An indoor zero-blue-light-health lighting system and method

Abstract

The application discloses an indoor zero-blue-light health lighting system and method, relates to the technical field of health lighting, and comprises the following steps: first, determining lighting parameters and demands in combination with the vision of the old and the pension scene; second, constructing zero-blue-light layered lighting hardware; third, integrating various sensors and various control functions to form an intelligent control module; fourth, realizing self-adaptive lighting adjustment through multiple algorithms; and finally, applying the adjusted system to the pension scene verification, fine-tuning parameters according to feedback, and forming an adaptive scheme; through the zero-blue-light layered lighting hardware and the multi-source perception fusion algorithm, the application adapts to the vision and behavior demands of the old, adopts pure LED light sources to eliminate the harm of blue light, cooperates layered lighting with intelligent control, dynamically adjusts to meet precise lighting, reduces energy consumption, responds to the environment and behavior in real time through multiple algorithms, maintains color temperature transition and zero-blue-light output, and improves health value and experience.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of healthy lighting, in particular to an indoor zero-blue-light healthy lighting system and method. BACKGROUND

[0002] With the acceleration of global aging process, the health, comfort and intelligence of the lighting system in the elderly care scene are put forward higher requirements, the visual system of the elderly degenerates significantly, the sensitivity to light environment decreases, the traditional lighting mode is easy to cause glare, blue light hazard and illumination discomfort and other problems, long-term exposure may aggravate visual impairment and affect sleep quality, at the same time, the function of the elderly care space is complex, covering reading, washing, walking and other high-frequency behaviors, which needs differentiated lighting design to adapt to the scene demand, the existing lighting technology focuses on single parameter adjustment, lacks multi-dimensional perception and dynamic adaptation ability, and it is difficult to meet the comprehensive needs of the elderly group for healthy light environment, in addition, blue light as high-energy short-wave light may interfere with biological clock and cause retinal damage, zero-blue-light lighting becomes an important research direction in the field of healthy lighting, under this background, developing a healthy lighting system integrating multi-source perception, adaptive adjustment and zero-blue-light output becomes a key technical requirement to improve the quality of elderly care.

[0003] The traditional lighting system has many defects in the elderly care scene: first, the light source design is mainly based on general standards, without fully considering the visual degradation characteristics of the elderly, resulting in insufficient or excessive illumination, which is easy to cause eye fatigue; second, the lighting control is mostly manual or simple timing mode, which cannot realize real-time perception of human behavior and environmental changes, and it is difficult to realize scene-based dynamic adjustment; third, the problem of blue light hazard is prominent, most LED light sources contain a high proportion of blue light components, long-term use may increase the risk of cataract and macular degeneration in the elderly group; finally, the layered lighting design is missing, the coordination between the main light and the auxiliary light is poor, and the spatial illumination uniformity is insufficient, which cannot meet the precise lighting needs of behaviors such as reading and walking, although some intelligent lighting systems introduce sensors, the perception dimension is single, the decision-making algorithm lacks multi-source data fusion, resulting in adjustment lag or misoperation, and the user experience is limited. SUMMARY

[0004] The purpose of the present application is to make up for the shortcomings of the prior art, provide an indoor zero-blue-light healthy lighting system and method, aiming at the visual degradation of the elderly and the needs of the elderly care scene, realize zero-blue-light output through silicon-based yellow light and red light LED mixing light technology, eliminate blue light hazard; integrate multi-source sensors and adaptive adjustment algorithm, dynamically perceive human behavior and environmental light intensity, realize intelligent linkage of color temperature, illumination and scene; the system also formulates differentiated lighting standards, optimizes the layered lighting structure, and forms a closed-loop adaptation scheme through scene verification, and comprehensively improves the safety, comfort and health value of the elderly care lighting.

[0005] The application provides the following technical solutions to solve the above technical problems: on the one hand, an indoor zero-blue-light health lighting system, the system comprises:

[0006] The lighting parameter and demand definition module: in combination with the visual degradation characteristics of the elderly and the space function of the pension scene, the differentiated illumination standards, the color temperature range, and the color rendering index requirements of each space are determined according to the use scene differences of different areas such as bedrooms, bathrooms, and corridors, to ensure that the lighting parameters of different areas match the visual perception ability of the elderly; at the same time, according to the daily activity rules of the elderly, the color temperature parameters of each basic scene such as life activity mode, pre-sleep mode, and night wake-up mode are set, and the lighting adjustment requirements corresponding to the high-frequency behaviors of the elderly such as reading, washing, and walking are set, to provide accurate parameter basis for the subsequent hardware configuration and intelligent adjustment of the lighting system, so that the lighting output can meet the actual eye use needs of the elderly in different scenes;

[0007] The zero-blue-light layered lighting hardware construction module: pure LED lighting sources are composed of silicon-based yellow light LEDs and silicon-based red light LEDs, the spectral output is strictly controlled through multi-primary color chip light mixing technology, the blue light component is eliminated from the source, and the adverse effects of blue light on the eyes of the elderly are avoided; the main lamp, the auxiliary lamp, and the key lighting lamps are configured to form a layered lighting structure, the main lamp meets the overall basic lighting needs of the space, the auxiliary lamp supplements the local lighting blind area of the space, and the key lighting lamps intensify the lighting effect for specific functional areas, to realize the comprehensiveness and pertinence of lighting coverage; a connection interface for the intelligent control integrated module is reserved, to build a hardware channel for subsequent access of intelligent control components and realization of dynamic adjustment of lighting parameters, and to ensure the collaborative operation of all parts of the system;

[0008] The intelligent control integrated module: millimeter wave radar, infrared sensors, digital light sensors, and low-power cameras are integrated, the sensing components are connected with the lighting system through the interface, real-time capture of key information such as indoor human presence state, environmental light intensity change, and human behavior action is realized, to provide real-time and accurate data support for lighting adjustment; at the same time, multi-scene color temperature and illumination switching functions are integrated, so that the lighting system can quickly adjust the output parameters according to the scene changes; the voice control function is integrated, to facilitate the elderly with visual impairment or difficulty in movement to control the lighting through voice commands; the timing switch and the gradual brightening and dimming functions are loaded, to meet the work and rest habits of the elderly, avoid sudden lighting or extinguishing of the light to stimulate the eyes, and improve the convenience and comfort of lighting use;

[0009] Adaptive lighting adjustment module: Collect data such as human activity, ambient light intensity, and behavior through sensors, combine multi-source perception fusion weight dynamic allocation algorithm, comprehensively analyze whether the human is active in the space, whether the ambient light meets the basic lighting needs, and the matching degree of behavior and lighting needs, to determine whether to turn off the main light and adjust the auxiliary light intensity, avoid unnecessary energy consumption, and ensure that the space lighting is always in a suitable state; According to the behavior-related illumination adaptive adjustment algorithm, for the special requirements of different behaviors on light, the corresponding lamp intensity is accurately adjusted, such as increasing the lamp intensity when reading to ensure clear vision, and adjusting the illumination when walking to ensure that the path is visible; According to the color temperature-scene-time linkage adjustment algorithm, combined with related parameters such as scene type and time change, smooth dynamic adjustment of color temperature is realized, and the lighting color temperature is matched with the human biological clock and scene atmosphere; And real-time association of zero-blue spectrum real-time control algorithm, continuously monitor the spectral output of the light source, and correct the spectral deviation in time to ensure that the lighting system always maintains a zero-blue output state and protects the eye health of the elderly;

[0010] Verification and adaptation module: Apply the parameters output by the adaptive lighting adjustment module to specific scenes such as the bedside reading area in the bedroom, the mirror area in the bathroom, and the night light coverage area, detect the illumination, color temperature, spectrum, and hardware performance using professional instruments such as illuminometers, color temperature meters, and spectrometers, and determine whether the lighting output meets the preset standards and whether the hardware devices are running stably; Test the accuracy of sensor data and the precision of control functions to identify issues such as data acquisition bias of perception components and execution delay of control instructions, and ensure the reliability of system adjustment; Combine the feedback of the elderly to understand their actual feelings about lighting brightness, color temperature, and control convenience, and fine-tune parameters such as lamp intensity reference value, sensor detection sensitivity, and algorithm weight coefficient to ultimately form a lighting solution adapted to the elderly care scene and make the system more suitable for the habits and needs of the elderly;

[0011] Verify the parameters set by the lighting parameter and demand definition module: Use illuminometers, color temperature meters, and color rendering index testers to collect illumination, color temperature, and color rendering index data multiple times in key areas such as the bedside reading area in the bedroom, the mirror area in the bathroom, and the night light coverage area to confirm that the data meets the differentiated standards set in 1.1;

[0012] Verify the hardware performance of the zero-blue layered lighting hardware construction module: Detect the spectral output of the light source using a spectrometer to confirm that there is no blue light component; Test the waterproof performance of the main light, the anti-glare effect of the auxiliary light, the flexibility of the lamp head rotation / tilt of the key lighting lamps, and the stability of the clamp fixing;

[0013] Verify the control function of the intelligent control integration module: Test the accuracy of sensor data collection, as well as the execution precision of multi-scene switching, voice control instruction recognition, timing switch, and gradual brightening and dimming functions;

[0014] Parameter fine-tuning and solution adaptation: Subjective feedback from elderly users was collected, and combined with the above verification data, parameters such as the illuminance benchmark value of the lamps, the sensor detection sensitivity, and the algorithm weight coefficient were fine-tuned to finally form a lighting solution adapted to the elderly care scenario.

[0015] Furthermore, in the lighting parameters and demand definition module, the differentiated illuminance standards include: illuminance of ≥200 lux in the bedroom bedside reading area, illuminance of ≥350 lux in the bathroom mirror area, and illuminance of ≤50 lux in the night light area; the basic scenarios include: daily activity mode, bedtime mode, and nighttime wake-up mode; the corresponding color temperatures are 4000K, 3000K, and 1900±100K, respectively; the high-frequency behaviors include reading, washing up, and walking, wherein the reading behavior corresponds to a reading light illuminance benchmark value of 220 lux, a color temperature benchmark value of 3800K, and a color rendering index benchmark value Ra≥92.

[0016] Furthermore, in the zero-blue-light layered lighting hardware module, the peak wavelength of the silicon-based yellow LED is 585nm-590nm, and the peak wavelength of the silicon-based red LED is 625nm-630nm, and the two are packaged in a 3:1 ratio; the thickness of the ceiling light in the main light is ≤5cm, and the protection level of the waterproof panel is ≥IP65; the wall light in the auxiliary light uses a diffuse reflection light-emitting material, and the anti-glare value UGR≤16; the reading light in the accent lighting fixture has a 360° rotating lamp head and a 180° flip function, and the maximum opening degree of the clamp is ≥5cm.

[0017] Furthermore, in the intelligent control integrated module, the millimeter-wave radar has a detection range of 0.5m-8m, a detection angle of 120°, and a resolution of 0.1m; the data collected by the millimeter-wave radar includes the human body's presence status, the distance between the human body and the radar, and the human body's movement speed; the infrared sensor has a detection range of 1m-5m, a detection angle of 90°, and a response time ≤0.5 seconds; the data collected by the infrared sensor includes the intensity of human body infrared radiation signal and human body activity trigger signal; the digital light sensor has a measurement range of 0-20000 lux, an accuracy of ±5%, and a response time ≤100ms; the collected data includes indoor real-time illuminance value, outdoor real-time illuminance value, and indoor-outdoor illuminance difference; the low-power camera has a resolution of 1080P and a frame rate of 15fps; the collected data includes human body contour images, human body behavior action sequence frames, and the human body's position coordinates in space.

[0018] Furthermore, in the adaptive lighting adjustment module, the calculation formula for the multi-source sensing fusion weight dynamic allocation algorithm is as follows: ,in: for Integrate decision-making weights at all times. To enhance the credibility of human body recognition, ambient light intensity factor, behavior recognition matching degree, weight coefficient representing human body recognition reliability, weight coefficient representing ambient light intensity factor, weight coefficient representing behavior recognition matching degree, and .

[0019] Further, in the adaptive lighting adjustment module, a multi-source perception fusion weight dynamic allocation algorithm is combined to determine whether to turn off the main light and adjust the auxiliary light illumination. When the main light is turned off when the ambient light intensity is less than the main light turning-off threshold 0.2; for auxiliary light illumination adjustment, an auxiliary light target illumination adjustment algorithm is combined with ambient light intensity data collected by a digital light sensor to calculate the illumination value to which the auxiliary light should be adjusted. The calculation formula of the auxiliary light target illumination adjustment algorithm is: wherein: is the auxiliary light basic illumination, is the adjustment coefficient, and the auxiliary light is adjusted in illumination, represents the target illumination of the auxiliary light, is the moment fusion decision weight.

[0020] Further, in the adaptive lighting adjustment module, the calculation formula of the behavior-related illumination adaptive adjustment algorithm is: wherein: is the moment light spectrum distribution, represents the wavelength of light, represents the time variable, is the standard spectrum of a silicon-based red light LED, is the standard spectrum of a silicon-based yellow light LED, represents the weight coefficient of the silicon-based yellow light LED at time t, represents the weight coefficient of the silicon-based red light LED at time t.

[0021] Further, in the adaptive lighting adjustment module, the calculation formula of the color temperature-scene-time linkage adjustment algorithm is: wherein: is the behavior corresponding target illumination, is the basic illumination set for the behavior b in the lighting parameter and demand definition module, is the fusion weight influence coefficient, is the distance between the elderly person and the lighting area, is the attenuation coefficient, represents the inverse function, is The moment fusion decision weight.

[0022] Further, in the adaptive lighting adjustment module, the calculation formula of the zero-blue light spectrum real-time regulation algorithm is: The moment actual color temperature, The scene basic color temperature, The scene allowed fluctuation range, The scene start time, The scene end time, The moment fusion decision weight, Indicates a time variable.

[0023] On the other hand, an indoor zero-blue light health lighting method, the specific steps of the method are:

[0024] S100, parameter and demand determination: combining the visual degradation characteristics of the elderly and the space function of the pension scene, fully considering the visual characteristics of the elderly such as lens opacity and decreased retinal sensitivity, as well as the functional differences of different spaces such as bedrooms, bathrooms, and living rooms, determine the differentiated illumination standard, color temperature range, and color rendering index requirements of each space, ensure that the lighting parameters can match the visual perception ability of the elderly, and reduce visual fatigue; At the same time, according to the daily work and rest habits of the elderly such as getting up in the morning, taking a break in the afternoon, and getting up at night, set the color temperature parameters of each basic scene such as the life activity mode, the pre-sleep mode, and the night waking mode, and clearly define the corresponding lighting adjustment requirements for the high-frequency behaviors of the elderly such as reading, washing, and walking, to provide accurate basis for subsequent hardware selection, algorithm design, and function integration, and make the lighting system fit the actual use scene of the elderly from the design source;

[0025] S200, zero-blue light hardware construction: pure LED lighting sources composed of silicon-based yellow light LEDs and silicon-based red light LEDs are adopted, and the spectral composition is precisely controlled through multi-primary color chip light mixing technology to eliminate blue light output from the light source level and avoid damage to the retina of the elderly caused by blue light; According to the lighting needs of different areas of the pension scene, configure main lights, auxiliary lights, and key lighting lamps to form a layered lighting structure-the main lights are responsible for the overall basic lighting of the space, ensuring the basic brightness requirement in the area, the auxiliary lights fill the lighting blind area of the main lights, and the key lighting lamps intensify the lighting effect in specific functional areas such as bedside reading and bathroom mirror, realizing the comprehensiveness and pertinence of lighting coverage; The connection interface with the intelligent control module is reserved to build a hardware channel for subsequent access to sensing components and realize dynamic adjustment of lighting parameters, ensuring the extensibility and cooperativity of the hardware system;

[0026] ​​​S300, intelligent control integration: integrate millimeter wave radar, infrared sensor, digital light sensor and low-power camera, connect each sensing component through interface and lighting system, wherein the millimeter wave radar captures the human presence state and moving track in real time, the infrared sensor senses the human activity trigger signal, the digital light sensor monitors the indoor and outdoor illumination change, the low-power camera identifies human behavior action, multi-dimensional data collection provides real-time and accurate information support for lighting adjustment; at the same time, integrate multi-scene color temperature and illumination switching function, so that the lighting system can quickly switch parameters according to the change of the old people's activity scene; integrate voice control function, which is convenient for the old people with poor mobility or visual impairment to control the lighting through voice instructions; carry timing switch and gradual brightening and dimming function, which is in line with the old people's work and rest habits, avoids sudden lightening or extinguishing of the light to stimulate the eyes, and improves the convenience and comfort of lighting use;

[0027] S400, adaptive lighting adjustment: use sensors to collect indoor human presence, environmental light intensity, behavior action and other data, combine multi-source perception fusion weight dynamic distribution algorithm, comprehensively analyze human activity state, whether the environment light meets the demand, the matching degree of behavior and lighting, to judge whether to close the main light and adjust the auxiliary light illumination, which avoids energy waste and ensures that the space lighting is always at an appropriate level; according to the behavior associated illumination adaptive adjustment algorithm, aiming at the special requirements of reading, washing and other different behaviors to light, accurately adjust the corresponding lamp illumination, such as reading to improve the illumination to ensure clear vision, walking to adjust the illumination to ensure the path visible; according to the color temperature-scene-time linkage adjustment algorithm, combined with scene type, time change and other parameters, realize the smooth dynamic adjustment of color temperature, make the lighting color temperature match with human biological clock and scene atmosphere; and real-time association of zero blue spectrum real-time regulation algorithm, continuously monitor the light source spectrum output, timely correct the spectrum deviation, ensure that the lighting system always maintains the zero blue light output state, and protect the eye health of the old people;

[0028] S500, scene verification and adaptation: apply the output parameters to the key areas such as the bedside reading area in the bedroom, the mirror area in the bathroom, and the night light coverage area in the elderly care scene, detect the lighting parameters through professional instruments such as illuminance meter, color temperature instrument, and spectrum instrument, judge whether it meets the standard set by the lighting parameter and demand definition module, and ensure that the lighting output meets the visual needs of the elderly; simultaneously detect the hardware performance of the zero-blue light layered lighting hardware construction module, including the waterproofness of the main lamp, the anti-glare effect of the auxiliary lamp, the flexibility and stability of the key lighting lamps, and troubleshoot hardware failure hazards; test the accuracy of sensor data and the precision of control function in the intelligent control integrated module to avoid the influence of lighting adjustment effect caused by data deviation or function delay; combine the feedback of the elderly, understand the actual feelings of the elderly on lighting brightness, color temperature, and operation convenience, etc., fine-tune the parameters such as lamp illuminance reference value, sensor detection sensitivity, and algorithm weight coefficient, and finally form a lighting scheme adapted to the elderly care scene, so that the system is more suitable for the use habits and needs of the elderly.

[0029] Compared with the prior art, the indoor zero-blue light health lighting system and method have the following beneficial effects:

[0030] Firstly, the present application realizes the deep adaptation of the lighting system to the visual health and behavior needs of the elderly through the combination of the zero-blue light layered lighting hardware construction module and the multi-source perception fusion algorithm; the system uses silicon-based yellow light and silicon-based red light LEDs to form a pure LED light source, which completely eliminates the harm of blue light through multi-primary color chip light mixing technology, thereby ensuring the eye safety of the elderly from the light source level; at the same time, the collaborative design of the layered lighting structure and the intelligent control integrated module enables the system to dynamically adjust the color temperature and illuminance according to different scenes, to meet the precise lighting needs of the elderly in high-frequency behaviors such as reading, washing, and walking, thereby not only improving the comfort and health of the lighting environment, but also reducing energy consumption through the self-adaptive adjustment mechanism, to provide a safer and more humanized lighting solution for the elderly care scene.

[0031] Secondly, the present application realizes the real-time response of the lighting system to environmental changes and user behaviors through the innovative application of the multi-source perception fusion weight dynamic distribution algorithm and the behavior-related illuminance adjustment algorithm; the system integrates millimeter wave radar, infrared sensor, digital light sensor, and low-power camera, which can accurately perceive the existence, activity state, and environmental light intensity of the human body, dynamically distribute the perception weight through the algorithm, and intelligently decide the main lamp switch and auxiliary lamp illuminance adjustment; in addition, the cooperation of the color temperature-scene-time linkage adjustment algorithm and the zero-blue light spectrum real-time regulation algorithm enables the system to maintain smooth transition of color temperature and zero-blue light output at different time periods, thereby further improving the health value and user experience of the lighting environment.

[0032] Additional advantages, objects, and features of the application will be apparent to those skilled in the art upon examination of the following detailed description of the application and the accompanying drawings in which: BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0034] Figure 1 The logic architecture diagram of the indoor zero-blue-light-health lighting system module;

[0035] Figure 2 The step flow chart of the indoor zero-blue-light-health lighting method. DETAILED DESCRIPTION

[0036] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined application purposes, the specific embodiments, structures, features and effects according to the present application will be described in detail as follows in combination with the drawings and preferred embodiments.

[0037] Embodiment one:

[0038] The anti-sensitivity application of the system in the old people's bedroom night getting up scene.

[0039] Lighting parameter and demand definition module:

[0040] In combination with the visual function degradation of the elderly with age, the tolerance of the pupil to light stimulation at night is greatly reduced, and the characteristics of needing to ensure walking safety in weak light when getting up at night, and the functional attributes of the bedroom as a resting and getting-up activity space, the core lighting parameters and adjustment requirements in this scenario are clearly defined. Among them, the bedroom night light illumination is strictly set to ≤50 lux. This value can provide the elderly with basic light to clearly identify the bed edge and ground obstacles, and can also avoid strong light direct radiation to cause pupil contraction, reduce eye discomfort and temporary blurred vision. The color temperature corresponding to the getting-up mode is determined to be 1900±100K. The warm light in this color temperature range is more in line with the visual adaptation habits of the elderly at night, which can reduce the interference of light on melatonin secretion and reduce the difficulty of falling asleep again after getting up. In view of the high-frequency behavior of the elderly getting up, the lighting adjustment requirement is set to "fast response + gradual light-up" to ensure that the lighting is started in time when the elderly get up, and at the same time, through the gradual brightening of the light, the eyes have sufficient time to adapt to the change of light, avoiding the problems of dizziness and blurred vision caused by sudden light-up, and ensuring the visual safety and comfort during the getting-up process, such as Figure 1 as shown in FIG.

[0041] Zero-blue layered lighting hardware construction module:

[0042] A pure LED lighting source composed of a silicon-based yellow light LED and a silicon-based red light LED is adopted, wherein the peak wavelength of the silicon-based yellow light LED is accurately controlled at 585nm-590nm, and the peak wavelength of the silicon-based red light LED is stably at 625nm-630nm. The two are packaged in a ratio of 3:1, and the blue light component in the light source is completely eliminated through multi-primary color chip light mixing technology, realizing zero-blue output, avoiding potential damage to the macular area of the retina of the elderly from blue light from the source, especially suitable for the more fragile physiological state of the eyes at night. In the bedroom space, configure main lights, auxiliary lights and key lighting lamps to form a layered lighting structure: the main light selects a ceiling light with a thickness ≤5cm, and the waterproof panel protection grade ≥IP65, which can effectively resist the humid water vapor that may occur in the bedroom environment (such as condensation water generated by winter window ventilation), prolong the service life of the lamp and ensure the safety of electricity. The auxiliary light adopts a wall light with a diffuse reflection light material, and the anti-glare value UGR ≤16, which can evenly disperse the light to the space, avoiding the strong light spots formed by direct light of the lamp, preventing the elderly from feeling dazzling when their eyes meet the lamp. The key lighting lamps (such as reading lamps) are not used in the getting-up scenario, and the connection interface with the intelligent control integrated module is reserved to provide hardware support for data transmission and function cooperation between modules, ensuring the stability and continuity of the operation of the whole lighting system.

[0043] Intelligent control integrated module:

[0044] The integrated millimeter wave radar, infrared sensor, digital light sensor, and low-power camera are four types of core sensing components, each of which is deeply adapted to the bedroom wake-up scene: the millimeter wave radar has a detection distance of 0.5m-8m, a detection angle of 120°, and a resolution accuracy of 0.1m, can collect the existence state of the elderly in the bedroom (such as whether they are on the bed, whether they get up), the distance value from the radar (to determine the relative position of the elderly and the bedside or doorway), and the moving speed (to identify the fast or slow rhythm of the wake-up action), and provide accurate human dynamic data support for lighting adjustment; the infrared sensor has a detection distance of 1m-5m, a detection angle of 90°, and a response time of ≤0.5s, can quickly capture the infrared radiation signal strength of the human body (to distinguish between the human body and non-living things such as furniture and clothes) and the activity trigger signal (to perceive the starting moment of the elderly getting up), to ensure that the lighting starts at the first time of the wake-up behavior, avoiding the elderly groping in the dark; the digital light sensor has a measurement range of 0-20000lux, an accuracy of ±5%, and a response time of ≤100ms, can obtain the real-time illuminance value and difference (to determine whether the outdoor moonlight or street light at night interferes with the indoor lighting), and provide accurate environmental light basis for auxiliary light illuminance adjustment; the low-power camera has a resolution of 1080P and a frame rate of 15fps, can clearly collect the human contour image (to confirm that the moving object is the elderly and not a pet), the behavior action sequence frame (to record the whole process from getting up, getting off the bed, to walking towards the doorway), and the position coordinates (to accurately locate the specific position of the elderly in the bedroom), further improving the accuracy and reliability of the sensing data. The sensing components are connected to the lighting system through a dedicated interface, and the functions of multi-scene color temperature and illuminance switching, voice control, timing switch, and gradual brightening and dimming are integrated. In the wake-up scene, the transition time and brightness change amplitude of the gradual brightening and dimming function are optimized to match the elderly's night vision adaptation rhythm, avoiding discomfort caused by sudden changes in light.

[0045] Adaptive lighting adjustment module:

[0046] The sensors collect human dynamic, environmental light intensity, and behavior image data in real time and transmit them to the module core. First, the multi-source sensing fusion weight dynamic distribution algorithm is combined to calculate the fusion decision weight at time t, which comprehensively considers the human recognition reliability (to confirm that the current moving object is the elderly and in a conscious state), the environmental light intensity influence factor (to determine whether there is other interference light in the room at night), and the behavior recognition matching degree (to confirm that the current action belongs to wake-up rather than turning over or adjusting sleeping posture). The calculation formula of the multi-source sensing fusion weight dynamic distribution algorithm is: wherein: is the human recognition reliability, is the environmental light intensity influence factor, is the behavior recognition matching degree, is the fusion decision weight at time t, For behavior recognition matching degree, The weighting coefficients representing the reliability of human body recognition. This represents the weighting coefficient of the ambient light intensity influencing factor. The weight coefficients represent the matching degree of behavior recognition, and This serves as the core basis for determining whether to turn off the main light and adjust the illuminance of the auxiliary light. When an elderly person gets out of bed to get up at night, the sensor detects continuous and stable human activity signals. If the fusion decision weight calculated by the algorithm is not less than the main light-off threshold of 0.2, the main light remains off to avoid the sudden bright light from disrupting nighttime visual inertia. Subsequently, using the auxiliary light target illuminance adjustment algorithm, combined with real-time ambient light intensity data collected by the digital light sensor, the target illuminance value that the auxiliary light should be adjusted to is accurately calculated. The calculation formula for the auxiliary light target illuminance adjustment algorithm is as follows: ,in To supplement the basic illuminance of the auxiliary lamps, To adjust the coefficient, and thus adjust the illuminance of the auxiliary lights, Indicates the target illuminance of the auxiliary lights. for The system integrates decision-making weights at all times to ensure that the auxiliary light illumination remains stable within the range of ≤50 lux, which meets the basic needs of identifying obstacles when getting up at night without causing excessive light.

[0047] Next, based on the behavior-related adaptive illuminance adjustment algorithm, and considering the changes in location during the elderly person's nighttime awakening process (such as walking from the bedside to the wardrobe, or from the wardrobe to the door), the calculation formula for the behavior-related adaptive illuminance adjustment algorithm is as follows: ,in: for Spectral distribution of light source at any time Indicates the wavelength of light. Represents a time variable. This is the standard spectrum of silicon-based red LEDs. This is the standard spectrum for silicon-based yellow LEDs. This represents the weighting coefficient of the silicon-based yellow LED at time t. This represents the weighting coefficient of the silicon-based red LED at time t, which dynamically adjusts the illuminance output of the auxiliary light to ensure that the elderly can obtain uniform and suitable lighting in different areas of the bedroom, avoiding excessively dim or bright light due to differences in location.

[0048] Meanwhile, based on the color temperature-scene-time linkage adjustment algorithm, combined with the attributes of the nighttime scene, the current nighttime period (such as the difference in visual sensitivity between 2 AM and 5 AM), and related parameters, the calculation formula for the color temperature-scene-time linkage adjustment algorithm is as follows: ,in: For behavior The corresponding target illuminance, is the base illuminance defined in the lighting parameter and demand definition module for behavior b, is the fusion weight influence coefficient, is the distance of the elderly person from the lighting area, is the decay coefficient, represents the inverse function, is The moment fusion decision weight, maintain 1900±100K soft color temperature, through the slow and continuous color temperature adjustment mode, realize the smooth dynamic change of color temperature, prevent color temperature mutation cause eye fatigue.

[0049] And, real-time correlation zero blue spectrum real-time regulation algorithm, continuous monitoring of the spectral distribution of the light source, zero blue spectrum real-time regulation algorithm calculation formula is: , wherein: is The moment actual color temperature, is the scene base color temperature, is the scene allowed fluctuation range, is the scene start time, is the scene end time, is The moment fusion decision weight, represents the time variable, once detected in the spectrum appears trace blue light component, immediately adjust the silicon-based yellow light LED and silicon-based red light LED light emitting ratio, ensure that in the whole night process always maintain zero blue light output, fundamentally reduce the light on the night sensitive eyes of the elderly people stimulation.

[0050] Verification and adaptation module:

[0051] The complete system after adaptive adjustment is applied to the real elderly bedroom night getting up scene, and a 15-day actual use test is conducted on the elderly population of 60-85 years old, covering different visual degradation degrees such as mild presbyopia and moderate postoperative cataract. The verification link focuses on three aspects: first, the parameters set by the lighting parameter and demand definition module are quantitatively detected, the night light illuminance in different areas of the bedroom (bedside, doorway, corridor) is measured multiple times by a professional illuminometer to ensure that it is stable ≤50 lux, and the color temperature value in the getting up mode is continuously monitored by a color temperature instrument to ensure that it is accurately maintained at 1900±100K; second, the hardware performance of the zero-blue-light layered lighting hardware construction module is detected, the anti-glare effect of the auxiliary light is evaluated by subjective feedback of the elderly (whether there are feedbacks such as dazzling and eye acidification is recorded), the light source output is monitored by a spectrometer throughout the process to confirm that the zero-blue-light state is stable, and the main light and auxiliary light are continuously operated for 72 hours to observe whether there are faults such as flickering and sudden brightness changes; third, the control function of the intelligent control integrated module is tested, the response time from the elderly getting up action to the start of the auxiliary light is recorded (the requirement is ≤1 second), the transition effect of the gradual brightening and dimming function is observed (to ensure that there is no obvious jam in the process from dark to light), and the data coordination of components such as millimeter wave radar and infrared sensor is checked (to avoid abnormal situations such as "the sensor detects a human body but the lighting is not started"). According to the feedback of the elderly during the test, if some of the elderly reflect that the light is still slightly dazzling, the basic illuminance of the auxiliary light is adjusted to 45 lux; if there is a situation that the color temperature is slightly high in the early morning period, the time correlation parameter in the color temperature-scene-time linkage adjustment algorithm is adjusted, and finally a personalized lighting solution that adapts to different visual states of the elderly and can stably meet the anti-sensitive needs of the bedroom night getting up is formed, ensuring that every elderly person can obtain safe, comfortable and non-stimulating lighting experience during the getting up process.

[0052] In summary, the embodiment focuses on the anti-sensitive scene of the elderly getting up at night in the bedroom, and shows the complete operation process of the indoor zero-blue-light healthy lighting system. The modules work together, the lighting parameter and demand definition module sets parameters according to the visual characteristics of the elderly at night, the zero-blue-light hardware construction module avoids blue light stimulation from the source, the intelligent control integrated module accurately perceives through multiple sensors, the adaptive lighting adjustment module realizes dynamic adaptation of lighting through multiple algorithms, and the verification and adaptation module optimizes the scheme through testing. The whole system from parameter setting to hardware construction, intelligent control and verification and adaptation, fully guarantees the visual comfort and safety of the elderly during the getting up process, and fully reflects the adaptability of the system in the elderly care scene.

[0053] Embodiment two:

[0054] Application of the method in the elderly bathroom washing scene.

[0055] S100, parameter and demand determination:

[0056] Considering the visual characteristics of elderly people who experience lens opacity and decreased sensitivity of retinal photoreceptor cells due to age, requiring clear visibility of facial details (such as beards and makeup residue) while washing their faces but unable to tolerate strong light stimulation, and given the functional needs of the bathroom as a washing space, the core parameters and adjustment directions for each dimension are clearly defined. The illuminance in the bathroom mirror area is set to ≥350 lux. This value ensures uniform lighting across all areas of the face, preventing insufficient illuminance from causing elderly people to be unable to see fine dirt or the location of toiletries. Since washing is classified as a daily activity, the corresponding color temperature is determined to be 4000K. At this color temperature, objects... The color reproduction is closer to natural colors, helping seniors accurately identify the true colors of toiletries such as toothpaste and facial cleanser, reducing the chances of mistaking items due to color discrepancies. With a color rendering index (Ra) of ≥92, it clearly displays changes in facial skin tone, making it easier for seniors to observe skin conditions (such as redness, swelling, or wounds). Furthermore, considering actions seniors might take during washing, such as approaching a mirror, bending over to get water, or raising their hands to wash their face, the lighting adjustment is set to "dynamic illuminance adaptation + stable color temperature," ensuring that the lighting always meets visual needs under different actions, avoiding any impact on washing efficiency or causing eye discomfort due to lighting issues. Figure 2 As shown.

[0057] S200, built with zero blue light hardware:

[0058] This system utilizes silicon-based yellow LEDs and silicon-based red LEDs to form a pure LED lighting source. The peak wavelength of the silicon-based yellow LEDs is precisely controlled between 585nm and 590nm, while the peak wavelength of the silicon-based red LEDs is stable between 625nm and 630nm. These two LEDs are packaged in a 3:1 ratio. Multi-color chip mixing technology thoroughly filters the blue light component from the light source, achieving zero blue light output. This prevents chronic damage to the macula of the retina in the elderly from blue light at the source, and is particularly suitable for the humid environment of bathrooms where eyes are more easily irritated. In the bathroom space, a layered lighting structure of "main light + auxiliary light + accent lighting" is constructed: the main light is a ceiling light with a thickness of ≤5cm and a waterproof panel protection rating of ≥IP65, effectively resisting the corrosion of moisture generated during washing. To prevent internal moisture and short circuits in the lamps, extending their lifespan and ensuring electrical safety, auxiliary lights are installed on both sides of the mirror. These lights utilize diffuse reflective material with an anti-glare value (UGR) ≤ 16, projecting soft light onto the face and preventing direct light from creating reflective spots on the lens, thus preventing glare for the elderly when looking in the mirror. The accent lighting fixtures feature 360° rotating heads and 180° flip-up functions, with a maximum clamp opening of ≥ 5cm, allowing for flexible clamping onto the edge of the sink or mirror cabinet. This provides supplementary lighting for specific tasks such as toothpaste dispensing and shaving, meeting the needs of refined grooming. Furthermore, each lamp interface has pre-installed ports for compatibility with the intelligent control module, establishing a hardware channel for subsequent data transmission and intelligent lighting adjustment, ensuring coordinated response from all lamps.

[0059] S300, intelligent control integration:

[0060] The four types of sensing components, millimeter wave radar, infrared sensor, digital light sensor, and low-power camera, are integrated, and each component function is deeply matched with the bathroom washing scene: the millimeter wave radar has a detection distance of 0.5m-8m, a detection angle of 120°, and a resolution accuracy of 0.1m, which can collect the position coordinates of the elderly in the bathroom (such as whether to approach the mirror or the distance from the washbasin), the moving speed (to judge whether it is slow washing or quick water taking), and provide dynamic human position data for lighting adjustment; the infrared sensor has a detection distance of 1m-5m, a detection angle of 90°, and a response time of ≤0.5s, which can quickly capture the human infrared radiation signal strength (distinguish between human and towels, storage racks, and other items in the bathroom) and activity trigger signal (sense the action of the elderly entering the bathroom and starting to wash), to ensure that the lighting starts in time when the elderly enter the scene, avoiding groping in the dark; the digital light sensor has a measurement range of 0-20000 lux, an accuracy control of ±5%, and a response time of ≤100ms, which can obtain the real-time illumination value in the bathroom (such as the brightness of natural light through the window during the day), the outdoor real-time illumination value, and the difference between the two, to provide environmental light basis for judging whether additional lighting is needed; the low-power camera has a resolution of 1080P and a frame rate of 15fps, which can clearly collect the human behavior action sequence frame (such as the complete action of washing face with hands and bending down to get water), and the human contour image (confirming that the moving object is the elderly), to further improve the accuracy of behavior recognition. The various sensing components are connected to the lighting system through a special data interface, and the functions of multi-scene color temperature and illumination switching, voice control, timing switch, and gradual brightening and dimming are integrated. The voice control function can support the elderly to adjust the lighting through voice commands such as "brighten the mirror light" and "lower the color temperature" when their hands are wet or they are holding washing supplies, to improve the convenience of use; the gradual brightening and dimming function can avoid the impact on the eyes caused by sudden turning on or off of the lighting.

[0061] S400, adaptive lighting adjustment:

[0062] The various sensors collect human position, behavior action, and environmental light intensity data in real time and transmit them to the adjustment core. First, the multi-source sensing fusion weight dynamic distribution algorithm is combined to calculate the fusion decision weight at time t, considering the human recognition reliability (confirming that the current moving object is the elderly and is in the washing state, rather than a brief passing), the environmental light intensity influence factor (such as insufficient illumination in the bathroom on a cloudy day, which requires lighting compensation), and the behavior recognition matching degree (judging whether the current action belongs to the washing link or not). The calculation formula of the multi-source sensing fusion weight dynamic distribution algorithm is: , which is the core basis of lighting adjustment. When the elderly approach the mirror to start washing, the algorithm determines that the main light does not need to be turned off, and the target illuminance adjustment algorithm of the auxiliary light is used. The calculation formula of the target illuminance adjustment algorithm of the auxiliary light is: , combined with the real-time environmental light intensity data collected by the digital light sensor, the target illuminance value that the auxiliary light should reach is accurately calculated to ensure that the illuminance in the mirror area is stable at ≥350 lux, and the light is evenly covered on the face.

[0063] Then, according to the behavior-related illuminance adaptive adjustment algorithm, according to the change of the elderly's washing action (such as bending down to get water, the head is close to the washstand, and the lighting below needs to be appropriately lowered to avoid being too bright; when washing face, the face is away from the mirror, and the angle of the mirror light needs to be adjusted to enhance the light coverage), the calculation formula of the behavior-related illuminance adaptive adjustment algorithm is: , dynamically adjusts the illuminance output of the corresponding lamps to ensure that the lighting in each action stage meets the visual needs.

[0064] At the same time, according to the color temperature-scene-time linkage adjustment algorithm, combined with the washing scene attribute, the current period (such as the need for clear light in the morning washing, and slightly soft light in the evening washing) and the distance between the elderly and the lighting area, the calculation formula of the color temperature-scene-time linkage adjustment algorithm is: , maintains a stable color temperature of 4000K, and avoids visual fatigue caused by color temperature fluctuations through subtle color temperature smoothing adjustment.

[0065] And the real-time correlation zero-blue spectrum real-time regulation algorithm, the calculation formula of the zero-blue spectrum real-time regulation algorithm is: , continuously monitors the spectral distribution of the light source. Once a trace of blue light component is detected in the spectrum, the light emitting ratio of the silicon-based yellow light LED and the silicon-based red light LED is immediately adjusted to ensure that zero blue light output is maintained throughout the washing process, reducing the stimulation of light on the eyes.

[0066] S500, scene verification and adaptation:

[0067] The adaptive lighting system is applied to a real bathroom washing scene of the elderly. A group of 60-80 year old elderly people with different eye conditions such as mild presbyopia and dry eye are selected for a 10-day actual use test. The verification link focuses on three aspects: first, the lighting parameters and the standards set in the demand determination stage are tested. The illuminance is measured multiple times at different positions (forehead, chin, cheek) in front of the mirror by a professional illuminometer to ensure that it is ≥ 350 lux. The color temperature value during washing is continuously monitored by a color temperature instrument to ensure that it is stable at 4000K. The color rendering index is verified by a color restoration test card to ensure that the color of the items is not significantly deviated, the second is to test the performance of the zero-blue hardware construction. The anti-glare effect of the auxiliary lamp is evaluated by the subjective feedback of the elderly (whether eye dryness, stinging and other discomforts occur are recorded), the light source output is monitored by a spectrometer throughout the process to confirm the stability of the zero-blue state. At the same time, the flexibility of the key lighting lamps is tested to check whether the lamp head rotation and the clamping effect meet the fine use requirements, the third is to test the intelligent control integration function. The response time from the elderly entering the bathroom to the lighting starting is recorded (the requirement is ≤ 1 second), the recognition accuracy of the voice control instruction is observed (such as whether the "brighten the mirror light" instruction can be accurately executed), and the sensor data coordination is checked (to avoid abnormal situations such as "the sensor detects the lifting action but the lighting is not adjusted"). According to the test feedback, if some elderly people reflect that there is slight glare in front of the mirror, the installation angle of the auxiliary lamp is adjusted and a soft light cover is added. If the elderly feel that the light is too strong when washing in the evening, the time period associated parameters are optimized through the color temperature-scene-time linkage adjustment algorithm, and finally a personalized lighting solution is formed which is adapted to different eye conditions of the elderly and can stably meet the bathroom washing needs, ensuring that the elderly can complete the washing in a safe and comfortable lighting environment.

[0068] In summary, this embodiment relies on the bathroom washing scene of the elderly to present the specific application of the indoor zero-blue healthy lighting method. From the parameters and demand determination to fit the washing visual demand, to the zero-blue hardware construction to create adaptive light source and lamp structure, to the intelligent control integration to realize multi-component linkage, the subsequent adaptive lighting adjustment algorithm accurately adapts the lighting, and finally the scene verification and adaptation optimization scheme, the steps of the method are closely linked, which not only ensures sufficient lighting and true color during washing, but also avoids blue light damage, and also considers the operation convenience, effectively meets the lighting needs of the elderly in the washing scene, and highlights the practicality and pertinence of the method.

[0069] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, as long as the changes or modifications do not deviate from the technical solution of the present application. Any modification, change, equivalent change and modification of the above embodiments made according to the technical essence of the present application still belong to the scope of the technical solution of the present application.

Claims

1. An indoor zero-blue-light healthy lighting system, characterized in that, The system includes: Lighting parameters and requirements definition module: Combining the visual degeneration characteristics of the elderly and the spatial functions of elderly care scenarios, determine the differentiated illuminance standards, color temperature range, and color rendering index requirements for each space, and set the color temperature parameters for each basic scenario and the lighting adjustment requirements corresponding to the high-frequency behaviors of the elderly. Zero blue light layered lighting hardware module: It uses silicon-based yellow LEDs and silicon-based red LEDs to form a pure LED lighting source. It achieves zero blue light output through multi-primary color chip light mixing technology. It is configured with main lights, auxiliary lights and accent lighting fixtures to form a layered lighting structure. It also reserves a connection interface with the intelligent control integration module. Intelligent control integrated module: integrates millimeter-wave radar, infrared sensor, digital light sensor and low power camera. Each sensing component is connected to the lighting system through interface. It also integrates multi-scene color temperature and illuminance switching, voice control, timed on / off and gradual brightening and dimming functions. Adaptive lighting adjustment module: This module collects data from sensors and uses a multi-source sensing fusion weighted dynamic allocation algorithm to determine whether to turn off the main light and adjust the illuminance of the auxiliary lights. The calculation formula for the multi-source sensing fusion weighted dynamic allocation algorithm is as follows: ,in: for Integrate decision-making weights at all times. To enhance the credibility of human body recognition, Ambient light intensity is an influencing factor. For behavior recognition matching degree, The weighting coefficients representing the reliability of human body recognition. This represents the weighting coefficient of the ambient light intensity influencing factor. The weight coefficients represent the matching degree of behavior recognition, and ;when When the light intensity is less than the main light shut-off threshold by 0.2, the main light is turned off. For auxiliary light illuminance adjustment, the target illuminance adjustment algorithm for auxiliary lights is used in conjunction with ambient light intensity data collected by a digital light sensor to calculate the appropriate illuminance value for the auxiliary lights. The calculation formula for the target illuminance adjustment algorithm for auxiliary lights is as follows: ,in: To supplement the basic illuminance of the auxiliary lamps, To adjust the coefficient, and thus adjust the illuminance of the auxiliary lights, Indicates the target illuminance of the auxiliary lights. for The decision weights are integrated at all times; the illuminance of the corresponding lamps is adjusted according to the behavior-related adaptive illuminance adjustment algorithm. The calculation formula of the behavior-related adaptive illuminance adjustment algorithm is as follows: ,in: for Spectral distribution of light source at any time Indicates the wavelength of light. Represents a time variable. This is the standard spectrum of silicon-based red LEDs. This is the standard spectrum for silicon-based yellow LEDs. This represents the weighting coefficient of the silicon-based yellow LED at time t. The weighting coefficient of the silicon-based red LED at time t is represented; the color temperature is smoothly and dynamically adjusted according to the color temperature-scene-time linkage adjustment algorithm combined with relevant parameters, and the zero blue light spectrum real-time control algorithm is linked in real time to maintain zero blue light output; Verification and Adaptation Module: The parameters output by the adaptive lighting adjustment module are applied to specific scenarios. Illuminance, color temperature, spectrum and hardware performance are detected by instruments. The accuracy of sensor data and the precision of control function are tested. The parameters are fine-tuned based on feedback from elderly users to form an adaptation solution.

2. The indoor zero-blue-light healthy lighting system according to claim 1, characterized in that, In the lighting parameters and demand definition module, the differentiated illuminance standards include: illuminance of ≥200 lux in the bedroom bedside reading area, illuminance of ≥350 lux in the bathroom mirror area, and illuminance of ≤50 lux in the night light area; the basic scenarios include: daily activity mode, bedtime mode, and nighttime wake-up mode; the corresponding color temperatures are 4000K, 3000K, and 1900±100K, respectively; the high-frequency behaviors include reading, washing up, and walking, wherein the reading behavior corresponds to a reading light illuminance benchmark value of 220 lux, a color temperature benchmark value of 3800K, and a color rendering index benchmark value Ra≥92.

3. The indoor zero-blue-light healthy lighting system according to claim 1, characterized in that, In the zero-blue-light layered lighting hardware module, the peak wavelength of the silicon-based yellow LED is 585nm-590nm, and the peak wavelength of the silicon-based red LED is 625nm-630nm. The two are packaged in a 3:1 ratio. The thickness of the ceiling light in the main light is ≤5cm, and the protection level of the waterproof panel is ≥IP65. The wall light in the auxiliary light uses a diffuse reflection light-emitting material with an anti-glare value UGR≤16. The reading light in the accent lighting fixture has a 360° rotating lamp head and a 180° flip function, and the maximum opening degree of the clamp is ≥5cm.

4. The indoor zero-blue-light healthy lighting system according to claim 1, characterized in that, In the intelligent control integrated module, the millimeter-wave radar has a detection range of 0.5m-8m, a detection angle of 120°, and a resolution of 0.1m; the data collected by the millimeter-wave radar includes the presence status of the human body, the distance between the human body and the radar, and the human body's movement speed; the infrared sensor has a detection range of 1m-5m, a detection angle of 90°, and a response time ≤0.5 seconds; the data collected by the infrared sensor includes the intensity of the human body's infrared radiation signal and the trigger signal of human activity; the digital light sensor has a measurement range of 0-20000 lux, an accuracy of ±5%, and a response time ≤100ms; the collected data includes real-time indoor illuminance values, real-time outdoor illuminance values, and the difference between indoor and outdoor illuminance; the low-power camera has a resolution of 1080P and a frame rate of 15fps; the collected data includes human body contour images, human body action sequence frames, and the human body's position coordinates in space.

5. The indoor zero-blue-light healthy lighting system according to claim 1, characterized in that, In the adaptive lighting adjustment module, the calculation formula for the color temperature-scene-time linkage adjustment algorithm is as follows: ,in: For behavior The corresponding target illuminance, The base illuminance set for behavior b in the lighting parameters and requirements definition module. To integrate the weighted influence coefficients, The distance between the elderly and the lighting area, The attenuation coefficient is... Describes the inverse function. for Integrate decision-making weights at all times.

6. The indoor zero-blue-light healthy lighting system according to claim 1, characterized in that, In the adaptive lighting adjustment module, the calculation formula for the zero-blue-light spectrum real-time control algorithm is as follows: ,in: for Actual color temperature at all times The base color temperature for the scene, For the allowable fluctuation range of the scene, The start time of the scene. The end time of the scene. for Integrate decision-making weights at all times. Represents a time variable.

7. A method for indoor zero-blue-light healthy lighting, the method being applicable to the indoor zero-blue-light healthy lighting system described in any one of claims 1-6, characterized in that, The specific steps of this method are as follows: S100, Parameter and Requirements Determination: Combining the visual degeneration characteristics of the elderly and the spatial functions of elderly care scenarios, determine the differentiated illuminance standards, color temperature range, and color rendering index requirements for each space, and set the color temperature parameters for each basic scenario and the lighting adjustment requirements corresponding to the high-frequency behaviors of the elderly. S200, Zero Blue Light Hardware Construction: It adopts silicon-based yellow LEDs and silicon-based red LEDs to form a pure LED lighting source, and achieves zero blue light output through multi-primary color chip light mixing technology. It is configured with main lights, auxiliary lights and accent lights to form a layered lighting structure, and reserves a connection interface with the intelligent control module. S300, intelligent control integration: integrates millimeter-wave radar, infrared sensor, digital light sensor and low power camera, connects each sensing component to the lighting system through interface, and integrates multi-scene color temperature and illuminance switching, voice control, timed on / off and gradual brightening and dimming functions. S400, Adaptive Lighting Adjustment: It uses sensor data collection and a multi-source perception fusion weight dynamic allocation algorithm to determine whether to turn off the main light and adjust the illuminance of the auxiliary light. It adjusts the illuminance of the corresponding lamps according to the behavior-related illuminance adaptive adjustment algorithm. It achieves smooth dynamic adjustment of color temperature according to the color temperature-scene-time linkage adjustment algorithm combined with relevant parameters, and maintains zero blue light output in real time with the zero blue light spectrum real-time control algorithm. S500 Scene Verification and Adaptation: The output parameters are applied to elderly care scenarios. The instrument detects whether the lighting parameters meet the standards set by the lighting parameter and demand definition module. Simultaneously, the hardware performance of the zero blue light layered lighting hardware building module is tested, and the accuracy of sensor data and control function precision in the intelligent control integration module are tested. The parameters are fine-tuned based on feedback from elderly users to form a lighting solution adapted to elderly care scenarios.

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