CN115175415A - Digital twinning light adjusting method, device and system - Google Patents
Digital twinning light adjusting method, device and system Download PDFInfo
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- H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
- H05B47/10—Controlling the light source
- H05B47/105—Controlling the light source in response to determined parameters
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Abstract
The application discloses a digital twin light adjusting method, device and system, and relates to the technical field of smart homes/smart families, wherein the method comprises the following steps: acquiring an indoor current scene image, current scene voice and current illumination intensity; determining an indoor user behavior recognition result based on the current scene image, and determining an indoor scene voice recognition result based on the current scene voice; judging the user behavior recognition result based on the scene voice recognition result, and determining an indoor user behavior judgment result; and determining the ideal illumination intensity corresponding to the user behavior discrimination result, and controlling indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity. The method, the device and the system improve the intelligent level of light adjustment and improve the comfort level of user living or working.
Description
Technical Field
The application relates to the technical field of smart homes/smart families, in particular to a digital twin light adjusting method, device and system.
Background
With the rapid development of science and technology, more and more intelligent devices are applied to family life to provide comfortable living environment for users.
At present, the demand of users for automatic adjustment of indoor light is more and more clear. In the existing family scene, when family members watch television in a living room in the noon, the indoor light is strong, the television is not clearly watched, and a user needs to wake up a voice assistant by voice to close a curtain or manually close the curtain; when a child reads a book under the desk lamp at night, the light intensity needs to be manually adjusted, so that the eyesight of the child is protected; when the child enters a sleep state at night, family members are required to check the state of the child and perform actions such as turning off the light, closing the curtain and the like.
The existing light adjusting method generally adopts a light sensor to identify the ambient light intensity, adjusts indoor light according to a preset threshold value, cannot meet the actual requirements of users, and is low in intelligence level and poor in experience.
Disclosure of Invention
The application provides a digital twin light adjusting method, device and system, which are used for solving the technical problems that the existing light adjusting method cannot meet the actual requirements of users, the intelligentization level is low, and the experience is poor.
The application provides a digital twinning light adjusting method, which comprises the following steps:
acquiring an indoor current scene image, current scene voice and current illumination intensity;
determining an indoor user behavior recognition result based on the current scene image, and determining an indoor scene voice recognition result based on the current scene voice;
judging the user behavior recognition result based on the scene voice recognition result, and determining the indoor user behavior judgment result;
and determining an ideal illumination intensity corresponding to the user behavior discrimination result, and controlling the indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
According to the digital twin light adjustment method provided by the application, the distinguishing of the user behavior recognition result based on the scene voice recognition result to determine the indoor user behavior distinguishing result comprises the following steps:
performing word segmentation and keyword extraction on the scene voice recognition result to obtain a keyword corresponding to the scene voice recognition result;
comparing the keywords with each preset keyword in a preset keyword library to determine a user behavior prediction result corresponding to the keywords; the preset keyword library comprises a plurality of preset keywords and a user behavior prediction result corresponding to each preset keyword;
and if the user behavior prediction result corresponding to the keyword is consistent with the user behavior identification result, determining the user behavior identification result as a user behavior judgment result.
According to the digital twin light adjustment method provided by the application, the determining of the ideal illumination intensity corresponding to the user behavior discrimination result includes:
identifying the user identity in the current scene image, and determining the user identity of the indoor user;
inputting the user identity and the user behavior discrimination result of the indoor user into an illumination intensity prediction model to obtain ideal illumination intensity corresponding to the user behavior discrimination result output by the illumination intensity prediction model;
the illumination intensity prediction model is obtained by training based on the sample user identity, the sample user behavior of the sample user identity and the sample illumination intensity corresponding to the sample user behavior.
According to the digital twin light adjustment method provided by the application, the controlling the indoor light adjustment device to adjust the indoor light intensity based on the ideal light intensity and the current light intensity comprises:
acquiring outdoor illumination intensity;
if the outdoor illumination intensity is greater than or equal to a preset illumination intensity threshold value, determining the opening and closing degree adjustment amount of the indoor shading equipment based on the difference value between the ideal illumination intensity and the current illumination intensity, and controlling the shading equipment to adjust the indoor illumination intensity based on the opening and closing degree adjustment amount;
if the outdoor illumination intensity is smaller than the preset illumination intensity threshold value, determining a power adjustment amount of the indoor lighting equipment based on a difference value between the ideal illumination intensity and the current illumination intensity, and controlling the lighting equipment to adjust the indoor illumination intensity based on the power adjustment amount.
According to the digital twin light adjusting method provided by the application, the step of controlling the indoor light adjusting device to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity comprises the following steps:
determining an active area of a user within the room based on the current scene image;
determining light ray adjusting equipment corresponding to the activity area based on the activity area and the corresponding relation between each indoor light ray adjusting equipment and each activity area;
and controlling light ray adjusting equipment corresponding to the active area to adjust the illumination intensity of the active area based on the ideal illumination intensity and the current illumination intensity.
According to the digital twin light adjustment method provided by the application, the distinguishing of the user behavior recognition result based on the scene voice recognition result to determine the indoor user behavior distinguishing result comprises the following steps:
if the scene voice recognition result is empty, sending a prompt voice containing a semantic filling slot;
receiving voice information input by a user based on the prompt voice;
and determining behavior keywords corresponding to the semantic filling grooves in the transcribed text based on the transcribed text of the voice information, and taking the behavior keywords as the indoor user behavior judgment result.
The present application provides a digital twinning light adjustment device, comprising:
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring indoor current scene images, current scene voices and current illumination intensity;
the recognition unit is used for determining an indoor user behavior recognition result based on the current scene image and determining an indoor scene voice recognition result based on the current scene voice;
the judging unit is used for judging the user behavior recognition result based on the scene voice recognition result and determining the indoor user behavior judging result;
and the adjusting unit is used for determining the ideal illumination intensity corresponding to the user behavior judging result and controlling the indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
The application provides a digital twinning light adjusting system, which comprises an image sensor, a sound pick-up, a light sensor, a light adjusting device and a digital twinning light adjusting device, wherein the image sensor is used for detecting the image of the image sensor;
the digital twinning light adjusting device is connected with the image sensor, the sound pick-up, the light sensor and the light adjusting equipment on the basis of a communication module;
the communication module comprises at least one of a Bluetooth module, a WIFI module, a 4G module and a 5G module.
The present application provides a computer-readable storage medium on which a computer program is stored, which computer program, when being executed by a processor, realizes the digital twinning light adjustment method.
The application provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the digital twinning light adjustment method.
According to the digital twinning light adjusting method, the device and the system, an indoor user behavior recognition result is determined according to a current scene image, and an indoor scene voice recognition result is determined according to a current scene voice; judging the user behavior recognition result according to the scene voice recognition result, and determining an indoor user behavior judgment result; the indoor light adjustment device comprises a light adjustment device, a scene image recognition device, a scene voice recognition device, a light adjustment device and a control device, wherein the light adjustment device is used for controlling the indoor light intensity according to the indoor user behavior discrimination result, the ideal illumination intensity corresponding to the user behavior discrimination result is determined according to the ideal illumination intensity and the current illumination intensity, the user behavior is obtained through scene image recognition and determined after discrimination by combining the scene voice, the high reliability is achieved, the actual requirements of a user in the current scene can be accurately reflected, meanwhile, the indoor light intensity is automatically adjusted in an adaptive mode according to the user behavior, manual participation of the user is not needed, the intelligent level of light adjustment is improved, and the comfort level of living or working of the user is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a digital twinning light adjustment method provided in the present application;
FIG. 2 is a schematic structural diagram of a digital twinning light adjustment apparatus provided in the present application;
FIG. 3 is a schematic structural diagram of a digital twinning light adjustment system provided in the present application;
FIG. 4 is a schematic diagram of the control logic of the digital twinning light adjustment system provided in the present application;
FIG. 5 is a hardware environment diagram of the digital twinning light adjustment method provided in the present application;
fig. 6 is a schematic structural diagram of an electronic device provided in the present application.
Reference numerals:
501: a terminal device; 502: and a server.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in this application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be implemented in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a schematic flowchart of a digital twinning light adjustment method provided in the present application, and as shown in fig. 1, the method includes step 110, step 120, step 130, and step 140.
And step 110, acquiring an indoor current scene image, current scene voice and current illumination intensity.
Specifically, the digital twinning light adjustment method provided by the embodiment of the application is suitable for light adjustment in a building room. The building room can be referred to as a room in a family place, including a living room, a bedroom, a study room and the like; the indoor space can also be referred to as an office space or a business space, and comprises a conference room, an office room, a movable room and the like. The execution subject of the digital twinning light regulation method is a digital twinning light regulation device. The digital twin light adjusting device can be a control device which is independently arranged, and can also be integrated with other indoor intelligent equipment, such as an intelligent sound box, an intelligent air conditioner, an intelligent refrigerator, an intelligent television, an intelligent lamp and the like.
The current scene image is an indoor environment image at the current moment. The current scene image records various indoor behaviors of each user at the current moment, including sleeping, reading books, watching television, moving and the like. The current scene image may be acquired by an image sensor provided indoors. The image sensor can be arranged indoors independently or in the intelligent device. If the output of the image sensor is a video stream, each frame of picture in the video stream can be used as a scene image.
The current scene voice is indoor environment voice at the current moment. The current scene voice records the voices, including the speaking voice and the reading voice of each user indoors, of each user and the program voice emitted by the intelligent television or the intelligent sound box, and the like, emitted by each user and each intelligent device at the current moment. The current scene voice can be acquired by a sound pickup provided indoors. The sound pickup can be arranged indoors independently, and can also be arranged in intelligent equipment.
The current illumination intensity is the indoor illumination intensity at the current moment. The current illumination intensity reflects the luminous flux of visible light received by the objects in the room. The current illumination intensity is closely related to the comfort level of the user. For example, when a user is watching television indoors, a smaller light intensity is often required; when a user is reading a book indoors, a greater intensity of illumination is typically required.
And step 120, determining an indoor user behavior recognition result based on the current scene image, and determining an indoor scene voice recognition result based on the current scene voice.
Specifically, the user behavior recognition result is a recognition result obtained by recognizing the indoor behavior of the user according to the scene image. For example, the user behavior recognition result may be sports, reading, watching television, sleeping, and the like.
The scene voice recognition result is a recognition result obtained by recognizing sound generated by indoor behaviors of the user according to the scene voice. For example, the scene speech recognition result may be background music without semantic meaning, semantic text corresponding to the speech sound of the user, and the like.
An artificial intelligence algorithm may be employed to perform behavior recognition on the current scene image or to perform speech recognition on the current scene speech. For example, for image behavior recognition, an iDT (advanced depth transactions) algorithm or the like may be employed; for the voice recognition, a DTW (Dynamic Time Warping) algorithm or the like may be employed.
And step 130, judging the user behavior recognition result based on the scene voice recognition result, and determining an indoor user behavior judgment result.
Specifically, the accuracy of the user behavior recognition result obtained only by the image recognition method is low, and the scene speech recognition result needs to be combined to distinguish the user behavior recognition result, so that a user behavior distinguishing result with higher accuracy is obtained. The user behavior judgment result is the user behavior result judged through the scene voice.
For example, when a user lies on a sofa in a living room and watches tv, if the current scene image is subjected to image recognition, the obtained user behavior recognition result may be watching tv or sleeping. And speech recognition is carried out on the current scene speech, and the obtained scene speech recognition result can be news reports, advertisements, TV plays and the like. And judging the user behavior recognition result according to the scene voice recognition result, and determining that the indoor user behavior judgment result is watching TV.
The discrimination method can adopt text similarity comparison. For example, the user behavior recognition result and the scene voice recognition result are compared in text similarity, if the text similarity is greater than or equal to a preset threshold, it is indicated that the user behavior recognition result is consistent with the scene voice recognition result, and the user behavior recognition result can be determined as a user behavior judgment result; if the text similarity is smaller than the preset threshold, it indicates that the user behavior recognition result is inconsistent with the scene voice recognition result, at this time, the user behavior recognition result cannot be determined as the user behavior discrimination result, and the user behavior discrimination result needs to be determined by combining information of other aspects, for example, the discrimination can be performed by adopting a voice query mode.
And 140, determining the ideal illumination intensity corresponding to the user behavior judgment result, and controlling indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
Specifically, the illumination intensity adjustment table may be set in advance. The corresponding relation between the user behavior and the ideal illumination intensity is recorded in the illumination intensity adjustment table. And after the indoor user behavior discrimination result is determined, inquiring the user behavior discrimination result in an illumination intensity adjustment table, and taking the ideal illumination intensity corresponding to the matched user behavior as the ideal illumination intensity corresponding to the user behavior discrimination result.
Comparing the ideal illumination intensity with the current illumination intensity to determine the adjustment amount of the illumination intensity. And generating the control quantity of the indoor light ray adjusting equipment according to the illumination intensity adjusting quantity, so as to control the light ray adjusting equipment and realize the adjustment of the indoor illumination intensity.
The light adjustment device may comprise a shading device and a lighting device. Shading devices include curtains, blinds and the like. The opening and closing degree of the curtain can be controlled by controlling the moving position of the curtain traction mechanism on the curtain guide rail, the luminous flux of natural light entering a room is increased or reduced, and the indoor illumination intensity is improved or reduced. The lighting equipment comprises various lamps and the like. The lighting intensity of the lamp can be controlled by increasing or decreasing the power of the lamp, so that the indoor illumination intensity can be increased or decreased.
The digital twin light adjusting method provided by the embodiment of the application determines an indoor user behavior recognition result according to a current scene image, and determines an indoor scene voice recognition result according to a current scene voice; judging the user behavior recognition result according to the scene voice recognition result, and determining an indoor user behavior judgment result; the indoor light adjustment device comprises a light adjustment device, a scene image recognition device, a scene voice recognition device, a light adjustment device and a control device, wherein the light adjustment device is used for controlling the indoor light intensity according to the indoor user behavior discrimination result, the ideal illumination intensity corresponding to the user behavior discrimination result is determined according to the ideal illumination intensity and the current illumination intensity, the user behavior is obtained through scene image recognition and determined after discrimination by combining the scene voice, the high reliability is achieved, the actual requirements of a user in the current scene can be accurately reflected, meanwhile, the indoor light intensity is automatically adjusted in an adaptive mode according to the user behavior, manual participation of the user is not needed, the intelligent level of light adjustment is improved, and the comfort level of living or working of the user is improved.
Based on the above embodiment, step 130 includes:
performing word segmentation and keyword extraction on the scene voice recognition result to obtain a keyword corresponding to the scene voice recognition result;
comparing the keywords with each preset keyword in a preset keyword library to determine a user behavior prediction result corresponding to the keywords; the preset keyword library comprises a plurality of preset keywords and a user behavior prediction result corresponding to each preset keyword;
and if the user behavior prediction result corresponding to the keyword is consistent with the user behavior identification result, determining the user behavior identification result as a user behavior judgment result.
Specifically, the scene voice recognition result may be a continuous character string having a certain length. In the character string, many nonsense words may be included, and the words are meaningless for the discrimination of the user behavior recognition result, so that the scene recognition result may be subjected to text processing, and the text processing method includes word segmentation, keyword extraction, and may also include noise word removal and the like.
The method is used for segmenting the scene voice recognition result, and aims to segment a longer text into words with independent meanings, so that the multiple meaning of one word is reduced as much as possible, and the data information is conveniently mined by a computer. The word segmentation method can comprise a forward maximum matching method, a reverse maximum matching method, a word segmentation algorithm based on an N-gram language model, a word segmentation algorithm based on sequence annotation and the like.
And extracting keywords from the scene voice recognition result, wherein the purpose is to extract subject words with rich semantics from the word segmentation result. The keyword extraction method may include TF-IDF (Term Frequency-Inverse Document method), textRank algorithm, and the like.
Before keyword extraction, noise word filtering can be carried out on the word segmentation result. For example, some nonsense linguistic words can be considered as noise words, and can be removed by adopting a text matching method.
After the keywords corresponding to the scene voice recognition result are obtained, the keywords can be compared with all preset keywords in a preset keyword library. The preset keyword library comprises a plurality of preset keywords and a user behavior prediction result corresponding to each preset keyword. For example, the preset keyword library may include "live report" or "local message", and the corresponding user behavior prediction result is watching television.
Here, the preset keyword library may also be established according to the needs of the user. For example, the user can set up a custom keyword according to the actual requirement of the user, and store the custom keyword and the user behavior prediction result in a preset keyword library in a correlated manner. When a user speaks indoors, the user can realize the purpose of adjusting indoor light by speaking the user-defined keywords. For example, the user may set a custom keyword "campaign," which is stored in association with the user behavior prediction result "campaign. When the digital twin light adjustment device detects that the scene voice recognition result contains "activity", it can be determined that the user behavior prediction result obtained from the scene voice recognition result is motion. And then, according to the user behavior prediction result, distinguishing the user behavior recognition result obtained by the scene image.
When the keyword corresponding to the scene speech recognition result is matched with the preset keyword, the user behavior prediction result corresponding to the preset keyword can be used as the user behavior prediction result corresponding to the keyword. And if the user behavior prediction result corresponding to the keyword is consistent with the user behavior identification result, determining the user behavior identification result as a user behavior judgment result.
According to the digital twinning light adjusting method, the user behavior prediction result is determined by performing word segmentation and keyword extraction on the scene voice recognition result and is used for judging the user behavior recognition result, so that the accuracy of user behavior judgment is improved, and the actual requirements of a user in the current scene can be accurately reflected.
Based on any of the above embodiments, step 140 includes:
identifying the user identity in the current scene image to determine the user identity of the indoor user;
inputting the user identity and the user behavior discrimination result of the indoor user into the illumination intensity prediction model to obtain ideal illumination intensity corresponding to the user behavior discrimination result output by the illumination intensity prediction model;
the illumination intensity prediction model is obtained by training based on the sample user, the sample user behaviors of the sample user and the sample illumination intensity corresponding to the sample user behaviors.
In particular, considering that the requirements of each user for the light intensity are different, establishing a light intensity prediction model may be adopted to provide personalized light adjustment services for each user. For example, when a user with an eye disease reads a book indoors, a higher light intensity may be required than an average person; still alternatively, older ones of the family members prefer higher light intensities, while comparable light intensities are uncomfortable for younger ones of the family members.
Therefore, the user identity in the current scene image can be identified, and the user identity of the indoor user can be determined. The user identity can be defined by the user to identify the role of the user in a home scene or an office scene. For example, in a home scenario, a user may define a user identity as { child, young, old }, or may define a user identity as { son, daughter, father, mom }.
The user identity recognition may adopt an artificial intelligence algorithm, for example, a convolutional neural network model is used as an initial model, a picture of a family member and a family member identity tag corresponding to the picture are used as samples, and the initial model is trained to obtain a family member identity recognition model. After the current scene image is input into the family member identity recognition model, the user identity of the indoor user can be obtained.
The ideal illumination intensity corresponding to the user behavior discrimination result can also be realized by adopting an artificial intelligence algorithm. The following description will be made with family members as users.
First, the preference of the illumination intensity of each family member under different behaviors can be collected in advance and sorted into a sample set. Specifically, each family member is used as a sample user, the identity of each family member is labeled to obtain the identity of the sample user, possible indoor behaviors of each family member are recorded, the behaviors are used as sample user behaviors, and the best illumination intensity experienced by each family member under different sample user behaviors is recorded as the sample illumination intensity.
And secondly, training by using the neural network model as an initial model and adopting the sample set obtained above, so as to improve the prediction capability of the initial model on ideal illumination intensity and obtain an illumination intensity prediction model.
And finally, inputting the user identity and the user behavior discrimination result of the indoor user, which are obtained through the current scene image and the current scene voice, into the illumination intensity prediction model, so as to obtain the ideal illumination intensity corresponding to the user behavior discrimination result output by the illumination intensity prediction model.
According to the digital twin light adjusting method, the personalized light adjusting service is provided for each user by establishing the illumination intensity prediction model, and the living or office comfort level of the user is improved.
Based on any of the above embodiments, step 140 includes:
acquiring outdoor illumination intensity;
if the outdoor illumination intensity is greater than or equal to the preset illumination intensity threshold, determining the opening and closing degree adjustment amount of the indoor shading equipment based on the difference between the ideal illumination intensity and the current illumination intensity, and controlling the shading equipment to adjust the indoor illumination intensity based on the opening and closing degree adjustment amount;
if the outdoor illumination intensity is smaller than the preset illumination intensity threshold value, determining the power adjustment amount of the indoor lighting equipment based on the difference value between the ideal illumination intensity and the current illumination intensity, and controlling the lighting equipment to adjust the indoor illumination intensity based on the power adjustment amount.
Specifically, for the adjustment of indoor light, two ways may be adopted, one is to control the shading device, and the other is to control the lighting device. The former can utilize natural light to accomplish the adjustment, and the latter needs the electric energy of consumption to accomplish the adjustment, has brought economic burden for the user, and the adjustment effect is not as better can improve user experience than natural light.
Outdoor illumination intensity can be collected. And setting a preset illumination intensity threshold value for measuring the intensity of outdoor natural light. The preset illumination intensity threshold may be set as desired.
If the outdoor illumination intensity is greater than or equal to the preset illumination intensity threshold value, it indicates that the outdoor natural light is sufficient, for example, the weather is clear, and the like, and the outdoor illumination intensity can be used for adjusting the indoor light. The adjustment amount of the opening and closing degree of the shading equipment (such as an intelligent curtain) can be determined according to the difference value between the ideal illumination intensity and the current illumination intensity, and the shading equipment is controlled to adjust the indoor illumination intensity. For example, the larger the difference between the ideal light intensity and the current light intensity is, the larger the amount of adjustment of the degree of opening and closing of the shading device is.
If the outdoor light intensity is smaller than the preset light intensity threshold value, it indicates that the outdoor natural light is insufficient, for example, cloudy days, and the like, and cannot be used for adjusting the indoor light. The power adjustment amount of the indoor lighting equipment can be determined according to the difference value between the ideal illumination intensity and the current illumination intensity, and the lighting equipment is controlled to adjust the indoor illumination intensity. For example, the greater the difference between the ideal illumination intensity and the current illumination intensity, the greater the amount of power adjustment of the lighting device.
According to the digital twinning light adjusting method, the power consumption is reduced, the economic burden of a user is reduced, and the user experience can be improved through the adjusting effect.
Based on any of the above embodiments, step 140 further includes:
determining an activity area of a user in a room based on a current scene image;
determining light ray adjusting equipment corresponding to the activity area based on the activity area and the corresponding relation between each indoor light ray adjusting equipment and each activity area;
and controlling light ray adjusting equipment corresponding to the active area to adjust the illumination intensity of the active area based on the ideal illumination intensity and the current illumination intensity.
Specifically, for a living room, when the area of the living room is large, there may be a plurality of groups of ceiling lamps, wall lamps, and the like, and each lamp is used for illuminating a partial area of the living room. For a large conference room, it is possible to provide a plurality of sets of luminaires, each for illuminating a respective part of the area of the conference room.
The room may be divided into a plurality of active areas. The size of the active area can be set as desired. Then, the indoor light adjusting devices are grouped, and the corresponding relation between each indoor light adjusting device and each activity area is determined.
According to the current scene image, the position of the user in the scene image can be determined, and the position corresponds to the indoor environment, so that the indoor activity area of the user is obtained. And determining the light ray adjusting equipment corresponding to the activity area where the user is located according to the corresponding relation between each indoor light ray adjusting equipment and each activity area.
And then, controlling light ray adjusting equipment corresponding to the active area to adjust the illumination intensity of the active area according to the ideal illumination intensity and the current illumination intensity.
The digital twinning light adjusting method provided by the application enables a user to do not need to illuminate the whole indoor space when the user moves indoors, and only needs to illuminate the moving area where the user is located, so that the purposes of energy conservation and consumption reduction are achieved.
Based on any of the above embodiments, step 130 includes:
if the scene voice recognition result is empty, sending a prompt voice containing a semantic filling slot;
receiving voice information input by a user based on the prompt voice;
and determining behavior keywords corresponding to the semantic filling grooves in the transcribed text based on the transcribed text of the voice information, and taking the behavior keywords as indoor user behavior judgment results.
Specifically, under the condition that the current scene voice recognition fails, the scene voice recognition result is empty, the user behavior recognition result cannot be determined as the user behavior discrimination result, and a voice query mode can be adopted for discrimination.
The semantic filling slot is an attribute which is clearly defined by the entity and can be used as information to be complemented in the conversation. The digital twinning light adjustment device may send a user a prompt voice containing a semantically filled groove. For example, a digital twin light adjustment device may send "what you are currently doing" with the semantics filling the slot "what is doing".
And the digital twin light adjusting device receives voice information input by a user according to the prompt voice, transcribes the voice information and obtains a transcribed text. And detecting the transcribed text according to the content of the semantic filling slot to obtain a behavior keyword corresponding to the semantic filling slot, and taking the behavior keyword as a user behavior judgment result.
For example, the voice information of the user is "i'm reading", the voice information is converted into characters, similarity matching is performed between words in the characters and the semantic filling slot, and a behavior keyword "reading" corresponding to the semantic filling slot "what is done" is obtained. According to the digital twin light adjustment method, the user behavior discrimination result is determined by adopting a voice query mode, the defect of scene voice recognition is overcome, and the intelligent level of light adjustment is improved.
Based on any of the above embodiments, fig. 2 is a schematic structural diagram of a digital twinning light adjustment device provided in the present application, as shown in fig. 2, the device includes:
an obtaining unit 210, configured to obtain an indoor current scene image, a current scene voice, and a current illumination intensity;
the recognition unit 220 is configured to determine an indoor user behavior recognition result based on the current scene image, and determine an indoor scene voice recognition result based on the current scene voice;
a distinguishing unit 230, configured to distinguish a user behavior recognition result based on a scene speech recognition result, and determine an indoor user behavior distinguishing result;
and an adjusting unit 240, configured to determine an ideal illumination intensity corresponding to the user behavior determination result, and control an indoor light adjusting device to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
The digital twin light adjusting device provided by the embodiment of the application determines an indoor user behavior recognition result according to a current scene image, and determines an indoor scene voice recognition result according to current scene voice; judging the user behavior recognition result according to the scene voice recognition result, and determining an indoor user behavior judgment result; the indoor light adjustment device comprises a light adjustment device, a scene image recognition device, a scene voice recognition device, a light adjustment device and a control device, wherein the light adjustment device is used for controlling the indoor light intensity according to the indoor user behavior discrimination result, the ideal illumination intensity corresponding to the user behavior discrimination result is determined according to the ideal illumination intensity and the current illumination intensity, the user behavior is obtained through scene image recognition and determined after discrimination by combining the scene voice, the high reliability is achieved, the actual requirements of a user in the current scene can be accurately reflected, meanwhile, the indoor light intensity is automatically adjusted in an adaptive mode according to the user behavior, manual participation of the user is not needed, the intelligent level of light adjustment is improved, and the comfort level of living or working of the user is improved.
Based on any of the above embodiments, the determination unit is specifically configured to:
performing word segmentation and keyword extraction on the scene voice recognition result to obtain a keyword corresponding to the scene voice recognition result;
comparing the keywords with all preset keywords in a preset keyword library to determine a user behavior prediction result corresponding to the keywords; the preset keyword library comprises a plurality of preset keywords and a user behavior prediction result corresponding to each preset keyword;
and if the user behavior prediction result corresponding to the keyword is consistent with the user behavior identification result, determining the user behavior identification result as a user behavior judgment result.
Based on any of the embodiments above, the adjusting unit is specifically configured to:
identifying the user identity in the current scene image to determine the user identity of the indoor user;
inputting the user identity and the user behavior discrimination result of the indoor user into the illumination intensity prediction model to obtain ideal illumination intensity corresponding to the user behavior discrimination result output by the illumination intensity prediction model;
the illumination intensity prediction model is obtained by training sample user behaviors based on the sample user identities and sample illumination intensities corresponding to the sample user behaviors.
Based on any of the above embodiments, the adjusting unit is further specifically configured to:
acquiring outdoor illumination intensity;
if the outdoor illumination intensity is greater than or equal to the preset illumination intensity threshold, determining the opening and closing degree adjustment amount of the indoor shading equipment based on the difference between the ideal illumination intensity and the current illumination intensity, and controlling the shading equipment to adjust the indoor illumination intensity based on the opening and closing degree adjustment amount;
if the outdoor illumination intensity is smaller than the preset illumination intensity threshold value, determining the power adjustment amount of the indoor lighting equipment based on the difference value between the ideal illumination intensity and the current illumination intensity, and controlling the lighting equipment to adjust the indoor illumination intensity based on the power adjustment amount.
Based on any of the above embodiments, the adjusting unit is further specifically configured to:
determining an activity area of a user in a room based on a current scene image;
determining light ray adjusting equipment corresponding to the activity area based on the activity area and the corresponding relation between each indoor light ray adjusting equipment and each activity area;
and controlling light ray adjusting equipment corresponding to the active area to adjust the illumination intensity of the active area based on the ideal illumination intensity and the current illumination intensity.
Based on any embodiment above, the apparatus further comprises:
the voice query unit is used for sending prompt voice containing a semantic filling slot if the scene voice recognition result is empty;
receiving voice information input by a user based on prompt voice;
and determining behavior keywords corresponding to the semantic filling grooves in the transcribed text based on the transcribed text of the voice information, and taking the behavior keywords as indoor user behavior judgment results.
Based on any of the above embodiments, fig. 3 is a schematic structural diagram of a digital twinning light adjustment system provided in the present application, as shown in fig. 3, the system includes an image sensor 310, a sound pickup 320, a light sensor 330, a light adjustment device 340, and a digital twinning light adjustment apparatus 350;
the digital twin light adjusting apparatus 350 is connected with the image sensor 310, the sound pickup 320, the light sensor 330 and the light adjusting device 340 based on the communication module 360; the communication module 360 includes at least one of a bluetooth module, a WIFI module, a 4G module and a 5G module.
Specifically, fig. 4 is a schematic diagram of a control logic of the digital twinning light adjustment system provided in the present application, and as shown in fig. 4, the control logic of the digital twinning light adjustment system is as follows:
and step 410, acquiring current environment video stream data through an image sensor, acquiring current environment light intensity through a light sensor, and acquiring current environment user audio information through a sound pick-up.
And step 420, identifying and classifying the family scene where the user is located through a deep learning technology according to the image acquisition information.
And step 430, combining the multi-frame video stream information, and preliminarily judging the current behavior of the user (watching television in a living room, reading under a desk lamp, sleeping in a bedroom and the like) through the user behavior identification model.
And step 440, combining the voice recognition information to assist in judging the user behavior. For example, when watching tv in a living room, sounds such as advertisements and dramas appear; when reading under the desk lamp, reading sound or no sound is generated; when sleeping in a bedroom, the sleeping pillow is basically silent.
And 450, establishing an optimal light intensity model of the user behavior based on the digital twinning technology, and actively judging whether the light needs to be adjusted to meet the user behavior requirement according to the light intensity information returned by the light sensor.
Step 460, if the light needs to be adjusted, the light adjusting device (desk lamp, curtain, ceiling lamp, lamp strip, etc.) is linked to actively adjust the ambient light to the optimal experience of the user.
The digital twin light adjustment system provided by the embodiment of the application can automatically adjust the indoor illumination intensity according to the user behavior without manual participation of a user, improves the intelligent level of light adjustment, and improves the comfort level of user living or working.
Based on any of the above embodiments, the present application further provides a digital twinning light adjustment method. The digital twin light adjusting method is widely applied to full-House intelligent digital control application scenes such as intelligent homes (Smart Home), intelligent homes, intelligent household equipment ecology, intelligent residence ecology and the like. In this embodiment, fig. 5 is a schematic diagram of a hardware environment of the digital twinning light adjustment method provided in this application, and the digital twinning light adjustment method can be applied to the hardware environment formed by the terminal device 501 and the server 502 shown in fig. 5. The server 502 is connected to the terminal device 501 through a network, and may be configured to provide a service (e.g., an application service) for the terminal or a client installed on the terminal, set a database on the server or separately from the server, and provide a data storage service for the server 502, and configure a cloud computing and/or edge computing service on the server or separately from the server, and provide a data operation service for the server 502.
The network may include, but is not limited to, at least one of: wired networks, wireless networks. The wired network may include, but is not limited to, at least one of: wide area networks, metropolitan area networks, local area networks, which may include, but are not limited to, at least one of the following: WIFI (Wireless Fidelity), bluetooth. Terminal equipment 501 can be but not limited to PC, the cell-phone, the panel computer, intelligent air conditioner, intelligent cigarette machine, intelligent refrigerator, intelligent oven, intelligent kitchen range, intelligent washing machine, intelligent water heater, intelligent washing equipment, intelligent dish washer, intelligent projection equipment, intelligent TV, intelligent clothes hanger, intelligent (window) curtain, intelligence audio-visual, smart jack, intelligent stereo set, intelligent audio amplifier, intelligent new trend equipment, intelligent kitchen guarding equipment, intelligent bathroom equipment, intelligence robot of sweeping the floor, intelligence robot of wiping the window, intelligence robot of mopping the ground, intelligent air purification equipment, intelligent steam ager, intelligent microwave oven, intelligent kitchen treasure, intelligent clarifier, intelligent water dispenser, intelligent lock etc..
Based on any one of the above embodiments, fig. 6 is a schematic structural diagram of an electronic device provided in the present application, and as shown in fig. 6, the electronic device may include: a Processor (Processor) 610, a communication Interface (Communications Interface) 620, a Memory (Memory) 630 and a communication Bus (Communications Bus) 640, wherein the Processor 610, the communication Interface 620 and the Memory 630 complete communication with each other through the communication Bus 640. The processor 610 may call logical commands in the memory 630 to perform the following method:
acquiring an indoor current scene image, current scene voice and current illumination intensity; determining an indoor user behavior recognition result based on the current scene image, and determining an indoor scene voice recognition result based on the current scene voice; judging the user behavior recognition result based on the scene voice recognition result, and determining an indoor user behavior judgment result; and determining the ideal illumination intensity corresponding to the user behavior discrimination result, and controlling indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
In addition, the logic commands in the memory 630 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic commands are sold or used as independent products. Based on such understanding, the technical solutions of the present application, or portions thereof, which substantially or partly contribute to the prior art, may be embodied in the form of a software product, which is stored in a storage medium and includes several commands for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The processor in the electronic device provided in the embodiment of the present application may call a logic instruction in a memory to implement the method, and a specific implementation manner of the method is consistent with the implementation manner of the method, and may achieve the same beneficial effects, which are not described herein again.
The embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to execute the methods provided by the foregoing embodiments.
The specific implementation manner is the same as the implementation manner of the method, and the same beneficial effects can be achieved, which is not described herein again.
Embodiments of the present application provide a computer program product, comprising a computer program, which when executed by a processor, implements the method as described above.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A digital twinning light adjustment method, comprising:
acquiring an indoor current scene image, current scene voice and current illumination intensity;
determining an indoor user behavior recognition result based on the current scene image, and determining an indoor scene voice recognition result based on the current scene voice;
judging the user behavior recognition result based on the scene voice recognition result, and determining the indoor user behavior judgment result;
and determining the ideal illumination intensity corresponding to the user behavior discrimination result, and controlling the indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
2. The digital twin light adjustment method according to claim 1, wherein the determining the user behavior recognition result based on the scene speech recognition result and determining the indoor user behavior recognition result includes:
performing word segmentation and keyword extraction on the scene voice recognition result to obtain a keyword corresponding to the scene voice recognition result;
comparing the keywords with each preset keyword in a preset keyword library to determine a user behavior prediction result corresponding to the keywords; the preset keyword library comprises a plurality of preset keywords and a user behavior prediction result corresponding to each preset keyword;
and if the user behavior prediction result corresponding to the keyword is consistent with the user behavior recognition result, determining the user behavior recognition result as a user behavior judgment result.
3. The method as claimed in claim 1 or 2, wherein the determining the ideal illumination intensity corresponding to the user behavior determination result comprises:
identifying the user identity in the current scene image, and determining the user identity of the indoor user;
inputting the user identity and the user behavior discrimination result of the indoor user into an illumination intensity prediction model to obtain an ideal illumination intensity corresponding to the user behavior discrimination result output by the illumination intensity prediction model;
the illumination intensity prediction model is obtained by training based on the identity of a sample user, the behavior of the sample user of the identity of the sample user and the illumination intensity of the sample corresponding to the behavior of the sample user.
4. The digital twinning light adjustment method of claim 1 or 2, wherein the controlling the indoor light adjustment device to adjust the indoor light intensity based on the ideal light intensity and the current light intensity comprises:
acquiring outdoor illumination intensity;
if the outdoor illumination intensity is greater than or equal to a preset illumination intensity threshold value, determining the opening and closing degree adjustment amount of the indoor shading equipment based on the difference value between the ideal illumination intensity and the current illumination intensity, and controlling the shading equipment to adjust the indoor illumination intensity based on the opening and closing degree adjustment amount;
if the outdoor illumination intensity is smaller than the preset illumination intensity threshold value, determining a power adjustment amount of the indoor lighting equipment based on a difference value between the ideal illumination intensity and the current illumination intensity, and controlling the lighting equipment to adjust the indoor illumination intensity based on the power adjustment amount.
5. The digital twinning light adjustment method of claim 1 or 2, wherein the controlling the light adjustment device in the room to adjust the illumination intensity in the room based on the ideal illumination intensity and the current illumination intensity comprises:
determining an active area of a user within the room based on the current scene image;
determining light ray adjusting equipment corresponding to the activity area based on the activity area and the corresponding relation between each indoor light ray adjusting equipment and each activity area;
and controlling light ray adjusting equipment corresponding to the active area to adjust the illumination intensity of the active area based on the ideal illumination intensity and the current illumination intensity.
6. The digital twin light adjustment method according to claim 1 or 2, wherein the determining the user behavior recognition result based on the scene speech recognition result and determining the indoor user behavior recognition result includes:
if the scene voice recognition result is empty, sending a prompt voice containing a semantic filling slot;
receiving voice information input by a user based on the prompt voice;
and determining behavior keywords corresponding to the semantic filling grooves in the transcribed text based on the transcribed text of the voice information, and taking the behavior keywords as the indoor user behavior judgment result.
7. A digital twinning light adjustment device, comprising:
the device comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring an indoor current scene image, current scene voice and current illumination intensity;
the recognition unit is used for determining an indoor user behavior recognition result based on the current scene image and determining an indoor scene voice recognition result based on the current scene voice;
the judging unit is used for judging the user behavior recognition result based on the scene voice recognition result and determining the indoor user behavior judging result;
and the adjusting unit is used for determining the ideal illumination intensity corresponding to the user behavior judging result and controlling the indoor light adjusting equipment to adjust the indoor illumination intensity based on the ideal illumination intensity and the current illumination intensity.
8. A digital twinning light adjustment system, comprising an image sensor, a sound pick-up, a light sensor, a light adjustment device, and a digital twinning light adjustment apparatus as claimed in claim 7;
the digital twin light adjusting device is connected with the image sensor, the sound pick-up, the light sensor and the light adjusting equipment on the basis of a communication module;
the communication module comprises at least one of a Bluetooth module, a WIFI module, a 4G module and a 5G module.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the digital twinning light adjustment method according to any one of claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the digital twinning light adjustment method of any of claims 1 to 6 when executing the program.
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