CN112261760A - Method for automatically adjusting light source and intelligent system - Google Patents
Method for automatically adjusting light source and intelligent system Download PDFInfo
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Abstract
The invention belongs to the technical field of intelligent illumination, and provides a method for automatically adjusting a light source and an intelligent system, which comprise the following steps: acquiring ambient light parameters of an area where a light source is located, wherein the ambient light parameters comprise ambient light intensity, ambient light color, and space or current time where the light source is located; calculating an adjustment parameter of the light source based on the ambient light parameter, and adjusting the light source according to the adjustment parameter. The color and the brightness of the ambient light of the light source and the time and the place of the light source are comprehensively considered, and the automatic adjustment is made according to the individual illumination requirements of different users in different spaces and different times, so that the illumination environment around the user can always keep stable brightness and color, and the illumination requirements can be met at various times and places without manual operation of the user.
Description
Technical Field
The invention belongs to the technical field of intelligent lighting, and particularly relates to a method for automatically adjusting a light source and an intelligent system.
Background
The desk lamp is a common household appliance in daily life, and is commonly used for auxiliary lighting or decorative lighting. The traditional table lamp only has a switch button, the brightness and the color of a light source of the traditional table lamp cannot be adjusted, once the traditional table lamp is started, the traditional table lamp emits light with fixed brightness and fixed color, and under the condition that some ambient light is dark, the brightness and the color of the traditional table lamp cause discomfort of a user and feel dazzling.
In order to improve the adaptability of the desk lamp to the use environment, some technologies provide a desk lamp with variable brightness by controlling the voltage of the light source. This part desk lamp uses the physics button to carry out manual regulation more, needs the user to carry out luminance adjustment manually, and this has solved the adaptation adjustment problem of light luminance and environment than traditional desk lamp in effect, but has caused new problem: the operation of turning on the desk lamp becomes relatively complicated, and people need to perform additional operation besides turning on the desk lamp through a physical button, so that the brightness of the desk lamp is suitable for the environment, and compared with the traditional desk lamp, the desk lamp brings more complicated operation.
In order to further solve the problem of complex operation of the desk lamp with adjustable brightness, the prior art (CN204408727U — a self-adaptive gradually-lighting desk lamp) discloses a self-adaptive gradually-lighting desk lamp, which obtains the brightness of ambient light through a light sensor, and amplifies the output voltage of the light sensor to determine the input voltage of a light source, so as to realize self-adaptive gradually-lighting adjustment according to the ambient light. The method also comprises the step of adding an infrared sensor into the system to acquire whether people are around the desk lamp or not, and automatically turning off the desk lamp if no people are around the desk lamp. According to the technology, the ambient light is obtained through the light sensor, and the brightness of the light source of the desk lamp is adjusted based on the ambient light, but in the application scene of the existing intelligent equipment, not only the brightness of the light source needs to be adjusted, but also the color of the light source needs to be adjusted; besides determining whether a person is near the light source, the method also needs to be intelligently adjusted according to the time and place of the light source. Based on the above analysis, it is necessary to find a new method to further increase the intelligent control performance of the light source, so that the method can intelligently adjust various parameters of the light source according to the ambient light and the space where the user is located.
Disclosure of Invention
In order to realize intelligent adjustment of various parameters of the desk lamp according to ambient light and a space where a user is located, the invention provides a method and a system for automatically controlling and adjusting a light source, and the specific technical scheme comprises the following steps:
acquiring ambient light parameters of an area where a light source is located, wherein the ambient light parameters comprise ambient light intensity, ambient light color, and space or current time where the light source is located;
calculating an adjustment parameter of the light source based on the ambient light parameter, and adjusting the light source according to the adjustment parameter.
Further, in the method for automatically adjusting a light source of the present invention, the calculating an adjustment parameter of the light source according to the ambient light parameter, and adjusting the light source according to the adjustment parameter specifically includes:
acquiring a brightness parameter table of the light source, and inquiring in the brightness parameter table to obtain brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time;
acquiring the ambient light intensity, the space where the light source is located and the brightness weight value of the current time, and calculating the brightness adjusting parameter of the light source based on the brightness weight value;
and adjusting the brightness of the light source according to the brightness adjusting parameter.
Further, in the method for automatically adjusting a light source of the present invention, the ambient light intensity, the space where the light source is located, and the brightness weight value of the current time are obtained by the following methods:
establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
and calculating a neural network model and brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time based on the brightness weight, and obtaining the brightness weight values of the ambient light intensity, the space where the light source is located and the current time.
Further, in a method for automatically adjusting a light source according to the present invention, the calculating an adjustment parameter of the light source based on each item of the environmental information, and adjusting the light source according to the adjustment parameter further includes:
acquiring a color parameter table of the light source, and acquiring color adjusting values corresponding to the color of the ambient light, the space where the light source is located and the current time by referring to the color parameter table;
calculating color adjusting parameters of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
adjusting the color of the light source according to the color adjustment parameter.
Further, in the method for automatically adjusting a light source of the present invention, the color of the ambient light, the space where the light source is located, and the color weight value of the current time are obtained by the following methods:
establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
and calculating a neural network model and color adjusting values corresponding to the environment light color, the space where the light source is located and the current time based on the color weights, and obtaining the color weight values of the environment light color, the space where the light source is located and the current time.
The invention also provides an intelligent system capable of automatically adjusting the light source, which comprises:
the environment light acquisition module is used for acquiring environment light parameters of an area where the light source is located, wherein the environment information comprises environment light intensity, environment light color, space where the light source is located and current time;
and the light source adjusting module is used for calculating adjusting parameters of the light source based on various pieces of environment information and adjusting the light source according to the adjusting parameters.
Further, in the intelligent system capable of automatically adjusting a light source of the present invention, the light source adjusting module specifically includes:
the brightness adjustment value acquisition submodule acquires a brightness parameter table of the light source, and inquires the brightness parameter table to obtain brightness adjustment values corresponding to the ambient light intensity, the space where the light source is located and the current time;
the brightness adjusting parameter calculating submodule is used for acquiring the brightness weight values of the ambient light intensity, the space where the light source is located and the current time and calculating the brightness adjusting parameter of the light source based on the brightness weight values;
and the light source brightness adjusting submodule adjusts the brightness of the light source according to the brightness adjusting parameter.
Further, in an intelligent system capable of automatically adjusting a light source according to the present invention, the system further includes:
the modeling module is used for establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
and the weight value calculating module is used for calculating brightness adjusting values corresponding to the neural network model, the ambient light intensity, the light source space and the current time based on the brightness weight, and obtaining the brightness weight values of the ambient light intensity, the light source space and the current time.
Further, in the intelligent system capable of automatically adjusting a light source of the present invention, the light source adjusting module specifically includes:
the color adjusting value obtaining sub-module is used for obtaining a color parameter table of the light source and obtaining color adjusting values corresponding to the color of the environment light, the space where the light source is located and the current time by referring to the color parameter table;
the color adjusting parameter calculating submodule calculates the color adjusting parameter of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
and the light source color adjusting submodule adjusts the color of the light source according to the color adjusting parameter.
Further, in an intelligent system capable of automatically adjusting a light source according to the present invention, the system further includes:
the modeling module is used for establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
and the weight value calculating module is used for calculating color adjusting values corresponding to the neural network model, the environment light color, the light source space and the current time based on the color weight, and obtaining the color weight values of the environment light color, the light source space and the current time.
Compared with the prior art, the invention can bring the following beneficial technical effects:
the method collects the ambient light intensity and color of the area where the light source is located and the space or time information of the light source, comprehensively considers the color and brightness of the ambient light where the light source is located and the time and place of the light source, and can automatically adjust the personalized illumination requirements of different users in different spaces and different times. Specifically, the information is parameterized, and parameters of the light source to be adjusted are calculated according to the parameters, so that the illumination environment around the user can always keep stable brightness and color, and the illumination requirements can be met at various times and places without manual operation of the user.
Drawings
FIG. 1 is a flow chart of a method of automatically adjusting a light source according to the present invention;
FIG. 2 is another flow chart of a method of automatically adjusting a light source according to the present invention;
FIG. 3 is yet another flow chart of a method of automatically adjusting a light source in accordance with the present invention;
FIG. 4 is another flow chart of a method of automatically adjusting a light source according to the present invention;
FIG. 5 is yet another flow chart of a method of automatically adjusting a light source in accordance with the present invention;
FIG. 6 is another flow chart of a method of automatically adjusting a light source according to the present invention;
FIG. 7 is a schematic diagram of an intelligent system for automatically adjusting a light source according to the present invention;
the reference numbers illustrate:
100 light source adjusting module 110 brightness adjusting value obtaining submodule
120 brightness adjustment parameter calculation submodule 130 light source brightness adjustment submodule
140 color adjustment value obtaining submodule 150 color adjustment parameter calculating submodule
160 light source color adjustment submodule 200 ambient light acquisition module
300 modeling module 400 weighted value calculation module
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
For the sake of simplicity, the drawings only schematically show the parts relevant to the present invention, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "one" means not only "only one" but also a case of "more than one".
With the development of technology, the demand of people for illumination is also changing continuously, from the beginning, only the surrounding environment is illuminated to the present, some lighting devices can automatically adjust brightness and color to meet the demands of users under different use environments, and these lighting devices that can be automatically adjusted are generally based on the perception of ambient light, so as to adjust the brightness and color of the lighting devices to the ambient light to create a stable light environment for the users, however, the demands of the users on the light environment are sometimes scene-based, and the lighting environments demanded by the users under different scenes, different geographic spaces and different time premises are often different. The invention provides a method and a system for intelligently adjusting a light source, which can meet various scene requirements of various users.
The first embodiment of the present invention. Fig. 1 is a flow chart of a method of automatically adjusting a light source according to the present invention, comprising:
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s200, calculating adjusting parameters of the light source based on the ambient light parameters, and adjusting the light source according to the adjusting parameters.
Specifically, the invention can be applied to an intelligent desk lamp, and in S100, the intelligent desk lamp obtains various parameters of ambient light around an area where the desk lamp is located, and in addition, the desk lamp can obtain the space and time where the desk lamp is located. Various different use scenes can be analyzed by synthesizing various parameters of the ambient light, the space and the time of the ambient light, for example, when the space where the desk lamp is located is a baby room, the current time is twelve am, and the current ambient light state is a dark state, the user can be considered to be in the use scene of watching a baby at night, the user can manually set the use scene for determining the scene, and the user can also use machine learning to automatically recognize the use scene. In the invention, the use scene of the user is determined based on several parameters, namely the position and the time of the desk lamp under the condition of ambient light, which is a precondition for intelligently adjusting the desk lamp. Each scene corresponds to a suitable light environment parameter, and after the scenes are obtained, target parameters of the light environment needing to be adjusted are obtained.
After determining target parameters of a light environment to be adjusted based on various parameters acquired by the desk lamp, the desk lamp also needs to calculate how to adjust the light source of the desk lamp, so that the adjusted light source of the desk lamp and the ambient light can reach the standard of the target light environment after being integrated. Therefore, in S200, the parameters of the light source of the desk lamp that needs to be adjusted are calculated based on the target parameters of the light environment obtained in S100, and it can be understood that the target light environment can be obtained after the light source of the desk lamp provides a supplementary lighting, and the brightness and color of the supplementary lighting are integrated with the existing light environment. The calculation methods are various, for example, the brightness and the color parameters of the light environment to be supplemented can be obtained by subtracting the brightness and the color parameters of the existing light environment from the brightness and the color target parameters of the light environment to be adjusted, and when the desk lamp is in the off state, the obtained brightness and the color parameters to be supplemented are the adjustment parameters in S200. When the desk lamp is in the on state, the brightness and color values provided by the light source of the desk lamp for the current light environment are also considered in the acquired brightness and color parameters needing supplementary lighting, and the adjustment parameters in the S200 are calculated based on the color and brightness of the light source of the desk lamp.
The invention discloses a method for automatically adjusting a light source, which is applied to an intelligent desk lamp, identifies an application scene of the desk lamp by the characteristics of ambient light around the intelligent desk lamp and space time of the desk lamp, calculates parameters of the desk lamp, which need to be adjusted by the light source, according to target light ambient parameters corresponding to the application scene, and automatically adjusts the light source of the desk lamp according to the obtained adjustment parameters. Through this kind of mode, realized that intelligent desk lamp is according to the current luminous environment around the space place, the time and the desk lamp that the user is located, the purpose of automatically regulated desk lamp light source, the user carries the desk lamp or puts the desk lamp in the indoor space and need not carry out manual operation to it again, can anytime and anywhere satisfy the illumination demand, brought very big convenience for the user.
A second embodiment of the invention. Fig. 2 is another flow chart of a method of automatically adjusting a light source according to the present invention, comprising:
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s110, acquiring a brightness parameter table of the light source, and inquiring in the brightness parameter table to obtain brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time;
s120, acquiring the ambient light intensity, the space where the light source is located and the brightness weight value of the current time, and calculating the brightness adjusting parameter of the light source based on the brightness weight value;
s210, adjusting the brightness of the light source according to the brightness adjusting parameter.
Specifically, the invention can be applied to an intelligent desk lamp, and in S100, the intelligent desk lamp obtains various parameters of ambient light around an area where the desk lamp is located, and in addition, the desk lamp can obtain the space and time where the desk lamp is located. Various different use scenes can be analyzed by synthesizing various parameters of the ambient light, the space and the time of the ambient light, for example, when the space where the desk lamp is located is a baby room, the current time is twelve am, and the current ambient light state is a dark state, the user can be considered to be in the use scene of watching a baby at night, the user can manually set the use scene for determining the scene, and the user can also use machine learning to automatically recognize the use scene. In the invention, the use scene of the user is determined based on several parameters, namely the position and the time of the desk lamp under the condition of ambient light, which is a precondition for intelligently adjusting the desk lamp. Each scene corresponds to a suitable light environment parameter, and after the scenes are obtained, target parameters of the light environment needing to be adjusted are obtained.
In the adjustment of the light source of the desk lamp, the brightness adjustment is an important part, so the light environment intensity obtained by the desk lamp and the current time of the space where the light source is located all correspond to corresponding target brightness parameters, the parameters are stored in a brightness parameter table, the brightness parameter table records the brightness adjustment value corresponding to each current environment light intensity, current space and time, in S110, the brightness parameter table is extracted, and each brightness adjustment value is obtained.
The number of the parameters obtained in S110 is three, and the parameters are respectively adjustment parameters corresponding to the current light environment brightness, the space where the desk lamp is located, and the time, but the three parameters need to be combined into one parameter for adjusting the light source of the desk lamp, and the parameter is finally used as the standard for adjusting the light source brightness of the desk lamp. S120 provides a method for obtaining a final brightness adjustment parameter based on the three parameters, where the three parameters affect the final brightness adjustment parameter according to their respective weight values, and the final brightness adjustment parameter is obtained by performing weighted summation on the three parameters according to the weight values. The weight value concept is introduced because the three conditions have different influences on the final brightness adjustment parameter in different scenes, for example, when the desk lamp of the present invention is used for providing illumination for infants, the work and rest time of some children is special, and higher brightness (some children are afraid of black) is needed by adults at night.
The final brightness adjustment parameters are obtained through S120, and in S210, the light source of the desk lamp is adjusted according to the obtained final brightness adjustment parameters.
The invention provides a method for automatically adjusting the brightness of a light source, which is characterized in that the brightness of ambient light and the space and time of a desk lamp are obtained based on a sensor of the desk lamp, brightness adjusting parameters corresponding to the above three conditions are inquired by using a brightness parameter table, the use scene of the desk lamp is identified, the brightness adjusting parameters corresponding to the three conditions are weighted and summed based on the use scene, so that the final brightness adjusting parameter is obtained, and the brightness of the light source of the desk lamp is adjusted according to the final brightness adjusting parameter. By the method, brightness of the intelligent desk lamp can be automatically adjusted based on the ambient light brightness and the time and space where the desk lamp is located, a user can meet the requirement for the illumination degree without manual operation when using the desk lamp, the user can adjust the brightness of the light source of the desk lamp more conveniently, and better experience is brought to the user.
A third embodiment of the present invention. FIG. 3 is a further flowchart of a method of automatically adjusting a light source of the present invention, comprising:
s001, establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
s002, calculating brightness adjusting values corresponding to the neural network model, the ambient light intensity, the light source space and the current time based on the brightness weight, and obtaining brightness weight values of the ambient light intensity, the light source space and the current time;
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s110, acquiring a brightness parameter table of the light source, and inquiring in the brightness parameter table to obtain brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time;
s120, acquiring the ambient light intensity, the space where the light source is located and the brightness weight value of the current time, and calculating the brightness adjusting parameter of the light source based on the brightness weight value;
s210, adjusting the brightness of the light source according to the brightness adjusting parameter.
Specifically, three conditions of light environment brightness, current space, and current time are three brightness adjustment parameters obtained by querying in the brightness parameter table, and the three parameters are subjected to weighted summation to obtain a final brightness adjustment parameter, how are weight values of the three parameters obtained?
In S001, a brightness weight calculation neural network of the ambient light intensity, the light source space and the current time is established based on semi-supervised learning, the brightness weight calculation neural network searches the influence of brightness adjusting parameters of the ambient light intensity, the light source space and the current time on the final brightness adjusting parameters in a specific scene according to the learning of a sample, and the influence is expressed in the form of a weight value.
In S002, after the training of the model is completed, under a specific scenario, we can obtain the respective metric weight values of the three conditions, i.e., the ambient light intensity, the space where the light source is located, and the current time.
In S100, the intelligent desk lamp obtains various parameters of ambient light around an area where the desk lamp is located, and in addition, the desk lamp can obtain a space and time where the desk lamp is located. Various different use scenes can be analyzed by synthesizing various parameters of the ambient light, the space and the time of the ambient light, for example, when the space where the desk lamp is located is a baby room, the current time is twelve am, and the current ambient light state is a dark state, the user can be considered to be in the use scene of watching a baby at night, the user can manually set the use scene for determining the scene, and the user can also use machine learning to automatically recognize the use scene. In the invention, the use scene of the user is determined based on several parameters, namely the position and the time of the desk lamp under the condition of ambient light, which is a precondition for intelligently adjusting the desk lamp. Each scene corresponds to a suitable light environment parameter, and after the scenes are obtained, target parameters of the light environment needing to be adjusted are obtained.
In the adjustment of the light source of the desk lamp, the brightness adjustment is an important part, so the light environment intensity obtained by the desk lamp and the current time of the space where the light source is located all correspond to corresponding target brightness parameters, the parameters are stored in a brightness parameter table, the brightness parameter table records the brightness adjustment value corresponding to each current environment light intensity, current space and time, in S110, the brightness parameter table is extracted, and each brightness adjustment value is obtained.
The number of the parameters obtained in S110 is three, and the parameters are respectively adjustment parameters corresponding to the current light environment brightness, the space where the desk lamp is located, and the time, but the three parameters need to be combined into one parameter for adjusting the light source of the desk lamp, and the parameter is finally used as the standard for adjusting the light source brightness of the desk lamp. S120 provides a method for obtaining a final brightness adjustment parameter based on the three parameters, where the three parameters affect the final brightness adjustment parameter according to their respective weight values, and the final brightness adjustment parameter is obtained by performing weighted summation on the three parameters according to the weight values. The weight value concept is introduced because the three conditions have different influences on the final brightness adjustment parameter in different scenes, for example, when the desk lamp of the present invention is used for providing illumination for infants, the work and rest time of some children is special, and higher brightness (some children are afraid of black) is needed by adults at night.
The final brightness adjustment parameters are obtained through S120, and in S210, the light source of the desk lamp is adjusted according to the obtained final brightness adjustment parameters.
In the invention, the three conditions of the light environment brightness of the light source, the space where the light source is located and the current time are weighted and summed to obtain the final brightness adjusting parameter. The samples can be from research personnel or daily use records of the user in a training mode, and by using machine learning, the invention realizes that the weight value is automatically obtained according to the samples. Preferably, if the user selects the daily use record of the user in the training mode as the training sample, the personalized weight value can be obtained according to the personalized requirements of the user, so that the method is suitable for different requirements of different users, and the weight value calculation scheme has wider applicability.
In a fourth embodiment of the present invention, fig. 4 is another flowchart of a method for automatically adjusting a light source according to the present invention, which includes:
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s140, acquiring a color parameter table of the light source, and acquiring color adjusting values corresponding to the ambient light color, the space where the light source is located and the current time by referring to the color parameter table;
s150, calculating color adjusting parameters of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
s220, adjusting the color of the light source according to the color adjusting parameter.
Specifically, the invention can be applied to an intelligent desk lamp, and in S100, the intelligent desk lamp obtains various parameters of ambient light around an area where the desk lamp is located, and in addition, the desk lamp can obtain the space and time where the desk lamp is located. Various different use scenes can be analyzed by synthesizing various parameters of the ambient light, the space and the time of the ambient light, for example, when the space where the desk lamp is located is a baby room, the current time is twelve am, and the current ambient light state is a dark state, the user can be considered to be in the use scene of watching a baby at night, the user can manually set the use scene for determining the scene, and the user can also use machine learning to automatically recognize the use scene. In the invention, the use scene of the user is determined based on several parameters, namely the position and the time of the desk lamp under the condition of ambient light, which is a precondition for intelligently adjusting the desk lamp. Each scene corresponds to a suitable light environment parameter, and after the scenes are obtained, target parameters of the light environment needing to be adjusted are obtained.
In the adjusting process of the light source of the desk lamp, the color of the light source is adjusted, so that the ambient light ambient color, the space where the ambient light ambient color is located and the current time which are acquired by the desk lamp correspond to corresponding target color parameters, the parameters are stored in a color parameter table, and in S140, the color parameter table is extracted and various color adjusting values are acquired.
The number of the parameters acquired in S140 is three, and the three parameters are color adjustment parameters corresponding to the current light environment color, the space where the desk lamp is located, and the time, respectively, and the color of the light source of the desk lamp is adjusted, and the three parameters need to be combined into one parameter, which is used as the light source color adjustment standard of the desk lamp. S150 provides a method for obtaining a final color adjustment parameter based on the three parameters, and the three parameters are weighted and summed according to their respective weight values to obtain the final color adjustment parameter. The respective weight values of the three parameters respectively represent the influence degrees of the three parameters on the light source color adjustment in the current scene.
We get the final color adjustment parameter through S150, and in S220, the light source of the desk lamp is color-adjusted according to the color adjustment parameter.
The invention provides a method for automatically adjusting the color of a light source, which comprises the steps of using color adjusting parameters corresponding to three conditions on a color parameter table based on the color of ambient light, the space where the ambient light is located and the current time, obtained by a desk lamp sensor, carrying out weighted summation on the three parameters to obtain a final color adjusting parameter, and then adjusting the color of the desk lamp light source according to the final color adjusting parameter. By the method, the color of the light source of the desk lamp is automatically adjusted based on the color of the luminous environment of the desk lamp, the space of the desk lamp and the current time, and the color temperature of the luminous environment can be met without manual operation when a user uses the desk lamp.
In a fifth embodiment of the present invention, fig. 5 is a flowchart of a method for automatically adjusting a light source according to the present invention, which includes:
s003, establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
s004, calculating color adjusting values corresponding to the neural network model, the environment light color, the light source space and the current time based on the color weight, and obtaining color weight values of the environment light color, the light source space and the current time;
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s140, acquiring a color parameter table of the light source, and acquiring color adjusting values corresponding to the ambient light color, the space where the light source is located and the current time by referring to the color parameter table;
s150, calculating color adjusting parameters of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
s220, adjusting the color of the light source according to the color adjusting parameter.
Specifically, three conditions, namely, the ambient light color, the current space, and the current time, may be queried in the color parameter table to obtain three color condition parameters, and the final color adjustment parameter may be obtained by performing weighted summation on the three color adjustment parameters, how to obtain weight values of the three conditions?
In S003, a color weight calculation neural network of the ambient light color, the space where the ambient light color is located and the current time is established based on semi-supervised learning, the color weight calculation neural network searches the influence of three conditions of the ambient light color, the space where the ambient light color is located and the current time on the final color adjusting parameter in a specific scene according to the learning of a sample, and the influence is expressed in the form of a weight value.
In S100, the intelligent desk lamp obtains various parameters of ambient light around an area where the desk lamp is located, and in addition, the desk lamp can obtain a space and time where the desk lamp is located. Various different use scenes can be analyzed by synthesizing various parameters of the ambient light, the space and the time of the ambient light, for example, when the space where the desk lamp is located is a baby room, the current time is twelve am, and the current ambient light state is a dark state, the user can be considered to be in the use scene of watching a baby at night, the user can manually set the use scene for determining the scene, and the user can also use machine learning to automatically recognize the use scene. In the invention, the use scene of the user is determined based on several parameters, namely the position and the time of the desk lamp under the condition of ambient light, which is a precondition for intelligently adjusting the desk lamp. Each scene corresponds to a suitable light environment parameter, and after the scenes are obtained, target parameters of the light environment needing to be adjusted are obtained.
In the adjusting process of the light source of the desk lamp, the color of the light source is adjusted, so that the ambient light ambient color, the space where the ambient light ambient color is located and the current time which are acquired by the desk lamp correspond to corresponding target color parameters, the parameters are stored in a color parameter table, and in S140, the color parameter table is extracted and various color adjusting values are acquired.
The number of the parameters acquired in S140 is three, and the three parameters are color adjustment parameters corresponding to the current light environment color, the space where the desk lamp is located, and the time, respectively, and the color of the light source of the desk lamp is adjusted, and the three parameters need to be combined into one parameter, which is used as the light source color adjustment standard of the desk lamp. S150 provides a method for obtaining a final color adjustment parameter based on the three parameters, and the three parameters are weighted and summed according to their respective weight values to obtain the final color adjustment parameter. The respective weight values of the three parameters respectively represent the influence degrees of the three parameters on the light source color adjustment in the current scene.
We get the final color adjustment parameter through S150, and in S220, the light source of the desk lamp is color-adjusted according to the color adjustment parameter.
In the present invention, the three conditions of the color of the light environment where the light source is located, the space where the light source is located, and the current time are weighted and summed to obtain the final brightness adjustment parameter. Further preferably, the user selects the daily use record of the user in the training mode as the training sample, and the personalized weight value can be obtained according to the personalized requirements of the user, so that the method is suitable for different requirements of different users, and the weight value calculation scheme has wider applicability.
Fig. 6 is another flowchart of a method for automatically adjusting a light source according to a sixth embodiment of the present invention, including:
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s101, establishing a brightness weight calculation neural network model of the ambient light intensity, the space where a light source is located and the current time through semi-supervised learning;
s102, calculating brightness adjusting values corresponding to the neural network model, the ambient light intensity, the light source space and the current time based on the brightness weights, and obtaining brightness weight values of the ambient light intensity, the light source space and the current time;
s003, establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
s004, calculating color adjusting values corresponding to the neural network model, the environment light color, the light source space and the current time based on the color weight, and obtaining color weight values of the environment light color, the light source space and the current time;
s100, obtaining an ambient light parameter of an area where a light source is located, wherein the ambient light parameter comprises ambient light intensity, ambient light color, and space where the light source is located or current time;
s110, acquiring a brightness parameter table of the light source, and inquiring in the brightness parameter table to obtain brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time;
s120, acquiring the ambient light intensity, the space where the light source is located and the brightness weight value of the current time, and calculating the brightness adjusting parameter of the light source based on the brightness weight value;
s140, acquiring a color parameter table of the light source, and acquiring color adjusting values corresponding to the ambient light color, the space where the light source is located and the current time by referring to the color parameter table;
s150, calculating color adjusting parameters of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
s210, adjusting the brightness of the light source according to the brightness adjusting parameter;
s220, adjusting the color of the light source according to the color adjusting parameter.
Specifically, this embodiment is a method embodiment combined with the first to fifth embodiments, and the technical problems solved, technical solutions used, and technical effects achieved are the same as those of the first to fifth embodiments, and are not repeated herein.
In a seventh embodiment of the present invention, fig. 7 is a schematic structural diagram of an intelligent system capable of automatically adjusting a light source according to the present invention, the system includes:
the ambient light obtaining module 200 is configured to obtain ambient light parameters of an area where the light source is located, where the ambient light parameters include ambient light intensity, ambient light color, space where the light source is located, and current time;
and a light source adjusting module 100 for calculating an adjusting parameter of the light source based on each item of the environment information, and adjusting the light source according to the adjusting parameter.
The light source adjusting module 100 specifically includes:
the brightness adjustment value obtaining sub-module 110 obtains a brightness parameter table of the light source, and obtains brightness adjustment values corresponding to the ambient light intensity, the space where the light source is located and the current time by querying in the brightness parameter table;
the brightness adjustment parameter calculation sub-module 120 is configured to obtain a brightness weight value of the ambient light intensity, a space where the light source is located, and a current time, and calculate a brightness adjustment parameter of the light source based on the brightness weight value;
and the light source brightness adjusting submodule 130 adjusts the brightness of the light source according to the brightness adjusting parameter.
The color adjustment value obtaining sub-module 140 obtains a color parameter table of the light source, and obtains color adjustment values corresponding to the color of the ambient light, the space where the light source is located and the current time by referring to the color parameter table;
the color adjusting parameter calculating submodule 150 calculates the color adjusting parameter of the light source based on the color of the ambient light, the space where the light source is located and the color weight value of the current time;
and a light source color adjusting sub-module 160 for adjusting the color of the light source according to the color adjusting parameter.
The modeling module 300 is used for establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
the modeling module 300 is further configured to establish a color weight calculation neural network model of the ambient light color, the space where the light source is located, and the current time through semi-supervised learning;
and the weight value calculating module 400 is used for calculating the brightness adjusting values corresponding to the neural network model, the ambient light intensity, the light source space and the current time based on the brightness weight, and obtaining the brightness weight values of the ambient light intensity, the light source space and the current time.
The weight value calculating module 400 is further configured to calculate, based on the color weights, color adjustment values corresponding to the neural network model, the ambient light color, the space where the light source is located, and the current time, and obtain color weight values of the ambient light color, the space where the light source is located, and the current time.
Specifically, this embodiment is a system embodiment corresponding to the sixth embodiment, and the technical problems solved, technical solutions used, and technical effects achieved by this embodiment are the same as those of the sixth embodiment, and are not described herein again.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method of automatically adjusting a light source, comprising:
acquiring ambient light parameters of an area where a light source is located, wherein the ambient light parameters comprise ambient light intensity, ambient light color, and space or current time where the light source is located;
calculating an adjustment parameter of the light source based on the ambient light parameter, and adjusting the light source according to the adjustment parameter.
2. The method according to claim 1, wherein the calculating an adjustment parameter of the light source based on the ambient light parameter, and adjusting the light source according to the adjustment parameter specifically includes:
acquiring a brightness parameter table of the light source, and inquiring in the brightness parameter table to obtain brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time;
acquiring the ambient light intensity, the space where the light source is located and the brightness weight value of the current time, and calculating the brightness adjusting parameter of the light source based on the brightness weight value;
and adjusting the brightness of the light source according to the brightness adjusting parameter.
3. The method of claim 2, wherein the ambient light intensity, the space where the light source is located, and the brightness weight value of the current time are obtained by:
establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
and calculating a neural network model and brightness adjusting values corresponding to the ambient light intensity, the space where the light source is located and the current time based on the brightness weight, and obtaining the brightness weight values of the ambient light intensity, the space where the light source is located and the current time.
4. A method for automatically adjusting a light source according to any one of claims 1-3, wherein the calculating an adjustment parameter of the light source based on each item of the environment information further comprises:
acquiring a color parameter table of the light source, and acquiring color adjusting values corresponding to the color of the ambient light, the space where the light source is located and the current time by referring to the color parameter table;
calculating color adjusting parameters of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
adjusting the color of the light source according to the color adjustment parameter.
5. The method of claim 4, wherein the color weight value of the ambient light color, the space where the light source is located, and the current time is obtained by:
establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
and calculating a neural network model and color adjusting values corresponding to the environment light color, the space where the light source is located and the current time based on the color weights, and obtaining the color weight values of the environment light color, the space where the light source is located and the current time.
6. An intelligent system capable of automatically adjusting a light source, comprising:
the environment light acquisition module is used for acquiring environment light parameters of an area where the light source is located, wherein the environment information comprises environment light intensity, environment light color, space where the light source is located and current time;
and the light source adjusting module is used for calculating adjusting parameters of the light source based on various pieces of environment information and adjusting the light source according to the adjusting parameters.
7. The intelligent system capable of automatically adjusting a light source according to claim 6, wherein the light source adjusting module specifically comprises:
the brightness adjustment value acquisition submodule acquires a brightness parameter table of the light source, and inquires the brightness parameter table to obtain brightness adjustment values corresponding to the ambient light intensity, the space where the light source is located and the current time;
the brightness adjusting parameter calculating submodule is used for acquiring the brightness weight values of the ambient light intensity, the space where the light source is located and the current time and calculating the brightness adjusting parameter of the light source based on the brightness weight values;
and the light source brightness adjusting submodule adjusts the brightness of the light source according to the brightness adjusting parameter.
8. The intelligent system for automatically adjusting a light source according to claim 7, further comprising:
the modeling module is used for establishing a brightness weight calculation neural network model of the ambient light intensity, the space where the light source is located and the current time through semi-supervised learning;
and the weight value calculating module is used for calculating brightness adjusting values corresponding to the neural network model, the ambient light intensity, the light source space and the current time based on the brightness weight, and obtaining the brightness weight values of the ambient light intensity, the light source space and the current time.
9. The intelligent system capable of automatically adjusting a light source according to claim 6, wherein the light source adjusting module specifically comprises:
the color adjusting value obtaining sub-module is used for obtaining a color parameter table of the light source and obtaining color adjusting values corresponding to the color of the environment light, the space where the light source is located and the current time by referring to the color parameter table;
the color adjusting parameter calculating submodule calculates the color adjusting parameter of the light source based on the color of the environment light, the space where the light source is located and the color weight value of the current time;
and the light source color adjusting submodule adjusts the color of the light source according to the color adjusting parameter.
10. The intelligent system for automatically adjusting a light source according to claim 9, further comprising:
the modeling module is used for establishing a color weight calculation neural network model of the ambient light color, the space where the light source is located and the current time through semi-supervised learning;
and the weight value calculating module is used for calculating color adjusting values corresponding to the neural network model, the environment light color, the light source space and the current time based on the color weight, and obtaining the color weight values of the environment light color, the light source space and the current time.
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Application publication date: 20210122 |