Indoor zero-blue-light healthy lighting system and method

Abstract

The invention discloses an indoor zero-blue-light healthy lighting system and method, and relates to the technical field of healthy lighting, and the method comprises the steps: firstly, determining lighting parameters and demands in combination with the vision of old people and a pension scene; zero blue light layered lighting hardware is constructed; integrating a plurality of sensors and a plurality of control functions to form an intelligent control module; then, self-adaptive illumination adjustment is achieved through multiple algorithms; and finally, applying the adjusted system to pension scene verification, and forming an adaptive scheme according to feedback fine tuning parameters. Through zero blue light layered lighting hardware and a multi-source perception fusion algorithm, the system adapts to the visual and behavior requirements of the elderly, adopts a pure LED light source to eliminate blue light hazards, achieves the cooperation of layered lighting and intelligent control, achieves the dynamic adjustment to meet precise lighting and reduce energy consumption, and also responds to the environment and behaviors in real time through various algorithms, maintains color temperature transition and zero blue light output, and achieves the intelligent control of the elderly. And the health value and experience are improved.

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 present 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: 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, color temperature ranges, and color rendering index requirements of different spaces 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, as well as the lighting adjustment requirements corresponding to the high-frequency behaviors of the elderly such as reading, washing, and walking, 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; 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, and the spectral output is strictly controlled through multi-primary color chip light mixing technology to eliminate blue light components from the source, avoiding the adverse effects of blue light on the eyes of the elderly; the main light, auxiliary light, and key lighting lamps are configured to form a layered lighting structure, the main light meets the overall basic lighting needs of the space, the auxiliary light supplements the local lighting blind area of the space, and the key lighting lamps intensify the lighting effect for specific functional areas, realizing the comprehensiveness and pertinence of lighting coverage; the connection interface of the intelligent control integrated module is reserved to build a hardware channel for subsequent access of intelligent control components and realize dynamic adjustment of lighting parameters, ensuring the collaborative operation of all parts of the system; The intelligent control integrated module: integrates millimeter wave radar, infrared sensors, digital light sensors, and low-power cameras, and each sensing component is connected to the lighting system through an interface to capture key information such as indoor human presence, environmental light intensity changes, and human behavior in real time, providing real-time and accurate data support for lighting adjustment; at the same time, it integrates multi-scene color temperature and illumination switching functions, allowing the lighting system to quickly adjust output parameters according to scene changes; it incorporates voice control functions to facilitate the elderly with visual impairment or mobility difficulties to control lighting through voice commands; it is equipped with a timing switch and a gradual brightening and dimming function to match the work and rest habits of the elderly, avoid sudden lighting or extinguishing that may irritate the eyes, and improve the convenience and comfort of lighting use; Adaptive lighting adjustment module: Collect data such as human activity, ambient light intensity, and behavior through sensors, and use a multi-source perception fusion weight dynamic allocation algorithm to 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, the corresponding lamp intensity is accurately adjusted according to the special requirements of different behaviors on light, 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 body biological clock and scene atmosphere; And real-time association with 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; 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, and use professional instruments such as illuminometers, color temperature meters, and spectrometers to detect illumination, color temperature, spectrum, and hardware performance to 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 control instruction execution delay to 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 finally form a lighting solution adapted to the elderly care scene and make the system more suitable for the habits and needs of the elderly; Verify the parameters set by the lighting parameter and demand definition module: Use an illuminometer, a color temperature meter, and a color rendering index tester 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; Verify the hardware performance of the zero-blue layered lighting hardware construction module: Use a spectrometer to detect the spectral output of the light source 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 fixation; 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; 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.

[0006] 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.

[0007] 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.

[0008] 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.

[0009] 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 .

[0010] Further, in the adaptive lighting adjustment module, the 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 less than the main light off threshold 0.2, the main light is turned off; for auxiliary light illumination adjustment, the ambient light intensity data collected by the digital light sensor is used to calculate the illumination value to which the auxiliary light should be adjusted, and the calculation formula of the auxiliary light target illumination adjustment algorithm is: wherein: is the auxiliary light basic illumination, is the adjustment coefficient, and then the auxiliary light is adjusted in illumination, represents the target illumination of the auxiliary light, is the moment fusion decision weight.

[0011] 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 the silicon-based red light LED, is the standard spectrum of the silicon-based yellow light LED, represents the weight coefficient of the silicon-based yellow light LED at t moment, represents the weight coefficient of the silicon-based red light LED at t moment.

[0012] 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 old person and the lighting area, is the attenuation coefficient, represents the inverse function, is Integrate decision-making weights at all times.

[0013] Furthermore, 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.

[0014] On the other hand, a method for indoor zero-blue-light healthy lighting includes the following specific steps: S100, Parameter and Requirements Determination: Combining the characteristics of visual degeneration in the elderly and the functions of elderly care spaces, and 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, differentiated illuminance standards, color temperature ranges, and color rendering index requirements for each space are determined to ensure that the lighting parameters can match the visual perception ability of the elderly and reduce visual fatigue. At the same time, based on the daily routines of the elderly such as waking up in the morning, taking a nap, and getting up at night, color temperature parameters for various basic scenarios such as daily activity mode, bedtime mode, and nighttime mode are set. For high-frequency behaviors of the elderly such as reading, washing, and walking, the corresponding lighting adjustment needs are clarified, providing a precise basis for subsequent hardware selection, algorithm design, and functional integration, so that the lighting system fits the actual usage scenarios of the elderly from the design source. The S200 features zero-blue-light hardware: it employs silicon-based yellow LEDs and silicon-based red LEDs to form a pure LED lighting source. Through multi-color chip mixing technology, it precisely controls the spectral composition, eliminating blue light output at the light source level and preventing damage to the retina of the elderly. Based on the lighting needs of different areas in the elderly care setting, it is configured with main lights, auxiliary lights, and accent lights to form a layered lighting structure. The main lights provide basic overall lighting for the space, ensuring basic brightness requirements within the area; auxiliary lights fill in the blind spots of the main lights; and accent lights enhance the lighting effect in specific functional areas such as bedside reading areas and areas in front of bathroom mirrors, achieving comprehensive and targeted lighting coverage. It also reserves a connection interface with a smart control module, providing a hardware channel for future integration of sensing components and dynamic adjustment of lighting parameters, ensuring the hardware system's scalability and synergy. 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, among which millimeter wave radar captures human presence state and moving track in real time, infrared sensor senses human activity trigger signal, digital light sensor monitors indoor and outdoor illumination changes, low-power camera identifies human behavior, 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 changes 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 commands; carry timing switch and gradual brightening and dimming function, which is in line with the old people's work and rest habits, avoids sudden lighting or extinguishing of lights to stimulate the eyes, and improves the convenience and comfort of lighting use; S400, adaptive lighting adjustment: use sensors to collect indoor human presence, environmental light intensity, behavior and other data, combine multi-source perception fusion weight dynamic distribution algorithm, comprehensively analyze human activity state, whether the environment light meets the demand, and the matching degree of behavior and lighting, to judge whether to turn off the main light and adjust the auxiliary light illumination, which not only avoids energy waste, but also ensures that the space lighting is always at an appropriate level; according to the behavior associated illumination adaptive adjustment algorithm, for the special requirements of reading, washing and other behaviors on light, the corresponding lamp illumination is accurately adjusted, such as increasing the illumination to ensure clear vision when reading, and adjusting the illumination to ensure the path is visible when walking; according to the color temperature-scene-time linkage adjustment algorithm, combined with scene type, time change and other parameters, the color temperature is smoothly and dynamically adjusted, so that the lighting color temperature is consistent with the human biological clock and the scene atmosphere; and real-time association with zero blue spectrum real-time regulation algorithm, continuously monitor the light source spectrum output, and timely correct the spectrum deviation, to ensure that the lighting system always maintains zero blue light output state, and protects the eye health of the old people; S500, scene verification and adaptation: apply the output parameters to key areas such as reading area at bedside in bedroom, mirror area in bathroom, night light coverage area in pension scene, detect lighting parameters through illuminometer, color temperature instrument, spectrometer and other professional instruments, judge whether it meets the standard set by lighting parameter and demand definition module, ensure that the lighting output meets the visual needs of the old people; simultaneously detect the hardware performance of the zero blue light layered lighting hardware construction module, including the waterproofness of the main light, the anti-glare effect of the auxiliary light, 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 intelligent control integration module, to avoid the influence of data deviation or function delay on lighting adjustment effect; combine the feedback of the old people, understand the actual feelings of the old people on lighting brightness, color temperature, control convenience and other aspects, fine-tune the parameters such as lamp illumination reference value, sensor detection sensitivity, algorithm weight coefficient, and finally form a lighting scheme adapted to the pension scene, so that the system is more in line with the usage habits and needs of the old people.

[0015] Compared with the prior art, the indoor zero-blue-light health lighting system and method have the following beneficial effects: I. The present application realizes the deep adaptation of the lighting system to the visual health and behavior needs of the elderly by combining the zero-blue-light layered lighting hardware construction module with 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, and 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, thereby meeting the precise lighting needs of the elderly in high-frequency behaviors such as reading, washing, and walking, improving the comfort and health of the lighting environment, and reducing energy consumption through the self-adaptive adjustment mechanism, thereby providing a safer and more humanized lighting solution for the elderly care scene.

[0016] II. 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 sensors, digital light sensors, and low-power cameras, which can accurately perceive the presence of the human body, the activity state, and the ambient light intensity, dynamically distribute the perception weights through the algorithm, and intelligently decide the main light switch and the auxiliary light illuminance adjustment; in addition, the color temperature-scene-time linkage adjustment algorithm and the zero-blue-light spectrum real-time regulation algorithm cooperate to enable the system to maintain smooth color temperature transition and zero-blue-light output at different time periods, thereby further improving the health value of the lighting environment and the user experience.

[0017] Other advantages, objects, and features of the present application will be set forth in part in the following specification, and in part will become apparent to those skilled in the art from a consideration of the following description, or from practice of the present application, and the present application will be realized and attained by means apparent to one of ordinary skill in the art. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without any creative effort.

[0019] Figure 1 Figure 1 is a module logic architecture diagram of the indoor zero-blue-light health lighting system; Figure 2 Figure 2 is a step flow chart of the indoor zero-blue-light health lighting method. DETAILED DESCRIPTION

[0020] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object of the present application, the specific embodiments, structures, features and effects thereof according to the present application are described in detail below in combination with the drawings and preferred embodiments.

[0021] Embodiment one: Anti-sensitivity application of the system in the scene of the elderly getting up at night.

[0022] Lighting parameter and demand definition module: In combination with the characteristics that the visual function of the elderly deteriorates with age, the tolerance of the pupil to light stimulation at night is greatly reduced, and walking safety needs to be ensured in dim light when getting up at night, and the functional attributes of the bedroom as a resting and getting-up space, the core lighting parameters and adjustment demands in this scene are determined, wherein the bedroom night light illumination area illuminance is strictly set to ≤50 lux, which 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 as 1900±100K, the warm light in this color temperature interval is more in line with the night visual adaptation habit of the elderly, which can reduce the interference of light on the secretion of melatonin and reduce the difficulty of falling asleep again after getting up at night; in view of the high-frequency behavior of the elderly getting up at night, the lighting adjustment demand is set as “fast response + gradual light-up” at the same time, to ensure that the lighting starts in time when the elderly get up, and at the same time, through the way of gradually brightening 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 process of getting up at night, as shown in Figure 1 .

[0023] Zero-blue-light layered lighting hardware construction module: A pure LED lighting source is composed of a silicon-based yellow light LED and a silicon-based red light LED, wherein the silicon-based yellow light LED has a peak wavelength accurately controlled at 585-590 nm, the silicon-based red light LED has a peak wavelength stably at 625-630 nm, and the two are packaged in a ratio of 3:1. Through multi-primary color chip light mixing technology, the blue light component in the light source is completely eliminated, realizing zero blue light output, avoiding potential damage of blue light to the macular area of the retina of the elderly from the source, especially suitable for the more fragile physiological state of the eyes at night. In the bedroom space, a layered lighting structure is formed by configuring main lights, auxiliary lights and key lighting lamps. The main light is a ceiling light with a thickness of less than 5 cm, and the waterproof panel has a protection level of ≥IP65, which can effectively resist the humid water vapor that may occur in the bedroom environment (such as condensation water generated by window ventilation in winter), prolong the service life of the lamp and ensure the safety of electricity. The auxiliary light is a wall lamp with diffuse reflection light material, and the anti-glare value UGR is ≤16, which can evenly disperse the light into the space, avoid the strong light spots formed by the direct light of the lamp, and prevent the elderly from feeling dazzling when their eyesight contacts the lamp. The key lighting lamps (such as reading lamps) are not used in the night scene, and the connection interface with the intelligent control integrated module is reserved, providing hardware support for data transmission and function cooperation between modules, ensuring the stability and continuity of the whole lighting system.

[0024] Intelligent control integrated module: Integrating four core sensing components—millimeter-wave radar, infrared sensor, digital light sensor, and low-power camera—each component's function is deeply adapted to the bedroom nighttime getting-up scenario: The millimeter-wave radar has a detection range of 0.5m-8m, a detection angle of up to 120°, and a resolution accurate to 0.1m. It can collect real-time data on the elderly person's presence in the bedroom (e.g., whether they are in bed or have gotten up), their distance from the radar (to determine their relative position to the bedside or doorway), and their movement speed (to identify the pace of their nighttime getting-up movements), providing precise human dynamic data support for lighting adjustment; the infrared sensor has a detection range of 1m-5m, a detection angle of 90°, and a response time ≤0.5 seconds. It can quickly capture the intensity of human infrared radiation signals (distinguishing between humans and inanimate objects such as furniture and clothing) and activity trigger signals (sensing the initial moment of the elderly person getting up), ensuring that the lighting starts immediately upon the nighttime getting-up behavior, preventing the elderly person from groping in the dark; the digital light sensor's measurement range covers… With a range of 0-20000 lux, accuracy controlled within ±5%, and a response time ≤100ms, it can acquire real-time indoor and outdoor illuminance values ​​and differences (to determine whether outdoor moonlight or streetlights interfere with indoor lighting at night), providing accurate ambient light data for adjusting auxiliary lighting. The low-power camera has a resolution of 1080P and a frame rate of 15fps, which can clearly capture human contour images (confirming that the active object is an elderly person and not a pet), behavioral action sequence frames (completely recording the entire process from getting up, getting out of bed to walking to the door), and location coordinates (precisely locating the elderly person's specific position in the bedroom), further improving the accuracy and reliability of the sensing data. Each sensing component is connected to the lighting system through a dedicated interface, and integrates multi-scene color temperature and illuminance switching, voice control, timed on / off, and gradual brightening / darkening functions. In the scenario of getting up at night, the transition time and brightness change range of the gradual brightening / darkening function are optimized to match the elderly person's nighttime visual adaptation rhythm and avoid discomfort caused by abrupt changes in light.

[0025] Adaptive lighting adjustment module: Each sensor collects real-time data on human movement, ambient light intensity, and behavioral images and transmits it to the module core. First, combining the multi-source sensing fusion weight dynamic allocation algorithm, it comprehensively considers human recognition reliability (confirming the current active object is an elderly person and is awake), ambient light intensity influencing factors (determining whether there are other interfering lights indoors at night), and behavioral recognition matching degree (confirming the current action is getting up at night rather than turning over or adjusting sleeping posture), to calculate the fusion decision weight at time t. 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 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 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.

[0026] 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.

[0027] 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, a base illuminance defined in the lighting parameter and demand defining module for the behavior b set, a fusion weight influence coefficient, a distance of the elderly person from the lighting area, a decay coefficient, denotes an inverse function, is The moment fusion decision weight, maintain 1900±100K soft color temperature, through slow and continuous color temperature adjustment mode, realize color temperature smooth dynamic change, prevent color temperature mutation cause eye fatigue.

[0028] 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, denotes a time variable, once the presence of trace blue light component in the spectrum is detected, immediately adjust the light emitting proportion of silicon-based yellow light LED and silicon-based red light LED, ensure that always maintain zero blue light output in the whole night process, fundamentally reduce the stimulation of light to the sensitive eyes of the elderly at night.

[0029] Verification and adaptation module: 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 illuminance of the night light 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. The color temperature value under the night 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 from 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. At the same time, 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 stuttering in the process from dark to light). 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 does not start"). According to the feedback from 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. 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 have a safe, comfortable and non-stimulating lighting experience during the night getting up process.

[0030] In summary, the embodiment focuses on the anti-sensitive scene of the elderly in the bedroom at night, and shows the complete operation process of the indoor zero-blue light healthy lighting system. Each module works 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. 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 night getting up, and fully reflects the adaptability of the system in the elderly care scene.

[0031] Embodiment two: Application of the method in the elderly bathroom washing scene.

[0032] S100, parameter and demand determination: In combination with the fact that the elderly have lens opacity, decreased sensitivity of retinal photoreceptor cells, and the need to clearly distinguish facial details (such as facial hair and makeup residue) while being unable to withstand strong light stimulation, and the fact that the bathroom is used as a space for washing and grooming, the core parameters and adjustment directions of each dimension are determined, and the illuminance of the bathroom mirror area is set to be ≥ 350 lux. This value can ensure that the light is evenly distributed over each area of the face, avoiding insufficient illumination that causes the elderly to be unable to see the fine dirt on their face or the location of their washing supplies. Washing behavior is a type of life activity, and the corresponding color temperature is determined to be 4000K. At this color temperature, the color reproduction of objects is closer to the natural state, which can help the elderly accurately identify the true colors of washing supplies such as toothpaste and facial cleanser, reducing the likelihood of mistakenly grabbing the wrong item due to color deviation. The color rendering index is required to be Ra≥92, which can clearly present the changes in facial skin color, making it easier for the elderly to observe their skin condition (such as whether there is redness, swelling, or wounds). In addition, in response to the actions that the elderly may take during the washing process, such as leaning towards the mirror, bending down to get water, and lifting their hands to wash their face, the lighting adjustment requirements are set to be "dynamic illumination adaptation + stable color temperature", ensuring that the lighting always meets the visual needs during different actions, avoiding issues such as reduced washing efficiency or eye discomfort caused by light problems, as shown in FIG. 8. Figure 2

[0033] S200, zero-blue hardware construction: A pure LED lighting source is adopted, which is composed of a silicon-based yellow light LED and a silicon-based red light LED. The peak wavelength of the silicon-based yellow light LED is precisely controlled at 585-590 nm, and the peak wavelength of the silicon-based red light LED is stably at 625-630 nm. The two are packaged in a ratio of 3:1, and the blue light component in the light source is completely filtered through multi-primary color chip light mixing technology, achieving zero-blue output. This avoids chronic damage to the elderly's macular area of the retina caused by blue light from the source, especially in the humid environment of the bathroom, where the eyes are more susceptible to irritation. In the bathroom space, a layered lighting structure of "main light + auxiliary light + key lighting" is constructed. The main light is a ceiling light with a thickness of ≤5 cm, and its waterproof panel has a protection level of ≥IP65, which can effectively resist water vapor erosion during washing, prevent short circuits caused by moisture in the lamp interior, prolong the service life, and ensure electrical safety. The auxiliary light is installed on both sides of the mirror and uses a diffuse reflection light material with a glare value of UGR≤16, which can softly project light onto the face, avoiding the formation of reflected light spots on the mirror caused by direct light from the lamp, and preventing the elderly from experiencing eye strain when looking at the mirror. The key lighting lamp is a model with a 360° rotating lamp head and a 180° flipping function, with a maximum opening degree of the clamp of ≥5 cm, which can be flexibly clamped on the edge of the washbasin or the mirror cabinet. It provides supplementary lighting for local operations such as toothpaste squeezing and razor use, meeting the needs of detailed washing. At the same time, the adaptation ports for the intelligent control module are reserved at the interfaces of each lamp, laying a hardware channel for subsequent sensing data transmission and intelligent lighting adjustment, ensuring that each lamp responds cooperatively.

[0034] ​S300, intelligent control integration: Integrate four types of sensing components: millimeter wave radar, infrared sensor, digital light sensor, and low-power camera. Each component is deeply matched with the bathroom washing scene: millimeter wave radar detects a distance of 0.5m-8m, an angle of 120°, and a resolution of 0.1m, which can collect the position coordinates of the elderly in the bathroom (such as whether they are close to the mirror or the distance from the washbasin), movement speed (to determine whether they are washing slowly or quickly taking water), and provide dynamic human position data for lighting adjustment; infrared sensor detects a distance of 1m-5m, an angle of 90°, and a response time of ≤0.5 seconds, which can quickly capture the intensity of human infrared radiation signals (distinguish between humans and towels, shelves, and other items in the bathroom) and activity trigger signals (sense the elderly entering the bathroom and starting to wash), ensuring that the lighting is turned on in time when the elderly enter the scene, avoiding groping in the dark; digital light sensor measures a range of 0-20000 lux with an accuracy of ±5% and a response time of ≤100ms, which can obtain real-time illumination values in the bathroom (such as the brightness of natural light through the window during the day), outdoor real-time illumination values, and the difference between the two, providing environmental light as a basis for determining whether additional lighting is needed; low-power camera with a resolution of 1080P and a frame rate of 15fps can clearly capture human behavior sequences (such as the complete action of washing face with hands or bending down to get water) and human contour images (confirming that the moving object is an elderly person), further improving the accuracy of behavior recognition. Connect each sensing component to the lighting system through a dedicated data interface, while integrating multi-scene color temperature and illumination switching, voice control, timing switch, and gradual brightening and dimming functions. 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, improving 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.

[0035] S400, adaptive lighting adjustment: Each sensor collects human position, behavior, and environmental light data in real time and transmits them to the adjustment core. First, combine the multi-source sensing fusion weight dynamic allocation algorithm, integrate human recognition reliability (confirm that the current moving object is an elderly person and is in a washing state, not just passing by), environmental light intensity influence factor (such as insufficient illumination in the bathroom on a cloudy day, which requires increased lighting compensation), and behavior recognition matching degree (determine whether the current action belongs to the washing process or not), calculate the fusion decision weight at time t, and the calculation formula of the multi-source sensing fusion weight dynamic allocation algorithm is: Use this as the core basis for lighting adjustment. When the elderly approach the mirror to start washing, this algorithm determines that the main light does not need to be turned off, and the auxiliary light target illumination adjustment algorithm is used. The calculation formula of the auxiliary light target illumination adjustment algorithm is: , combined with the real-time ambient light intensity data collected by the digital light sensor, the target illuminance value that the auxiliary lamp should reach is accurately calculated, ensuring that the illuminance in the mirror area is stable at ≥350 lux, and the light is evenly covered on the face.

[0036] Then, according to the behavior-related illuminance adaptive adjustment algorithm, according to the change of the old people's washing action (such as bending down to get water, the head is close to the washstand, the lower lighting needs to be appropriately reduced to avoid being too bright; when washing face, the face is far away from the mirror, 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 adjust the illuminance output of the corresponding lamps, and ensure that the lighting in each action stage meets the visual needs.

[0037] 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 morning washing needs clear light, the evening washing needs slightly soft light) and the distance between the old people and the lighting area, the calculation formula of the color temperature-scene-time linkage adjustment algorithm is: , maintain a stable color temperature of 4000K, and avoid visual fatigue caused by color temperature fluctuations through subtle color temperature smoothing adjustment.

[0038] 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 monitor the spectral distribution of the light source, and once a trace of blue light component is detected in the spectrum, immediately adjust the light-emitting ratio of the silicon-based yellow light LED and the silicon-based red light LED, to ensure that the zero-blue light output is maintained throughout the washing process, and reduce the stimulation of light to the eyes.

[0039] S500, scene verification and adaptation: 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 does not deviate significantly, the second is to test the performance of the zero-blue hardware construction. The anti-glare effect of the auxiliary lamp is evaluated by subjective feedback from 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 clamp fixing 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 command is observed (such as whether the "brighten the mirror light" command can be accurately executed), 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, finally forming a personalized lighting solution that adapts 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.

[0040] In summary, this embodiment relies on the bathroom washing scene of the elderly, presents the specific application of indoor zero-blue healthy lighting method, from the parameters and demand determination to meet 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, then through the adaptive lighting adjustment algorithm to accurately adapt the lighting, finally through the scene verification and adaptation optimization scheme, the method is closely linked at each step, 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.

[0041] 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-health hazard lighting system, characterized in that, The system comprises: An illumination parameter and demand definition module: in combination with the visual degradation characteristics of the elderly and the spatial functions of the pension scene, the differentiated illumination standards, color temperature ranges, and color rendering index requirements of each space are determined, and the color temperature parameters of each basic scene and the lighting adjustment needs corresponding to the high-frequency behaviors of the elderly are set; A zero-blue layered lighting hardware construction module: pure LED lighting sources are composed of silicon-based yellow light LEDs and silicon-based red light LEDs, zero-blue output is achieved through multi-primary color chip light mixing technology, main lights, auxiliary lights, and key lighting lamps are configured to form a layered lighting structure, and a connection interface for an intelligent control integrated module is reserved; An intelligent control integrated module: integrating millimeter wave radar, infrared sensors, digital light sensors, and low-power cameras, each sensing component is connected to the lighting system through an interface, and multi-scene color temperature and illumination switching, voice control, timing switch, and gradual brightening and dimming functions are integrated; An adaptive lighting adjustment module: through sensor data collection, a multi-source sensing fusion weight dynamic distribution algorithm is used to determine whether to turn off the main light and adjust the auxiliary light illumination, a behavior-associated illumination adaptive adjustment algorithm is used to adjust the corresponding lamp illumination, a color temperature-scene-time linkage adjustment algorithm is used to achieve smooth dynamic adjustment of the color temperature in combination with related parameters, and a zero-blue spectrum real-time regulation algorithm is used to maintain zero-blue output; A verification and adaptation module: the parameters output by the adaptive lighting adjustment module are applied to specific scenes, the illumination, color temperature, spectrum, and hardware performance are detected by instruments, the accuracy of sensor data and the precision of control functions are tested, the parameters are fine-tuned in combination with the feedback of the elderly, and an adaptation scheme is formed.

2. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, In the illumination parameter and demand definition module, the differentiated illumination standards include: bedhead reading area illumination ≥200lux, mirror area illumination in the bathroom ≥350lux, night light illumination area illumination ≤50lux; the basic scenes include: life activity mode, pre-sleep mode, night mode; the corresponding color temperatures are 4000K, 3000K, and 1900±100K; the high-frequency behaviors include reading, washing, and walking, wherein the reading behavior corresponds to a reading light illumination reference value of 220lux, a color temperature reference value of 3800K, and a color rendering index reference value Ra≥92.

3. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, In the zero-blue layered lighting hardware construction module, the peak wavelength of the silicon-based yellow light LED is 585nm-590nm, the peak wavelength of the silicon-based red light LED is 625nm-630nm, and they are packaged in a ratio of 3:1; the thickness of the ceiling light in the main light is ≤5cm, and the waterproof panel has a protection level ≥IP65; the wall light in the auxiliary light uses a diffuse reflection light output material, and the anti-glare value UGR≤16; the reading light in the key lighting lamp has a 360° rotating lamp holder and a 180° flipping function, and the maximum opening degree of the clamp is ≥5cm.

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

5. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, The calculation formula of the multi-source perception fusion weight dynamic distribution algorithm in the adaptive lighting adjustment module is: Wherein: is the moment fusion decision weight, is the human body recognition reliability, is the environmental light intensity influence factor, is the behavior recognition matching degree, indicates the weight coefficient of the human body recognition reliability, indicates the weight coefficient of the environmental light intensity influence factor, indicates the weight coefficient of the behavior recognition matching degree, and .

6. An indoor non-blue light hazard lighting system according to claim 5, characterized in that, In the adaptive lighting adjustment module, whether to close the main light and adjust the auxiliary light illumination is determined by combining a multi-source perception fusion weight dynamic allocation algorithm When the main light closing threshold value 0.2 is less than the main light closing threshold value 0.2, the main light is closed; for the auxiliary light illumination adjustment, the auxiliary light target illumination adjustment algorithm is used to combine the environmental light intensity data collected by the digital light sensor to calculate the illumination value to which the auxiliary light should be adjusted, and the calculation formula of the auxiliary light target illumination adjustment algorithm is as follows: Wherein: is the auxiliary light basic illumination, is the adjustment coefficient, and then the illumination of the auxiliary light is adjusted, represents the target illumination of the auxiliary light, is the moment fusion decision weight.

7. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, The adaptive lighting adjustment module, the calculation formula of the behavior associated with the adaptive adjustment algorithm is: Wherein: The light source spectral distribution at time t, Indicates the wavelength of light, Indicates the time variable, The standard spectrum of silicon-based red light LED, The standard spectrum of silicon-based yellow light LED, Indicates the weight coefficient of silicon-based yellow light LED at time t, Indicates the weight coefficient of silicon-based red light LED at time t.​ 8. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, The calculation formula of the color temperature-scene-time linkage adjustment algorithm in the adaptive lighting adjustment module is: Wherein: is the behavior corresponding target illuminance, is the basic illuminance set for the behavior b in the lighting parameter and demand definition module, is the fusion weight influence coefficient, is the distance between the old people and the lighting area, is the attenuation coefficient, represents the inverse function, is the moment fusion decision weight.

9. An indoor non-blue light hazard lighting system according to claim 1, characterized in that, The calculation formula of the zero-blue spectrum real-time regulation algorithm in the adaptive lighting adjustment module is: Wherein: is actual color temperature at the moment, scene base color temperature, scene allowed fluctuation range, scene start time, scene end time, is fusion decision weight at the moment, denotes a time variable.

10. A method of indoor zero-blue-light-health lighting, the method being applicable to an indoor zero-blue-light-health lighting system according to any one of claims 1-9, characterized in that, The specific steps of the method are: S100, parameter and demand determination: combining the visual degradation characteristics of the elderly and the space function of the pension scene, determining the differentiated illuminance standard, color temperature range, and color rendering index requirements of each space, setting the color temperature parameters of each basic scene and the lighting adjustment requirements corresponding to the high-frequency behaviors of the elderly; S200, zero-blue hardware construction: using silicon-based yellow light LEDs and silicon-based red light LEDs to form a pure LED lighting source, achieving zero-blue output through multi-primary color chip light mixing technology, configuring main lights, auxiliary lights, and key lighting lamps to form a layered lighting structure, and reserving a connection interface with the intelligent control module; S300, intelligent control integration: integrating millimeter wave radar, infrared sensors, digital light sensors, and low-power cameras, connecting each sensing component to the lighting system through the interface, and integrating multi-scene color temperature and illuminance switching, voice control, timing switch, and gradual brightening and dimming functions; S400, adaptive lighting adjustment: using sensor data collection, combining a multi-source perception fusion weight dynamic allocation algorithm to determine whether to turn off the main light and adjust the auxiliary light illuminance, adjusting the corresponding lamp illuminance according to the behavior-related illuminance adaptive adjustment algorithm, implementing color temperature smooth dynamic adjustment according to the color temperature-scene-time linkage adjustment algorithm combined with related parameters, and maintaining zero-blue spectrum real-time regulation algorithm in real time; S500, scene verification and adaptation: applying the output parameters to the pension scene, detecting whether the lighting parameters meet the standards set by the lighting parameter and demand definition module through instrument detection, synchronously detecting the hardware performance of the zero-blue layered lighting hardware construction module, testing the sensor data accuracy and control function precision in the intelligent control integrated module, and fine-tuning the parameters based on the feedback of the elderly to form a lighting solution adapted to the pension scene.

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