Intelligent human-factor lighting method and system

Abstract

The present invention provides an intelligent human-centric lighting system, comprising a client, an intelligent lighting terminal, and an ambient light sensor. The client uses a portable communication device to download a specific spectral recipe or a contextual dynamic spectral program from the cloud via the internet. The intelligent lighting terminal is equipped with a lamp group, which provides multi-spectral human-centric lighting to multiple users within the intelligent lighting terminal based on the specific spectral recipe or contextual dynamic spectral program. The ambient light sensor, configured within the intelligent lighting terminal, provides ambient light parameters within the intelligent lighting terminal's environment. The client adjusts the optical signal parameters within the specific spectral recipe or contextual dynamic spectral program based on the ambient light parameters.

Description

Technical Field

[0001] The present invention provides an intelligent human-centric lighting method, and more particularly, relates to an intelligent human-centric lighting method that uses physiological signal measurements of the human body as emotional judgment to adjust the luminous spectrum. 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 can be 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 recorded 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. Summary of the Invention

[0005] Based on the above description, the present invention provides an application of an electroencephalogram (EEG) brain wave pattern as human-induced lighting in a commercial system after establishing a correlation with the blood oxygen concentration dependent contrast (BOLD) of a functional magnetic resonance imaging system (fMRI).

[0006] The present invention first provides an intelligent human-centric lighting system, characterized by comprising a client, a smart lighting terminal, and an environment terminal. The client uses a portable communication device to download a specific spectral recipe or a contextual dynamic spectral program from the cloud via the internet. The smart lighting terminal is equipped with a lamp group that provides multi-spectral human-centric lighting to multiple users located within the smart lighting terminal based on the specific spectral recipe or contextual dynamic spectral program. An ambient light sensor, configured within the smart lighting terminal, provides ambient light parameters within the smart lighting terminal's environment. The client adjusts the optical signal parameters within the specific spectral recipe or contextual dynamic spectral program based on the ambient light parameters.

[0007] This invention provides a process for establishing various "spectral recipes" and a database for establishing "human-centric lighting parameter adjustment" services. The databases for the hardware and software services required for establishing "human-centric lighting parameter adjustment" are all built on a light environment "sharing platform." It is particularly important to note that the resulting "sharing platform" is capable of providing effective "situational dynamic spectrum programs" that combine spectrums for multiple light scenes and multiple moods. This shared platform can then be used to provide various commercial services and operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1a This is the original data collection framework of the present invention on the physiological and emotional responses of people to light;

[0009] Figure 1b This is a flow chart for collecting original data on human physiological and emotional responses to light exposure according to the present invention;

[0010] Figure 1c This is the process of judging the human response to specific physiological emotions due to illumination in the present invention;

[0011] Figure 2a The present invention is a method for establishing a brain wave graph of a person's physiological and emotional response to light exposure;

[0012] Figure 2b The present invention constructs a lighting database for users to perform effective human factors lighting;

[0013] Figure 3 This is a system architecture diagram of the intelligent human-centered lighting system of the present invention;

[0014] Figure 4 This is a method of the present invention for constructing a human-induced lighting environment sharing platform;

[0015] Figure 5a This is an automatically adjustable intelligent human-factor lighting method of the present invention;

[0016] Figure 5b This is the editing process of the contextual dynamic spectrum editing platform of the present invention;

[0017] Figure 5c It is a situational dynamic spectrum program with conference function of the present invention; and

[0018] Figure 6 The invention is an intelligent human-factor lighting system applied to commercial operations. DETAILED DESCRIPTION

[0019] In the following description of this invention, the functional magnetic resonance imaging system is referred to as the "fMRI system," the electroencephalogram is referred to as the "EEG," and the blood oxygen concentration-dependent contrast is referred to as "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 those skilled in the art, relevant 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.

[0020] The present invention uses an fMRI system and physiological signal measurement methods to understand the correspondence between light spectrum and emotion in the brain, thereby establishing 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, the present invention further uses electroencephalography (EEG) to record brain wave changes and establish a correlation between the two. This approach aims to replace the fMRI system's emotional judgment with brain wave changes recorded by the EEG.

[0021] 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 the "effective color temperature" and the EEG (electroencephalogram) records the brainwave pattern under the "effective color temperature" stimulation. Once a correlation is established between the specific EEG brainwave pattern and the specific BOLD response, the specific EEG brainwave pattern can be used to assist in determining the user's emotional changes. This allows the construction of a commercially viable human-factor lighting system and method, thereby eliminating the need to use expensive fMRI systems to implement human-factor lighting systems, reducing operating costs, and further meeting customized service needs.

[0022] First, please refer to Figure 1a , is the original data collection framework of the present invention on the physiological and emotional response of people to light. Figure 1a As shown, the intelligent human-centered lighting system 100 is activated in an environment (e.g., a test space) equipped with various adjustable lighting modules, providing variable light signal parameters such as spectrum, light intensity, flicker rate, and color temperature. The present invention utilizes an fMRI-compatible image interaction platform 110, developed by an fMRI system, to target different target emotions. This platform uses voice and image guidance, along with a specific effective spectrum for 40 seconds of stimulation. By observing changes in the blood oxygen level in the brain, the researchers verify whether the "effective color temperature" can significantly induce emotional responses in the subjects. This is explained in detail below.

[0023] Next, please refer to Figure 1b and Figure 1c ,in Figure 1b This is a flow chart of the original data collection of the physiological and emotional response of people to light. Figure 1c It is the process of judging people’s specific physiological and emotional reactions to light. Figure 1b As shown in step 1100, each subject is already on the compatible image interaction platform 110. Next, each subject is guided through known images to experience various emotional stimulations. Subsequently, as shown in step 1200, the compatible image interaction platform 110 records the BOLD responses in the subject's brain to various emotions after being stimulated by the images. Next, as shown in step 1300, visual stimulation is provided to the subject by illuminating the subject with light to provide spectra with different color temperature parameters. For example, LED lamps are used in conjunction with electronic dimmers to provide spectra with different color temperature parameters. In an embodiment of the present invention, nine sets of visual stimulations with different color temperatures are provided: 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K. After each 40-second period of effective light exposure and stimulation, the subject can be given one minute of ineffective light (full-spectrum, flicker-free white light) to achieve emotional relaxation. Furthermore, the test subject may be given a 40-second counter-effect light stimulus to observe whether the area that responded to the original effective light stimulus has a reduced response. In the embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of a specific emotion in the brain of the test subject after being stimulated by the picture, the test subject is visually stimulated by providing spectra with different color temperature parameters, such as Figure 1c As shown in step 1310, 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 tester.

[0024] 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.

[0025] Table 1

[0026]

[0027]

[0028] The compatible image interaction platform 110 records the BOLD response results in specific brain regions. The response results are determined by calculating the area size of the emotional response sites when there are more limbic systems with BOLD emotional responses in the brain region. For example, the larger the area with BOLD emotional response, the stronger the response to a specific physiological emotion. In the embodiment of the present invention, Figure 1c Step 1410 in the image processing system records the BOLD response after exposure to a spectrum with a color temperature of 3000K. Next, step 1420 records the BOLD response after exposure to a spectrum with a color temperature of 4000K. Finally, step 1430 records the BOLD response after exposure to a spectrum with a color temperature of 5700K. After the subject underwent the light exposure procedure to induce excitement, the compatible image interaction platform 110 recorded the BOLD response in specific brain regions, as shown in Table 2.

[0029] Table 2

[0030]

[0031] Among them, after the test subject went through the light exposure procedure after the happiness emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 3.

[0032] Table 3

[0033]

[0034]

[0035] Among them, after the test subject went through the light exposure procedure after the amusement emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 4.

[0036] Table 4

[0037]

[0038] 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 1 through 3. 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.

[0039] As shown in step 1510, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure, the maximum reaction value is calculated. For example, according to the record in Table 2, the total score of 3000K (577) is subtracted from the total score of 4000K (226), resulting in 351. Then, the total score of 3000K (577) is subtracted from the total score of 5700K (-105), resulting in 682. The total reaction value score under 3000K illumination after the excitement emotion is induced is 1033.

[0040] Then, if Figure 1c In step 1520, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the lighting procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score of 4000K (226) is subtracted from the total score of 3000K (577), and the result is -351. Then, the total score of 4000K (266) is subtracted from the total score of 5700K (-105), and the result is 371.

[0041] Then, if Figure 1c In step 1530, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the lighting procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score of 5700K (-105) is subtracted from the total score of 3000K (577), resulting in -682. Then, the total score of 5700K (-105) is subtracted from the total score of 4000K (-105), resulting in 371.

[0042] 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 and joy, different "effective color temperatures" can be obtained using the calculations from steps 1510 to 1530, as shown in Table 5.

[0043] Table 5

[0044] Physiological emotions Effective color temperature Excitement 3000K Happiness 4000K Amusement 5700K

[0045] Next, based on the statistical results in Table 5, 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." For example, an effective color temperature of 4000K can represent the fMRI system's "enhancement spectrum" for the emotion of "happiness." For example, an effective color temperature of 5700K can represent the fMRI system's "enhancement spectrum" for the emotion of "pleasure."

[0046] Finally, as shown in step 1600, an "enhancement spectrum" database corresponding to the effects of specific emotions can be established within the fMRI system. The subject is stimulated using the aforementioned human-induced lighting parameters, and the fMRI system observes and records the BOLD response of the subject's brain during the illumination. Simultaneously, the fMRI brain images are used to determine which part of the brain experiences an additive "blood oxygen concentration dependency" response to the illumination. This allows a specific effective color temperature to be considered the fMRI enhancement spectrum of the 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 5, the present invention objectively infers the subject's "enhancement spectrum" for specific physiological emotions. This "enhancement spectrum" serves as evidence of 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).

[0047] It should be emphasized that the present invention Figure 1b and Figure 1cIn the entire implementation process, 100 testers were subjected to complete tests on multiple specific emotions, and the statistical results in Table 5 were obtained. For example: in terms of excitement, providing an effective color temperature of 3000K as the "enhanced spectrum" under the physiological emotional response of excitement can make the tester's excitement produce a physiological emotional response with the strongest additive effect. For example: in terms of happiness, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotional response of happiness can make the tester's happiness produce a physiological emotional response with the strongest additive effect. For another example: in terms of pleasure, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotional response of pleasure can make the tester's pleasure produce a physiological emotional response with the strongest additive effect.

[0048] In addition, it should be emphasized that the above three color temperatures are only used as examples of the present invention, and do not limit the use of these three color temperatures as the "enhanced spectrum" for the three physiological emotional responses. In fact, after the color temperature of 2000K, each 100K increase can be used as an interval to enhance different emotions (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness or neutrality, etc.). Figure 1b and Figure 1c Therefore, Table 5 of the present invention only discloses part of the results and is not intended to limit the present invention to these three embodiments.

[0049] Next, the present invention aims to establish an artificial intelligence model for the correlation between brain waves and brain images associated with 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 electroencephalogram (EEG). In the following embodiment, an EEG 130 is used to establish a person's physiological emotional response to lighting. 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.

[0050] Please refer to Figure 2a , is a method of establishing a human brain wave graph of physiological emotional response to light exposure. Figure 2aAs shown, the present invention is a method for establishing human-induced lighting responses to physiological emotions using an electroencephalograph 130. The method includes the following steps: First, as shown in step 2100, the "enhanced spectrum" database information in Table 5 is also stored in the memory of the electroencephalograph 130. Next, as shown in step 2200, the subject wears the electroencephalograph and is guided through various emotional stimulations using elements from known images or videos. Next, as shown in step 2300, the intelligent human-induced lighting system 100 is activated and provides variable light signal parameters such as spectrum, light intensity, flicker rate, and color temperature to stimulate the subject. The electroencephalograph 130 then records the brainwave files of the subjects after exposure to light of 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 files of the subject's specific emotions during the excitement stimulation and after the light stimulation at different color temperatures are recorded and stored in the memory of the electroencephalograph 130. In this embodiment of the present invention, EEG files of 100 subjects after the specific emotional stimulation and light stimulation have been recorded, thus requiring a larger memory.

[0051] Next, as shown in step 2400, the EEG files representing specific emotions (e.g., excitement, happiness, and joy) stored in the EEG device 130's memory are learned through artificial intelligence learning. Since the EEG device 130 can only store brainwave waveforms, the EEG files currently stored in the EEG device 130's memory are EEG files 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 have different EEG files generated 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 information from the "enhanced spectrum" database to classify EEG files related to specific emotions. For example, for EEG files related to excitement, only EEG files from different test subjects at a color temperature of 3000K are grouped together. For another example, for EEG files related to happiness, only EEG files from different test subjects at a color temperature of 4000K are grouped together. For another example, for EEG files related to pleasure, only EEG files from different test subjects at a color temperature of 5700K are grouped together. The EEG device 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.

[0052] 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 among EEG file groups for specific emotions. For example, when learning and training a group of EEG file groups with a color temperature of 3000K, the learning and training is performed by statistically analyzing, calculating, and comparing the ranking of the EEG file groups with the highest similarity and the ranking of the EEG file groups with the lowest similarity among the EEG file groups with a color temperature of 3000K, thereby ranking the EEG file groups with the highest similarity and the ranking of the EEG file groups with the lowest similarity. For example, the EEG file groups with the highest similarity can be considered the EEG file groups with the strongest emotion, while the EEG file groups with the lowest similarity can be considered the EEG file groups with the weakest emotion. The EEG file groups with the strongest emotion can be used as the "target value," while the EEG file groups with the weakest emotion can be used as the "starting value." For ease of explanation, the most similar EEG file group is used as the "target value," while the least similar EEG file group is used as the "starting value." Different scores are assigned to these groups, 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 file for the happy emotion level at the 4000K color temperature category and the EEG file for the surprised emotion level at the 5700K color temperature category. The "starting value" and "target value" can be set to form a similarity score range.

[0053] Afterwards, as shown in step 2500, an artificial intelligence EEG classification and grading database (which may be referred to as an artificial intelligence EEG file database) is established. After step 2400, the EEG file groups of various specific color temperatures are given "target value" scores and "starting value" scores to form a database with grading results, which is stored in the memory of the electroencephalograph 130. The purpose of the present invention in establishing an EEG classification and grading database in step 2500 is to obtain the EEG file of an unknown tester after the unknown tester receives specific emotional stimulation and is given light of a specific color temperature, and then compare the EEG file of the unknown tester with the EEG file similarity score interval in the database, so as to judge or infer the current congestion reaction condition in the brain of the unknown tester. The detailed process is as follows. Figure 2b shown.

[0054] Next, please refer to Figure 2b , is the lighting database for users to conduct effective human-factor lighting. First, as shown in step 3100, the tester wears the electroencephalograph 130 and is asked to watch pictures that induce specific emotions. Then, as shown in step 3200, the human-factor lighting system 100 is started in an environment (e.g., a test space) that has been equipped with various adjustable multi-spectral lighting modules. Through the management control module 611 (e.g., Figure 3Then, as shown in step 3300, the EEG file of the test subject after the emotion induction and light exposure is obtained and stored in the memory module 617 of the cloud 610 (as shown in step 3300). Figure 3 Then, 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 will set a score to determine whether the similarity is sufficient. For example, when the similarity score is set to 75 points or above, it means that the tester's brain congestion reaction is sufficient. Then, as shown in step 3500, the management and control module 611 will compare the similarity of the tester's EEG file and the artificial intelligence EEG file. For example, when the similarity score after the comparison of the tester's EEG file is 90 points, the management and control module 611 will immediately determine that the tester's brain congestion reaction is very sufficient, so it will proceed to step 3600 to terminate the human factor lighting test for a specific emotion. Then, step 3700 is performed to record the human factor lighting parameters when the tester's brain congestion reaction has reached the stimulation level into a database and store it in the memory module 617.

[0055] Then, in Figure 2b In step 3500, if the similarity score after comparing the subject's EEG file with the artificial intelligence EEG file is 35, the management and control module 611 will determine that the subject's brain hyperemia response is insufficient and will proceed to step 3800. The management and control module 611 will continue to strengthen the human-factor illumination test, including providing appropriate increases in illumination time or intensity based on the similarity score. Then, step 3300 is repeated to obtain the EEG file after the increased illumination time or intensity. The human-factor illumination test will not be terminated until the similarity score reaches a set similarity score of 75 or above, proceeding through step 3400. If the management and control module 611 determines that the subject's brain hyperemia response has reached a stimulation level, a human-factor illumination parameter data file will be 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.

[0056] 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 EEG file interpretation results from the electroencephalograph 130. Therefore, it eliminates the need for expensive fMRI systems and can infer physiological and emotional changes in brain images based on the artificial intelligence model of the "Human Factor Lighting Parameter Database." 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 further stored in an internal private cloud 6151 within the cloud 610.

[0057] Next, please refer to Figure 3 , is a system architecture diagram of the intelligent human factor lighting system 600 of the present invention. Figure 3As shown, the overall architecture of the intelligent human-centered lighting system 600 of the present invention can be divided into three modules: a cloud 610, a lighting field end 620, and a client 630. These three modules are connected via the internet, so they can be located in different regions or even co-located. The cloud 610 further includes a management and control module 611, which is used for cloud computing, cloud environment construction, cloud management, and the use of cloud computing resources. Users can also access, construct, or modify the content within each module through the management and control module 611. A consumption module 613, connected to the management and control module 611, serves as a cloud service for users to subscribe to and consume. Therefore, the consumption module 613 can access each module within the cloud 610. A cloud environment module 615, connected to the management and control module 611 and the consumption module 613, divides the cloud backend environment into an internal private cloud 6151, an external private cloud 6153, and a public cloud 6155 (e.g., a commercial cloud), providing interfaces for external or internal services for system providers or users. The memory module 617 is connected to the management and control module 611 and serves as a storage area for the cloud backend. The technical content required to be implemented by each module in the present invention will be described in detail in subsequent embodiments. The lighting field terminal 620 can communicate with the cloud 610 or the client 630 via the Internet. The lighting field terminal 620 is configured with a lamp assembly 621 consisting of multiple light-emitting devices. The client 630 can also communicate with the cloud 610 or the lighting field terminal 620 via the Internet. The client 630 of the present invention includes general users and editors who use the intelligent human-based lighting system 600 of the present invention for various business operations. Representative devices or apparatuses of the client 630 can be fixed devices with computing capabilities or portable intelligent communication devices. In the following description, users, creators, editors, or portable communication devices can all represent the client 630. Furthermore, in the present invention, the Internet can be an intelligent Internet of Things (AIoT).

[0058] Please refer to Figure 4 , is a method 400 of constructing a lighting environment sharing platform of the present invention. Figure 4 In the process of Figure 3The intelligent human-centered lighting system 600 includes multiple light-emitting devices 621 providing different light spectra, which may be an LED lamp assembly. The present invention specifically emphasizes that the LED lamp assembly can selectively modulate the voltage or current of individual LED lamps to produce a multi-spectral combination with a specific color temperature, thereby providing multi-spectral illumination. Of course, the present invention can also utilize multiple LED lamps with specific emission spectra, providing a fixed voltage or current to cause each energized LED lamp to emit its specific spectrum, thereby producing a multi-spectral combination with a specific color temperature. Furthermore, it should be emphasized that the light-emitting devices 621 with different spectra described in the present invention are based on the need for the actual lighting process to emit different spectra via multiple light-emitting devices 621. Therefore, the light-emitting devices 621 with different spectra can be composed of light-emitting devices with different spectra, or they can be multiple identical light-emitting devices whose emitted spectra can be modulated to different spectra by power provided by a control device. Therefore, the present invention is not limited to the above implementation of the light-emitting device 621 with different spectra, and of course also includes light-emitting devices with different spectra formed by other methods.

[0059] 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 different color temperatures can stimulate people (or users) with corresponding emotions. For example, a specific color temperature can stimulate a specific emotion with a synergistic effect.

[0060] 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 different color temperatures can stimulate people (or users) with corresponding emotions. For example, a specific color temperature can stimulate a specific emotion with a synergistic effect.

[0061] Next, as shown in step 411, a cloud database of light scenes of a multi-spectral lighting device is constructed. Since each color temperature can be combined through different multiple spectra, that is to say, the same color temperature can be obtained by different multi-spectral combinations. For example, when we want to establish a spectrum that can provide a 4000K color temperature, we can choose a multi-spectral combination of Maldives at a color temperature of 4000K, or a multi-spectral combination of Bali, Thailand at a color temperature of 4000K, or further choose a multi-spectral combination of Monaco Beach at a color temperature of 4000K. Obviously, these multi-spectral combinations with a color temperature of 4000K have different multi-spectral combinations based on their geographical location (including: longitude and latitude), time / brightness / flicker rate and other factors. Therefore, in step 411, based on the relationship between color temperature and corresponding emotions in the "human-centric lighting parameter database," different multispectral combinations at specific color temperatures at different geographic locations on Earth can be collected through the cloud 610. For example, different multispectral combinations at a color temperature of 4000K at different geographic locations on Earth can be collected (e.g., 4000K color temperature at different longitudes and latitudes), or different multispectral combinations at a color temperature of 4000K at different times on Earth (e.g., 4000K color temperature at 9:00 AM). These collected multispectral combinations at specific color temperatures at different geographic locations on Earth are then stored in the memory module 617. Under the control of the management and control module 611 in the intelligent human-centric lighting system 600, the parameters of various multispectral combinations at specific color temperatures (i.e., at different geographic locations or at different times at different geographic locations) can be adjusted by controlling the multiple light-emitting devices 621. After storage in the memory module 617, the intelligent human-centric lighting system 600 of the present invention constructs a "multispectral lighting device cloud database" of multispectral combinations at various color temperatures at different geographic locations. Clearly, the "multi-spectral lighting device cloud database" constructed in step 411 is the result of adjustments made using multiple light-emitting devices 621 with different spectra. Furthermore, it should be emphasized that, having understood how specific color temperatures can have a stimulating effect on specific emotions, the present invention can, in addition to creating multi-spectral combinations based on different geographic locations, also utilize artificial intelligence to synthesize or combine multi-spectral combinations that differ from actual geographic locations, taking into account factors such as latitude and longitude, time, brightness, and flicker rate. This is not a limitation of the present invention. Clearly, in step 411, the present invention has already constructed a light scene database comprising multiple multi-spectral lighting devices. Therefore, based on this constructed database of different light scenes, the intelligent human-centered lighting system 600 can provide multi-spectral lighting services at different color temperatures using multi-spectral lighting devices.At this point, the "multi-spectral light emitting device cloud database" constructed in step 411 can be stored in the memory module 617 or the internal private cloud 6151 or the public cloud 6155 (eg, a commercial cloud).

[0062] As shown in step 430, the effectiveness of the multi-spectral combination illumination is determined. Because the effects of human-centric lighting spectrum on emotional stimulation or influence may vary among different users, the illumination spectrum of the multi-spectral combination needs to be adjusted. Next, when user 630 accesses the intelligent human-centric lighting system 600 of the present invention, they can select the desired emotion from the "multi-spectral lighting device cloud database" in the memory module 617, the internal private cloud 6151, or the public cloud 6155 through the management and control module 611. The management and control module 611 then selects a default multi-spectral combination from the memory module 617, the internal private cloud 6151, or the public cloud 6155. The management and control module 611 then controls multiple light devices 621 with different spectra to adjust the multi-spectral combination to achieve the desired emotion, and then uses this adjusted multi-spectral combination to illuminate the user. For example, if the user wants to adjust their mood to happiness or joy, a color temperature of 4000K can be selected based on the "human-centric lighting parameter database." At this point, the user can select the default multispectral combination provided by the "Multispectral Lighting Device Cloud Database" or choose a multispectral combination that provides a color temperature of 4000K. Of course, the user can also select a specific multispectral combination that is widely used for illumination. In this case, when the user uses the multispectral combination provided by the human factor lighting system 600 in the "Multispectral Lighting Device Cloud Database", the present invention refers to it as the default multispectral combination.

[0063] Next, as shown in step 430, when the user selects a multi-spectral combination preset for a happy or pleasant emotion (for example, the system defaults to the Maldives multi-spectral combination at a color temperature of 4000K), and a lighting program is performed using the multi-spectral combination adjusted by multiple light-emitting devices 621 with different spectra, for example, after 15 minutes of lighting, the user can determine or evaluate whether the multi-spectral combination illumination has effectively achieved a happy or pleasant emotion. The user can determine or evaluate whether the multi-spectral combination illumination has effectively achieved a happy or pleasant emotion based on their own feelings.

[0064] Continuing with step 430, when the user intuitively feels that they have effectively achieved a happy or joyful mood, they can record and store this usage experience in an external private cloud 6153 or a public cloud 6155. For example, after recording and storing the usage experience in the external private cloud 6153, it can serve as the user's own usage experience file. For example, this usage experience can also 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 joyful mood, the user can adjust the multi-spectral combination lighting recipe through the management and control module 611, for example, by adjusting the exposure time to 30 minutes or changing the multi-spectral combination light scene. For example, returning to step 411 and reselecting another multi-spectral combination light scene, such as changing the default multi-spectral combination light scene from the Maldives to Bali, Thailand. Afterwards, in step 430, the multispectral lighting process is repeated for 15 minutes. After the lighting process is completed, it is once again determined or evaluated whether the multispectral combination lighting of Bali has effectively achieved a happy or pleasant mood. Until the user feels that the multispectral lighting of the current light scene has effectively achieved a happy or pleasant mood, the effective light scene usage experience can be recorded and stored to form a "spectral recipe". Finally, this "spectral recipe" is stored in an external private cloud 6153 or a public cloud 6155 to form a shared platform. Obviously, multiple "spectral recipes" are stored in the shared platform, where the content stored in the shared platform includes: the light scene that the user achieves a specific emotional effect and the lighting control parameters of the multispectral combination of multiple light-emitting devices 621 with different spectra that produce the specific emotional light scene (hereinafter referred to as lighting parameters).

[0065] 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 file, but the intelligent human-centered lighting system 600 can also, in step 470, perform a massive data analysis on 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 on the user experience data, the intelligent human-centered lighting system 600 can determine the ranking of user-selected "spectral recipes" for different light scenes with a specific color temperature. This ranking can provide users with a reference when selecting a "spectral recipe." Furthermore, after analyzing this massive data, various indicators can be generated for user reference. For example, different multi-spectral combinations of 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 other 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 default multi-spectral combinations. Furthermore, users can also select a most popular "spectral recipe" for lighting based on the calculated user experience data.

[0066] exist Figure 4 In this embodiment, step 450 is optional. For example, if the user is only creating a database for their own use, step 450 can be skipped. After the user determines that the data is valid in step 430, the valid usage experience can be recorded and stored in an external private cloud 6153 or public cloud 6155. The database for the "spectral recipe" establishment service to be established in step 450 will be described in a later embodiment.

[0067] Then, in Figure 4Another embodiment that can be used for commercial services and operations provides a creation platform that allows different users or creators to create new "spectral recipes" through this creation platform. As shown in step 460, a "spectral recipe" creation platform is provided in the intelligent human-centered lighting system 600. Creators 630 using this "spectral recipe" creation platform can be distributed around the world and can connect to the "sharing platform" of the light environment in the cloud 610 of the present invention via the Internet. Obviously, the present invention defines a "spectral recipe" creation platform as a user or creator 630 connecting to the public cloud 6155 or "sharing platform" in the cloud 610 via the Internet, allowing users or creators 630 to use the "spectral recipe" information on the public cloud 6155 or "sharing platform" to perform editing work. 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 "spectral formula" of multi-scene or multi-emotional multi-spectral combination.

[0068] First, the present invention uses a "spectral recipe" creation platform for commercial services and operations in a first embodiment. For example, for an emotionally stimulating result of a 4000K color temperature, users or creators 630 can use the "spectral recipe" creation platform to create combinations of different light scenes. For example, creator 630 might select a multispectral combination of the Maldives for the first segment, a multispectral combination of Bali for the second segment, and finally, a multispectral combination of 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 "spectral recipe" for mood adjustment. The creation platform of the present invention also allows for selecting specific color temperatures at specific times. For example, if a user wants to perform emotionally stimulating human-induced lighting at 9 AM, they can further select the aforementioned three multispectral combinations for 9 AM. Furthermore, the multispectral 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.

[0069] Secondly, in the second embodiment of the present invention using the "Spectral Recipe" creation platform, different color temperatures (i.e., multiple emotions) can be combined to achieve specific emotional stimulation results through multi-emotional lighting. For example, creator 630 can use the "Spectral Recipe" creation platform to create a multi-emotional combination. For example, creator 630 can select a multi-spectral combination of 4000K (happy mood) for the first segment, 3000K (excited mood) for the second segment, and finally, 5700K (pleasant mood) for the third segment. By combining or configuring the multi-spectral exposure time for each segment, a new multi-emotional multi-spectral combination is formed. Finally, this multi-emotional multi-spectral combination is stored on the "sharing platform," allowing users to select this multi-emotional multi-spectral combination as their "spectral recipe" for mood adjustment. Similarly, the creation platform in this embodiment can also select a specific color temperature for a specific time. For example, if a user wants to perform emotionally stimulating human-induced lighting at 9 AM, they can further select the multi-spectral combination of the three aforementioned segments for 9 AM. Furthermore, the multi-spectral exposure time can be configured to be the same or different for each segment, for example, each segment can be 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 same or different time configurations can be selected by the user.

[0070] Next, it should be further explained that after the editing or creation of the first embodiment (multi-spectral combination of multiple light scenes) and the second embodiment (multi-spectral combination of multiple mood light scenes) are completed, the process from steps 430 to 470 is also required. For example, first, in step 411, a multi-spectral combination of light-emitting devices 621 with different spectra is used for illumination. Next, in step 430, it is determined whether the above-mentioned "spectral recipe" combination achieves the desired effect. This includes the spectral combination and corresponding illumination time of the multi-light scene in the first embodiment, and the spectral combination and configured illumination time of the multi-mood light scene in the second embodiment. If the desired effect is achieved, the control parameters of the light-emitting devices 621 required to create these "spectral recipes" can be compiled into a database that provides a "spectral recipe" creation service, as shown in step 450. Then, as shown in step 470, after the "spectral recipe" creation service database constructed in step 450 is uploaded to the cloud, these "spectral recipes" can be added to the public cloud 6155 of the present invention to form a light environment "sharing platform." If, after step 430, it is determined that a certain "spectral formula" does not achieve the effect set by the creator, the process can return to step 411 to adjust the exposure time of each segment, or change to a different light scene combination (first embodiment) or a different mood combination (second embodiment) until these "spectral formulas" can achieve the effect set by the creator. Then, through the process of steps 430 to 470, these "spectral formulas" that have been determined to be effective can be added to the public cloud 6155 of the present invention to form a light environment "sharing platform."

[0071] In addition, in order to enable the multi-scene combination or multi-emotion combination of the "spectral formula" creation platform to have an effect, it may be necessary to pass through a specific lighting device 621 or a specific configuration diagram to achieve the best effect. Therefore, the present invention is further configured with a database of hardware services, as shown in step 420, and further configured with a database of software services, as shown in step 440. Among them, the database of hardware services and the database of software services also embed some management information when building "spectral formulas", including: installation or transportation of hardware devices, or including: providing software services such as space design, scene planning or interface settings required to build these "spectral formulas" through the database of software services. In addition, the database of hardware services and the database of software services can be configured on the creator 630 side, or in the cloud 610, and the present invention does not limit this. Obviously, the present invention is Figure 4In this embodiment, the process for creating various "spectral recipes" and the database of "spectral recipe" creation services are provided. The database of hardware and software services required for "spectral recipe" creation is also established on the light environment "sharing platform." It is important to note that the "sharing platform" ultimately established in step 470 is capable of providing effective "spectral recipes" for multiple light scenes and multiple mood light scenes. Subsequently, various commercial services and operations can be provided through this "sharing platform."

[0072] Next, please refer to Figure 3 and Figure 5a As shown, Figure 5a This is an automatically adjustable intelligent human-centric lighting method 500 of the present invention. First, as shown in step 510, the management and control module 611 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 that various color temperatures can stimulate people (or users) with corresponding emotions. For example, a specific color temperature can stimulate a specific emotion with a synergistic effect.

[0073] Next, as shown in step 530, a multi-spectral recipe cloud database for human-centric lighting is constructed. In step 530, the management control module 611 downloads the "spectral recipe" stored in the "sharing platform" established in step 470 as a source for constructing the multi-spectral recipe cloud database for human-centric lighting. Therefore, the process of creating the "spectral recipe" in step 470 will not be described in detail; please refer to step 470 for a detailed description.

[0074] Next, as shown in step 520, a "contextual dynamic spectrum editing platform" is provided. Similarly, the present invention defines a "contextual dynamic spectrum editing platform" similar to the aforementioned "spectral recipe creation platform." The present invention's "contextual dynamic spectrum editing platform" refers to a platform that allows users or creators 630 to connect to a public cloud 6155 or "sharing platform" in the cloud 610 via the internet, allowing users or creators 630 to use the "spectral recipe" information on the public cloud 6155 or "sharing platform" to perform contextual editing. After the "Contextual Dynamic Spectrum Editing Platform" obtains a variety of "spectral formula" data from the "sharing platform", the "Contextual Dynamic Spectrum Editing Platform" can use the software application to perform contextual editing or creation on the "spectral formula" 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.

[0075] Next, the editing process of the "situational dynamic spectrum program" in step 520 is described in detail. Figure 5bThis is the editing process of the contextual dynamic spectral editing platform of the present invention. As shown in step 5210, editor 630 downloads the "spectral recipe" stored in the "sharing platform" established in step 470 to the management control module 611 in cloud 610 via the internet. This download is then transferred to the editing device used by editor 630, which can be, for example, a computer, smartphone, or workstation. Specifically, one or more "spectral recipes" are connected to a Software as a Service (SaaS) or Platform as a Service (PaaS) system deployed in cloud 610 via editor 630's editing device. Afterwards, as shown in step 5220, the downloaded "spectral 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, etc., 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 "spectral recipe", or changing the light scenes in the "spectral recipe", or deleting specific light scenes in the "spectral recipe", or adding new light scenes to the "spectral 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 "spectral 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 multispectral combination, or simultaneously adjust the spectral flicker rate of the second Bali multispectral combination, or adjust the lighting sequence or duration of the three multispectral combinations. Alternatively, they can consider the multispectral combinations 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 multispectral combination for Cannes, France, at a color temperature of 4000K, or remove the multispectral combination for Monaco's beaches and replace it with a multispectral combination for Miami Beach, USA, at a color temperature of 4000K. For example, when a user or editor 630 downloads a "spectral recipe" for a spectral 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 emotional (color temperature) combinations. For example, in the aforementioned "spectral 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 lighting.

[0076] Next, as shown in step 5230, the association between the contextual function and the "spectral recipe" is edited. In step 5230, the "spectral recipe" adjusted or set in step 5220 is associated with the specific contextual function desired by the user or editor 630. The association is divided into multiple blocks, and each block is associated with a light scene in the "spectral recipe." For example, in step 5210, the user downloads a "spectral recipe" of a happy, exciting, and joyful multi-light scene. 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 "spectral recipe" can be adjusted to a "spectral recipe" of multi-light scenes such as relaxation, concentration, and pleasure 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 "spectral recipes" of the multi-light scenes of relaxation, concentration, and pleasure, so that the situation of the entire conference process is associated with the "spectral recipe" of the multi-light scene 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 "spectral recipe" of the multi-light scene, and then added "time setting" to the context block, a "context-based dynamic spectrum program" with conference context function can be completed. For example, the playback time of the opening, discussion and conclusion blocks of the meeting is set to 5 minutes, 15 minutes and 10 minutes respectively. Figure 5c As shown, the "situational dynamic spectrum program" with conference situation function can be completed. Obviously, after Figure 5bThe "Contextual Dynamic Spectrum Program" generated through the editing process can be stored in the memory module 617 or the external private cloud 6153 or public cloud 6155 in step 530. These "Contextual Dynamic Spectrum Programs" stored in the external private cloud 6153 can then become "Contextual Dynamic Spectrum Programs" with automatically adjustable intelligent human-centered lighting, providing users with their own 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, enabling commercial use by other users through the cloud 610. Clearly, in step 530, in addition to the various "spectral recipes" downloaded from step 470, the "Contextual Dynamic Spectrum Program" is also included. Therefore, the cloud database established in step 530 can provide users with human-centered 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 of a single emotion and a combination of multiple light scenes of multiple emotions. Of course, specific emotions included in the combination of multiple light scenes of multiple emotions can also be combined using multiple light scenes, and the present invention is not limited to this.

[0077] In addition, in the above Figure 5b During the editing process, another implementation method can be selected. Editor 630 downloads the "spectral 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 the cloud 610. Then, the user or editor 630 can first edit the specific scenario function they want to achieve through the SaaS or PaaS system (i.e., first divide the specific scenario function into multiple blocks). Then, they can associate the specific scenario with the downloaded "human-induced lighting parameter database" to complete the association editing between the multiple scenario blocks and the corresponding emotions (color temperature) 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, then they can select the "spectral recipe" corresponding to the multi-light scene corresponding to the corresponding emotions of relaxation, concentration, and joy from the "human-induced lighting parameter database" stored in the memory module 617, or select the "spectral 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.

[0078] 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 "spectral formula" on different users and / or the lighting hardware configuration in different locations to achieve the light stimulation effects of the "spectral formula." These all require adjustments.

[0079] Next, as shown in steps 550 and 570, the user or editor adjusts the "spectral formula" in the "situational dynamic spectrum program" to meet emotional needs. First, the user or editor 630 has downloaded a "situational dynamic spectrum program" from an external private cloud 6153 or public cloud 6155. This "situational dynamic spectrum program" can be a "spectral formula" for multiple emotions and multiple light scenes, or a "spectral formula" for multiple light scenes with a single emotion. Next, the user or editor 630 needs to be in a "specific environment" to execute the selected "situational dynamic spectrum program." In this embodiment of the present invention, "specific environments" are divided into three types, as shown in step 570, including: closed lighting systems, intelligent lighting fields, and portable human-factor lighting devices. When the "specific environment" is a closed lighting system, wherein the closed lighting system is a closed control room with multiple light-emitting devices (for example, a closed cavity that can isolate external light), one or more users can be provided with a "spectral formula" of the selected "situational dynamic spectrum program" in the closed cavity, as shown in step 571. During the spectral illumination process, the present invention provides a function with control mode setting, for example, the "spectral formula" of multiple light scenes can be adjusted through an app on a mobile device used by the user or editor 630 or a control module in the closed cavity. For example, under the influence of an ambient light environment, the "spectral formula" 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. In addition, when the "specific environment" is a smart lighting field, a smart lighting field is a field with multiple light-emitting devices that can accommodate multiple users, such as a conference room, a classroom, an office, a social venue, or a factory, so that multiple users can receive "situational dynamic spectrum program" and perform "spectral formula" illumination in the smart lighting field, as shown in step 573. During the spectral illumination process, the field controller, user, or editor 630 can adjust the "spectral formula" of the selected "situational dynamic spectrum program" through the application (App) on the mobile device used or the control module in the field. For example, the "spectral formula" 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 / latitude and longitude / brightness / flicker rate, etc., as shown in step 540.Furthermore, when the "specific environment" is a mobile portable lighting device, wherein the mobile 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 "spectral formula" illumination, as shown in step 575. During the spectral illumination process, the user or editor 630 can adjust the "spectral formula" 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 "spectral formula" 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.

[0080] In the operation process of the above-mentioned steps 540, 550 and 570, it is obvious that the default value of the "spectral recipe" is adjusted for the "specific environment" where the user is located. In the process of performing this default value adjustment, the ambient light sensor 650 (such as Figure 3 or Figure 6 ), the ambient light information is transmitted to the application (App) on the mobile device of the user or editor 630 or the control module in the "specific environment" through a wireless communication device as a reference for adjusting the default value of the "spectral recipe". In addition, the presence sensor 660 (such as Figure 3 or Figure 6 (as shown), information about the number of people in the environment is transmitted via wireless communication to an application (app) on the user or editor 630's mobile device or to the control module in the "specific environment" to serve as a reference for adjusting the default values ​​of the "spectral recipe." The 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, it can be a camera system that uses artificial intelligence (AI) facial recognition to determine the number of people. Furthermore, it can be a gas concentration detector that detects changes in oxygen (O2) or carbon dioxide (CO2) concentration to determine the effect of the spectral illumination on the user. For example, if 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" with automatically adjustable intelligent human-centered lighting can be created.

[0081] 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 on whether the user has achieved the desired emotional effect after being illuminated by the "spectral formula" 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.

[0082] As shown in step 580, after the user has performed lighting according to the "spectral recipe" of a specific "situational dynamic spectrum program" in a "specific environment," an algorithm will be used to determine whether the current spectral lighting process has met the user's emotional needs. The algorithm in step 580 may calculate a ratio between the user's physiological signals (including heart rate, blood pressure, pulse, and respiratory rate) and use this ratio as a basis for determining whether the specific emotional needs have been met. 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 in 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 their 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 this feedback data through an algorithm to calculate a ratio. This ratio is then transmitted via the internet to the management control module 611, where it is compared with the ratio stored in the memory module 617 or the internal private cloud 6151. For example, if the algorithm-calculated ratio falls between 1.1 and 1.15, the management control module 611 determines that the probability of this ratio 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 "spectral formula" of the selected "Situational Dynamic Spectrum Program." The illumination process will be terminated after the "Situational Dynamic Spectrum Program" completes the illumination process. Subsequently, in step 590, the current "spectral formula" 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 "spectral formula" of the selected "Situational Dynamic Spectrum Program," the user's desired happy mood has not yet been achieved. At this point, it is necessary to return to step 550, adjust the "spectral formula" of the selected "situational dynamic spectrum program" through the control module 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 module in the field through the contact physiological sensor of step 561. After the ratio is calculated by the algorithm, this ratio is transmitted to the cloud database via the Internet at one time 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 "spectral formulas" 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.

[0083] 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 with the selected "spectral formula," allowing the user to determine or feel for themselves whether the lighting 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.

[0084] According to the above-mentioned intelligent human-factor lighting method that can be automatically controlled, the present invention further provides an intelligent human-factor lighting system for commercial operations, such as Figure 6 As shown. The intelligent human-centered lighting system 600 applied to commercial operations of the present invention includes: a cloud 610, a management control module 611, a lighting field end 620 of intelligent lighting, and a portable communication device 630. The devices configured in the lighting field end 620 include: a lamp group or a light-emitting device 621, at least one occupancy sensor 622, at least one ambient light sensor 623, and a switch device 640. Among them, the lighting field end 620 includes a "specific environment", according to Figure 5a As shown, "specific environments" can be divided into three types of fields, including: closed spaces or smart lighting fields that can be used by multiple people, and mobile portable human-centered lighting devices or closed spaces for personal use.

[0085] first, Figure 6Disclosed is 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 "spectral 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.

[0086] Next, when multiple users are already distributed in a closed space or a smart lighting field, they can use the portable communication device 630 to start the lamp group 621 to perform human-induced lighting with a specific "spectral formula" or "situational dynamic spectrum program". Among them, 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 space, a social venue or a factory, etc., which can provide multiple users with human-induced lighting in the smart lighting field.

[0087] 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 "spectral recipe" or "situational dynamic spectrum program." Furthermore, to more quickly achieve the desired human-focused lighting effect, contact 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 the user has achieved 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 Artificial Intelligence of Things (AIoT) to the management and control module 611 in the cloud 610 for calculation to determine whether the user has achieved the desired effect. Similarly, during the spectrum irradiation process, the "spectral formula" of the multi-light scene 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 "spectral formula" of the selected "situational dynamic spectrum program" can be adjusted. The adjustment methods include: time, longitude and latitude, brightness, flashing rate, etc. (For details, please refer to Figure 4 The operation process of step 540, step 550, step 570 and step 580 is shown).

[0088] then, Figure 6 Also disclosed is an intelligent human-centric lighting system 600A for commercial operations, as shown, and is applicable to an embodiment of personal use. A user can use a portable communication device 630 to download a "spectral 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 a lamp assembly 621 within the portable human-centric lighting device for human-centric lighting using a specific "spectral recipe" or "situational dynamic spectrum program." The portable human-centric lighting device is a virtual device associated with the metaverse, such as a virtual reality (VR), mixed reality (MX), or extended reality (XR) device, that allows a single user to receive human-centric lighting through the virtual device.

[0089] Furthermore, to enable the portable human-centric lighting device to achieve the desired human-centric lighting 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 spectral illumination process, the "spectral recipe" of the multi-light scene can be adjusted through the app on the mobile device used by user 630 or the control module in the closed cavity (please refer to the operation process of steps 540, 550, 570, and 580 for details).

[0090] In a preferred embodiment, the configuration of the lamp group 621 can be customized according to the hardware service database of step 420 and the software service database of step 440. 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 control module 611 through the intelligent Internet of Things (AIoT). This APP allows users to connect to the public cloud in the cloud 610 and then select the desired "spectral formula" or "dynamic spectrum program" from the public cloud for human-centered lighting. At the same time, this app can also allow the lamp group 621 to be remotely turned on or off through a short-range communication protocol, thereby controlling the spectrum to achieve the effect of human-centered lighting. Among them, if the user confirms that those "spectral formulas" or "situational dynamic spectrum programs" have therapeutic effects, these "spectral formulas" or "situational dynamic spectrum programs" can be downloaded to the client's portable communication device 630. Afterwards, by configuring the switch device 640 on the client, the "spectral formula" or "situational dynamic spectrum program" can be directly turned on 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.

[0091] 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 multi-spectral lighting devices. This cloud database allows users to set desired emotional needs within the human-centric lighting system. The system then determines or recommends light formulas. 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 brain's emotional needs are not met, the system continuously updates the "spectral recipe" program via wireless feedback signals. After readjusting the "spectral recipe," the system re-verifies whether the desired emotional needs are met. If the brain's emotional needs are met, the system provides a "spectral recipe" or "situational dynamic spectrum program" tailored to the user's emotional needs, 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 of the brain's emotional needs in commercial promotion without the need for fMRI, benefiting more users.

[0092] Finally, it should be emphasized 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. An intelligent human-factor lighting system, characterized in that: include: The client uses a portable communication device to download spectral formulas or situational dynamic spectral programs from the cloud-based human factors lighting parameter database via the Internet; The intelligent lighting terminal is equipped with a lamp group, and the lamp group provides multi-spectral human-induced lighting for multiple users located in the intelligent lighting terminal according to the situational dynamic spectrum program; and An ambient light sensor is configured in the smart lighting terminal to provide ambient light parameters in the environment of the smart lighting terminal; wherein, The human-caused lighting parameter database stores human-caused lighting parameters to form a memory module, allowing users to obtain corresponding emotional stimulation. The spectrum formula is a record of the use of lighting control parameters of a light scene that achieves a specific emotional effect and a multi-spectral combination of lighting devices with different spectra that produce a specific emotional light scene when the multi-spectral lighting has effectively achieved a specific emotional effect; and The client edits the contextual dynamic spectrum program according to the ambient light parameters, wherein the method for editing the contextual dynamic spectrum program comprises the following steps: setting lighting control parameters for the downloaded spectrum formula through a SaaS or PaaS system configured on the cloud, editing the correlation between the set spectrum formula and the specific contextual function desired by the user, and then adding a time setting to the context block to complete a contextual dynamic spectrum program with the specific contextual function; The setting items of the illumination control parameters include: spectrum generation time, spectrum longitude and latitude, spectrum brightness, spectrum contrast, and spectrum flicker rate; The correlation editing divides the specific situational function to be achieved into multiple situational blocks, and corresponds each of the situational blocks to a light scene in the spectral formula, so that the spectral formula of multiple light scenes in the space is correlated.

2. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: The Internet is an intelligent Internet of Things formed by the Internet of Things and artificial intelligence.

3. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: The Internet is a wireless communication protocol formed by gateways.

4. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: The system also includes at least one presence sensor for providing vibration frequency, ambient temperature, ambient carbon dioxide concentration, and face recognition.

5. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: It also includes a plurality of contact physiological sensors, which are respectively configured on the plurality of users.

6. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: The smart lighting terminal is a conference room, a classroom, an office, a social place or a factory.

7. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: The smart lighting end is a closed space.

8. The intelligent human-centered lighting system as claimed in claim 1, characterized in that: Also included is a switch device, which is configured in the intelligent lighting terminal.

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