Intelligent human factor lighting system for monitoring ambient light of lighting field environment

Abstract

The invention discloses a system for automatically adjusting space illumination parameters. A control panel is used for setting illumination target parameters in a space and driving an ambient light sensing module to control an intelligent lamp group in the space to illuminate according to the illumination parameters of a preset light formula; the control panel compares the numerical value of the illumination parameter in the actual environment detected by the ambient light sensing module with a set target parameter; when the control panel judges that the numerical value detected by the ambient light is different from a target parameter value, the control panel drives the ambient light sensing module to carry out a dimming program on the intelligent lamp group, and the dimming program comprises the step of adjusting the illumination uniformity of the space according to the actual illumination detected by the ambient light sensing module. And after calculation by an illuminance uniformity formula, adjusting the illuminance uniformity to target illuminance uniformity.

Description

Intelligent human-factor lighting system for ambient light monitoring of lighting site environments Technical Field

[0001] The present invention provides a system and method for establishing a multi-spectral lighting scenario database, and more particularly relates to an intelligent human-factor lighting system for performing ambient light monitoring on a lighting scene. Background Art

[0002] Humans are highly emotional beings, experiencing varying emotions depending on their state of mind. These emotions range from excitement, amusement, anger, disgust, fear, happiness, sadness, calmness, and neutrality. When negative emotions (such as anger, disgust, and fear) are not properly managed, they can cause psychological harm or trauma, ultimately leading to mental illness. Therefore, in today's highly competitive and stressful society, providing a timely emotional resolution, relief, or treatment system that meets user needs presents significant business opportunities.

[0003] Modern medical equipment now uses functional magnetic resonance imaging (fMRI) systems to measure changes in blood dynamics caused by neuronal activity. Due to its non-invasive nature and low radiation exposure, fMRI is currently primarily used for brain and spinal cord research in humans and animals. Electroencephalography (EEG) can also be used to examine subjects using the same emotional stimulation to reveal responses to different emotions. For example, distinct EEG patterns are observed for fear and happiness. When observing the responses to specific emotions under fMRI and EEG, for example, when stimulating happiness (e.g., through image induction and facial emotion recognition), fMRI blood oxygenation level-dependent contrast (BOLD) responses have revealed significant responses in the medial prefrontal cortex (MPFC) compared to corresponding emotions (anger and fear). In contrast, for example, when examining the blood oxygen concentration-dependent contrast (BOLD) response during fear and anger, fMRI reveals a significant response in the amygdala, indicating that the two emotions are responsive to distinct brain regions. Therefore, the BOLD response in these different brain regions can be used to clearly identify the subject's current emotion. Furthermore, when using an electroencephalogram (EEG) to examine and measure subjects, using the same emotional stimulation method, distinct brainwave patterns can be observed for fear and happiness. Therefore, these different EEG patterns can also be used to identify the subject's current emotion. As mentioned above, fMRI distinguishes emotions through different BOLD responses, while EEG distinguishes emotions through different EEG patterns. Obviously, the methods used by the two to judge the test subject's emotions and the content of the records are completely different. Therefore, based on current technology, it is impossible to use the brainwave patterns of an electroencephalogram (EEG) to replace the blood oxygen concentration-dependent contrast (BOLD) response of a functional magnetic resonance imaging (fMRI) system for the test results of the same emotion on the same test subject.

[0004] The above discussion of the use of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) for emotion judgment is based on the fact that fMRI systems are very expensive and large, making them unsuitable for commercial systems and methods for human-induced lighting. Similarly, if only EEG brainwave patterns are used to judge a subject's emotions, different subjects may have different brainwave patterns for different emotions. Therefore, it is currently impossible to use the blood oxygen concentration-dependent contrast (BOLD) response of a functional magnetic resonance imaging (fMRI) system alone, or the brainwave patterns of an EEG system alone, to create a commercially viable human-induced lighting method and system through light recipe editing.

[0005] The aforementioned process has proven that human emotions can be altered by illuminating them. Therefore, when commercializing these human-centric lighting methods and systems, the light recipe must precisely control the environment in which the human-centric lighting is provided, as well as the actual light field of the lighting module in different lighting fields. This ensures that the lighting recipe (e.g., color temperature or illuminance) provided by the human-centric lighting achieves the desired effect for the user.

[0006] Summary of the Invention

[0007] According to the above description, commercial human-caused lighting systems need to further detect various background light sources in the control light field, especially the light that overflows into the space through the windows of the building, and compensate for the impact of the target spectrum set in the control light field so that the lighting field can maintain the lighting program in the environment of the set target spectrum.

[0008] Therefore, the present invention first provides a system for automatically adjusting spatial lighting parameters. The system comprises multiple smart lighting groups, multiple ambient light sensing modules, a control panel, and an interface device, all of which are connected via wireless communication. The smart lighting groups and the interface device are paired with the ambient light sensing modules and the control module, respectively, via a wireless communication protocol. The system is characterized by:

[0009] The control panel sets the lighting target parameters in the space and drives the ambient light sensing module to control the lighting of the smart lamp group in the space with the lighting parameters of the preset light recipe;

[0010] The control panel compares the value of the lighting parameter in the actual environment detected by the ambient light sensing module with the set target parameter; wherein,

[0011] When the control panel determines that the ambient light detection value is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe;

[0012] When the control panel determines that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes:

[0013] The ambient light sensing module adjusts the light according to the target parameter so that the value of the lighting parameter in the actual environment is the same as the set target parameter value; and

[0014] Adjusting the illumination uniformity of the space is based on the actual illumination detected by the ambient light sensing module. After calculating the illumination uniformity formula, the illumination uniformity is adjusted to the target illumination uniformity.

[0015] The present invention further provides a method for automatically adjusting lighting parameters in a space. The method comprises: configuring a plurality of smart lighting groups, a plurality of ambient light sensing modules, a control panel, and an interface device in the space, all of which are connected via a wireless communication protocol. The smart lighting groups and the interface device are paired with the ambient light sensing modules and the control module, respectively, via the wireless communication protocol. The method is characterized by:

[0016] Driving the smart lamp group in the space to illuminate is done by the ambient light sensing module using the lighting parameters of the preset light recipe to drive the smart lamp group in the space to illuminate;

[0017] Setting the lighting target parameters in the space. The user sets the lighting target parameters in the space through the control panel;

[0018] The control panel drives the ambient light sensing module to detect the ambient light in the space, and transmits the detected ambient light value to the control module;

[0019] To determine whether the ambient light detection value is the same as the target parameter, the control panel compares the value of the lighting parameter detected in the actual environment with the set target parameter;

[0020] When it is determined that the value of the ambient light detection is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe;

[0021] When it is determined that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes:

[0022] The ambient light sensing module adjusts the light according to the target parameter so that the value of the lighting parameter in the actual environment is the same as the set target parameter value; and

[0023] Adjusting the illumination uniformity of the space is based on the actual illumination detected by the ambient light sensing module. After calculating the illumination uniformity formula, the illumination uniformity is adjusted to the target illumination uniformity.

[0024] The present invention further provides a method for automatically adjusting lighting parameters in a space. Multiple smart lighting groups, multiple ambient light sensing modules, a control panel, and an interface device are configured in the space, all connected via a wireless communication protocol. The smart lighting groups and the interface device are paired with the ambient light sensing modules and the control module, respectively, via the wireless communication protocol. Furthermore, the control module and the interface device are connected to the cloud via an intelligent Internet of Things. The method is characterized by:

[0025] Driving the smart lamp group in the space to illuminate is done by the ambient light sensing module using the lighting parameters of the preset light recipe to drive the smart lamp group in the space to illuminate;

[0026] Set the lighting target parameters in the space. The control panel sets the equivalent black level (EML) and physiological stimulation value (CAF) values ​​of the human circadian rhythm according to the time of day, which serve as the target parameters set in the space.

[0027] Driving the ambient light sensing module to detect ambient light in the space, the control panel drives the ambient light sensing module to detect ambient light in the space, and transmits the detected ambient light value to the control module;

[0028] To determine whether the ambient light detection value is the same as the target parameter, the control panel compares the value of the lighting parameter detected in the actual environment with the set target parameter;

[0029] When it is determined that the value of the ambient light detection is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe;

[0030] When it is determined that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes:

[0031] The ambient light sensing module adjusts the light according to the target parameter so that the value of the lighting parameter in the actual environment is the same as the set target parameter value;

[0032] Adjusting the illumination uniformity of the space is based on the actual illumination detected by the ambient light sensing module. After calculating the illumination uniformity formula, the illumination uniformity is adjusted to the target illumination uniformity.

[0033] The system and method for automatically adjusting spatial lighting parameters provided by the present invention can precisely control various lighting parameters within a lighting field, including at least illuminance (lx), color temperature (CCT), color rendering index (Ra), equivalent blackout illuminance (EML), color irritation factor (CAF), flicker rate (Flicker), and / or illumination uniformity. In particular, accurate EML and CAF within the lighting field are crucial to determine the mood-adjusting effect of the user's "light recipe." BRIEF DESCRIPTION OF THE DRAWINGS

[0034] FIG1a is a raw data collection framework for human physiological and emotional responses to light according to the present invention;

[0035] FIG1b is a flowchart of collecting raw data on human physiological and emotional responses to light according to the present invention;

[0036] FIG1c is a flow chart of the present invention showing the determination process of a person's response to specific physiological emotions due to illumination;

[0037] FIG2a is a method of establishing a brainwave diagram of a person's physiological and emotional response to light exposure according to the present invention;

[0038] FIG2 b is a lighting database constructed by the present invention for users to perform effective ergonomic lighting;

[0039] FIG3 is a system architecture diagram of the intelligent human-induced lighting system of the present invention;

[0040] FIG4 is a method for constructing a human-induced lighting environment sharing platform according to the present invention;

[0041] FIG5 a is an automatically adjustable intelligent human-induced lighting method of the present invention;

[0042] FIG5 b is an editing process of the contextual dynamic spectrum editing platform of the present invention;

[0043] FIG5c is a situational dynamic spectrum program with conference function according to the present invention; and

[0044] FIG6 is an intelligent human-centered lighting system according to the present invention applied to commercial operations;

[0045] FIG7 is a lighting fixture group control architecture of the intelligent human-centered lighting system of the present invention at the lighting field end relative to FIG6 ;

[0046] FIG8a is a schematic diagram of a configuration for controlling lighting of a smart lamp group in a lighting field according to the present invention;

[0047] FIG8 b is a schematic diagram of another configuration of controlling the lighting of a smart lamp group in a lighting field according to the present invention;

[0048] FIG9 is a control device with display and communication functions according to the present invention;

[0049] 10a to 10d are schematic diagrams showing some embodiments of the present invention in which an external light source is incident on a space equipped with an intelligent human-centered lighting system;

[0050] FIG11a is an intelligent method for automatically adjusting spatial lighting parameters according to the present invention;

[0051] FIG. 11 b shows another intelligent method for automatically adjusting spatial lighting parameters according to the present invention. DETAILED DESCRIPTION

[0052] In the following description of this invention, the functional magnetic resonance imaging system is referred to as the "fMRI system," the electroencephalogram (EEG) is referred to as the "EEG," and the blood oxygen concentration-dependent contrast (BOLD) is referred to as the "BOLD." Furthermore, in the color temperature test embodiment of this invention, the test is performed in 100K increments. However, to avoid excessive length, the specific emotions referred to in the following description refer to excitement, happiness, or pleasure, and the corresponding specific emotional responses will be described using color temperatures of 3000K, 4000K, and 5700K as examples. Therefore, the invention is not limited to these three color temperature embodiments. Furthermore, to facilitate a thorough understanding of the technical content of this invention by those skilled in the art, related embodiments and examples are provided herein. When reading the embodiments of this invention, please refer to the drawings and the following description. The shapes and relative sizes of the components in the drawings are provided solely to facilitate understanding of the present embodiments and are not intended to limit the shapes and relative sizes of the components. For this purpose, please note that the following description of the embodiments of this invention is provided in conjunction with the accompanying drawings. The shapes and relative sizes of the components in the drawings are provided solely to facilitate understanding of the present embodiments and are not intended to limit the shapes and relative sizes of the components.

[0053] The present invention uses an fMRI system to measure physiological signals, understanding the correspondence between light spectrum and emotion in the brain and developing a preliminary mechanism for how light influences human physiological and psychological responses. Because the fMRI system's brain images can determine which part of the brain experiences hyperemia when stimulated by light, they can also record the BOLD response. This BOLD response to brain hyperemia is also known as a "blood oxygen concentration-dependent increase." Therefore, the present invention can accurately and objectively infer the subject's physiological emotional changes based on the fMRI system's recorded brain hyperemia data under various emotions and the "blood oxygen concentration-dependent increase" response. Based on the physiological emotions confirmed by the fMRI system, electroencephalography (EEG) is used to record brainwave changes and establish a correlation between the two. This approach aims to replace the fMRI system's emotional judgments with those recorded by the EEG.

[0054] Therefore, the main purpose of the present invention is to record the BOLD response of the subject to the specific emotion while the subject is being tested with an fMRI system. This allows the subject to identify specific "effective color temperatures" that have a synergistic effect on the specific emotion, and to use this color temperature as the "effective color temperature" corresponding to the specific emotion. The subject is then illuminated with light at the "effective color temperature," and the brainwave pattern under the "effective color temperature" is recorded using an electroencephalogram (EEG). Once a correlation is established between the specific EEG brainwave pattern and the specific BOLD response, the EEG brainwave pattern can be used to assist in determining the user's emotional changes. This results in a commercially viable human-centered lighting system and method. This eliminates the need for expensive fMRI systems to implement human-centered lighting systems, reduces operating costs, and further meets customized service needs.

[0055] First, please refer to Figure 1a, which is the original data collection framework of the present invention's human-induced lighting response to physiological emotions. As shown in Figure 1a, the intelligent human-induced lighting system 100 is activated in an environment that has been configured with various adjustable lighting modules (for example, a test space) and provides light signal lighting parameters such as adjustable spectrum, light intensity, flicker rate, and color temperature. The present invention uses a compatible image interaction platform 110 (fMRI compatible image interaction platform) formed by an fMRI system to target different target emotions. It uses voice and image emotional guidance, and at the same time uses a specific effective spectrum for 40 seconds of stimulation to observe changes in the blood oxygen content in the test subject's brain to verify whether the "effective color temperature" can significantly induce the test subject's emotional response. The details are as follows.

[0056] Next, please refer to Figure 1b and Figure 1c, wherein Figure 1b is a flowchart of the original data collection of the human-induced lighting response to physiological emotions of the present invention, and Figure 1c is a judgment process of the human-induced lighting response to specific physiological emotions. As shown in step 1100 in Figure 1b, each tester is already on the compatible image interaction platform 110. Then, each tester is guided to stimulate various emotions through known pictures. Afterwards, as shown in step 1200, the BOLD response of the tester's brain to various emotions after being stimulated by the pictures is recorded through the compatible image interaction platform 110. Then, as shown in step 1300, the tester is visually stimulated by providing a spectrum of different color temperature parameters through lighting. For example: using LED lamps with electronic dimmers to provide a spectrum of different color temperature parameters. In an embodiment of the present invention, nine sets of visual stimuli with different color temperatures are provided: 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K. After each 40-second effective light exposure and stimulation, the subject can be given a one-minute ineffective light source (full-spectrum, flicker-free white light) to achieve emotional relaxation. Furthermore, the subject can be given a 40-second counter-effect light stimulus to observe whether areas that were responsive to the original effective light stimulus exhibit a decreased response. In an embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of the test subject's brain to a specific emotion after being stimulated by the image, spectra with different color temperature parameters are provided to provide visual stimulation to the test subject. As shown in step 1310 in Figure 1c, a spectrum with a color temperature of 3000K is provided. Then, as shown in step 1320, a spectrum with a color temperature of 4000K is provided. Finally, as shown in step 1330, a spectrum with a color temperature of 5700K is provided to provide visual stimulation to the test subject.

[0057] Next, as shown in step 1400, the compatible image interaction platform 110 records the BOLD responses of the subject's brain to various emotions after being exposed to light stimulation. In this embodiment of the present invention, after the subject is exposed to light stimulation with different color temperature parameters, the compatible image interaction platform 110 sequentially records the BOLD responses of the corresponding emotionally responsive regions in the subject's limbic system. Different emotions trigger different areas of the limbic system, and the limbic system regions with emotional responses are shown in Table 1 below.

[0058] Table 1

[0059] The compatible image interaction platform 110 records the BOLD response results in specific brain regions. This response result is determined by calculating the area size of these emotional response sites based on the number of limbic systems with BOLD emotional responses in the brain region. For example, the larger the area with BOLD emotional responses, the stronger the response to a specific physiological emotion. In an embodiment of the present invention, as shown in step 1410 in Figure 1c, the BOLD response results are recorded after irradiation with a spectrum having a color temperature of 3000K. Next, as shown in step 1420, the BOLD response results are recorded after irradiation with a spectrum having a color temperature of 4000K. Finally, as shown in step 1430, the BOLD response results are recorded after irradiation with a spectrum having a color temperature of 5700K. After the subject underwent the illumination procedure to induce excitement, the compatible image interaction platform 110 recorded the BOLD response results in specific brain regions, as shown in Table 2. Clearly, irradiation at a color temperature of 3000K enhances excitement. Therefore, according to the results of the present embodiment, the optimal stimulating color temperature is between 3000K and 4000K. However, it should be noted that irradiation at a color temperature of 5700K has a negative inhibitory effect on excitement.

[0060] Table 2

[0061] After the subjects went through a lighting procedure to induce happiness, the compatible image interaction platform 110 recorded BOLD responses in specific brain regions, as shown in Table 3. Clearly, illumination at a color temperature of 4000K enhanced BOLD responses in the happiness context more than illumination at the other two color temperatures. Therefore, according to the results of this embodiment of the present invention, the optimal stimulus color temperature for happiness is around 4000K.

[0062] Table 3

[0063] After the subjects underwent a lighting procedure that induced amusement, the compatible image interaction platform 110 recorded BOLD responses in specific brain regions, as shown in Table 4. Clearly, all three color temperatures enhanced the BOLD response in amusement-related brain regions, with higher color temperatures showing stronger BOLD responses.

[0064] Table 4

[0065] After the subjects underwent a lighting procedure that induced emotions related to the Serene Index, the compatible image interaction platform 110 recorded BOLD responses in specific brain regions, as shown in Table 5. Clearly, exposure to a low color temperature of 3000K enhanced feelings of tranquility or relaxation. However, higher color temperatures negatively inhibited Serene Index emotions, with the negative inhibitory effect becoming more pronounced at higher color temperatures.

[0066] Table 5

[0067] Next, as shown in step 1500, the specific color temperature that increases the BOLD-dependent response to a specific emotion is screened through illumination. This specific color temperature is referred to as the "effective color temperature." In this embodiment, the BOLD response results of the corresponding emotionally responsive regions in the subject's limbic system are recorded to summarize the stimulating effects of color temperature on the brain, as shown in Tables 2 through 5. To screen the specific color temperatures that increase the BOLD-dependent response to a specific emotion, the specific color temperatures that maximize the response to that specific emotion (i.e., the area with the largest BOLD response) are calculated.

[0068] As shown in step 1510 in FIG. 1c , after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score for 3000K (577) is subtracted from the total score for 4000K (226), resulting in 351. Next, the total score for 3000K (577) is subtracted from the total score for 5700K (-105), resulting in 682. Therefore, the total response value after the excitement emotion is induced and under the illumination of 3000K is 1033.

[0069] Next, as shown in step 1520 in FIG. 1c , after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score for 4000K (226) is subtracted from the total score for 3000K (577), resulting in -351. Next, the total score for 4000K (266) is subtracted from the total score for 5700K (-105), resulting in 371. Therefore, the total response value after the excitement emotion is induced and under the illumination of 4000K is 20.

[0070] Next, as shown in step 1530 in FIG1c , after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score for 5700K (-105) is subtracted from the total score for 3000K (577), resulting in -682. Next, the total score for 5700K (-105) is subtracted from the total score for 4000K (266), resulting in -371. Therefore, the total response value after the excitement emotion is induced and under the illumination of 5700K is -1033.

[0071] According to the above calculations, after excitement is induced, an illuminance of 3000K maximizes the response. This means that 3000K produces a more pronounced boost in excitement (i.e., compared to the calculated total scores for 4000K and 5700K, 3000K achieves the highest total score of 1033). Therefore, 3000K is used as the "effective color temperature" for excitement. For other emotions, such as happiness, joy, and tranquility, different "effective color temperatures" can be obtained using the calculations from steps 1510 to 1530, as shown in Table 6.

[0072] Table 6

[0073] Next, based on the statistical results in Table 6, the effective color temperature can be interpreted as the result of a specific physiological emotion-dependent response. This effective color temperature can be considered the "enhancement spectrum" of the fMRI system's "blood oxygen concentration dependence" on a particular emotion. For example, an effective color temperature of 3000K can represent the fMRI system's "enhancement spectrum" for the emotion of "excitement," where the optimal stimulation color temperature should fall between 3000K and 4000K. For example, an effective color temperature of 4000K can represent the fMRI system's "enhancement spectrum" for the emotion of "happiness," where the optimal stimulation color temperature for happy situations is around 4000K. For example, an effective color temperature of 5700K can represent the fMRI system's "enhancement spectrum" for the emotion of "pleasure." For example, an effective color temperature of 3000K can also represent the fMRI system's "enhancement spectrum" for the emotion of "tranquility," where the optimal stimulation color temperature for tranquility is around 3000K.

[0074] Finally, as shown in step 1600, a "light recipe" database of "enhanced spectra" corresponding to specific emotional effects can be established within the fMRI system. By stimulating the subject with the aforementioned human-induced lighting parameters, observing and recording the BOLD response of the subject's brain during the light stimulation using the fMRI system, and simultaneously recording fMRI brain images, determining which part of the brain experiences an additive "blood oxygen concentration dependency" response to the light stimulation, a specific effective color temperature can be considered the "light recipe" for the fMRI "blood oxygen concentration dependency" of a specific emotion. Clearly, based on the statistical results of additive BOLD responses to specific emotions at specific "effective color temperatures" as shown in Table 6, the present invention objectively infers the "light recipe" for the subject's specific physiological emotional response. This "light recipe" serves as evidence for the physiological emotional response that produces the strongest additive effect for a specific emotion (including excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness, or neutrality).

[0075] It should be emphasized that in the entire implementation process of Figures 1b and 1c of the present invention, after conducting complete tests on multiple specific emotions on 100 test subjects, the statistical results in Table 6 were obtained based on this. For example, with respect to the emotion of excitement, providing an effective color temperature of 3000K as the "enhanced spectrum" under the physiological emotional response of excitement as a "light formula" can make the test subject's excitement produce a physiological emotional response with the strongest additive effect. For example, with respect to the emotion of happiness, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotional response of happiness as a "light formula" can make the test subject's happy emotion produce a physiological emotional response with the strongest additive effect. For another example, with respect to the emotion of pleasure, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotional response of pleasure as a "light formula" can make the test subject's pleasure produce a physiological emotional response with the strongest additive effect.

[0076] Furthermore, it should be emphasized that the three color temperatures described above represent only three examples of the present invention, and are not intended to be the only lighting systems to be used as an "enhanced spectrum" for physiological emotional responses. In practice, the entire process illustrated in Figures 1b and 1c can be repeated for different emotions (including excitement, happiness, joy, anger, disgust, fear, sadness, calmness, or neutrality) by increasing the color temperature from 2000K to 100K in increments of 100K. Therefore, Table 6 of the present invention only discloses a portion of the results and is not intended to limit the present invention to these examples.

[0077] Next, the present invention aims to establish an artificial intelligence model for the correlation between brain waves and brain images of general physiological emotions. This allows for future commercialization, allowing the inference of physiological emotions directly from other sensing devices without the need for an fMRI system. The sensing device used in the present invention includes an EEG. In the following embodiment, an EEG is used to establish physiological emotional responses to light. Alternatively, an eye tracker 150 or an expression recognition technology-assisted program 170 can be used to replace the fMRI system for physiological emotional responses. However, the eye tracker 150 and expression recognition technology-assisted program 170 will not be disclosed in this invention, but are hereby disclaimed.

[0078] Please refer to Figure 2a, which illustrates a method for grading physiological and emotional responses to human-induced lighting using electroencephalograms. As shown in Figure 2a, the present invention utilizes an electroencephalogram (EEG) device 130 to establish physiological and emotional responses to human-induced lighting. The method includes the following steps: First, as shown in step 2100, the "enhanced spectrum" database information in Table 6 is stored in the memory of the EEG device 130. Next, as shown in step 2200, the subject wears the EEG device and is guided through various emotional stimulations using known images or video elements. For example, the International Affection Picture System (IAPS) can be used as the emotional stimulation for known images or videos. Next, as shown in step 2300, the intelligent human-induced lighting system 100 is activated to provide variable light signal parameters, such as spectrum, light intensity, flicker rate, and color temperature, to stimulate the subject's light. The EEG device 130 then records the EEG data after exposure to light at different color temperatures under specific emotions. For example, in this embodiment, each subject is first stimulated with excitement. Subsequently, as in steps 2310 to 2330, different color temperatures of 3000K, 4000K, and 5700K are provided to the subject for light stimulation. EEG patterns of the subject's specific emotions during the excitement stimulation and after the different color temperature light stimulation are recorded and stored in the memory of the electroencephalogram 130. In this embodiment of the present invention, the EEG patterns of 100 subjects after the specific emotional stimulation and light exposure are recorded, thus requiring a larger memory.

[0079] Next, as shown in step 2400, the EEG pattern files corresponding to specific emotions (e.g., excitement, happiness, and joy) stored in the EEG device 130's memory are learned through artificial intelligence learning. Because the EEG device 130 can only memorize brainwave waveforms, the EEG patterns currently stored in the EEG device 130's memory are those generated in response to specific known triggering emotional stimuli and illumination at different color temperatures. It should be noted that in actual testing, different test subjects will experience different EEG patterns in response to the same emotional stimulus and illumination at the same color temperature. Therefore, during the learning process in step 2400, the present invention uses the information in the "light recipe" database of the "enhanced spectrum" to classify brainwave patterns associated with specific emotions. For example, for excited brainwave patterns, only brainwave patterns generated at a color temperature of 3000K by different test subjects are grouped together. For happy brainwave patterns, only brainwave patterns generated at a color temperature of 4000K by different test subjects are grouped together. For joyful brainwave patterns, only brainwave patterns generated at a color temperature of 5700K by different test subjects are grouped together. The electroencephalometer is then trained using machine learning within artificial intelligence. In this embodiment of the present invention, a transfer learning model is specifically selected for learning and training.

[0080] During the learning and training process using the transfer learning model in step 2400, the learning and training is performed by statistically analyzing, calculating, and comparing similarities for groups of EEG patterns for specific emotions. For example, when learning and training a group of EEG patterns with a color temperature of 3000K, the learning and training is performed by statistically analyzing, calculating, and comparing the most similar and least similar EEG patterns for excitement, among the EEG patterns with a color temperature of 3000K. For example, the EEG patterns with the highest similarity can be considered the EEG patterns with the strongest emotions, while the patterns with the lowest similarity can be considered the EEG patterns with the weakest emotions. The EEG patterns ranked for the strongest emotions can be used as the "target value," while the patterns ranked for the weakest emotions can be used as the "starting value." For ease of explanation, the most similar EEG pattern is used as the "target value," while the least similar EEG pattern is used as the "starting value." Different scores are assigned, for example, a similarity score of 90 is assigned to the "target value," and a similarity score of 30 is assigned to the "starting value." Similarly, complete the EEG files for the levels of happiness in the 4000K color temperature category and the levels of surprise in the 5700K color temperature category. The "starting value" and "target value" can be used to form a similarity score range.

[0081] Next, as shown in step 2500, an artificial intelligence EEG classification and grading database (referred to as the artificial intelligence EEG file database) is established. After step 2400, the EEG file groups of various specific color temperatures are assigned "target value" scores and "starting value" scores, forming a database of the grading results, which is stored in the memory of the electroencephalogram (EEG) device 130. The purpose of establishing the EEG classification and grading database in step 2500 is to obtain an EEG file of an unknown subject after being exposed to specific emotional stimulation and illuminated with a specific color temperature. By comparing the similarity score range of this EEG file with the EEG files in the database, the current state of the unknown subject's cerebral congestion reaction can be determined or inferred. The detailed process is shown in Figure 2b.

[0082] Next, please refer to Figure 2b, which illustrates the present invention's construction of a lighting database for effective human-factored lighting. First, as shown in step 3100, the subject wears an electroencephalogram (EEG) monitor 130 and views images that induce specific emotions. Next, as shown in step 3200, the human-factored lighting system 100 is activated to apply a "light recipe" to the subject. This occurs in an environment (e.g., a testing space) equipped with various adjustable multi-spectral lighting modules. The management and control module 611 (shown in Figure 3) provides variable light signal parameters such as spectrum, light intensity, flicker rate, color temperature, and exposure time. Next, as shown in step 3300, the subject's EEG files after emotional induction and lighting exposure are acquired and recorded, and stored in the memory module 617 (shown in Figure 3) of the cloud 610. Next, as shown in step 3400, the artificial intelligence EEG file database is imported into the management and control module 611. The management and control module 611 sets a score to determine whether the similarity is sufficient. For example, a similarity score of 75 or above indicates that the subject's brain congestion response is sufficient. Next, as shown in step 3500, the management and control module 611 compares the subject's EEG file with the artificial intelligence EEG file for similarity. For example, if the similarity score after the comparison of the subject's EEG file is 90, the management and control module 611 immediately determines that the subject's brain congestion response is sufficient and proceeds to step 3600, terminating the specific emotion human factor illumination test. Next, step 3700 records the human factor illumination parameters at which the subject's brain congestion response reached the desired level of stimulation and stores them in the database in the memory module 617.

[0083] Next, in step 3500 of FIG2b , if the similarity score between the subject's EEG file and the artificial intelligence EEG file is 35, the management and control module 611 determines that the subject's brain hyperemia response is insufficient and proceeds to step 3800 . The management and control module 611 then continues to strengthen the human-factor illumination test, including increasing illumination time or intensity based on the similarity score. Step 3300 is then repeated to obtain EEG files after increasing illumination time or intensity. The human-factor illumination test is terminated only after the similarity score reaches a predetermined score of 75 or higher, proceeding through step 3400 . If the management and control module 611 determines that the subject's brain hyperemia response has reached a certain level of stimulation, a human-factor illumination parameter data file is created for the subject in step 3700 . Finally, the management control module 611 compiles each test subject's human factors lighting parameters into a "human factors lighting parameter database" and stores it in the memory module 617. Obviously, as more test subjects are included, the artificial intelligence EEG file database of the present invention will learn more EEG files, making the similarity score of the present invention increasingly accurate.

[0084] After establishing the artificial intelligence model for the "Human Factor Lighting Parameter Database," the present invention can, upon activation of the human factor lighting system 100, infer physiological and emotional changes in a new test subject's brain images simply by observing the electroencephalogram (EEG) analysis results from the electroencephalogram (EEG) monitor 130. This eliminates the need for expensive fMRI systems, as the artificial intelligence model for inferring physiological and emotional changes in brain images can be used. This allows the human factor lighting system 100 to be promoted and used commercially. Furthermore, to facilitate commercial use of the "Human Factor Lighting Parameter Database," the "Human Factor Lighting Parameter Database" can be stored in an internal private cloud 6151 within the cloud 610.

[0085] Next, please refer to Figure 3, which is a system architecture diagram of the intelligent human-centered lighting system 600 of the present invention. As shown in Figure 3, the overall architecture of the intelligent human-centered lighting system 600 of the present invention can be divided into three blocks, including: a cloud 610, a lighting field 620, and a client 630. These three blocks are connected via the Internet. Therefore, the three blocks can be distributed in different areas or configured together. The cloud 610 further includes a management and control module 611, which is used for cloud computing, cloud environment construction, cloud management, and use of cloud computing resources. It also allows users to access, construct, or modify the content in each module through the management and control module 611. The consumption module 613 is connected to the management and control module 611 and serves as a cloud service that users subscribe to and consume. Therefore, the consumption module 613 can access each module in the cloud 610. The cloud environment module 615 is connected to the management control module 611 and the consumption module 613, and divides the cloud backend environment into an internal private cloud 6151, an external private cloud 6153, and a public cloud 6155 (for example, a commercial cloud), etc., and can provide an interface for external or internal services of the system provider or user. The memory module 617 is connected to the management control module 611 and is used as a storage area for the cloud backend. The technical content required to be executed by each module in the present invention will be specifically described in different subsequent embodiments. The lighting field 620 can communicate with the cloud 610 or the client 630 via the Internet. Among them, a lamp group 621 composed of multiple light-emitting devices is configured in the lighting field 620. And the client 630 can communicate with the cloud 610 or the lighting field 620 via the Internet. The client 630 of the present invention includes general users and editors who use the intelligent human-centered lighting system 600 of the present invention for various business operations. All of these belong to the client 630 of the present invention. The representative device or apparatus of the client 630 can be a fixed device with computing functions or a portable intelligent communication device. In the following description, users, creators, editors, or portable communication devices can all represent the client 630. In addition, in the present invention, the Internet can be an intelligent Internet of Things (AIoT).

[0086] Please refer to Figure 4, which is a method 400 of the present invention for constructing a lighting environment sharing platform. The process of Figure 4 is carried out in the system of the intelligent human-centered lighting system 600 in Figure 3, wherein the intelligent human-centered lighting system 600 has a plurality of light-emitting devices 621 that provide different spectrums, which can be an LED lamp group. The present invention particularly explains that the LED lamp group can choose to combine a light formula with a specific color temperature by modulating the voltage or current of individual LED lamps to provide a light formula for lighting. Of course, the present invention can also choose to use a plurality of LED lamps with specific light-emitting spectra, and by providing a fixed voltage or current to allow each energized LED lamp to emit its specific spectrum, to combine a light formula with a specific color temperature for lighting. Furthermore, it should be emphasized that the actual illumination process of the light-emitting devices 621 with different spectra described in the present invention is to emit different spectra through multiple LED lamp groups. Therefore, the light-emitting devices with different spectra can be composed of light-emitting devices 621 with different spectra, or they can be composed of multiple identical light-emitting devices 621, and the emitted spectra can be adjusted to different spectra by the power provided by the control device. Therefore, the present invention is not limited to the above-mentioned embodiments of the light-emitting devices 621 with different spectra, and of course also includes light-emitting devices with different spectra formed by other methods.

[0087] First, as shown in step 410, a multi-spectral lighting device cloud database is constructed. The management and control module 611 in the cloud 610 loads the "human-factor lighting parameter database" stored in the memory module 617 or the internal private cloud 6151 into the management and control module 611. The "human-factor lighting parameter database" stored in the cloud 610 already knows how various color temperatures can stimulate people (or users) with corresponding emotions. For example, the specific color temperatures shown in Table 6 can stimulate specific emotions with a synergistic effect.

[0088] Next, as shown in step 420, a cloud database of light scenes for a multi-spectral lighting device is constructed. Since each color temperature can be combined through a variety of different spectra, that is, the same color temperature can be obtained by different light recipes. For example, when we want to establish a spectrum that can provide a 4000K color temperature, we can choose a light recipe for the Maldives at a 4000K color temperature, or we can choose a light recipe for Bali, Indonesia at a 4000K color temperature, or further choose a light recipe for Monaco Beach at a 4000K color temperature. Obviously, these light recipes with a 4000K color temperature have different light recipes based on their geographical location (including: longitude and latitude), time / brightness / flicker rate and other factors. Therefore, in step 420, based on the relationship between color temperature and corresponding emotions in the "human-centric lighting parameter database," cloud 610 can collect different light recipes at various specific color temperatures for different geographic locations on Earth. For example, different light recipes at a 4000K color temperature for different geographic locations on Earth can be collected (e.g., 4000K color temperature at different longitudes and latitudes), or different light recipes at a 4000K color temperature at different times on Earth (e.g., 4000K color temperature at 9:00 AM). Subsequently, the collected different light recipes at various specific color temperatures for different geographic locations on Earth are similarly stored in memory module 617. Under the control of management control module 611 in intelligent human-centric lighting system 600, various light recipe parameters with specific color temperatures (i.e., different geographic locations or different times at different geographic locations) can be adjusted by controlling multiple light-emitting devices 621 with different spectra. Finally, after storing the various light recipe parameters with specific color temperatures in the memory module 617, the intelligent human-centered lighting system 600 of the present invention can construct a "multi-spectral lighting device cloud database" that produces various color temperatures at different geographic locations. Obviously, the "multi-spectral lighting device cloud database" constructed in step 420 is a preset "light recipe" adjusted by multiple light devices 621 with different spectrums. For example, each multi-spectral light recipe is adjusted by the light device 621 by adjusting or controlling the color rendering index (Ra), flicker, illuminance, and color temperature. Furthermore, it is important to emphasize that by understanding how specific color temperatures can stimulate specific emotions with additive effects, the present invention can generate various preset "light recipes." In addition to using light recipes based on different geographic locations on Earth, the present invention can also use artificial intelligence to synthesize or combine preset "light recipes" that differ from actual geographic locations by taking into account factors such as latitude and longitude, time of day, brightness, and flicker rate. This is not a limitation of the present invention. Obviously, in step 420, the present invention has already constructed a database of multiple preset "light recipes."Therefore, based on the constructed preset "light recipe" database, the intelligent human-centered lighting system 600 can provide various preset "light recipe" lighting services through the lighting device 621. At this point, the various "light recipe cloud databases" constructed in step 420 can be stored in the memory module 617, the internal private cloud 6151, or the public cloud 6155 (e.g., a commercial cloud).

[0089] As shown in step 430, it is necessary to determine whether the preset "light recipe" is effective. Because the effects of human-centric lighting spectrum exposure on emotional stimulation or influence may vary among different users, the preset "light recipe" illumination spectrum needs to be further adjusted. When user 630 enters the intelligent human-centric lighting system 600 of the present invention, the management and control module 611 can access the memory module 617 or the "multi-spectral lighting device cloud database" in the internal private cloud 6151 or the public cloud 6155 to select the preset "light recipe" that matches the desired emotion. The management and control module 611 then selects a preset "light recipe" from the memory module 617 or the "multi-spectral lighting device cloud database" in the internal private cloud 6151 or the public cloud 6155, and controls the lighting device 621 configured at user 630 to illuminate the preset "light recipe" that matches the desired emotion, thereby performing the lighting program for the user. For example, if a user wants to adjust their mood to a happy or joyful one, they can choose to use a preset "light recipe" with a color temperature of 4000K based on the "Human Factor Lighting Parameter Database." At this point, the user can access the preset "light recipes" provided by the "Multi-spectral Lighting Device Cloud Database," or select a preset "light recipe" that provides a 4000K color temperature. Of course, users can also select a specific preset "light recipe" that is widely used.

[0090] Next, as shown in step 430, when the user selects a preset "light recipe" for a happy or pleasant emotion (for example, the system presets a Maldives light recipe at a color temperature of 4000K), and the light recipe is adjusted by multiple light-emitting devices 621 and then a lighting program is performed, for example, after 15 minutes of lighting, the user can determine or evaluate whether the light recipe has effectively achieved a happy or pleasant emotion. The user can determine or evaluate whether the light recipe has effectively achieved a happy or pleasant emotion based on their own feelings.

[0091] Continuing with step 430, when the user intuitively feels that they have effectively achieved a happy or pleasant mood, they can record and store this experience in an external private cloud 6153 or a public cloud 6155. For example, after recording and storing this experience in the external private cloud 6153, it can serve as the user's personal experience archive. Alternatively, this experience can be recorded and stored in the public cloud 6155 for reference by other users. If, after 15 minutes of light exposure, the user still feels that they have not achieved a happy or pleasant mood, they can adjust the light recipe through the management and control module 611, for example, by adjusting the exposure time to 30 minutes or changing the light scene of the light recipe. For example, returning to step 420 and selecting another light recipe scene, such as changing the preset Maldives scene to Bali, Indonesia, is performed again in step 430. After the light exposure process is completed, it is again determined or evaluated whether the Bali light recipe has effectively achieved a happy or pleasant mood. When the user feels that the multispectral lighting of the current light scene has effectively achieved a happy or joyful mood, they can record and store the effective light scene usage experience to form a "light recipe." Finally, this "light recipe" is stored in an external private cloud 6153 or public cloud 6155 to form a shared platform. Obviously, the shared platform stores multiple "light recipes," including the lighting control parameters of the light recipe that achieves the user's specific emotional effect (hereinafter referred to as "lighting parameters").

[0092] Finally, as shown in step 470, a shared platform for the lighting environment is established. After users record and store their effective user experience in an external private cloud 6153 or public cloud 6155, this not only serves as the user's personal experience archive, but the intelligent human-centered lighting system 600 can also, in step 470, perform a massive data analysis of this extensive user experience data and then record and store it in the internal private cloud 6151 or public cloud 6155. This allows the information stored in the public cloud 6155 to form a shared platform for the lighting environment. For example, after performing a massive data analysis of the user experience data, the intelligent human-centered lighting system 600 can determine the ranking of user-selected "light recipes" for different light scenes with a specific color temperature. This ranking can provide users with a reference when selecting a "light recipe." Furthermore, after analyzing this massive data, various indicators can be generated for user reference. For example, different light recipes with a 4000K color temperature can be ranked based on user gender, age, race, season, time of day, and so on. This allows the light environment sharing platform constructed by the present invention to serve as a platform for designers interested in or willing to provide human-centric lighting recipes, using these indicators to conduct commercial services and operations. Therefore, the light environment sharing platform constructed by the present invention allows the intelligent human-centric lighting system 600 to provide various user experiences that have been curated or algorithmically calculated as preset light recipes. Furthermore, users can also select a most popular "light recipe" for lighting based on the calculated user experience data.

[0093] In the embodiment of Figure 4, step 450 is optional. For example, if the user is simply creating a database for their own use, step 450 can be skipped. After determining validity in step 430, the user experience can be directly stored in the "light recipe sharing platform" in step 470. For example, valid user experience can be recorded and stored in an external private cloud 6153 or a public cloud 6155. The database for the "light recipe" creation service established in step 450 will be described in later embodiments.

[0094] Next, Figure 4 shows another embodiment that provides a creation platform for commercial services and operations. This creation platform allows different users or creators to create new "light recipes." As shown in step 460, a "light recipe" creation platform is provided within the intelligent human-centered lighting system 600. Creators 630 using this "light recipe" creation platform can be located anywhere in the world and can connect to the "light recipe sharing platform" in the cloud 610 of the present invention via the internet. Obviously, the present invention defines a "light recipe" creation platform as one that allows users or creators 630 to connect to the public cloud 6155 or "light recipe sharing platform" in the cloud 610 via the internet, allowing users or creators 630 to edit the "light recipe" information on the public cloud 6155 or "light recipe sharing platform." Therefore, when the user or creator 630 obtains various calculated usage experience data from the "sharing platform", the user or creator 630 can edit or create the creator 630 personally based on the user's gender, age, race, season, time and other experience data to construct an edited multi-scene or multi-emotional "light recipe".

[0095] First, the present invention uses a "light recipe" creation platform for commercial services and operations in a first embodiment. For example, for an emotional stimulation result of 4000K color temperature, users or creators 630 can use the "light recipe" creation platform to create spectral combinations for different light scenes. For example, creator 630 might select a light recipe for the Maldives for the first segment, a light recipe for Bali for the second segment, and finally, a light recipe for a beach in Monaco for the third segment. By combining or configuring the spectral exposure time for each segment, a new spectral combination of multiple light scenes is formed. Finally, this spectral combination of multiple light scenes is stored on the "sharing platform," allowing other users to select this spectral combination of multiple light scenes as their own "light recipes" for mood adjustment. The creation platform of the present invention also allows for the selection of specific color temperatures at specific times. For example, if a user wants to perform emotional stimulation light treatment at 9 AM, they can select the three aforementioned light recipes for 9 AM to accommodate the human body's circadian rhythm. Furthermore, the multi-spectral exposure time for each segment can be configured to be the same or different, for example, each segment can be exposed for 15 minutes. Alternatively, the first and third segments may be configured for 15 minutes, while the second segment may be configured for 30 minutes. These same or different time configurations may be selected by the user.

[0096] Secondly, in the second embodiment of the present invention using the "Light Recipe" creation platform, different color temperatures (i.e., multiple emotions) can be combined to achieve a transition effect through multi-emotional lighting. For example, creator 630 can use the "Light Recipe" creation platform to combine multiple emotions. For example, if creator 630 wants to edit an emotion transition from tension to joy, the first segment can be a light recipe of 4000K (happy emotion), the second segment can be a light recipe of 3000K (excited emotion), and finally, the third segment can end with a light recipe of 5700K (pleasant emotion). In this way, after each segment is combined or configured with multi-spectral exposure time, a light recipe combination for emotion transition can be formed. Finally, this light recipe combination for emotion transition can be stored on the "sharing platform", which can provide users with the option to select this light recipe combination for emotion transition or adjustment. Similarly, the creative platform in this embodiment can also select specific color temperatures for specific times. For example, if a user wants to perform emotionally stimulating human-induced lighting at 9 a.m., they can further select the aforementioned three-segment light recipe combination for 9 a.m. to accommodate the human body's circadian rhythm. Furthermore, the multispectral illumination time for each segment can be configured to be the same or different, for example, each segment can be configured for 15 minutes. Alternatively, the first and third segments can be configured for 15 minutes, while the second segment can be configured for 30 minutes. These identical or different time configurations can be selected by the user.

[0097] Next, it is further explained that after the editing or creation of the above-mentioned first embodiment (light formula for multiple light scenes) and the second embodiment (light formula combination for multiple emotions), it is also necessary to go through the process of steps 430 to 470. For example: the creator 630 will edit the light formula combination for multiple emotions, and must first go through step 420 to illuminate the user with the light formula combination for multiple emotions through multiple light-emitting devices 621. Then, through step 430, it is determined whether the combination of the above-mentioned "light formulas" achieves the effect that the creator wants to achieve, including: the spectral combination of the multiple light scenes of the first embodiment and the corresponding configured illumination time, and the multi-emotion light formula combination and the configured illumination time of the second embodiment. If the effect set by the creator can be achieved, the lighting control parameters of the light-emitting devices 621 required for establishing these "light formulas" can be established in the database of the service, as shown in step 450. , wherein lighting control parameters include color rendering index (Ra), flicker, illuminance, and color temperature. Subsequently, as shown in step 470, after uploading the lighting control parameter database of the "light recipes" constructed in step 450 to the cloud, these "light recipes" can be added to the public cloud 6155 of the present invention to form a "light recipe sharing platform." If, after step 430, a "light recipe" is determined not to achieve the desired effect, the process can return to step 420 to adjust the exposure time for each segment, or change different light scene combinations (first embodiment) or different mood combinations (second embodiment) until all "light recipes" achieve the desired effect. Then, through steps 430 to 470, these "light recipes" that have been determined to be effective can be added to the public cloud 6155 of the present invention to form a "light recipe sharing platform."

[0098] Furthermore, in order to achieve the desired effect of the multi-scene or multi-emotional combinations within the "light recipe" creation platform, specific lighting devices 621 may need to be configured within the venue and evaluated by professional designers to achieve the optimal effect. Therefore, the present invention further configures a hardware service database, as shown in step 4510, and a software service database, as shown in step 4520. The hardware and software service databases also embed management information for creating "light recipes," including hardware device installation and delivery, or software services required for creating these "light recipes" such as spatial design, scene planning, or interface settings, provided through the software service database. Furthermore, the hardware and software service databases can be located on the creator's 630 end or in the cloud 610, and this is not a limitation of the present invention. Clearly, in the embodiment of FIG. 4 , the present invention already provides the process for creating various "light recipes" and the database for "light recipe" creation services. The hardware and software service databases required for creating "light recipes" are also located within the "light recipe sharing platform." It is particularly important to note that the "light recipe sharing platform" ultimately established in step 470 is a "light recipe" that can provide effective spectral combinations of multiple light scenes and spectral combinations of multiple mood light scenes. Afterwards, various commercial services and operations can be provided through this "sharing platform."

[0099] Next, please refer to Figures 3 and 5a. Figure 5a illustrates an automatically controllable intelligent human-centric lighting method 500 according to the present invention. First, as shown in step 510, a cloud database for multi-spectral lighting devices is constructed. The management and control module 611 in the cloud 610 loads the "human-centric lighting parameter database" stored in the memory module 617 or in the internal private cloud 6151 into the management and control module 611. The "human-centric lighting parameter database" stored in the cloud 610 already knows how different color temperatures can stimulate people (or users) with certain emotions. The management and control module 611 then loads the "human-centric lighting parameter database" stored in the memory module 617 into the management and control module 611. The "human-centric lighting parameter database" stored in the memory module 617 already knows how different color temperatures can stimulate people (or users) with certain emotions. For example, as shown in Table 6, a specific color temperature can stimulate a specific emotion with a multiplier effect.

[0100] Next, as shown in step 530, a cloud-based database of light recipes for human-centric lighting is constructed. In step 530, the management control module 611 downloads the "light recipes" stored in the "sharing platform" established in step 470, serving as the source for constructing a multi-light recipe cloud-based database for human-centric lighting. Therefore, the process of creating the "light recipes" established in step 470 will not be detailed here. Please refer to steps 410 through 470 in Figure 4 for a detailed description.

[0101] Next, as shown in step 520, a "situational dynamic spectrum editing platform" is provided. Similarly, the present invention defines a "situational dynamic spectrum editing platform" similar to the aforementioned "light recipe creation platform." The present invention's "situational dynamic spectrum editing platform" refers to a platform that allows users or creators 630 to connect to a public cloud 6155 or a "light recipe sharing platform" in the cloud 610 via the internet, allowing users or creators 630 to use the "light recipe" information on the public cloud 6155 or the "light recipe sharing platform" to perform contextual editing. After the "Contextual Dynamic Spectrum Editing Platform" obtains multiple "light recipe" data from the "Light Recipe Sharing Platform", the "Contextual Dynamic Spectrum Editing Platform" can edit or create the "light recipe" contextually through the software application to construct an edited "Contextual Dynamic Spectrum Program" that achieves (or satisfies) a specific emotional effect. This "Contextual Dynamic Spectrum Program" can also be uploaded to the external private cloud 6153 and public cloud 6155 in the cloud 610 to form a database of "Contextual Dynamic Spectrum Programs" that achieve (or satisfy) a specific emotional effect.

[0102] Next, the editing process of the "situational dynamic spectrum program" in step 520 will be described in detail. Please refer to Figure 5b, which shows the editing process of the situational dynamic spectrum editing platform of the present invention. As shown in step 5210, the editor 630 downloads the "light recipe" stored in the "sharing platform" established in step 470 to the editing device used by the editor 630 via the Internet to the management control module 611 in the cloud 610. For example, the editing device can be a computer, a smart phone, or a workstation. In particular, one or more "light recipes" are connected to the Software as a Service (SaaS) or Platform as a Service (PaaS) system configured in the cloud 610 through the editing device of the editor 630. Afterwards, as shown in step 5220, the downloaded "light recipe" is configured through the SaaS or PaaS system configured on the cloud to set the lighting parameters of a specific color temperature (i.e., a specific emotion), wherein the setting items of the lighting parameters include: the generation time of the spectrum, the longitude and latitude of the spectrum, the brightness of the spectrum, the contrast of the spectrum, the flicker rate of the spectrum, and the control of the color rendering index (Ra) and other lighting parameters of the "light recipe", which are adjusted and set. The above-mentioned adjustment method is the same as the aforementioned method of the present invention, including: changing the order of light scenes in the "light recipe", or changing the light scenes in the "light recipe", or deleting specific light scenes in the "light recipe", or adding new light scenes to the "light recipe", etc. Since these adjustment methods have been explained, they will not be repeated here. For example, if a user downloads a spectral combination of multiple light scenes as a "light recipe" for achieving a happy (4000K) mood, they can use the SaaS or PaaS system to fine-tune the multispectral brightness and contrast of the Maldives light recipe. They can also choose to adjust the spectral flicker rate of the second Bali light recipe, or adjust the lighting sequence or duration of the three light recipes. Alternatively, they can consider the light recipes provided based on the latitude and longitude of the spectrum or the time of day. For example, through the SaaS or PaaS system, they can add a light recipe for Cannes, France, at a color temperature of 4000K, or remove the light recipe for Monaco's beaches and replace it with a light recipe for Miami Beach, USA, at a color temperature of 4000K. For example, when a user or editor 630 downloads a "light recipe" for a spectrum combination of multiple light scenes, other light scene combinations can be made through the SaaS or PaaS system. The above adjustment and change process can also be performed by accessing the "human factors lighting parameter database" stored in the memory module 617 in step 510 to make other emotion (color temperature) combinations. For example, in the aforementioned "light recipe" for multiple light scenes of happiness, excitement, and pleasure, a fourth color temperature segment for the emotion of tranquility can be added as the final stage of the lighting.

[0103] Next, as shown in step 5230, the association between the contextual function and the "light recipe" is edited. In step 5230, the "light recipe" adjusted or set in step 5220 is edited to associate with the specific contextual function desired by the user or editor 630. The association is to divide the desired specific contextual function into multiple blocks, and each of these blocks corresponds to a light scene in the "light recipe." For example, in step 5210, the user downloads a "light recipe" of happy, exciting, and joyful multi-light scenes. When the user or editor 630 ultimately wants to achieve a good situational effect in the conference room (wherein, the so-called good conference situational effect, for example, the editor 630 chooses that during the conference, all participants should be relaxed at the opening, focused during the discussion, and happy at the conclusion), the original "light recipe" can be adjusted to a "light recipe" of relaxation, focus, and joyful multi-light scenes through step 5220. In step 5230, the user or editor 630 divides the conference process into three situational blocks: opening, discussion, and conclusion. Then, the three situational blocks of opening, discussion, and conclusion are respectively corresponded to the "light recipes" of relaxation, focus, and joyful multi-light scenes, so that the situation of the entire conference process is associated with the "light recipes" of the multi-light scenes in the conference room. Next, as shown in step 5240, after the user or editor 630 has completed the association between the context of the meeting process and the "light recipe" of the multi-light scene, and then added "time settings" to the context blocks, a "contextual dynamic spectrum program" with meeting context functions is created. For example, by setting the playback time of the opening, discussion, and conclusion blocks to 5 minutes, 15 minutes, and 10 minutes, as shown in Figure 5c, a "contextual dynamic spectrum program" with meeting context functions is created. Finally, as shown in step 5250, the "contextual dynamic spectrum program" with context functions is uploaded to the cloud database. Obviously, the "contextual dynamic spectrum program" generated through the editing process of Figure 5b can be stored in the memory module 617 or the external private cloud 6153 or public cloud 6155 through step 530. These "contextual dynamic spectrum programs" stored in the external private cloud 6153 can then become a "contextual dynamic spectrum program" with automatically adjustable intelligent human-induced lighting, available for personal use. For example, when a user or editor 630 selects a "Contextual Dynamic Spectrum Program" for a meeting, the spectrum in the conference room can be automatically adjusted during the meeting. Of course, the "Contextual Dynamic Spectrum Program" edited by editor 630 can also be stored in the public cloud 6155, allowing it to be used by other users through the cloud 610 for commercial purposes.Obviously, in step 530, in addition to the various "light recipes" downloaded from step 470, "situational dynamic spectrum programs" are also included. Therefore, all data stored in the cloud database established in step 530 can be provided to users for human-oriented lighting. In addition, it should be emphasized that in this embodiment, the editing of "situational dynamic spectrum programs" for multiple light scenes includes single-emotion multi-light scene combinations and multi-emotion multi-light scene combinations. Of course, specific emotions within the multi-emotion multi-light scene combination can also be combined using multiple light scenes, and the present invention is not limited to this.

[0104] In addition, during the editing process of FIG. 5 b , another embodiment can be selected. Editor 630 downloads the "light recipe" stored in the "sharing platform" established in step 470 to the editing device used by editor 630 via the Internet to the management control module 611 in cloud 610. Then, the user or editor 630 can first edit the specific scenario function they want to achieve (i.e., first divide the specific scenario function into multiple blocks) through the SaaS or PaaS system. Then, they can associate the specific scenario function with the downloaded "human-based lighting parameter database" to complete the association editing between the multiple scenario blocks and the corresponding emotions (color temperatures) to form a multi-emotion multi-light scene combination. For example, if the editor has already divided the meeting process into three blocks: opening, discussion, and conclusion, they can then select a "light recipe" corresponding to the multi-light scene corresponding to the corresponding emotions of relaxation, concentration, and joy from the "human-based lighting parameter database" stored in the memory module 617, or select a "light recipe" corresponding to the multi-light scene corresponding to joy, concentration, and relaxation. Since the method of editing itinerary association is the same, it will not be described in detail in this embodiment.

[0105] Next, the present invention provides another preferred embodiment of an automatically adjustable intelligent human-factor lighting method. Since the "situational dynamic spectrum program" constructed in step 530 is the result of editing by individual editors 630, to achieve optimal results, it is necessary to consider the light stimulation effects of the "light recipe" on different users and / or the lighting hardware configuration in different locations to achieve the light stimulation effects of the "light recipe." These all require adjustments.

[0106] Next, as shown in steps 550 and 570, the user or editor further adjusts the lighting parameters in the specific environment where the "Contextual Dynamic Spectrum Program" is executed to achieve a specific emotional need or achieve a desired emotional shift. First, as shown in step 550, the user or editor 630 has downloaded a "Contextual Dynamic Spectrum Program" from an external private cloud 6153 or public cloud 6155. For example, the "Contextual Dynamic Spectrum Program" downloaded in step 530 can be a "light recipe" for multiple moods and multiple light scenes, or a "light recipe" for multiple light scenes with a single emotion. Next, in step 550, the user or editor 630 specifies the "specific environment" in which the selected "Contextual Dynamic Spectrum Program" will be executed. In this embodiment of the present invention, "specific environments" are categorized into three types, as shown in step 570: a closed lighting system, an intelligent lighting field, and a portable human-centric lighting device. When the "specific environment" is a closed lighting system, for example, the closed lighting system is a closed control room (i.e., a closed cavity that can isolate external light) with multiple light-emitting devices 621, which can provide one or more users with a "light recipe" of receiving the selected "situational dynamic spectrum program" in the closed cavity, as shown in step 571. During the spectrum illumination process, the present invention provides a function with a control mode setting, as shown in step 540, which can adjust the "light recipe" through an app on a mobile device used by the user or editor 630 or a control module in the closed cavity (e.g., a monitoring panel 670). For example, under the influence of an ambient light environment, the lighting parameters of the "light recipe" of the selected "situational dynamic spectrum program" can be adjusted, and the adjustment methods include: time / latitude and longitude / brightness / flicker rate. In addition, when the "specific environment" is a smart lighting field, the smart lighting field is a field that can accommodate multiple people and has multiple light-emitting devices 621, such as a conference room, a classroom, an office space, a social venue, or a factory, so that multiple users can receive "situational dynamic spectrum program" and perform "light recipe" illumination in the smart lighting field, as shown in step 573. Obviously, during the illumination process in step 570, the controller, user, or editor 630 of the field can adjust the lighting parameters of the "light recipe" of the selected "situational dynamic spectrum program" through the application (App) on the mobile device used or the control panel 670 in the field. For example, the lighting parameters of the "light recipe" can be adjusted based on the influence of the ambient light environment or the number of people in the field. The adjustment methods include time, longitude and latitude, brightness, flashing rate, etc., as shown in step 540.Furthermore, when the "specific environment" is a portable lighting device, wherein the portable human-factor lighting device is a virtual device related to the metaverse, such as a virtual reality (VR), mixed reality (MX), or extended reality (XR) device, the user can receive the selected "situational dynamic spectrum program" through the virtual device for "light recipe" illumination, as shown in step 575. During the light recipe illumination process, the user or editor 630 can adjust the lighting parameters of the "light recipe" through the app on the mobile device or the control module in the virtual device. For example, under the influence of an ambient light environment, the lighting parameters of the "light recipe" of the selected "situational dynamic spectrum program" can be adjusted, and the adjustment methods include: time / latitude and longitude / brightness / flicker rate, etc., as shown in step 540.

[0107] During the operations of steps 540, 550, and 570 described above, it is apparent that the preset values ​​of the "light recipe" for the user's "specific environment" are adjusted. During this preset value adjustment process, an ambient light sensor 650 (as shown in FIG. 3 or FIG. 6 ) located in the "specific environment" transmits ambient light information via wireless communication to an application (app) on the user's or editor's 630's mobile device, or to a control module within the "specific environment," for use as a reference for adjusting the preset values ​​of the "light recipe." Furthermore, a presence sensor 660 (as shown in FIG. 3 or FIG. 6 ) located in the "specific environment" transmits information about the number of people in the environment via wireless communication to an application (app) on the user's or editor's 630's mobile device, or to a control module within the "specific environment," for use as a reference for adjusting the preset values ​​of the lighting parameters in the "light recipe." This occupancy sensor 660 can be a vibration sensor that determines the number of people by the frequency of vibration. Alternatively, it can be a temperature sensor that determines the number of people by the ambient temperature. Alternatively, occupancy sensor 660 can be a camera system that uses artificial intelligence (AI) facial recognition to determine the number of people present. Furthermore, occupancy sensor 660 can also be a gas concentration detector that detects changes in oxygen (O2) or carbon dioxide (CO2) concentrations to determine the spectral illumination effect on the user. For example, when the ambient temperature increases and the carbon dioxide (CO2) concentration also increases, the spectral illumination is determined to have achieved the desired emotional effect. Clearly, through the operations of steps 540, 550, and 570, a "situational dynamic spectral program" of intelligent human-centered lighting with automatically adjustable lighting parameters can be created. It is particularly important to note that, in order to ensure that users can achieve the desired mood-changing or emotionally shifting effects during intelligent human-centered lighting, the lighting parameters of the lighting device 621 performing the lighting must be monitored and adjusted in real time in different specific environments or fields to achieve the desired effect.

[0108] The present invention then provides another preferred embodiment of an automatically adjustable intelligent human-centered lighting method. It further provides some sensing devices to provide feedback to the user on whether the desired emotional effect is achieved after being illuminated by the "light recipe" of the above-mentioned "situational dynamic spectrum program." These sensing devices include: contact physiological sensors (such as step 561) or non-contact optical sensors (such as step 563). Among them, the contact physiological sensors are configured on each user to measure the user's heart rate, blood pressure, pulse, blood oxygen concentration, or electrocardiogram, etc., to determine whether the user has achieved the desired emotion. The non-contact optical sensors can be configured in the lighting environment where the user is located to measure the illuminance, color temperature, spectrum, color rendering, etc. in the "specific environment" to determine whether the user has achieved the desired emotion.

[0109] As shown in step 580, it is determined whether the user's emotional needs have been met after the lighting. After the user has performed lighting according to the "light recipe" of a specific "situational dynamic spectrum program" in a "specific environment", an algorithm will be used to determine whether the current spectrum lighting process has met the user's emotional needs. The algorithm in step 580 can be a ratio between the user's physiological signals (including: heart rate, blood pressure, pulse and respiratory rate) and the ratio value is used to determine whether the specific emotional needs have been met. Therefore, after calculation and processing by the management and control module 611, a database of physiological signal ratios corresponding to various emotions is established and stored in the memory module 617 in the cloud 610 or the internal private cloud 6151. For example, after a user has been exposed to the "happy mood-enhancing dynamic spectrum program" for a period of time, the contact physiological sensor in step 561 feeds back heart rate, blood pressure, and blood oxygen levels to the mobile device app or the control module in the "specific environment." The mobile device app or the control module in the "specific environment" then uses an algorithm to calculate a ratio value based on this feedback data. This ratio value is then transmitted via the internet to the management control module 611, where it is compared with the ratio value stored in the memory module 617 or the internal private cloud 6151. For example, if the algorithm-calculated ratio value falls between 1.1 and 1.15, the management control module 611 determines that the probability of this ratio value representing a happy mood is 80% and the probability of representing a pleasant mood is 20%. If the probability of achieving the desired effect is determined to be 75%, the management control module 611 will determine that the user has achieved the desired happy mood after using the "light recipe" of the selected "Situational Dynamic Spectrum Program." The lighting process will then be terminated after the "Situational Dynamic Spectrum Program" completes the lighting process. Subsequently, in step 590, the current "light recipe" data for the "Situational Dynamic Spectrum Program" is stored in the internal private cloud 6151, external private cloud 6153, or public cloud 6155 within the cloud 610. If the algorithm determines that the user has only a 50% probability of achieving a happy mood after using the "light recipe" of the selected "Situational Dynamic Spectrum Program," the desired happy mood has not yet been achieved. At this point, it is necessary to return to step 550, adjust the lighting parameters of the "light recipe" of the selected "situational dynamic spectrum program" through the control mode of step 540, and then perform the lighting program again. The user's heart rate, blood pressure and blood oxygen are fed back to the App on the mobile device or the control panel 670 in the field through the contact physiological sensor of step 561. After the ratio is calculated by the algorithm, this ratio is once again transmitted to the cloud database via the Internet and compared with the ratio in the cloud database until the required happy mood is achieved.Obviously, during the storage process in step 590, it will also be stored in step 530 at the same time. Therefore, in addition to the various "light recipes" downloaded from step 470, the cloud database established in step 530 also includes the "situational dynamic spectrum program" adjusted by the algorithm. Therefore, the "situational dynamic spectrum program" cloud database stored in step 530 can provide more effective "situational dynamic spectrum program" for users to perform human-induced lighting. In addition, it should be emphasized that in this embodiment, the editing of the "situational dynamic spectrum program" of multiple light scenes includes a combination of multiple light scenes for a single emotion and a combination of multiple light scenes for multiple emotions. Of course, specific emotions in the combination of multiple light scenes for multiple emotions can also be combined using multiple light scenes, and the present invention is not limited to this.

[0110] The automatically adjustable intelligent human-centered lighting system or method provided by the present invention can use feedback signals to determine whether the user has achieved the desired effect after being illuminated by the selected "light recipe," allowing the user to determine or feel for themselves whether the desired effect has been achieved. The solution provided by the present invention utilizes the user's actual physiological signals for this determination. Therefore, the above-mentioned embodiments using physiological signals as algorithms are merely illustrative, intended to facilitate public understanding of the technical implementation methods of the present invention, and should not be construed as limiting the scope of the present invention. The present invention emphasizes that any "algorithm" described herein encompasses any individual comparison of a user's physiological signals or further comparison of physiological signals with data in the cloud 610 database after processing.

[0111] Based on the aforementioned automatically controllable intelligent human-centered lighting method, the present invention further provides an intelligent human-centered lighting system for commercial operations, as shown in FIG6 . The intelligent human-centered lighting system 600 for commercial operations of the present invention includes a cloud 610, a management and control module 611, an intelligent lighting field 620, and a portable communication device 630. The devices configured in the lighting field 620 include a lamp assembly or light-emitting device 621, at least one occupancy sensor 660, at least one ambient light sensor 650, and a control module 640. The lighting field 620 includes a "specific environment." As shown in FIG5a , this "specific environment" can be divided into three types: an enclosed space or intelligent lighting field for multiple users, and a portable human-centered lighting device or an enclosed space for individual use.

[0112] First, FIG6 discloses an intelligent human-centered lighting system 600A for commercial operations, which can be applied to an embodiment for use by multiple people. The client can use a portable communication device 630 to download a "light recipe" or a "situational dynamic spectrum program" to the cloud 610 via the Internet, and use the portable communication device 630 to start the lamp group 621 for human-centered lighting to form an automatically adjustable intelligent human-centered lighting system. In this embodiment, the client can be remote or in a specific environment at the near end. When the client is remote, the Internet is an intelligent Internet of Things (AIoT) formed by the Internet of Things (IoT) and artificial intelligence (AI). When the client is at the near end, the Internet is a wireless communication protocol formed by a gateway, including: Wifi or Bluetooth, etc.

[0113] Next, when multiple users are already distributed in a closed space or smart lighting field, they can use the portable communication device 630 to activate the lamp group 621 to perform human-induced lighting with a specific "light recipe" or "situational dynamic spectrum program." The closed lighting system is an enclosed space with multiple light-emitting devices (for example, a closed cavity that can isolate external light), which can provide one or more users with human-induced lighting in the closed cavity. The smart lighting field is a field with multiple light-emitting devices that can accommodate multiple people, such as a conference room, a classroom, an office, a social venue, or a factory, etc., which can provide multiple users with human-induced lighting in the smart lighting field.

[0114] Furthermore, the lamp assembly 621 can be further configured within an enclosed space or smart lighting environment. When multiple users engage in human-focused lighting within this enclosed space, the enclosed space provides a space isolated from external environmental interference, allowing users to immerse themselves in their selected "light recipe" or "situational dynamic spectrum program." Furthermore, to more quickly achieve the desired human-focused lighting effect, contact-based physiological sensors can be installed on each user to measure their heart rate, blood pressure, pulse, blood oxygen concentration, or electrocardiogram (ECG) to determine whether they are achieving the desired mood. Furthermore, the vibration frequency, ambient temperature, and carbon dioxide concentration detected by the presence sensor 660 and ambient light sensor 650 within the smart lighting environment can be used for facial recognition. The carbon dioxide concentration, spectrum, light intensity, flicker rate, and color temperature can be transmitted via the AIIoT to the management control module 611 in the cloud 610 for calculation to determine whether the user has achieved the desired effect. Similarly, during the spectral illumination process, the "light recipe" of the multiple light scenes can be adjusted through the App on the mobile device used by the user 630 or the control module in the smart lighting field. For example, when the ambient light sensor 650 detects the influence of ambient light, the "light recipe" of the selected "situational dynamic spectrum program" can be adjusted. The adjustment methods include: time, longitude and latitude, brightness, flashing rate, etc. (please refer to the operation process of steps 540, 550, 570 and 580 shown in Figure 5 for details).

[0115] Next, Figure 6 discloses an embodiment of an intelligent human-centric lighting system 600A for commercial operations, which is applied to personal use. A user can use a portable communication device 630 to download a "light recipe" or "situational dynamic spectrum program" to a cloud 610 via the internet. The portable communication device 630 can then be used to activate a portable human-centric lighting device for human-centric lighting, creating an automatically adjustable intelligent human-centric lighting system. Specifically, once the user has worn the portable human-centric lighting device, the portable communication device 630 can be used to activate the lamp assembly 621 within the portable human-centric lighting device to provide human-centric lighting based on a specific "light recipe" or "situational dynamic spectrum program." The portable human-centric lighting device is a virtual device related to the metaverse, such as a virtual reality (VR), mixed reality (MX), or extended reality (XR) device, which allows a single user to receive human-centric lighting through a virtual device.

[0116] Furthermore, to enable the portable human-caused lighting device to achieve the desired effect more quickly, contact physiological sensors can be installed on the user to measure the user's heart rate, blood pressure, pulse, blood oxygen concentration, or electrocardiogram, thereby determining whether the user has achieved the desired mood. Similarly, during the spectrum illumination process, the "light recipe" of the multi-light scene can be adjusted through the app on the user's mobile device 630 or the control module 640 in the closed cavity (please refer to the operation process of steps 540, 550, 570, and 580 for details).

[0117] In a preferred embodiment, the configuration of the lamp assembly 621 can be customized based on the hardware service database of step 4510 and the software service database of step 4520. Finally, in the automatically adjustable intelligent human-centered lighting system of the present invention, the portable communication device 630 can be a smartphone, a tablet device, or a workstation. The portable communication device 630 can download an application (APP) containing intelligent human-centered lighting to the management and control module 611 via the Intelligent Internet of Things (AIoT). This APP allows the user to connect to the public cloud in the cloud 610 and select a desired "light recipe" or "dynamic spectrum program" from the public cloud for human-centered lighting. Furthermore, this APP allows the lamp assembly 621 to be remotely turned on or off via a short-range communication protocol, thereby controlling the spectrum to achieve the desired human-centered lighting effect. Among them, if the user confirms that the "light formula" or "situational dynamic spectrum program" has therapeutic effects, these "light formula" or "situational dynamic spectrum program" can be downloaded to the client's portable communication device 630. Afterwards, through the control module 640 configured on the client, the "light formula" or "situational dynamic spectrum program" can be directly activated to perform human-induced light therapy without going through the Internet connection process, allowing the user to quickly enter the human-induced light therapy program.

[0118] The aforementioned intelligent, automatically controllable human-centric lighting system builds a database of the brain's "blood oxygen concentration-dependent response to elevated levels." This database, through editing light recipes, creates a cloud-based database for multispectral lighting devices. This cloud database allows users to set desired emotional needs within the human-centric lighting system. The human-centric lighting system then determines or recommends a light recipe. This operational logic can be implemented in closed human-centric lighting devices, open intelligent lighting environments, and mobile human-centric lighting devices. Subsequently, as users experience light scenarios, the human-centric lighting system's algorithms assess their physiological and psychological states. If the emotional needs are not met, the system continuously updates the light recipe via wireless feedback signals. After readjusting the light recipe, it re-verifies whether the desired emotional needs are met. If the emotional needs are met, a human-centric lighting "light recipe" or "situational dynamic spectrum program" tailored to the user's emotional needs is provided, and the lighting process continues. Obviously, the intelligent human-caused lighting method and system disclosed in the present invention can achieve the human-caused lighting effect based on the brain's emotional needs in commercial promotion without the need for fMRI, thus benefiting more users.

[0119] Next, please refer to Figure 7, which further discloses the lighting fixture group control architecture of the intelligent human-centered lighting system of Figure 6 at the lighting field end of the present invention. First, as shown in Figure 7, the lighting field 620 of the intelligent human-centered lighting system 600 is an enclosed area or space. Several lighting fixture groups 621 may be configured within the lighting field 620. In this embodiment, the lighting fixture groups 621 are intelligent lighting fixture groups with communication capabilities (hereinafter referred to as intelligent lighting fixture groups). In this embodiment of the present invention, the intelligent lighting fixture group 6211 can be a single lighting fixture or a group consisting of multiple lighting fixtures. Next, ambient light sensors 650 are configured within the lighting field 620. The number of ambient light sensors 650 can be one or more, depending on the number of intelligent lighting fixture groups 621 configured. Each of these ambient light sensors 650 is equipped with a communication module, enabling pairing with the intelligent lighting fixture groups 621 via a communication protocol 801 such as Zigbee, Bluetooth, or Wi-Fi. The pairing described here refers to connecting an ambient light sensor 650 with a smart lamp group 621 through a communication protocol 801 such as Zigbee, Bluetooth or WIFI, so that the smart lamp group 621 can be controlled by the ambient light sensor 650 connected or paired with it to control its lighting spectrum, wherein the smart lamp group 621 can be composed of multiple smart lamps.

[0120] To further illustrate, in subsequent embodiments of the present invention, a single ambient light sensor 650 can be connected or paired with multiple smart lamp groups 621, enabling the single ambient light sensor 650 to control the lighting spectra of multiple smart lamp groups, as shown in Figure 8a. Figure 8a illustrates a configuration for controlling the lighting of smart lamp groups within a lighting field according to the present invention. Continuing with Figure 8a, multiple ambient light sensors (6501, 6503, 6505) are paired one-to-one with multiple smart lamp groups (6211, 6213, 6215). For example, a single ambient light sensor 6501 is connected or paired with a smart lamp group 6211, which consists of multiple lamps. Thus, a single ambient light sensor 6501 can control multiple smart lamps within the smart lamp group 6211 to emit the same "light recipe." Based on the foregoing, a preferred embodiment of the ambient light sensor 650 of the present invention is a sensing chip capable of providing constant illumination, comprising an illumination sensor and an LED driver circuit.

[0121] In another embodiment, multiple ambient light sensing modules (6511, 6513, 6515) can be connected or paired with multiple smart lighting groups (6211, 6213, 6215) via a communication protocol 801 such as Zigbee, Bluetooth, or WiFi, as shown in FIG8b , which is a schematic diagram of another configuration for controlling the lighting of a smart lighting group in a lighting field according to the present invention. Continuing with FIG8b , each ambient light sensing module (6511, 6513, 6515) is composed of multiple ambient light sensors. When multiple ambient light sensing modules (6511, 6513, 6515) are connected or paired with multiple smart lighting groups (6211, 6213, 6215), ideally, one ambient light sensor in each ambient light sensing module 6511 is paired with one smart lighting in one smart lighting group 621, allowing one ambient light sensor to control the lighting of one smart lighting group to the same "light recipe." Obviously, the present invention does not impose any limitation on the number of connections or pairings between the ambient light sensor 650 and the smart lamp group 621 .

[0122] Next, to facilitate user adjustment of the lighting parameters of the smart lighting set 621 within the lighting field 620, the present invention further provides a control panel 670 with a display function. The control panel 670 can be the user's mobile device 630 shown in FIG6 or the control module 640 disposed within the enclosed cavity. The control panel 670 can be disposed or fixed within the lighting field 620.

[0123] The control panel 670 in this embodiment has both display and communication functions. This communication function allows it to connect to the ambient light sensor 650, allowing the connection or pairing results between the ambient light sensor 650 and the smart light assembly 621 to be stored on the control panel 670. This allows the control panel 670 to control the lighting spectrum of the smart light assembly 621 via the ambient light sensor 650. Furthermore, the control panel 670 in this embodiment can also directly connect to or pair with the smart light assembly 621 via the communication function, allowing the control panel 670 to directly control the lighting spectrum of the smart light assembly 621 according to user needs. The connection or pairing between the control panel 670, the ambient light sensor 650, and the smart light assembly 621 is accomplished via a communication protocol 801, such as Zigbee, Bluetooth, or Wi-Fi, located within the enclosed space of the lighting field 620. Therefore, when the control panel 670 controls the smart lamp groups 621 to provide a lighting spectrum, this is also accomplished through a communication protocol 801 such as Zigbee, Bluetooth, or WiFi. As previously mentioned, the ambient light sensor 650 disclosed in the present invention is not only equipped with a communication module (not shown), but also further equipped with an illuminance detection module (not shown). Therefore, it is capable of monitoring the lighting environment conditions in the lighting field 620 and the spectrum, brightness, and illuminance of each smart lamp group 621. These detected lighting environment conditions can be transmitted to the control panel 670 via a communication protocol such as Zigbee, Bluetooth, or WiFi.

[0124] After the ambient light sensor 650, smart lighting assembly 621, and control panel 670 configured in the lighting field 620 have been paired via a communication protocol 801 such as Zigbee, Bluetooth, or WiFi, the present invention further discloses a method of using a user's mobile communication device as an interface device 630 between the cloud 610 and the lighting field 620. The interface device 630 includes a smartphone, a personal digital assistant (PDA), or a laptop computer. The interface device 630 can connect to a Software as a Service (SaaS) or Platform as a Service (PaaS) system program via an application (App) on the smartphone or laptop computer to pair and connect the interface device 630 with the ambient light sensor 650 and the control panel 670. This allows the user interface (UI) to be viewed through the interface device 630, and the user can control the lighting spectrum of the ambient light sensor 650 by operating the user interface (UI) of the interface device 630. The interface device 630, ambient light sensor 650, and control panel 670 can also be paired using Zigbee, Bluetooth, or Wi-Fi communication protocols 801. Therefore, when the ambient light sensor 650 detects ambient or background light, the interface device 630 or control panel 670 can adjust the selected "situational dynamic spectrum program" or "circadian rhythm-related settings" through the cloud 610. Adjustments include time, longitude and latitude, brightness, flashing rate, and other adjustments (see steps 540, 550, 570, and 580 in FIG5 for details). Both the interface device 630 and control panel 670 can communicate with the cloud 610 via the Artificial Intelligence of Things (AIoT). Clearly, within the control architecture of the lighting field 620, the intelligent human-centered lighting system of the present invention can control the smart lighting set 621 via a mobile phone 630, ambient light sensor 650, or monitoring panel 670, allowing users to easily operate or control the lighting in the field 620.

[0125] Next, please refer to Figure 9, which illustrates a control device with display and communication functions according to the present invention. As shown in Figure 9, first, in terms of appearance, the control panel 670 can be configured in a geometric shape. For example, this embodiment utilizes a rectangular structure, particularly one with a golden ratio (16:9), where the long side is 100mm to 150mm long. Next, a display 810 is located near the center of the control panel 670, displaying digital signals indicating the lighting parameters of the ambient light sensors 650 and the smart lighting fixture group 621 within the lighting field 620. Below the display 810, multiple operation buttons are located. Button 831 is an overview button that allows viewing the values ​​of all ambient light sensors 650 and also serves as a function key to switch parameters. Button 833 is a selection (or switching) button that sequentially displays dynamic information about the current ambient light detected by each ambient light sensor 650. Button 835 is a lighting parameter switching button that sequentially selects or switches to the lighting parameters the user desires to display, including information such as illuminance (lx), color temperature (CCT), color rendering index (Ra), equivalent blackout illuminance (EML), calorimetric intensity (CAF), and / or flicker rate (Flicker). Button 837 is an illuminance adjustment button that adjusts the illuminance of the smart lighting set 621 paired with the selected ambient light sensor 650. For example, button 837 can adjust the illuminance upward or downward. Button 839 is a color temperature adjustment button that adjusts the color temperature of the smart lighting set 621 paired with the selected ambient light sensor 650. For example, button 839 can adjust the color temperature upward or downward.

[0126] The calculation principle for the Equivalent Melanopic Lux (EML) is to multiply the vertical visual illuminance in a space by the ratio of the illuminant source. Therefore, Equivalent Melanopic Lux (EML) measures the level of light stimulation on the human circadian cycle in a given area. It is used to quantify the biological effects of light on humans and is one of the criteria recommended by the international WELL Building Standard for planning human-centric lighting. Therefore, different daily activities are suited to different EML values. For example, a high EML value is desirable during the day or when concentration is required, while a low EML value is desirable at night or when relaxation is desired. Therefore, after the intelligent human-centric lighting system 100 of the present invention is activated, the control panel 670 can reset the EML value based on the time of day. For example, the control panel 670 can set the maximum and minimum EML values ​​based on the time of day. When the EML value detected by the ambient light sensor 650 reaches the maximum and minimum values, the control panel 670 will generate a signal, including a different sound or displaying a different color screen. In an embodiment of the present invention, the indoor vertical visual EML value during daytime is set to 250-500, the indoor vertical visual EML value during dusk is set to 100-150, and the indoor vertical visual EML value during nighttime is set to 50-75.

[0127] Furthermore, the aforementioned Circadian Action Factor (CAF) is primarily calculated based on the illumination provided by the smart lighting assembly 621. It measures the level of stimulation a lighting provides to the human body. For example, a higher CAF value indicates a higher physiological stimulation, making people feel more alert. A lower CAF value indicates a lower stimulation, making people feel more relaxed. Therefore, the control panel 670 can set the CAF value based on the user's individual circadian rhythm. For example, between 9:00 AM and 11:00 AM, the control panel 670 can set a "light recipe" with a color temperature of 5700K and a CAF of 0.8. The control panel 670 can also set an upper limit (e.g., 1) and a lower limit (e.g., 0.6) for the CAF. Therefore, when the CAF value detected by the ambient light sensor 650 reaches the highest or lowest values, the control panel 670 will generate a signal, including a different sound or displaying a different color screen.

[0128] The obvious difference between CAF and EML is that the former measures the human stimulation of the light spectrum of the smart lamp set 621, while the latter measures the stimulation of the field. However, the two have one thing in common: higher values ​​indicate greater stimulation, which can boost spirits; lower values ​​indicate less stimulation, which can help relax the body and mind.

[0129] In addition, the multiple ambient light sensors (6501, 6503, 6505) or the multiple ambient light sensing modules (6511, 6513, 6515) in Figures 8a and 8b are paired with the control panel 670 via a communication protocol 801 such as Zigbee, Bluetooth, or WiFi. Therefore, after the control panel 670 downloads a specific "light recipe" from the cloud, it can transmit the "light recipe" to the ambient light sensors (6501, 6503, 6505) or the multiple ambient light sensing modules (6511, 6513, 6515) via a communication protocol 801 such as Zigbee, Bluetooth, or WiFi. Then, the ambient light sensors (6501, 6503, 6505) or the multiple ambient light sensing modules (6511, 6513, 6515) control the smart lighting group (6211, 6213, 6215) to provide lighting according to the "light recipe."

[0130] Because the intelligent human-centered lighting system 100 disclosed herein is a commercially viable system with practical applications, it must precisely control various lighting parameters within the lighting field 620, including at least information such as illuminance (lx), color temperature (CCT), color rendering index (Ra), equivalent blackout illuminance (EML), color irritation factor (CAF), flicker rate (Flicker), and / or illuminance uniformity. In particular, the EML and CAF within the lighting field 620 must be accurate to determine the effect of the user's "light recipe" on mood adjustment. Therefore, the present invention requires further monitoring of various background light sources within the lighting field 620, particularly light spilling into the space through building windows, to compensate for the impact of the target spectrum set within the lighting field 620, ensuring that the lighting field 620 maintains the set target spectrum.

[0131] Next, the present invention discloses an intelligent human-centered lighting system and method for automatically adjusting spatial lighting parameters. First, Figures 10a to 10d illustrate some embodiments of an external light source entering a space equipped with an intelligent human-centered lighting system. First, multiple ambient light sensors 650 are positioned within a space 620. Multiple openings 623 are located on one side of the space 620, allowing external light to enter the space 620. The openings 623 can be windows or doors. The external light can be sunlight during the day, moonlight at night, or neon lights. The intelligent human-centered lighting system 100 deployed within the space 620 can be the one shown in Figures 3, 6, or 7, but the present invention is not limited thereto. Furthermore, to clearly illustrate the intelligent human-centered lighting system and method for automatically adjusting spatial lighting parameters, the intelligent human-centered lighting system 600 shown in Figure 7 is used as an example.

[0132] First, Figure 10a shows multiple ambient light sensors 650 spaced apart within space 620. In one embodiment, the spacing between the multiple ambient light sensors 650 is uniform. Figures 10b and 10c build upon the structure of Figure 10a by further grouping the multiple ambient light sensors 650 spaced apart within space 620. In a preferred embodiment of Figure 10b , the multiple spaced apart ambient light sensors 650 are grouped horizontally (from left to right in the direction of the diagram). In a preferred embodiment of Figure 10c , the multiple spaced apart ambient light sensors 650 are grouped vertically (from top to bottom in the direction of the diagram). The purpose of grouping is to reduce the load on the control panel 670 by enabling parallel computation and control of the control panel 670 based on the number of groups, especially when space 620 is large and a large number of ambient light sensors 650 are deployed. In the embodiment shown in FIG10d , a spacer 625 is used to divide the space 620 into a plurality of sub-spaces of different sizes, wherein: sub-space 6210 and sub-space 6220 both have windows that allow external light to enter sub-space 6210 and sub-space 6220, while sub-space 6230 is a closed space that is not affected by external light. Its purpose is to reveal and deduce the light environment of various specific environments.

[0133] Next, please refer to Figure 11a, which illustrates a method for automatically adjusting spatial lighting parameters according to the present invention. First, as shown in step 1110, the ambient light sensing module 650 drives the smart lighting assembly 621 in the space 20 to illuminate. The lighting parameters used for illumination can be a preset light recipe, which can be retrieved by the ambient light sensing module 650 from the control panel 670. The preset light parameters may include information such as illuminance, color temperature, color rendering index (Ra), equivalent black level (EML), physiological stimulus value (CAF), flicker rate (Flicker), and / or illuminance uniformity.

[0134] Next, as shown in step 1120, the user sets the target lighting parameters for the space. In embodiments of the present invention, the target lighting parameters may include information such as illuminance, color temperature, color rendering index (Ra), equivalent black level (EML), luminance factor (CAF), flicker rate (Flicker), and / or illuminance uniformity. For example, when the user sets the "target parameters" for a work area to a color temperature of 5700K, illuminance, and CAF of 0.6 via the control panel 670, the ambient light sensor module 650 will drive the smart lamp assembly 621 to illuminate according to the "target parameters" of the "light recipe."

[0135] Next, as shown in step 1130, the ambient light sensing module 650 is driven to detect the ambient light in the space 20. For example, the control panel 670 drives the ambient light sensing module 650 to detect the ambient light environment in the space 20. The ambient light sensing module 650 detects the ambient light environment in the space 20 using the light detection module disposed therein. The detected lighting parameters include at least illuminance (lx) and color temperature (CCT). Because each ambient light sensing module 650 is located at a different location, the illuminance (lx) and color temperature (CCT) detected by each ambient light sensing module 650 will vary. In particular, as the space 20 becomes larger, the uneven illuminance (lx) and color temperature (CCT) at different locations becomes more severe. For example, in FIG10a , ambient light sensor module No. 1 measures illuminance = 800 and color temperature = 6200K, ambient light sensor module No. 2 measures illuminance = 400 and color temperature = 5500K, and ambient light sensor module No. 3 measures illuminance = 100 and color temperature = 5200K. It should be emphasized that the ambient light detection of the space 20 shown in step 1130 is continuous. Therefore, the light parameter values ​​detected by the ambient light sensor module 650 are recorded or stored according to a schedule and transmitted to the memory (not shown) of the control panel 670.

[0136] Next, as shown in step 1140, the ambient light detection values ​​are compared and determined to be consistent with the target parameter values. For example, the control panel 670 compares the actual ambient lighting parameter values ​​detected by each ambient light sensor module 650 with the set target parameters. If the control panel 670 determines that the preset lighting parameters detected by each ambient light sensor module 650 are consistent with the set target parameters, for example, when the illuminance and color temperature measured by ambient light sensor modules No. 1, No. 2, and No. 3 (6501, 6502, 6503) in FIG10a are consistent with the target parameters, the process proceeds to step 1150, where the smart lighting fixture groups 621 driven by the ambient light sensor modules 650 continue to provide lighting using the current lighting parameters, and the lighting is stored in the control panel 670. Furthermore, if the control panel 670 compares the preset lighting parameters detected by at least one ambient light sensor module 650 and the set target parameters, the process proceeds to step 1660, where the control panel 670 activates the ambient light sensor module to dim the smart lighting assembly. As previously mentioned, the ambient light sensor module 650 of the present invention is a constant-illuminance sensor chip. Therefore, during chip operation, it can continuously detect changes in lighting parameters in the space 620 and store them in a storage device.

[0137] The dimming process in step 1160 of the present invention is divided into three steps. First, as shown in step 1161, the ambient light sensor module 650 automatically adjusts the color temperature of the illumination according to the target parameters. For example, when the color temperature measured by ambient light sensor module 6501 is 6200K, ambient light sensor module 6501 gradually adjusts the illumination provided by its paired smart lamp group 621 to 5700K. Similarly, the illumination provided by the smart lamp groups 621 paired with ambient light sensor modules 6502 and 6503 is gradually adjusted to 5700K. It should be emphasized that, as shown in FIG. 10a , in the worst case scenario, when the color temperatures of all nine ambient light sensor modules differ from the color temperature set by the target parameters, the color temperature of each ambient light sensor module is adjusted to 5700K using either sequential or parallel processing, but the present invention is not limited thereto. The second step of the dimming process will not proceed until the control panel 670 confirms that the color temperature of each ambient light sensor module has been adjusted to 5700K. It should be noted that while this embodiment of the dimming process illustrates color temperature adjustment, it is not intended to limit the dimming process of the present invention to color temperature adjustment only. As previously mentioned, the preset light parameters of the present invention may include illuminance, color temperature, color rendering index (Ra), equivalent black level (EML), physiological stimulation value (CAF), light flicker rate (Flicker), and / or illuminance uniformity, all of which can be adjusted during the dimming process.

[0138] The second step, shown in step 1163, automatically adjusts the power parameters of the smart lamp group 621. The control panel 670 controls the power of the paired smart lamp group 621 based on the location of the ambient light sensor module 650. In this embodiment, pulse-width modulation (PWM) is used to control the power of the smart lamp group 621. For example, ambient light sensor module 6501 is closest to the window, so its background light is the brightest. Therefore, a lower power value can be applied, such as a 30% duty cycle for the paired smart lamp group 621. For another example, based on the location of ambient light sensor module 6502 from the window, a 50% duty cycle can be applied to the paired smart lamp group 621. For example, since ambient light sensor module 6503 number 3 is farthest from the window, a PWM duty cycle of 80% can be set for the smart lighting set 621 paired with ambient light sensor module 6503 number 3. Clearly, the present invention utilizes PWM dimming because it offers advantages such as no color shift, high dimming accuracy, digital dimming technology, a wide dimming range, and flicker-free operation. Furthermore, this step can achieve energy savings.

[0139] The third step, as shown in step 1165, is to automatically adjust the indoor illumination uniformity. This is based on the actual illumination detected by the ambient light sensor module 650, calculated using the illumination uniformity formula, and compared with the target illumination uniformity. If the illumination uniformity has reached the target value, then the process proceeds to step 1150, where the current illumination parameters are used to provide illumination and are stored in the memory of the control panel 670. The illumination uniformity calculation formula and example are as follows: Illumination uniformity = minimum illumination value / average illumination value [Equation 1]

[0140] For example, when the target illumination uniformity is set to 0.6, and the illuminations measured by the ambient light sensing modules No. 1, No. 2, and No. 3 in FIG10a are 800, 400, and 100, respectively, then the average illumination value measured by the ambient light sensing modules No. 1, No. 2, and No. 3 is

[0141] (800+400+100) / 3=433, then according to equation 1 we can get

[0142] Illumination uniformity = 100 / 433 = 0.23

[0143] When the ambient light sensing modules No. 1, No. 2, and No. 3 in Figure 10a are illuminated, the obtained illumination uniformity is 0.23, which obviously does not reach the target illumination uniformity setting value of 0.6. Therefore, it is necessary to adjust the illumination of the smart lamp group 621 paired with the ambient light sensing modules No. 1, No. 2, and No. 3. In a preferred embodiment of the present invention, when the actual illumination uniformity is lower than the target illumination uniformity, the smart lamp group 621 with the smallest illumination (that is, the smart lamp group 6503 farthest from the window) is the priority adjustment object. For example: the control panel 670 drives the smart lamp group 621 paired with the ambient light sensing module No. 3 to increase its illumination. For example, when the illumination of the smart lamp group 621 No. 3 is increased to 300, the average illumination value measured by the ambient light sensing modules No. 1, No. 2, and No. 3 is:

[0144] (800+400+300) / 3=500, then according to equation 1 we can get

[0145] Illumination uniformity = 300 / 500 = 0.6

[0146] When the adjusted illumination uniformity reaches the target illumination uniformity, the process proceeds to step 1150 , where illumination is provided with the current illumination parameters and stored in the memory.

[0147] Next, it should be further explained that after all nine ambient light sensing modules in Figure 10a are illuminated, the actual illumination uniformity should be calculated by substituting the illumination measured by the nine ambient light sensing modules into Equation 1. Regarding the nine ambient light sensing modules in Figure 10b , after the nine ambient light sensors are grouped into zones according to space 20, the average illumination value for each zone is first calculated. For example:

[0148] Ea area = (E1+E2+E3) / 3,

[0149] Eb area = (E4+E5+E6) / 3,

[0150] Ec area = (E7+E8+E9) / 3,

[0151] Then, the illumination uniformity is obtained according to Equation 1, where

[0152] The calculation formula for illumination uniformity in Figure 10b is as follows: Illumination uniformity = Min(Ea, Eb, Ec) / Avg(Ea, Eb, Ec) [Equation 2]

[0153] Finally, it is determined whether the illumination uniformity in FIG. 10 b is greater than the set target value.

[0154] For the nine ambient light sensing modules in FIG10c, the average illumination value of each partition is calculated first. For example:

[0155] Ea area = (E1+E4+E7) / 3,

[0156] Eb area = (E2+E5+E8) / 3,

[0157] Ec area = (E3 + E6 + E9) / 3

[0158] Since Ea, Eb, and Ec have different distances from the opening 623, they need to be weighted accordingly. Based on Equation 1, the formula for calculating illumination uniformity in FIG10c is as follows: Illumination Uniformity = Min(Ca*Ea, Cb*Eb, Cc*Ec) / Avg(Ca*Ea, Cb*Eb, Cc*Ec) [Equation 3]

[0159] Among them, Ca, Cb, and Cc are weight parameters. In a preferred embodiment of the present invention, the weight parameters can be, for example: Ca is between 0.25 and 0.5, Cb is between 0.5 and 0.75, and Cc is between 0.75 and 1.0.

[0160] Finally, it is determined whether the illumination uniformity in FIG. 10 c is greater than the set target value.

[0161] For another example, in the embodiment of FIG10 d , multiple sub-spaces of different sizes can be distinguished in one space 620 , but all of them can be calculated according to equation 1 in FIG10 c .

[0162] Finally, when the present invention completes the dimming process of step 1160, and all the dimmed lighting parameters are compared and confirmed to meet the target parameters in step 1140, it will go to step 1150, and continue to drive the smart lamp group 621 by the ambient light sensing module 650 to provide lighting with the current (and dimmed) lighting parameters, and store the current lighting parameters in the control panel 670.

[0163] Furthermore, it should be emphasized that, within the dimming process of step 1160 of the present invention, the step of automatically adjusting the power parameters of the smart lamp group 621 in step 1163 can be optionally incorporated into the dimming process. Implementing both steps 1163 and 1165 constitutes another preferred embodiment of the present invention. Furthermore, if the target illuminance parameter includes information such as equivalent blackout illuminance (EML) and a cardiac arrest factor (CAF), these information can be calculated based on the illuminance detected by the ambient light sensor 650.

[0164] Next, please refer to Figure 11b, which illustrates another method for automatically adjusting spatial lighting parameters according to the present invention. It should be noted that the difference between Figure 11b and Figure 11a lies in step 1121. As shown in step 1121, control panel 670 can set the equivalent blackout illuminance (EML) and circadian rhythm (CAF) values, based on daily time intervals, as target parameters for space 620. The difference between CAF and EML is that CAF measures the human stimulation of the light spectrum of smart lighting assembly 621, while EML measures the human stimulation of the field. However, the two methods share the same principle: higher values ​​result in higher stimulation, boosting spirits; lower values ​​result in lower stimulation, promoting relaxation. For example, maintain a CAF > 0.4 during daytime hours and < 0.1 after dusk. As for EML, the WELL Building Standard requires that the EML be between 200 and 250 during daytime activity and below 50 at dusk. Therefore, the present invention can use EML and CAF as target parameters.

[0165] In a preferred embodiment, a numerical database of CAF or EML parameters can be established in step 1125, and the CAF or EML target parameters in step 1121 can be automatically updated based on time intervals. Then, as shown in FIG11b, after the CAF or EML target parameters are updated, steps 1130 through 1165 are identical to the corresponding steps in FIG11a.

[0166] For example, during the morning hours of 9:00 AM, current intelligent human-centered lighting systems can already provide physiological target parameters for this time period, specifically color temperature adjusted to 5700K, CAF greater than 0.4, and EML reaching 0.65. Then, when the time period enters the 11:00 AM to 1:00 PM period, the new color temperature, CAF, or EML parameter database established in step 1125 is used to set target parameters, such as color temperature = 4000K, illuminance uniformity = 0.51, CAF maintained greater than 0.4, and EML maintained at 200. At this point, in step 1121, the control panel 670 activates the ambient light sensor 650 to illuminate according to the newly set target parameters. At this point, the system proceeds to step 1130, where the ambient light sensor 650 detects light in the room 20. In step 1140, the detected light parameters are compared with the newly set target parameters. Obviously, since the target parameters have been changed to the new target parameters, the dimming process in step 1160 must be continued. At this point, as shown in step 1161, the ambient light sensor module 650 will first gradually adjust the illumination provided by its paired smart lamp group 621 to 4000K. When the control panel 670 confirms that each smart lamp group 621 has adjusted its color temperature to 4000K, the process proceeds to step 1163, appropriately adjusting the power parameters of the smart lamp groups 621 based on the location of the ambient light sensor module 650. Step 1165 automatically adjusts the indoor illumination uniformity. Similarly, based on the illumination detected by the ambient light sensor module 650, after calculation using the illumination uniformity formula and comparing it to the target illumination uniformity, if the illumination uniformity has reached the target value, the process proceeds to step 1150, providing illumination using the current light parameters and storing them in memory. For example, if the illumination of smart lamp group 621 No. 1 is lowered to 250, the average illumination value measured by ambient light sensor modules No. 1, No. 2, and No. 3 is:

[0167] (800+400+250) / 3=483, then according to equation 1 we can get

[0168] Illumination uniformity = 250 / 483 = 0.52

[0169] When the adjusted illumination uniformity reaches the target illumination uniformity, the process proceeds to step 1150 , where illumination is provided with the current light parameters and stored in the memory.

[0170] Afterwards, when the time interval changes, step 1125 will again update the target parameters in step 1121 based on the parameter database such as color temperature, CAF, or EML, and then repeat steps 1130 to 1165, so that the present invention provides an intelligent human-centered lighting system with automatic adjustment of spatial lighting parameters.

[0171] Finally, we must once again emphasize that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Furthermore, the above description should be readily apparent to those skilled in the relevant art and should be readily applicable. Therefore, any equivalent changes or modifications that do not depart from the concepts disclosed herein are intended to be encompassed by the scope of the present invention.

Claims

1. A method for automatically adjusting the lighting parameters of a space, wherein a plurality of intelligent lamp groups, a plurality of ambient light sensing modules, a control panel and an interface device are arranged in the space, all of which are connected via a wireless communication protocol, wherein: The smart lamp group and the interface device are paired with the ambient light sensing module and the control module respectively through a wireless communication protocol, and the method is characterized in that: Driving the smart lamp group in the space to illuminate, the ambient light sensing module drives the smart lamp group in the space to illuminate with the illumination parameters of the preset light recipe; Setting the lighting target parameters in the space, wherein the user sets the lighting target parameters in the space through the control panel; The ambient light sensing module is driven to detect ambient light in the space, and the control panel is used to drive the ambient light sensing module to detect ambient light in the space, and the value of the ambient light detection is transmitted to the control module; Determine whether the ambient light detection value is the same as the target parameter, and compare the value of the lighting parameter detected in the actual environment with the set target parameter by the control panel; wherein, When it is determined that the value of the ambient light detection is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe; When it is determined that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes: The ambient light sensing module performs dimming according to the target parameter so that the value of the illumination parameter in the actual environment is the same as the set target parameter value; and The illumination uniformity of the space is adjusted by calculating the illumination uniformity formula based on the actual illumination detected by the ambient light sensing module and adjusting the illumination uniformity to a target illumination uniformity.

2. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: The interface device is paired with the ambient light sensor and the control panel through a system program of software as a service (SaaS) or platform as a service (PaaS).

3. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: The preset light parameters include: illumination, color temperature, color rendering index (Ra), equivalent black level (EML), physiological stimulation value (CAF), light flicker rate (Flicker) and / or illumination uniformity and other information.

4. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: When the value of the lighting parameter in the actual environment is the same as the set target parameter value, it further includes adjusting the power parameter of the smart lamp group, and the control panel controls the power value of the smart lamp group paired with it according to the position of the ambient light sensing module.

5. The method for automatically adjusting spatial lighting parameters according to claim 4, characterized in that: The power parameters of the smart lamp group are adjusted by pulse width modulation (PWM) to control the power of the smart lamp group.

6. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: The formula for illumination uniformity is: Illumination uniformity = minimum illumination value / average illumination value.

7. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: The plurality of ambient light sensors disposed in the space has a function of grouping the plurality of ambient light sensors.

8. The method for automatically adjusting spatial lighting parameters according to claim 7, wherein: When the ambient light sensors are grouped according to space partitions, the average illumination value of each partition is first calculated, and then the illumination uniformity formula is used for calculation.

9. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: When the ambient light sensors are grouped according to spatial partitions, the average illumination value of each partition is first calculated, and then different weight parameters are set according to the configuration of the grouped ambient light sensor positions, and then the illumination uniformity formula is used for calculation.

10. The method for automatically adjusting spatial lighting parameters according to claim 1, wherein: The control module and the interface device are further connected to the cloud via an intelligent Internet of Things.

11. A method for automatically adjusting the lighting parameters of a space, wherein a plurality of intelligent lamp groups, a plurality of ambient light sensing modules, a control panel and an interface device are arranged in the space, all of which are connected via a wireless communication protocol, wherein: The smart lamp group and the interface device are paired with the ambient light sensing module and the control module respectively through a wireless communication protocol, and the control module and the interface device are connected to the cloud through an intelligent Internet of Things. The method is characterized in that: Driving the smart lamp group in the space to illuminate, the ambient light sensing module drives the smart lamp group in the space to illuminate with the illumination parameters of the preset light recipe; Set the lighting target parameters in the space. The control panel sets the equivalent black light illuminance (EML) and physiological stimulation value (CAF) of the human circadian rhythm according to the daily time interval as the target parameters set in the space; The ambient light sensing module is driven to detect ambient light in the space, and the control panel is used to drive the ambient light sensing module to detect ambient light in the space, and the value of the ambient light detection is transmitted to the control module; Determine whether the ambient light detection value is the same as the target parameter, and compare the value of the lighting parameter detected in the actual environment with the set target parameter by the control panel; wherein, When it is determined that the value of the ambient light detection is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe; When it is determined that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes: The ambient light sensing module adjusts the light according to the target parameter so that the value of the lighting parameter in the actual environment is the same as the set target parameter value; The illumination uniformity of the space is adjusted by calculating the illumination uniformity formula based on the actual illumination detected by the ambient light sensing module and adjusting the illumination uniformity to a target illumination uniformity.

12. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: The interface device is paired with the ambient light sensor and the control panel through a system program of software as a service (SaaS) or platform as a service (PaaS).

13. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: The preset light parameters include: illumination, color temperature, color rendering index (Ra), equivalent black level (EML), physiological stimulation value (CAF), light flicker rate (Flicker) and / or illumination uniformity and other information.

14. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: A numerical database of CAF or EML parameters is established, and CAF or EML target parameters are automatically changed according to time intervals.

15. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: When the value of the lighting parameter in the actual environment is the same as the set target parameter value, it further includes adjusting the power parameter of the smart lamp group, and the control panel controls the power value of the smart lamp group paired with it according to the position of the ambient light sensing module.

16. The method for automatically adjusting spatial lighting parameters according to claim 15, wherein: The power parameters of the smart lamp group are adjusted by pulse width modulation (PWM) to control the power of the smart lamp group.

17. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: The formula for illumination uniformity is: Illumination uniformity = minimum illumination value / average illumination value.

18. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: The plurality of ambient light sensors disposed in the space has a function of grouping the plurality of ambient light sensors.

19. The method for automatically adjusting spatial lighting parameters according to claim 18, wherein: When the ambient light sensors are grouped according to space partitions, the average illumination value of each partition is first calculated, and then the illumination uniformity formula is used for calculation.

20. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: When the ambient light sensors are grouped according to spatial partitions, the average illumination value of each partition is first calculated, and then different weight parameters are set according to the configuration of the grouped ambient light sensor positions, and then the illumination uniformity formula is used for calculation.

21. The method for automatically adjusting spatial lighting parameters according to claim 11, wherein: The control module and the interface device are further connected to the cloud via an intelligent Internet of Things.

22. A system for automatically adjusting lighting parameters of a space, wherein a plurality of smart lamp groups, a plurality of ambient light sensing modules, a control panel and an interface device are arranged in the space, all of which are connected via wireless communication, wherein the smart lamp groups and the interface device are paired with the ambient light sensing module and the control module respectively via a wireless communication protocol, wherein the system is characterized in that: The control panel is used to set the lighting target parameters in the space and drive the ambient light sensing module to control the smart lamp group in the space to perform lighting according to the lighting parameters of the preset light recipe; The control panel compares the value of the illumination parameter in the actual environment detected by the ambient light sensing module with the set target parameter; wherein, When the control panel determines that the value of the ambient light detection is the same as the target parameter value, the ambient light sensing module continues to drive the smart lamp group to illuminate with the lighting parameters of the preset light recipe; When the control panel determines that the value of the ambient light detection is different from the target parameter value, the control panel drives the ambient light sensing module to perform a dimming procedure on the smart lamp group, wherein the dimming procedure includes: The ambient light sensing module performs dimming according to the target parameter so that the value of the illumination parameter in the actual environment is the same as the set target parameter value; and The illumination uniformity of the space is adjusted by calculating the illumination uniformity formula based on the actual illumination detected by the ambient light sensing module and adjusting the illumination uniformity to a target illumination uniformity.

23. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: The interface device is paired with the ambient light sensor and the control panel through a system program of software as a service (SaaS) or platform as a service (PaaS).

24. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: The preset light parameters include: illumination, color temperature, color rendering index (Ra), equivalent black level (EML), physiological stimulation value (CAF), light flicker rate (Flicker) and / or illumination uniformity and other information.

25. The system for automatically adjusting spatial lighting parameters as claimed in claim 24, characterized in that: The preset equivalent black illuminance (EML) and physiological stimulation value (CAF) are used to establish a numerical database of CAF or EML parameters, and automatically change the CAF or EML target parameters according to the time interval.

26. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: When the value of the lighting parameter in the actual environment is the same as the set target parameter value, it further includes adjusting the power parameter of the smart lamp group, and the control panel controls the power value of the smart lamp group paired with it according to the position of the ambient light sensing module.

27. The system for automatically adjusting spatial lighting parameters as claimed in claim 26, characterized in that: The power parameters of the smart lamp group are adjusted by pulse width modulation (PWM) to control the power of the smart lamp group.

28. The method for automatically adjusting spatial lighting parameters as claimed in claim 22, wherein: The formula for illumination uniformity is: Illumination uniformity = minimum illumination value / average illumination value.

29. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: The plurality of ambient light sensors disposed in the space has a function of grouping the plurality of ambient light sensors.

30. The system for automatically adjusting spatial lighting parameters as claimed in claim 29, characterized in that: When the ambient light sensors are grouped according to space partitions, the average illumination value of each partition is first calculated, and then the illumination uniformity formula is used for calculation.

31. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: When the ambient light sensors are grouped according to spatial partitions, the average illumination value of each partition is first calculated, and then different weight parameters are set according to the configuration of the grouped ambient light sensor positions, and then the illumination uniformity formula is used for calculation.

32. The system for automatically adjusting spatial lighting parameters as claimed in claim 22, characterized in that: The control module and the interface device are further connected to the cloud via an intelligent Internet of Things.

Images