A classroom light environment dynamic adjustment system based on multi-source information perception

Abstract

The application relates to the technical field of classroom light environment regulation, and discloses a classroom light environment dynamic regulation system based on multi-source information sensing, which comprises an identification module, the identification module is used for identifying light sources, generating light source data, and collecting refraction data, site data and personnel data, a prediction module is used for determining a light scene through the site data, the personnel data and historical data, the prediction module is used for calculating and screening a first adjustment scheme in combination with the refraction data, the light scene, the light source data and the historical data, and an adjustment module is used for analyzing and executing the first adjustment scheme so as to change the position, angle, brightness and color temperature of the light source. The monitoring module and the identification module can determine in which dark environment the personnel is, the dark environment ending time is determined, the dark environment adjustment scheme is transmitted to the adjustment module between the dark environment ending time, 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 adjustment, and in particular to a classroom light environment dynamic adjustment system based on multi-source information perception. Background Art

[0002] The physiological and psychological environment created indoors by light (illuminance level and distribution, lighting form) and color (hue, color saturation, indoor color distribution, and color appearance), which is related to the room's shape, is a key component of the physical and psychological environment. People perceive the world through hearing, vision, smell, taste, and touch. 80% of the information they receive comes from visual perception induced by light. The light environment also has a positive impact on people's mental state and psychological experience. For example, in places of production, work, and study, a good lighting environment can invigorate the spirit, improve work efficiency, and enhance product quality. In public places for rest and entertainment, an appropriate lighting environment can create a comfortable, elegant, lively, or solemn atmosphere. The lighting environment in classrooms, in particular, must balance functionality and health.

[0003] The existing classroom lighting environment can only be judged after detection by light sensors, and it is impossible to perceive and predict in advance to make corresponding adjustments. For example, when a sunny day turns cloudy and then turns sunny, the light sensor will send a signal after detecting it, causing the light source inside the classroom to change. At this time, the people inside the classroom will experience rapid changes in pupils due to the rapid changes in light, which is not conducive to human health. A stable lighting rhythm helps maintain the normal development of the eyeball, while a disordered lighting rhythm may interfere with the refractive development process of the eyeball. Secondly, the existing room light environment adjustment system cannot change the classroom light environment in advance according to the behavior that classroom personnel are about to perform. For example, when classroom personnel need to do eye exercises, they need to close their eyes for a period of time. When they open their eyes after completing the eye exercises, the outside light will irritate their eyes. Therefore, the existing classroom light environment adjustment system cannot dynamically adjust the classroom light environment in real time. Summary of the Invention

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

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

[0006] an identification module, the identification module being used to identify light sources, generate light source data, and collect refraction data, site data, and personnel data;

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

[0008] The prediction module calculates and filters the refraction data, lighting scene, light source data and historical data to generate a first adjustment plan;

[0009] an adjustment module, the adjustment module analyzing and executing a first adjustment scheme to change the position, angle, brightness, and color temperature of the light source;

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

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

[0012] When the threshold of the light source is exceeded, the monitoring module feeds back to the prediction module, the prediction module optimizes the first adjustment plan to generate a second adjustment plan, and the adjustment module analyzes and executes the second adjustment plan;

[0013] A dark environment duration threshold is set, 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 generated through calculation and screening by the prediction module and historical data, and the dark environment adjustment plan is analyzed and executed by the adjustment module.

[0014] As an optional solution of the classroom light environment dynamic adjustment system based on multi-source information perception of the present invention, wherein: the lighting scene includes a teaching scene, a demonstration scene and a self-study scene;

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

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

[0017] Creating a character model based on the personnel data and importing it into the three-dimensional model of the classroom;

[0018] The image captured by the recognition module is corrected through the classroom three-dimensional model and the character model to accurately obtain the light source data, and the first adjustment scheme, the second adjustment scheme and the dark environment adjustment scheme are optimized based on the accurate light source data.

[0019] As an optional solution of the classroom light environment dynamic adjustment system based on multi-source information perception of the present invention, wherein: a safe light source range table of the character data is established according to the light source data, and a median value of the first safe light source range table is calculated using a MEDIAN function;

[0020] Re-optimizing the light source data by the prediction module according to the weather data combined with the historical data prediction, establishing a second safe light source range table for the character data based on the re-optimized light source data and obtaining a middle value of the second safe light source range table;

[0021] The second adjustment scheme is optimized 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.

[0022] As an optional solution of the classroom light environment dynamic adjustment system based on multi-source information perception described in the present invention, wherein: the light source adjustment range is determined according to the middle value of the first safe light source range table and the middle value of the second safe light source range table, and the light source adjustment range adopts zone light control and step-by-step adjustment;

[0023] The zoned light control includes dividing the light and dark intensity areas according to the site data and the personnel data, and adjusting the dark intensity areas and the light intensity areas in sequence;

[0024] The step-by-step adjustment includes determining a brightness threshold according to personnel data, and gradually adjusting the light source according to the brightness threshold in combination with a light source adjustment range and a time node.

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

[0026] The prediction module determines the natural light transformation in each time period in combination with weather data to generate determination data;

[0027] Presetting the camera parameters based on the determination data to adapt to light changes caused by weather changes;

[0028] The second control scenario is optimized again using the decision data.

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

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

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

[0032] Among them, the position of the light source with excessive stroboscopic light source and light source attenuation is determined, and communication maintenance is carried out.

[0033] As an optional solution of the classroom light environment dynamic adjustment system based on multi-source information perception of the present invention, wherein: the monitoring module determines the change of personnel data based on the character model and the image captured by the recognition module, and adjusts the second adjustment solution accordingly;

[0034] The personnel data changes include personnel seat adjustments, personnel shortages, and personnel physiological changes.

[0035] As an optional solution to the classroom light environment dynamic adjustment system based on multi-source information perception described in the present invention, the prediction module is used to collect sound and combine historical data to determine personnel behavior through big data analysis to assist in determining the lighting scene.

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

[0037] A threshold value of eye fatigue value is set. When the eye use time exceeds the threshold value of eye fatigue value, the person is prompted through the prompt module, and the person's eye angle is corrected according to the historical data.

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

[0039] 1. This classroom light environment dynamic adjustment system based on multi-source information perception determines the dark environment a person is in through the monitoring module and the recognition module, and predicts the end time of the dark environment. The dark environment adjustment plan is transmitted to the adjustment module before the dark environment ends, so that the adjustment module can dynamically adjust the classroom light source in real time.

[0040] 2. The dynamic adjustment system of classroom light environment based on multi-source information perception uses the monitoring module to capture words related to teaching aid demonstration in the teaching content, and uses the recognition module to capture the courseware content displayed on the multimedia display screen to determine that a teaching demonstration is about to be required. When the monitoring module and the recognition module determine that a teaching aid demonstration is about to be required, the classroom light source is adjusted and then the curtains are closed to achieve dim lighting in the student area in the demonstration scene. The classroom demonstration area uses downlights to illuminate the demonstration teaching aids, and spotlights are used to chase and focus on the operation principle of the demonstration teaching aids, thereby improving the teaching demonstration effect in the demonstration scene.

[0041] 3. The dynamic adjustment system of classroom light environment based on multi-source information perception collects light source data of the camera's distant image through light sensors to assist in modifying part of the light data of the simulated classroom light model. The modified simulated classroom light model light data is then used to correct the camera image, so that the distant data of the camera image fits the actual situation. 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Schematic diagram of the process of the system of the present invention.

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

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

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

[0046] Figure 5 This is the third display diagram of the system of the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] Example 1

[0049] See also Figure 1-Figure 5 , one of which is a classroom light environment dynamic adjustment system based on multi-source information perception, including:

[0050] Identification module, which is used to identify light sources, generate light source data, and collect refraction data, site data, and personnel data;

[0051] Prediction module, which determines the lighting scene based on site data, personnel data and historical data;

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

[0053] an adjustment module, the adjustment module parses and executes the first adjustment scheme 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 the light source threshold and dynamically adjust the light source threshold based on personnel data, refraction data, light source data and site data;

[0056] When the dynamic light source adjustment threshold is exceeded, the monitoring module feeds back to the prediction module, the prediction module optimizes the first adjustment plan to generate a second adjustment plan, and the adjustment module analyzes and executes the second adjustment plan;

[0057] A dark environment duration threshold is set, 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 generated through calculation and screening by the prediction module and historical data, and the dark environment adjustment plan is analyzed and executed by the adjustment module.

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

[0059] By inputting the data of purchased light source into the identification module, the purchased light source data includes light intensity, luminous flux, color temperature, color rendering index, viewing angle, lumen, wattage, light decay value Data, brightness Data, including light attenuation value Data, brightness The data is obtained through calculation;

[0060] The camera captures the location of the light source in the venue to determine the coordinates of the light source. The light source includes natural light and unnatural light. Unnatural light includes lamps and display screens. The camera and light sensor are 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 outputs RGB data. In the automatic exposure technology, the RGB data output by the sensor is converted into YUV color space, in which the brightness component Y accounts for 93% of the weight and is used to represent the overall brightness of the picture. The formula is:

[0062] in, is the average brightness value of the image;

[0063] The smaller the aperture (the larger the number), the less light enters.

[0064] is the shutter speed (seconds). The longer the time, the more photons the sensor receives.

[0065] The system transmittance is usually 0.85-0.95, which is determined by the transmittance of the lens coating and the sensor protective layer;

[0066] is the sensor sensitivity, specified by the manufacturer;

[0067] in, The calculation formula is: ;

[0068] k is the linear response coefficient, E is the illumination received by the sensor;

[0069] Then calculate the light attenuation value of the non-natural light at each distance node between the starting position and the ground of the site Data, the calculation formula is:

[0070]

[0071] is the maintenance factor, generally 0.7-0.8;

[0072] is the light intensity of the light source;

[0073] is the distance height node;

[0074] By inputting the refraction data of personnel uniforms, classroom chairs, blackboards, walls, floors, and glass into the recognition module;

[0075] By inputting site data into the recognition module, the site data includes site size data and building data;

[0076] By entering personnel data into the recognition module, the personnel data includes the name of the student and teacher, the height of the student, and the face of the student;

[0077] The historical data includes the previous year's teaching content, the courseware and demonstration teaching aids that match the teaching content, and the lighting layout that matches the courseware;

[0078] The prediction module is used to collect sounds and combine them with historical data to determine human behavior through big data analysis, and to assist in determining lighting scenes;

[0079] The system also includes a microphone, which collects conversations between teachers and students in the classroom. The system uses the conversation content and combines it with historical data to predict tomorrow's teaching content, thereby determining the lighting requirements for tomorrow's teaching content. For example, if the voice contains words such as the number of pages to be previewed in the evening or the teaching aid demonstration required tomorrow, combined with the teaching courseware, the system can determine the lighting requirements for the teaching aid demonstration scene required tomorrow.

[0080] Furthermore, to improve accuracy, the communication teacher confirms whether the predicted teaching content and / or demonstration aids are correct. If the prediction is wrong, the teacher manually changes it;

[0081] Natural light includes the natural light data generated by light from sunny, cloudy, overcast, and rainy days shining on the outside of the classroom. The light source data includes natural light data.

[0082] The prediction module then combines the refraction data, lighting scene, light source data, and the lighting layout of the matching teaching content courseware in the historical data through algorithm calculation to select the appropriate lighting data, thereby generating the first adjustment plan to change the position, angle, brightness, and color temperature of the current light source;

[0083] The average illumination of the desk is ≥300lx, and the illumination uniformity is ≥0.7;

[0084] The lighting of the blackboard should maintain an average illumination of ≥500lx and a uniformity of ≥0.8;

[0085] The color temperature is 3000K-5500K;

[0086] Select spotlights and ceiling lights. Ceiling lights are used for wide-area lighting, while spotlights are used for key areas. Choose the appropriate number of spotlights, downlights, and ceiling lights according to the classroom structure.

[0087] Among them, the calculation formulas of the first adjustment plan, the second adjustment plan and the dark environment adjustment plan use genetic algorithms, big data algorithms, ant algorithms, etc. with screening data;

[0088] Using big data algorithms and cluster analysis to filter out the optimal lighting combination for similar scenes from tens of thousands of courseware, this allows for rapid data screening.

[0089] The genetic algorithm is more suitable for the lighting layout optimization requirements of teaching scenarios with small samples, multiple constraints, and strong domain knowledge;

[0090] The ant algorithm is particularly suitable for lighting optimization tasks in teaching scenarios that require a balance of physical rules, historical experience, and dynamic response. It simultaneously processes continuous variables such as lamp color temperature, light intensity distribution, and beam angle to generate a globally optimal or near-optimal solution.

[0091] The light source is connected to the electric slide rail. When the light source position needs to be changed, it can be changed by sliding the light source. The light angle can be changed by rotating the lamp body, and the color temperature and brightness can be changed by switching the color temperature and brightness modes.

[0092] After the first adjustment plan is implemented on the second day, the refraction data, site data, personnel data, and light source data are monitored in real time through the monitoring module to verify the prediction results of the prediction module;

[0093] 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;

[0094] Because the external light environment on sunny, cloudy, overcast, and rainy days is similar, the light source threshold perceived by the pupils under the influence of natural light is also different. In response to this, the prediction module recalculates the user data, refraction data, venue data, and light source data to derive a second adjustment plan. Compared with the first adjustment plan, the second adjustment plan considers more detailed factors, and the light source after implementation is more suitable for the classroom light environment on that day;

[0095] Furthermore, due to the ever-changing weather, natural light may change at any time. If the monitoring module updates the light source data to the prediction module after the natural light has changed, the comfort level of the students in the classroom lighting environment will be reduced. Therefore, by using tool software to obtain cloud cover observation information and cloud layer characteristics in real time, cloud changes in each time period can be predicted to determine whether the weather will change in the future. In this way, the prediction module can prepare and adjust the plan in advance.

[0096] It should be noted that the tool software includes Yuntiantong, Lijing Weather, Aimeiyi, etc.

[0097] The dark environment duration is the time a person spends in a relatively dark environment. The dark environment duration threshold is set at 10-25 minutes. When the monitoring module cooperates with the recognition module to detect that a person is in a dark environment, the time the person spends 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.

[0098] It should be noted that dark environments include situations such as teaching aid demonstrations, eye exercises, and lunch breaks. Therefore, the monitoring module and the recognition module will determine what kind of dark environment the person is in, and thus determine the end time of the dark environment. Before the end of the dark environment, the dark environment adjustment plan will be transmitted to the adjustment module, so that the adjustment module can dynamically adjust the classroom light source in real time.

[0099] 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;

[0100] It should be noted that the classroom windows are equipped with electric curtains. When the end time of the dark environment is determined, the electric curtains will be used to seal the glass first to isolate the natural light from the outside, and then the classroom light source will be adjusted in steps to adapt to the natural light, and then the electric curtains will be slowly opened to achieve a natural connection between the classroom light source and natural light.

[0101] Example 2

[0102] This embodiment is an improvement made on the basis of embodiment 1. For details, please refer to Figure 1-Figure 5 ,The light scenes include teaching scenes, demonstration scenes and ,self-study scenes;

[0103] The prediction module collects the current day's teaching content and locates the chapter position in the textbook to determine tomorrow's teaching content. It also uses historical data to determine whether it is a teaching scenario, demonstration scenario, or self-study scenario.

[0104] The prediction module cooperates with AI through textbook content to determine the demonstration principle of the simulation teaching aids, compares the demonstration teaching aids through the recognition module, matches the demonstration details, and adjusts the light source to adapt to the demonstration according to the demonstration details.

[0105] The prediction module collects the teaching courseware content of the day and locates the courseware and demonstration teaching aids that match the teaching content in the history book, as well as the lighting layout of the courseware that matches the teaching content. The prediction module then locates the next teaching content of the teaching content and determines the lighting scene based on the lighting layout of the courseware that matches the teaching content recorded in the historical data. In this way, the lighting environment layout for tomorrow is determined in advance and adjusted according to tomorrow's weather changes.

[0106] In the demonstration scenario, after determining that tomorrow's teaching content requires the use of a demonstration aid, the name of the demonstration aid is searched through AI to determine the operating principle of the demonstration aid. The operating principle is broken down into several steps, where each step completes an action. The key content of the operating principle of the demonstration aid is searched through AI, and several steps corresponding to the key content in the operating principle are marked. These steps and the marked steps are then included in the second adjustment plan;

[0107] The teaching content is monitored by a microphone, and the monitoring module is used to capture the words related to the teaching aid demonstration in the teaching content, and the recognition module is used to capture the courseware content displayed on the multimedia display screen, so as to determine that a teaching demonstration is about to be required. When the monitoring module and the recognition module determine that a teaching aid demonstration is about to be required, the classroom light source is adjusted, and then the curtains are closed, so that the light in the demonstration scene is dim in the student area, and the classroom demonstration area is illuminated by downlights for the demonstration teaching aids, and spotlights are used to chase and focus on the operation principle of the demonstration teaching aids, so as to improve the teaching demonstration effect in the demonstration scene;

[0108] It should be noted that the brightness of the downlight above the demonstration teaching aid is lower than that of the spotlight, and the color temperature of the downlight and the spotlight are different, so the demonstration teaching aid is illuminated by the spotlight to specifically demonstrate the key points in the operating principle of the demonstration teaching aid.

[0109] Example 3

[0110] This embodiment is an improvement made on the basis of embodiment 2. For details, please refer to Figure 1-Figure 5 ,The three-dimensional model of the classroom is preset in the prediction module;

[0111] Create character models based on personnel data and import them into the 3D classroom model;

[0112] The image captured by the recognition module is corrected through the classroom three-dimensional model and the character model to obtain accurate light source data, and the first adjustment plan, the second adjustment plan and the dark environment adjustment plan are optimized based on the accurate light source data.

[0113] Since a camera is used to assist the light sensor in determining the classroom light environment, the camera has the problem of large images at a distance and small images at a distance, which makes the camera's distant images inaccurate. This leads to errors in the calculation of the light source brightness in Example 1 and the determination of the brightness data for each distance node, which in turn causes the second adjustment scheme to fail to accurately adjust the classroom light environment.

[0114] For this, see Figure 2 , through the cooperation of the prediction module and 3D simulation lighting software, the classroom three-dimensional model and character model are established in advance, and the indoor lighting data and position are input into the 3D simulation lighting software to generate a simulated classroom lighting model. Then, the camera image is compared with the simulated classroom lighting model to determine the error data ratio between the camera image and the simulated classroom lighting model. Then, the camera image is adjusted to correct the camera image data;

[0115] It should be noted that the lighting data in the simulated classroom lighting model is theoretical data. Therefore, the near image of the camera image is compared first. Since the camera contains an image sensor CMOS, the light source data of the near image is more accurate. Therefore, the light source data of the near image is used as the starting part of the lighting data of the simulated classroom lighting model, so as to modify the lighting data of the simulated classroom lighting model of the 3D simulation lighting software. Then, the light source data of the distant image of the camera is collected through the light sensor to assist in modifying part of the lighting data of the simulated classroom lighting model. Then, the modified simulated classroom lighting model lighting data is used to correct the camera image, so that the distant data of the camera image fits the actual situation. In this way, the second adjustment plan obtained by screening and calculation is more suitable for the classroom light environment, making the eyes of classroom personnel more comfortable.

[0116] It should be noted that 3D lighting simulation software includes Light Tools (optical system modeling), Set ALight 3D Studio (photographic lighting simulation), Lightscape, etc.

[0117] Furthermore, since natural light is inclined, there will be a problem of inconsistent natural light in the front and back areas of the classroom. Therefore, the tool software is used to determine whether the weather will cause natural light changes in the future time period, and the camera and light sensor are used to determine the natural light intensity and light direction in the front and back areas of the classroom. The tool software is then used to predict future natural light data, and then the future natural light data is imported into the 3D simulation lighting software, so that further optimization and changes to the indoor light source can be made through the prediction module.

[0118] Example 4

[0119] This embodiment is an improvement made on the basis of embodiment 3. For details, please refer to Figure 1-Figure 5 , establish a safe light source range table for character data based on light source data, and use the MEDIAN function to calculate the middle value of the first safe light source range table;

[0120] The prediction module predicts and optimizes light source data based on weather data combined with historical data, and re-establishes a second safe light source range table for character data using the optimized light source data and obtains a median value of the second safe light source range table;

[0121] The second adjustment scheme is optimized 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.

[0122] Collect personnel height and eye disease data, including myopia, hyperopia, astigmatism, amblyopia, and strabismus, and create personnel files based on facial data and names;

[0123] Because each person's height varies, and some people suffer from eye diseases, the height of the person's head is first determined by the height. The distance from the head to the eyes is then subtracted, generally taking a value of 5-8 cm, to obtain the distance from the light to the person's eyes. The light attenuation value E of each distance node is then calculated in Example 1 to determine the light brightness value at the person's eyes. The safe light source range value and brightness threshold acceptable to the person's eye disease are then determined based on medical recommendation data. The safe light source range values ​​of all people are summarized into a first safe light source range table, and the median value of the first safe light source range table is calculated using the MEDIAN function in Excel.

[0124] Furthermore, the prediction module obtains predicted light source data based on weather data combined with historical data. The predicted light source data is imported into the simulated classroom lighting model to obtain predicted light brightness values, thereby generating a second safe light source range table. The appropriate light source parameters are selected based on the middle value of the second safe light source range table to optimize the second adjustment plan. The light source is adjusted according to the optimized second adjustment plan to further improve the comfort of people in the classroom.

[0125] It should be noted that the middle value of the second safe light source range table needs to meet the safe light source value of ≥80% of the personnel. If it is lower than 80%, the predicted light source data will be transferred to the simulated classroom lighting model, and the position of the character model below the middle value will be changed or the light source parameters will be changed until it meets the safety light source value of ≥80% of the personnel.

[0126] It should be noted that the difference between the light source intensity to which people who do not meet the median value are exposed and the light source intensity to which people who meet the median value are exposed is equal to ±6%, which meets the medical recommendation data.

[0127] Example 5

[0128] This embodiment is an improvement made on the basis of embodiment 4. For details, please refer to Figure 1-Figure 5 , determine the light source adjustment range according to the middle value of the first safe light source range table and the middle value of the second safe light source range table, and adopt zone light control and step-by-step adjustment according to the light source adjustment range;

[0129] Zoning light control includes dividing the light and dark intensity areas according to the site data and personnel data, and adjusting the dark intensity area and the light intensity area in turn;

[0130] Step-by-step adjustment includes determining the brightness threshold based on personnel data, and gradually adjusting the light source through the brightness threshold combined with the light source adjustment range and time nodes.

[0131] In teaching mode, the light in the podium area needs to be brighter than that in the student area to help students focus on the podium.

[0132] In self-study mode, the lights in the student area are brighter than those in the podium area, because the podium area is not used by anyone and does not need lights, which can save electricity.

[0133] When demonstrating teaching aids, the lights in the podium area need to be brighter than those in the student area, and the lights in the student area should be adjusted to dim. The podium area should focus on illuminating the teaching aids to facilitate students to observe the operating principles of the teaching aids.

[0134] Therefore, zone light control is adopted to control the brightness of the area lights. When it is necessary to switch from the demonstration teaching aid mode to the teaching mode, since people have been in the dark environment for a long time, quickly increasing the brightness will cause the pupils to change drastically. Therefore, the darker intensity area is adjusted first, and a step-by-step adjustment method is adopted to determine the brightness threshold of each person in the second safe light source range table. Then, according to the brightness threshold combined with the light source adjustment range and time node, the light source is gradually adjusted to make the darker intensity gradually close to natural light. Then the curtains are opened to further protect the eyes of the people, so that the nerves of the people's eyeballs will not be strongly stimulated. In addition, by dynamically adjusting the classroom light environment, people can feel more comfortable in the classroom.

[0135] 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 brightness difference threshold. The absolute brightness threshold refers to the minimum light brightness that can make the eye feel light, while the brightness difference threshold refers to the minimum light change that the eye can distinguish.

[0136] Example 6

[0137] This embodiment is an improvement made on the basis of embodiment 5. For details, please refer to Figure 1-Figure 5 ,The prediction module combines weather data to determine the natural light ,change in each time period and generates determination data;

[0138] Pre-set camera parameters based on judgment data to adapt to light changes caused by weather changes;

[0139] The second adjustment plan is optimized again by judging the data.

[0140] When the light changes suddenly, the camera will be exposed and the camera image will be white as a whole. It takes a certain amount of time for the camera to adjust and recover on its own, which will cause the recognition module to temporarily lose its working function and fail to achieve the effect of real-time monitoring. Therefore, cloud cover observation information and cloud feature information are obtained in real time through tool software to predict cloud changes in each time period, so as to judge whether the weather will change in the future time period. In this way, the movement trajectory of the clouds can be inferred, and the time node when the clouds pass the sun can be determined, which is the judgment data. The camera parameter adjustment plan is set based on the judgment data and included in the second adjustment plan. Before the time node when the clouds pass the sun is reached, 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 exposure of the camera caused by sudden changes in light.

[0141] Light sources include natural light and unnatural light;

[0142] The light sensor is used to detect natural light and unnatural light in the classroom and record the data of natural light and unnatural light;

[0143] The monitoring module stores non-natural light source values, compares the non-natural light data with the stored non-natural light source values, determines whether the light source has light decay and excessive stroboscopic, and modifies the stored non-natural light source values. The second adjustment scheme adjusts the light source according to the modified stored non-natural light source values;

[0144] Among them, determine the location of the light source with excessive flicker and light source attenuation, and communication maintenance;

[0145] Among them, the LED lights 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 lights 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 lights, the second adjustment plan cannot achieve the theoretical light environment effect. For this, the light values ​​of spotlights, downlights, and ceiling lights are detected by light sensors, and compared with the light values ​​of factory spotlights, downlights, and ceiling lights stored in historical data to calculate the difference, and then 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.

[0146] Example 7

[0147] This embodiment is an improvement made on the basis of embodiment 6. For details, please refer to Figure 1-Figure 5 , the monitoring module determines the change of personnel data based on the character model and the image captured by the recognition module, and adjusts the second adjustment plan accordingly;

[0148] Personnel data changes include personnel seat adjustments, personnel shortages, and personnel physiological changes;

[0149] Due to unexpected situations such as seat adjustments, staff shortages, and physiological changes, the monitoring module uses the character model and recognition module to promptly determine changes in personnel data during the initial stage of the second adjustment plan to change the light source, so that timely adjustments can be made.

[0150] Among them, the physiological change of the person is the change in height during puberty, so that the current person's height matches the brightness value of the distance node, and the second adjustment plan is revised;

[0151] Determine the eye usage data of the person according to the recognition module and the monitoring module, the eye usage data of the person including the eye usage time and eye usage angle;

[0152] Set the eye fatigue threshold. When the eye use time exceeds the eye fatigue threshold, the prompt module will remind the person and correct the person's eye angle through historical data.

[0153] Sitting forward shortens the distance between the eyes and objects to less than 30 cm (normal should be 50-70 cm), causing continuous tension in the ciliary muscles and accelerating lens accommodation fatigue;

[0154] Tilting the head or body may block the light source, resulting in partial shadows or screen reflections, forcing the pupils to frequently adjust light intensity, increasing the strain on the eyes.

[0155] When concentrating, sitting in an incorrect posture may reduce the blink rate from the normal 15 times / minute to 5 times / minute, and the tear film cannot be replenished in time, resulting in dryness and burning sensation;

[0156] Long-term bowing of the head or hunching over can compress the blood vessels and nerves in the neck, reducing the blood oxygen supply to the retina, and causing chain reactions such as blurred vision and eye socket pain.

[0157] In summary, it is necessary to detect and determine the sitting posture of the person;

[0158] The historical data stores the correct sitting posture model of the simulated personnel;

[0159] The recognition module and the monitoring module record the eye usage data of each person, including the time and angle of eye usage. The eye usage angle is determined by obtaining the camera image and matching it with the simulated classroom lighting model to determine the sitting posture of the person in the camera image. The eye usage angle is then determined, and the person is prompted through the prompt module and corrected through historical data.

[0160] It should be noted that, in this document, relational terms such as first and second, etc., are used only 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 terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0161] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A classroom light environment dynamic adjustment system based on multi-source information perception, comprising: Identification module, prediction module, adjustment module and monitoring module; Its characteristics are: The recognition module is used to identify the light source, generate light source data, and collect refraction data, site data, and personnel data; The prediction module determines the lighting scene through site data, personnel data and historical data; The prediction module calculates and filters the refraction data, lighting scene, light source data and historical data to generate a first adjustment plan; The adjustment module analyzes and executes the first adjustment scheme to change the position, angle, brightness and color temperature of the light source; Setting a light source threshold, and dynamically adjusting the light source threshold according to the personnel data, refraction data, light source data, and site data; When the threshold of the light source is exceeded, the monitoring module feeds back to the prediction module, the prediction module optimizes the first adjustment plan to generate a second adjustment plan, and the adjustment module analyzes and executes the second adjustment plan; Establishing a first safe light source range table for personnel data according to the light source data; Optimize light source data based on weather data combined with historical data; Establish a second safety light source range table for personnel data based on the optimized light source data; The MEDIAN function is used to calculate the median value of the first and second safety light source range tables to optimize the second adjustment scheme to adapt it to each person.

2. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 1 is characterized by: The lighting scenes include teaching scenes, demonstration scenes and self-study scenes; The prediction module collects the teaching content of the day and locates the chapter position of the textbook to determine the teaching content of tomorrow, and combines the historical data to determine whether the teaching content of tomorrow is a teaching scene and / or a demonstration scene, or a self-study scene.

3. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 2 is characterized by: The prediction module is preset with a three-dimensional model of the classroom; Creating a character model based on the personnel data and importing it into the three-dimensional model of the classroom; The image captured by the recognition module is corrected through the classroom three-dimensional model and the character model to accurately obtain the light source data, and the first adjustment scheme, the second adjustment scheme and the dark environment adjustment scheme are optimized based on the accurate light source data.

4. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 3 is characterized by: Determine a light source adjustment range according to the middle value of the first safe light source range table and the middle value of the second safe light source range table, wherein the light source adjustment range adopts zoned light control and step-by-step adjustment; The zoned light control includes dividing the light and dark intensity areas according to the site data and the personnel data, and adjusting the dark intensity areas and the light intensity areas in sequence; The step-by-step adjustment includes determining a brightness threshold according to personnel data, and gradually adjusting the light source according to the brightness threshold in combination with a light source adjustment range and a time node.

5. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 2 is characterized by: The identification module includes a light sensor and a camera; The prediction module determines the natural light transformation in each time period in combination with weather data to generate determination data; Presetting the camera parameters based on the determination data to adapt to light changes caused by weather changes; The second control scenario is optimized again using the decision data.

6. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 5 is characterized by: The light source includes natural light and unnatural light; The light sensor is used to detect natural light and unnatural light in the classroom and record data of natural light and unnatural light; The monitoring module stores non-natural light source values, compares the non-natural light data detected by the light sensor with the stored non-natural light source values, determines whether there is light decay and excessive stroboscopic light source, and modifies the stored non-natural light source values. The second adjustment scheme adjusts the light source according to the modified stored non-natural light source values. Among them, the position of the light source with excessive stroboscopic light source and light source attenuation is determined, and communication maintenance is carried out.

7. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 6 is characterized by: The monitoring module determines changes in the personnel data based on the person model and the image captured by the recognition module, and adjusts the second adjustment plan accordingly; The personnel data changes include personnel seat adjustments, personnel shortages, and personnel physiological changes.

8. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 5 is characterized by: The prediction module is used to collect sounds and combine historical data to determine human behavior through big data analysis, and assist in determining lighting scenes.

9. The classroom light environment dynamic adjustment system based on multi-source information perception according to claim 8 is characterized by: Determine the eye usage data of the person according to the identification module and the monitoring module, wherein the eye usage data of the person includes the eye usage time and the eye usage angle; A threshold value of eye fatigue value is set. When the eye use time exceeds the threshold value of eye fatigue value, the person is prompted through the prompt module, and the person's eye angle is corrected according to the historical data.

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