CN117729672A

CN117729672A - Healthy lighting control method, device, equipment and medium based on human body rhythm

Info

Publication number: CN117729672A
Application number: CN202410027489.5A
Authority: CN
Inventors: 曹小兵; 李超; 林金填; 陈冲; 卢淑芬; 周裕强
Original assignee: ZHONGSHAN INNOCLOUD INTELLECTUAL PROPERTY SERVICES CO LTD; Xuyu Optoelectronics Shenzhen Co ltd
Current assignee: ZHONGSHAN INNOCLOUD INTELLECTUAL PROPERTY SERVICES CO LTD; Xuyu Optoelectronics Shenzhen Co ltd
Priority date: 2024-01-04
Filing date: 2024-01-04
Publication date: 2024-03-19

Abstract

The invention belongs to the technical field of health illumination, solves the problem of lack of response capability to individual differences and real-time environmental changes in the prior art, and provides a health illumination control method, device, equipment and medium based on human body rhythms. The method comprises the following steps: acquiring environmental parameters of a target illumination space, wherein the environmental parameters comprise illumination parameters and temperature and humidity parameters of the target illumination space; acquiring activity parameters of a user in the target lighting space according to a preset vision algorithm; acquiring illumination demand data according to the environment parameters and the activity parameters; acquiring illumination regulation parameters according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model; and controlling the light source of the target illumination space to illuminate according to the illumination adjustment parameters. The invention combines the human biological rhythm model to dynamically adjust the illumination demand data, thereby realizing the accurate control of brightness and color temperature.

Description

Healthy lighting control method, device, equipment and medium based on human body rhythm

Technical Field

The present invention relates to the field of health lighting, and in particular, to a method, apparatus, device, and medium for controlling health lighting based on a human body rhythm.

Background

The main concern of traditional lighting is to provide enough illumination to meet basic visual and aesthetic requirements. Such lighting designs often ignore the effects of light on human physiological and psychological health. With the advancement of technology and the intensive research on human physiology, the concept of healthy lighting has been developed. Healthy lighting takes into account the effects of light on the biological rhythm of the human body, especially on sleep cycle, mood, productivity and general health. The lighting mode aims at improving the life quality and the working efficiency of people and reducing light pollution and energy consumption by simulating the periodic variation of natural light.

Existing health lighting schemes typically employ timed dimming and color temperature adjustment techniques that automatically adjust the brightness and color temperature as a function of time to simulate the sunrise and sunset of natural light. Some advanced systems may also be personalized based on the user's activities and preferences.

Although these systems improve the indoor light environment to some extent, they often lack the ability to respond to individual differences and real-time environmental changes. Most systems rely on preset schedules and standardized settings that cannot flexibly adapt to the actual activity pattern of the user or the lighting requirements of a particular environment. Furthermore, these systems often ignore the impact of environmental parameters on human comfort and lighting requirements.

Disclosure of Invention

In view of this, the embodiments of the present invention provide a method, apparatus, device and storage medium for controlling healthy illumination based on a human body rhythm, which are used to solve the problem that the illumination scheme in the prior art lacks the response capability to individual differences and real-time environmental changes.

In a first aspect, an embodiment of the present invention provides a method for controlling healthy lighting based on a human rhythm, the method including:

acquiring environmental parameters of a target illumination space, wherein the environmental parameters comprise illumination parameters and temperature and humidity parameters of the target illumination space;

acquiring activity parameters of a user in the target lighting space according to a preset vision algorithm, wherein the activity parameters comprise the moving intensity and the stay time of the user in the target lighting space;

acquiring illumination demand data according to the environment parameters and the activity parameters;

acquiring illumination adjustment parameters according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model, wherein the illumination adjustment parameters comprise brightness parameters and color temperature parameters;

and controlling the light source of the target illumination space to illuminate according to the illumination adjustment parameters.

As an optional embodiment of the present invention, the obtaining, according to a preset visual algorithm, an activity parameter of a user in the target lighting space includes:

acquiring video data of the target lighting space;

tracking a user in the video data according to the preset visual algorithm to obtain the stay time of the user in the target illumination space and the moving distance and the moving time of the user in a preset time threshold, wherein the preset visual algorithm comprises a YOLO algorithm and a multi-target tracking algorithm;

obtaining the moving strength according to the moving distance and the moving time;

and obtaining the activity parameter according to the movement intensity and the residence time.

As an optional embodiment of the invention, the step of obtaining the lighting requirement data according to the environmental parameter and the activity parameter comprises:

acquiring the environmental comfort level of the target illumination space according to the temperature and humidity parameters;

acquiring the activity intensity of the target illumination space according to the activity parameters;

according to the environmental comfort, the activity intensity and the illumination parameters, the illumination demand data of the target illumination space is calculated through a preset illumination demand calculation formula, wherein the preset illumination demand calculation formula is as follows:

Ereq＝α*Eenv+β*Pact+γ*Eclim

Wherein Ereq is the light demand data, eenv is the light intensity, pact is the activity intensity, eclim is the environmental comfort, α is a first adjustment coefficient, β is a second adjustment coefficient, and γ is a third adjustment coefficient.

As an optional embodiment of the present invention, the temperature and humidity parameter includes an ambient temperature and a relative humidity of the target lighting space, and the step of obtaining the ambient comfort level of the target lighting space according to the temperature and humidity parameter includes:

and acquiring the environmental comfort level of the target illumination space according to the environmental temperature, the relative humidity and a preset environmental comfort level calculation formula, wherein the preset environmental comfort level calculation formula is as follows:

Eclim＝μ*T+(1-μ)*H

wherein Eclim is the environmental comfort, μ is a first preset weight, T is the environmental temperature, and H is the relative humidity.

As an optional embodiment of the present invention, the step of obtaining the activity intensity of the target lighting space according to the activity parameter includes:

normalizing the moving intensity and the residence time according to a maximum and minimum value normalization method to obtain target moving intensity and target residence time;

Calculating the activity intensity of the target illumination space according to the target movement intensity, the target stay time and a preset activity intensity calculation formula, wherein the preset activity intensity calculation formula is as follows:

Pact＝λ*Mnorm+(1-λ)*Tnorm

wherein Pact is the activity intensity, mnorm is the target movement intensity, tnorm is the residence time, and λ is a second preset weight.

As an optional embodiment of the present invention, the step of obtaining the illumination adjustment parameter according to the illumination requirement data, the current time and the illumination control algorithm based on the human body rhythm model includes:

acquiring a reference data set, wherein the reference data set comprises a plurality of pieces of reference data, and each piece of reference data comprises temperature and humidity parameters;

constructing an illumination parameter prediction model according to the reference data set, wherein the illumination parameter prediction model is constructed based on a logistic regression algorithm, takes the illumination demand data and the current time as inputs and takes a brightness parameter and a color temperature parameter as outputs;

inputting the illumination demand data and the current time into the illumination parameter prediction model to obtain a predicted illumination control parameter;

controlling the light source to perform test illumination according to the predicted illumination control parameter to obtain test data and user feedback data;

Acquiring the human body rhythm model according to the test data and the feedback data, wherein the human body rhythm model comprises a brightness parameter acquisition function and a color temperature parameter acquisition function;

wherein the color temperature parameter acquisition function is as follows

Tcolor＝f1(Ereq,Time)

The brightness parameter acquisition function is as follows:

Lbrightness＝f2(Ereq,Time)

wherein Tcolor is the color temperature parameter, lbright is the brightness parameter, ereq is the lighting requirement data, and Time is the current Time;

and inputting the lighting requirement data and the current time into the human body rhythm model to obtain the lighting adjustment parameters.

As an optional embodiment of the present invention, the target lighting space is a classroom, the illumination adjustment parameter further includes a blue light parameter, the blue light parameter includes a blue light wavelength and a blue light intensity, and the step of controlling the light source of the target lighting space to illuminate according to the illumination adjustment parameter includes:

and acquiring a schedule corresponding to the classroom, wherein the schedule comprises: the teaching activity information comprises teaching activity types, wherein the teaching activity types comprise courses, rest between courses, examination and special activities, and the courses comprise theoretical courses, test courses and computer courses;

Inquiring the time schedule according to the current time to acquire teaching activity information corresponding to the current time;

acquiring parameter adjustment coefficients of the illumination adjustment parameters according to the teaching activity types, wherein the parameter adjustment coefficients comprise color temperature adjustment coefficients, brightness adjustment coefficients and blue light adjustment coefficients, and the color temperature adjustment coefficients and/or the brightness adjustment coefficients and/or the blue light parameters of the parameter adjustment coefficients corresponding to different teaching activity types are different;

adjusting the illumination adjustment parameters according to the parameter adjustment coefficients to obtain target illumination parameters;

according to the current target illumination parameter, the historical illumination adjustment parameter of the previous time period, the current teaching activity type and the corresponding time period, acquiring an illumination adjustment rate, wherein the illumination adjustment rate is calculated by the following formula:

wherein R is the illumination adjustment rate, W _B 、W _C And W is _G Respectively representing weights of brightness parameter, color temperature brightness and blue light parameter in illumination regulation rate, and delta B, delta C and delta G are respectively the change rates of the brightness parameter, the color temperature brightness and the blue light parameter, T _activity For the length of the current teaching activity period, p is the adjustment time window factor, F _activity A rate adjustment factor derived based on the type of teaching activity;

and controlling the light source to illuminate according to the target illumination parameter and the illumination adjustment rate.

In a second aspect, an embodiment of the present invention provides a healthy lighting control device based on a human body rhythm, where the device includes:

the environment parameter acquisition module is used for acquiring environment parameters of a target illumination space, wherein the environment parameters comprise illumination parameters and temperature and humidity parameters of the target illumination space;

the activity parameter acquisition module is used for acquiring activity parameters of a user in the target lighting space according to a preset visual algorithm, wherein the activity parameters comprise the moving intensity and the stay time of the user in the target lighting space;

the illumination demand acquisition module is used for acquiring illumination demand data according to the environment parameters and the activity parameters;

the adjusting parameter acquisition module is used for acquiring illumination adjusting parameters according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model, wherein the illumination adjusting parameters comprise brightness parameters and color temperature parameters;

and the illumination control module is used for controlling the light source of the target illumination space to illuminate according to the illumination adjustment parameters.

In a third aspect, an embodiment of the present invention provides an electronic device, including: at least one processor, at least one memory and computer program instructions stored in the memory, which when executed by the processor, implement the method as in the first aspect of the embodiments described above.

In a fourth aspect, embodiments of the present invention provide a storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method as in the first aspect of the embodiments described above.

In summary, the beneficial effects of the invention are as follows:

according to the healthy lighting control method, device, equipment and medium based on the human body rhythm, provided by the embodiment of the invention, the environment parameters of the target lighting space are obtained, wherein the environment parameters comprise the lighting parameters and the temperature and humidity parameters of the target lighting space, and the adjustment of the lighting system can be ensured to be suitable for the actual environment by knowing the current environment conditions, so that the lighting efficiency and the comfort level are improved;

according to a preset visual algorithm, acquiring activity parameters of a user in the target lighting space, wherein the activity parameters comprise moving intensity and stay time of the user in the target lighting space, and the illumination can be adjusted according to actual activities of the user in the space, so that personalized illumination setting is realized, comfort level is improved, and productivity and safety of the user can be possibly improved;

According to the environment parameters and the activity parameters, obtaining illumination demand data, and ensuring that illumination setting accords with not only environment conditions but also actual demands of users, thereby improving energy efficiency and user satisfaction; according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model, acquiring illumination adjustment parameters, wherein the illumination adjustment parameters comprise brightness parameters and color temperature parameters, and the optimal setting of brightness and color temperature is determined by comprehensively analyzing the illumination demand, the current time and the human body biological rhythm model, so that an illumination environment synchronous with the natural rhythm of the human body is created, sleep quality can be improved, eye fatigue can be reduced, and even overall health and mood can be improved; according to the illumination adjustment parameters, the light source of the target illumination space is controlled to illuminate, and finally the brightness and the color temperature of the light source are adjusted to meet the optimal illumination parameters obtained by the analysis, and the illumination conditions which are most suitable for the current environment and the user requirements can be created by accurately controlling the illumination parameters, so that the energy efficiency is improved, the energy consumption is reduced, and the optimal visual experience and the optimal physiological comfort level are provided.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described, and it is within the scope of the present invention to obtain other drawings according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a healthy lighting control method based on a human body rhythm according to an embodiment of the invention.

FIG. 2 is a flow chart of the method for obtaining activity parameters according to an embodiment of the invention.

Fig. 3 is a flowchart illustrating a process for obtaining an illumination demand parameter according to an embodiment of the present invention.

Fig. 4 is a schematic structural diagram of a healthy lighting control device based on a human body rhythm according to an embodiment of the present invention.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely configured to illustrate the invention and are not configured to limit the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the invention by showing examples of the invention.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

Example 1

Referring to fig. 1, an embodiment of the present invention provides a method for controlling healthy illumination based on a human body rhythm, the method including:

s1, acquiring environmental parameters of a target illumination space, wherein the environmental parameters comprise illumination parameters and temperature and humidity parameters of the target illumination space;

In order to know the current environment state of the target lighting space, firstly, acquiring environment parameters of the target lighting space, wherein the environment parameters comprise illumination parameters and temperature and humidity parameters of the target lighting space, so as to ensure that the adjustment of a lighting system is adapted to the actual environment, and improve the lighting efficiency and comfort;

specifically, the illumination parameters and the temperature and humidity parameters can be obtained through corresponding sensors, for example, the illumination parameters can be obtained through a light sensor, the light sensor can detect the illumination intensity and the illumination range of indoor natural light and artificial light, and the temperature and humidity parameters can be obtained through a temperature sensor and a humidity sensor so as to monitor the temperature and the humidity level in the space;

s2, acquiring activity parameters of a user in the target lighting space according to a preset visual algorithm, wherein the activity parameters comprise the moving intensity and the stay time of the user in the target lighting space;

this step monitors and analyzes the user's activity pattern in the target space, and tracks the user's movement intensity and dwell time with a preset vision algorithm, including, but not limited to, object tracking algorithms, body posture recognition algorithms, deep learning algorithms, behavior pattern recognition algorithms, etc., through cameras or other vision sensors mounted in the target lighting space, where the object tracking algorithms can identify and track personnel in the space, for example using multi-target tracking techniques in the OpenCV library. The system can continuously track the moving path of the user in the space, and provide more accurate activity intensity and residence time data; the human body gesture recognition algorithm can recognize and analyze the gesture of a human body, such as standing, sitting or walking, and can more finely understand the activity state of a user in space by using tools such as OpenPose; deep learning algorithms, such as using convolutional neural networks, can analyze images captured by cameras, identify the number of people in space, the type of activity, etc., and can extract useful information from complex environments to better adjust lighting settings. Behavior pattern recognition algorithms may learn a user's regular behavior patterns, such as often stay in an area for a certain period of time, to predict future behavior and lighting needs. The above algorithms belong to the prior art and are not repeated here;

As an optional embodiment of the present invention, referring to fig. 2, the acquiring, according to a preset vision algorithm, activity parameters of a user in the target lighting space includes:

s21, acquiring video data of the target illumination space;

specifically, the real-time video data in the illumination space is collected firstly as the basis for analyzing the user behaviors, visual sensors such as cameras are installed in the illumination space, videos are recorded in real time, the visual sensors can cover the whole space, the user activities can be captured without dead angles, the video data refer to continuous image data captured by a camera system and used for subsequent analysis and processing, so that a comprehensive visual angle is provided for observing and analyzing the behaviors of the user in the space, and a data basis is provided for more accurate activity analysis

S22, tracking a user in the video data according to the preset visual algorithm to obtain the stay time of the user in the target illumination space and the moving distance and the moving time of the user in a preset time threshold, wherein the preset visual algorithm comprises a YOLO algorithm and a multi-target tracking algorithm;

to accurately identify and track users in video data, acquire their activity data, track each user in the video using computer vision algorithms, such as YOLO (You Only Look Once), for real-time object detection, and multi-target tracking algorithms, YOLO algorithms quickly and accurately identify people in the video, while multi-target tracking algorithms continuously track the movements of those people;

YOLO is a popular object detection algorithm that can quickly identify different objects (e.g., people) in a video. The multi-target tracking algorithm DeepSORT (Deep Simple Online and Realtime Tracking) is an efficient multi-target tracking algorithm, which combines a traditional tracking algorithm with deep learning, provides a precise and rapid multi-target tracking solution, and is mainly used for tracking the movement of a plurality of objects in a video sequence in real time in a video stream;

through a YOLO and a multi-target tracking algorithm, the stay time of a user in the target illumination space and the moving distance and moving time of the user in a preset time threshold can be obtained;

s23, obtaining the moving strength according to the moving distance and the moving time;

the step quantifies the moving strength of the user, which is a quantified index for measuring the activity level of the user, reflects the moving speed and the activity level of the user, calculates the moving distance and the moving time of the user within a preset time threshold by analyzing tracking data, and thus obtains the moving strength, and the moving strength can be calculated by dividing the moving distance by the moving time, thus providing a quantified mode for evaluating the activity level of the user in space, which is important for adjusting the lighting setting.

S24, obtaining the activity parameters according to the movement intensity and the residence time.

Specifically, the calculated movement intensity is combined with the residence time of the user in the space to obtain more comprehensive activity parameters, wherein the activity parameters refer to data comprehensively reflecting the activity characteristics of the user in the space, the data comprise the movement intensity and the residence time, and the lighting system can be more accurately adjusted to adapt to the actual requirements of the user by analyzing the activity parameters, so that the lighting effect and the user experience are improved.

S3, acquiring illumination demand data according to the environment parameters and the activity parameters;

the method comprises the steps of determining the current illumination requirement by integrating environment and user activity data, comprehensively analyzing environment parameters (such as illumination intensity, temperature and humidity) and user activity parameters (such as moving intensity and residence time), and obtaining current illumination requirement data, wherein the illumination requirement data is key information for guiding an intelligent illumination system how to adjust output of the intelligent illumination system to meet the requirements of a specific environment and a user, and is comprehensively obtained based on the environment parameters and the user activity parameters and aims at creating a comfortable and efficient illumination environment;

In particular, the lighting demand data may be analyzed using specific algorithms by integrating data of environmental parameters and activity parameters, including intensity of user activity, pattern of use of space, and current light level, e.g., increasing brightness in areas where light is dark and user activity is frequent, or decreasing brightness in areas where light is sufficient but not used by humans;

as an alternative embodiment of the present invention, referring to fig. 3, the step of obtaining the lighting requirement data according to the environmental parameter and the activity parameter includes:

s31, acquiring the environmental comfort level of the target illumination space according to the temperature and humidity parameters;

the environmental comfort level of the target illumination space is evaluated through the temperature and humidity parameters, the temperature and humidity data can be compared with comfort level standards to determine whether the environment is in a comfortable range, the environmental comfort level has important influence on the feeling and behavior of a human body, and the environmental comfort level can influence the perception of illumination requirements of people;

S311, acquiring the environmental comfort degree of the target illumination space according to the environmental temperature, the relative humidity and a preset environmental comfort degree calculation formula, wherein the preset environmental comfort degree calculation formula is as follows:

Eclim＝μ*T+(1-μ)*H

Specifically, this step quantifies and evaluates the environmental comfort of the target illumination space, which is calculated using the formula eclim=μ×t+ (1- μ) ×h. Here, T represents ambient temperature, H represents relative humidity, and μ is a preset weight for balancing the influence of temperature and humidity on comfort, temperature has a significant influence on comfort of human body, in general, a suitable temperature range may make people feel more comfortable, humidity also affects comfort, too high or too low humidity may cause discomfort, the relative importance of temperature and humidity in comfort calculation is determined by the first preset weight for balancing the influence of temperature and humidity on comfort index, different space and use situations may require different weight settings, environmental comfort may be classified into three classes of unsuitable, suitable, very suitable according to Eclim's value;

S32, acquiring the activity intensity of the target illumination space according to the activity parameters;

quantifying the activity intensity of the target illumination space through the activity parameters, wherein the activity intensity reflects the activity level of a user in the space, which directly influences the requirements of the illumination intensity and the type, and determining the activity intensity by analyzing the movement intensity and the stay time of the user and the movement tracking and behavior analysis data as described before;

as an optional embodiment of the invention, the step of obtaining the activity intensity of the target lighting space according to the activity parameter includes:

s321, normalizing the moving strength and the residence time according to a maximum and minimum value normalization method to obtain target moving strength and target residence time;

to convert the movement intensity and dwell time to a unified measure for comparison and calculation, the data is first processed using a max-min normalization method. The method converts all data into the range of 0 to 1, so that different data types (moving intensity and residence time) can be compared on the same scale, after normalization, the minimum value in the data is changed to 0, the maximum value is changed to 1, other values are adjusted according to the relative positions between the minimum value and the maximum value, and normalization processing is helpful for eliminating the difference between different data types or metrics, so that comparison and subsequent calculation are more reasonable.

S322, calculating the activity intensity of the target illumination space according to the target movement intensity, the target stay time and a preset activity intensity calculation formula, wherein the preset activity intensity calculation formula is as follows:

Pact＝λ*Mnorm+(1-λ)*Tnorm

Specifically, to comprehensively consider the movement intensity and the residence time of the user, a comprehensive index representing the activity intensity is obtained, and the activity intensity is calculated by using the formula pact=λ×mnorm+ (1- λ) ×tnorm. Here, mnorm is a normalized moving intensity, representing the activity degree of the user in the space, tnorm is a normalized stay time, reflecting the stay or rest degree of the user in a certain area, and λ is a preset weight, determining the relative importance of the moving intensity and stay time when calculating the moving intensity, for balancing the influence of the moving intensity and stay time;

by accurately reflecting the user's activity status, ineffective or excessive lighting can be avoided, energy is saved, and a reasonable lighting setting can provide a more comfortable and healthy light environment according to the user's actual behavior in space.

And S33, acquiring the illumination demand data of the target illumination space according to the environmental comfort, the activity intensity and the illumination parameters.

This step comprehensively considers the environmental comfort, activity intensity and current light level to determine the most suitable light demand, and algorithms or rules can be used to comprehensively analyze these parameters and determine the best light demand for the target lighting space. For example, if the environmental comfort is low and the activity intensity is high, it may be desirable to increase the light intensity to provide more energy and improve the environment, in particular, environmental comfort may be classified as unsuitable, suitable, very suitable levels according to the environmental comfort and the preset comfort threshold, activity intensity may be classified as low, medium, high three levels according to the value of the activity intensity and the preset activity intensity threshold, for example, if Eclim is less than the preset comfort threshold, it may be considered that the environment is too cold or too dry, it may be considered that the light is increased, if Eclim is greater than the preset comfort threshold, it may be considered that the environment is too hot or too wet, it may be desirable to reduce the light, if Pact is greater than the preset activity intensity threshold, it may be considered that the area is frequent to be increased, if Pact is less than the preset activity intensity threshold, it may be considered that the area is relatively stationary, it may be reduced; and determining an adjustment amplitude according to the difference between the current illumination intensity and the ideal illumination intensity, if the indexes of the environmental comfort level and the activity intensity are both directed to the increased illumination, executing the brightness enhancement operation, if one of the indexes is directed to the reduced illumination, and the other is in an ideal range, executing the fine adjustment operation, and if the indexes are both directed to the reduced illumination, executing the light reduction operation.

As an optional embodiment of the present invention, the illumination parameter includes illumination intensity, and the step of obtaining illumination requirement data of the target illumination space according to the environmental comfort, activity intensity and illumination parameter includes:

s331, calculating the illumination demand data of the target illumination space through a preset illumination demand calculation formula according to the environmental comfort, the activity intensity and the illumination parameters, wherein the preset illumination demand calculation formula is as follows:

Ereq＝α*Eenv+β*Pact+γ*Eclim

wherein Ereq is the illumination demand data, eenv is the illumination intensity, pact is the activity intensity, eclim is the environmental comfort level, alpha is a first adjustment coefficient, beta is a second adjustment coefficient, and gamma is a third adjustment coefficient;

specifically, in this embodiment, the preset illumination demand calculation formula is used to calculate the illumination demand data, and the formula integrates the ambient illumination intensity, the user activity intensity and the ambient comfort level, so as to provide a comprehensive view angle for determining the illumination demand, and the illumination setting can be more adapted to the demand of a specific environment according to different space types and usage scene adjustment coefficients;

The first adjustment coefficient α, i.e. the illumination intensity coefficient, may be set according to the use of the space and the availability of natural light, e.g. for a space dependent on natural light the value of α may be reduced.

The second adjustment coefficient β, i.e. the activity intensity coefficient, may be set according to the use of the space, and if the space is often used for activity intensive work or learning, β may be set higher to ensure adequate illumination;

the third adjustment coefficient y, the environmental comfort coefficient, may be adjusted according to the sensitivity of the user to temperature and humidity. For example, γ may be set higher for a living space that is more temperature and humidity comfortable.

In a specific application, the setting of these coefficients should be based on user feedback, environmental monitoring data and analysis of actual usage. Adjustments and optimizations may be required, either experimentally or through in-field testing, to ensure that they accurately reflect the needs of different spaces and user populations.

S4, acquiring illumination adjustment parameters according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model, wherein the illumination adjustment parameters comprise brightness parameters and color temperature parameters;

this step aims at combining the calculated lighting demand data with the current time, using a model based on the human body rhythm to determine the most suitable brightness and color temperature settings, adjusting the lighting to improve the comfort and health of the human body by taking into account the response of the human body's biological clock to the lighting, a human body rhythm model, usually referred to as a model of the human body's biological clock, which explains how the human body's interior naturally adjusts its physiological and behavioral processes. These physiological and behavioral processes follow a period of about 24 hours, called circadian rhythms, which are the internal clock systems of the human body that control various physiological processes of sleep-wake cycle, hormone secretion, thermoregulation, etc. These rhythms are regulated by a small region of the brain (called the supraoptic nucleus), and natural and artificial light have a significant impact on the human biological clock. Light is a major external factor in regulating biological rhythms, especially blue light, which is important in regulating sleep-wake cycle;

Specifically, first, the calculated lighting demand data is analyzed, which may include an assessment of the required lighting intensity and color temperature type for a specific area, taking into account the functionality of the space and the activity type of the user, e.g. reading and office areas may require higher lighting intensity and colder color temperature; the illumination settings are then adjusted according to the time of day (morning, noon, evening) to simulate daily changes in natural light, e.g. the morning may use warm light to simulate sunrise and the evening may use cooler light to simulate sunset; subsequently, the illumination setting is adjusted based on the human body rhythm model, taking into account natural reactions of the human body to light, such as melatonin secretion and alertness cycle, for example, reducing blue light exposure at night to promote melatonin production, contributing to improving sleep quality; an algorithm is used to determine the optimal settings of the brightness (e.g., lumens) and color temperature (e.g., kelvin) of the light source, in combination with all of the above factors; finally, combining all the factors, determining the optimal setting of the brightness and the color temperature of the light source by using an algorithm, and ensuring that the illumination setting accords with the actual requirements of users and biological clocks, thereby improving the overall user experience;

s41, acquiring a reference data set, wherein the reference data set comprises a plurality of pieces of reference data, and each piece of reference data comprises temperature and humidity parameters;

specifically, first, a plurality of pieces of reference data including temperature and humidity parameters are collected, basic data is provided for constructing an illumination parameter prediction model, data is collected from different illumination environments, including environment parameters such as temperature, humidity and the like related to illumination, and the data sets help to determine ideal illumination settings under different environment conditions

S42, constructing an illumination parameter prediction model according to the reference data set, wherein the illumination parameter prediction model is constructed based on a logistic regression algorithm, and takes the illumination demand data and the current time as input and takes a brightness parameter and a color temperature parameter as output;

constructing a model based on a logistic regression algorithm to predict ideal brightness and color temperature under specific illumination requirements and time, analyzing a reference data set by using the logistic regression algorithm, and learning the relationship between the illumination requirements data and time and the brightness and color temperature, wherein the model can predict the optimal illumination setting under any given condition;

Specifically, the step of constructing an illumination parameter prediction model according to the reference data set includes:

s421, preprocessing the reference data set according to a preset data preprocessing method to obtain a target data set;

specifically, in order to convert the original reference data set into a format suitable for model training, ensure the quality and consistency of data, a preset data preprocessing method is applied, such as deletion value removal, outlier processing, feature standardization or normalization, the reference data set is preprocessed, and a clean and formatted target data set is obtained, so that the method is suitable for further analysis and model training;

s422, dividing the target data set into a training set and a testing set according to a preset proportion;

in order to divide the target data set into a training set and a test set for evaluating the performance and generalization ability of the model while training the model, in particular, the data set is divided according to a preset proportion, the setting of which is critical in the model training and testing process, because it determines how much data is used for training the model and how much data is used for evaluating the generalization ability of the model, the correct proportion setting is for avoiding overfitting;

The preset ratio may be 70% training set/30% test set, which is the most common dividing ratio, suitable for most cases, especially when the data set is large enough; the preset ratio may also be 80% training set/20% test set: when the data volume is larger, more data can be selected to be reserved for training, so that the learning capacity of the model is improved; the preset ratio may also be 60% training set/40% test set: the proportion of the test set may be increased when the data set is relatively smaller or when more stringent assessment of model performance is required.

In practical applications, it is preferable to try different division ratios and observe changes in model performance. Sometimes, cross-validation (e.g., K-fold cross-validation) can be used in place of fixed-scale partitioning, which more fully evaluates the performance of the model by repeating training and testing the model by dividing the data set into multiple small portions.

S423, training an initial prediction model constructed based on a logistic regression algorithm according to the training set to obtain an intermediate prediction model;

the method comprises the steps of applying a logistic regression algorithm to train a model, using a training set, selecting characteristics as model input from the training set, wherein the characteristics are key factors influencing illumination parameters (brightness and color temperature), such as environment temperature and humidity, illumination demand data, current time and the like, initializing the logistic regression model, setting basic parameters of the model, such as regularization coefficients, learning rate and the like, inputting prepared training data into the model, adjusting model weights through an iterative process (such as a gradient descent algorithm), minimizing a loss function, and monitoring performance indexes in the training process, such as loss values and accuracy rate, so as to ensure correct learning of the model, wherein the model obtained after training and verification is an intermediate prediction model, and can reasonably predict training data.

S423, adjusting the intermediate prediction model according to the test set to obtain an illumination parameter prediction model.

The method comprises the steps of evaluating performance of an intermediate prediction model by using a test set, mainly focusing on performance of the model on unseen data, inputting the data of the test set into the model, and calculating accuracy, error rate or other relevant performance indexes of the model on the test set; by comparing the performance metrics of the training set and the test set, the type and pattern of errors are analyzed, e.g., high bias may indicate under-fitting and high variance may indicate over-fitting; subsequently, adjusting model parameters according to the result of the previous analysis to improve the performance of the model parameters on the test set, such as adjusting learning rate, regularization parameters or complexity of the model; the model is retrained by using the adjusted parameters, the same training set data is used, updated model parameters are applied, the adjusted model is estimated again by using the test set, the improved model is ensured to obtain better results on the test set, and the finally obtained model is the illumination parameter prediction model through the steps.

S43, inputting the illumination demand data and the current time into the illumination parameter prediction model to obtain a predicted illumination control parameter;

The current illumination demand data and time are used as input, the predicted illumination setting is obtained through an illumination parameter prediction model, the illumination parameter prediction model based on logistic regression is more personalized, specific data in specific environments, such as an activity mode of a specific user, the ambient light intensity and the indoor temperature and humidity, are considered, the specific demands of the user can be met more accurately by analyzing a large amount of data to optimize and personalize the illumination setting, the model is possibly more suitable for complex or changing environments, and real-time adjustment can be performed to respond to the change of the environments;

s44, controlling the light source to perform test illumination according to the predicted illumination control parameter to obtain test data and user feedback data;

specifically, in order to evaluate the effectiveness of the predictive model in the control environment, firstly, a plurality of light sources are arranged in a laboratory or a simulation environment, the brightness and the color temperature can be regulated, the parameters of the light sources are set according to the output of the predictive model, in each test scene, the light sources are regulated according to the prediction of the model, the actual setting and the environmental condition of the light sources are recorded, the feedback of the user is collected through questionnaires, interviews or real-time observation, the subjective feeling and the response of the user to different illumination settings are collected, the influence of the illumination settings on the comfort and the satisfaction of the user are analyzed, and the user feedback under different illumination settings is compared; through the process, the illumination prediction model can be ensured to accurately meet the actual demands of users, and the performance and the user satisfaction of the intelligent lighting system are improved.

S45, acquiring the human body rhythm model according to the test data and the feedback data, wherein the human body rhythm model comprises a brightness parameter acquisition function and a color temperature parameter acquisition function;

wherein the color temperature parameter acquisition function is as follows

Tcolor＝f1(Ereq,Time)

The brightness parameter acquisition function is as follows:

Lbrightness＝f2(Ereq,Time)

specifically, to extract valuable information from the actual test and user feedback for guiding the establishment of a human body rhythm model, first analyzing the illumination settings (such as brightness and color temperature) collected during the test and the user's response to these settings, identifying the illumination patterns preferred by the user at different points in time and different lighting needs, using the data analysis results to define the form of the f1 function, possibly including linear or nonlinear relationships, to create a function, determining the optimal color temperature based on the lighting needs and the current time, and determining the structure of the f2 function based on the test data and the user feedback, considering how best to reflect the relationship of brightness preferences with time and lighting needs;

The human body rhythm model can be obtained through the construction of the brightness parameter acquisition function and the color temperature parameter acquisition function;

s46, inputting the lighting requirement data and the current time into the human body rhythm model to obtain the lighting adjustment parameters.

Finally, the lighting demand data and the current time are input into the human body rhythm model to obtain lighting adjustment parameters, and the human body rhythm model focuses more on simulating the natural biological rhythm of a human body, particularly the rhythm related to the sleep-wake cycle, and is generally based on generalized human biological clock data and possibly considers the physiological demands of light at different time points in the day; the human body biological rhythm model is mainly used for simulating the influence of natural environment on human rhythm, such as illumination change during sunrise and sunset; the intelligent and automatic level of the lighting system is improved based on the lighting control of the human body rhythm and the actual data;

in this scheme, the human biorhythms model and the logistic regression-based prediction model are used at the same time, although they all use the same inputs (time and illumination requirements) to predict color temperature and brightness. Indeed, although they are similar, their application and emphasis are different:

Specifically, if the biorhythm model is used alone, the biorhythm model provides only one baseline, simulating the change in illumination of the natural environment, while the logistic regression model adds personalized adjustments to this baseline. The combination of the two can ensure that the lighting system not only meets the common physiological requirements of human beings, but also can adapt to the specific requirements of individual users or specific environments;

i.e. the biorhythmic model may not be sufficient to cope with all individual differences or the needs of a specific environment. The logistic regression model provides greater flexibility and enables more accurate adjustments to be made based on real-time data. In complex or changing environments, a logistic regression model based on real-time data may be more efficient because it can reflect and adapt to environmental changes in time. In summary, while the two models overlap in terms of input and object, they differ in their emphasis and effect in practical applications. The use of these two models in combination may provide a more comprehensive, flexible, more personalized lighting solution.

And S5, controlling the light source of the target illumination space to illuminate according to the illumination adjustment parameters.

Finally, the light source is actually adjusted according to the illumination adjustment parameters so as to meet the illumination parameters obtained by analysis, the illumination conditions which are most suitable for the current environment and the user requirements are created, the optimal visual experience and physiological comfort level are provided, the energy efficiency is improved, and the energy consumption is reduced.

As an optional embodiment of the present invention, the target lighting space is a classroom, and the illumination adjustment parameter further includes a blue light parameter, where the blue light parameter includes a blue light wavelength and a blue light intensity;

specifically, in this embodiment, the target lighting space is a classroom, and in such lighting space, a blue light parameter is included, where the blue light parameter includes a blue light wavelength and a blue light intensity, and the blue light has a significant effect on a human biological clock. In a teaching environment, suitable blue light intensity can help to regulate student's biorhythms, improving their attention and vitality in the class. For example, stronger blue light (particularly long-wave blue light) may excite vigor in the morning, improving alertness; proper blue light intensity helps to improve cognitive function and learning efficiency. In teaching activities (such as examination) requiring high concentration, properly increasing the intensity of blue light may be helpful to improve student performance; prolonged exposure to high intensity short wave blue light can adversely affect the eyes, especially for young students. Therefore, it is important to control the blue wavelengths and intensities to ensure that they are within safe and healthy limits;

in non-classroom scenarios, such as offices and homes, the blue light parameters may be set by default to short wave blue light and low intensity, helping to reduce eye fatigue and risk of interfering with sleep cycles;

In this embodiment, the step of controlling the light source of the target lighting space to illuminate according to the illumination adjustment parameter includes:

s51, acquiring a schedule corresponding to the classroom, wherein the schedule comprises: the teaching activity information comprises teaching activity types, wherein the teaching activity types comprise courses, rest between courses, examination and special activities, and the courses comprise theoretical courses, test courses and computer courses;

specifically, to ensure that the lighting system can predict and adapt to the teaching activities that will occur, thereby adjusting the lighting settings in advance, the step collects the timetable of the classroom, including various teaching activities and time periods thereof;

to ensure that the lighting settings can be accurately adapted to the needs of various teaching environments. Different teaching activity types have significant differences in the demands of illumination and therefore distinguishing these activity types is critical to achieving optimal lighting effects.

The courses include a theoretical course, an experimental course and a computer course, wherein the theoretical course generally requires uniform and soft illumination to reduce eye fatigue and promote learning concentration, the experimental course requires higher brightness to ensure accuracy of experimental operation, and a specific color temperature may be required to reduce interference to experimental observation; the computer lesson needs to reduce brightness and adjust blue light intensity to reduce screen reflection and reduce eye strain;

When the students rest in class, the students can be helped to restore energy before the next class by properly reducing the brightness or adjusting the color temperature; higher brightness and reduced shadows are often required during the test so that students can clearly see the test paper and concentrate their attention; for special events held by schools, such as meetings or celebrations, special lighting settings may be required to create an appropriate atmosphere.

Through discernment and according to these different teaching activity types adjustment illumination setting, intelligent lighting system not only can improve student's learning efficiency and comfort level, can also promote teacher's teaching experience, can also the energy saving simultaneously effectively.

S52, inquiring the time schedule according to the current time to acquire teaching activity information corresponding to the current time;

specifically, the step extracts relevant teaching activity information from the time table according to the current time, so that the lighting system can react in real time, and the illumination is adjusted according to the current activity.

S53, acquiring parameter adjustment coefficients of the illumination adjustment parameters according to the teaching activity types, wherein the parameter adjustment coefficients comprise color temperature adjustment coefficients, brightness adjustment coefficients and blue light adjustment coefficients, and the color temperature adjustment coefficients and/or the brightness adjustment coefficients and/or the blue light parameters of the parameter adjustment coefficients corresponding to different teaching activity types are different;

According to the teaching activity type (such as a theoretical course, an experimental course and the like), the adjusting coefficients of the color temperature, the brightness and the blue light parameters are determined, and customized illumination setting aiming at specific teaching activities is realized so as to improve teaching and learning effects.

In a specific embodiment, according to the teaching activity type, obtaining the parameter adjustment coefficient of the illumination adjustment parameter may be implemented through an activity type-adjustment coefficient mapping table, and to construct the mapping table, firstly, an illumination requirement needs to be defined;

the lighting requirements for each type of teaching activity are as follows:

theoretical lessons: uniform and soft illumination is required.

Experiment course: high brightness and proper color temperature are required to ensure accurate visual observation.

Computer course: it is desirable to reduce brightness and blue light intensity to reduce screen reflection and visual fatigue.

Rest in class: a medium brightness and warm color temperature are required to create a relaxed environment.

Examination: high brightness and neutral color temperature are required to improve attention and reduce shadows.

Special activities: depending on the nature of the activity, adjustable color temperature and brightness may be required, or high excitation power may be achieved using long-wave blue light intensities.

When the illumination requirements are defined, the comfort level, the activity property and the influence of illumination on the biological rhythm of a human body of a user are considered, and the correct illumination setting can improve the learning efficiency of students, reduce eye fatigue and create a proper learning environment;

According to the illumination requirements, a color temperature adjustment coefficient, a brightness adjustment coefficient and a blue light adjustment coefficient are determined, wherein the color temperature adjustment coefficient is determined according to a color temperature range (warm light, neutral light or cold light) required by an activity, the brightness adjustment coefficient is determined according to a brightness level required by the activity, for example, the brightness possibly required by an experiment course is higher than that of a theoretical course, and the blue light parameter is adjusted according to the requirements on the attention and visual comfort of students, for example, the blue light intensity is reduced in a computer course;

when the lighting requirements are clarified and an activity type-adjustment coefficient map is established, the activity type-adjustment coefficient map is exemplarily shown in the following table 1, and table 1 is an exemplary table of the activity type-adjustment coefficient map:

table 1 exemplary table of the Activity type-adjustment coefficient mapping table

Teaching activity type	Color temperature adjusting coefficient	Brightness adjustment coefficient	Blue light adjustment coefficient
				Theoretical lessons	0.8	1.0	0.9
Test course	1.0	1.2	1.0
				Computer course	0.7	0.8	0.5
Rest in class	0.9	0.9	0.8
				Examination method	1.0	1.3	1.1
Special activities	1.0	1.0	1.0

In practice, these coefficients will be used to adjust the base illumination setting derived from the body rhythm model. For example, if the base setting suggests a medium brightness and neutral color temperature, then for "experimental session" the lighting system will adjust to a higher brightness and maintain the neutral color temperature. In this way, the lighting system is able to more accurately adapt to the specific needs of different teaching activities, it being noted that the above adjustment factors are merely by way of example and not by way of limitation.

S54, adjusting the illumination adjustment parameters according to the parameter adjustment coefficients to obtain target illumination parameters;

specifically, for each teaching activity type, the corresponding color temperature adjustment coefficient, brightness adjustment coefficient and blue light adjustment coefficient are applied to adjust the illumination control parameters obtained by the human body rhythm model, and the adjustment coefficient can increase or decrease the values of the illumination control parameters obtained by the human body rhythm model according to the requirement of a specific activity.

The illumination adjusting method can ensure that the illumination system in the classroom flexibly adapts to different teaching requirements, and provides the students and teachers with optimal learning and teaching environments.

S55, acquiring an illumination adjustment rate according to the current target illumination parameter, the historical illumination adjustment parameter of the previous time period, the current teaching activity type and the corresponding time period;

specifically, the current target illumination parameter and the illumination parameter of the previous time period are obtained, the difference between the target illumination parameter and the illumination parameter of the previous time period is determined, and the adjustment rate required for reaching the target illumination state is calculated based on the activity type, the time period and the illumination variation;

different teaching activities have different demands for illumination. By adjusting the illumination rate to accommodate these demands, the efficiency and comfort of the teaching activity can be improved, in particular, smooth adjustment of the illumination can avoid abrupt changes, thereby reducing interference to students and teachers, especially in environments where attention needs to be focused, and proper adjustment of the rate helps to maintain visual comfort in the teaching room, avoiding visual discomfort caused by too fast changes in illumination.

Specifically, the illumination adjustment rate is calculated by the following formula:

wherein R is the illumination adjustment rate, W _B 、W _C And W is _G Respectively representing weights of brightness parameter, color temperature brightness and blue light parameter in illumination adjusting speed, wherein DeltaB, deltaC and DeltaG are respectively the brightness parameter, the color temperature brightness and the blue light parameterRate of change, T _activity For the length of the current teaching activity period, p is the adjustment time window factor, F _activity A rate adjustment factor derived based on the type of teaching activity;

wherein W is _B 、W _C And W is _G The weights of the brightness parameter, the color temperature brightness and the blue light parameter in the illumination adjustment rate are respectively expressed, and the setting of the weights is based on the importance of the influence of each illumination parameter on teaching activities. For example, for experimental courses requiring a high degree of visual accuracy, brightness may be more important than color temperature or blue light, such a setting can ensure that illumination adjustment is finer and focused on the most critical illumination parameters, improving pertinence and effectiveness of illumination effects;

the effect of the activity type adjusting factor sensitivity is to adjust the overall speed of illumination adjustment according to the characteristics of different teaching activities so as to ensure that illumination changes are matched with the properties of the activities, and the activity type adjusting factor sensitivity is set according to the difference of illumination sensitivity and requirements of different activity types, wherein the value of the activity type adjusting factor sensitivity indicates the sensitivity of specific teaching activities to illumination conditions, and a higher value indicates that the activities are more sensitive to illumination changes or require more specific illumination conditions;

For some teaching activities, such as examination or special demonstrations, it may be desirable to reach the ideal lighting conditions faster to minimize interference and provide the necessary visual support. In this case F _activity May be set higher to speed up the rate of adjustment, e.g., 1.2.

For the conventional teaching activities or rest between classes, the illumination adjustment can be milder and flatter, F _activity Will be set lower to reduce the adjustment rate by, for example, 0.8;

adjusting the time window factor, set based on urgency of the activity and sensitivity to changes in illumination, a rapid change may be suitable for short and urgent activities, while a slower change is suitable for long-term activities, if it is desired that the adjustment is completed 1/4 of the time before the start of the activity, p=1/4, by controlling the adjustment rate, abrupt changes in illumination can be avoided from interfering with teaching activities while providing enough time to accommodate the new illumination environment.

In summary, by determining the illumination adjustment rate by considering the current and historical illumination parameters and the characteristics of the teaching activities, the setting method not only improves the intelligence and adaptability of the classroom illumination system, but also helps create an environment more suitable for learning and teaching.

S56, controlling the light source to illuminate according to the target illumination parameter and the illumination adjustment rate.

Finally, according to the calculated target illumination parameters and the adjustment rate, the light source is controlled to illuminate, smooth and accurate illumination adjustment is realized, so that a continuous and comfortable teaching environment is provided, illumination is dynamically adjusted according to actual use conditions and requirements of classrooms, and an optimal teaching and learning environment is created.

Example 2

Referring to fig. 4, an embodiment of the present invention provides a healthy lighting control device based on a human body rhythm, the device including:

It should be noted that, each module and each unit in the healthy lighting control device based on the human body rhythm in this embodiment are in one-to-one correspondence with each step in the healthy lighting control method based on the human body rhythm in the foregoing embodiment, so specific implementation of this embodiment may refer to implementation of the foregoing healthy lighting control method based on the human body rhythm, and will not be described herein again.

Example 3

In addition, the human rhythm-based healthy lighting control method of the embodiment of the present invention described in connection with fig. 1 may be implemented by an electronic device. Fig. 5 shows a schematic hardware structure of an electronic device according to an embodiment of the present invention.

The electronic device may include a processor and memory storing computer program instructions.

In particular, the processor may comprise a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present invention.

The memory may include mass storage for data or instructions. By way of example, and not limitation, the memory may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. The memory may include removable or non-removable (or fixed) media, where appropriate. The memory may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory is a non-volatile solid state memory. In a particular embodiment, the memory includes Read Only Memory (ROM). The ROM may be mask programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these, where appropriate.

The processor reads and executes the computer program instructions stored in the memory to implement any of the human rhythm-based health lighting control methods of the above embodiments.

In one example, the electronic device may also include a communication interface and a bus. As shown in fig. 5, the processor 401, the memory 402, and the communication interface 403 are connected by a bus 410 and perform communication with each other.

The communication interface is mainly used for realizing communication among the modules, the devices, the units and/or the equipment in the embodiment of the invention.

The bus includes hardware, software, or both that couple components of the electronic device to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. The bus may include one or more buses, where appropriate. Although embodiments of the invention have been described and illustrated with respect to a particular bus, the invention contemplates any suitable bus or interconnect.

Example 4

In addition, in combination with the human body rhythm-based health lighting control method in the above embodiment, the embodiment of the invention may be implemented by providing a computer readable storage medium. The computer readable storage medium has stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the human rhythm-based healthy lighting control methods of the above embodiments.

In summary, according to the method, the device, the equipment and the medium for controlling healthy illumination based on the human body rhythm provided by the embodiment of the invention, the environmental parameters of the target illumination space are obtained, wherein the environmental parameters comprise the illumination parameters and the temperature and humidity parameters of the target illumination space, and the adjustment of the illumination system can be ensured to be suitable for the actual environment by knowing the current environmental conditions, so that the illumination efficiency and the comfort level are improved; according to a preset visual algorithm, acquiring activity parameters of a user in the target lighting space, wherein the activity parameters comprise moving intensity and stay time of the user in the target lighting space, and the illumination can be adjusted according to actual activities of the user in the space, so that personalized illumination setting is realized, comfort level is improved, and productivity and safety of the user can be possibly improved; according to the environment parameters and the activity parameters, obtaining illumination demand data, and ensuring that illumination setting accords with not only environment conditions but also actual demands of users, thereby improving energy efficiency and user satisfaction; according to the illumination demand data, the current time and an illumination control algorithm based on a human body rhythm model, acquiring illumination adjustment parameters, wherein the illumination adjustment parameters comprise brightness parameters and color temperature parameters, and the optimal setting of brightness and color temperature is determined by comprehensively analyzing the illumination demand, the current time and the human body biological rhythm model, so that an illumination environment synchronous with the natural rhythm of the human body is created, sleep quality can be improved, eye fatigue can be reduced, and even overall health and mood can be improved; according to the illumination adjustment parameters, the light source of the target illumination space is controlled to illuminate, and finally the brightness and the color temperature of the light source are adjusted to meet the optimal illumination parameters obtained by the analysis, and the illumination conditions which are most suitable for the current environment and the user requirements can be created by accurately controlling the illumination parameters, so that the energy efficiency is improved, the energy consumption is reduced, and the optimal visual experience and the optimal physiological comfort level are provided.

It should be understood that the invention is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after appreciating the spirit of the present invention.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

In the foregoing, only the specific embodiments of the present invention are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present invention is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and they should be included in the scope of the present invention.

Claims

1. A method for controlling healthy lighting based on a human rhythm, the method comprising:

2. The human rhythm-based health lighting control method according to claim 1, wherein the acquiring the activity parameters of the user in the target lighting space according to the preset visual algorithm comprises:

acquiring video data of the target lighting space;

3. The human rhythm-based health lighting control method according to claim 2, wherein the step of acquiring lighting demand data based on the environmental parameter and the activity parameter comprises:

Ereq＝α*Eenv+β*Pact+γ*Eclim

4. The human rhythm-based health lighting control method according to claim 3, wherein the temperature and humidity parameter includes an ambient temperature and a relative humidity of the target lighting space, and the step of obtaining the ambient comfort level of the target lighting space according to the temperature and humidity parameter includes:

Eclim＝μ*T+(1-μ)*H

5. The human rhythm-based health lighting control method according to claim 3, wherein the step of acquiring the activity intensity of the target lighting space according to the activity parameter comprises:

Pact＝λ*Mnorm+(1-λ)*Tnorm

6. The human rhythm-based health lighting control method according to claim 5, wherein the step of acquiring the lighting adjustment parameters according to the lighting demand data, the current time and a human rhythm model-based lighting control algorithm comprises:

wherein the color temperature parameter acquisition function is as follows

Tcolor＝f1(Ereq,Time)

The brightness parameter acquisition function is as follows:

Lbrightness＝f2(Ereq,Time)

7. The human rhythm-based health lighting control method according to any one of claims 1-6, wherein said target lighting space is a classroom, said illumination adjustment parameters further include blue light parameters including blue light wavelength and blue light intensity, said step of controlling a light source of said target lighting space to illuminate according to said illumination adjustment parameters includes:

8. A healthy lighting control device based on a human rhythm, the device comprising:

9. An electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, which when executed by the processor, implement the method of any one of claims 1-7.

10. A storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1-7.