Scene control interaction method and intelligent interaction system

Abstract

The technical scheme of the invention provides an interaction control method for scene control, which comprises the following steps: setting at least one touch key on an intelligent panel, after triggering the touch key, obtaining interaction information of the triggered intelligent panel and a state value of a current fuzzy instruction of the intelligent panel, and generating a fuzzy instruction to be executed; and according to the fuzzy instruction to be executed, acquiring a scene target data set of the triggered intelligent panel and the triggered touch key, and determining a target scene triggered this time. According to the technical scheme, the problems that interaction is complex, the number of scenes is insufficient, after-sale is troublesome, and user experience is poor are solved.

Description

Technical Field

[0001] The present invention relates to the field of human-computer interaction, and in particular to an interactive method and an intelligent interactive system for scene control. Background Art

[0002] With the continuous development of Internet of Things technology, smart home has become an indispensable part of people's lives, bringing more convenient and comfortable experience to people's lives. With the rapid growth of the categories and quantity of smart home devices, the mainstream products in the market have transitioned from the initial smart single products to the current whole-house smart products. In the whole-house smart system, scene control plays a key role. Through scene control, multiple devices can be linked with one click to meet the needs of different usage occasions.

[0003] The interactive control methods of scene control are generally physical buttons, touch buttons, multi-touch display screens, voice control, and App control. When there are a large number of scenes, finding the scene to be controlled currently requires considering the execution actions corresponding to the scene, which is not only time-consuming but also may cause interaction errors and fail to achieve the expected results. In view of the above situation, how to solve the problems of complex interaction, insufficient number of scenes, troublesome after-sales service, and poor user experience has become one of the current problems that need to be solved urgently. Summary of the invention

[0004] The present invention provides an interactive control method for scene control, comprising:

[0005] At least one touch button is set on the smart panel, and the area and shape of the touch button are determined based on the smart panel; after the touch button is triggered, the interaction information of the triggered smart panel and the state value of the current fuzzy instruction of the smart panel are obtained, and the fuzzy instruction to be executed is generated; the interaction information includes one or a combination of triggering action type, operation distance, signal strength, coordinates, triggering area, triggering time, the number of triggered touch buttons, the number of signals, button codes, and button types; the fuzzy instruction to be executed includes the button code of the triggered touch button, the code of the triggered smart panel and the type of the fuzzy instruction to be executed; according to the fuzzy instruction to be executed, the scene target data set of the triggered smart panel and the triggered touch button is obtained to determine the target scene of this triggering.

[0006] Furthermore, when the smart panel is only set with one touch button, the target scene triggered and controlled by the touch button is a multi-target scene, and the trigger area reaches the preset trigger area and the trigger time of the triggered touch button reaches the trigger time threshold, then the target scene corresponding to the triggered touch button is triggered and controlled; otherwise, the touch scene fails.

[0007] Furthermore, it also includes setting at least one physical button on the smart panel, the physical button is independent of the touch button, and the area and shape of the physical button are determined based on the smart panel; setting the trigger time threshold and target scene of the physical button, and the target scene is triggered and controlled by the physical button; when the trigger button and the physical button are triggered at the same time, the trigger button triggers multiple target scenes, and the physical button triggers a single determined target scene.

[0008] Furthermore, when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is two or more, the triggering area of ​​each triggered trigger button reaches the preset triggering area and the triggering time of each triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is one, the triggering area of ​​the triggered trigger button reaches the preset triggering area and the triggering time of the triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; otherwise, the touch control scene fails.

[0009] Furthermore, the touch button is a multi-touch display screen, and the number of the triggered trigger buttons is the number of touch points of the multi-touch display screen.

[0010] Furthermore, the smart panel is provided with a gesture sensor, the gesture sensor is adapted to the touch button, and the interaction information and the trigger time are obtained by the gesture sensor.

[0011] Furthermore, according to the fuzzy instruction to be executed, the scene target data set of the triggered smart panel and the triggered touch button is obtained, and the target scene of this triggering is determined, including: according to one or a combination of the external information of this trigger, historical execution information and smart device information, the scene target data set is weighted calculated and sorted to determine the target scene of this triggering.

[0012] Furthermore, the external information includes one or a combination of the current time, the current environment and the current area; the historical execution information includes the execution record of the target scene within a preset time; and the smart device information includes the status information and / or quantity of the smart device.

[0013] Furthermore, the weighted calculation and sorting of the scene target data set to determine the target scene triggered this time includes: calculating the time score of each scene in the scene data set according to the external information and the effective time and effective environment of the target scene expected to be executed; calculating the frequency score of each scene in the scene data set according to the historical execution information, the smaller the deviation between the historical execution information and the external information, the higher the integral, the larger the deviation, the smaller the integral, and the higher the integral, the higher the frequency score of each scene in the scene data set; determining the smart device of the target scene expected to be executed according to the smart device information; weighting the time score and frequency score to obtain a relative superiority; and sorting the relative superiority from high to bottom to determine the target scene triggered this time.

[0014] The present invention also provides an intelligent interactive system adapted to the interactive control method of scene control as described above, comprising an intelligent panel provided with at least one touch button and at least one intelligent device for scene control by the intelligent panel.

[0015] The technical solution of the present invention solves the problems of complex interaction, insufficient number of scenes, troublesome after-sales service and poor user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the physical button panel;

[0017] Figure 2 It is a schematic diagram of the touch button panel;

[0018] Figure 3 is a schematic diagram of a multi-touch display screen;

[0019] Figure 4 It is an implementation method of applying a human-computer interaction method based on touch and gesture to a smart panel with a single touch button;

[0020] Figure 5 It is the first implementation method of applying the human-computer interaction method based on touch and gesture to a smart panel with multiple touch buttons;

[0021] Figure 6 It is a second implementation method of applying the human-computer interaction method based on touch and gesture to a smart panel with multiple touch buttons;

[0022] Figure 7 It is the third implementation method of applying the human-computer interaction method based on touch and gesture to the smart panel with multi-touch buttons;

[0023] Figure 8 It is the fourth implementation method of applying the human-computer interaction method based on touch and gesture to the smart panel with multi-touch buttons;

[0024] Fig. 9 It is an implementation method of applying a human-computer interaction method based on touch and gesture to a smart panel that combines touch buttons and physical buttons;

[0025] Fig.10 It is the first implementation method of human-computer interaction method based on touch and gesture applied to multi-touch display intelligent panel;

[0026] Fig.11 The second implementation method of the human-computer interaction method based on touch and gesture is applied to the multi-touch display screen smart panel

[0027] Fig.12 This is an embodiment of the human-computer interaction method based on touch and gesture provided by the present invention applied to a smart panel with a gesture sensor;

[0028] Fig.13 It is an embodiment of the multi-objective fuzzy optimization system provided by the present invention;

[0029] Fig.14 It is another embodiment of the multi-objective fuzzy optimization system provided by the present invention;

[0030] Fig.15 It is a schematic diagram of a scenario in which the multi-objective fuzzy optimization algorithm provided by the present invention calculates the optimal membership degree;

[0031] Fig.16 It is a schematic diagram of scene control of a multi-objective fuzzy optimization system for intelligent host calculation provided by the present invention;

[0032] Fig.17 It is a schematic diagram of scene control of a multi-objective fuzzy optimization system for intelligent panel calculation provided by the present invention;

[0033] Fig.18 The present invention provides a schematic diagram of an interactive control method for scene control. DETAILED DESCRIPTION

[0034] There are three ways to implement scene control: centralized, distributed, and hybrid. The centralized method is to store scene information in the control terminal or central control host. After the scene is triggered, the control terminal or master control host reads the scene parameters and then sends the executed action to each device participating in the scene. The advantages of the centralized method are simple protocol, powerful and flexible functions, and fast configuration; the disadvantages are that when there are a large number of devices, the bandwidth of the communication network is greatly limited, the reliability is low, and the synchronization of the execution action is not good. The distributed method is to store the scene information in each device participating in the scene. The control terminal only stores the scene number. The scene number is broadcasted during control. After the device receives the scene number, it reads the locally stored scene information and executes the action by itself. The advantages of the distributed method are high reliability and good synchronization of the execution action; the disadvantages are complex protocols, relatively single functions, and a time-consuming configuration process. The hybrid method is to use a combination of centralized and distributed methods. The scene data is stored in the execution device and the central control host at the same time. It has powerful functions, good synchronization, and high reliability.

[0035] The interactive control methods of scene control are generally physical buttons, touch buttons, multi-touch screens, voice control, and App control. Various control terminals control the devices in the whole house by sending scene control instructions (scene numbers). Figure 1 As shown in the figure, the physical button panel is generally equipped with 1 to 8 physical buttons, each of which can be bound to a scene. When in use, click a preset button to trigger the corresponding scene. Figure 2 As shown in the figure, the touch button panel is generally equipped with 1 to 4 buttons, each of which can be bound to a scene. When in use, the corresponding scene is triggered by touching a preset button. Figure 3 As shown, the screen size of the multi-touch display is generally between 4 and 10 inches. Each scene will be set with an icon and name. Generally, there is no limit on the number of scenes. However, due to the limited screen area, a single screen cannot display all the scenes. You need to turn the page to display them completely. When using, touch the icon of a scene to trigger the corresponding scene.

[0036] Ordinary smart panels, mass-produced physical buttons, touch buttons without engraving, make it difficult for consumers to find the scene they want to control. Although the multi-touch display has icons and text, due to the limitation of screen size, it is necessary to turn pages many times to find the scene, which is troublesome to operate. When there are many scenes, it takes time to think about what action to execute when finding the scene you want to control. The interaction does not achieve the expected effect, and it requires a high learning cost, which is not friendly to the elderly and children.

[0037] For panels with physical buttons and touch buttons, the number of scenes that can be controlled is limited due to the number of buttons, and cannot fully meet the control needs of consumers. With the popularization of the concept of healthy lighting, consumers not only pay attention to the functionality of lighting products, but also pay more attention to the impact of lighting on human physical and mental health, and need to create a full-spectrum, all-weather, continuous and dynamically changing light environment. The demand for healthy lighting also requires a sufficient number of scenes to meet the light environment requirements at different times. Ordinary smart panels obviously cannot support so many scenes.

[0038] Due to the high technical threshold of equipment configuration, consumers generally cannot change the parameters of the smart panel by themselves after the whole-house smart project is delivered, and professional debugging engineers are required to make the changes. If consumers have changes in their needs during use and want to revise the control targets of the already configured smart panel, they must find an after-sales debugging engineer to assist, and the service cost is relatively high.

[0039] like Fig.18 The present invention provides an interactive control method for scene control, comprising:

[0040] S1, setting at least one touch button on the smart panel, wherein the area and shape of the touch button are determined based on the smart panel (in a specific implementation, the area and shape of the touch button shall not be larger than the panel at most, and shall not affect touch usage at least);

[0041] S2, after the touch button is triggered, the interaction information of the triggered smart panel and the state value of the current fuzzy instruction of the smart panel are obtained, and the fuzzy instruction to be executed is generated; the interaction information includes one or a combination of the triggering action type, operation distance, signal strength, coordinates, triggering area, triggering time, the number of the triggered touch buttons, the number of signals, key codes, and key types; the fuzzy instruction to be executed includes the key code of the triggered touch button, the code of the triggered smart panel and the type of the fuzzy instruction to be executed;

[0042] S3, according to the fuzzy instruction to be executed, obtaining the scene target data set of the triggered smart panel and the triggered touch button, and determining the target scene of this triggering.

[0043] In a specific implementation, at least one touch button is set on the smart panel, and the area and shape of the touch button are determined based on the smart panel; the smart panel needs to judge the interaction behavior between the user and the smart panel (in the current technical solution, the panel is mainly touched by a single button, and the touch of multiple buttons is not combined for judgment and control), and needs to judge: the trigger action type (for example, a press signal or a release signal, a touch or a leave, a gesture exists or disappears), the operation distance (for example, a gesture operation, how far the hand is from the panel, or whether the person is standing within one meter of the panel), the signal strength (for example, a vibration sensor, detecting a hand tapping the panel). The trigger area, trigger time, number of triggered buttons or signals, corresponding button ID (such as buttons 1, 2, 3, 4), button type (such as touch button, physical button, gesture sensor), combined with the current fuzzy command state value of the smart panel (generally the most commonly used A / B state switching can realize the first touch to turn on the light and the second touch to turn off the light. It can also be set to only A, which is only responsible for turning on the light. There can also be more states, A / B / C / D, which are distinguished according to the touch time threshold. For example, short press is A / B and long press is C / D).

[0044] A fuzzy instruction is generated according to the rules (including the current smart panel ID, the corresponding button ID, and the corresponding fuzzy instruction type (for example, the fuzzy instruction type may be A and B, and the fuzzy instruction state value is a value of the current record, such as A. The instruction can also add additional content), and sent out. After the host receives the fuzzy instruction (one solution is for the host to make the judgment, and the other solution is for the smart panel to make the judgment by itself without sending it to the host), according to the fuzzy instruction triggered this time, the scene target data set of the corresponding smart panel and button is obtained, and the scene control instruction triggered this time is calculated through the rules and sent out.

[0045] In the specific implementation, according to the fuzzy command triggered this time, the scene target data set of the corresponding smart panel and button is obtained, and the scene control command triggered this time is calculated through the rules and sent out. If the scene target data has only one scene, there is no need to run the rules to calculate, and the scene corresponding to the fuzzy command is directly obtained and sent out.

[0046] Among them, when the smart panel is only set with one touch button (one touch button can be set with one target scene or multiple target scenes), the target scene triggered and controlled by the touch button is a multi-target scene. When the trigger area reaches the preset trigger area and the trigger time of the triggered touch button reaches the trigger time threshold, the target scene corresponding to the triggered touch button is triggered and controlled; otherwise, the touch scene fails.

[0047] It also includes setting at least one physical button on the smart panel, the physical button is independent of the touch button, and the area and shape of the physical button are determined based on the smart panel; setting a trigger time threshold and a target scene for the physical button, and the target scene is triggered and controlled by the physical button; when the trigger button and the physical button are triggered at the same time, the trigger button triggers multiple target scenes, and the physical button triggers a single determined target scene.

[0048] When the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is two or more, the triggering area of ​​each triggered trigger button reaches the preset triggering area and the triggering time of each triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is one, the triggering area of ​​the triggered trigger button reaches the preset triggering area and the triggering time of the triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; otherwise the touch control scene fails.

[0049] The touch button is a multi-touch display screen, and the number of the triggered trigger buttons is the number of touch points of the multi-touch display screen. The smart panel is provided with a gesture sensor, the gesture sensor is adapted to the touch button, and the interaction information and the trigger time are obtained by the gesture sensor.

[0050] The method of obtaining the scene target data set of the triggered smart panel and the triggered touch button according to the fuzzy instruction to be executed, and determining the target scene of this triggering includes: parsing the instruction type in the fuzzy instruction triggered this time and the scene target data set controlled by the instruction type according to one or a combination of the external information, historical execution information and smart device information of this triggering, performing weighted calculation and sorting on the scene target data set controlled by the instruction type to determine the target scene of this triggering.

[0051] The weighted calculation and sorting of the scene target data set corresponding to the control of the instruction type to determine the target scene triggered this time includes: calculating the time score of each scene in the scene data set according to the external information and the effective time and effective environment of the target scene expected to be executed; calculating the frequency score of each scene in the scene data set according to the historical execution information, the smaller the deviation between the historical execution information and the external information, the higher the integral, the larger the deviation, the smaller the integral, and the higher the integral, the higher the frequency score of each scene in the scene data set; determining the smart device of the target scene expected to be executed according to the smart device information; weighting the time score and frequency score to obtain a relative superiority; and sorting the relative superiority from high to low to determine the target scene triggered this time.

[0052] The external information includes one or a combination of the current time, the current environment and the current area; the historical execution information includes the execution record of the target scene within a preset time; the smart device information includes the status information and / or quantity of the smart device.

[0053] The present invention also provides an intelligent interactive system, comprising an intelligent panel provided with at least one touch button and at least one intelligent device for scene control by the intelligent panel.

[0054] like Figure 4 As shown, when the human-computer interaction method based on touch and gesture is applied to a smart panel with a single touch button, the detailed description is as follows:

[0055] This type of smart panel must have a single touch button; the area and shape of the touch button of this type of smart panel are not restricted; a single finger or a larger trigger area can trigger multi-target fuzzy control of the scene; the touch operation needs to exceed the minimum touch time threshold, otherwise the scene control will not be triggered to avoid accidental touches.

[0056] Among them, when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is two or more, the triggering area of ​​each triggered trigger button reaches the preset triggering area and the triggering time of each triggered touch button reaches the triggering time threshold, then the target scene corresponding to the triggered touch button is triggered and controlled; when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is one, the triggering area of ​​the triggered trigger button reaches the preset triggering area and the triggering time of the triggered touch button reaches the triggering time threshold, then the target scene corresponding to the triggered touch button is triggered and controlled; otherwise, the touch scene fails.

[0057] like Figure 5 , Figure 6 , Figure 7 , Figure 8 As shown, when the human-computer interaction method based on touch and gesture is applied to a smart panel with multi-touch buttons, the detailed description is as follows:

[0058] This type of smart panel needs to have multiple touch buttons; the area and shape of the touch buttons of this type of smart panel are not restricted; when touching, when the palm or fingers touch 2 or more buttons at the same time, the multi-target fuzzy control of the scene can be triggered; when touching, when the palm or fingers only touch 1 button, the multi-target fuzzy control of the scene will not be triggered, and only the scene control of a single determined target can be triggered; the operation of touching multiple buttons at the same time needs to exceed the minimum touch time threshold, otherwise the scene control will not be triggered to avoid accidental touch; the figure takes a smart panel with four touch buttons as an example, but it can actually support touch button smart panels with more than or equal to 2 buttons.

[0059] Among them, the technical solution of the present invention also includes setting at least one physical button on the smart panel, the physical button is independent of the touch button, and the area and shape of the physical button are determined based on the smart panel; setting the trigger time threshold and target scene of the physical button, and the target scene is triggered and controlled by the physical button; when the trigger button and the physical button are triggered at the same time, the trigger button triggers multiple target scenes, and the physical button triggers a single determined target scene.

[0060] like Fig. 9 As shown, when the human-computer interaction method based on touch and gesture is applied to a smart panel that combines touch buttons and physical buttons, the detailed description is as follows:

[0061] This type of smart panel needs to have a single touch button plus several physical buttons; the area and shape of the touch and physical buttons of this type of smart panel are unlimited; a single finger or a larger trigger area can trigger the multi-target fuzzy control of the scene; only the touch button can trigger the multi-target fuzzy control of the scene, and the physical button can only trigger the scene control of a single determined target; the touch operation needs to exceed the minimum touch time threshold, otherwise the scene control will not be triggered to avoid accidental touches. Wherein, when the touch button is a multi-touch display screen, the number of the triggered trigger buttons is the number of touch points of the multi-touch display screen.

[0062] like Fig.10 , Fig.11 As shown, when the human-computer interaction method based on touch and gesture is applied to a multi-touch display smart panel, the detailed description is as follows:

[0063] This type of smart panel needs to have a display screen that supports multi-touch; the area and shape of the display screen of this type of smart panel are unlimited; when touching, the palm or two or more fingers touch the screen at the same time, and the multi-touch display screen senses multiple contact points, which can trigger the multi-target fuzzy control of the scene; when touching, only one finger touches the screen, and the multi-touch display screen senses one contact point, which does not trigger the multi-target fuzzy control of the scene, and can only trigger the scene control of a single determined target; the operation of touching multiple buttons at the same time needs to exceed the minimum touch time threshold, otherwise the scene control will not be triggered to avoid accidental touches. Wherein, when the smart panel is provided with a gesture sensor, the gesture sensor is adapted to the touch button, and the interaction information and the trigger time are obtained by the gesture sensor.

[0064] like Fig.12 As shown, when the human-computer interaction method based on touch and gesture is applied to a smart panel with a gesture sensor, the detailed description is as follows:

[0065] This type of smart panel must have gesture sensors, including but not limited to infrared sensors, ultrasonic sensors, and millimeter wave sensors; the sensors of this type of smart panel must be able to sense the distance of the approaching palm; the sensors of this type of smart panel must be able to set the sensitivity of the sensing and adjust the distance and sensing area of ​​the sensing trigger; the approaching and staying palm can trigger the multi-target fuzzy control of the scene; the approaching and shaking palm can trigger the multi-target fuzzy control of the scene; the operation of the approaching palm needs to exceed the minimum sensing time threshold, otherwise the scene control will not be triggered to avoid accidental touch.

[0066] like Fig.15 As shown, the specific process S10 of calculating the optimal membership scenario by the multi-objective fuzzy optimization algorithm is described in detail as follows:

[0067] Parse the fuzzy control instruction and obtain the ID of the smart panel that triggers the fuzzy control; obtain the scene target data set corresponding to the smart panel; parse the fuzzy control instruction and obtain the instruction type of the fuzzy control; if it is determined to be instruction A, filter the scene target set data obtained in the previous step and save the scene target set data related to instruction A; if it is determined to be instruction B, filter the scene target set data obtained in the previous step and save the scene target set data related to instruction B;

[0068] Get the current time, and calculate the time score of each scene in the scene data set according to the effective time parameters of each scene. If the current time is within the effective time range, the score is the highest score of 10 points; if the current time is not within the effective time range, the score is calculated based on the deviation from the effective time. The smaller the deviation, the higher the score, and the larger the deviation, the lower the score. When the deviation reaches 6 hours, the score is 0 points;

[0069] Get local weather data, and calculate the weather score of each scene in the scene data set according to the weather parameters applicable to the scene. If the current weather meets the applicable weather parameters, the score is the highest score of 10 points; if the current weather does not meet the applicable weather parameters, the score is calculated based on the deviation between the weather and temperature. The smaller the deviation, the higher the score, and the larger the deviation, the lower the score. When the weather does not meet the requirements and the temperature deviation reaches 15 degrees Celsius, the score is 0 points;

[0070] Get the execution records of each scenario within 3 days, and calculate the 3-day frequency score of each scenario in the scenario data set. Calculate the points based on the deviation between the execution record time and the current time. The smaller the deviation, the higher the points, and the larger the deviation, the lower the points. If a scenario has an execution record within plus or minus half an hour of the current time, each execution record will accumulate 12 points. Points are calculated at one level every half an hour, and no points are awarded outside of plus or minus 6 hours. Sort the scenes in the scenario data set by points. The first-ranked scene will receive the highest score of 10 points, and the score will decrease by 1 point for each lower ranking.

[0071] Get the execution records of each scenario within one month, and calculate the monthly frequency score of each scenario in the scenario data set. Calculate the points based on the deviation between the execution record time and the current time. The smaller the deviation, the higher the points, and the larger the deviation, the lower the points. If a scenario has an execution record within plus or minus half an hour of the current time, each execution record will accumulate 12 points. Points are calculated in one gear every half hour, and there are no points outside of plus or minus 6 hours. Sort the scenes in the scenario data set by points. The first-ranked scene will receive the highest score of 10 points, and the score will decrease by 1 point for each lower ranking.

[0072] Get the historical execution records of each scenario, and calculate the historical frequency score of each scenario in the scenario data set. Calculate points based on the deviation between the execution record time and the current time. The smaller the deviation, the higher the points, and the larger the deviation, the lower the points. If a scenario has an execution record within plus or minus half an hour of the current time, each execution record will score 12 points. Points are calculated in one gear every half hour, and there are no points outside of plus or minus 6 hours. Sort the scenes in the scenario data set by points. The first-ranked scene is scored with the highest score of 10 points, and the score decreases by 1 point for each lower ranking.

[0073] In order to improve the calculation speed of the above three types of frequency scores, you can pre-calculate the scores and store the score sets at a node every 15 minutes during the idle time period. You can then directly search for the scores of each scenario closest to the node based on time to avoid time-consuming calculations that affect user experience;

[0074] Read the scoring weights of the multi-objective fuzzy optimization algorithm, multiply each score by the weight, and get the final weighted score. The scoring weights can be dynamically adjusted according to the actual project needs. The initial parameters can be set to: time scoring weight (0.25), weather scoring weight (0.15), 3-day frequency scoring weight (0.25), monthly frequency scoring weight (0.2), historical frequency scoring weight (0.15);

[0075] The target scene set and the weighted scoring parameters of each scene are used to construct a scoring value matrix as follows:

[0076]

[0077] (i=1,2,3,4,5;j=1,2,…,n)

[0078] In the matrix X, x ij represents the i-th weighted score value of the j-th scene.

[0079] Since the basic parameters of each score are different, in order to facilitate the evaluation of each scene, we must first normalize the weighted score values ​​in the matrix X, that is, find the relative superiority of each weighted score value. When the weighted score value is larger, it means better, and the solution formula for the relative superiority is:

[0080]

[0081] After solving each weighted score in the score matrix X, the relative superiority matrix can be obtained:

[0082]

[0083] The scores of good and bad scenes are expressed as follows relative to the good and bad attribute vectors:

[0084] G = (g1, g2, g3, g4, g5) T =(1,1,1,1,1) T

[0085] B=(b1,b2,b3,b4,b5) T =(0,0,0,0,0) T

[0086] The formula of weighted distance can be expressed as:

[0087]

[0088] Taking p = 2, the membership of each scene relative to the ideal scene can be expressed as:

[0089]

[0090] According to the above algorithm, the relative membership of each scene is calculated; the membership of each scene is sorted to obtain the scene with the optimal membership.

[0091] The specific embodiments are as follows:

[0092] At 7 o'clock in the evening, when the user returns home from get off work normally and wants to turn on the light, he touches the smart panel to trigger the fuzzy interaction. The smart panel issues a command to turn on the light (command A). After receiving the command, the smart host starts to calculate which scene control is the most appropriate at this time. Inside the smart host, 20 scenes that can be triggered by the command to turn on the light have been set. After obtaining the data of these 20 scenes, the effective time of each scene is first analyzed. For example, there are bright scenes and warm light scenes, which are effective from 7 to 9 o'clock, so the time scores of these two scenes are the highest; then analyze the current weather conditions. For example, in winter, the temperature is below zero, then the warm light scene will give people a warm feeling, and the bright scene will give people a cool feeling. The weather score is high for the warm light scene; then analyze the scene execution of users within three days, and find that around 7 o'clock, the warm light scene is executed, so the warm light scene score is high; then analyze the usage for one month, find the scenes around 7 o'clock in one month, and score them; then analyze the historical records inside the smart host and score them; finally, the scene with the best membership is calculated as the warm light scene. The smart host then sends warm light scene instructions to all devices, and the 20 lights in the house are turned on at the same time, with a brightness of 80% and a color temperature of 3500K.

[0093] At 24:00 in the evening, when the user needs to go to bed, he touches the smart panel to trigger the fuzzy interaction. The smart panel issues a command to turn off the lights (command B). The smart host has set a scene that can be triggered by the command to turn off the lights, the sleep scene. Since there is only one scene, the scene with the best membership must be the sleep scene. The smart host sends the command of the sleep scene to all devices, and all 20 lights in the house are turned off.

[0094] At 23:00 the next night, when the user returns home after working overtime and wants to turn on the light, he touches the smart panel to trigger the fuzzy interaction. The smart panel issues a command to turn on the light (command A). After receiving the command, the smart host starts to calculate which scene control is the most appropriate at this time. Inside the smart host, 20 scenes that can be triggered by the command to turn on the light have been set. After obtaining the data of these 20 scenes, the effective time of each scene is first analyzed. For example, if there is a rest scene, the effective time is 21:00-24:00, then the time score of this scene is the highest; then the current weather conditions are analyzed. For example, if it is winter and the temperature is below zero, then the warm light scene will give people a warm feeling, and the weather score is high for the warm light scene; then the scene execution of the user within three days is analyzed, and it is found that there is no execution record around 23:00; then the usage for one month is analyzed, and the scene around 23:00 in one month is found. There is a record of executing the rest scene once, so the rest scene has the highest score; then the historical records inside the smart host are analyzed and scored; finally, the scene with the best membership is calculated as the rest scene. The smart host then sends rest scene instructions to all devices, and the five lights in the house are turned on at the same time, with a brightness of 20% and a color temperature of 2700K.

[0095] like Fig.16 As shown, the specific process S20 of the scene control of the multi-objective fuzzy optimization system calculated by the intelligent host is described in detail as follows:

[0096] The touch and gestures that meet the human-computer interaction regulations of the above five types of smart panels are used to operate the smart panel to trigger the fuzzy control event; the smart panel obtains the current AB instruction state stored in the local storage medium (the smart panel can be set to the AB instruction mode, and can issue both A / B instructions; it can also be set to the A instruction mode, and the A instruction is issued in any case); if it is determined that the current instruction is A, then the control instruction A is generated; if it is determined that the current instruction is B, then the control instruction B is generated;

[0097] The smart panel sends the control command generated in the previous step to the smart host through power line communication, wired communication or wireless communication. After receiving the command, the smart host parses the command, obtains the command content and reads the scene data set stored in the local computer to calculate the score of each scene.

[0098] The intelligent host inputs the scene data set and the score into the multi-objective fuzzy optimization algorithm to calculate the scene with the optimal membership degree; the intelligent host broadcasts and sends the scene command through power line communication, wired communication and wireless communication; after all the intelligent panels receive the scene command, they refresh the AB command status according to the locally stored scene data and store it in the local storage medium; after all the controlled devices receive the scene command, they automatically execute the scene action according to the locally stored scene data; the process of this scene control is completed.

[0099] like Fig.17 As shown, the specific process S30 of scene control of the multi-objective fuzzy optimization system calculated by the smart panel is described in detail as follows:

[0100] The touch and gestures that meet the human-computer interaction regulations of the above five types of smart panels are used to operate the smart panel to trigger a fuzzy control event; the smart panel obtains the current AB instruction state stored in the local storage medium; if it is determined that the current instruction is A, then a control instruction A is generated; if it is determined that the current instruction is B, then a control instruction B is generated; the smart panel reads the scene data set stored in the local according to the instruction content and calculates the score of each scene; the smart panel inputs the scene data set and the score into the multi-objective fuzzy optimization algorithm to calculate the scene with the optimal membership degree;

[0101] The smart panel broadcasts the scene command through power line communication, wired communication or wireless communication; after receiving the scene command, all smart panels refresh the AB command status according to the locally stored scene data and store it in the local storage medium; after receiving the scene command, all controlled devices automatically execute the scene action according to the locally stored scene data; the process of this scene control is completed.

[0102] Multi-objective fuzzy optimization system modules such as Fig.13 (The intelligent panel and the controlled device in the multi-objective fuzzy optimization system 100 communicate via power line communication or bus communication) Fig.14 (Smart panels and controlled devices in the multi-objective fuzzy optimization system 200, through wireless communication) as shown, include a smart host, several smart panels (the figure takes two smart panels as an example, and can actually support several smart panels), and several controlled devices (the figure takes four controlled devices as an example, and can actually support several controlled devices).

[0103] like Fig.13 , Fig.14 As shown, the various devices in the system can communicate with each other through power line communication, bus communication or wireless communication. A single communication method can be used, or multiple communication methods can be mixed. For example, the smart panel uses wireless communication, the controlled device uses power line communication, and the smart host supports both power line communication and wireless communication.

[0104] The intelligent host is a core module that integrates control, management, computing and communication functions. In the system, the communication module is used to perform protocol conversion and communicate with sub-devices. It can support multiple communication methods and protocols, has scene configuration management and control functions, multi-objective fuzzy optimization functions, networking control, network maintenance and management functions, control program logic configuration and control functions, system equipment status monitoring functions; and has the ability to synchronously transmit system instructions to the cloud through the network.

[0105] Smart panels are devices that trigger scene control through touch and gestures. The system supports multiple types of smart panels, including but not limited to single-touch button panels, multi-touch button panels, touch button and physical button combination panels, multi-touch display panels, infrared sensor panels, ultrasonic sensor panels, millimeter wave sensor panels, etc. The system communicates through communication modules and can support multiple communication methods and protocols. Depending on the performance of the processor, the smart panel can choose whether to have a built-in multi-target fuzzy optimization function. Smart panels that do not have this function built-in only need to store the status of the AB instructions and the scene ID data triggered by the AB instructions. Panels with this function built-in need to store the status of the AB instructions and the entire scene data set triggered by the AB instructions, and need to monitor the scene control data of the communication network for revising system parameters and executing algorithms.

[0106] The controlled device is the device that receives scene instructions and performs actions. The system supports multiple types of controlled devices, including but not limited to lighting equipment, sunshade equipment, HVAC, audio and video equipment, etc. The system communicates through the communication module and can support multiple communication methods and protocols. Different scene actions can be performed depending on the type of device. For example, lighting equipment can control the opening, brightness, color temperature and color of lamps by scenes; sunshade equipment can control the opening and closing of curtains.

[0107] The main technical problem solved by the present invention is to propose a human-computer interaction method based on touch and gesture and a multi-objective fuzzy optimization system, which can solve the complex problems of human-computer interaction of smart home scene panels and control terminals, reduce the learning cost of users, and improve usability; can increase the number of controllable target scenes on smart home scene panels and control terminals without increasing the number of buttons and screen size, and meet more and more scene control needs; can record the user's control behavior during the scene control process, adjust system parameters, and optimize the scene that better meets user needs, thereby reducing the number of debugging engineer services and reducing the cost of after-sales service.

Claims

1. An interactive control method for scene control, characterized in that: include: At least one touch button is provided on the smart panel, wherein the area and shape of the touch button are determined based on the smart panel; After the touch button is triggered, the interaction information of the triggered smart panel and the state value of the current fuzzy instruction of the smart panel are obtained, and the fuzzy instruction to be executed is generated; the interaction information includes one or a combination of the triggering action type, operation distance, signal strength, coordinates, triggering area, triggering time, the number of the triggered touch buttons, the number of signals, key codes, and key types; the fuzzy instruction to be executed includes the key code of the triggered touch button, the code of the triggered smart panel, and the type of the fuzzy instruction to be executed; According to the fuzzy instruction to be executed, the scene target data set of the triggered smart panel and the triggered touch button is obtained to determine the target scene of this triggering.

2. The interactive control method for scene control according to claim 1, characterized in that: When the smart panel is only set with one touch button, the target scene triggered and controlled by the touch button is a multi-target scene. When the trigger area reaches the preset trigger area and the trigger time of the triggered touch button reaches the trigger time threshold, the target scene corresponding to the triggered touch button is triggered and controlled; otherwise, the touch scene fails.

3. The interactive control method for scene control according to claim 2, characterized in that: It also includes setting at least one physical button on the smart panel, the physical button is independent of the touch button, and the area and shape of the physical button are determined based on the smart panel; setting a trigger time threshold and a target scene for the physical button, and the target scene is triggered and controlled by the physical button; when the trigger button and the physical button are triggered at the same time, the trigger button triggers multiple target scenes, and the physical button triggers a single determined target scene.

4. The interactive control method for scene control according to claim 1, characterized in that: When the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is two or more, the triggering area of ​​each triggered trigger button reaches the preset triggering area and the triggering time of each triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; when the smart panel is only provided with at least two touch buttons, if the number of triggered trigger buttons is one, the triggering area of ​​the triggered trigger button reaches the preset triggering area and the triggering time of the triggered touch button reaches the triggering time threshold, then the target scene triggered this time by the triggered touch button is triggered and controlled; otherwise the touch control scene fails.

5. The interactive control method for scene control according to claim 4, characterized in that: The touch button is a multi-touch display screen, and the number of the triggered trigger buttons is the number of touch points of the multi-touch display screen.

6. The interactive control method for scene control according to claim 1, characterized in that: The smart panel is provided with a gesture sensor, the gesture sensor is adapted to the touch button, and the interaction information and the trigger time are obtained by the gesture sensor.

7. The interactive control method for scene control according to claim 1, characterized in that: According to the fuzzy instruction to be executed, the scene target data set of the triggered smart panel and the triggered touch button is obtained, and the target scene of this triggering is determined, including: according to one or a combination of the external information of this trigger, historical execution information and smart device information, the scene target data set is weighted calculated and sorted to determine the target scene of this triggering.

8. The interactive control method for scene control according to claim 7, characterized in that: The external information includes one or a combination of the current time, the current environment and the current area; the historical execution information includes the execution record of the target scene within a preset time; the smart device information includes the status information and / or quantity of the smart device.

9. The interactive control method for scene control according to claim 7, characterized in that: The weighted calculation and sorting of the scene target data set to determine the target scene triggered this time includes respectively calculating the time score of each scene in the scene data set according to the external information and the effective time and effective environment of the expected target scene to be executed; According to the historical execution information, the frequency score of each scene in the scene data set is calculated respectively; the smaller the deviation between the historical execution information and the external information, the higher the score, and the larger the deviation, the smaller the score. The higher the score, the higher the frequency score of each scene in the scene data set; the smart device of the target scene to be executed is determined according to the smart device information; the time score and the frequency score are weighted to obtain a relative superiority; the relative superiority is sorted from high to low to determine the target scene triggered this time.

10. An intelligent interactive system adapted to the interactive control method of scene control according to any one of claims 1 to 9, characterized in that: It comprises a smart panel provided with at least one touch button and at least one smart device for scene control by the smart panel.

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