A residential rhythmic lighting control method and system

Abstract

This application provides a residential rhythmic lighting control method and system, relating to the field of lighting control technology. The method includes: in response to a preset trigger signal, acquiring the user's pose parameters, a first driving strategy for the light source module, and melanin-equivalent daylight illuminance parameters; adjusting the first driving strategy based on the user's pose parameters and melanin-equivalent daylight illuminance parameters to obtain a second driving strategy for the light source module; and driving the light source module according to the second driving strategy. This application aims to address the problem that existing methods cannot meet the user's rhythmic lighting needs.

Description

Technical Field

[0001] This application relates to the field of lighting control technology, and in particular to a residential rhythmic lighting control method and system. Background Technology

[0002] With the development of smart home technology, residential lighting systems have gradually evolved from traditional manual switch control to automation and intelligence. Residential lighting systems can combine time information, environmental sensing information, and user interaction information to adjust parameters such as the on / off status, brightness, and color temperature of lights within the home, thereby improving the convenience, comfort, and intelligence of residential lighting.

[0003] In existing technologies, residential lighting systems typically adjust the brightness and color temperature of luminaires based on a fixed schedule or single-point ambient light detection. This makes it difficult to accurately reflect the actual light intensity to the eyes, and can easily lead to insufficient or excessive compensation, thus failing to meet the user's rhythmic lighting needs. Summary of the Invention

[0004] The embodiments disclosed in this application provide a residential rhythmic lighting control method and system, which can improve the problem that the prior art cannot meet the user's rhythmic lighting needs.

[0005] The embodiments of this application adopt the following technical solutions: In a first aspect, a residential rhythmic lighting control method is provided, the method comprising: in response to a preset trigger signal, acquiring user pose parameters, a first driving strategy of a light source module and a melanin equivalent daylight illuminance parameter; adjusting the first driving strategy according to the user pose parameters and the melanin equivalent daylight illuminance parameter to obtain a second driving strategy of the light source module; and driving the light source module according to the second driving strategy.

[0006] The residential rhythmic lighting control method provided in this application constructs a closed-loop control mechanism for rhythmic lighting under the synergistic effect of natural light and artificial light. By making full use of real-time natural light, it adaptively compensates for or suppresses artificial lighting, ensuring that users can obtain appropriate rhythmic stimulation in different locations, postures, and time periods, thereby improving the accuracy of residential rhythmic lighting control and lighting comfort.

[0007] In one possible implementation of the first aspect, before responding to a preset trigger signal, the method further includes: acquiring residential environment information and user rhythm information, determining a configuration strategy for the lighting control system based on the residential environment information and user rhythm information, and deploying the lighting control system according to the configuration strategy.

[0008] In one possible implementation of the first aspect, the residential environment information includes the geographical location of the residence, the spatial characteristics of the residence, and the lighting design information of the residence. Determining the configuration strategy of the residential lighting control system based on the environmental information and user rhythm information includes: constructing a user rhythmic lighting demand model based on the user rhythm information, the rhythmic lighting demand model being used to characterize the user's visual melanin equivalent daylight illuminance demand value at different times; constructing a natural light calculation model of the residence based on the geographical location and spatial characteristics of the residence; constructing an artificial light calculation model of the residence based on the spatial characteristics and lighting design information of the residence, the artificial light calculation model being used to characterize the correspondence between the output parameters of each luminaire group in the lighting control system and the user's eye exposure illuminance contribution at each pose; and determining a sensor deployment strategy for the lighting control system based on the natural light calculation model and the artificial light calculation model, the sensor deployment strategy including at least the placement locations of light sensors.

[0009] In one possible implementation of the first aspect, a sensor deployment strategy for the lighting control system is determined based on a natural light calculation model and an artificial light calculation model, including: acquiring the pose distribution of users within the residence; and determining the deployment locations of light sensors based on the artificial light calculation model, the natural light calculation model, and the pose distribution.

[0010] In one possible implementation of the first aspect, determining the placement location of the illumination sensor based on the artificial light calculation model, the natural light calculation model, and the pose distribution includes: using the prediction accuracy of the illumination sensor location on the contribution of natural light to eye exposure under different pose distributions as a first evaluation index based on the matching result of the natural light calculation model and the pose distribution; using the prediction accuracy of the illumination sensor location on the contribution of artificial light to eye exposure under different output parameter conditions for each lamp group as a second evaluation index based on the matching result of the artificial light calculation model and the pose distribution; comprehensively evaluating the candidate placement locations based on the first and second evaluation indices; and determining the candidate placement location with the best comprehensive evaluation result as the placement location of the illumination sensor.

[0011] In one possible implementation of the first aspect, adjusting a first driving strategy based on the user's pose parameters and the melanin equivalent sunlight illuminance parameters to obtain a second driving strategy for the light source module includes: determining a first illumination contribution value of natural light based on the melanin equivalent sunlight illuminance parameters and the first driving strategy, wherein the first illumination contribution value is used to characterize the degree of contribution of natural light to the melanin equivalent sunlight illuminance at the light sensor acquisition location; determining a second illumination contribution value of natural light based on the first illumination contribution value of natural light and the user's pose parameters, wherein the second illumination contribution value is used to characterize the degree of contribution of natural light to the melanin equivalent sunlight illuminance at the eye exposure location of the user's location; and adjusting the first driving strategy based on the second illumination contribution value of natural light to obtain a second driving strategy for the light source module.

[0012] In one possible implementation of the first aspect, determining the first illumination contribution value of natural light based on the melanin equivalent daylight illuminance parameter and the first driving strategy includes: determining the illumination contribution value of artificial light output by the light source module at the location of the light sensor based on the mapping relationship between the artificial light calculation model and the first driving strategy; and determining the first illumination contribution value of natural light at the location of the light sensor based on the current melanin equivalent daylight illuminance value and the illumination contribution value of artificial light at the location of the light sensor.

[0013] In one possible implementation of the first aspect, determining a second illumination contribution value of natural light based on a first illumination contribution value of natural light and the user's pose parameters includes: determining a mapping coefficient between the first illumination contribution value and the second illumination contribution value based on the matching result between the pose parameters and the natural light calculation model; and determining the second illumination contribution value of natural light based on the first illumination contribution value and the mapping coefficient.

[0014] In one possible implementation of the first aspect, the driving strategy includes a target luminaire group and target driving parameters. The first driving strategy is adjusted according to the second illumination contribution value of natural light to obtain a second driving strategy for the light source module. This includes: determining the user's melanin equivalent daylight illuminance demand value at the current moment based on the user's circadian rhythm lighting demand model; determining the illumination contribution value of artificial light output by the light source module based on the melanin equivalent daylight illuminance demand value and the second illumination contribution value of natural light; the illumination contribution value of artificial light is used to characterize the illumination contribution value of artificial light at the user's current eye exposure position; and adjusting the first driving strategy based on the matching result of the artificial light calculation model and the illumination contribution value of artificial light to obtain a second driving strategy.

[0015] In one possible implementation of the first aspect, the driving strategy includes a target luminaire group and driving configuration parameters for the target luminaire group. Based on the matching result of the artificial light calculation model and the illumination contribution value of artificial light, the first driving strategy is adjusted to obtain a second driving strategy, including: determining the number of target luminaire groups to be activated according to the matching result of the artificial light calculation model and the illumination contribution value of artificial light; selecting a target luminaire group that matches the number of drives from multiple candidate luminaire groups; and determining the corresponding driving configuration parameters according to the location of the target luminaire group.

[0016] In one possible implementation of the first aspect, selecting a target luminaire group matching the number of drives from a plurality of candidate luminaire groups includes: determining the energy consumption parameters of each candidate luminaire group when achieving the illumination contribution value of artificial light, and determining a first candidate luminaire group set from the plurality of candidate luminaire groups based on the energy consumption parameters; the energy consumption parameters are used to characterize the power consumption level required by the candidate luminaire group combination to achieve the same illumination contribution value of artificial light in the current control cycle; determining the user preference degree of each candidate luminaire group, determining a second candidate luminaire group set from the plurality of candidate luminaire groups based on the user preference degree, determining a third candidate luminaire group set based on the intersection result of the first candidate luminaire group set and the second candidate luminaire group set, and selecting a target luminaire group matching the number of drives from the third candidate luminaire group set according to the comprehensive evaluation score from high to low.

[0017] Secondly, a residential rhythmic lighting control system is provided. The system includes a light acquisition module, a positioning module, a light source module, a driving module, and a control module. The light acquisition module is configured to acquire the equivalent daylight illuminance parameter of melanin in response to a preset trigger signal. The positioning module is configured to acquire the user's pose parameter in response to a preset trigger signal. The control module is configured to adjust a first driving strategy based on the user's pose parameter and the equivalent daylight illuminance parameter of melanin to obtain a second driving strategy for the light source module. The driving module is configured to drive the light source module according to the second driving strategy.

[0018] Thirdly, embodiments of this application provide a computer-readable storage medium storing computer instructions. When these computer instructions are executed by a processor, they are used to implement the method as described in the first aspect and any possible implementation thereof.

[0019] Fourthly, embodiments of this application provide a computer program product that, when the computer program product is run on a computer / executed by the computer's processor, implements the method as described in the first aspect and any of its possible design methods.

[0020] Understandably, the technical effects of the second to fourth aspects refer to the technical effects of the first aspect and any of its embodiments, and will not be repeated here. Attached Figure Description

[0021] Figure 1 A system framework diagram of a residential rhythmic lighting control system provided in this application embodiment; Figure 2 A flowchart illustrating the steps of a residential rhythmic lighting control method provided in this application embodiment; Figure 3 The second flowchart illustrates the steps of a residential rhythmic lighting control method provided in this application embodiment. Detailed Implementation

[0022] The technical solutions in some embodiments of this application will be clearly and completely described below with reference to the figures. Obviously, the embodiments described in the specification are only some embodiments of this application, and not all embodiments. Based on the embodiments provided in this application, all other embodiments obtained by those skilled in the art are within the scope of protection of this application.

[0023] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as open-ended and encompassing, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "exemplary," or "some examples," etc., are intended to indicate that a particular parameter, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this application. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0024] The use of “configured as” in this article implies an open and inclusive language that does not exclude the applicability to or configuration of devices to perform additional tasks or steps.

[0025] With the continuous development of smart home technology, healthy building concepts, and human-centered lighting technology, the functional positioning of lighting systems has gradually evolved from simply meeting visual visibility needs to considering visual comfort, energy-saving control, and the promotion of human health. Traditional residential lighting typically focuses on meeting illuminance requirements, on / off control, or simple dimming, paying more attention to whether the space brightness is sufficient and whether energy consumption is controllable, while relatively neglecting the impact of lighting on human physiological rhythms, mental state, sleep quality, and long-term health.

[0026] Therefore, if lighting systems are configured solely based on visual illumination in terms of brightness and color temperature, it is often difficult to simultaneously address the diverse rhythmic stimulation needs of the human body at different times of day. Furthermore, in residential settings, rhythmic lighting control is more individualized and complex compared to settings such as offices, classrooms, and hospitals.

[0027] On the one hand, residences are highly personalized living spaces, with significant differences among users in terms of their daily routines, living habits, space usage, and lighting preferences. For example, different residents show considerable differences in their wake-up times on weekdays and weekends, nighttime activity times, time spent in bedrooms and living rooms, and preferred illuminance and color temperature in reading or leisure settings.

[0028] On the other hand, the positions and postures of people in residential spaces are more flexible. Users may frequently switch between various typical postures, such as sitting on a sofa, lying in bed, sitting at a dining table, sitting at a desk, and standing by a window. The actual light exposure level received by the human eye varies greatly under different postures, and the contribution of the same light fixture to the eye stimulation of people in different positions and orientations also varies significantly. Therefore, if the traditional method of using the overall average illuminance of the room as the control target is still used, it is often difficult to accurately reflect the actual rhythmic stimulation level received by users, and it is also difficult to achieve truly refined lighting control that is geared towards human eye exposure.

[0029] Typically, the brightness and color temperature of residential lighting fixtures can be adjusted through preset schedules, ambient light sensor readings, or manual user settings to achieve basic lighting control or simple rhythmic lighting switching. However, most of these solutions rely solely on fixed time rules or single-point illumination detection results, lacking comprehensive consideration of the user's real-time location, posture changes, and differences in illumination distribution within the residential space. Especially in residential scenarios where natural and artificial light work together, it is difficult to accurately assess the actual illumination level at the user's current eye exposure position, easily leading to insufficient or excessive artificial lighting compensation, thereby affecting the accuracy, comfort, and energy-saving effects of rhythmic lighting control.

[0030] To address the problems existing in related technologies, this application provides a residential rhythmic lighting control method. By acquiring residential environment information, user rhythm information, illumination data collected by light sensors, and real-time pose information of the user, an artificial light calculation model in the residential space is constructed. Based on the artificial light calculation model, the actual illumination contribution at the user's current eye exposure position is estimated. While making full use of natural light, artificial lighting is adaptively compensated or suppressed, thereby providing users with a residential lighting environment that better meets rhythmic needs and balances comfort and energy saving.

[0031] The residential rhythmic lighting control method provided in this application can be applied to intelligent lighting control scenarios in residential indoor spaces, such as rhythmic lighting adjustment scenarios in living spaces like bedrooms, living rooms, studies, and dining rooms.

[0032] It is understood that the executing entity of this method can be a lighting decision module in a residential rhythmic lighting control system, or a control program module deployed in a local gateway, smart lighting master control device, edge computing device, smart home control terminal, or cloud server. In some embodiments, the executing entity can also be a functional module implemented by a processor calling and running a computer program stored in memory to perform the various steps of the above-described residential rhythmic lighting control method.

[0033] First, a feasible hardware implementation method of this application is described, see reference. Figure 1 The residential rhythmic lighting control system 100 provided in this application embodiment may include a light acquisition module 101, a positioning module 102, a light source module 103, a user interaction module 104, a drive module 105, and a control module 106.

[0034] The light acquisition module, positioning module, user interaction module, and drive module are all communicatively connected to the control module. They are used to transmit corresponding acquired data, status data, or interactive data to the control module, and / or receive control commands from the control module. The drive module is electrically connected to the light source module and is used to drive the light source module to emit light according to the control parameters output by the control module. The user interaction module can also interact with the user, receiving control information input by the user and displaying the current lighting status information to the user.

[0035] Specifically, the light acquisition module can be used to collect real-time light environment data in the indoor space of a residence and send the light environment data to the control module so that the control module can determine the current ambient light status in the space.

[0036] As an example, the light acquisition module may include an illuminance sensor, a spectral sensor, or other detection devices capable of characterizing indoor light environment parameters, for acquiring ambient light information under the combined effect of natural light and / or artificial light.

[0037] The positioning module is used to acquire the user's current location and / or current pose information in the indoor space of the residence, and send the location data and / or pose data to the control module so that the control module can determine the user's current typical pose.

[0038] As an example, the positioning module can be implemented using ultra-wideband positioning devices, Bluetooth positioning devices, WiFi positioning devices, infrared positioning devices, smart wearable devices, or other non-contact, image-free positioning devices, thereby reducing the risk of privacy leaks while identifying the user's spatial location.

[0039] The light source module is used to provide artificial lighting output in residential interior spaces. The light source module may include one or more dimmable luminaires, which can be divided into multiple independently controllable luminaire groups according to a preset method, so that the output state of each luminaire group can be adjusted according to different lighting needs.

[0040] The user interaction module receives user-input interaction information and sends it to the control module. It also receives status information output by the control module and displays the current system operating status to the user. In some embodiments, the interaction information may include lighting mode selection information, user pose correction information, user preference information, or other control information; the status information may include current time, current lighting mode, current recognition pose, current eye exposure data, and current lamp output status. The user interaction module can be a local control panel, a mobile terminal application, a smart home control terminal, or a combination thereof.

[0041] The driver module receives the lighting control parameters output by the control module and drives the light source module according to these parameters to adjust its light emission state. Simultaneously, the driver module can also acquire the current output state information of the light source module and send this information to the control module. In some embodiments, the lighting control parameters may include the on / off state of the lighting group, output power ratio, drive current, brightness parameters, color temperature parameters, or other control parameters characterizing the light source output state.

[0042] The control module receives ambient light data from the illumination acquisition module, position and / or pose data from the positioning module, interaction data from the user interaction module, and light source output status data from the driver module. Based on the ambient light data, position and / or pose data, interaction data, and light source output status data, it processes and calculates to determine the user's current eye exposure and the corresponding target luminaire control parameters. Subsequently, the control module sends the target luminaire control parameters to the driver module to control the light source module to output corresponding rhythmic illumination. Furthermore, the control module can also send information such as the current lighting mode, user pose, eye exposure data, and luminaire output status to the user interaction module for display.

[0043] It should be noted that, Figure 2 This is a flowchart illustrating a residential rhythmic lighting control method provided in an embodiment of this application. The residential rhythmic lighting control method can be executed by the residential rhythmic lighting control system in the foregoing embodiments, and can be completed collaboratively by the control module calling the light acquisition module, positioning module, user interaction module, drive module, and light source module.

[0044] The residential rhythmic lighting control method of this application can include two stages: The first stage is the preliminary construction stage of rhythmic lighting control, which is used to establish a basic model of rhythmic lighting control based on the residential space structure, lighting fixture arrangement, typical user activity areas, and typical user posture information to characterize the eye light exposure under different positions and postures, and / or pre-configure target rhythmic lighting parameters corresponding to different time periods. The second stage is the real-time control stage of rhythmic lighting, which is used to dynamically determine the current eye exposure of the user during actual residential use by combining real-time ambient light information, real-time user position and posture information, and current time information, and generate corresponding lighting fixture control parameters accordingly to achieve rhythmic lighting adjustment in residential scenarios.

[0045] First, let's explain the first stage. For an example, please see... Figure 2 As shown, the residential rhythmic lighting control method may include S201 to S202.

[0046] S201: Obtain residential environment information and user rhythm information.

[0047] Residential environmental information is used to characterize the basic environmental conditions and lighting configuration conditions of a residential setting, while user circadian rhythm information is used to characterize users' physiological rhythm needs, sleep habits, and lighting preferences at different times of day. Residential environmental information may include: the geographical location of the residence, the spatial characteristics of the residence, and the lighting design information of the residence.

[0048] The geographical location of a residence is used to characterize the background features of the natural light environment in the area where the residence is located. Specifically, the geographical location of a residence may include at least one of the following: latitude and longitude, city information, time zone information, orientation information, and / or information on the solar radiation patterns of the area. By obtaining the geographical location of a residence, it is possible to further determine the sunrise time, sunset time, solar altitude angle variation trend, duration of daylight, and typical natural light variation patterns of the residence in different seasons and time periods, thereby providing a basic reference for subsequently determining the rhythmic lighting targets within the residence at different time periods.

[0049] The spatial characteristics of a residence are used to characterize its internal spatial structure and the distribution of its functional areas. Specifically, these characteristics may include at least one of the following: apartment layout information, number of rooms, room type, spatial dimensions of each functional area, connectivity between areas, distribution of doors and windows, window orientation, distribution of lighting surfaces, furniture arrangement, distribution of typical user activity areas, and typical user resting locations. By acquiring these spatial characteristics, the differences in lighting conditions, activity purposes, and user resting patterns among different functional areas can be determined, thus providing support for establishing rhythmic lighting control logic for subsequent zoning.

[0050] Residential lighting design information is used to characterize the layout and controllability of the artificial lighting system within the residence. In some embodiments, residential lighting design information may include at least one of the following: number of luminaires, luminaire installation location, luminaire type, luminaire grouping method, luminaire illumination direction, luminaire light distribution characteristics, luminaire adjustable parameter range, control loop configuration relationship, luminaire coverage area, and mapping relationship between each luminaire group and each functional area. Further, the luminaire adjustable parameter range may include brightness adjustment range, color temperature adjustment range, spectral adjustment capability, drive power range, and / or switching control method. By obtaining residential lighting design information, the illumination effect of each luminaire or luminaire group on different spatial areas, different user positions, and different user postures can be clarified, so as to generate targeted luminaire control parameters according to user rhythm requirements.

[0051] User circadian rhythm information is used to characterize the circadian lighting needs of users at different time periods. Specifically, user circadian rhythm information may include at least one of the following: user's preset daily routine information, user's sleep-wake cycle information, user's daily routine information, distribution of typical user activity time, user lighting preference information, target lighting mode information corresponding to different time periods, and user's manually input current activity status information.

[0052] In some embodiments, users can input their circadian rhythm information through the user interaction module. For example, users can input their personal sleep schedule, lifestyle habits, lighting preferences, and / or current activity status to the user interaction module via a local control panel, mobile application, tablet, wall-mounted interactive terminal, smart speaker, or other smart home interactive device. After receiving the user's input, the user interaction module can send the information to the control module for parsing, storage, and subsequent use in circadian rhythm lighting control.

[0053] S202: Determine the configuration strategy of the lighting control system based on residential environment information and user rhythm information, and deploy the lighting control system according to the configuration strategy.

[0054] The configuration strategy of a lighting control system can include multiple dimensions, such as: sensor deployment dimension, rhythm demand modeling dimension, light distribution modeling dimension, luminaire grouping and control dimension, and user interaction configuration dimension.

[0055] The sensor deployment dimension can be used to determine the installation location, quantity, and coverage of light sensors and / or other auxiliary sensors within the residence to ensure accurate perception of the light environment status of different functional areas. The rhythm demand modeling dimension can be used to establish a model of users' rhythmic lighting needs at different times based on their work-rest patterns, time preferences, and lighting preferences. The light distribution modeling dimension can be used to establish an artificial light calculation model representing the mapping relationship between luminaire output parameters and the actual light contribution value exposed to the user's eyes, and a natural light calculation model representing the mapping relationship between the actual light contribution value of natural light at the light sensor location and the actual light contribution value exposed to the user's eyes, based on the residential spatial structure, luminaire arrangement, and typical user posture distribution. The luminaire grouping and control dimension can be used to determine the logical grouping method of each luminaire within the residence, the control objects corresponding to each luminaire group, and the priority control relationships for different functional areas. The user interaction configuration dimension can be used to determine the interaction methods of user interaction modules, the range of configurable items, the method of inputting user preferences, and user identification information.

[0056] By adopting the above multi-dimensional configuration strategies, a control foundation that matches the characteristics of residential space, user rhythm characteristics, and artificial lighting capabilities can be established during the system deployment phase.

[0057] In one feasible implementation, determining the configuration strategy for a residential lighting control system may include the following steps: S2021: Based on user rhythm information, construct a user's rhythmic lighting demand model. The rhythmic lighting demand model is used to characterize the user's visual melanin equivalent daylight illuminance demand value at different times.

[0058] In this embodiment, user circadian rhythm information may include the user's sleep schedule, weekday and weekend routines, daily habits, nighttime activity habits, bedtime preparation habits, morning wake-up habits, and other information that reflects the user's diurnal rhythm characteristics. Based on user circadian rhythm information, the intensity of the user's circadian stimulation needs at different time periods can be pre-established, and the intensity of circadian stimulation needs can be further converted into the corresponding melanin-equivalent daylight illuminance demand value to form a circadian lighting demand model.

[0059] By constructing a circadian rhythm lighting demand model, lighting control systems can provide differentiated lighting targets based on users' actual circadian rhythms at different times. For example, during periods requiring enhanced circadian stimulation, such as when users are waking up, working, or engaging in daytime activities, a higher lower limit for melanin-equivalent daylight illuminance can be set to promote wakefulness and enhance alertness. Conversely, during periods requiring suppressed circadian stimulation, such as before bedtime, nighttime activities, or transitioning to rest, a lower upper limit for melanin-equivalent daylight illuminance can be set to minimize interference with users' circadian rhythms. Therefore, the circadian rhythm lighting demand model not only reflects users' differentiated needs for circadian stimulation intensity at different times but also provides a clear target constraint basis for subsequent lighting control stages.

[0060] In one feasible implementation, constructing a user's circadian rhythm lighting demand model based on user circadian rhythm information may include the following steps: S20211: Based on the user's circadian rhythm characteristics, establish an hourly target threshold judgment table for eye exposure.

[0061] The hourly target threshold determination table for eye exposure can be shown in Formula 1: T i ={t:(E t C t )}(1; Where i represents the i-th lighting mode, t represents time, and E t C represents the target eye exposure threshold corresponding to time t in the i-th lighting mode. t This indicates the rhythmic stimulus constraint type identification identifier corresponding to the target threshold at time t. Where, when E t At time t, the upper limit of rhythmic stimulation is set, meaning that the user's eye exposure at time t should not exceed E. t At that time, C can be set t =1. When Et is at the lower limit of rhythmic stimulation at time t, that is, the user's eye exposure at time t should not be less than E. t At that time, C can be set t =2.

[0062] It should be noted that E t The retinomena equivalent solar illuminance (m-EDI) can be used as a parameter, with units of lux. m-EDI can be calculated based on the retinomena equivalent solar illuminance model. E t The specific values ​​and their corresponding constraint types C t The formulation can be based on relevant standards or adjusted according to individual user habits; this application does not impose any restrictions on this.

[0063] S20212: Based on the preset lighting mode, perform pattern-based management of the hourly target threshold judgment table for eye exposure.

[0064] In some embodiments, the lighting modes may include at least a weekday mode and a rest day mode, and may also include a holiday mode, a work-from-home mode, a night shift compensation mode, or other user-defined modes. For different lighting modes, corresponding hourly target threshold judgment tables for eye exposure can be established to reflect the differentiated lighting needs under different circadian rhythm scenarios.

[0065] Optionally, a mapping relationship i(t) between time t and lighting mode i can be established. In subsequent operation, the lighting control system can automatically determine the current lighting mode based on the current time information and retrieve the corresponding target threshold judgment table to reduce manual switching operations and improve the system automation level.

[0066] In some embodiments, the granularity of the time t definition can be set according to actual application requirements. For example: You can set it by year, and the format can be mmdd00:00, where mmdd represents the date; It can be set by week, and the format can be ww00:00, where ww represents the week of the week; You can also set it by single day, and the format can be 00:00.

[0067] Furthermore, the time interval t can be set according to the user's dimming frequency requirements, such as dividing it into 5 minutes, 10 minutes, 15 minutes or other preset intervals, in order to achieve a balance between control precision and computational complexity.

[0068] S20213: Determine the hourly target threshold judgment table for eye exposure as the user's rhythmic lighting demand model.

[0069] After constructing the hourly target threshold judgment table, it can be used as the user's rhythmic lighting demand model. In the subsequent lighting control phase, the lighting control system can extract the target threshold E corresponding to the current moment from the rhythmic lighting demand model based on the current time information and the current lighting mode. t and constraint type C t This serves as the target for rhythmic lighting control at the current moment.

[0070] S2022: Construct a computational model of natural light for a residence based on its geographical location and spatial characteristics.

[0071] The light distribution model can be divided into two parts: a natural light calculation model and an artificial light calculation model. The natural light calculation model represents the mapping relationship between the actual light contribution value of natural light at the light sensor location and the actual light contribution value of natural light at the eye exposure location in a certain pose. Specifically, when the actual light contribution value of natural light at the light sensor location is 'a', the actual light contribution value 'b' of natural light at the eye exposure location in the user's current pose can be determined based on the natural light calculation model and combined with the user's pose information. That is, the natural light calculation model can map the measured natural light result at the light sensor location to the actual natural light contribution value at the user's eye exposure location, thereby representing the actual degree of effect of natural light on the user's current rhythmic stimulation.

[0072] S2023: Construct a computational model of artificial light for a residence based on environmental information and the user's pose distribution.

[0073] Artificial light computational models are used to describe the contribution of artificial light to user eye exposure under different user poses in residential spaces. Specifically, these models can characterize how changes in the output parameters of each luminaire group affect the illumination contribution at the user's eye position under different typical poses. They can also be used, combined with data collected by light sensors, to infer the contribution of current natural light to user eye exposure under different typical poses.

[0074] In one feasible implementation, constructing a computational model of artificial light for a residence based on environmental information and the user's pose distribution may include the following steps: S20231: Based on residential space characteristics, user pose distribution, and lighting design information, establish the characterization relationship of the illumination contribution of artificial light at the user's eye exposure position.

[0075] Based on the spatial characteristics of the user's residence, the user's living habits, and the user's usual activity areas in the residence, multiple typical postures can be defined. Typical postures are used to represent the user's common staying positions and corresponding postures in the residential space, such as sitting posture at the sofa in the living room, sitting posture at the desk, standing posture in the kitchen work area, and lying posture in the bed in the bedroom.

[0076] Furthermore, based on residential lighting design information, multiple independently controllable luminaires within the residence can be divided into multiple luminaire groups, forming corresponding luminaire group sequences. Subsequently, a mapping relationship is established between the output parameters of each luminaire group and its contribution to the user's eye exposure at various typical poses. This characterizes the degree of artificial light contribution generated by each luminaire group at the user's current eye exposure position under different driving states. Output parameters may include output power, driving current, dimming ratio, or combinations thereof. Preferably, a unit of measurement consistent with the subsequent rhythmic lighting requirements is used to characterize the illumination contribution, such as visual melanin equivalent daylight illuminance. The mapping relationship can further include a representation of the maximum contribution of each luminaire group to the eye exposure at various typical poses under maximum output conditions. This describes the maximum illumination contribution capability that each luminaire group can provide under different typical poses, thus providing a basis for quickly determining whether the target rhythmic lighting requirements are met.

[0077] S20232: Establish the illumination contribution characterization relationship of artificial light at the location of the illumination sensor to support the separate calculation of natural light and artificial light.

[0078] The location of a light sensor can be determined based on residential environment information. This sensor can then collect spectral illuminance data at its location in real time and convert it into the corresponding melanin-equivalent solar illuminance value. The total illumination monitoring value at the sensor location includes both natural light and artificial light contributions. To this end, a mapping relationship can be established between the output parameters of each luminaire group and its contribution to the illumination at the sensor location, characterizing the degree of artificial light contribution from each luminaire group under different output parameter conditions. Based on this mapping relationship, given the current output parameters of each luminaire group, the total contribution of artificial light at the sensor location can be calculated. Combined with the total illumination value monitored in real time by the sensor, the actual contribution of natural light at the sensor location can be separated. In this way, the mixed illumination result collected by the sensor can be decomposed into natural light and artificial light components, providing an intermediate calculation basis for subsequently estimating the natural light contribution at the user's actual location.

[0079] S2024: Based on the natural light calculation model and the artificial light calculation model, determine the sensor deployment strategy for the lighting control system.

[0080] The sensor deployment strategy determines the installation method of sensors used to sense the residential lighting environment within the residence, so as to accurately acquire ambient lighting information for different functional areas and under different lighting conditions. Since different areas within a residence differ in terms of window orientation, distribution of lighting surfaces, spatial dimensions, and shading conditions, it is necessary to plan the sensor deployment locations specifically based on residential environmental information.

[0081] Once the natural light calculation model and the artificial light calculation model are obtained, the sensor deployment location can be selected based on these models.

[0082] In one feasible implementation, the sensor deployment strategy of the lighting control system is determined based on environmental information, including: S20241: Obtain the user's pose distribution within the residence; S20242: Determine the placement of the light sensor based on the artificial light calculation model, the natural light calculation model, and the pose distribution.

[0083] First, the user's pose distribution within the residence is acquired. Pose distribution characterizes typical poses that users may exhibit in different spatial locations and activity scenarios within the residence. Pose can include information such as the user's position, orientation, head posture, and eye height. The main activity areas of the residence can be identified by combining the spatial characteristics of the residence, such as the living room, bedroom, dining room, or study. Based on the functional attributes of each activity area and the user's daily behavioral characteristics, the typical pose distribution that the user may exhibit in each activity area can be determined, such as sitting, standing, lying, or leaning postures. Subsequently, the deployment locations of the illumination sensors can be determined based on artificial light calculation models, natural light calculation models, and the pose distribution. After comprehensively considering the frequency of occurrence, duration of dwell time, and representativeness of different activity areas of each typical pose in the pose distribution, the target location that can better reflect the actual light exposure state of the user's eyes and is conducive to artificial lighting control can be selected from multiple candidate locations as the deployment location of the light sensor. This allows the deployed light sensor to effectively reflect the changes in natural light in the residential environment and accurately characterize the actual light level at the user's eye exposure location in real-life scenarios, thus providing a reliable environmental perception basis for subsequent rhythmic lighting control based on the synergistic effect of natural and artificial light.

[0084] In one feasible implementation, the placement of the illumination sensor is determined based on the artificial light calculation model, the natural light calculation model, and the pose distribution, including: Based on the matching results of the natural light calculation model and the pose distribution, the prediction accuracy of the contribution of the light sensor position to the natural light exposure of the eye under different pose distributions is used as the first evaluation index. Based on the matching results of the artificial light calculation model and pose distribution, the prediction accuracy of the artificial light contribution of the light sensor position to the eye exposure under different output parameter conditions of each lamp group is used as the second evaluation index. Based on the first and second evaluation indicators, the candidate deployment locations are comprehensively evaluated, and the candidate deployment location with the best comprehensive evaluation result is determined as the deployment location of the light sensor.

[0085] When determining the placement of light sensors, multiple candidate locations can be identified first. For example, multiple candidate locations for light sensors can be pre-defined on the wall facing the window in a residential room. Subsequently, through on-site monitoring or computer simulation, a mapping relationship between each candidate point and the contributions of natural and artificial light can be established. Specifically, for each candidate point, the natural light contribution E at that point can be established. d,s E, the contribution value of natural light to the user's current eye exposure under various typical poses d,j The regression equation between E and E. d,s E can represent the illuminance contribution of natural light at the selected point location under natural light conditions. d,j This can represent the natural light contribution value received by the user's eye position when the user is in the j-th typical pose. By establishing E... d,s With E d,j The regression equation between them can be used to predict the natural light exposure of the user's eyes under different typical poses by using sensor measurements at the selected points.

[0086] Based on this, the accuracy of predicting the contribution of the illumination sensor position to the natural light exposure of the user's eyes under different poses can be used as the primary evaluation metric. For example, the goodness of fit, prediction error, correlation, or consistency of the natural light contribution values ​​of the user's eyes under various typical poses can be evaluated using regression equations. In one specific implementation, the coefficient of determination R of the regression equation can be used. 2 R serves as the evaluation criterion for the primary evaluation indicator. 2 The higher the value, the stronger the predictive ability of the natural light sample value at the candidate point for the user's natural light exposure.

[0087] At the same time, for each candidate point, the current output parameter W of each lighting group can also be established separately. a The illuminance contribution value E at the candidate point a,s The regression equation between them. Here, W a This can represent the output parameters of the a-th lighting group at the current moment. The output parameters may include brightness parameters, drive current parameters, power parameters, color temperature parameters, or combinations thereof. a,s This can represent the illuminance contribution of the a-th luminaire group to the selected point location under the current output parameters. By establishing W... a With E a,s The regression equation between them can characterize the sensor response at the candidate point to perceive different lighting groups and their different output states.

[0088] The accuracy of predicting the artificial light contribution of each luminaire group under different output parameter conditions based on the position of the light sensor can be used as a second evaluation metric. For example, it can be evaluated based on the goodness of fit, prediction error, response sensitivity, or discriminability of the regression equations corresponding to each luminaire group. In one specific implementation, the coefficient of determination R0 of the regression equations corresponding to each luminaire group can also be used. 2 As the evaluation basis for the second evaluation indicator, R 2 The higher the value, the stronger the ability of the candidate point to represent changes in artificial lighting.

[0089] After obtaining the first and second evaluation indicators for each candidate point, a set of regression equations can be formed for each candidate point, and a comprehensive evaluation of the regression equations can be performed. The regression equations should include at least: the natural light contribution value E at the candidate point. d,s， E, the contribution value of natural light to user eye exposure under various typical poses d,j The regression equation between them, and the current output parameter W of each lighting group. a The illuminance contribution value E at the candidate point a,s The regression equation between them.

[0090] For each candidate point, the overall fit of its corresponding regression equation system can be compared and used as the comprehensive evaluation result of that candidate point.

[0091] For example, the first and second evaluation indicators can be weighted and fused to obtain a comprehensive score for each candidate point; alternatively, the coefficient of determination R of each regression equation can be used. 2 Statistical summarization was performed. Finally, the overall R-value of the regression equation system was selected. 2 The candidate points with the highest overall score or the best overall score will be selected as the final locations for the light sensor deployment.

[0092] The determined light sensor position, obtained through the above method, can not only accurately reflect the user's natural light exposure under different typical postures, but also better characterize the impact of each luminaire group on the indoor illuminance environment under different output states. Thus, the light sensor can be used for subsequent user eye exposure estimation and subsequent artificial lighting adjustment feedback.

[0093] Preferably, the light sensor can be installed on the wall facing the window inside the house.

[0094] The second stage will then be explained. For an example, please see [link to example]. Figure 3 As shown, the residential rhythmic lighting control method may include S301 to S303.

[0095] S301: In response to a preset trigger signal, acquire the user's pose parameters, the first driving strategy of the light source module, and the equivalent sunlight illuminance parameters of the visual melanin.

[0096] After completing the deployment of the lighting control system and establishing the user's circadian lighting demand model, artificial light calculation model, and natural light calculation model, the system can perceive the current residential environment and user status in real time during operation, and dynamically adjust the current lighting strategy based on the real-time perception results. To this end, in response to a preset trigger signal, the system acquires the user's pose parameters, the first driving strategy of the light source module, and the equivalent daylight illuminance parameters of visual melanin, serving as the basic input for subsequent lighting strategy adjustments.

[0097] The preset trigger signal can include at least one of the following: the current time reaches the preset sampling time, the user's posture changes, the user enters or leaves the target space, etc. By setting the above preset trigger signal, the lighting control results can be updated in a timely manner when the user's activity state changes or the ambient light fluctuates significantly, thereby improving the real-time performance and accuracy of rhythmic lighting control.

[0098] As an example, the trigger condition could be a timed trigger every hour.

[0099] The user's pose parameters can be used to characterize the user's current position and posture information in the target residential space. Preferably, the pose parameters can correspond to a typical pose identifier in a pre-built list of typical poses, or include the user's position coordinates, orientation information, and body posture information in the spatial coordinate system.

[0100] The first driving strategy of the light source module can be used to characterize the initial driving state of each lamp group at the current moment. The first driving strategy can include at least one of the following: the switching state of each lamp group, brightness control parameters, driving current parameters, output power parameters, and dimming duty cycle parameters.

[0101] As an example, the first driving strategy can be the current actual driving strategy after the execution of the previous control cycle.

[0102] The melanin-equivalent daylight illuminance parameter can be used to characterize the real-time rhythmic stimulation level at the current location of the light sensor. Preferably, the melanin-equivalent daylight illuminance parameter is the m-EDI value calculated from the spectral illuminance data collected by the light sensor using the melanin-equivalent daylight illuminance model. Since this parameter includes the combined contributions of natural and artificial light at the location of the light sensor, it is necessary to separate the artificial light component in conjunction with the first driving strategy of the current light source module to further estimate the actual contribution of natural light to the user's eye exposure position.

[0103] S302: Adjust the first driving strategy according to the user's pose parameters and the equivalent daylight illuminance parameters of visual melanin to obtain the second driving strategy of the light source module.

[0104] After obtaining the current user's pose parameters, the first driving strategy of the current light source module, and the equivalent daylight illuminance parameters of visual melanin collected by the current light sensor, the system can further separate the contribution of natural light and artificial light in the current environment according to the pre-built artificial light calculation model, and calculate the actual rhythmic stimulation level of natural light at the user's eye exposure position in combination with the user's current pose, and then dynamically correct the output parameters of each lamp group to obtain a second driving strategy suitable for the current moment.

[0105] The second driving strategy characterizes the target output state of each luminaire group after compensation and adjustment under the current natural light conditions and the current user pose. Compared with the first driving strategy, the second driving strategy is better able to meet the target visual melanin equivalent daylight illuminance threshold required by the user's rhythmic lighting demand model at the current moment, while also taking into account the user's preference for commonly used luminaire groups and the comfort of spatial lighting.

[0106] Based on the user's pose parameters and the equivalent daylight illuminance parameters of retinas, the first driving strategy is adjusted to obtain the second driving strategy for the light source module, including: S3021: Determine the first illuminance contribution value of natural light based on the equivalent solar illuminance parameter of visual melanin and the first driving strategy.

[0107] During operation, the retinocyte-equivalent daylight illuminance parameter at the light sensor's acquisition location is typically a combined result of natural and artificial light. Therefore, to accurately assess the contribution of natural light to the rhythmic stimulation at the user's current eye exposure location, it is necessary to first separate the artificial light contribution from the retinocyte-equivalent daylight illuminance parameter. To this end, based on the first driving strategy of each luminaire group at the current moment, combined with a pre-built artificial light calculation model, the illuminance contribution value of artificial light at the light sensor's acquisition location can be calculated. Then, the artificial light contribution can be separated from the current retinocyte-equivalent daylight illuminance parameter to obtain the first illuminance contribution value of natural light at the light sensor's acquisition location.

[0108] The first illumination contribution value can correspond to the natural light contribution value E at the aforementioned illumination sensor location. d,s This is used to characterize the actual contribution of natural light to the equivalent daylight illuminance of visual melanin at the current sensor acquisition location. By first determining the first illuminance contribution value, the comprehensive illuminance information monitored by the light sensor can be decomposed into natural light and artificial light components, providing a basis for subsequently estimating the natural light contribution at the user's eye exposure location based on the user's pose.

[0109] In one feasible implementation, determining the first illumination contribution value of natural light includes: S30211: Based on the mapping relationship between the artificial light calculation model and the first driving strategy, determine the illumination contribution value of the artificial light output by the light source module at the position of the light sensor. S30212: Determine the illumination contribution of natural light at the location of the illumination sensor based on the current equivalent solar illuminance value of melanin and the illumination contribution value of artificial light at the location of the illumination sensor.

[0110] The lighting decision module can retrieve the output parameters W of each lighting group contained in the first driving strategy of each lighting group. a The parameters of each lamp group are then substituted into the pre-established mapping equation E between their output parameters and their contribution to illumination at the location of the light sensor. a,s (W a This process is used to determine the illumination contribution of each luminaire group to the artificial light at the location of the illumination sensor under the current output state. Then, the illumination contribution values ​​of the artificial light corresponding to each luminaire group are summed to obtain the total illumination contribution value E of the artificial light at the location of the illumination sensor at the current moment. l,s .

[0111] Because the light acquisition module collects the current melanin equivalent solar illuminance value E s The illumination decision module is the sum of the contributions of natural light and artificial light at the location of the illumination sensor. Therefore, it can make decisions based on the current equivalent daylight illuminance value E of visual melanin. s The total illumination contribution value E of artificial light at the location of the light sensor l,s Determine the illumination contribution value E of natural light at the location of the light sensor. d,s The illumination contribution of natural light at the location of the illumination sensor can be obtained by subtracting the total illumination contribution of artificial light at the location of the illumination sensor from the current equivalent daylight illuminance value of visual melanin.

[0112] S3022: Determine the second illumination contribution value of natural light based on the first illumination contribution value of natural light and the user's pose parameters.

[0113] Because the location of the light sensor does not usually coincide with the user's actual location, the contribution of natural light at the light sensor's acquisition location cannot be directly equated to the contribution of natural light at the user's current eye exposure location. In particular, the level of natural light rhythmic stimulation received by the user's eyes will vary significantly depending on the user's location, orientation, or posture.

[0114] Therefore, after obtaining the first illumination contribution value of natural light, it is possible to further combine it with the current user's pose parameters and invoke a pre-constructed natural light contribution mapping relationship to convert the first illumination contribution value of natural light at the light sensor acquisition location into a second illumination contribution value of natural light at the user's current eye exposure location. The second illumination contribution value can correspond to the natural light contribution value E at the user's eye exposure location under the aforementioned typical poses. d,j .

[0115] In one feasible implementation, determining the second illumination contribution value of natural light includes: S30221: Determine the mapping coefficients of the first illumination contribution value and the second illumination contribution value based on the matching results of the pose parameters and the natural light calculation model; S30222: Determine the second illumination contribution value of natural light based on the first illumination contribution value and the mapping coefficient.

[0116] The lighting decision module can determine the natural light contribution mapping relationship for the current user by matching the current user's pose parameters uploaded by the human positioning module with a pre-built natural light calculation model. Specifically, the pose parameters can include the user's current location within the residence, orientation, head posture, and eye height. The natural light calculation model can pre-establish natural light contribution mapping relationships corresponding to multiple typical poses. Each natural light contribution mapping relationship can characterize the mapping relationship between the first illumination contribution value at the location of the light sensor and the second illumination contribution value at the user's eye exposure location under the corresponding typical pose. Based on the matching results between the pose parameters and the natural light calculation model, the lighting decision module can determine the target mapping relationship that best matches the current user's pose, and further determine the mapping coefficients between the first and second illumination contribution values ​​based on the target mapping relationship.

[0117] Mapping coefficients can be used to characterize the proportional relationship or mapping transformation between natural light at the location of the light sensor and the user's eye exposure location. When the natural light contribution mapping relationship adopts a linear mapping method, the mapping coefficients can be determined based on the regression equation parameters corresponding to a typical pose matched with the current pose parameters; when the natural light contribution mapping relationship adopts a nonlinear mapping method, the mapping coefficients can also be determined based on the matched model parameters or mapping function. Subsequently, the illumination decision module can determine the second illumination contribution value of natural light at the user's eye exposure location under the current pose based on the first illumination contribution value detected by the light sensor and the mapping coefficients.

[0118] S3023: Adjust the first driving strategy according to the second illumination contribution value of natural light to obtain the second driving strategy of the light source module.

[0119] After determining the second illumination contribution value of natural light at the user's current eye exposure position, the lighting decision module can further combine the user's rhythmic lighting needs at the current moment to dynamically modify the current first driving strategy. Specifically, based on the equivalent daylight illuminance requirement value of visual melanin at the current moment, it can determine whether natural light at the user's current eye exposure position already meets the rhythmic lighting needs. If natural light has met or exceeded the current needs, the output of artificial light can be reduced or some / all luminaires can be turned off; if natural light is insufficient, the target compensation value that artificial light needs to provide can be determined based on the gap amount, and the output parameters of each luminaire can be adjusted based on the artificial light calculation model, thereby obtaining a second driving strategy that meets the current rhythmic stimulation target.

[0120] The second driving strategy characterizes the target driving state of each luminaire group after dynamic correction under the current time, current natural light conditions, and current user posture. This step allows the lighting control system to perform closed-loop adjustment based on the user's real-time light exposure, thereby meeting rhythmic lighting needs while reducing unnecessary artificial light output, improving energy efficiency and user comfort.

[0121] The specific steps for obtaining the second driving strategy for the light source module may include: S30231: Determine the user's visual melanin equivalent daylight illuminance requirement at the current moment based on the user's circadian lighting demand model; S30232: Based on the equivalent solar illuminance requirement value of visual melanin and the second illuminance contribution value of natural light, determine the illuminance contribution value of artificial light output by the light source module. The illuminance contribution value of artificial light is used to characterize the illuminance contribution value of artificial light at the user's current eye exposure position. S30233: Based on the matching results of the artificial light calculation model and the illumination contribution value of artificial light, the first driving strategy is adjusted to obtain the second driving strategy.

[0122] The lighting decision module can retrieve the current time t at the current trigger moment and determine the corresponding melanin equivalent daylight illuminance demand value E based on the pre-built user rhythm lighting demand model. t And the corresponding judgment identifier C t The lighting decision module can determine the current daylight illuminance requirement based on the visual melanin equivalent solar illuminance value E. t E, the second illumination contribution value of natural light d,j Determine the target illumination contribution value E' that artificial light needs to provide at the user's current eye exposure position. l,j .

[0123] Specifically, when the second illumination contribution value of natural light is greater than or equal to the equivalent daylight illuminance requirement for retinas, it can be determined that natural light has met the rhythmic illumination requirements at the current user's eye exposure position, and the target illumination contribution value of artificial light can be set to zero. When the second illumination contribution value of natural light is less than the equivalent daylight illuminance requirement for retinas, the target illumination contribution value that artificial light needs to provide at the user's current eye exposure position can be determined based on the difference between the two.

[0124] Optionally, the target illumination contribution value of the artificial light can correspond to the aforementioned typical pose P. j Artificial light contribution threshold E' at eye exposure l,j .

[0125] The lighting decision module can re-solve and adjust the output parameters of each luminaire group in the current first driving strategy based on the target illumination contribution value of artificial light and the mapping relationship between the output parameters of each luminaire group in the artificial light calculation model and their illumination contribution value at the current typical pose eye exposure position, so as to obtain the second driving strategy.

[0126] Specifically, in the typical pose P corresponding to the current user pose j Below, the mapping equation set E between the output parameters of each lighting group and its contribution to illumination at typical pose eye exposure positions can be retrieved. a,j (W a The system then matches and solves the target output parameters of each lighting group based on the artificial light target illumination contribution value. Optionally, the matching and solving process can be carried out sequentially according to the user's preset lighting group usage preference order, so as to adjust the user's commonly used lighting groups first, and then adjust the auxiliary lighting groups, so as to meet the rhythmic lighting needs while taking into account the user's subjective lighting habits.

[0127] When judging the identifier C t When =1, it indicates that the current moment corresponds to the rhythmic stimulation upper limit control scenario. In this case, it is preferable to limit the additional rhythmic stimulation provided by artificial light. This can be achieved by reducing the output parameters of each lamp group, turning off auxiliary lamp groups, or directly turning off all lamp groups to generate a second driving strategy; when the judgment flag C t When =2, it indicates that the current moment corresponds to the lower limit control scenario of rhythmic stimulation. At this time, it is preferable to turn on or increase the output parameters of some lamp groups according to the contribution value of artificial light target illumination, so that the total visual melanin equivalent sunlight illuminance at the current eye exposure position of the user reaches or approaches the required value.

[0128] Through the above implementation method, the first driving strategy can be dynamically modified in a targeted manner based on the user's current rhythmic lighting demand value, the actual contribution value of natural light, and the distribution relationship of artificial light under the current posture, so as to obtain a second driving strategy that is more in line with the user's current rhythmic stimulation needs.

[0129] In one feasible implementation, the driving strategy includes the target luminaire group and its driving configuration parameters. Based on the matching results of the artificial light calculation model and the illumination contribution value of artificial light, the first driving strategy is adjusted to obtain the second driving strategy. The specific implementation steps may include: The number of target luminaire groups to be activated is determined based on the matching results of the artificial light calculation model and the illumination contribution value of artificial light. Select the target luminaire group that matches the number of drives from multiple candidate luminaire groups; And determine the corresponding drive configuration parameters based on the location of the target lighting group.

[0130] The number of target luminaire groups activated can be used to characterize the minimum number of luminaire groups required to meet the artificial light contribution requirements at the user's current eye exposure position within the current control cycle. Specifically, based on an artificial light calculation model, the contribution capability of each candidate luminaire group at the eye exposure position corresponding to the user's current pose can be obtained, and the minimum number of luminaire groups required to meet the artificial light illumination contribution value can be determined according to the degree to which each candidate luminaire group meets the artificial light illumination contribution value. Further, after determining the number of activated luminaire groups, target luminaire groups that match the number of activated luminaire groups are selected from multiple candidate luminaire groups. Based on the spatial position, illumination direction, and illumination contribution mapping relationship of each target luminaire group in the current pose, the driving configuration parameters of each target luminaire group are determined in reverse, so that the target luminaire groups can form an artificial light contribution that meets the user's current rhythmic lighting requirements when outputting collaboratively.

[0131] In one feasible implementation, the specific steps for selecting a target luminaire group that matches the number of drives from multiple candidate luminaire groups may include: Determine the energy consumption parameters for each candidate luminaire group to achieve the illumination contribution value of artificial light, and determine the first candidate luminaire group set from multiple candidate luminaire groups based on the energy consumption parameters; the energy consumption parameters are used to characterize the power consumption level required for the candidate luminaire group combination to achieve the same illumination contribution value of artificial light in the current control cycle; Determine the user preference for each candidate lighting fixture group, and determine the second candidate lighting fixture group set from multiple candidate lighting fixture groups based on the user preference; The third candidate lighting fixture set is determined based on the intersection of the first candidate lighting fixture set and the second candidate lighting fixture set. Based on the comprehensive evaluation scores from high to low, the target lighting group that matches the number of drives is selected from the third candidate lighting group set.

[0132] Energy consumption parameters can be determined based on at least one of the following: output power, drive current, dimming ratio, continuous working duration, or unit contribution power consumption ratio when each candidate luminaire group achieves the predetermined artificial light contribution value under the current pose. These parameters characterize the energy-saving advantages and disadvantages of different candidate luminaire groups or combinations of luminaire groups in achieving the same artificial light contribution target. User preference can be determined based on information such as user interaction history, frequently used lighting modes actively set by the user, user frequency of use of different luminaire groups, user dwell time in different spatial areas, and user's adjustment habits for the brightness or color temperature of different luminaire groups. These parameters characterize the user's subjective acceptance or usage tendency towards each candidate luminaire group.

[0133] Furthermore, the comprehensive evaluation score can be determined based on one or more of the following: energy consumption index, user preference index, luminaire spatial proximity index, and contribution efficiency index. The luminaire spatial proximity index characterizes the spatial matching degree of the candidate luminaire group relative to the user's current pose, while the contribution efficiency index characterizes the artificial light contribution capability of the candidate luminaire group to the user's current eye exposure position under unit power consumption conditions. In some embodiments, candidate luminaire groups with lower energy consumption and higher user preference can be preferentially retained, and then, while meeting the constraint on the number of luminaires to be activated, the final target luminaire group can be determined from high to low based on the comprehensive evaluation score.

[0134] By adopting the above approach, we can avoid the problems of high energy consumption, low comfort, or inconsistency with user habits caused by selecting luminaires based solely on their single illumination contribution capability. This ensures that the selected target luminaire group can not only meet the current artificial light contribution requirements, but also take into account energy saving, spatial matching, and personalized experience, thereby improving the overall optimization effect of residential rhythmic lighting control.

[0135] In one feasible implementation, after determining the target luminaire group, the contribution share of artificial light borne by each target luminaire group can be further determined based on the spatial relationship between each target luminaire group and the user's current pose. Then, based on the pre-established illumination contribution mapping relationship in the artificial light calculation model, the driving configuration parameters corresponding to each target luminaire group are solved in reverse. The driving configuration parameters may include brightness driving parameters, color temperature driving parameters, spectral channel driving ratio parameters, duty cycle parameters, current parameters, or combinations thereof.

[0136] For example, when the target lighting group consists of only one lighting group, the illumination contribution value of artificial light can be used as the target contribution value of the target lighting group at the user's current eye exposure position, and the corresponding drive configuration parameters can be directly determined in reverse based on the illumination contribution mapping relationship of the target lighting group; when the target lighting group consists of multiple lighting groups, the corresponding contribution share can be allocated according to the contribution efficiency, spatial proximity or preset priority of each target lighting group, and the corresponding drive configuration parameters can be determined in reverse based on the target contribution share undertaken by each group.

[0137] S303: Drive the light source module according to the second driving strategy.

[0138] After determining the second driving strategy, the control module can send the second driving strategy to the driving module, which then drives the target luminaire group in the light source module according to the second driving strategy, so that the target luminaire group outputs target illumination according to the corresponding driving configuration parameters. Driving configuration parameters may include brightness parameters, color temperature parameters, dimming ratio, driving current, output power, or combinations thereof. By coordinating the driving of the target luminaire group, artificial light compensation matching the target rhythmic lighting requirements can be obtained at the user's current eye exposure position, thus ensuring that the total illumination level actually received by the user meets the rhythmic lighting requirements corresponding to the current time period. Simultaneously with the execution of driving control, the lighting decision module can also synchronously transmit the operating status information corresponding to the current control cycle to the user interaction module for display.

[0139] The residential rhythmic lighting control method provided in this application collects ambient light information in real time by deploying light sensors in different areas of the residence, and combines this with non-invasive human positioning technology to obtain the user's posture and activity location, thereby achieving dynamic adjustment of artificial lighting. It can intelligently adjust the brightness and color temperature of the lamps based on real-time changes in natural light and the user's actual eye position, ensuring that users receive appropriate rhythmic lighting stimulation while making full use of natural light. Simultaneously, through localized light acquisition and non-contact positioning, it avoids interference with user privacy. Furthermore, this application can flexibly control lighting based on the user's activity time distribution and spatial characteristics within the residential space, achieving precise lighting compensation, accurate rhythmic regulation, improved user comfort, reduced energy consumption, and enhanced overall performance of residential rhythmic lighting control.

[0140] This application also provides a computer-readable storage medium storing computer instructions. When these computer instructions are executed by a processor, they are used to implement the technical solution of residential rhythmic lighting control in the above embodiments. Specifically, when the computer instructions are executed by a processor, the computer device can execute the technical solution of the residential rhythmic lighting control method provided in the above embodiments.

[0141] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, it can implement the technical solution of the residential rhythmic lighting control method provided in the above embodiments.

[0142] It should be noted that the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0143] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0144] It should be understood that the steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0145] The technical parameters in the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical parameters in the above embodiments are described. However, as long as these combinations of technical parameters do not contradict each other, they should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application's patent. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical parameters in the formula. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A residential rhythmic lighting control method, characterized by, The method includes: In response to a preset trigger signal, the user's pose parameters, the first driving strategy of the light source module, and the equivalent sunlight illuminance parameters of the visual melanin are obtained. Based on the user's pose parameters and the visual melanin equivalent sunlight illuminance parameters, the first driving strategy is adjusted to obtain the second driving strategy of the light source module. The light source module is driven according to the second driving strategy.

2. The residential rhythmic lighting control method according to claim 1, characterized in that, Prior to responding to a preset trigger signal, the method further includes: Acquire residential environment information and user circadian rhythm information; The configuration strategy of the lighting control system is determined based on the residential environment information and the user rhythm information; The lighting control system is deployed according to the configuration strategy described above.

3. The residential rhythm lighting control method according to claim 2, characterized in that, The residential environment information includes the residence's geographical location, spatial characteristics, and lighting design information. Determining the configuration strategy for the residence's lighting control system based on the environmental information and the user's circadian rhythm information includes: Based on the user's circadian rhythm information, a circadian lighting demand model for the user is constructed. The circadian lighting demand model is used to characterize the user's visual melanin equivalent daylight illuminance demand value at different times. Based on the geographical location and spatial characteristics of the residence, a calculation model of the natural light of the residence is constructed. Based on the spatial characteristics of the residence and the lighting design information of the residence, an artificial light calculation model of the residence is constructed. The artificial light calculation model is used to characterize the correspondence between the output parameters of each lamp group in the lighting control system and the contribution of the user's eye exposure illumination under each pose. Based on the natural light calculation model and the artificial light calculation model, the sensor deployment strategy of the lighting control system is determined, and the sensor deployment strategy includes at least the deployment locations of the light sensors.

4. The residential rhythm lighting control method according to claim 3, characterized in that, The step of determining the sensor deployment strategy for the lighting control system based on the natural light calculation model and the artificial light calculation model includes: Obtain the user's pose distribution within the residence; The placement locations of the light sensors are determined based on the artificial light calculation model, the natural light calculation model, and the pose distribution.

5. The residential rhythm lighting control method according to claim 4, characterized in that, Determining the placement of the illumination sensor based on the artificial light calculation model, the natural light calculation model, and the pose distribution includes: Based on the matching results of the natural light calculation model and the pose distribution, the prediction accuracy of the contribution of the light sensor position to the natural light exposure of the eye under different pose distributions is used as the first evaluation index. Based on the matching results of the artificial light calculation model and the pose distribution, the prediction accuracy of the contribution of the light sensor position to the artificial light of eye exposure under different output parameter conditions of each lamp group is used as the second evaluation index. Based on the first evaluation index and the second evaluation index, the candidate deployment locations are comprehensively evaluated, and the candidate deployment location with the best comprehensive evaluation result is determined as the deployment location of the light sensor.

6. The residential rhythm lighting control method of claim 1, wherein, The step of adjusting the first driving strategy based on the user's pose parameters and the equivalent daylight illuminance parameters of the retinas to obtain the second driving strategy for the light source module includes: Based on the retinoid equivalent daylight illuminance parameter and the first driving strategy, a first light contribution value of natural light is determined. The first light contribution value is used to characterize the degree of contribution of natural light to the retinoid equivalent daylight illuminance at the light sensor acquisition location. Based on the first illumination contribution value of the natural light and the user's pose parameters, a second illumination contribution value of the natural light is determined. The second illumination contribution value is used to characterize the degree of contribution of natural light to the equivalent daylight illuminance of visual melanin at the eye exposure position of the user's location. The first driving strategy is adjusted according to the second illumination contribution value of the natural light to obtain the second driving strategy of the light source module.

7. The residential rhythmic lighting control method according to claim 6, characterized in that, The step of determining the first illuminance contribution value of natural light based on the melanin-equivalent solar illuminance parameter and the first driving strategy includes: Based on the mapping relationship between the artificial light calculation model and the first driving strategy, the illumination contribution value of the artificial light output by the light source module at the position of the light sensor is determined. The illumination contribution of natural light at the location of the light sensor is determined based on the current equivalent daylight illuminance value of visual melanin and the illumination contribution value of artificial light at the location of the light sensor.

8. The residential rhythmic lighting control method of claim 6, wherein, The step of determining the second illumination contribution value of natural light based on the first illumination contribution value of the natural light and the user's pose parameters includes: Based on the matching results between the pose parameters and the natural light calculation model, the mapping coefficients between the first illumination contribution value and the second illumination contribution value are determined; The second illumination contribution value of natural light is determined based on the first illumination contribution value and the mapping coefficient.

9. The residential rhythmic lighting control method of claim 1, wherein, The driving strategy includes a target luminaire group and target driving parameters. Adjusting the first driving strategy based on the second illumination contribution value of the natural light to obtain the second driving strategy for the light source module includes: Based on the user's circadian lighting demand model, determine the user's visual melanin equivalent daylight illuminance demand value at the current moment; Based on the equivalent solar illuminance requirement value of the visual melanin and the second illuminance contribution value of the natural light, the illuminance contribution value of the artificial light output by the light source module is determined. The illuminance contribution value of the artificial light is used to characterize the illuminance contribution value of the artificial light at the current eye exposure position of the user. Based on the matching results of the artificial light calculation model and the illumination contribution value of the artificial light, the first driving strategy is adjusted to obtain the second driving strategy.

10. The residential rhythmic lighting control method of claim 9, wherein, The driving strategy includes a target luminaire group and driving configuration parameters for the target luminaire group. The second driving strategy is obtained by adjusting the first driving strategy based on the matching results of the artificial light calculation model and the illumination contribution value of the artificial light, including: Based on the matching results of the artificial light calculation model and the illumination contribution value of the artificial light, the number of target lighting fixtures to be activated is determined; From multiple candidate luminaire groups, select a target luminaire group that matches the number of drives; And determine the corresponding drive configuration parameters based on the location of the target lighting group.

11. The residential rhythmic lighting control method of claim 8, wherein, The step of selecting a target lighting fixture group that matches the number of drives from multiple candidate lighting fixture groups includes: Determine the energy consumption parameters for each of the candidate luminaire groups to achieve the illumination contribution value of the artificial light, and determine a first candidate luminaire group set from multiple candidate luminaire groups based on the energy consumption parameters; the energy consumption parameters are used to characterize the power consumption level required by the candidate luminaire group combination to achieve the same illumination contribution value of artificial light in the current control cycle; Determine the user preference degree for each of the candidate lighting fixture groups, and determine a second set of candidate lighting fixture groups from multiple candidate lighting fixture groups based on the user preference degree; The third candidate lighting fixture set is determined based on the intersection of the first candidate lighting fixture set and the second candidate lighting fixture set. Based on the comprehensive evaluation scores from high to low, a target lighting group matching the number of drives is selected from the third candidate lighting group set.

12. A residential rhythmic lighting control system characterized by, The system includes a light acquisition module, a positioning module, a light source module, a driving module, and a control module; The light acquisition module is configured to: in response to a preset trigger signal, acquire the equivalent solar illuminance parameter of visual melanin; The positioning module is configured to: acquire the user's pose parameters in response to a preset trigger signal; The control module is configured to adjust the first driving strategy according to the user's pose parameters and the visual melanin equivalent daylight illuminance parameters to obtain the second driving strategy of the light source module. The driving module is configured to drive the light source module according to the second driving strategy.

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