high, and step S24 is executed.

it should be noted that, in the decision tree model shown in fig. 4, the decision tree is divided into several layers, each layer is provided with several decision points, and what the judgment policy of each decision point is, a user can set the decision points as needed. The decision tree model shown in fig. 4 is only an example, and does not represent that the technical solution provided by the present invention can only use the decision tree model shown in fig. 4, and the specific structure of the decision tree model allows a user to flexibly set the decision tree model according to his own needs. For example, the south wind air is relatively humid, and a decision point for judging the humidity of the outdoor air can be added on the basis of the decision tree model shown in fig. 4; the north air is dry and easy to scrape the north wind in winter, and a decision point for judging the outdoor wind direction can be additionally arranged on the basis of the decision tree model shown in the figure 4.

Step S24, determining a control parameter of the intelligent device according to the processed environmental data by adopting a preset control parameter determination model, wherein the input and the output of the control parameter determination model are respectively environmental data and the control parameter;

Taking the control parameter determination model as an artificial neural network model and the intelligent device including an air-conditioning-related household appliance as an example, as shown in fig. 5, the input of the artificial neural network is processed environmental data, such as: indoor environment temperature, outdoor environment humidity, indoor environment humidity, outdoor air volume level, rainfall, target value set by a user, comfort data fed back by the user and outdoor air quality; the output of the artificial neural network is the control parameter of the intelligent device, such as: window opening, air conditioner operating condition, air purifier operating condition, dehumidifier operating condition, humidifier operating condition.

It should be noted that, in the artificial neural network model shown in fig. 5, a user may set multiple hidden layers as needed, and each layer sets multiple hidden node numbers. The artificial neural network model shown in fig. 5 is only an example, and does not represent that the technical solution provided by the present invention can only use the artificial neural network model shown in fig. 5, and the artificial neural network model includes but is not limited to: a supervised learning network model, an unsupervised learning network model, a mixed learning network model, an associative learning network model and an optimal learning network.

Step S25, carrying out linkage control on the intelligent equipment according to the control parameters;

And step S26, end.

In this embodiment, preferably, the intelligent device at least includes: air conditioners and windows.

It can be understood that, compare pure window or air conditioner control mode among the correlation technique, the air conditioner that this embodiment provided and the coordinated control mode of window have richened indoor air conditioning's means, can improve user's comfort level and experience, also can reduce the energy resource consumption that the air conditioner brought simultaneously, reduce the user because of the cold that blows the air conditioner for a long time, the emergence of air conditioner disease.

preferably, the smart device further comprises at least one of:

Fresh air machine, air purifier, dehumidifier, humidifier.

It can be understood that if windowing, there will be air quality problem certainly, so if on the basis of air conditioner and window control, in addition to the coordinated control to other air condition adjusting device, can further improve user's comfort level and experience. For example: under the windy condition of outdoor cloudy day, can control and open the window and cool down the ventilation, but this moment if there is dust, pollen, catkin or air quality not good in the air, if can the simultaneous control air purifier open, can realize the accurate regulation to the indoor air situation, further improve user's comfort level and experience. The embodiment determines a model through preset control parameters, such as an artificial neural network model, so that a plurality of linked intelligent devices work together efficiently, energy-saving and orderly, the service efficiency of the intelligent devices is improved, and meanwhile, the intelligent decision making is realized for a user, for example, when the intelligent devices are used, how large the power is opened, and the like.

it can be understood that, when the control parameter is obtained to control the window by determining a model, such as an artificial neural network model, by a preset control parameter, a deviation occurs. If the weather conditions are storm, severe haze and the like, the windowing cannot be performed in the weather conditions, but because the artificial neural network model has randomness, the output result is likely to be small-amplitude windowing, but the output result is unsafe. The embodiment provides a control algorithm of a decision tree model and an artificial neural network model, the extreme weather conditions are screened out through the decision tree model, and then the corresponding environment data is input into the artificial neural network model to obtain the control parameters of the intelligent device, so that the condition that the artificial neural network model outputs windowing control parameters to control windowing under the extreme weather conditions is avoided, and the reliability and the safety of the system are greatly improved.

in summary, compared with the technical scheme shown in fig. 1, the technical scheme provided in this embodiment adopts a control algorithm of a decision model (e.g., a decision tree model) and a control parameter determination model (e.g., an artificial neural network model), so as to realize indoor air condition regulation, enable an air conditioner and other household appliances to operate more efficiently, energy-saving, orderly, improve the use efficiency of intelligent devices, solve the problem that the artificial neural network model may trigger windowing in extreme weather, and greatly improve the reliability and safety of the system.

Fig. 3 is a flowchart illustrating a control method of a smart device according to another exemplary embodiment, as shown in fig. 3, the method including the steps of:

step S31, acquiring environmental data;

The environmental data includes, but is not limited to: indoor and outdoor temperature and humidity data, wind speed, wind direction, rainfall, PM2.5 value, oxygen content, formaldehyde content and the like.

Step S32, processing the environmental data;

The processing of the environment data includes but is not limited to: and performing linear processing such as normalization and nonlinear processing such as logarithmic transformation, square root transformation and cubic root on the environmental data, and removing abnormal data.

Step S33, judging whether the intelligent equipment needs to be linked or not according to the processed environmental data by adopting a preset judgment model; if yes, executing step S34, otherwise jumping to step S36;

step S34, determining a control parameter of the intelligent device according to the processed environmental data by adopting a preset control parameter determination model, wherein the input and the output of the control parameter determination model are respectively environmental data and the control parameter;

Step S35, carrying out linkage control on the intelligent equipment according to the control parameters;

step S36, acquiring monitoring data, and sending the monitoring data to the mobile terminal to display the monitoring data on the mobile terminal, wherein the monitoring data comprises at least one of the following items: environmental data, control parameters and running state information of the intelligent equipment after being controlled;

step S37, receiving a control instruction sent by the mobile terminal, wherein the control instruction is generated by the mobile terminal according to the control operation of a user, and the control operation is generated by the user according to the monitoring data displayed on the mobile terminal;

And step S38, end.

It should be noted that, compared with the technical solution shown in fig. 2, in this embodiment, only step S36 and step S37 are added, and the implementation manners of other steps are the same, and since the implementation manners of the steps have been described in detail in the foregoing embodiment, details are not described here.

In addition, in fig. 3, step S36 and step S37 are placed after step S35, and in fact, step S36 and step S37 may be performed simultaneously with any one of step S31 to step S35, and fig. 3 is only a given example and does not represent that step S36 and step S37 must be performed after step S35.

it can be understood that, compared with the technical scheme shown in fig. 2, in this embodiment, the monitoring data is sent to the mobile terminal, so that the user can monitor the indoor and outdoor air conditions and the operating states of the intelligent devices through the mobile terminal, the user experience can be improved, and meanwhile, the user can quickly locate the fault when the intelligent devices cannot work normally.

In addition, due to individual differences, the control method for the intelligent device provided by the embodiment does not satisfy every user in terms of adjustment of the indoor air condition, and the user feeds back own requirements (for example, an expected wind speed value, an expected wind direction value and a temperature and humidity value) to the preset control parameter model through the mobile terminal according to monitoring data displayed on the mobile terminal, so that the preset parameter model corrects output control parameters, and comfort experience of the user can be improved.

Fig. 6 is a schematic block diagram illustrating a control apparatus 100 of an intelligent device according to another exemplary embodiment, and referring to fig. 6, the apparatus includes:

An obtaining module 101, configured to obtain environmental data;

A determining module 102, configured to determine a control parameter of an intelligent device according to the environment data, where the intelligent device is an intelligent device that is linked with each other;

And the control module 103 is used for performing linkage control on the intelligent equipment according to the control parameters.

according to the technical scheme, the control parameters of the intelligent equipment are determined through the acquired environment data, so that linkage control over the intelligent equipment is achieved.

Preferably, the apparatus is located in a linkage controlled smart device, or in a remote server, or in a central processor of a smart device.

preferably, the determination model 102 is specifically configured to:

When the intelligent equipment is determined to need linkage, a preset control parameter determination model is adopted, the control parameters of the intelligent equipment are determined according to the environment data, and the input and the output of the control parameter determination model are the environment data and the control parameters respectively.

Preferably, the determination model 102 is further configured to:

and judging whether the intelligent equipment needs to be linked or not according to the environment data by adopting a preset judgment model.

Preferably, the control parameter determination model is an artificial neural network model.

preferably, the decision model is a decision tree model.

It can be understood that the air quality problem exists due to the windowing ventilation, the model is determined through the preset control parameters, such as an artificial neural network model, a plurality of linked intelligent devices work together efficiently, energy-saving and orderly, the use efficiency of the intelligent devices is improved, and meanwhile, the intelligent decision making is realized for users, for example, when the intelligent devices are used, how large the power is opened and the like.

it can be understood that, when the control parameter is obtained to control the window by determining a model, such as an artificial neural network model, by a preset control parameter, a deviation occurs. If the weather conditions are storm, severe haze and the like, the windowing cannot be performed in the weather conditions, but because the artificial neural network model has randomness, the output result is likely to be small-amplitude windowing, but the output result is unsafe. The invention provides a control algorithm of a decision tree model and an artificial neural network model, which is characterized in that extreme weather conditions are screened out through the decision tree model, and then corresponding environment data is input into the artificial neural network model to obtain control parameters of intelligent equipment, so that the condition that the artificial neural network model outputs windowing control parameters to control windowing under the extreme weather conditions is avoided, and the reliability and the safety of a system are greatly improved.

Preferably, referring to fig. 7, the control apparatus 100 of the intelligent device further includes:

An obtaining module 104, configured to obtain monitoring data, and send the monitoring data to a mobile terminal, so as to display the monitoring data on the mobile terminal, where the monitoring data includes at least one of the following items: environmental data, control parameters and running state information of the intelligent equipment after being controlled.

it can be understood that, the monitoring data is sent to the mobile terminal, so that the user can monitor the indoor and outdoor air conditions and the running states of the intelligent devices through the mobile terminal, the user experience can be improved, and meanwhile, the user can rapidly position faults when the intelligent devices cannot work normally.

preferably, the control apparatus 100 of the smart device further includes:

The receiving module 105 is configured to receive a control instruction sent by the mobile terminal, where the control instruction is generated by the mobile terminal according to a control operation of a user, and the control operation is generated by the user according to monitoring data displayed on the mobile terminal.

It can be understood that, due to individual differences, the control method of the intelligent device provided by the invention is not satisfactory for each user in terms of adjustment of the indoor air condition, and the user feeds back own requirements (such as an expected wind speed value, an expected wind direction value and a temperature and humidity value) to the preset control parameter model through the mobile terminal according to the monitoring data displayed on the mobile terminal, so that the preset parameter model corrects the output control parameters, and the comfort experience of the user can be improved.

Preferably, the smart device comprises at least: air conditioners and windows.

compared with a simple window or air conditioner control mode in the related technology, the air conditioner and window linkage control mode provided by the invention enriches the indoor air conditioning means, can improve the comfort experience of a user, can reduce the energy consumption brought by the air conditioner, and reduces the occurrence of cold and air conditioner diseases caused by long-time air blowing of the user.

preferably, the smart device further comprises at least one of:

Fresh air machine, air purifier, dehumidifier, humidifier.

it can be understood that if windowing, there will be air quality problem certainly, so if on the basis of air conditioner and window control, in addition to the coordinated control to other air condition adjusting device, can further improve user's comfort level and experience. For example: under the windy condition of outdoor cloudy day, can control and open the window and cool down the ventilation, but this moment if there is dust, pollen, catkin or air quality not good in the air, if can the simultaneous control air purifier open, can realize the accurate regulation to the indoor air situation, further improve user's comfort level and experience.

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 the terms "first," "second," and the like in the description of the present invention 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 invention, 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 alternate implementations are included within the scope of the preferred embodiment of the present invention 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 invention.

It should be understood that portions of the present invention 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 invention 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, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean 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 invention. 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 invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (11)

1. a control method of an intelligent device is characterized by comprising the following steps:
Acquiring environmental data;
Determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is mutually linked intelligent equipment;
And performing linkage control on the intelligent equipment according to the control parameters.
2. The method of claim 1, wherein determining control parameters for the smart device based on the environmental data comprises:
When the intelligent equipment is determined to need linkage, a preset control parameter determination model is adopted, the control parameters of the intelligent equipment are determined according to the environment data, and the input and the output of the control parameter determination model are the environment data and the control parameters respectively.
3. The method of claim 2, further comprising:
And judging whether the intelligent equipment needs to be linked or not according to the environment data by adopting a preset judgment model.
4. The method of claim 2, wherein the control parameter determination model is an artificial neural network model.
5. The method of claim 3, wherein the decision model is a decision tree model.
6. The method of claim 1, further comprising:
Acquiring monitoring data, and sending the monitoring data to a mobile terminal so as to display the monitoring data on the mobile terminal, wherein the monitoring data comprises at least one of the following items: environmental data, control parameters and running state information of the intelligent equipment after being controlled.
7. The method of claim 6, further comprising:
And receiving a control instruction sent by the mobile terminal, wherein the control instruction is generated by the mobile terminal according to the control operation of a user.
8. the method according to claim 1, characterized in that the smart device comprises at least: air conditioners and windows.
9. the method of claim 8, wherein the smart device further comprises at least one of:
fresh air machine, air purifier, dehumidifier, humidifier.
10. A control device of an intelligent device, comprising:
the acquisition module is used for acquiring environmental data;
The determining module is used for determining control parameters of intelligent equipment according to the environment data, wherein the intelligent equipment is a plurality of intelligent equipment which are mutually linked;
and the control module is used for carrying out linkage control on the intelligent equipment according to the control parameters.
11. The apparatus of claim 10, wherein the apparatus is located in a co-operated smart device, or in a remote server, or in a central processor of a smart device.
CN201810564690.1A 2018-06-04 2018-06-04 Control method and device of intelligent equipment CN110553354A (en)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201594190U (en) * 2009-12-31 2010-09-29 青岛海尔软件有限公司 Intelligent home system
CN104486175A (en) * 2014-12-11 2015-04-01 乐视致新电子科技(天津)有限公司 Intelligent household equipment linkage control method and router
CN104865943A (en) * 2015-05-29 2015-08-26 四川长虹电器股份有限公司 Entrance guard system based linked control method for intelligent household electrical appliance
CN107368044A (en) * 2016-10-13 2017-11-21 宋显峰 A kind of real-time control method of intelligent electric appliance, system
JP2018071834A (en) * 2016-10-26 2018-05-10 三菱電機株式会社 Indoor environment control system, humidifier, and air conditioner

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN201594190U (en) * 2009-12-31 2010-09-29 青岛海尔软件有限公司 Intelligent home system
CN104486175A (en) * 2014-12-11 2015-04-01 乐视致新电子科技(天津)有限公司 Intelligent household equipment linkage control method and router
CN104865943A (en) * 2015-05-29 2015-08-26 四川长虹电器股份有限公司 Entrance guard system based linked control method for intelligent household electrical appliance
CN107368044A (en) * 2016-10-13 2017-11-21 宋显峰 A kind of real-time control method of intelligent electric appliance, system
JP2018071834A (en) * 2016-10-26 2018-05-10 三菱電機株式会社 Indoor environment control system, humidifier, and air conditioner

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