Indoor illuminance detection method, system and equipment

Abstract

The invention discloses an indoor illuminance detection method. The method comprises the following steps: acquiring indoor illumination data and indoor space data of a target space; determining light attenuation values of different light sources in the target space according to the indoor illumination data and the indoor space data; determining an actual lumen value in the target space according to the light attenuation values of the different light sources; determining a simulated lumen value in the target space according to the indoor space data; and generating a detection result for indicating whether the indoor illuminance of the target space is qualified or not according to the actual lumen value and the simulated lumen value. According to the method, factors such as indoor furniture and wall colors which can block or absorb light are considered, and meanwhile, the actual lumen value obtained through detection is compared with the simulated lumen value obtained through ideal simulation of indoor space data, so that the accuracy of an indoor illuminance detection result is improved.

Description

Technical Field

[0001] This invention relates to the field of indoor lighting testing technology, and in particular to a method, system and equipment for indoor lighting intensity testing. Background Technology

[0002] Indoor lighting is an indispensable part of people's daily life, work, and study environment. Appropriate lighting not only provides people with a comfortable visual experience and protects eye health, but also improves work efficiency and quality of life to a certain extent. Different indoor scenarios, such as homes, offices, school classrooms, and hospital wards, have different requirements for light intensity. For example, studies need higher lighting to meet the needs of reading and writing, while bedrooms need relatively soft light to create a restful atmosphere.

[0003] As people's requirements for quality of life and working environment continue to improve, they are paying more and more attention to the precise control and scientific management of indoor lighting. Furniture is an unavoidable obstruction in indoor spaces, which will directly block, absorb or reflect light. Bookshelves may block the light from the ceiling lights onto the table, and dark sofas will absorb some light, resulting in a decrease in the surrounding illuminance.

[0004] However, most indoor illuminance testing currently relies on manual operation, directly measuring indoor illuminance from multiple light fixtures. This manual testing does not take into account the influence of furniture and wall colors on light, resulting in a discrepancy between the measured lumen value used to reflect illuminance and the actual illuminance perceived by the human eye.

[0005] Therefore, existing technologies that rely on manual detection of indoor lighting do not adequately consider factors such as indoor furniture and wall colors that may block or absorb light, resulting in low accuracy of the detection results. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the present invention aims to provide an indoor lighting intensity detection method, system and equipment that takes into account factors such as indoor furniture and wall colors that may block or absorb light, thereby effectively improving the accuracy of indoor lighting detection results.

[0007] To solve the above problems, the present invention is implemented according to the following solution: A method for detecting indoor illuminance is provided, including: Acquire indoor lighting data and indoor space data of the target space; Based on the indoor lighting data and the indoor space data, determine the light attenuation value of different light sources in the target space; The actual lumen value within the target space is determined based on the light attenuation value of different light sources; Based on the indoor space data, determine the simulated lumen value within the target space; Based on the actual lumen value and the simulated lumen value, a test result is generated to indicate whether the indoor illuminance of the target space is qualified.

[0008] Compared with existing technologies, the beneficial effects of the indoor illuminance detection method of the present invention are as follows: Based on indoor lighting data and indoor space data used to indicate the presence of indoor obstructions or light-absorbing objects, a light attenuation value is determined to fully consider factors such as indoor furniture and wall colors that may obstruct or absorb light; at the same time, the actual lumen value detected is compared with the simulated lumen value obtained by idealizing the indoor space data to quantify the deviation between the actual lighting environment and the ideal lighting state, effectively avoiding the problem of deviation between the detection results and the actual situation caused by traditional detection methods ignoring actual space factors such as furniture obstruction and wall color light absorption.

[0009] Optionally, the indoor lighting data includes lighting data for different functional areas within the target space; Acquire indoor lighting data for the target space, including: Acquire the original lighting data of different functional areas within the target space; Feature extraction is performed on the original lighting data to obtain multidimensional data of the original lighting data; Based on the multidimensional data, lighting data for different functional areas within the target space are obtained.

[0010] Optionally, based on the indoor lighting data and the indoor space data, the light attenuation values ​​of different light sources in the target space are determined, including: Based on the indoor space data, establish the light propagation paths of different light sources within the target space; The light attenuation value is determined based on at least one of the indoor lighting data and the light propagation path.

[0011] Optionally, the light attenuation value includes an occlusion attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the obstruction of the light source during propagation and the corresponding material of the obstruction; Based on the material of the shield, determine the absorption rate of the shield to the light source; Based on the obstruction and the light source, determine the obstruction ratio between the obstruction and the light source; The shading attenuation value is determined based on the indoor lighting data, the absorption rate, and the shading ratio.

[0012] Optionally, the light attenuation value may also include a reflection attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the number of reflections of the light source during propagation and the reflective material corresponding to the reflective surface; Based on the reflective material, determine the reflectivity of the light source on the reflective surface; The reflection attenuation value is determined based on the indoor lighting data and the reflectivity.

[0013] Optionally, the light attenuation value may also include a distance attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the actual path length of the light source during propagation; The distance attenuation value is determined based on the indoor lighting data and the actual path length.

[0014] Optionally, the light attenuation value may also include an environmental scattering attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Acquire environmental data within the target space; Based on the environmental data, determine the environmental scattering coefficient; The environmental scattering attenuation value is determined based on the indoor lighting data and the environmental scattering coefficient.

[0015] Optionally, based on the indoor space data, determining the simulated lumen value within the target space includes: Based on the indoor space data, construct a three-dimensional model of the target space; Based on a preset optical model, a virtual light source is generated for the three-dimensional model; Based on the virtual light source, a heat map is generated to indicate the illumination distribution corresponding to different lumen values ​​within the target space; The simulated lumen value is determined based on the heat map.

[0016] An indoor illuminance detection system is also provided, which applies the above-mentioned indoor illuminance detection method, including: The data acquisition module is used to acquire indoor lighting data and indoor space data of the target space; The illumination analysis module is used for: Based on the indoor lighting data and the indoor space data, determine the light attenuation value of different light sources in the target space; The actual lumen value within the target space is determined based on the light attenuation value of different light sources; The indoor analysis module is used to determine the simulated lumen value in the target space based on the indoor space data. The result generation module is used to generate a test result indicating whether the indoor illuminance of the target space is qualified, based on the actual lumen value and the simulated lumen value.

[0017] A computer device is also provided, including a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the processor loads and executes the at least one instruction, at least one program, code set or instruction set to implement the indoor illumination detection method described above. Attached Figure Description

[0018] Figure 1 This is a flowchart of the detection method of the present invention. Detailed Implementation

[0019] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0020] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0021] See Figure 1 As shown, an indoor illuminance detection method of the present invention includes: S1: Acquire indoor lighting data and indoor space data of the target space; In one embodiment of the present invention, the indoor lighting data includes lighting data of different functional areas within the target space; Acquiring indoor lighting data of the target space includes: acquiring original lighting data of different functional areas within the target space; extracting features from the original lighting data to obtain multidimensional data of the original lighting data; and obtaining lighting data of different functional areas within the target space based on the multidimensional data.

[0022] In one embodiment of the present invention, the sensors used to acquire indoor lighting data include three different types of sensors: silicon photodiode sensors, spectral sensors, and color temperature sensors. The sensors are arranged based on indoor functional zoning. Specifically, the three different types of sensors are provided in different functional areas of the target space to cover the key indoor lighting areas of the target space, rather than being located in one place.

[0023] In one embodiment of the present invention, before extracting features from the original lighting data to obtain multidimensional data of the original lighting data, it is necessary to perform data preprocessing on the original lighting data, including data cleaning, data standardization, and data smoothing. Data cleaning is used to remove outliers and missing values ​​in the original lighting data caused by sensor failure, environmental interference, etc., to avoid invalid data affecting subsequent detection results. Data standardization is used to unify lighting data (such as brightness, color temperature, etc.) collected by different sensors of different magnitudes and units into the same numerical range to avoid affecting subsequent detection results. Data smoothing is used to filter out random noise in the original lighting data, making the change trend of the original lighting data more stable and realistic. After performing data preprocessing on the original lighting data, the data quality of the original lighting data is improved, ensuring the accuracy of the extracted features.

[0024] In one embodiment of the present invention, feature extraction is performed on the original lighting data, specifically extracting three features that reflect indoor lighting intensity: light intensity, color temperature, and spectrum. Light intensity is used to measure the brightness of light; color temperature is used to measure the warmth or coolness of light, which affects the comfort and suitability of the lighting environment; and spectrum is used to indicate the composition of light.

[0025] S2: Based on indoor lighting data and indoor space data, determine the light attenuation value of different light sources in the target space, including: establishing the light propagation path of different light sources in the target space based on indoor space data; and determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path.

[0026] In one embodiment of the present invention, the indoor space data includes the position information of multiple lamps for emitting light sources in the target space, the position information of furniture obstructions in the target space, and the position information of emitting surfaces (e.g., walls, furniture) in the target space. The initial emission coordinates and emission angle of the light are determined by the lamp position information. Then, based on the furniture obstruction position information and the emitting surface position information, it is determined whether there are furniture obstructions and the number of reflections of the light during its propagation to the sensor that acquires indoor lighting data.

[0027] In one embodiment of the present invention, the light attenuation value includes an obstruction attenuation value; determining the light attenuation value based on at least one of indoor lighting data and light propagation path includes: determining the obstruction object and the corresponding material of the obstruction object during the propagation of the light source based on the light propagation path; determining the absorption rate of the obstruction object to the light source based on the material of the obstruction object; determining the obstruction ratio between the obstruction object and the light source based on the obstruction object and the light source; and determining the obstruction attenuation value based on indoor lighting data, absorption rate, and obstruction ratio.

[0028] Indoor obstructions include, but are not limited to, wooden furniture and metal cabinets. Since wood and metal have different absorption rates of light emitted by the light source, in one embodiment of the present invention, the obstruction ratio between the obstruction and the light source is determined based on the obstruction and the light source. This includes: calculating the projected area of ​​the obstruction on the light propagation path based on a spatial geometry algorithm, and then comparing it with the total area of ​​the light cross section determined by the beam angle and the propagation distance to obtain the obstruction ratio.

[0029] In one embodiment of the present invention, the occlusion attenuation value is the light intensity value after the light source reaches the sensor through the light propagation path and is attenuated by the occlusion object. The calculation formula for the occlusion attenuation value is determined based on indoor lighting data, absorptivity and occlusion ratio: Occlusion attenuation value = original intensity value * (1 - absorptivity * occlusion ratio).

[0030] In one embodiment of the present invention, the light attenuation value further includes a reflection attenuation value; determining the light attenuation value based on at least one of indoor lighting data and light propagation path includes: determining the number of reflections of the light source during propagation and the reflective material corresponding to the reflective surface based on the light propagation path; determining the reflectivity of the light source on the reflective surface based on the reflective material; and determining the reflection attenuation value based on indoor lighting data and reflectivity.

[0031] Indoor reflective surfaces include, but are not limited to, walls, ceilings, and floors of different materials (such as wood flooring, tiles, and carpets). Different materials have different reflectivities of light emitted from the light source. Therefore, when calculating the reflection attenuation value, it is not only necessary to consider the number of reflections, but also to consider that the reflection effects of different materials vary. By taking a more comprehensive approach, the accuracy of subsequent indoor illuminance test results can be ensured.

[0032] In one embodiment of the present invention, the reflection attenuation value is the light intensity value after the light source reaches the sensor through the light propagation path and is attenuated by multiple reflections on different reflective surfaces. Based on indoor lighting data and reflectivity, the calculation formula for the reflection attenuation value is determined as follows: intensity after the first reflection = incident intensity * reflectivity 1, intensity after the second reflection = intensity after the first reflection * reflectivity 2, and the reflection attenuation value is obtained by calculating the intensity value after each reflection in sequence.

[0033] In one embodiment of the present invention, the light attenuation value further includes a distance attenuation value; determining the light attenuation value based on at least one of indoor lighting data and light propagation path includes: determining the actual path length of the light source during propagation based on the light propagation path; and determining the distance attenuation value based on indoor lighting data and the actual path length.

[0034] In one embodiment of the present invention, determining the actual path length of the light source during propagation based on the light propagation path includes: performing a three-dimensional model of the light propagation path, measuring the actual path length of the light from emission to reception, and improving the accuracy of determining the actual path length.

[0035] In one embodiment of the present invention, the distance attenuation value is the light intensity value after the light source reaches the sensor through the light propagation path and is attenuated by the propagation distance. According to the optical principle that "light intensity is inversely proportional to the square of the propagation distance", the influence of the propagation distance on the attenuation of the light emitted by the light source is calculated by substituting the distance parameter (actual path length). Based on indoor lighting data and the actual path length, the formula for calculating the distance attenuation value is: Distance attenuation value = Original intensity * (Reference distance / Actual path length) 2 .

[0036] In one embodiment of the present invention, the light attenuation value further includes an environmental scattering attenuation value; determining the light attenuation value based on at least one of indoor lighting data and light propagation path includes: acquiring environmental data within the target space; determining the environmental scattering coefficient based on the environmental data; and determining the environmental scattering attenuation value based on the indoor lighting data and the environmental scattering coefficient.

[0037] In one embodiment of the present invention, a temperature and humidity sensor for measuring environmental data is also included. The environmental data includes temperature and humidity. During the detection of illumination, temperature affects indoor air density. For example, when the temperature rises, the air density decreases. The density difference will change the propagation path of light in the air, resulting in changes in the degree of scattering. For example, the density unevenness formed by hot air convection will make light scattering more obvious. Humidity is related to the water vapor content in the air. When the humidity is high, there are more and larger water vapor particles in the air. These water vapor particles will have a stronger scattering effect on light. For example, in a humid environment, light is more likely to appear softer or foggy due to water vapor scattering. Therefore, different temperatures and humidity will cause differences in light scattering by changing the air state and particle conditions.

[0038] In one embodiment of the present invention, determining the environmental scattering coefficient based on environmental data includes: determining the environmental scattering coefficient based on environmental data and a preset scattering coefficient lookup table, wherein the preset heat dissipation coefficient lookup table includes a one-to-one correspondence of temperature, humidity and environmental heat dissipation coefficient. For example, for every 10% increase in humidity, the environmental scattering coefficient increases by 5%; for every 5°C increase in temperature, the environmental scattering coefficient is finely adjusted by 2%.

[0039] In one embodiment of the present invention, the environmental scattering attenuation value is the light intensity value after the light source passes through the light propagation path to the sensor and then passes through the target space after environmental attenuation. Based on indoor lighting data and environmental scattering coefficient, the calculation formula for the environmental scattering attenuation value is: Environmental scattering attenuation value = original intensity value * (1 - environmental scattering coefficient).

[0040] S3: Determine the actual lumen value in the target space based on the light attenuation values ​​of different light sources, including: determining the total attenuation value of different light sources based on the occlusion attenuation value, reflection attenuation value, distance attenuation value, and environmental attenuation value; then determining the actual intensity value of different light sources after attenuation based on the original intensity value and the total attenuation value; finally, determining the actual lumen value in the target space based on the actual intensity value.

[0041] In one embodiment of the present invention, the formula for calculating the total attenuation value is: Total attenuation value = shading attenuation value * reflection attenuation value * distance attenuation value * environmental attenuation value; the formula for calculating the actual intensity value is: Actual intensity value = original intensity value * total attenuation value.

[0042] In one embodiment of the present invention, determining the actual lumen value within the target space based on the actual intensity value includes: calculating the actual illuminated area covered by the light by acquiring the light illumination angle and propagation distance (actual path length) of the light emitted by different light sources; and then multiplying the actual illuminated area by the actual intensity value according to the physical definition of lumen value to obtain the actual lumen value.

[0043] S4: Determine the simulated lumen value in the target space based on the indoor space data, including: constructing a three-dimensional model of the target space based on the indoor space data; generating a virtual light source for the three-dimensional model based on a preset optical model; generating a heat map to indicate the lighting distribution corresponding to different lumen values ​​in the target space based on the virtual light source; and determining the simulated lumen value based on the heat map.

[0044] In one embodiment of the present invention, a three-dimensional model of the target space is constructed based on indoor space data. Specifically, after inputting indoor space data into a computer simulation system, a three-dimensional model proportional to the target space is automatically constructed. The model is imported into the system strictly according to the length, width, and height dimensions of the interior space, as well as the spatial parameters of the door, window, and wall positions (indoor space data), to ensure that the three-dimensional model can realistically reproduce the structure of the target space. Then, according to the different functional areas within the target space, the corresponding lighting standard reference requirements are selected. For example, the illuminance reference for an office area may be set to 300 lux, while that for a bedroom is 150 lux. At the same time, simulation accuracy parameters are set. Too high an accuracy will prolong the calculation time, while too low an accuracy will affect the reliability of the results. Usually, it is necessary to balance simulation efficiency and result accuracy according to actual needs, and medium or higher accuracy is selected to ensure data validity.

[0045] In one embodiment of the present invention, the preset optical model is a hybrid optical model that combines radiometry and ray tracing. Radiometry can efficiently calculate the energy transfer between surface light sources, while ray tracing can accurately simulate the reflection and refraction paths of light. The combination of the two can balance simulation speed and detail reproduction.

[0046] During the lighting simulation of the 3D model of the target space, multiple virtual light source layout schemes are automatically generated based on indoor space data (light source position, obstruction position, etc.) to cover different numbers of lamps (light sources), installation positions, and light emission angles. Based on the baseline illuminance requirements of each functional area, combined with parameters such as the beam angle and luminous efficacy of the light source, the initial lumen value range to be output by each virtual light source is calculated. Through multiple rounds of iterative calculations, the illuminance distribution of each functional area in the room under different lumen values ​​is simulated one by one, generating an illuminance heat map with distinct color gradients. The red area represents overexposure (illuminance higher than the baseline value), the blue area represents underexposure (illuminance lower than the baseline value), and the green area represents the illuminance standard area. The lighting status of each functional area is intuitively marked by color.

[0047] In one embodiment of the present invention, for different functional areas within the target space, each functional area has a corresponding heat map for each lumen value; based on the heat map, the simulated lumen value is determined, including: considering the lighting needs of each functional area and the overall energy consumption balance, selecting the scheme with the highest indoor illuminance uniformity (e.g., illuminance deviation in each area controlled within ±10%) and the lowest total lumen value from a variety of virtual light sources based on the heat map, and summing the lumen values ​​of all virtual light sources in the scheme to obtain a simulated lumen value that can simultaneously take into account the lighting effect and energy saving target.

[0048] S5: Based on the actual lumen value and the simulated lumen value, generate a test result to indicate whether the indoor illuminance of the target space is qualified, including: first, determining the target threshold to indicate the user's lighting habits; then, based on the target threshold, determining whether the actual lumen value and the simulated lumen value meet the target threshold. If they do not meet the target threshold, the test result is unqualified; if they do meet the target threshold, the test result is qualified.

[0049] In one embodiment of the present invention, determining the target threshold includes: dividing the target space into multiple functional areas according to function, determining the basic lighting characteristics and special needs of different functional areas within the target space; assigning weights to the lighting indicators of each functional area, and determining an initial benchmark threshold by combining simulated lumen values ​​and lighting standards; conducting more than three actual tests on the initial benchmark threshold range, and if the consistency between the test results and the subjective feelings of personnel reaches more than 90%, it is determined as the target threshold; otherwise, after re-dividing the functional areas, the above steps are repeated to reconfirm the target threshold.

[0050] This invention determines light attenuation values ​​based on indoor lighting data and indoor space data used to indicate the presence of indoor obstructions or light-absorbing objects, fully considering factors such as indoor furniture and wall colors that may obstruct or absorb light. Simultaneously, it compares the actual lumens value obtained from the detected values ​​with the simulated lumens value obtained through idealized simulation of the indoor space data, quantifying the deviation between the actual lighting environment and the ideal lighting state. This effectively avoids the problem of discrepancies between the detection results and actual conditions caused by traditional detection methods neglecting actual spatial factors such as furniture obstruction and wall color light absorption.

[0051] The present invention provides an indoor illuminance detection system, which applies the above-described indoor illuminance detection method, comprising: The data acquisition module is used to acquire indoor lighting data and indoor space data of the target space. Specifically, it uses three different types of sensors: silicon photocell sensors, spectral sensors, and color temperature sensors. The sensors are arranged based on the indoor functional zoning. Specifically, the three types of sensors are set in different functional areas of the target space to cover the key indoor lighting areas of the target space, and are not set in one place.

[0052] The illumination analysis module is used for: Based on indoor lighting data and indoor space data, determine the light attenuation value of different light sources in the target space; The actual lumen value within the target space is determined based on the light attenuation value of different light sources. The indoor analysis module is used to determine the simulated lumen value in the target space based on indoor space data; The result generation module is used to generate test results indicating whether the indoor illuminance of the target space is qualified, based on the actual lumen value and the simulated lumen value.

[0053] The computer device of the present invention includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the above-described method for improving the real-time performance of virtual machine interrupt handling.

[0054] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0055] The memory can be used to store the computer program or module. The processor implements various functions of the method for improving the real-time performance of virtual machine interrupt handling by running or executing the computer program or module stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0056] The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for detecting indoor illuminance, characterized in that, include: Acquire indoor lighting data and indoor space data of the target space; Based on the indoor lighting data and the indoor space data, determine the light attenuation value of different light sources in the target space; The actual lumen value within the target space is determined based on the light attenuation value of different light sources; Based on the indoor space data, determine the simulated lumen value within the target space; Based on the actual lumen value and the simulated lumen value, a test result is generated to indicate whether the indoor illuminance of the target space is qualified.

2. The method for detecting indoor illuminance according to claim 1, characterized in that, The indoor lighting data includes lighting data for different functional areas within the target space; Acquire indoor lighting data for the target space, including: Acquire the original lighting data of different functional areas within the target space; Feature extraction is performed on the original lighting data to obtain multidimensional data of the original lighting data; Based on the multidimensional data, lighting data for different functional areas within the target space are obtained.

3. The method for detecting indoor illuminance according to claim 2, characterized in that, Based on the indoor lighting data and the indoor space data, determine the light attenuation values ​​of different light sources within the target space, including: Based on the indoor space data, establish the light propagation paths of different light sources within the target space; The light attenuation value is determined based on at least one of the indoor lighting data and the light propagation path.

4. The method for detecting indoor illuminance according to claim 3, characterized in that, The light attenuation value includes the occlusion attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the obstruction of the light source during propagation and the corresponding material of the obstruction; Based on the material of the shield, determine the absorption rate of the shield to the light source; Based on the obstruction and the light source, determine the obstruction ratio between the obstruction and the light source; The shading attenuation value is determined based on the indoor lighting data, the absorption rate, and the shading ratio.

5. The method for detecting indoor illuminance according to claim 4, characterized in that, The light attenuation value also includes the reflection attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the number of reflections of the light source during propagation and the reflective material corresponding to the reflective surface; Based on the reflective material, determine the reflectivity of the light source on the reflective surface; The reflection attenuation value is determined based on the indoor lighting data and the reflectivity.

6. The method for detecting indoor illuminance according to claim 5, characterized in that, The light attenuation value also includes a distance attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Based on the light propagation path, determine the actual path length of the light source during propagation; The distance attenuation value is determined based on the indoor lighting data and the actual path length.

7. The method for detecting indoor illuminance according to claim 6, characterized in that, The light attenuation value also includes the environmental scattering attenuation value; Determining the light attenuation value based on at least one of the indoor lighting data and the light propagation path includes: Acquire environmental data within the target space; Based on the environmental data, determine the environmental scattering coefficient; The environmental scattering attenuation value is determined based on the indoor lighting data and the environmental scattering coefficient.

8. The method for detecting indoor illuminance according to claim 2, characterized in that, Based on the indoor space data, the simulated lumen value within the target space is determined, including: Based on the indoor space data, construct a three-dimensional model of the target space; Based on a preset optical model, a virtual light source is generated for the three-dimensional model; Based on the virtual light source, a heat map is generated to indicate the illumination distribution corresponding to different lumen values ​​within the target space; The simulated lumen value is determined based on the heat map.

9. An indoor illuminance detection system, employing the indoor illuminance detection method according to any one of claims 1-8, characterized in that, include: The data acquisition module is used to acquire indoor lighting data and indoor space data of the target space; The illumination analysis module is used for: Based on the indoor lighting data and the indoor space data, determine the light attenuation value of different light sources in the target space; The actual lumen value within the target space is determined based on the light attenuation value of different light sources; The indoor analysis module is used to determine the simulated lumen value in the target space based on the indoor space data. The result generation module is used to generate a test result indicating whether the indoor illuminance of the target space is qualified, based on the actual lumen value and the simulated lumen value.

10. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set, or instruction set, the at least one instruction, at least one program, code set, or instruction set being loaded and executed by the processor to implement an indoor illuminance detection method as described in any one of claims 1 to 8.

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