Ecological protection-oriented light pollution prevention and control method and system for travel building group

Abstract

The invention provides an ecological-protection-oriented travel building group light pollution prevention and control method and system, and relates to the technical field of ecological protection, and the method comprises the steps: building a light environment digital twinning system, constructing a biological spectrum sensitivity evaluation system, carrying out the space mapping of a light pollution influence range and a spectrum protection unit, and obtaining a light environment digital twinning system; a multi-layer light-proof curtain system is constructed in a light pollution prevention and control area, and a monitoring device is arranged to realize dynamic regulation and control. The method can effectively reduce the interference of the light radiation of the text travel building on the surrounding ecological environment, and protects the natural activity law of organisms.

Description

Technical Field

[0001] This invention relates to ecological protection technology, and more particularly to a method and system for controlling light pollution in cultural and tourism building complexes for ecological protection. Background Technology

[0002] With the rapid development of the cultural tourism industry, nighttime lighting of tourist buildings has become an important means of attracting tourists and enhancing the tourist experience. However, the nighttime lighting of cultural tourism buildings constructed in or around ecological protection areas significantly disrupts the living habits, migration routes, and reproductive behaviors of local organisms, especially nocturnal animals. Light pollution not only alters the diurnal rhythms of organisms but also leads to ecosystem dysfunction and reduced biodiversity.

[0003] Existing light pollution control technologies for cultural and tourism building complexes mainly rely on static light barriers or simple lighting time control, which have several limitations. First, traditional light pollution control methods lack a refined assessment of the spectral sensitivity characteristics of organisms within the area, failing to provide differentiated protection based on the spectral sensitivity of different organisms, resulting in poor control effectiveness. Second, existing technologies typically employ fixed light-blocking facilities, which cannot be dynamically adjusted according to seasonal changes, weather conditions, and biological activity patterns, lacking flexibility in protection and failing to adapt to the complex and ever-changing ecological environment. Furthermore, current light pollution control systems lack real-time monitoring and feedback mechanisms, making it impossible to respond and optimize in real time to actual light pollution conditions and biological activity, thus failing to balance the conflict between tourism lighting needs and ecological protection. Summary of the Invention

[0004] This invention provides a method and system for controlling light pollution from cultural and tourism building complexes for ecological protection, which can solve the problems in the prior art.

[0005] A first aspect of this invention provides a method for controlling light pollution from cultural and tourism building complexes for ecological protection, comprising: Acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and establish a digital twin system for the regional light environment of the building complex. Collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit; The light environment digital twin system is used to calculate the light pollution impact range of the building complex lighting equipment, and the light pollution impact range is spatially mapped with the spectral protection unit to obtain the light pollution prevention and control area; A multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold so that the intensity of the penetrating light meets the protection requirements. Radiation intensity and biological activity monitoring devices are installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtains. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtains is reduced to form dynamic light environment regulation.

[0006] Biological activity data is collected within the building complex area. Based on this data, a biological spectral sensitivity assessment system is constructed. The biological activity area is divided into multiple spectral protection units, and permissible radiation thresholds are set for each spectral protection unit, including: Collect biological activity data within the building complex area, perform spatiotemporal cluster analysis on the biological activity data, and identify biological activity hotspot areas; Based on the aforementioned hotspot areas of biological activity, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation and generates a spectral sensitivity distribution map of the hotspot areas. The biological activity hotspots are spatially divided according to the spectral sensitivity distribution map to obtain initial protection zones; The initial protection zone is dynamically optimized by introducing biological migration path weights and establishing a time-series-based boundary adjustment method to transform the initial protection zone into a dynamic protection unit. The permissible radiation threshold for each dynamic protection unit is calculated based on the biological spectral sensitivity analysis system.

[0007] Based on the aforementioned biological activity hotspots, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation, generating a spectral sensitivity distribution map of the hotspots, including: Environmental spectral data of the biological activity hotspot area were collected, and the intensity values ​​of light radiation at different time points and at different wavelengths were recorded. The environmental spectral data and biological activity frequency information were subjected to time-series correlation analysis. The rate of change of biological activity intensity under different wavelength light radiation was calculated based on a sliding time window, and a spectrum-activity correlation curve was constructed. Multiple monitoring sampling points are set up in the biological activity hotspot area to record the spectral intensity data and biological activity data of each sampling point; based on the spectrum-activity correlation curve, the spectral sensitivity coefficient of each sampling point is calculated, and the spectral sensitivity coefficient is processed into a continuous form using a spatial interpolation algorithm to generate a spectral sensitivity distribution map covering the entire hotspot area.

[0008] The light pollution impact range of the building complex lighting equipment is calculated using the aforementioned digital twin system for the light environment. This light pollution impact range is then spatially mapped to the spectral protection unit to obtain the light pollution control area, which includes: Extracting luminous parameters and spatial distribution information of lighting equipment in building complexes based on a digital twin system of the light environment; In the digital twin system of the light environment, a light flux propagation path is constructed. Combining the building reflectivity and atmospheric transmittance, the energy attenuation value on each light flux propagation path is calculated. Based on the energy attenuation value, the boundary of the light pollution impact range of the building group lighting equipment is drawn. Obtain the spatial distribution information of the spectral protection units and extract the boundary coordinates of the spectral protection units; The boundary of the light pollution impact range is projected onto the boundary of the spectral protection unit using a spatial grid division method. The light flux penetration intensity and spectral protection sensitivity within each grid are calculated. The grid light pollution risk value is determined based on the product of the light flux penetration intensity and the spectral protection sensitivity. Grid areas whose light pollution risk values ​​exceed a preset risk threshold are marked as light pollution prevention and control areas.

[0009] A multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold to ensure that the intensity of penetrating light meets the protection requirements. A multi-layered light-blocking curtain system was constructed in the light pollution control area, and the initial position information of each layer of light-blocking curtain was recorded; The light-blocking effect of the light-blocking curtain is analyzed based on the ray tracing algorithm. The reflection path of light between adjacent light-blocking curtains is calculated, the minimum interlayer spacing and the maximum overlap range of the light-blocking curtain are determined, and the adjustable area of ​​the light-blocking curtain is divided according to the minimum interlayer spacing and the maximum overlap range. A collaborative adjustment method for light-blocking curtains is established within the adjustable area. By calculating the position increment of each layer of light-blocking curtains, a height-tilt angle linkage curve is constructed, so that the position changes of adjacent light-blocking curtains mutually restrict each other, ensuring that the intensity of penetrating light does not exceed the allowable radiation threshold.

[0010] A coordinated adjustment method for light-blocking curtains is established within the adjustable area. This method constructs a height-tilt angle linkage curve by calculating the positional increment of each layer of light-blocking curtains, ensuring that the positional changes of adjacent light-blocking curtains mutually constrain each other. The adjustable area is divided into multiple light-proof curtain adjustment steps, and the position coordinates of each layer of light-proof curtain at each adjustment step are obtained. Based on the location coordinates, a rule for calculating the position increment of the light-proof curtain is established, and the relative displacement between adjacent light-proof curtains is set as a constraint variable. The position increment of each layer of light-proof curtain is calculated through the constraint variable. A height-tilt angle linkage curve is constructed based on the position increment. The relationship between the lifting and rotating motions of the light-proof curtain is determined based on the position increment calculation rules of the light-proof curtain. The motion trajectory of the light-proof curtain is determined through the height-tilt angle linkage curve, so that adjacent light-proof curtains maintain a positional constraint relationship during the adjustment process.

[0011] Radiation intensity and biological activity monitoring devices are installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtains. When the monitoring data shows that the transmitted light is below the allowable radiation threshold, the overlap of the light-blocking curtains is reduced, forming a dynamic light environment control system, including: In areas where light pollution is controlled, radiation intensity and biological activity monitoring devices are installed to collect radiation intensity monitoring data and biological activity monitoring data. Based on the radiation intensity monitoring data and the biological activity monitoring data, the real-time difference between the transmitted light and the allowable radiation threshold is calculated. The real-time difference is used as the basis for adjusting the position of the light-proof curtain to determine the adjustment direction of the overlap of the light-proof curtain. The position of the light-blocking curtain is adjusted according to the adjustment direction. When the real-time difference is positive, the overlap of the light-blocking curtain is reduced; when the real-time difference is negative, the overlap of the light-blocking curtain is increased. The light environment is controlled by the dynamic adjustment of the overlap of the light-blocking curtain.

[0012] A second aspect of the present invention provides a light pollution control system for cultural and tourism building complexes for ecological protection, comprising: Module 1 is used to acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and to establish a digital twin system of the lighting environment of the building complex area; Module 2 is used to collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit. Module 3 is used to calculate the light pollution impact range of the building complex lighting equipment using the light environment digital twin system, and to spatially map the light pollution impact range with the spectral protection unit to obtain the light pollution control area; Module 4 is used to construct a multi-layer light-blocking curtain system in the light pollution control area, and to adjust the height and tilt angle of each layer of light-blocking curtain according to the permissible radiation threshold so that the intensity of penetrating light meets the protection requirements. Module 5 is used to install radiation intensity and biological activity monitoring devices in the light pollution control area, and use the monitoring data to adjust the position of the light-blocking curtain. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtain is reduced to form dynamic light environment regulation.

[0013] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0015] The beneficial effects of this application are as follows: By establishing a digital twin system for the light environment of building complexes, the impact of light pollution from lighting equipment in cultural and tourism building complexes can be accurately simulated and predicted, improving the scientific nature and accuracy of light pollution prevention and control. Based on biological activity data, a biological spectral sensitivity assessment system was constructed, dividing biological activity areas into multiple spectral protection units and setting permissible radiation thresholds. This enables differentiated light pollution protection for different biological types, meeting the refined needs of ecological protection.

[0016] By spatially mapping the light environment digital twin system with the spectral protection unit, the light pollution control area was accurately identified, avoiding the blindness and inefficiency of traditional control methods. An innovative multi-layered light-blocking curtain system was constructed, which can automatically adjust the height and tilt angle of the curtains according to the permissible radiation threshold, effectively solving the problem of poor adaptability of traditional single-mode light protection.

[0017] By setting up radiation intensity and biological activity monitoring devices, the position of the light-proof curtain can be dynamically adjusted in real time, forming a dynamic light environment regulation mechanism that responds to the laws of biological activity. This not only ensures ecological security but also takes into account the lighting needs of cultural and tourism buildings, achieving a balance between ecological protection and tourism development. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for controlling light pollution from cultural and tourism building complexes for ecological protection, as described in an embodiment of the present invention. Figure 2 This is a flowchart of the dynamic collaborative control and adjustment method for the position parameters of the light-blocking curtain system according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0021] Figure 1 This is a flowchart illustrating a method for controlling light pollution from cultural and tourism building complexes for ecological protection, as described in an embodiment of the present invention. Figure 1 As shown, the method includes: Acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and establish a digital twin system for the regional light environment of the building complex. Collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit; The light environment digital twin system is used to calculate the light pollution impact range of the building complex lighting equipment, and the light pollution impact range is spatially mapped with the spectral protection unit to obtain the light pollution prevention and control area; A multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold so that the intensity of the penetrating light meets the protection requirements. Radiation intensity and biological activity monitoring devices are installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtains. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtains is reduced to form dynamic light environment regulation.

[0022] In one optional implementation, biological activity data within the building complex area is collected, and a biological spectral sensitivity assessment system is constructed based on the biological activity data. The biological activity area is divided into multiple spectral protection units, and an allowable radiation threshold is set for each spectral protection unit, including: Collect biological activity data within the building complex area, perform spatiotemporal cluster analysis on the biological activity data, and identify biological activity hotspot areas; Based on the aforementioned hotspot areas of biological activity, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation and generates a spectral sensitivity distribution map of the hotspot areas. The biological activity hotspots are spatially divided according to the spectral sensitivity distribution map to obtain initial protection zones; The initial protection zone is dynamically optimized by introducing biological migration path weights and establishing a time-series-based boundary adjustment method to transform the initial protection zone into a dynamic protection unit. The permissible radiation threshold for each dynamic protection unit is calculated based on the biological spectral sensitivity analysis system.

[0023] Biological activity data were acquired through a multi-sensor network deployed within the building complex area. This network included infrared thermal imaging sensors, acoustic sensors, vibration sensors, and optical sensors. The infrared thermal imaging sensors employed uncooled microbolometer detectors with an operating wavelength range of 8 to 14 micrometers, a spatial resolution of 0.1 meters, a time sampling interval of 30 seconds, and a temperature resolution of 0.1 degrees Celsius. The acoustic sensors used omnidirectional condenser microphones with a frequency response range of 20 Hz to 20 kHz, a dynamic range of at least 90 dB, a sampling rate of 48 kHz, and a sampling period of 10 seconds. The vibration sensors used triaxial accelerometers with a measurement range of ±16g, a resolution of 0.001g, and a sampling frequency of 1 kHz. The optical sensors employed CMOS image sensors with a pixel resolution of 1920 × 1080, a frame rate of 30 frames per second, and an exposure time adaptively adjusted according to ambient light, ranging from 1 millisecond to 100 milliseconds.

[0024] Sensor data is transmitted in real time to the data acquisition server via a wireless communication module. The wireless communication uses the 802.11ac protocol with a transmission bandwidth of at least 100 megabits per second. The data acquisition server preprocesses the received raw data, including noise filtering, data calibration, and format standardization. Noise filtering employs the Kalman filter algorithm, the state transition matrix is ​​set according to the sensor type, and the process noise covariance and observation noise covariance are determined statistically from historical data. Data calibration is based on the sensor's factory calibration parameters and field calibration coefficients, which are updated monthly. Format standardization unifies different types of sensor data into structured records containing timestamps, location coordinates, sensor identification, numerical values, and units.

[0025] Spatiotemporal clustering analysis employs the DBSCAN algorithm to process biological activity data. Spatial distance is calculated based on Euclidean distance, while temporal distance is calculated using the absolute value of the time difference. Spatiotemporal distance is calculated through a weighted combination, with a spatial weight coefficient set to 0.7 and a temporal weight coefficient set to 0.3. The cluster radius parameter is determined based on the area of ​​the building cluster and the sensor density: for areas less than 1000 square meters, the cluster radius is set to 5 meters; for areas between 1000 and 5000 square meters, the cluster radius is set to 10 meters; and for areas greater than 5000 square meters, the cluster radius is set to 15 meters. The minimum number of cluster points is set to 5% of the total number of sensors, with a minimum of 3 points. The clustering algorithm executes iteratively, processing data from the previous 24 hours in each iteration, with a sliding window step size of 1 hour.

[0026] The identification of biological activity hotspots is based on density analysis and persistence assessment of clustering results. Density analysis calculates the intensity of biological activity per unit area within each cluster. The intensity of biological activity is calculated by integrating infrared signal intensity, acoustic energy, vibration amplitude, and optical rate of change. Infrared signal intensity is expressed as the standard deviation of temperature change, acoustic energy as the root mean square value of sound pressure level, vibration amplitude as the peak value of acceleration, and optical rate of change as the average difference between adjacent frames. These four indicators are normalized using Z-scores and then summed with equal weights. Persistence assessment statistically analyzes the frequency of occurrence of each cluster within a continuous time period. Regions with a frequency exceeding 50% are identified as stable hotspots, regions with a frequency between 20% and 50% are identified as intermittent hotspots, and regions with a frequency below 20% are identified as sporadic hotspots.

[0027] The biospectral sensitivity analysis system was constructed based on the assessment of the impact of different wavelengths of light radiation on biological activities, covering the visible light range of 380 nm to 780 nm and the near-ultraviolet light range of 280 nm to 380 nm. The width of each wavelength interval was set to 10 nm, resulting in a total of 50 spectral channels. The attenuation coefficient of biological activity intensity was calculated by comparing biological activity data under both illuminated and dark conditions. The attenuation coefficient is defined as the ratio of biological activity intensity under illuminated conditions to that under dark conditions; a ratio less than 1 indicates that light radiation inhibits biological activity, while a ratio greater than 1 indicates that light radiation promotes biological activity.

[0028] The spectral sensitivity distribution map was generated using interpolation and smoothing techniques. For wavelength channels with missing data, cubic spline interpolation was used to supplement them. A Gaussian filter was used for smoothing, with the filter standard deviation set to the width of two wavelength channels. The distribution map uses the geographic coordinates of hotspot areas as the horizontal and vertical axes, and the spectral sensitivity values ​​are color-mapped, ranging from 0 to 1, where 0 represents complete insensitivity and 1 represents extreme sensitivity. The color mapping uses a blue-green-yellow-red gradient scheme, with blue representing low sensitivity and red representing high sensitivity.

[0029] The initial spatial division of the protection zones was based on contour analysis of the spectral sensitivity distribution map, with the contour interval set to 0.1 sensitivity units. The area between adjacent contour lines constituted an initial protection zone. Each zone had relatively uniform spectral sensitivity characteristics, and the zone boundaries were fitted to smooth curves using the least squares method. The zone area was controlled within the range of 100 square meters to 1000 square meters. Zones with too small an area were merged with their adjacent zones with the closest sensitivity, while zones with too large an area were further subdivided using the K-means clustering algorithm.

[0030] Boundary dynamic optimization is achieved by introducing biological migration path weights. These migration paths are determined by analyzing the movement trajectories of biological activity hotspots over a continuous time period. Trajectory extraction employs a centroid tracking algorithm, with the centroid coordinates being the weighted average position of all biological activity points within the hotspot area. Migration path weights are calculated based on path usage frequency and migration distance, with higher weights assigned to paths that are used more frequently and have longer migration distances. Weight values ​​range from 0.1 to 1.0, with a default weight of 0.5.

[0031] The time-series-based boundary adjustment method employs a sliding time window to analyze the periodic changes in biological activity patterns. The time window length is set to 7 days, with a sliding step of 1 day. Within each time window, the daily average intensity, peak period, and trough period of biological activity are calculated. Boundary adjustment rules include: when the biological activity intensity of a partition exceeds 150% of the average intensity of adjacent partitions for three consecutive days, the boundary of that partition expands towards adjacent partitions with lower activity intensity by 10% of the original partition's equivalent radius; when the biological activity intensity of a partition is below 50% of the average intensity of adjacent partitions for three consecutive days, the boundary of that partition contracts by 10% of the original partition's equivalent radius. Boundary adjustment operations are performed every 24 hours, maintaining the connectivity and integrity of the partitions during the adjustment process.

[0032] The generation of dynamic protection units integrates the initial protection zoning and boundary adjustment results. Each dynamic protection unit includes a unique identifier, geographic boundary coordinates, spectral sensitivity parameters, biological activity characteristics, and time validity. Geographic boundaries are represented by polygons with a coordinate accuracy of 0.1 meters. The spectral sensitivity parameters record the sensitivity values ​​and corresponding confidence intervals for 50 spectral channels. Biological activity characteristics include average activity intensity, peak activity intensity, activity period distribution, and major biological types. Time validity identifies the establishment time and expected update time of the protection unit.

[0033] The permissible radiation threshold is calculated based on the sensitivity parameters and safety factors of the biospectral sensitivity analysis system. For each spectral channel, the permissible radiation threshold equals the reference radiation intensity divided by the sensitivity coefficient and then multiplied by the safety factor. The reference radiation intensity adopts the spectral radiation distribution of the natural environment recommended by the International Commission on Illumination (ICI). The safety factor is set according to biological type: 0.1 for mammals, 0.2 for birds, 0.5 for insects, and 0.8 for plants. The final permissible radiation threshold is the minimum value of the thresholds corresponding to all relevant biological types, ensuring adequate protection for all organisms in the area.

[0034] In one optional implementation, based on the biological activity hotspot region, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation, generating a spectral sensitivity distribution map of the hotspot region, including: Environmental spectral data of the biological activity hotspot area were collected, and the intensity values ​​of light radiation at different time points and at different wavelengths were recorded. The environmental spectral data and biological activity frequency information were subjected to time-series correlation analysis. The rate of change of biological activity intensity under different wavelength light radiation was calculated based on a sliding time window, and a spectrum-activity correlation curve was constructed. Multiple monitoring sampling points are set up in the biological activity hotspot area to record the spectral intensity data and biological activity data of each sampling point; based on the spectrum-activity correlation curve, the spectral sensitivity coefficient of each sampling point is calculated, and the spectral sensitivity coefficient is processed into a continuous form using a spatial interpolation algorithm to generate a spectral sensitivity distribution map covering the entire hotspot area.

[0035] In practical applications, spectral monitoring equipment should be deployed in areas of high activity for the target organisms. This equipment should cover the visible to near-infrared wavelength range (approximately 380nm-1000nm), with a sampling frequency of once every 5 minutes to capture dynamic changes in the light environment. Simultaneously, biological activity monitoring devices, such as infrared-triggered cameras, sound recorders, or behavioral recognition sensors, should be deployed to record the frequency and intensity of the target organisms' activity.

[0036] During environmental spectral data acquisition, complete spectral curves are recorded at each time point, including light radiation intensity values ​​for different wavelength ranges (e.g., blue light: 430-490nm, green light: 490-570nm, red light: 620-750nm, etc.). To minimize interference from weather and seasonal changes, the data collection period should be no less than 14 days, ensuring sufficient data samples are available under different weather conditions. Spectral data for each monitoring point are expressed as photon flux density (μmol·m⁻¹). -2 ·s -1 ) or irradiance (W·m -2 Records are kept in units of ).

[0037] When performing time-series correlation analysis between collected environmental spectral data and biological activity frequency information, a unified time coordinate system is established, aligning the two types of data according to time labels. A sliding time window technique is employed, with a window size of 30 minutes and a sliding step of 10 minutes. Within each window, the correlation between spectral data and biological activity data is calculated. For each wavelength λ, the relationship between changes in light radiation intensity and changes in biological activity intensity at that wavelength is calculated to obtain the wavelength-dependent rate of change in biological activity.

[0038] Specifically, for wavelength λ, the change in light radiation intensity ΔI(λ) and the change in biological activity intensity ΔA within the same time window are calculated. Biological activity intensity can be quantified using indicators such as activity frequency, duration, or intensity score. The rate of change in biological activity intensity R(λ) = ΔA / ΔI(λ) is then calculated, reflecting the degree of influence of light radiation changes at wavelength λ on biological activity. By traversing all monitored wavelength ranges, a complete spectrum-activity correlation curve is constructed, representing the intensity of the influence of different wavelengths of light radiation on biological activity.

[0039] To improve analytical accuracy, multiple monitoring sampling points were set up within the hotspot area to form a monitoring grid. Depending on the size of the hotspot area and the terrain characteristics, the spacing between sampling points was typically set to 20-50 meters to ensure the grid could cover the entire study area. At each sampling point, spectral intensity data and biological activity data were recorded simultaneously for the same duration as the aforementioned environmental spectral data collection.

[0040] For each sampling point, the spectral sensitivity coefficient S is calculated based on the previously established spectrum-activity correlation curve. The spectral sensitivity coefficient calculation takes into account the degree of influence of the change in light radiation at a specific wavelength at that sampling point on biological activity, i.e., S(p, λ) = R(λ) × W(p), where p represents the location of the sampling point, and W(p) is the location weighting factor for that point, used to adjust for environmental differences at different locations.

[0041] To generate a spectral sensitivity distribution map covering the entire hotspot region, the spectral sensitivity coefficients of each sampling point are processed using a spatial interpolation algorithm. Commonly used spatial interpolation algorithms include inverse distance weighted interpolation (IDW), kriging, or spline interpolation. In practice, kriging typically provides better interpolation results, taking into account spatial autocorrelation and providing prediction error estimates.

[0042] Using a selected interpolation algorithm, the discrete sampling point spectral sensitivity coefficients are extended to the entire study area, forming a continuous distribution map. Individual sensitivity distribution maps are generated for each key wavelength range (e.g., blue, green, red light), and these can be overlaid to generate a comprehensive spectral sensitivity heatmap. The final distribution map uses color gradients to represent the sensitivity of different regions to specific wavelengths of light radiation; red typically represents high-sensitivity areas, and blue represents low-sensitivity areas.

[0043] In practical applications, taking a bird activity hotspot area within a wetland ecosystem as an example, analysis using the above methods revealed that the 430-450nm blue light band and the 650-680nm red light band have the most significant impact on bird activity, with the sensitivity coefficient in the central wetland area being higher than that in the peripheral areas. This spectral sensitivity distribution map provides a scientific basis for subsequent light pollution control and ecological protection, and can be used to formulate zoning management strategies and light environment optimization schemes.

[0044] This biological spectral sensitivity analysis system can accurately quantify the impact of different wavelengths of light radiation on biological activities in specific areas, providing data support and a theoretical basis for ecological light environment management.

[0045] In one optional implementation, the light environment digital twin system is used to calculate the light pollution impact range of the building complex lighting equipment, and the light pollution impact range is spatially mapped with the spectral protection unit to obtain the light pollution control area, which includes: Extracting luminous parameters and spatial distribution information of lighting equipment in building complexes based on a digital twin system of the light environment; In the digital twin system of the light environment, a light flux propagation path is constructed. Combining the building reflectivity and atmospheric transmittance, the energy attenuation value on each light flux propagation path is calculated. Based on the energy attenuation value, the boundary of the light pollution impact range of the building group lighting equipment is drawn. Obtain the spatial distribution information of the spectral protection units and extract the boundary coordinates of the spectral protection units; The boundary of the light pollution impact range is projected onto the boundary of the spectral protection unit using a spatial grid division method. The light flux penetration intensity and spectral protection sensitivity within each grid are calculated. The grid light pollution risk value is determined based on the product of the light flux penetration intensity and the spectral protection sensitivity. Grid areas whose light pollution risk values ​​exceed a preset risk threshold are marked as light pollution prevention and control areas.

[0046] Based on a digital twin system for the lighting environment, the luminous parameters and spatial distribution information of the lighting equipment in the building complex are extracted. This information is then imported into the lighting equipment's database through the digital twin platform, including the luminous power, spectral distribution characteristics, beam angle, and spatial coordinates of each device. For example, for LED floodlights on the building facade, parameters such as luminous flux of 1500 lumens, color temperature of 6500K, beam angle of 45°, installation height of 20 meters, and orientation towards due north are extracted. Simultaneously, the specific locations of all lighting equipment in space are recorded, establishing a spatial distribution network for the lighting equipment, facilitating the subsequent construction of luminous flux propagation paths.

[0047] In a digital twin system for the lighting environment, luminous flux propagation paths are constructed. Combining building reflectivity and atmospheric transmittance, the energy attenuation value on each luminous flux propagation path is calculated, and the boundary of the light pollution impact range of the building complex's lighting equipment is drawn based on these energy attenuation values. Specifically, a three-dimensional Cartesian coordinate system is first established, with the geometric center of the building complex as the origin, north as the positive y-axis, east as the positive x-axis, and vertically upward as the positive z-axis. Light rays are emitted from each lighting device, forming luminous flux propagation paths in space at different angles. For each light path, the reflection direction and intensity of the light on the building surface are calculated according to the law of reflection. The reflectivity of the building surface is usually set based on material properties; for example, the reflectivity of a glass curtain wall is 0.15, and that of a white wall is 0.85. The attenuation effect of atmospheric transmittance on the light is also considered; under standard atmospheric conditions, a 5% attenuation of light intensity per 100 meters can be used for calculation. Taking into account the initial light intensity, propagation distance, number of reflections, and the reflectivity and atmospheric transmittance of each reflecting surface, the energy attenuation value on each propagation path is calculated. The threshold for light pollution impact is determined based on energy attenuation. For example, when the luminous flux density attenuates to 5% of its initial value, this point can be considered the boundary of the light pollution impact range. Connecting all boundary points forms a three-dimensional closed surface, which represents the boundary of the light pollution impact range of the building complex's lighting equipment.

[0048] The spatial distribution information of spectral protection units is obtained, and their boundary coordinates are extracted. Spectral protection units include areas sensitive to light pollution, such as astronomical observatories, nature reserves, and residential areas. The spatial distribution information of these areas is obtained through a geographic information system or spatial database, and the coordinate sequence of the boundary polygon of each protection unit is recorded. For example, for an astronomical observatory, its center coordinates can be extracted as (x1, y1, z1), and its protection radius as r1; for a nature reserve, the coordinate sequence of each vertex of its boundary polygon is extracted. Simultaneously, the sensitivity levels of different spectral protection units are marked, such as astronomical observatories having a sensitivity of 5 (highest level), and residential areas having a sensitivity of 3 (medium level), etc.

[0049] A spatial grid division method is used to project the boundary of the light pollution impact range onto the boundary of the spectral protection unit. The light flux penetration intensity and spectral protection sensitivity within each grid are calculated. The light pollution risk value of the grid is determined by multiplying the light flux penetration intensity and the spectral protection sensitivity. Grid areas whose light pollution risk values ​​exceed a preset risk threshold are marked as light pollution control areas. In specific implementation, the study space is divided into regular three-dimensional grid units. The grid size can be set according to accuracy requirements, such as 10m × 10m × 10m. For each grid unit, it is determined whether it is simultaneously located within the light pollution impact range and the spectral protection unit. If so, the light flux penetration intensity within the grid unit is calculated, which can be represented by the light flux density at the grid center point, in lux. Simultaneously, the sensitivity level of the spectral protection unit to which the grid unit belongs is determined, with a value ranging from 1 to 5. The light flux penetration intensity is multiplied by the spectral protection sensitivity to obtain the grid light pollution risk value. A preset risk threshold is set; if the risk value is greater than 15, the grid is marked as a light pollution control area. The resulting visualization of the light pollution control area is displayed in the digital twin system of the light environment, providing spatial guidance for the subsequent development of targeted light pollution control strategies.

[0050] In practical applications, taking the nighttime lighting plan of a science and technology park as an example, analysis using the above methods revealed that the LED facade lighting of the high-rise buildings on the east side of the park poses a high risk of light pollution to residential areas 500 meters away, especially between 8:00 PM and 11:00 PM, when the light pollution risk value reaches 18.5, exceeding the preset threshold of 15. To address this, lighting parameters can be simulated and adjusted in a digital twin system for the light environment. For example, reducing the LED color temperature from 6500K to 3000K, decreasing the luminous flux by 30%, and adding directional shading devices can lower the light pollution risk value to 12.3, below the preset threshold, thus achieving effective light pollution control.

[0051] In one optional implementation, a multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold to ensure that the intensity of penetrating light meets the protection requirements. A multi-layered light-blocking curtain system was constructed in the light pollution control area, and the initial position information of each layer of light-blocking curtain was recorded; The light-blocking effect of the light-blocking curtain is analyzed based on the ray tracing algorithm. The reflection path of light between adjacent light-blocking curtains is calculated, the minimum interlayer spacing and the maximum overlap range of the light-blocking curtain are determined, and the adjustable area of ​​the light-blocking curtain is divided according to the minimum interlayer spacing and the maximum overlap range. A collaborative adjustment method for light-blocking curtains is established within the adjustable area. By calculating the position increment of each layer of light-blocking curtains, a height-tilt angle linkage curve is constructed, so that the position changes of adjacent light-blocking curtains mutually restrict each other, ensuring that the intensity of penetrating light does not exceed the allowable radiation threshold.

[0052] like Figure 2 As shown, the method includes: In light pollution control areas, a multi-layered light-blocking curtain system is constructed to determine the characteristics of light pollution sources and the permissible radiation thresholds for that area. The characteristics of light pollution sources include parameters such as light source type, location, and light intensity distribution, while the permissible radiation thresholds are set according to different scenarios, such as residential areas, astronomical observation areas, and ecological protection areas, which have different light pollution tolerances.

[0053] When constructing a multi-layered light-blocking curtain system, each curtain unit has an adjustable height and tilt angle. The curtain units are made of light-blocking material, and reflective, absorptive, or composite materials can be selected according to different needs. During the initial installation of the system, the curtains are arranged according to a preset layout, usually with equal spacing or with the initial spacing determined based on the distribution characteristics of light pollution sources.

[0054] The initial position information of each layer of the light-blocking curtain is recorded, including horizontal coordinates, vertical height, and initial tilt angle. This position information constitutes the initial state matrix of the light-blocking curtain system, serving as the reference data for subsequent adjustments. For a system containing n layers of light-blocking curtains, the initial position of each curtain can be represented as a combination of coordinate points and angle values.

[0055] When analyzing the shading effect of light-blocking curtains using ray tracing algorithms, a three-dimensional coordinate system is first established, mapping the light source, the light-blocking curtain, and the protected area into this coordinate system. Light rays are emitted from the light source in the form of rays. When a ray intersects the surface of the light-blocking curtain, the reflected and transmitted rays are calculated based on the optical properties of the curtain material. Through iterative calculations, the multiple reflection paths of the light rays between the various light-blocking curtains are traced until the light energy attenuates below a preset threshold or leaves the calculation area.

[0056] When calculating the reflection path, Snell's law and Fresnel's equations are applied to calculate the reflection and transmission ratios of light at different medium interfaces. By accumulating the energy loss after multiple reflections, the final light intensity distribution penetrating the system is determined. Based on this analysis, the minimum interlayer spacing and maximum overlap range of the light-blocking curtain are determined.

[0057] Minimum interlayer spacing refers to the minimum distance that must be maintained between two adjacent layers of light-blocking curtains to ensure the mechanical stability of the system and avoid interference between the curtains. This distance is determined based on the physical characteristics of the light-blocking curtains, environmental wind conditions, and operation and maintenance requirements. Maximum overlap refers to the maximum allowable overlap length of adjacent light-blocking curtains in the vertical projection. This parameter affects the overall light-blocking effect of the system and the light reflection path.

[0058] Based on the calculated minimum interlayer spacing and maximum overlap, each layer of the light-blocking curtain is divided into adjustable zones. The adjustable zone is represented as a two-dimensional range in both the height and angular directions, within which the light-blocking curtain can be safely and effectively adjusted in position and angle. This zone is subject to both mechanical limitations and optical performance requirements.

[0059] A coordinated adjustment method for light-blocking curtains is established within a defined adjustable area. The core of this coordinated adjustment is the construction of a height-tilt angle linkage curve, which describes the functional relationship between height changes and tilt angle changes while maintaining the light-blocking effect. In practice, the position increment of each layer of the light-blocking curtain is first calculated, that is, the amount of change in the current position relative to the initial position.

[0060] The location increment calculation considers factors such as changes in light pollution source intensity and sunlight angle, and uses an optimization algorithm to find the optimal adjustment scheme that satisfies the constraints. The optimization objective is to minimize the total energy consumption of the light-blocking curtain system while ensuring that the intensity of transmitted light does not exceed the allowable radiation threshold. In practical applications, gradient descent or genetic algorithms can be used to solve this optimization problem.

[0061] Once the height-tilt angle linkage curve is established, when the height of a certain layer of light-proof curtain needs to be adjusted due to changes in external conditions, the system automatically calculates the corresponding tilt angle change based on the linkage curve and synchronously adjusts the position parameters of adjacent light-proof curtains to ensure the coordination of the entire system. During the linkage adjustment process, the position changes of each layer of light-proof curtain are mutually restrictive, forming a dynamic equilibrium system.

[0062] In actual operation, the intensity of transmitted light is periodically monitored and compared with the allowable radiation threshold. If the detected value exceeds the threshold, an emergency adjustment mechanism is activated to temporarily increase the overlap of the light-blocking curtains or adjust their tilt angle to enhance the shading effect. The system can also preset multiple adjustment schemes based on seasonal changes, weather conditions, and other factors to achieve intelligent management of the light-blocking curtain system.

[0063] By constructing and adjusting the aforementioned multi-layered light-blocking curtain system, the impact of light pollution on specific areas can be effectively controlled, ensuring that the light environment of the protected area meets requirements, while minimizing system energy consumption and maintenance costs. This method is particularly suitable for locations requiring precise control of lighting conditions, such as observatories, ecological reserves, and precision optical laboratories.

[0064] In one optional implementation, a coordinated adjustment method for the light-blocking curtains within the adjustable area is established. This method constructs a height-tilt angle linkage curve by calculating the positional increment of each layer of light-blocking curtains, ensuring that the positional changes of adjacent light-blocking curtains mutually constrain each other. The adjustable area is divided into multiple light-proof curtain adjustment steps, and the position coordinates of each layer of light-proof curtain at each adjustment step are obtained. Based on the location coordinates, a rule for calculating the position increment of the light-proof curtain is established, and the relative displacement between adjacent light-proof curtains is set as a constraint variable. The position increment of each layer of light-proof curtain is calculated through the constraint variable. A height-tilt angle linkage curve is constructed based on the position increment. The relationship between the lifting and rotating motions of the light-proof curtain is determined based on the position increment calculation rules of the light-proof curtain. The motion trajectory of the light-proof curtain is determined through the height-tilt angle linkage curve, so that adjacent light-proof curtains maintain a positional constraint relationship during the adjustment process.

[0065] The adjustable area is divided into multiple adjustment steps, each representing a discrete adjustment point. In practical applications, the adjustment area can be divided into n equidistant steps, such as 5 cm each, or unequal steps can be set according to actual needs. For a window with a height of 3 meters, if the adjustment step is set to 10 cm, 30 adjustment points can be obtained.

[0066] At each adjustment step, the position coordinates of each layer of the light-blocking curtain are obtained. Assuming the light-blocking curtain system has m layers, then m×n position coordinate points need to be determined. The position coordinates typically include the height coordinate h and tilt angle coordinate θ of the light-blocking curtain, representing the vertical position and horizontal rotation angle of the light-blocking curtain, respectively. The position coordinates of the i-th layer of the light-blocking curtain at the j-th step can be expressed as (h_ij, θ_ij). The position coordinates can be obtained through pre-design or dynamic calculation based on sunlight conditions.

[0067] Based on the acquired location coordinates, a rule for calculating the position increment of the light-blocking curtains is established. The core of this rule is to set the relative displacement between adjacent light-blocking curtains as a constraint variable to ensure that adjacent light-blocking curtains maintain an appropriate distance and avoid mutual interference. For adjacent light-blocking curtains of layer i and layer i+1, their relative displacement can be defined as Δh_i = h_(i+1) - h_i, and the relative angle difference is Δθ_i = θ_(i+1) - θ_i.

[0068] The position increment calculation needs to consider two constraints: vertical position constraints and angular constraints. In the vertical direction, it is necessary to ensure that the minimum safe distance d_min is maintained between adjacent light-blocking curtains, i.e., Δh_i ≥ d_min; in the angular direction, the angular difference between adjacent light-blocking curtains needs to meet a certain range, usually |Δθ_i| ≤ θ_max, where θ_max is the maximum allowable angular difference. This ensures a uniform light blocking effect.

[0069] In practical applications, the specific d_min and θ_max values ​​can be determined based on the size parameters and installation requirements of the light-blocking curtain. For example, for a light-blocking curtain with a width of 60 cm, d_min can be set to 10 cm and θ_max to 15 degrees. When adjusting the light-blocking curtain, if it is found that adjacent light-blocking curtains do not meet these constraints, their positions or angles need to be adjusted.

[0070] Through iterative calculations, the position increment of each layer of the light-blocking curtain as it moves from one adjustment step to the next is determined. For the i-th layer of the light-blocking curtain moving from the j-th step to the (j+1)-th step, the height increment is Δh_ij = h_i(j+1) - h_ij, and the angle increment is Δθ_ij = θ_i(j+1) - θ_ij. These increment values ​​constitute the movement trajectory of the light-blocking curtain during the adjustment process.

[0071] Based on the calculated position increments, a height-tilt angle linkage curve is constructed. This curve describes how the tilt angle should change accordingly when the vertical position of the light-blocking curtain changes. For each layer of the light-blocking curtain, its height-tilt angle linkage curve can be represented as a series of point sets {(h_ij, θ_ij) | j = 1, 2, ..., n}. To obtain a continuous curve, interpolation methods, such as linear interpolation or spline interpolation, can be used to construct a continuous function θ_i = f_i(h_i).

[0072] When constructing the height-tilt angle linkage curve, it is necessary to ensure the smoothness and continuity of the curve to avoid abrupt changes in the light-blocking curtain during adjustment. This can be achieved by setting appropriate interpolation methods and boundary conditions. For example, cubic spline interpolation can be used to ensure that the first and second derivatives are continuous at each node.

[0073] Based on the calculation rules for the position increment of the light-proof curtain and the height-tilt angle linkage curve, the relationship between the lifting and rotating motions of the light-proof curtain is determined. When the height of the light-proof curtain changes, the corresponding tilt angle value can be queried through the linkage curve to achieve coordinated changes in height and tilt angle. This linkage relationship can be expressed as: when the height of the i-th layer of the light-proof curtain is h_i, its tilt angle should be θ_i = f_i(h_i).

[0074] In practical control, interpolation algorithms can be used to interpolate between known height and inclination points to obtain the inclination value at any height. For example, for the case where the height h_i is between [h_ij, h_i(j+1)], the corresponding inclination angle θ_i can be calculated by linear interpolation as θ_i = θ_ij + (θ_i(j+1) - θ_ij) × (h_i - h_ij) / (h_i(j+1) - h_ij).

[0075] The movement trajectory of the light-blocking curtains is determined by a height-tilt angle linkage curve, ensuring that adjacent curtains maintain a positional constraint relationship during adjustment. When one layer of the light-blocking curtain moves, the adjacent curtains will adjust accordingly based on the positional constraint relationship, ensuring the coordination and shading effect of the entire system. This constraint relationship is achieved through the aforementioned position increment calculation rules, ensuring that adjacent curtains meet the requirements for safe distance and angle difference under any adjustment state.

[0076] Ultimately, this collaborative adjustment method enables intelligent control of the light-blocking curtain system, optimizing the shading effect while avoiding interference between light-blocking curtains, thus improving the system's safety and reliability.

[0077] In one optional implementation, a radiation intensity and biological activity monitoring device is installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtain. When the monitoring data shows that the transmitted light is below the allowable radiation threshold, the overlap of the light-blocking curtain is reduced, forming a dynamic light environment control system, including: In areas where light pollution is controlled, radiation intensity and biological activity monitoring devices are installed to collect radiation intensity monitoring data and biological activity monitoring data. Based on the radiation intensity monitoring data and the biological activity monitoring data, the real-time difference between the transmitted light and the allowable radiation threshold is calculated. The real-time difference is used as the basis for adjusting the position of the light-proof curtain to determine the adjustment direction of the overlap of the light-proof curtain. The position of the light-blocking curtain is adjusted according to the adjustment direction. When the real-time difference is positive, the overlap of the light-blocking curtain is reduced; when the real-time difference is negative, the overlap of the light-blocking curtain is increased. The light environment is controlled by the dynamic adjustment of the overlap of the light-blocking curtain.

[0078] Radiation intensity monitoring devices and biological activity monitoring devices are deployed in the light pollution control area. The radiation intensity monitoring devices can include various photosensitive sensors, such as photodiode arrays and spectrometers, capable of detecting the intensity distribution of light at different wavelengths. These sensors are distributed in a grid pattern within the control area, spaced 5-10 meters apart, to ensure the spatial representativeness of the collected data. The biological activity monitoring devices include infrared cameras, ultrasonic detectors, and bioacoustic monitoring equipment, used to collect biological response data such as animal activity status and plant growth within the area. All these monitoring devices are connected to a central data processing unit for real-time data transmission and storage.

[0079] The data collected by the monitoring device is divided into two categories: radiation intensity monitoring data and biological activity monitoring data. Radiation intensity monitoring data records the wavelength, intensity, incident angle, and temporal variation characteristics of light, forming a light pollution characteristic matrix. Biological activity monitoring data includes parameters such as the frequency of biological activity, changes in activity range, and fluctuations in physiological indicators. These parameters can be used to assess the actual impact of light pollution on organisms.

[0080] The data processing unit calculates the real-time difference between transmitted light and the permissible radiation threshold based on collected radiation intensity monitoring data and biological activity monitoring data. The permissible radiation threshold is a pre-set safe lighting standard based on the characteristics of the biological population in the area. For example, the permissible radiation threshold for nocturnal animal areas is usually set within 1.5 times the intensity of natural moonlight. An adaptive weighting algorithm is used in the calculation process to dynamically adjust the weights of various monitoring indicators according to different time periods and different biological activity states, improving the scientific accuracy of the difference calculation.

[0081] After the real-time difference is calculated, it is used as the basis for adjusting the position of the light-blocking curtain to determine the direction of adjustment of the overlap of the light-blocking curtain. When the real-time difference is positive, it indicates that the current transmitted light is lower than the allowable radiation threshold. At this time, the overlap of the light-blocking curtain can be appropriately reduced to increase the ambient light. When the real-time difference is negative, it indicates that the current light radiation exceeds the allowable threshold. The overlap of the light-blocking curtain needs to be increased to reduce light pollution.

[0082] The position adjustment of the light-blocking curtain is achieved through an electric control system, which includes a stepper motor, a transmission device, and a position feedback device, enabling precise control of the overlap of the curtain. The light-blocking curtain adopts a multi-layer structure design, consisting of an outer layer of semi-transparent material with 80% light transmittance and an inner layer of light-blocking material with 20% light transmittance. The overlap between the two layers can be steplessly adjusted within the range of 0-100%, achieving precise control over the intensity of transmitted light.

[0083] When it is determined that the overlap of the light-blocking curtain needs to be reduced, the control system calculates the optimal adjustment range, adhering to the principle that the overlap adjustment should not exceed 5% at a time, to prevent stress responses to organisms caused by sudden changes in the light environment. After the adjustment is executed, the monitoring system continues to collect data and calculate new real-time differences, forming a closed-loop control. If the new difference is still positive and exceeds the set threshold, the overlap is further reduced; if the difference is close to zero, the current state is maintained.

[0084] When it is determined that the overlap of the light-blocking curtains needs to be increased, the control system will prioritize adjusting the curtains facing the light source to increase their overlap and block direct sunlight to the greatest extent. The rate at which the overlap is increased can be dynamically adjusted according to the difference; the larger the difference, the faster the adjustment rate, up to 10% per minute.

[0085] A light environment control system is formed by dynamically adjusting the overlap of the light-blocking curtains. This system can also automatically adjust the baseline parameters according to seasonal changes and weather conditions. For example, the weight of biological activity monitoring data is increased during the breeding season; the allowable radiation threshold is reduced during cloudy or rainy weather to accommodate the organisms' adaptation to darker environments.

[0086] In practical applications, this technical solution can be used for light pollution control in the buffer zones of nature reserves. Taking a wetland reserve as an example, by installing 20 monitoring devices and 30 adjustable light-blocking curtains in the buffer zone, effective blocking of light pollution from adjacent urban areas was achieved. Monitoring data shows that after implementing this solution, the nocturnal activities of migratory birds in the area returned to normal, and insect community diversity increased by 15%, demonstrating the positive impact of dynamic light environment regulation on the ecosystem.

[0087] In addition, this technical solution is also applicable to the prevention and control of light pollution in the surrounding areas of astronomical observatories. By precisely adjusting the overlap of the light-blocking curtains, the basic lighting needs of the surrounding residents can be guaranteed while minimizing the interference of scattered light on astronomical observations and improving the quality of observation data.

[0088] A second aspect of the present invention provides a light pollution control system for cultural and tourism building complexes for ecological protection, comprising: Module 1 is used to acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and to establish a digital twin system of the lighting environment of the building complex area; Module 2 is used to collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit. Module 3 is used to calculate the light pollution impact range of the building complex lighting equipment using the light environment digital twin system, and to spatially map the light pollution impact range with the spectral protection unit to obtain the light pollution control area; Module 4 is used to construct a multi-layer light-blocking curtain system in the light pollution control area, and to adjust the height and tilt angle of each layer of light-blocking curtain according to the permissible radiation threshold so that the intensity of penetrating light meets the protection requirements. Module 5 is used to install radiation intensity and biological activity monitoring devices in the light pollution control area, and use the monitoring data to adjust the position of the light-blocking curtain. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtain is reduced to form dynamic light environment regulation.

[0089] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0090] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0091] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling light pollution from cultural and tourism building complexes for ecological protection, characterized in that, include: Acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and establish a digital twin system for the regional light environment of the building complex. Collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit; The light environment digital twin system is used to calculate the light pollution impact range of the building complex lighting equipment, and the light pollution impact range is spatially mapped with the spectral protection unit to obtain the light pollution prevention and control area; A multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold so that the intensity of the penetrating light meets the protection requirements. Radiation intensity and biological activity monitoring devices are installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtains. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtains is reduced to form dynamic light environment regulation.

2. The method according to claim 1, characterized in that, Biological activity data is collected within the building complex area. Based on this data, a biological spectral sensitivity assessment system is constructed. The biological activity area is divided into multiple spectral protection units, and permissible radiation thresholds are set for each spectral protection unit, including: Collect biological activity data within the building complex area, perform spatiotemporal cluster analysis on the biological activity data, and identify biological activity hotspot areas; Based on the aforementioned hotspot areas of biological activity, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation and generates a spectral sensitivity distribution map of the hotspot areas. The biological activity hotspots are spatially divided according to the spectral sensitivity distribution map to obtain initial protection zones; The initial protection zone is dynamically optimized by introducing biological migration path weights and establishing a time-series-based boundary adjustment method to transform the initial protection zone into a dynamic protection unit. The permissible radiation threshold for each dynamic protection unit is calculated based on the biological spectral sensitivity analysis system.

3. The method according to claim 2, characterized in that, Based on the aforementioned biological activity hotspots, a biological spectral sensitivity analysis system is constructed. This system calculates the attenuation coefficient of biological activity intensity for different wavelengths of light radiation, generating a spectral sensitivity distribution map of the hotspots, including: Environmental spectral data of the biological activity hotspot area were collected, and the intensity values ​​of light radiation at different time points and at different wavelengths were recorded. The environmental spectral data and biological activity frequency information were subjected to time-series correlation analysis. The rate of change of biological activity intensity under different wavelength light radiation was calculated based on a sliding time window, and a spectrum-activity correlation curve was constructed. Multiple monitoring sampling points are set up in the biological activity hotspot area to record the spectral intensity data and biological activity data of each sampling point; based on the spectrum-activity correlation curve, the spectral sensitivity coefficient of each sampling point is calculated, and the spectral sensitivity coefficient is processed into a continuous form using a spatial interpolation algorithm to generate a spectral sensitivity distribution map covering the entire hotspot area.

4. The method according to claim 1, characterized in that, The light pollution impact range of the building complex lighting equipment is calculated using the aforementioned digital twin system for the light environment. This light pollution impact range is then spatially mapped to the spectral protection unit to obtain the light pollution control area, which includes: Extracting luminous parameters and spatial distribution information of lighting equipment in building complexes based on a digital twin system of the light environment; In the digital twin system of the light environment, a light flux propagation path is constructed. Combining the building reflectivity and atmospheric transmittance, the energy attenuation value on each light flux propagation path is calculated. Based on the energy attenuation value, the boundary of the light pollution impact range of the building group lighting equipment is drawn. Obtain the spatial distribution information of the spectral protection units and extract the boundary coordinates of the spectral protection units; The boundary of the light pollution impact range is projected onto the boundary of the spectral protection unit using a spatial grid division method. The light flux penetration intensity and spectral protection sensitivity within each grid are calculated. The grid light pollution risk value is determined based on the product of the light flux penetration intensity and the spectral protection sensitivity. Grid areas whose light pollution risk values ​​exceed a preset risk threshold are marked as light pollution prevention and control areas.

5. The method according to claim 1, characterized in that, A multi-layered light-blocking curtain system is constructed in the light pollution control area. The height and tilt angle of each layer of the light-blocking curtain are adjusted according to the permissible radiation threshold to ensure that the intensity of penetrating light meets the protection requirements. A multi-layered light-blocking curtain system was constructed in the light pollution control area, and the initial position information of each layer of light-blocking curtain was recorded; The light-blocking effect of the light-blocking curtain is analyzed based on the ray tracing algorithm. The reflection path of light between adjacent light-blocking curtains is calculated, the minimum interlayer spacing and the maximum overlap range of the light-blocking curtain are determined, and the adjustable area of ​​the light-blocking curtain is divided according to the minimum interlayer spacing and the maximum overlap range. A collaborative adjustment method for light-blocking curtains is established within the adjustable area. By calculating the position increment of each layer of light-blocking curtains, a height-tilt angle linkage curve is constructed, so that the position changes of adjacent light-blocking curtains mutually restrict each other, ensuring that the intensity of penetrating light does not exceed the allowable radiation threshold.

6. The method according to claim 5, characterized in that, A coordinated adjustment method for light-blocking curtains is established within the adjustable area. This method constructs a height-tilt angle linkage curve by calculating the positional increment of each layer of light-blocking curtains, ensuring that the positional changes of adjacent light-blocking curtains mutually constrain each other. The adjustable area is divided into multiple light-proof curtain adjustment steps, and the position coordinates of each layer of light-proof curtain at each adjustment step are obtained. Based on the location coordinates, a rule for calculating the position increment of the light-proof curtain is established, and the relative displacement between adjacent light-proof curtains is set as a constraint variable. The position increment of each layer of light-proof curtain is calculated through the constraint variable. A height-tilt angle linkage curve is constructed based on the position increment. The relationship between the lifting and rotating motions of the light-proof curtain is determined based on the position increment calculation rules of the light-proof curtain. The motion trajectory of the light-proof curtain is determined through the height-tilt angle linkage curve, so that adjacent light-proof curtains maintain a positional constraint relationship during the adjustment process.

7. The method according to claim 1, characterized in that, Radiation intensity and biological activity monitoring devices are installed in the light pollution control area. The monitoring data is used to adjust the position of the light-blocking curtains. When the monitoring data shows that the transmitted light is below the allowable radiation threshold, the overlap of the light-blocking curtains is reduced, forming a dynamic light environment control system, including: In areas where light pollution is controlled, radiation intensity and biological activity monitoring devices are installed to collect radiation intensity monitoring data and biological activity monitoring data. Based on the radiation intensity monitoring data and the biological activity monitoring data, the real-time difference between the transmitted light and the allowable radiation threshold is calculated. The real-time difference is used as the basis for adjusting the position of the light-proof curtain to determine the adjustment direction of the overlap of the light-proof curtain. The position of the light-blocking curtain is adjusted according to the adjustment direction. When the real-time difference is positive, the overlap of the light-blocking curtain is reduced; when the real-time difference is negative, the overlap of the light-blocking curtain is increased. The light environment is controlled by the dynamic adjustment of the overlap of the light-blocking curtain.

8. A light pollution control system for cultural and tourism building complexes oriented towards ecological protection, used to implement the method of any one of claims 1-7, characterized in that, include: Module 1 is used to acquire three-dimensional spatial information and lighting equipment distribution data of cultural and tourism building complexes, and to establish a digital twin system of the lighting environment of the building complex area; Module 2 is used to collect biological activity data within the building complex area, construct a biological spectral sensitivity assessment system based on the biological activity data, divide the biological activity area into multiple spectral protection units, and set an allowable radiation threshold for each spectral protection unit. Module 3 is used to calculate the light pollution impact range of the building complex lighting equipment using the light environment digital twin system, and to spatially map the light pollution impact range with the spectral protection unit to obtain the light pollution control area; Module 4 is used to construct a multi-layer light-blocking curtain system in the light pollution control area, and to adjust the height and tilt angle of each layer of light-blocking curtain according to the permissible radiation threshold so that the intensity of penetrating light meets the protection requirements. Module 5 is used to install radiation intensity and biological activity monitoring devices in the light pollution control area, and use the monitoring data to adjust the position of the light-blocking curtain. When the monitoring data shows that the transmitted light is lower than the allowable radiation threshold, the overlap of the light-blocking curtain is reduced to form dynamic light environment regulation.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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