A light intensity adaptive adjustment system, method and medium for flower planting

Abstract

The present invention discloses a light intensity adaptive adjustment system, method, and medium for flower planting, relating to the field of flower planting technology. The system comprises: a joint matching module for performing joint matching of illumination intervals using growth stage identification results; an optimization module for performing feedback correction of flower growth effects using the matching illumination intervals as the optimization space; a control fitting module for performing control fitting of light sources using the batch optimal illumination trajectory as the tracking target; an individual feedback module for performing individual adaptive illumination adaptation evaluation based on growth tracking markers; and a correction module for performing cluster control feedback of dimmable LED light sources. The system solves the technical problems in the prior art of flower planting light adjustment being unable to adapt to the different growth stages and individual differences of flowers, and lacking in light adjustment precision and flexibility, resulting in poor flower growth quality and quality, thereby achieving the technical effect of improving flower growth quality and flower planting efficiency.

Description

Technical Field

[0001] The present application relates to the technical field related to flower planting, and in particular to a light intensity adaptive adjustment system, method and medium for flower planting. Background Art

[0002] Light is a key environmental factor affecting the growth and development of flowers. Its intensity, duration and spectral distribution affect the morphological development, photosynthesis, flowering and fruiting of flowers. Most existing flower planting lighting controls adopt a fixed lighting mode, that is, the light intensity and lighting time are preset throughout the entire planting cycle. The differences in light requirements of flowers at different growth stages (such as seedling stage, growth period, flowering period, etc.) are not fully considered, which can easily lead to insufficient light for flowers at certain growth stages, affecting photosynthesis efficiency. There are also growth differences between individual flowers in the same batch, such as plant size, health status, etc. The existing lighting system is difficult to provide personalized light adjustment according to the characteristics of individual flowers, and thus cannot accurately adjust the light intensity according to the differences between individuals. In addition, traditional lighting equipment cannot quickly and accurately adjust the light intensity and spectral distribution according to the actual needs of flowers, affecting the accuracy and effectiveness of light adjustment.

[0003] Therefore, in the current relevant technologies, there are technical problems such as the inability of flower planting light regulation to adapt to the different growth stages and individual differences of flowers, and the lack of precision and flexibility in light regulation, which leads to poor growth quality and quality of flowers. Summary of the Invention

[0004] This application solves the technical problems in the prior art that light intensity adaptive adjustment for flower planting cannot adapt to the different growth stages and individual differences of flowers, and that light adjustment accuracy and flexibility are insufficient, resulting in poor growth quality and quality of flowers, by providing a light intensity adaptive adjustment system, method and medium for flower planting. This achieves the technical effect of improving flower growth quality and flower planting efficiency.

[0005] The present application provides a light intensity adaptive adjustment system for flower planting, the system comprising: a joint matching module for performing growth stage identification of batches of flowers, and using the growth stage identification results to perform joint matching of illumination intervals to establish matching illumination intervals; an optimization module for using the matching illumination intervals as an optimization space, and using a dynamic feedback channel within the optimization space to perform feedback correction of flower growth effects to establish an optimal illumination trajectory for the batch; a control fitting module for, when performing illumination control of the same batch of flowers, reading adjustment parameters and position information of a dimmable LED light source, and performing control fitting of the dimmable LED light source with the batch optimal illumination trajectory as a tracking target to establish a control fitting result; an individual feedback module for performing growth tracking labeling on the flowers of the same batch after performing control of the dimmable LED light source using the control fitting result, and performing individual adaptive illumination adaptation evaluation based on the growth tracking labeling to establish individual illumination feedback; and a correction module for performing cluster control feedback of the dimmable LED light source based on the individual illumination feedback, and correcting the control fitting result based on the cluster control feedback.

[0006] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: a cluster matching submodule, used to obtain the individual position coordinates of individual flowers in the same batch, and perform association clustering of individual flowers in the same batch with dimmable LED light sources based on the individual position coordinates and the position information, and establish an association clustering result; a feedback authentication submodule, used to perform feedback adaptation evaluation of the group based on the association clustering result and the individual lighting feedback, and establish cluster control feedback using the feedback adaptation evaluation result.

[0007] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: a key positioning unit, used to perform array intersection identification of dimmable LED light sources based on the position information, locate the array intersection area, and locate key flowers of the same batch based on the array intersection area and the individual position coordinates; a penalty compensation unit, used to perform execution fitting of the dimmable LED light source based on the cluster control feedback, and perform adaptation analysis on the key flowers of the same batch, and establish penalty compensation based on the adaptation analysis results; an optimization unit, used to optimize the corrected control fitting results based on the penalty compensation.

[0008] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: extracting flower characteristics of the batch of flowers, using the flower characteristic extraction results and the growth stage identification results as matching features, performing similarity matching of the historical database, and establishing a first joint lighting interval based on the similarity matching results, and the first joint lighting interval is set with a similarity weight; conducting a lighting experiment test on the batch of flowers under the growth stage identification results, and establishing a second joint lighting interval based on the lighting experiment test results, and the second joint lighting interval is set with a stable weight; completing the joint matching of the lighting intervals based on the first joint lighting interval, the second joint lighting interval, the similarity weight, and the stable weight to establish a matching lighting interval.

[0009] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: using an image acquisition device to perform time-series image acquisition of the same batch of flowers to establish a time-series image data set; calling the zero-point image in the time-series image data set, using the zero-point image as the reference image, performing frame-by-frame image comparison of the time-series image data set, and establishing a frame image comparison deviation; using the frame image comparison deviation to perform growth tracking fitting to complete growth tracking labeling.

[0010] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: a cross-stage identification module, which is used to read the growth status data of the same batch of flowers before executing the light control of the same batch of flowers, establish a growth prediction result, and judge whether the growth prediction result meets the cross-stage interval threshold; a constraint establishment module, which is used to establish a cross-stage lighting constraint if the growth prediction result meets the cross-stage interval threshold, and complete the control fitting after constraining the optimal lighting trajectory of the batch according to the cross-stage lighting constraint.

[0011] In a possible implementation, the light intensity adaptive adjustment system for flower planting further performs the following processing: performing control fitting of the batch optimal light trajectory according to the adjustment parameters and position information, and establishing an initial fitting scheme; activating the light sensor at the standard position, monitoring the light data through the light sensor, and establishing a light response; establishing residual feedback according to the light response and the light residual of the batch optimal light trajectory; and using the residual feedback to update the initial fitting scheme and establish a control fitting result.

[0012] In a possible implementation, the light intensity adaptive adjustment system for flower planting also performs the following processing: an array monitoring module, used to perform array light deviation monitoring on all dimmable LED light sources, and generate array light deviation monitoring results; an early warning response module, used to perform deviation trigger verification on the array light deviation monitoring results, and report a balance abnormality early warning.

[0013] The present application also provides a method for adaptively adjusting light intensity for flower planting, the method comprising: performing growth stage identification on batches of flowers, using the growth stage identification results to perform joint matching of illumination intervals, and establishing matching illumination intervals; using the matching illumination intervals as an optimization space, performing feedback correction of flower growth effects within the optimization space using a dynamic feedback channel, and establishing an optimal illumination trajectory for the batch; in performing illumination control on the same batch of flowers, after reading adjustment parameters and position information of a dimmable LED light source, performing control fitting of the dimmable LED light source with the batch optimal illumination trajectory as a tracking target, and establishing a control fitting result; after performing control of the dimmable LED light source using the control fitting result, performing growth tracking marking on the flowers of the same batch, performing individual adaptive illumination adaptation evaluation based on the growth tracking marking, and establishing individual illumination feedback; performing cluster control feedback of the dimmable LED light source using the individual illumination feedback, and correcting the control fitting result based on the cluster control feedback.

[0014] The present application also provides a computer-readable storage medium, comprising: a computer program stored thereon, which, when executed by a processor, implements a light intensity adaptive adjustment system for flower planting.

[0015] This application proposes a light intensity adaptive adjustment system, method, and medium for flower cultivation, including a joint matching module for jointly matching illumination intervals using growth stage identification results; an optimization module for performing feedback correction on flower growth effects using the matching illumination intervals as the optimization space; a control fitting module for performing control fitting of dimmable LED light sources with the batch optimal illumination trajectory as the tracking target; an individual feedback module for performing individual adaptive illumination adaptation evaluation based on growth tracking markers; and a correction module for performing clustered control feedback of dimmable LED light sources. This solves the technical problems in the prior art of flower cultivation light adjustment that cannot adapt to the different growth stages and individual differences of flowers, and lacks light adjustment precision and flexibility, resulting in poor flower growth quality and quality, thereby achieving the technical effect of improving flower growth quality and flower cultivation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1This is a structural schematic diagram of a light intensity adaptive adjustment system for flower cultivation provided in an embodiment of the present application.

[0018] Figure 2 A flow chart of a method for adaptively adjusting light intensity for flower cultivation provided in an embodiment of the present application.

[0019] Description of reference numerals: joint matching module 10 , optimization module 20 , control fitting module 30 , individual feedback module 40 , correction module 50 . DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0023] The embodiment of the present application provides a light intensity adaptive adjustment system for flower planting, such as Figure 1 As shown, the system includes:

[0024] The joint matching module 10 is used to perform growth stage recognition of batches of flowers, and use the growth stage recognition results to perform joint matching of light intervals to establish matching light intervals.

[0025] Preferably, the joint matching module performs joint matching of light intervals through stage identification → feature extraction → dynamic matching, with the growth stage as the driving factor, to achieve precise alignment of flower growth requirements and light supply and refined flower planting. Specifically, batches of flowers from the same source are set to be cultivated at different times, and the specific growth stage of the current flower is judged through sensor data collection (such as camera shooting images, spectral sensor detection of leaf pigment content, etc.) or growth cycle feature analysis (such as the morphology of typical stages such as germination period, seedling period, bolting period, flowering period, and fruiting period). For example, a flower growth stage classification model is trained based on a machine learning algorithm (such as a convolutional neural network CNN), and the growth stage is automatically identified through image features (number of leaves, plant height, bud status, etc.).

[0026] Preferably, a lighting interval refers to a combination of lighting parameters that are strongly correlated with the growth stage of the flower. These may include light intensity (e.g., 5000-8000 Lux), spectral distribution (e.g., red / blue light ratio, supplemental light wavelength), lighting duration (e.g., 12 hours of light per day), and spatial distribution (e.g., top lighting as primary, supplemented by side lighting). A mapping relationship between each flower growth stage and lighting parameters is pre-established to form a standardized lighting interval library. For example, the seedling stage corresponds to low-intensity diffuse light, while the flowering stage corresponds to high-intensity full-spectrum light. Based on the growth stage identification results, the corresponding basic lighting interval is then retrieved from the database. At the same time, adaptive fine-tuning is performed based on environmental parameters (e.g., natural light intensity, temperature and humidity) and historical data (e.g., growth feedback from previous batches) to generate a matching lighting interval. By dividing flower growth into discrete stages and matching the corresponding lighting, light utilization efficiency is improved.

[0027] The optimization module 20 is used to use the matching illumination interval as an optimization space, perform feedback correction on the flower growth effect by using a dynamic feedback channel in the optimization space, and establish an optimal illumination trajectory for a batch.

[0028] Preferably, the optimization module converts the static matching lighting interval into a dynamically optimized lighting trajectory through a feedback iteration mechanism under the matching lighting interval constraint, thereby realizing precise lighting based on real-time data. Specifically, the matching lighting interval is used to set a safe and feasible domain to prevent lighting parameters from exceeding the physiological tolerance range of flowers (such as burns caused by strong light or excessive growth caused by weak light). For example, if the joint matching module determines that a batch of roses is in the "bud formation period", its matching lighting interval is an intensity of 6000~7500Lux and a red light ratio of 40%~50%. The optimization space parameters are within this range. Among them, the lighting parameters included in the optimization space may include light intensity, spectral ratio (such as the ratio of red / blue / green light), lighting duration, lighting uniformity (differences in light intensity between different plants), and the start time of the photoperiod (such as the time point of sunrise simulation).

[0029] Preferably, a dynamic feedback channel is used to perform feedback correction on the growth effect of flowers. Specifically, the flower growth feedback data is monitored in real time by sensors, such as detecting photosynthetic efficiency through a chlorophyll fluorescence meter, analyzing leaf health through a multispectral camera, and recording plant growth rate through a weighing sensor. The real-time data is compared with the preset growth target threshold to calculate the deviation of the current lighting parameters. A PID control algorithm is used to automatically adjust the lighting parameters according to the deviation. For example, if the flower is detected to be elongated (slender stems and sparse leaves), it is determined that the light intensity is low, and the light intensity is gradually increased within the matching range (such as from 6000 Lux to 6500 Lux). If flowering is delayed, the proportion of red light in the photoperiod may be adjusted (such as from 40% to 45%). Several optimization cycles are set in each growth stage (such as fine-tuning parameters once a day) to avoid stress caused by frequent adjustments on the flowers. After each adjustment, it is necessary to wait for the data to stabilize (such as 24 hours) before the next round of feedback correction.

[0030] Preferably, a sequence representation is constructed using light intensity, spectral ratio, and light duration as parameters to create a light trajectory, thereby establishing and outputting the optimal light trajectory for a batch. For example, the light trajectory of a batch of tulips from the seedling stage → bud stage → flowering stage is shown in Table 1:

[0031] Table 1 Light trajectory parameters for tulip growth stages

[0032]

[0033] The control fitting module 30 is used to read the adjustment parameters and position information of the dimmable LED light source when performing lighting control for the same batch of flowers, and then perform control fitting of the dimmable LED light source with the optimal lighting trajectory of the batch as the tracking target to establish a control fitting result.

[0034] Preferably, the control fitting module converts the abstract batch optimal lighting trajectory output by the optimization module into an executable LED light source control scheme to ensure that the theoretical optimal lighting scheme is implemented in the actual planting environment and realizes the accurate reproduction of lighting. Specifically, when executing the lighting control of the same batch of flowers, the adjustment parameters and position information of the dimmable LED light source are read, wherein the adjustment parameters of the dimmable LED light source include the spectral characteristics of each LED light source (such as the RGBW four-channel ratio range), the dimming curve (the nonlinear relationship between current and light intensity), and the light decay coefficient (the influence of usage time on luminous efficiency). The position information refers to the three-dimensional coordinates, illumination angle, and coverage radius of the LED light source in the planting space, which is used to construct a spatial lighting distribution model. For example, the top light source (height 2m, spacing 1.5m) and the side fill light source (height 0.8m, elevation angle 45°) have different light intensity contributions to different parts of the plant.

[0035] Preferably, flowers in standard positions are selected, and the optimal batch illumination trajectory is used as the target to be followed. This trajectory is discretized into a sequence of time slices (e.g., one control cycle per hour). Each time slice contains target parameters, target light intensity distribution (e.g., 6500 Lux on the top of the plant and 4000 Lux on the side), target spectral ratio (e.g., red: blue: green = 5:3:2), and target uniformity (e.g., light intensity difference between plants ≤ ±10%). Then, control fitting of the dimmable LED light source is performed. Specifically, a mapping relationship of "LED parameters → spatial illumination distribution" is established based on optical propagation laws (e.g., Lambert's cosine law):

[0036] ;

[0037] in, Represents the light intensity at a spatial point (x, y, z), represents the power of the i-th LED, Indicates the distance from the LED to the target point, Indicates the angle between the direction of the LED light irradiating the target point and the direction of the LED optical axis. Indicates the angle between the LED light and the LED optical axis in a plane. Indicates the angle between the LED light and another plane (perpendicular to the light-LED optical axis plane). n Indicates the number of dimmable LED light sources, m It is a constant used to adjust the degree of influence of angle on light intensity. For example, when m=1, it is a cosine relationship. The larger the angle (the more inclined the light), the smaller the contribution of light intensity. Indicates the attenuation relationship between light intensity and distance. The farther away from the LED, The larger it is, the greater the light intensity attenuation.

[0038] By adjusting the power and spectral ratio of each LED, the mean square error between the actual light distribution and the target trajectory is minimized. Hardware constraints are then set, including an upper limit on LED power (e.g., a maximum power of 150W for a single lamp), dimming resolution (e.g., a 0.1% step size), and response time (e.g., 50ms for spectrum switching). Energy consumption constraints are set to minimize total energy consumption while meeting lighting requirements. Uniformity constraints are set to ensure that the light intensity difference between any two plants does not exceed a threshold (e.g., ±10%) to avoid local growth inconsistencies. Finally, specific LED light source control instructions are generated for each time slice, as shown in Table 2:

[0039] Table 2 LED light source control instruction table at different times

[0040]

[0041] In addition, according to the photoperiod requirements, the natural light gradient process is simulated during sunrise and sunset (for example, a linear increase from 0 Lux to 6000 Lux within 1 hour). At the same time, zone control is adopted for LED groups in different areas. For example, the power of lamps in edge areas is increased to compensate for light leakage loss. Ultimately, the control fitting results of the dimmable LED light source are obtained.

[0042] The individual feedback module 40 is used to perform growth tracking marking on the flowers of the same batch after executing the dimmable LED light source control using the control fitting result, perform individual adaptive lighting adaptation evaluation based on the growth tracking mark, and establish individual lighting feedback.

[0043] Preferably, the control fitting result obtained by controlling the optimal illumination trajectory of the batch is used to perform the dimmable LED light source control, and the individual feedback module uses a variety of sensors to perform growth tracking marking on the flowers of the same batch. Specifically, data collection of the flowers of the same batch is performed, including using a camera to capture morphological images of the flowers to obtain appearance information such as plant height, number and size of leaves, and number of flowers; using a chlorophyll fluorescence meter to measure parameters related to leaf photosynthetic efficiency to understand the physiological state of the flowers; and then establishing a unique identification for each flower through electronic tags, image recognition feature codes, etc., and associating the flower growth data collected at different time points with the unique identification to realize tracking and recording of the growth process of individual flowers. For example, a QR code label is assigned to each pot of tulips, and the growth stage information of the corresponding plant is entered by scanning the code each time data is collected.

[0044] Preferably, individual adaptive light adaptation evaluation is performed based on growth tracking markers. Specifically, evaluation indicators are set using the growth stages and planting goals of flowers. For example, in the seedling stage, attention is paid to survival rate and leaf health; in the flowering stage, attention is paid to flowering rate, flower size and color, etc.; and reasonable weights are determined for each evaluation indicator. For example, the flowering rate in the flowering stage has a weight of 40%, the flower size has a weight of 30%, and the color has a weight of 30%; then the individual flower growth data obtained by the tracking markers is substituted into the evaluation index system for calculation. For example, if a tulip has a flowering rate of 80% (the corresponding index standard is 70%-90%), a flower size reaches 90% of the standard diameter (the standard is 80%-100%), and a color score of 8 points (out of 10 points), a weighted calculation is performed to obtain the light adaptation score of this tulip in the flowering stage, Finally, the light adaptation evaluation results of each flower are integrated with the unique identification, growth data and other information of the flower to form individual light feedback. For example, a feedback report is generated containing the tulip number, growth data of each stage, light adaptation score and evaluation conclusion (such as "light adaptation is good" and "light intensity needs to be adjusted", etc.).

[0045] The correction module 50 is configured to perform cluster control feedback of the dimmable LED light source using the individual illumination feedback, and perform control fitting result correction according to the cluster control feedback.

[0046] Preferably, the correction module realizes precise and intelligent lighting control through a closed-loop process of data clustering → strategy generation → parameter correction, and uses individual lighting feedback to perform cluster control feedback of the dimmable LED light source. Specifically, the key features that affect the lighting demand are extracted from the individual lighting feedback (growth indicators, lighting adaptation scores and spatial location information of each flower), such as growth progress characteristics such as "fast growth type", "standard type" and "lagging type", spatial distribution characteristics such as "edge area", "central area" and "top area", and lighting response characteristics of "sensitive / tolerant to light intensity". The flowers are divided into 3-5 clusters based on K-means clustering, as shown in Table 3:

[0047] Table 3 Flower clustering results

[0048]

[0049] Then, correction strategies are formulated for different clusters. For example, Cluster 1 (high light demand) increases the light intensity by 15% and extends the lighting time by 1 hour. Cluster 2 (standard demand) maintains the original trajectory and fine-tunes the spectral ratio (such as increasing blue light by 2%). Cluster 3 (low light demand) reduces the light intensity by 10% and adjusts the red light / far-red light ratio to promote internode elongation. The correction strategy is then converted into LED control parameter adjustment amounts, and the clustering frequency is dynamically adjusted according to the growth stage. For example, clustering is performed once a week in the seedling stage (growth differences are small), once every 3 days in the rapid growth period (differences expand), and once a day in the flowering period (fine control is required). Finally, the control fitting results are corrected, and the lighting plan is dynamically optimized to reduce unnecessary light redundancy while ensuring growth effects.

[0050] Furthermore, the specific configuration of the correction module 50 also includes a cluster matching submodule, which is used to obtain the individual position coordinates of individual flowers in the same batch, and perform association clustering of individual flowers in the same batch with dimmable LED light sources based on the individual position coordinates and the position information to establish an association clustering result; a feedback authentication submodule, which is used to perform feedback adaptation evaluation of the group based on the association clustering result and the individual lighting feedback, and establish cluster control feedback using the feedback adaptation evaluation result.

[0051] Preferably, through positioning technology (such as arranging positioning sensors in the flower planting area, or using image recognition combined with coordinate calibration), the position coordinates of each flower in the same batch in the planting space are accurately obtained, and the specific position of the flowers in the planting environment such as greenhouses and flower houses is clarified, such as whether it is in the corner of the greenhouse, the middle area, or near the window, etc.; then, combined with the obtained individual position coordinates and the position information of the dimmable LED light source (such as how high the LED light source is installed above the flower, in which direction of the flower, etc.), the relative position relationship between each flower and each dimmable LED light source is analyzed, and then the individual flowers in the same batch are associated with the dimmable LED light sources and clustered. For example, flowers with similar distances and the corresponding LED light sources are classified into one category, or flowers that are mainly illuminated by the same group of LED light sources are divided into a cluster, and finally the associated clustering results are established to clarify the corresponding relationship between different individual flowers and LED light sources.

[0052] Preferably, a comprehensive evaluation is performed on each cluster based on the associated clustering results and individual light feedback (including information such as the growth status of each flower plant and light adaptation evaluation), including evaluating whether the overall growth consistency of the flowers in the cluster (such as differences in plant height, flowering time, etc.), the degree of adaptation to the current light conditions (judged by the light adaptation score), etc. are within a reasonable range, and whether most flowers show good adaptability to the current light; and then, based on the results of the feedback adaptation evaluation, a light adjustment strategy is determined for each cluster group, thereby establishing cluster control feedback. For example, if the evaluation finds that the flowers in a certain cluster group grow slowly and have a low light adaptation score, the conclusion is drawn that the light intensity of the corresponding LED light source of the group is increased or the spectral ratio is adjusted; if the growth of flowers in the group is relatively consistent and the adaptation score is high, the current light conditions are maintained or only fine-tuned.

[0053] Furthermore, the specific configuration of the feedback authentication submodule also includes a key positioning unit, which is used to perform array intersection identification of the dimmable LED light source based on the position information, locate the array intersection area, and locate the key flowers of the same batch based on the array intersection area and the individual position coordinates; a penalty compensation unit, which is used to perform execution fitting of the dimmable LED light source based on the cluster control feedback, and perform adaptation analysis on the key flowers of the same batch, and establish penalty compensation based on the adaptation analysis results; an optimization unit, which is used to optimize the corrected control fitting results based on the penalty compensation.

[0054] Preferably, based on the position information of the dimmable LED light source (such as installation coordinates, irradiation direction, etc.), the intersection of the light from each LED light source is analyzed to determine the area where the light from different LED light sources intersects in the planting space, that is, the array intersection area; and then combined with the position coordinates of individual flowers from the same batch, find out the individual flowers located in the key array intersection area and use them as the key flowers from the same batch. Based on the lighting adjustment strategy for different cluster groups determined by the cluster control feedback, the operating parameters of the dimmable LED light source (such as power, spectral ratio, lighting duration, etc.) are adjusted and fitted to make them meet the expected lighting control requirements as much as possible. Then, for the key flowers of the same batch located by the key positioning unit, their adaptation under the lighting conditions after fitting is analyzed, including evaluating whether the growth indicators of the flowers (such as plant height, leaf health, flowering status, etc.) are improved due to the lighting adjustment, or whether new mismatch problems arise. For example, observing whether the leaves of the flowers show signs of burning (too strong light) or whether growth is still slow (insufficient light). Then, based on the adaptation analysis results, if it is found that some key flowers are not well adapted to the growth after the lighting adjustment, a corresponding penalty compensation mechanism is established. If the light is too strong and causes burns to the flowers, the power of the corresponding LED light source is reduced (penalty); if the light is insufficient, the power of nearby LED light sources is increased or the spectrum is adjusted (compensation). Finally, penalty compensation measures are used to optimize the control fitting results, that is, to optimize and adjust the lighting control scheme to ensure that the lighting conditions can not only meet the growth needs of flowers, but also achieve the best lighting effect overall, thereby improving the overall growth quality of flowers.

[0055] Furthermore, the specific configuration of the joint matching module 10 also includes extracting flower features of the batch of flowers, using the flower feature extraction results and the growth stage identification results as matching features, performing similarity matching of the historical database, and establishing a first joint illumination interval based on the similarity matching results, and the first joint illumination interval is set with a similarity weight; conducting an illumination experiment test on the batch of flowers under the growth stage identification results, and establishing a second joint illumination interval based on the illumination experiment test results, and the second joint illumination interval is set with a stable weight; completing the joint matching of the illumination intervals based on the first joint illumination interval, the second joint illumination interval, the similarity weight, and the stable weight, and establishing a matching illumination interval.

[0056] Preferably, a comprehensive observation and measurement of flowers in the same batch is carried out to extract features that can reflect their characteristics, which may include flower varieties (such as tulips, roses), plant morphology (plant height, stem thickness, leaf shape and size, etc.), and physiological characteristics (such as chlorophyll content, photosynthetic rate, etc.). The flower extraction results and the growth stage identification results are then used as matching features for similarity matching in the historical database, where the historical database stores a large amount of characteristic information of flowers at different growth stages and the corresponding suitable light intervals, etc. Then, based on the similarity matching results (i.e., the light intervals corresponding to similar records), a first joint light interval is established, and a similarity weight is set. The higher the degree of similarity, the greater the weight, indicating that the interval is more reliable as a reference. During the growth phase of the current batch of flowers, a lighting experiment is conducted. This involves setting different combinations of lighting conditions, such as varying light intensities, spectral ratios, and durations. The growth responses of the flowers under these conditions are then observed and recorded. This includes measuring their growth rate (e.g., changes in plant height and leaf count), changes in physiological indicators (e.g., photosynthetic efficiency and nutrient accumulation), and appearance (e.g., leaf color and flower development). This allows the selection of a range of lighting conditions that promotes optimal flower growth. This allows the establishment of a second combined lighting interval, which is then assigned a stable weight to reflect its stability and reliability in reflecting the current light needs of the flowers. Finally, the first and second combined lighting intervals are weighted and fused to determine a matching lighting interval for optimal light control and regulation of the flowers.

[0057] Furthermore, the specific configuration of the individual feedback module 40 also includes using an image acquisition device to perform time-series image acquisition of the same batch of flowers to establish a time-series image data set; calling the zero-point image in the time-series image data set, using the zero-point image as the reference image, performing frame-by-frame image comparison of the time-series image data set, and establishing a frame image comparison deviation; using the frame image comparison deviation to perform growth tracking fitting to complete growth tracking marking.

[0058] Preferably, an image acquisition device (such as a camera, etc.) is used to continuously photograph the same batch of flowers at fixed time intervals (such as every day or every hour), and images at different time points are obtained to form a time-series image dataset, recording the appearance changes of the flowers during the growth process (such as leaf expansion, flower opening, plant height growth, color change, etc.). Then, an image at an initial time point (such as the image at the beginning of the experiment) is selected from the time-series image dataset as the zero-point image, and then a frame-by-frame image comparison of the time-series image dataset is performed using the zero-point image as the reference image, that is, each frame image in the dataset is compared with the zero-point image at the pixel level. For example, image processing (such as edge detection and feature point matching) is used to identify differences in the image, including changes in plant morphology (increase in the number of leaves, elongation of stems, changes in flower size, etc.), position movement (changes in plant posture), and color or texture changes (such as yellowing of leaves, color change of petals, etc.). The difference between each frame image and the reference image is quantified as a comparison deviation, such as the change in plant height, the rate of change in leaf area, the degree of flower opening, etc. Then, growth tracking fitting is performed based on the comparison deviation data to determine the dynamic growth trend of flowers. For example, according to the plant height deviation at different time points, a "plant height-time" growth curve is fitted; according to the change in the number of leaves, the leaf growth rate is fitted; finally, the dynamic growth trend of flowers and the actual image deviation are combined to mark the key growth node features in the time series image. For example, labels are added to images of different growth stages (such as "5th day of seedling stage" and "3rd day of flowering stage").

[0059] Furthermore, the specific configuration of the control fitting module 30 also includes a cross-stage identification module, which is used to read the growth status data of the flowers in the same batch before executing the lighting control of the flowers in the same batch, establish a growth prediction result, and judge whether the growth prediction result meets the cross-stage interval threshold; a constraint establishment module, which is used to establish a cross-stage lighting constraint if the growth prediction result meets the cross-stage interval threshold, and complete the control fitting after constraining the optimal lighting trajectory of the batch according to the cross-stage lighting constraint.

[0060] Preferably, before controlling the light of the same batch of flowers, the current growth status data of the batch of flowers (such as plant height, number of leaves, physiological indicators, growth rate, etc.) are obtained, and the future growth trend of the flowers is predicted by combining the historical growth data and environmental parameters through a time series prediction model to form a growth prediction result; then, the transition thresholds between different growth stages are preset (such as the plant height threshold from the seedling stage to the growth stage, the accumulated temperature threshold from the bud stage to the flowering stage, etc.), and the growth prediction results are compared with these thresholds to determine whether the flowers may enter the next growth stage ahead of schedule or delayed. For example, if the prediction result shows that the flowers will reach the plant height threshold of the bud stage within 3 days, it is determined that the "cross-stage interval threshold" is met, that is, the growth progress may exceed the expected range of the current stage. If the growth prediction result meets the cross-stage threshold, the cross-stage lighting constraint is established according to the lighting requirements of the next stage. For example, if the plant is currently in the seedling stage but is predicted to enter the growth stage, the lighting parameters of the growth stage (such as higher light intensity, different spectral ratios) need to be introduced in advance as constraints, which may include the lower or upper limit of the lighting range of the next stage (such as light intensity must be ≥6000Lux, and the proportion of red light must be ≥40%); finally, the cross-stage lighting constraint is superimposed on the original batch optimal lighting trajectory, and it is corrected and controlled to ensure that the lighting control is synchronized with the actual growth progress of the flowers, avoiding growth problems caused by stage mismatch (such as insufficient light affecting flower quality when flowering early).

[0061] Furthermore, the specific configuration of the control fitting module 30 also includes performing control fitting of the batch optimal lighting trajectory according to the adjustment parameters and position information to establish an initial fitting scheme; activating the light sensor at the standard position, monitoring the lighting data through the light sensor, and establishing a lighting response; establishing residual feedback according to the lighting response and the lighting residual of the batch optimal lighting trajectory; using the residual feedback to update the initial fitting scheme and establish a control fitting result.

[0062] Preferably, according to the adjustment parameters (such as power, spectral ratio, lighting duration, etc.) and position information (such as lamp coordinates, illumination angle) of the dimmable LED light source, combined with the theoretical parameters of the batch optimal lighting trajectory (such as target light intensity and spectral distribution at each time point), preliminary control fitting is performed through light propagation path calculation and light intensity attenuation formula, and an initial fitting scheme is generated to make the LED light source output close to the target trajectory; then, light sensors are deployed at standard positions in the planting space (such as above the flower canopy and near typical plants) to monitor the actual light data (such as current light intensity, spectral composition, and uniformity) in real time, and the monitored data is compared with the target value of the initial fitting scheme to form a light response. For example, if the target light intensity is 6500Lux and the sensor measures 6200Lux, the light response shows a deviation of 300Lux; if the target red light ratio in the spectrum is 45% and the measured value is 40%, the red light channel power needs to be adjusted.

[0063] Preferably, the illumination residual between the actual illumination data and the batch optimal illumination trajectory is calculated, that is, the difference between the target value and the measured value, including the illumination intensity residual, spectral residual and uniformity residual, and these residuals are integrated into residual feedback to clarify the execution deviation direction and degree of the initial fitting scheme; finally, the initial fitting scheme is iteratively adjusted based on the residual feedback. Specifically, for the intensity residual, the LED power is proportionally adjusted (for example, if the light intensity is less than 5%, the relevant LED power is increased by 5%); for the spectral residual, the ratio of each channel is fine-tuned (for example, if the red light ratio is 5% lower, the red light channel power is increased by 5%); if the uniformity residual exceeds the standard, the power compensation of the LED in the edge area is increased (for example, the power of the edge lamp is increased by 8%), or the illumination angle is adjusted to reduce occlusion; dynamic iteration is performed until the residual is reduced to the allowable range (for example, the light intensity error is ≤±3%, the spectral ratio error is ≤±2%), and finally the control fitting result is generated to ensure that the LED light source output is highly consistent with the batch optimal illumination trajectory.

[0064] Furthermore, the specific configuration of a light intensity adaptive adjustment system for flower planting also includes an array monitoring module, which is used to monitor the array light deviation of all dimmable LED light sources and generate array light deviation monitoring results; an early warning response module, which is used to perform deviation trigger verification on the array light deviation monitoring results and issue a balance abnormality early warning.

[0065] Preferably, array illumination deviation monitoring is performed on all dimmable LED light sources, that is, the actual illumination data of each light source (such as light intensity, spectrum, irradiation angle, uniformity, etc.) is collected through a sensor network (such as a multi-node light intensity meter, a spectrometer) deployed in the planting area or a feedback device provided by the light source, and the output status of all dimmable LED light sources is monitored in real time, and compared with the preset target parameters (such as the light intensity that the light source should output in the current period is 6000 Lux, red light: blue light = 3:1), to form an array illumination deviation monitoring result; then a threshold range of illumination deviation is preset (such as the single light source light intensity deviation is allowed to be ±5%, the spectrum ratio deviation is allowed to be ±5%). ±3%, regional uniformity deviation ±10%), and then verify the array illumination deviation monitoring results to determine whether they exceed the threshold. When a deviation exceeding the threshold is detected, a balance abnormality warning is reported. The warning content clearly specifies the type, location and degree of the abnormality, such as "Warning: The light intensity of the light source in the 2nd row and 5th column is abnormally low (-8.3%), which may cause insufficient lighting for flowers in this area." This reminds the operator to promptly check the problem (such as light source failure, occlusion, parameter drift, etc.) to avoid flower growth differences due to uneven lighting (such as some plants growing too long and some being stunted), and ensure the consistency, stability and quality of flowers in the same batch in the lighting environment.

[0066] In the above, refer to Figure 1The light intensity adaptive adjustment system for flower planting according to the embodiment of the present invention is described in detail. Figure 2 A method for adaptively adjusting light intensity for flower planting according to an embodiment of the present invention is described. Figure 2 As shown, the method includes: performing growth stage identification on batches of flowers, using the growth stage identification results to perform joint matching of lighting intervals, and establishing matching lighting intervals; using the matching lighting intervals as an optimization space, using a dynamic feedback channel in the optimization space to perform feedback correction on the flower growth effect, and establishing a batch optimal lighting trajectory; when performing lighting control on the same batch of flowers, after reading the adjustment parameters and position information of the dimmable LED light source, taking the batch optimal lighting trajectory as a tracking target, performing control fitting of the dimmable LED light source, and establishing a control fitting result; after performing control of the dimmable LED light source using the control fitting result, performing growth tracking marking on the flowers in the same batch, performing individual adaptive lighting adaptation evaluation based on the growth tracking marking, and establishing individual lighting feedback; using the individual lighting feedback to perform cluster control feedback of the dimmable LED light source, and correcting the control fitting result based on the cluster control feedback.

[0067] In one possible implementation, the method for adaptively adjusting light intensity for flower planting further includes: a cluster matching submodule, used to obtain the individual position coordinates of individual flowers in the same batch, and to perform association clustering of individual flowers in the same batch with dimmable LED light sources based on the individual position coordinates and the position information, to establish an association clustering result; a feedback authentication submodule, used to perform feedback adaptation evaluation of the group based on the association clustering result and the individual lighting feedback, and to establish cluster control feedback using the feedback adaptation evaluation result.

[0068] In one possible implementation, the method for adaptively adjusting light intensity for flower planting also includes: a key positioning unit, used to perform array intersection identification of dimmable LED light sources based on the position information, locate the array intersection area, and locate key flowers of the same batch based on the array intersection area and the individual position coordinates; a penalty compensation unit, used to perform execution fitting of the dimmable LED light source based on the cluster control feedback, and perform adaptation analysis on the key flowers of the same batch, and establish penalty compensation based on the adaptation analysis results; an optimization unit, used to optimize the corrected control fitting results based on the penalty compensation.

[0069] In a possible implementation, the method for adaptively adjusting light intensity for flower planting also includes: extracting flower characteristics of the batch of flowers, using the flower characteristic extraction results and the growth stage identification results as matching features, performing similarity matching of the historical database, and establishing a first joint lighting interval based on the similarity matching results, and the first joint lighting interval is set with a similarity weight; conducting a lighting experiment test on the batch of flowers under the growth stage identification results, and establishing a second joint lighting interval based on the lighting experiment test results, and the second joint lighting interval is set with a stable weight; completing the joint matching of the lighting intervals based on the first joint lighting interval, the second joint lighting interval, the similarity weight, and the stable weight to establish a matching lighting interval.

[0070] In a possible implementation, the method for adaptively adjusting light intensity for flower planting also includes: using an image acquisition device to perform time-series image acquisition of flowers in the same batch to establish a time-series image data set; calling the zero-point image in the time-series image data set, using the zero-point image as the reference image, performing frame-by-frame image comparison of the time-series image data set, and establishing a frame image comparison deviation; using the frame image comparison deviation to perform growth tracking fitting to complete growth tracking marking.

[0071] In one possible implementation, the method for adaptively adjusting light intensity for flower planting also includes: a cross-stage identification module, which is used to read the growth status data of the same batch of flowers before executing light control of the same batch of flowers, establish a growth prediction result, and judge whether the growth prediction result meets the cross-stage interval threshold; a constraint establishment module, which is used to establish a cross-stage lighting constraint if the growth prediction result meets the cross-stage interval threshold, and complete the control fitting after constraining the optimal lighting trajectory of the batch according to the cross-stage lighting constraint.

[0072] In one possible implementation, the method for adaptively adjusting light intensity for flower planting further includes: performing control fitting of a batch optimal light trajectory according to the adjustment parameters and position information, and establishing an initial fitting scheme; activating a light sensor at a standard position, monitoring light data through the light sensor, and establishing a light response; establishing residual feedback according to the light response and the light residual of the batch optimal light trajectory; and using the residual feedback to update the initial fitting scheme and establish a control fitting result.

[0073] In one possible implementation, the method for adaptively adjusting light intensity for flower planting also includes: an array monitoring module, which is used to perform array light deviation monitoring on all dimmable LED light sources and generate array light deviation monitoring results; an early warning response module, which is used to perform deviation trigger verification on the array light deviation monitoring results and issue a balance abnormality early warning.

[0074] The light intensity adaptive adjustment system for flower planting provided by an embodiment of the present invention can execute the light intensity adaptive adjustment method for flower planting provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0075] Based on the foregoing embodiments, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it can implement a light intensity adaptive adjustment system for flower planting as described in any of the previous embodiments.

[0076] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0077] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A light intensity adaptive adjustment system for flower planting, characterized in that: The system comprises: A joint matching module is used to perform growth stage recognition of batches of flowers, and use the growth stage recognition results to perform joint matching of light intervals to establish matching light intervals; An optimization module is used to use the matching illumination interval as an optimization space, perform feedback correction on the flower growth effect by using a dynamic feedback channel in the optimization space, and establish an optimal illumination trajectory for a batch; A control fitting module is used to read the adjustment parameters and position information of the dimmable LED light source in the lighting control of the same batch of flowers, perform control fitting of the dimmable LED light source with the optimal lighting trajectory of the batch as the tracking target, and establish a control fitting result; An individual feedback module is configured to perform growth tracking marking on the flowers of the same batch after executing the dimmable LED light source control using the control fitting result, perform individual adaptive lighting adaptation evaluation based on the growth tracking marking, and establish individual lighting feedback; a correction module, configured to perform cluster control feedback of the dimmable LED light source using the individual illumination feedback, and perform control fitting result correction according to the cluster control feedback; The correction module includes: A cluster matching submodule is used to obtain the individual position coordinates of individual flowers in the same batch, perform association clustering between the individual flowers in the same batch and the dimmable LED light source based on the individual position coordinates and the position information, and establish an association clustering result; A feedback authentication submodule, configured to perform group feedback adaptation evaluation based on the associated clustering results and the individual illumination feedback, and establish cluster control feedback using the feedback adaptation evaluation results; The feedback authentication submodule includes: A key positioning unit, configured to identify the array intersection of the dimmable LED light source according to the position information, locate the array intersection area, and locate the key flowers of the same batch according to the array intersection area and the individual position coordinates; A penalty compensation unit, configured to perform execution fitting of the dimmable LED light source according to the cluster control feedback, perform adaptation analysis on the key flowers of the same batch, and establish penalty compensation according to the adaptation analysis results; an optimization unit, configured to optimize the corrected control fitting result according to the penalty compensation; In the joint matching module, the growth stage recognition results are used to perform joint matching of illumination intervals to establish matching illumination intervals, including: Extracting flower features of the batch of flowers, using the flower feature extraction results and the growth stage identification results as matching features, performing similarity matching on a historical database, and establishing a first joint illumination interval based on the similarity matching results, wherein the first joint illumination interval is set with a similarity weight; Conducting a lighting experiment test on a batch of flowers based on the growth stage identification result, and establishing a second joint lighting interval based on the lighting experiment test result, wherein the second joint lighting interval is set with a stable weight; completing joint matching of illumination intervals according to the first joint illumination interval, the second joint illumination interval, the similarity weight, and the stability weight, and establishing a matching illumination interval; The individual feedback module performs growth tracking marking on the flowers of the same batch, including: Using an image acquisition device to perform time-series image acquisition of flowers in the same batch, and establishing a time-series image dataset; Calling a zero-point image in a time-series image dataset, using the zero-point image as a reference image, performing frame-by-frame image comparison of the time-series image dataset, and establishing a frame image comparison deviation; The frame image comparison deviation is used to perform growth tracking fitting to complete growth tracking labeling.

2. The light intensity adaptive adjustment system for flower planting according to claim 1, characterized in that: The control fitting module also includes: A cross-stage identification module is used to read the growth status data of the flowers in the same batch before executing the light control of the flowers in the same batch, establish a growth prediction result, and determine whether the growth prediction result meets the cross-stage interval threshold; The constraint establishment module is used to establish a cross-stage illumination constraint if the growth prediction result meets the cross-stage interval threshold, and complete the control fitting after constraining the batch optimal illumination trajectory according to the cross-stage illumination constraint.

3. The light intensity adaptive adjustment system for flower planting according to claim 1, characterized in that: In the control fitting module, the control fitting of the dimmable LED light source is performed with the batch optimal illumination trajectory as the tracking target, and a control fitting result is established, including: Perform control fitting of batch optimal lighting trajectories according to the adjustment parameters and position information, and establish an initial fitting scheme; activating a light sensor at a standard position, monitoring light data through the light sensor, and establishing a light response; Establishing residual feedback based on the illumination response and the illumination residual of the batch optimal illumination trajectory; The residual error feedback is used to update the initial fitting solution and establish a control fitting result.

4. The light intensity adaptive adjustment system for flower planting according to claim 1, characterized in that: The system further comprises: The array monitoring module is used to monitor the array illumination deviation of all dimmable LED light sources and generate array illumination deviation monitoring results; The early warning response module is used to perform deviation trigger verification on the array illumination deviation monitoring result and report a balance abnormality early warning.

5. A method for adaptively adjusting light intensity for flower planting, characterized in that: The method is applied to a light intensity adaptive adjustment system for flower planting according to any one of claims 1 to 4, and the method comprises: Perform growth stage recognition of batches of flowers, use the growth stage recognition results to perform joint matching of light intervals, and establish matching light intervals; The matching illumination interval is used as an optimization space, and a dynamic feedback channel is used within the optimization space to perform feedback correction on the flower growth effect to establish an optimal illumination trajectory for a batch; In the light control of the same batch of flowers, after reading the adjustment parameters and position information of the dimmable LED light source, the optimal light trajectory of the batch is used as the tracking target, and the control fitting of the dimmable LED light source is performed to establish the control fitting result; After using the control fitting result to perform the dimmable LED light source control, growth tracking marking is performed on the flowers of the same batch, and individual adaptive light adaptation evaluation is performed according to the growth tracking marking to establish individual light feedback; Cluster control feedback of the dimmable LED light source is performed using the individual illumination feedback, and control fitting result correction is performed according to the cluster control feedback.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a light intensity adaptive adjustment system for flower planting according to any one of claims 1 to 4 is implemented.

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