Classroom light environment dynamic adjusting system based on multi-source information perception

Abstract

The invention relates to the technical field of classroom light environment adjustment, and discloses a classroom light environment dynamic adjustment system based on multi-source information perception, and the system comprises an identification module which is used for identifying a light source, generating light source data, and collecting refraction data, site data and personnel data. The prediction module judges a light scene through the site data, the personnel data and the historical data, the prediction module calculates, screens and generates a first adjustment scheme in combination with the refraction data, the light scene, the light source data and the historical data, and the adjustment module analyzes and executes the first adjustment scheme so as to change the position, the angle, the brightness and the color temperature of the light source. According to the invention, the monitoring module and the identification module can determine the dark environment in which people are located so as to determine the end time of the dark environment, so that the dark environment adjustment scheme is transmitted to the adjustment module when the dark environment ends, and the adjustment module can dynamically adjust the classroom light source in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of classroom light environment regulation, and specifically provides a dynamic classroom light environment regulation system based on multi-source information perception. Background Art

[0002] The physiological and psychological environment related to the room shape established indoors by light (illuminance level and distribution, lighting form) and color (hue, color saturation, indoor color distribution, color rendering). People understand the world through hearing, vision, smell, taste, and touch. 80% of the information obtained comes from vision caused by light, and the light environment also has a positive impact on people's mental state and psychological feelings. For example, in production, work, and study places, a good light environment can boost morale, improve work efficiency and product quality; in public places for rest and entertainment, a suitable light environment can create a comfortable, elegant, lively or solemn atmosphere. Among them, the classroom light environment needs to meet national standards and balance function and health.

[0003] The existing classroom light environment can only be judged after detection by a light sensor and cannot pre-perceive and make corresponding adjustments in advance. For example, when the weather changes from sunny to cloudy and then back to sunny, after the light sensor detects it, it will send a signal to change the light source inside the classroom. At this time, the people inside the classroom will have their pupils change rapidly due to the rapid change of light, which is not conducive to human health. A stable light rhythm helps maintain the normal development of the eyeballs, while the disorder of the light rhythm may interfere with the refractive development process of the eyeballs. Secondly, the existing indoor light environment regulation system cannot change the classroom light environment in advance according to the upcoming actions of classroom personnel. For example, when classroom personnel need to do eye exercises and need to close their eyes for a period of time, when they open their eyes after completing the eye exercises, the external lights will stimulate their eyes. Therefore, the existing classroom light environment regulation system cannot dynamically regulate the classroom light environment in real time. Summary of the Invention

[0004] The present invention provides a dynamic classroom light environment regulation system based on multi-source information perception, which has the beneficial effect of dynamically adjusting the light environment and solves the problems of unstable adjustment of the light environment and inability to dynamically adjust the light environment mentioned in the above background art.

[0005] The present invention provides the following technical solution: A dynamic classroom light environment regulation system based on multi-source information perception, comprising:

[0006] An identification module, which is used to identify the light source, generate light source data, and collect refraction data, site data, and personnel data;

[0007] A prediction module, which determines the lighting scene through site data, personnel data, and historical data;

[0008] The prediction module combines refraction data, lighting scenarios, light source data, and historical data to calculate, screen, and generate a first adjustment plan;

[0009] An adjustment module that parses and executes the first adjustment plan to change the position, angle, brightness, and color temperature of the light source;

[0010] A monitoring module that is used to monitor refraction data, site data, personnel data, and light source data in real time;

[0011] Set a light source threshold, and dynamically adjust the light source threshold according to the personnel data, refraction data, light source data, and site data;

[0012] When the dynamically adjusted light source threshold is exceeded, the monitoring module feeds back to the prediction module, and the prediction module optimizes the first adjustment plan to generate a second adjustment plan, which is parsed and executed by the adjustment module;

[0013] Set a dark environment duration threshold, and the monitoring module determines whether the personnel data exceeds the dark environment duration threshold. When the dark environment duration threshold is exceeded, a dark environment adjustment plan is calculated, screened, and generated by the prediction module and historical data, and the dark environment adjustment plan is parsed and executed by the adjustment module.

[0014] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: the lighting scenarios include teaching scenarios, demonstration scenarios, and self-study scenarios;

[0015] The prediction module collects the teaching content of the day to locate the position of the textbook chapter, thereby determining the teaching content of tomorrow, and combines the historical data to determine whether the teaching content of tomorrow is a teaching scenario and / or a demonstration scenario, a self-study scenario.

[0016] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: a three-dimensional model of the classroom is preset in the prediction module;

[0017] Establish a character model according to the personnel data and import it into the three-dimensional model of the classroom;

[0018] The images captured by the recognition module correct the image data through the three-dimensional model of the classroom and the character model, thereby accurately determining the light source data, and optimizing the first adjustment plan, the second adjustment plan, and the dark environment adjustment plan according to the accurately determined light source data.

[0019] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: establish a safe light source range table of the personnel data according to the light source data, and use the MEDIAN function to calculate the median value of the first safe light source range table;

[0020] The prediction module predicts and further optimizes the light source data based on weather data combined with historical data, and the further optimized light source data establishes a second safe light source range table for the personnel data and obtains the median value of the second safe light source range table;

[0021] Optimize the second adjustment plan according to the median value of the first safe light source range table and the median value of the second safe light source range table to adapt to each person.

[0022] As an alternative solution of the classroom light environment dynamic adjustment system based on multi-source information perception according to the present invention, wherein: determine the light source adjustment range according to the median value of the first safe light source range table and the median value of the second safe light source range table, and the light source adjustment range adopts zonal light control and stepped adjustment;

[0023] The zonal light control includes dividing bright and dark intensity areas according to site data and personnel data, and sequentially adjusting the dark intensity area and the bright intensity area;

[0024] The stepped adjustment includes determining the lightness threshold according to the personnel data, and gradually adjusting the light source by combining the light source adjustment range and the time node through the lightness threshold.

[0025] As an alternative solution of the classroom light environment dynamic adjustment system based on multi-source information perception according to the present invention, wherein: the recognition module includes a light sensor and a camera;

[0026] The prediction module combines weather data to determine the natural light transformation in each time period and generates determination data;

[0027] Based on the determination data, preset the parameters of the camera to adapt to the light change caused by the weather change;

[0028] Further optimize the second adjustment plan through the determination data.

[0029] As an alternative solution of the classroom light environment dynamic adjustment system based on multi-source information perception according to the present invention, wherein: the light source includes natural light and non-natural light;

[0030] The light sensor is used to detect the natural light and non-natural light in the classroom and record the data of the natural light and non-natural light;

[0031] The monitoring module stores the light source value of the non-natural light, compares the data of the non-natural light with the stored light source value of the non-natural light, determines whether there is light source light decay and excessive stroboscopic, and modifies the stored light source value of the non-natural light. The second adjustment plan adjusts the light source according to the modified stored light source value of the non-natural light;

[0032] Among them, determine the light source position of the stroboscopic overshoot and light source attenuation for communication maintenance.

[0033] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: the detection module determines the change of personnel data according to the personnel model and the captured image of the recognition module, and adjusts the second adjustment plan accordingly.

[0034] The change of the personnel data includes personnel seat adjustment, personnel shortage and personnel physiological change.

[0035] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: the prediction module is used to collect sounds and determine personnel behaviors through big data analysis in combination with historical data, and assist in determining the lighting scene.

[0036] As an alternative solution of the classroom light environment dynamic regulation system based on multi-source information perception according to the present invention, wherein: determine the personnel eye use data according to the recognition module and the monitoring module, and the personnel eye use data includes eye use time and eye use angle.

[0037] Set a threshold value for eye fatigue. When the eye use time exceeds the threshold value of eye fatigue, prompt the personnel through the prompt module, and correct the personnel's eye use angle through the historical data.

[0038] The present invention has the following beneficial effects:

[0039] 1. For the classroom light environment dynamic regulation system based on multi-source information perception, the monitoring module and the recognition module determine what kind of dark environment the personnel are in, and predict the end time of the dark environment. Then, transmit the dark environment adjustment plan to the adjustment module before the end of the dark environment, so that the adjustment module can dynamically adjust the classroom light source in real time.

[0040] 2. For the classroom light environment dynamic regulation system based on multi-source information perception, the monitoring module captures relevant words about teaching aids demonstration in the teaching content, and the recognition module captures the courseware content displayed on the multimedia display screen to determine that a teaching demonstration is about to be carried out. When the monitoring module and the recognition module determine that a teaching aid demonstration is about to be carried out, adjust the classroom light source, and then close the curtains, so that the light in the student area is dim in the demonstration scene, and the classroom demonstration area is illuminated by downlights to demonstrate the teaching aids. The spotlight chases and follows according to the operating principle of the demonstration teaching aid and focuses on lighting, so as to improve the teaching demonstration effect in the demonstration scene.

[0041] 3. The classroom light environment dynamic adjustment system based on multi-source information perception collects the light source data of the images in the distance captured by the camera through the light sensor, and uses this to assist in modifying part of the light data in the simulated classroom lighting model. Subsequently, the light data of the simulated classroom lighting model that has been modified twice is used to correct the camera image, so that the data in the distance of the camera image fits the real situation. In this way, the second adjustment plan obtained through screening and calculation is more suitable for the classroom light environment, making the eyes of the classroom personnel more comfortable. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic flowchart of the system of the present invention.

[0043] Figure 2 It is a display diagram of the three-dimensional model of the classroom of the system of the present invention.

[0044] Figure 3 It is the first display diagram of the system of the present invention.

[0045] Figure 4 It is the second display diagram of the system of the present invention.

[0046] Figure 5 It is the third display diagram of the system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Embodiment 1

[0049] Please refer to Figures 1 - 5 , in which a classroom light environment dynamic adjustment system based on multi-source information perception includes:

[0050] An identification module for identifying a light source, generating light source data, and collecting refraction data, site data, and personnel data;

[0051] A prediction module for determining a lighting scenario through site data, personnel data, and historical data;

[0052] The prediction module combines refraction data, lighting scenario, light source data, and historical data to calculate, screen, and generate a first adjustment plan;

[0053] An adjustment module for parsing and executing the first adjustment plan to change the position, angle, brightness, and color temperature of the light source;

[0054] Monitoring module, which is used to monitor refraction data, site data, personnel data, and light source data in real time;

[0055] Set a light source threshold value, and dynamically adjust the light source threshold value according to personnel data, refraction data, light source data, and site data;

[0056] When the dynamically adjusted light source threshold value is exceeded, the monitoring module feeds back to the prediction module, optimizes the first adjustment plan through the prediction module to generate a second adjustment plan, and parses and executes the second adjustment plan through the adjustment module;

[0057] Set a dark environment duration threshold value. The monitoring module determines whether the personnel data exceeds the dark environment duration threshold value. When the dark environment duration threshold value is exceeded, a dark environment adjustment plan is calculated and screened through the prediction module and historical data, and the dark environment adjustment plan is parsed and executed through the adjustment module.

[0058] The recognition module includes a camera and a light sensor, and uses the recognition module to confirm the current light source coordinates;

[0059] By inputting the data of the purchased light source into the recognition module, where the purchased light source data includes luminous intensity, luminous flux, color temperature, color rendering index, viewing angle, lumen, wattage, light decay value data, brightness data, where the light decay value data, brightness data is obtained by calculation;

[0060] The position of the light source in the site is photographed by the camera to determine the coordinates of the light source position. The light source includes natural light and non-natural light. The non-natural light includes lamps and displays. The cooperation of the camera and the light sensor is used to assist in calculating the brightness of the light source. The specific calculation method is as follows:

[0061] The camera captures photon signals through the image sensor CMOS, converts them into electrical signals, and then outputs RGB data. In the automatic exposure technology, the RGB data output by the sensor is converted into the YUV color space. Among them, the luminance component Y accounts for 93% of the weight and is used to represent the overall brightness of the picture. Brightness The formula is:

[0062]

[0063] Among them, is the average image brightness value;

[0064] is the aperture value (f / number). The smaller the aperture (the larger the value), the lower the light input;

[0065] is the shutter speed (seconds). The longer the time, the more photons the sensor receives;

[0066] is the system transmittance, usually 0.85 - 0.95, which is determined by the lens coating and the light transmittance of the sensor protective layer;

[0067] is the sensor sensitivity, calibrated by the manufacturer;

[0068] Among them, The calculation formula of is:

[0069] k is the linear response coefficient, and E is the illuminance received by the sensor;

[0070] Subsequently, calculate the light attenuation values of non-natural light at each distance node from the starting position to the ground of the site data, and the calculation formula is:

[0071]

[0072] is the maintenance factor, generally taken as 0.7 - 0.8;

[0073] is the light intensity of the light source;

[0074] is the distance height node;

[0075] By inputting the refraction data of school uniforms, desks and chairs, blackboards, walls, floors, and glass of personnel into the recognition module;

[0076] By inputting site data into the recognition module, and the site data includes site size data and building data;

[0077] By inputting personnel data into the recognition module, and the personnel data includes the names of students and teachers, students' heights, and students' faces;

[0078] Among them, the historical data includes the teaching content of the previous year, the courseware and demonstration teaching aids matching the teaching content, and the lighting layout of the courseware matching the teaching content;

[0079] The prediction module is used to collect sounds and determine personnel behaviors through big data analysis in combination with historical data to assist in determining the lighting scene;

[0080] It also includes a microphone to collect the conversations between teachers and students in the classroom through the microphone, predict the teaching content of tomorrow based on the conversation content and in combination with historical data, so as to determine the lighting scene of the teaching content of tomorrow. For example, if the conversation contains words such as the number of pages to be previewed at night and the teaching aids to be demonstrated tomorrow and in combination with the teaching courseware, the lighting requirements for the teaching aid demonstration scene tomorrow can be determined;

[0081] Further, to improve accuracy, the communication teacher confirms whether the predicted teaching content and / or demonstration teaching aids are correct. When the prediction is incorrect, the teacher manually makes changes;

[0082] Among them, natural light includes the natural light data generated by the light irradiation from sunny days, cloudy days, overcast days, and rainy days to the outside of the classroom. The light source data contains natural light data;

[0083] Subsequently, the prediction module combines the refraction data, lighting scene, light source data, and the lighting layout of the teaching content courseware in the historical data to calculate and screen appropriate light data through an algorithm, so as to generate a first adjustment plan to change the position, angle, brightness, and color temperature of the current light source;

[0084] The average illuminance on the desk surface ≥ 300 lx, and the illuminance uniformity ≥ 0.7;

[0085] The maintained average illuminance of the blackboard lighting ≥ 500 lx, and the uniformity ≥ 0.8;

[0086] The color temperature is selected as 3000K - 5500K;

[0087] Spotlights and ceiling lights are selected. The ceiling lights provide large - scale lighting, and the spotlights provide key - area lighting. The appropriate number of spotlights, downlights, and ceiling lights is selected according to the classroom structure;

[0088] Among them, the calculation formulas of the first adjustment plan, the second adjustment plan, and the dark - environment adjustment plan are selected from genetic algorithms, big - data algorithms, ant algorithms, etc. that can screen data;

[0089] The big - data algorithm is used to screen the optimal lighting combination of similar scenarios from tens of thousands of courseware through cluster analysis, so as to achieve rapid data screening;

[0090] The genetic algorithm is more suitable for the lighting layout optimization requirements of small samples, multiple constraints, and strong domain knowledge in the teaching scenario;

[0091] Among them, the ant algorithm is especially suitable for the lighting optimization task of teaching scenarios that need to consider physical rules, historical experience, and dynamic response. It can simultaneously process continuous variables such as the color temperature, light intensity distribution, and beam angle of lamps, and generate a global optimal or approximate optimal solution;

[0092] The light source is connected to the electric slide rail. When the position of the light source needs to be changed, the light source is slid to change its position. Its lighting angle is changed by rotating the lamp body, and the color temperature and brightness are changed by switching the color - temperature and brightness modes;

[0093] When the first adjustment plan is executed the next day, the monitoring module monitors the refraction data, site data, personnel data, and light source data in real - time to verify the prediction results of the prediction module;

[0094] When there is a deviation between the monitoring data of the monitoring module and the data collected and predicted by the prediction module, the latest refraction data, site data, personnel data, and light source data are transmitted to the prediction module through the monitoring module, and the first adjustment plan is changed through the prediction module;

[0095] Since the external light environment is the same on sunny, cloudy, overcast and rainy days, the light source threshold perceived by the pupils of personnel under the influence of natural light is also different. In this regard, the prediction module calculates the second adjustment plan again based on the personnel data, refraction data, site data and light source data. Compared with the first adjustment plan, the second adjustment plan considers more detailed factors, and the light source after execution is more suitable for the classroom light environment of the day;

[0096] Furthermore, due to the changeable weather, natural light may change at any time. When the natural light has changed, the monitoring module will update the light source data to the prediction module, which will reduce the comfort of personnel in the classroom light environment. Therefore, cloud observation information and cloud layer characteristics information are obtained in real time with the help of tool software to predict cloud changes in each time period, so as to judge whether the weather will change in the future time period, so that the prediction module can prepare adjustment plans in advance;

[0097] It should be noted that the tool software includes Yuntiantong, Lijing Weather, and Aimeiyi, etc.

[0098] The dark environment duration is the time that a person is in a relatively dark environment. The dark environment duration threshold is set to 10-25 minutes. When the monitoring module cooperates with the recognition module to detect that a person is in a dark environment, the time that the person is in the dark environment is counted. When the dark environment duration threshold is exceeded, the prediction module calculates and filters to generate a dark environment adjustment plan.

[0099] It should be noted that the dark environment includes teaching aid demonstrations, eye exercises, lunch breaks, etc. Therefore, the monitoring module and the recognition module will determine what kind of dark environment the person is in, so as to determine the end time of the dark environment, and transmit the dark environment adjustment plan to the adjustment module before the end of the dark environment, so that the adjustment module can dynamically adjust the classroom light source in real time;

[0100] The dark environment adjustment solution is to adjust the light source to dim, and then adjust the brightness of the light source in a step-by-step manner, so that people can gradually adapt to the light source from dark to bright;

[0101] It should be noted that the classroom windows are equipped with electric curtains. When the end time of the dark environment is determined, the glass will be sealed with electric curtains to first isolate the natural light from the outside, and then the classroom light source will be adjusted in steps to adapt to natural light. Then the electric curtains will be slowly opened to achieve a natural connection between the classroom light source and natural light.

[0102] Example 2

[0103] This embodiment is an improvement based on Embodiment 1. Specifically, please refer to Figures 1 - 5 , and the light scenarios include teaching scenarios, demonstration scenarios, and self-study scenarios;

[0104] The prediction module collects the teaching content of the day to locate the position of the textbook chapter, thereby determining the teaching content of tomorrow, and determines whether it is a teaching scenario and / or a demonstration scenario, a self-study scenario through historical data;

[0105] The prediction module cooperates with the AI through the textbook content to determine the principle of the simulated teaching aid demonstration, compares the demonstration teaching aid through the recognition module, matches the demonstration details, and adjusts the light source according to the demonstration details to adapt to the demonstration.

[0106] The prediction module collects the teaching courseware content of the day, thereby locating the courseware that matches the teaching content in the history book, the demonstration teaching aid, and the lighting layout of the courseware that matches the teaching content. Subsequently, the prediction module locates the next teaching content of the teaching content, and determines the lighting scenario through the lighting layout of the courseware that matches the teaching content recorded in the historical data, thereby determining the light environment layout of tomorrow in advance and making adjustments in combination with the weather changes of tomorrow;

[0107] Demonstration scenario. When it is determined that a demonstration teaching aid is needed for tomorrow's teaching content, the demonstration teaching aid searches for the name of the demonstration teaching aid through the AI, thereby determining the operating principle of the demonstration teaching aid, decomposing the operating principle into several steps. Among them, each step completes an action, and searches for the key content of the operating principle of the demonstration teaching aid through the AI, marks several steps corresponding to the key content part in the operating principle, and incorporates several steps and the key-marked steps into the second adjustment plan;

[0108] Monitor the teaching content through the microphone, thereby using the monitoring module to capture the words related to the teaching aid demonstration in the teaching content, and capture the courseware content displayed on the multimedia display screen through the recognition module, thereby determining that a teaching demonstration is about to be carried out. When the monitoring module and the recognition module determine that a teaching aid demonstration is about to be needed, adjust the classroom light source, and then close the curtains, so as to achieve that the light in the student area is dim in the demonstration scenario, and the classroom demonstration area is irradiated by downlights to demonstrate the teaching aid, and the spotlight chases and focuses on illuminating according to the operating principle of the demonstration teaching aid, so as to improve the teaching demonstration effect in the demonstration scenario;

[0109] It should be noted that the brightness of the downlights above the demonstration teaching aid is lower than that of the spotlights, and the color temperatures of the downlights and the spotlights are not the same, so as to specifically show the key content in the operating principle of the demonstration teaching aid by irradiating the demonstration teaching aid with the spotlight.

[0110] Embodiment 3

[0111] This embodiment is an improvement made on the basis of Embodiment 2. Specifically, please refer to Figures 1 - 5 ; a three-dimensional classroom model is preset in the prediction module;

[0112] A human model is established according to the personnel data and imported into the three-dimensional classroom model;

[0113] The images captured by the recognition module correct the image data through the three-dimensional classroom model and the human model, so as to accurately obtain the light source data, and optimize the first adjustment plan, the second adjustment plan and the dark environment adjustment plan according to the accurate light source data.

[0114] Since a camera is used to assist the light sensor to determine the classroom light environment, but there is a problem of perspective distortion in camera shooting, that is, the images of distant objects are inaccurate when captured by the camera, resulting in errors in calculating the light source brightness and judging the brightness data of each distance node in Embodiment 1, and further causing the second adjustment plan to be unable to accurately adjust the classroom light environment;

[0115] In this regard, please refer to Figure 2 ; by cooperating the prediction module with 3D simulation lighting software, the three-dimensional classroom model and the human model are established in advance, and the indoor lighting data and positions are input into the 3D simulation lighting software to generate a simulated classroom lighting model. Then, the camera images are compared with the simulated classroom lighting model to determine the error data ratio between the camera images and the simulated classroom lighting model. Subsequently, the camera images are adjusted to correct the camera image data;

[0116] It should be particularly noted that the lighting data in the simulated classroom lighting model is theoretical data. Therefore, first compare the near images of the camera images. Since the camera contains an image sensor CMOS, the light source data of the near images is relatively accurate. Therefore, use the light source data of the near images as the starting part of the lighting data of the simulated classroom lighting model in the 3D simulation lighting software to modify the lighting data of the simulated classroom lighting model. Subsequently, collect the light source data of the distant images of the camera by the light sensor to assist in modifying some of the lighting data in the simulated classroom lighting model. Then, correct the camera images with the lighting data of the simulated classroom lighting model modified twice, so that the distant data of the camera images fits the real situation. In this way, the second adjustment plan obtained through screening and calculation is more suitable for the classroom light environment, making the eyes of classroom personnel more comfortable.

[0117] It should be particularly noted that the 3D simulation lighting software includes Light Tools (optical system modeling), Set ALight 3D Studio (photography lighting simulation), Lightscape, etc.

[0118] Further, since natural light shines obliquely, there will be a problem of inconsistent natural light in the front and rear areas of the classroom. Therefore, the tool software is used to judge whether the natural light will change in the future time period, and the camera and light sensor are used to determine the natural light intensity and illumination direction in the front and rear areas of the classroom. Then, the tool software predicts the future natural light data, and then imports the future natural light data into the 3D simulation lighting software, so as to further optimize and change the indoor light source through the prediction module.

[0119] Embodiment 4

[0120] This embodiment is an improvement based on Embodiment 3. Specifically, please refer to Figures 1 - 5 , establish a safety light source range table for human data according to the light source data, and use the MEDIAN function to calculate the median value of the first safety light source range table;

[0121] The prediction module predicts and optimizes the light source data according to the weather data combined with the historical data. A second safety light source range table for human data is established again through the optimized light source data, and the median value of the second safety light source range table is obtained;

[0122] Optimize the second adjustment plan according to the median value of the first safety light source range table and the median value of the second safety light source range table to adapt to each person.

[0123] Collect the height of the personnel and the data of the personnel's eye diseases. The data of the personnel's eye diseases include myopia, hyperopia, astigmatism, amblyopia, strabismus, etc., and establish a personnel file in combination with the face data and name;

[0124] Since there are differences in the height of each person and some people have eye diseases, the height of the person's head is first determined by height, and then the distance from the head to the eyes is subtracted, generally taking a value of 5-8 cm, so as to obtain the distance from the light to the person's eyes. Then, the light decay value E at each distance node is calculated in Embodiment 1 to determine the light brightness value at the light to the person's eyes. Then, according to the medical recommendation data, the safety light source range value and brightness threshold that the person's eye diseases can accept are determined. The safety light source range values of all personnel are summarized into a first safety light source range table, and the MEDIAN function in the excel table is used to calculate the median value of the first safety light source range table;

[0125] Further, the prediction module obtains the predicted light source data according to the weather data combined with the historical data. By importing the predicted light source data into the simulated classroom lighting model, the predicted light brightness value is obtained, and a second safety light source range table is generated. The appropriate light source parameters are selected through the median value of the second safety light source range table to optimize the second adjustment plan. The light source is adjusted through the optimized second adjustment plan to further improve the comfort of the personnel in the classroom;

[0126] It should be specifically noted that the median value of the second safe light source range table needs to meet the safe light source values of ≥ 80% of the personnel. When it is lower than 80%, the predicted light source data is transmitted into the simulated classroom lighting model, and the positions of the human models lower than the median value or the light source parameters are changed until ≥ 80% of the personnel are satisfied.

[0127] It should be specifically noted that the difference between the light source intensity received by the personnel who do not meet the median value and the light source intensity received by the personnel who meet the median value is equal to ±6%, meeting the medical recommendation data.

[0128] Embodiment 5

[0129] This embodiment is an improvement based on Embodiment 4. Specifically, please refer to Figures 1 - 5 , determine the light source adjustment range according to the median value of the first safe light source range table and the median value of the second safe light source range table, and adopt zonal light control and stepped adjustment according to the light source adjustment range;

[0130] Zonal light control includes dividing bright and dark intensity areas according to the site data and personnel data, and adjusting the dark intensity area and the bright intensity area in sequence;

[0131] Stepped adjustment includes determining the brightness threshold according to the personnel data, and gradually adjusting the light source by combining the brightness threshold with the light source adjustment range and time nodes.

[0132] Among them, in the teaching mode, the lighting area of the podium needs to be brighter than that of the student area to facilitate students to focus their attention on the podium;

[0133] In the self-study mode, the lighting in the student area is brighter than that in the podium lighting area because there are no people using the podium area and no lighting is required, which can save electricity;

[0134] In the demonstration teaching aid mode, the lighting area of the podium needs to be brighter than that of the student area, and the lighting in the student area needs to be adjusted to be dim. The lighting area of the podium focuses on illuminating the teaching aids to facilitate students to observe the operating principle of the teaching aids;

[0135] Therefore, zonal light control is used to control the brightness of the area lights. When it is necessary to change from the demonstration teaching aid mode to the teaching mode, since the personnel have been in the dark environment for a long time, a rapid increase in the bright light will cause a sharp change in the pupil. Therefore, the darker intensity area is adjusted first, and the stepped adjustment method is adopted to determine the brightness threshold of each person in the second safe light source range table. Subsequently, the light source is gradually adjusted by combining the brightness threshold with the light source adjustment range and time nodes, so that the darker intensity gradually approaches the natural light. Then the curtains are opened, further protecting the eyes of the personnel, so that the nerves of the personnel's eyeballs are not strongly stimulated, and by dynamically adjusting the classroom light environment, the personnel are made more comfortable in the classroom;

[0136] It should be noted that the brightness threshold refers to the critical value of the eye's ability to perceive light, including the absolute brightness threshold and the differential brightness threshold. The absolute brightness threshold refers to the lowest light illumination that can cause the eye to have a light sensation, while the differential brightness threshold refers to the smallest light change that the eye can distinguish.

[0137] Example 6

[0138] This embodiment is an improvement based on Embodiment 5. Specifically, please refer to Figures 1 - 5 , the prediction module combines weather data to determine the natural light transformation in each time period and generates determination data;

[0139] Based on the determination data, the parameters of the camera are preset in advance to adapt to the light change caused by the weather change;

[0140] The second adjustment plan is optimized again through the determination data.

[0141] When the light suddenly changes, the camera will produce overexposure, and the camera screen will turn white as a whole. It takes a certain amount of time for the camera to adjust and recover by itself. Therefore, the recognition module will lose its working function briefly and cannot achieve the effect of real-time monitoring. Therefore, the cloud amount observation information and cloud layer feature information are obtained in real time through the tool software to predict the cloud change in each time period, so as to judge whether the weather will change in the future time period, so as to infer the moving track of the cloud, and thus determine that the time node when the cloud drifts past the sun is the determination data. Through the determination data, the parameter adjustment plan of the camera is set and incorporated into the second adjustment plan. Before the time node when the cloud drifts past the sun, the exposure compensation value, IOS value, backlight compensation value, etc. of the camera are changed in advance through the parameter adjustment plan to reduce the occurrence of overexposure of the camera caused by sudden light change;

[0142] The light source includes natural light and non-natural light;

[0143] The light sensor is used to detect the natural light and non-natural light in the classroom and record the data of the natural light and non-natural light;

[0144] The light source values of non-natural light are stored in the monitoring module. The data of non-natural light are compared with the stored light source values of non-natural light to determine whether there is light source light decay and excessive stroboscopic, and the stored light source values of non-natural light are modified. The second adjustment plan adjusts the light source according to the modified stored light source values of non-natural light;

[0145] Among them, determine the light source position of excessive stroboscopic and light source attenuation, and communicate for repair;

[0146] Among them, the LED lamps installed in the classroom will produce light decay and excessive flicker after being used for a period of time, which will cause the light values emitted by the LED lamps to change. Then, when the second adjustment plan is used, since the second adjustment plan fails to calculate and adjust according to the actual light values emitted by the LED lamps, the second adjustment plan cannot achieve the theoretical light environment effect. For this reason, the light values of spotlights, downlights, and ceiling lamps are detected by light sensors, and compared with the light values of factory spotlights, downlights, and ceiling lamps stored in historical data, the difference is calculated, and the data of the second adjustment plan is adaptively adjusted based on the difference, thereby ensuring that the desired classroom light environment effect can be achieved.

[0147] Example 7

[0148] This embodiment is an improvement made on the basis of embodiment 6. For details, please refer to Figures 1 - 5 , the detection module determines the change of the personnel data according to the character model and the image captured by the recognition module, and adjusts the second adjustment scheme accordingly;

[0149] Personnel data changes include personnel seat adjustments, personnel shortages, and personnel physiological changes;

[0150] Due to emergencies such as seat adjustment, staff shortage and physiological changes of personnel, in the initial stage of changing the light source in the second adjustment scheme, the detection module timely determines the change of personnel data according to the character model and the recognition module, so that timely adjustments can be made;

[0151] Among them, the physiological change of the personnel is the change of height during puberty, so that the current height of the personnel matches the brightness value of the distance node, and the second adjustment plan is revised;

[0152] Determine the eye usage data of the person according to the recognition module and the monitoring module, the eye usage data of the person includes the eye usage time and the eye usage angle;

[0153] Set the eye fatigue value threshold. When the eye use time exceeds the eye fatigue value threshold, the prompt module will prompt the person and correct the person's eye angle through historical data.

[0154] Sitting forward will shorten the distance between the eyes and objects to less than 30cm (normal should be 50-70cm), causing continuous tension in the ciliary muscles and accelerating lens accommodation fatigue;

[0155] A tilted head or crooked body may block the light source, resulting in partial shadows or screen reflections, forcing the pupil to frequently adjust the light intensity, increasing the burden on the eyes;

[0156] When concentrating, sitting in an incorrect posture may reduce the number of blinks from the normal 15 times / minute to 5 times / minute, and the tear film cannot be replenished in time, resulting in dryness and burning sensations;

[0157] Long-term head-down or hunchback postures can compress the blood vessels and nerves in the neck, reducing the oxygen supply to the retina and triggering a series of reactions such as blurred vision and orbital pain;

[0158] In summary, it is necessary to detect and determine the sitting postures of personnel;

[0159] The historical data stores a model of the correct sitting posture of simulated personnel;

[0160] The eye usage data of each person is recorded through the recognition module and the detection module, including the eye usage time and the eye usage angle. The eye usage angle is determined by matching the acquired camera image with the simulated classroom lighting model, thereby determining the sitting posture of the person in the camera image and thus determining the eye usage angle. Therefore, the personnel are prompted through the prompting module and corrected by the historical data.

[0161] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0162] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A dynamic regulation system for classroom light environment based on multi-source information perception, characterized in that Including: An identification module, which is used to identify a light source, generate light source data, and collect refraction data, site data, and personnel data; A prediction module, which determines a lighting scenario through site data, personnel data, and historical data; The prediction module combines refraction data, lighting scenario, light source data, and historical data to calculate, screen, and generate a first adjustment plan; An adjustment module, which analyzes and executes the first adjustment plan to change the position, angle, brightness, and color temperature of the light source; A monitoring module, which is used to monitor refraction data, site data, personnel data, and light source data in real time; Set a light source threshold, and dynamically adjust the light source threshold according to the personnel data, refraction data, light source data, and site data; When the dynamically adjusted light source threshold is exceeded, the monitoring module feeds back to the prediction module, and the prediction module optimizes the first adjustment plan to generate a second adjustment plan, which is analyzed and executed by the adjustment module; Set a dark environment duration threshold, and the monitoring module determines whether the personnel data exceeds the dark environment duration threshold. When the dark environment duration threshold is exceeded, a dark environment adjustment plan is calculated, screened, and generated by the prediction module and historical data, and the dark environment adjustment plan is analyzed and executed by the adjustment module.

2. The dynamic lighting environment adjustment system for classrooms based on multi-source information perception according to claim 1, wherein: The lighting scenario includes a teaching scenario, a demonstration scenario, and a self-study scenario; The prediction module collects the teaching content of the current day to locate the position of the textbook chapter, thereby determining the teaching content of tomorrow, and combines the historical data to determine whether the teaching content of tomorrow is a teaching scenario and / or a demonstration scenario, a self-study scenario.

3. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 2, wherein: A classroom three-dimensional model is preset in the prediction module; Establish a character model according to the personnel data and import it into the classroom three-dimensional model; The image captured by the identification module corrects the image data through the classroom three-dimensional model and the character model, thereby accurate the light source data, and optimizes the first adjustment plan, the second adjustment plan, and the dark environment adjustment plan according to the accurate light source data.

4. The dynamic lighting environment adjustment system for classrooms based on multi-source information perception according to claim 3, wherein: Establish a safety light source range table for the personnel data according to the light source data, and calculate the median value of the first safety light source range table by using the MEDIAN function; The prediction module predicts and optimizes the light source data again according to the weather data and historical data, establishes a second safety light source range table for the personnel data with the optimized light source data, and obtains the median value of the second safety light source range table; Optimize the second adjustment plan according to the median value of the first safety light source range table and the median value of the second safety light source range table to adapt to each person.

5. The classroom light environment dynamic regulation system based on multi-source information perception according to claim 4, characterized in that: Determine the light source adjustment range according to the median value of the first safety light source range table and the median value of the second safety light source range table, and the light source adjustment range adopts zoned light control and stepped adjustment; The zoned light control includes dividing bright and dark intensity areas according to site data and personnel data, and sequentially adjusting the dark intensity area and the bright intensity area; The stepped adjustment includes determining a lightness threshold according to the personnel data, and gradually adjusting the light source by combining the lightness threshold with the light source adjustment range and time nodes.

6. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 3, characterized in that: The identification module includes a light sensor and a camera; The prediction module combines weather data to determine the natural light transformation for each time period and generates determination data; Based on the determination data, the parameters of the camera are preset in advance to adapt to the light changes caused by weather changes; The second adjustment plan is optimized again through the determination data.

7. The dynamic lighting environment adjustment system for classrooms based on multi-source information perception according to claim 6, characterized in that: The light source includes natural light and non-natural light; The light sensor is used to detect the natural light and non-natural light in the classroom and record the data of the natural light and non-natural light; The monitoring module stores the light source values of non-natural light, compares the data of non-natural light detected by the light sensor with the stored light source values of non-natural light, determines whether there is light source light decay and excessive stroboscopic, and modifies the stored light source values of non-natural light. The second adjustment plan adjusts the light source according to the modified stored light source values of non-natural light; Among them, determine the light source positions of the excessive stroboscopic and light source attenuation, and communicate for maintenance.

8. The classroom light environment dynamic regulation system based on multi-source information perception according to claim 7, characterized in that: The detection module determines the change of personnel data according to the person model and the captured image of the recognition module, and adjusts the second adjustment plan accordingly; The change of personnel data includes personnel seat adjustment, personnel absence, and personnel physiological changes.

9. The dynamic lighting environment adjustment system for classrooms based on multi-source information perception according to claim 6, characterized in that: The prediction module is used to collect sounds and combine historical data to determine personnel behavior through big data analysis to assist in determining the lighting scene.

10. The dynamic lighting environment adjustment system for classrooms based on multi-source information perception according to claim 9, characterized in that: Determine the personnel eye use data according to the recognition module and the monitoring module, and the personnel eye use data includes eye use time and eye use angle; Set the threshold value of eye fatigue. When the eye use time exceeds the threshold value of eye fatigue, the personnel are prompted by the prompt module, and the eye use angle of the personnel is corrected through the historical data.

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