Active adjusting method and system based on intelligent door and window

Abstract

The invention is suitable for the technical field of intelligent control, and provides an active adjustment method and system based on an intelligent door and window, and the method comprises the steps: firstly obtaining outdoor environment feature set information and real-time indoor light intensity value information, then carrying out the retrieval of a historical environment feature database based on the outdoor environment feature set information, and obtaining a real-time indoor light intensity value; outdoor predicted light intensity value information is determined, and finally a shutter blind adjusting instruction is intelligently generated according to the outdoor predicted light intensity value information and the real-time indoor light intensity value information. According to the intelligent door and window, the shutter blind of the intelligent door and window can be automatically adjusted according to the specific change of the environment, more efficient indoor temperature control is achieved, the energy consumption of indoor equipment can be effectively reduced, the burden of an air conditioner and other electric appliances can be reduced, it can be ensured that the brightness of the window meets the preference of a user, the use experience of the user is remarkably improved, and the user experience is improved. Under different weather conditions, natural light can be utilized to the maximum extent, the requirement for artificial illumination is reduced, the overall energy consumption is further reduced, and environmental protection and sustainable development are promoted.

Description

Technical Field

[0001] This application relates to the technical field of intelligent control, and more specifically, to an active adjustment method and system for intelligent doors and windows. Background Technology

[0002] With the continuous advancement of dual-carbon policies, the construction industry is paying increasing attention to sustainable development, making the promotion of zero-carbon building construction particularly crucial. On the path to carbon reduction, green buildings are considered a primary solution, and doors and windows serve as an important component connecting green buildings to the outside world.

[0003] Currently, doors and windows typically rely on manual operation by users and lack a mechanism to automatically adjust according to specific environmental changes. This makes it difficult to effectively control indoor temperature, which is not conducive to reducing the energy consumption of indoor equipment and results in a poor user experience. Further improvements are needed. Summary of the Invention

[0004] Based on this, embodiments of this application provide an active adjustment method and system for smart doors and windows to solve the problem of poor user experience in the prior art.

[0005] In a first aspect, embodiments of this application provide an active adjustment method based on smart doors and windows, the method comprising:

[0006] Acquire outdoor environmental feature set information and real-time indoor light intensity value information;

[0007] Based on the outdoor environmental feature set information, the preset historical environmental feature database is searched to determine the outdoor predicted light intensity value information;

[0008] Based on the outdoor predicted light intensity information and the real-time indoor light intensity information, a Venetian blind adjustment command is generated, wherein the Venetian blind adjustment command is used to indicate the adjustment of the blade angle of the Venetian blind of the smart door and window.

[0009] Compared with existing technologies, the beneficial effects are as follows: The active adjustment method based on smart doors and windows provided in this application embodiment allows the terminal device to first acquire outdoor environmental feature set information and real-time indoor light intensity value information. Then, based on the outdoor environmental feature set information, it searches a preset historical environmental feature database to quickly determine the outdoor predicted light intensity value information. Finally, based on the outdoor predicted light intensity value information and real-time indoor light intensity value information, it effectively generates Venetian blind adjustment instructions, thereby realizing automatic adjustment of the Venetian blinds of smart doors and windows according to specific environmental changes. This not only effectively controls indoor temperature and reduces the energy consumption of indoor equipment, but also ensures that the brightness of the window meets user preferences, greatly improving the user experience and solving the problem of poor user experience to a certain extent.

[0010] Secondly, embodiments of this application provide an active adjustment system based on intelligent doors and windows, the system comprising:

[0011] Outdoor environment feature set information acquisition module: used to acquire outdoor environment feature set information and real-time indoor light intensity value information;

[0012] Outdoor predicted light intensity value determination module: used to search a preset historical environmental feature database based on the outdoor environmental feature set information to determine the outdoor predicted light intensity value information;

[0013] Venetian blind adjustment command generation module: used to generate Venetian blind adjustment commands based on the outdoor predicted light intensity value information and the real-time indoor light intensity value information, wherein the Venetian blind adjustment commands are used to indicate the adjustment of the blade angle of the Venetian blinds of the smart doors and windows.

[0014] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0016] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0018] Figure 1 This is a schematic flowchart of an embodiment of the active adjustment method provided in this application;

[0019] Figure 2 This is a flowchart illustrating step S200 in an active adjustment method provided in an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating the process after step S230 in an active adjustment method provided in an embodiment of this application;

[0021] Figure 4 This is a flowchart illustrating step S300 in an active adjustment method provided in an embodiment of this application;

[0022] Figure 5 This is a flowchart illustrating the process after step S300 in an active adjustment method provided in an embodiment of this application;

[0023] Figure 6 This is a block diagram of an active adjustment system provided in an embodiment of this application;

[0024] Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation

[0025] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0026] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0029] See also Figure 1 , Figure 1This is a flowchart illustrating the active adjustment method for smart doors and windows provided in this embodiment. In this embodiment, the executing entity of the active adjustment method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablets, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.

[0030] See also Figure 1 The active adjustment method provided in this application includes, but is not limited to, the following steps:

[0031] In S100, outdoor environmental feature set information and real-time indoor light intensity value information are acquired.

[0032] Specifically, the terminal device can first acquire outdoor environmental feature set information and real-time indoor light intensity value information. The real-time indoor light intensity value information is used to describe the real-time indoor light intensity value. The outdoor environmental feature set information includes the first recording time information, real-time air temperature information, real-time air humidity information, real-time outdoor light intensity value information, real-time outdoor wind speed information, and real-time atmospheric pressure information.

[0033] Specifically, the first recording time information is used to describe the recording time of the outdoor environmental feature set information; the real-time air temperature information is used to describe the real-time outdoor air temperature; the real-time air humidity information is used to describe the real-time outdoor air humidity; the real-time outdoor light intensity information is used to describe the real-time outdoor light intensity; the real-time outdoor wind speed information is used to describe the real-time outdoor wind speed; and the real-time atmospheric pressure information is used to describe the real-time outdoor atmospheric pressure.

[0034] Without loss of generality, the historical environmental feature database pre-stores multiple sets of historical environmental feature information. Each set of historical environmental feature information includes second recording time information, historical air temperature information, historical air humidity information, historical outdoor light intensity information, historical outdoor wind speed information, and historical atmospheric pressure information. Among them, the second recording time information is used to describe the recording time of the historical environmental feature set information; the historical air temperature information is used to describe the historical outdoor air temperature; the historical air humidity information is used to describe the historical outdoor air humidity; the historical outdoor light intensity information is used to describe the historical outdoor light intensity; the historical outdoor wind speed information is used to describe the historical outdoor wind speed; and the historical atmospheric pressure information is used to describe the historical outdoor atmospheric pressure.

[0035] In S200, based on the outdoor environment feature set information, the preset historical environment feature database is searched to determine the outdoor predicted light intensity value information.

[0036] Specifically, after the terminal device acquires outdoor environmental feature set information and real-time indoor light intensity value information, the terminal device can search the preset historical environmental feature database based on the outdoor environmental feature set information to effectively determine the outdoor predicted light intensity value information. The outdoor predicted light intensity value information is used to describe the outdoor predicted light intensity value in the next specified time period.

[0037] In some possible implementations, for efficient determination of outdoor predicted light intensity information, please refer to [link / reference needed]. Figure 2 Step S200 includes, but is not limited to, the following steps:

[0038] In S210, sampling time period information is generated based on the first recording time information and the preset time span value information.

[0039] Specifically, the terminal device can generate sampling time period information based on the first recorded time information and the preset time span value information. The sampling time period information describes a time period with the first recorded time information as the intermediate time, the time corresponding to the time span value information preceding the first recorded time information as the starting time, and the time corresponding to the time span value information following the first recorded time information as the ending time. The specific value of the time span value information can be customized by the user. For example, the preferred time span value information is 10 minutes.

[0040] In S220, based on the sampling time period information, the preset historical environmental feature database is searched to determine multiple preliminary environmental feature sets.

[0041] Specifically, after the terminal device generates the sampling time period information, the terminal device can search the preset historical environmental feature database based on the sampling time period information to quickly determine multiple preliminary environmental feature sets. The preliminary environmental feature sets are used to describe the historical environmental feature sets of the second recording time information within the sampling time period information.

[0042] In S230, based on the outdoor environmental feature set information, multiple preliminary environmental feature set information are retrieved to determine the target environmental feature set information.

[0043] Specifically, after the terminal device determines multiple preliminary environmental feature sets, it can retrieve these preliminary environmental feature sets based on the outdoor environmental feature set information. In the retrieval of these preliminary environmental feature sets, the target environmental feature set information is effectively determined. The target environmental feature set information describes historical environmental feature sets where historical air temperature information equals real-time air temperature information, historical air humidity information equals real-time air humidity information, historical outdoor light intensity information equals real-time outdoor light intensity information, historical outdoor wind speed information equals real-time outdoor wind speed information, and historical atmospheric pressure information equals real-time atmospheric pressure information.

[0044] In S240, based on the historical environmental feature database, the historical outdoor light intensity value information corresponding to the target environmental feature set information in the next recording time period is determined as the outdoor predicted light intensity value information.

[0045] Specifically, after the terminal device determines the target environment feature set information, the terminal device can determine the historical outdoor light intensity value information corresponding to the target environment feature set information in the next recording time period based on the historical environment feature database. The next recording time period is used to describe a time period with the end time of the sampling time period information as the start time and twice the time span value as the time length.

[0046] In some possible implementations, for more efficient determination of the target environment feature set information, please refer to [link / reference]. Figure 3 After step S230, the method further includes, but is not limited to, the following steps:

[0047] In S231, it is determined whether the number of target environment feature set information is one.

[0048] Specifically, the terminal device can determine whether the number of target environment feature set information is one.

[0049] In S232, if the number of target environment feature set information is one, then continue to execute the determination of the historical outdoor light intensity value information corresponding to the target environment feature set information in the next recording time period based on the historical environment feature database as the outdoor predicted light intensity value information.

[0050] Specifically, if the number of target environment feature set information is one, the terminal device can continue to execute the above step S240.

[0051] In S233, if there are multiple target environment feature set information, the selected environment feature set information is determined based on the first recording time information and the second recording time information.

[0052] Specifically, if there are multiple target environmental feature sets, the terminal device can effectively determine the selected environmental feature set information based on the first recording time information and the second recording time information. The selected environmental feature set information is used to describe the target environmental feature set information that is closest to the first recording time information in the second recording time information.

[0053] In S300, adjustment commands for the Venetian blinds are generated based on outdoor predicted light intensity information and real-time indoor light intensity information.

[0054] Specifically, after the terminal device determines the outdoor predicted light intensity value, it can generate a blind adjustment command based on the outdoor predicted light intensity value and the real-time indoor light intensity value. This enables the smart door and window blinds to be automatically adjusted according to the specific changes in the environment, which can effectively control the indoor temperature to reduce the energy consumption of indoor equipment, and also make the window brightness meet the user's preferences, greatly improving the user experience. The blind adjustment command is used to indicate the adjustment of the corresponding blade angle of the smart door and window blinds.

[0055] In some possible implementations, in order to generate the Venetian blind adjustment command, the method may include, but is not limited to, the following steps before step S300:

[0056] In S301, the indoor light intensity value information of the target user is obtained.

[0057] Specifically, the terminal device can obtain the target user's preferred indoor light intensity value information, which describes the indoor light intensity value customized by the target user based on personal preferences.

[0058] In one possible implementation, the Venetian blind adjustment command includes a real-time adjustment command and a subsequent adjustment command; the subsequent adjustment command includes a first adjustment command or a second adjustment command; both the real-time adjustment command and the subsequent adjustment command are used to instruct the adjustment of the blade angle of the Venetian blind of the smart door and window until the indoor preferred light intensity value is equal to the indoor preferred light intensity value; the execution time of the real-time adjustment command is earlier than the execution time of the subsequent adjustment command.

[0059] Accordingly, please refer to Figure 4 Step S300 includes, but is not limited to, the following steps:

[0060] In S310, it is determined whether the real-time indoor light intensity value is equal to the indoor preferred light intensity value.

[0061] Specifically, the terminal device can first determine whether the real-time indoor light intensity value is equal to the preferred indoor light intensity value.

[0062] In S320, if the real-time indoor light intensity value is not equal to the preferred indoor light intensity value, a real-time adjustment command is generated based on the preset adjustment angle information.

[0063] Specifically, if the real-time indoor light intensity value is not equal to the preferred indoor light intensity value, the terminal device can generate a real-time adjustment command based on the preset adjustment angle information, where the adjustment angle information is a preset value and can be 0.1 degrees.

[0064] In S330, the outdoor predicted light intensity value information and the real-time outdoor light intensity value information are compared.

[0065] Specifically, after the terminal device generates a real-time adjustment command, the terminal device can plan the next control command in advance to perform data calculation in advance and shorten the waiting interval of the overall adjustment process. Therefore, the terminal device can compare the outdoor predicted light intensity value information with the real-time outdoor light intensity value information.

[0066] In S340, if the outdoor predicted light intensity value is greater than the real-time outdoor light intensity value, the trend of increasing blade angle is determined.

[0067] Specifically, if the outdoor predicted light intensity value is greater than the real-time outdoor light intensity value, the terminal device can determine the blade angle increasing trend information. The blade angle increasing trend information is used to indicate increasing the blade angle so that the blade is adjusted to a vertical state.

[0068] In S350, a first adjustment command is generated based on the blade angle increase trend information and the preset adjustment angle information.

[0069] Specifically, after the terminal device determines the blade angle increase trend information, the terminal device can generate a first adjustment command based on the blade angle increase trend information and the preset adjustment angle information.

[0070] In S360, if the predicted outdoor light intensity is less than the real-time outdoor light intensity, the blade angle reduction trend is determined.

[0071] Specifically, if the outdoor predicted light intensity value is less than the real-time outdoor light intensity value, the terminal device can determine the blade angle decreasing trend information. The blade angle increasing trend information is used to indicate the reduction of the blade angle, so that the blade is adjusted to a horizontal state.

[0072] In S370, a second adjustment command is generated based on the blade angle reduction trend information and the preset adjustment angle information.

[0073] Specifically, after the terminal device determines the blade angle reduction trend information, the terminal device can generate a second adjustment command based on the blade angle reduction trend information and the preset adjustment angle information.

[0074] In some possible implementations, please refer to [link / reference needed] for better energy efficiency. Figure 5 After step S300, the method further includes, but is not limited to, the following steps:

[0075] In the S400, real-time glass temperature information of smart doors and windows is obtained.

[0076] Specifically, the terminal device can first obtain the real-time glass temperature information of the smart doors and windows, where the real-time glass temperature information is used to describe the real-time temperature of the glass of the smart doors and windows.

[0077] In S410, the real-time glass temperature information is compared with the preset first temperature threshold information.

[0078] Specifically, after the terminal device obtains the real-time glass temperature information, the terminal device can compare the real-time glass temperature information with the preset first temperature threshold information, wherein the first temperature threshold information is a preset value, for example, the first temperature threshold information can be thirty-five degrees Celsius.

[0079] In S420, if the real-time glass temperature information is greater than the first temperature threshold information, a fan system start command information is generated.

[0080] It should be noted that the smart doors and windows are pre-installed with a fan system and a heat exchanger. The specific installation locations of the fan system and heat exchanger can be found in the Chinese utility model patent with application number 202521506753.X.

[0081] Specifically, if the real-time glass temperature information is greater than the first temperature threshold information, the terminal device can effectively generate a fan system start command information. The fan system start command information is used to instruct the smart door and window to start the built-in fan system to reduce the glass temperature of the smart door and window.

[0082] In S430, the real-time glass temperature information is compared with the preset second temperature threshold information.

[0083] Specifically, the terminal device can compare real-time glass temperature information with preset second temperature threshold information, wherein the second temperature threshold information is a preset value, for example, the second temperature threshold information can be five degrees Celsius.

[0084] In S440, if the real-time glass temperature information is less than the first temperature threshold information, a heat exchanger start command information is generated.

[0085] Specifically, if the real-time glass temperature information is lower than the first temperature threshold information, the terminal device can generate a heat exchanger start command information, which is used to instruct the activation of the heat exchanger built into the smart door and window to increase the glass temperature of the smart door and window.

[0086] The implementation principle of the active adjustment method for smart doors and windows in this application embodiment is as follows: The terminal device can first acquire outdoor environmental feature set information and real-time indoor light intensity value information. Then, based on the outdoor environmental feature set information, it searches the preset historical environmental feature database to quickly determine the outdoor predicted light intensity value information. Finally, based on the outdoor predicted light intensity value information and the real-time indoor light intensity value information, it effectively generates a blind adjustment command, thereby realizing the automatic adjustment of the blinds of smart doors and windows according to the specific changes in the environment. This can effectively control the indoor temperature, reduce the energy consumption of indoor equipment, and make the brightness of the window meet the user's preferences, greatly improving the user experience.

[0087] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0088] Embodiments of this application also provide an active adjustment system based on smart doors and windows. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 6 As shown, the system 60 includes:

[0089] Outdoor environment feature set information acquisition module 61: used to acquire outdoor environment feature set information and real-time indoor light intensity value information;

[0090] Outdoor predicted light intensity value determination module 62: used to retrieve the outdoor predicted light intensity value information from a preset historical environmental feature database based on outdoor environmental feature set information;

[0091] Venetian blind adjustment command generation module 63: used to generate Venetian blind adjustment commands based on outdoor predicted light intensity information and real-time indoor light intensity information. The Venetian blind adjustment commands are used to indicate the adjustment of the corresponding blade angle of the Venetian blinds of the smart doors and windows.

[0092] Optionally, the outdoor environmental feature set information includes first recording time information, real-time air temperature information, real-time air humidity information, real-time outdoor light intensity information, real-time outdoor wind speed information, and real-time atmospheric pressure information. The historical environmental feature database pre-stores multiple historical environmental feature sets, each of which includes second recording time information, historical air temperature information, historical air humidity information, historical outdoor light intensity information, historical outdoor wind speed information, and historical atmospheric pressure information. The aforementioned outdoor predicted light intensity information determination module 62 includes:

[0093] The sampling time period information generation submodule is used to generate sampling time period information based on the first recorded time information and the preset time span value information;

[0094] The initial environmental feature set information determination submodule is used to search the preset historical environmental feature database based on the sampling time period information to determine multiple initial environmental feature set information. The initial environmental feature set information is used to describe the historical environmental feature set information of the second recording time information within the sampling time period information.

[0095] The target environmental feature set information determination submodule is used to retrieve multiple initially selected environmental feature set information based on outdoor environmental feature set information to determine the target environmental feature set information. The target environmental feature set information is used to describe historical environmental feature set information where historical air temperature information is equal to real-time air temperature information, historical air humidity information is equal to real-time air humidity information, historical outdoor light intensity information is equal to real-time outdoor light intensity information, historical outdoor wind speed information is equal to real-time outdoor wind speed information, and historical atmospheric pressure information is equal to real-time atmospheric pressure information.

[0096] The outdoor predicted light intensity value determination submodule is used to determine the historical outdoor light intensity value information corresponding to the target environmental feature set information in the next recording time period based on the historical environmental feature database.

[0097] Optionally, the system 60 also includes:

[0098] Target environment feature set information judgment module: used to determine whether the number of target environment feature set information is one;

[0099] Outdoor predicted light intensity value determination module: If the number of target environment feature set information is one, then continue to execute based on the historical environment feature database to determine the historical outdoor light intensity value information corresponding to the target environment feature set information in the next recording time period as the outdoor predicted light intensity value information;

[0100] Target environment feature set information determination module: If there are multiple target environment feature set information, then based on the first recording time information and the second recording time information, determine the selected environment feature set information, wherein the selected environment feature set information is used to describe the target environment feature set information that is closest to the first recording time information in the second recording time information.

[0101] Optionally, the system 60 also includes:

[0102] Indoor preferred light intensity information acquisition module: Used to acquire the indoor preferred light intensity information of the target user;

[0103] Accordingly, the Venetian blind adjustment instructions include real-time adjustment instructions and subsequent adjustment instructions. Subsequent adjustment instructions include either a first adjustment instruction or a second adjustment instruction. Both real-time and subsequent adjustment instructions are used to instruct the adjustment of the corresponding blade angle of the Venetian blinds in the smart door and window until the indoor preferred light intensity value equals the indoor preferred light intensity value. The execution time of the real-time adjustment instruction is earlier than the execution time of the subsequent adjustment instruction. The Venetian blind adjustment instruction generation module 63 includes:

[0104] Determine whether the real-time indoor light intensity value is equal to the indoor preferred light intensity value;

[0105] Real-time adjustment command generation submodule: If the real-time indoor light intensity value is not equal to the preferred indoor light intensity value, then based on the preset adjustment angle information, a real-time adjustment command is generated.

[0106] Outdoor predicted light intensity information comparison submodule: used to compare outdoor predicted light intensity information with real-time outdoor light intensity information;

[0107] The submodule for determining the increasing trend of the blade angle is used to determine the increasing trend of the blade angle if the predicted outdoor light intensity is greater than the real-time outdoor light intensity.

[0108] First adjustment command generation submodule: used to generate the first adjustment command based on the blade angle, the added trend information, and the preset adjustment angle information;

[0109] The submodule for determining the decreasing trend of the blade angle is used to determine the decreasing trend of the blade angle if the predicted outdoor light intensity is less than the real-time outdoor light intensity.

[0110] The second adjustment command generation submodule is used to generate a second adjustment command based on the blade angle reduction trend information and the preset adjustment angle information.

[0111] Optionally, the system 60 also includes:

[0112] Real-time glass temperature information acquisition module: used to acquire real-time glass temperature information of smart doors and windows;

[0113] Real-time glass temperature information comparison module: used to compare real-time glass temperature information with preset first temperature threshold information;

[0114] Fan system start command information generation module: If the real-time glass temperature information is greater than the first temperature threshold information, then generate fan system start command information, wherein the fan system start command information is used to instruct the smart door and window to start the built-in fan system to reduce the glass temperature of the smart door and window;

[0115] Real-time glass temperature information comparison module: used to compare real-time glass temperature information with preset second temperature threshold information;

[0116] Heat exchanger start command information generation module: If the real-time glass temperature information is less than the first temperature threshold information, the heat exchanger start command information is generated. The heat exchanger start command information is used to instruct the activation of the heat exchanger built into the smart door and window to increase the glass temperature of the smart door and window.

[0117] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0118] This application also provides a terminal device, such as... Figure 7 As shown, the terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps described in the above-described active adjustment method embodiment, for example... Figure 1 Steps S100 to S300 are shown; or, when processor 71 executes computer program 73, it implements the functions of each module in the above-described device, for example... Figure 6 The functions of modules 61 to 63 are shown.

[0119] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 70 and does not constitute a limitation on terminal device 70. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 70 may also include input / output devices, network access devices, buses, etc.

[0120] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0121] The memory 72 can be an internal storage unit of the terminal device 70, such as a hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.

[0122] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0123] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.

Claims

1. A method for active adjustment of intelligent doors and windows, characterized in that, The method includes: Acquire outdoor environmental feature set information and real-time indoor light intensity value information; Based on the outdoor environmental feature set information, the preset historical environmental feature database is searched to determine the outdoor predicted light intensity value information; Based on the outdoor predicted light intensity information and the real-time indoor light intensity information, a Venetian blind adjustment command is generated, wherein the Venetian blind adjustment command is used to indicate the adjustment of the blade angle of the Venetian blind of the smart door and window.

2. The method according to claim 1, characterized in that, The outdoor environmental feature set information includes first recording time information, real-time air temperature information, real-time air humidity information, real-time outdoor light intensity information, real-time outdoor wind speed information, and real-time atmospheric pressure information. The historical environmental feature database pre-stores multiple historical environmental feature sets, each of which includes second recording time information, historical air temperature information, historical air humidity information, historical outdoor light intensity information, historical outdoor wind speed information, and historical atmospheric pressure information. The step of retrieving the predicted outdoor light intensity value information from the preset historical environmental feature database based on the outdoor environmental feature set information includes: Based on the first recorded time information and the preset time span value information, a sampling time period information is generated; Based on the sampling time period information, a preset historical environmental feature database is searched to determine multiple preliminary environmental feature sets, wherein the preliminary environmental feature sets are used to describe the historical environmental feature sets of the second recording time information within the sampling time period information. Based on the outdoor environmental feature set information, multiple preliminary environmental feature set information are retrieved to determine the target environmental feature set information. The target environmental feature set information is used to describe historical environmental feature set information in which historical air temperature information is equal to real-time air temperature information, historical air humidity information is equal to real-time air humidity information, historical outdoor light intensity information is equal to real-time outdoor light intensity information, historical outdoor wind speed information is equal to real-time outdoor wind speed information, and historical atmospheric pressure information is equal to real-time atmospheric pressure information. Based on the historical environmental feature database, the historical outdoor light intensity value information corresponding to the target environmental feature set information in the next recording time period is determined as the outdoor predicted light intensity value information.

3. The method according to claim 2, characterized in that, After retrieving multiple initially selected environmental feature sets based on the outdoor environmental feature set information and determining the target environmental feature set information, the method further includes: Determine whether the number of the target environment feature set information is one; If the number of target environment feature set information is one, then continue to execute the step of determining the historical outdoor light intensity value information corresponding to the target environment feature set information in the next recording time period as the outdoor predicted light intensity value information based on the historical environment feature database; If there are multiple target environment feature set information, then the selected environment feature set information is determined based on the first recording time information and the second recording time information, wherein the selected environment feature set information is used to describe the target environment feature set information that is closest to the first recording time information in the second recording time information.

4. The method according to claim 1, characterized in that, Before generating the Venetian blind adjustment command based on the outdoor predicted light intensity information and the real-time indoor light intensity information, the method further includes: Obtain the indoor preferred light intensity information of the target user; Accordingly, the Venetian blind adjustment command includes a real-time adjustment command and a subsequent adjustment command. The subsequent adjustment command includes a first adjustment command or a second adjustment command. Both the real-time adjustment command and the subsequent adjustment command are used to instruct the adjustment of the slat angle of the Venetian blinds in the smart door and window until the indoor preferred light intensity value is equal to the indoor preferred light intensity value. The execution time of the real-time adjustment command is earlier than the execution time of the subsequent adjustment command. Generating the Venetian blind adjustment command based on the outdoor predicted light intensity value and the real-time indoor light intensity value includes: Determine whether the real-time indoor light intensity value is equal to the indoor preferred light intensity value; If the real-time indoor light intensity value is not equal to the preferred indoor light intensity value, a real-time adjustment command is generated based on the preset adjustment angle information. Compare the predicted outdoor light intensity value with the real-time outdoor light intensity value; If the outdoor predicted light intensity value is greater than the real-time outdoor light intensity value, then the trend of increasing blade angle is determined. Based on the blade angle increase trend information and the preset adjustment angle information, a first adjustment command is generated; If the outdoor predicted light intensity value is less than the real-time outdoor light intensity value, then the blade angle reduction trend information is determined. Based on the blade angle reduction trend information and the preset adjustment angle information, a second adjustment command is generated.

5. The method according to claim 1, characterized in that, After generating the Venetian blind adjustment command based on the outdoor predicted light intensity information and the real-time indoor light intensity information, the method further includes: Obtain the real-time glass temperature information of the smart doors and windows; Compare the real-time glass temperature information with the preset first temperature threshold information; If the real-time glass temperature information is greater than the first temperature threshold information, a fan system start command information is generated, wherein the fan system start command information is used to instruct the activation of the built-in fan system of the smart door and window to reduce the glass temperature of the smart door and window; Compare the real-time glass temperature information with the preset second temperature threshold information; If the real-time glass temperature information is less than the first temperature threshold information, a heat exchanger start command information is generated, wherein the heat exchanger start command information is used to instruct the activation of the heat exchanger built into the smart door and window to increase the glass temperature of the smart door and window.

6. An active adjustment system based on intelligent doors and windows, characterized in that, The system includes: Outdoor environment feature set information acquisition module: used to acquire outdoor environment feature set information and real-time indoor light intensity value information; Outdoor predicted light intensity value determination module: used to search a preset historical environmental feature database based on the outdoor environmental feature set information to determine the outdoor predicted light intensity value information; Venetian blind adjustment command generation module: used to generate Venetian blind adjustment commands based on the outdoor predicted light intensity value information and the real-time indoor light intensity value information, wherein the Venetian blind adjustment commands are used to indicate the adjustment of the blade angle of the Venetian blinds of the smart doors and windows.

7. The system according to claim 6, characterized in that, The system also includes: Real-time glass temperature information acquisition module: used to acquire the real-time glass temperature information of the smart doors and windows; Real-time glass temperature information comparison module: used to compare the real-time glass temperature information with a preset first temperature threshold information; Fan system start command information generation module: used to generate fan system start command information if the real-time glass temperature information is greater than the first temperature threshold information, wherein the fan system start command information is used to instruct the activation of the built-in fan system of the smart door and window to reduce the glass temperature of the smart door and window; Real-time glass temperature information comparison module: used to compare the real-time glass temperature information with a preset second temperature threshold information; Heat exchanger start-up command information generation module: used to generate heat exchanger start-up command information if the real-time glass temperature information is less than the first temperature threshold information, wherein the heat exchanger start-up command information is used to instruct the start-up of the heat exchanger built into the smart door and window to increase the glass temperature of the smart door and window.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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