Systems and methods for controlling plant growth

Abstract

The present invention provides a system (10) for controlling plant growth, comprising at least one lighting device (1), at least one sensor (2), and a processor (3), wherein the lighting device (1) irradiates light of variable spectra toward the plant, the sensor (2) is configured to detect growth parameters of the plant, and the processor is configured to analyze the growth parameters detected by the sensor. The processor (3) is further configured to control various combinations of light spectra based on the growth parameters, such that the light spectra are combined in ratios to enable customization of lighting conditions for different plants. The present invention also relates to a method for controlling plant growth, comprising the steps of detecting plant growth parameters by the at least one sensor, analyzing the detected growth parameters by the processor, and irradiating light by the at least one lighting device in RGB ratios to enable customization of lighting conditions for different plants.

Description

[Technical Field]

[0001] RELATED APPLICATIONS This invention claims priority to Singapore Patent Application No. 10202251653Q filed on November 7, 2022, the entire disclosure of which is incorporated herein by reference.

[0002] The present invention relates to agricultural technology, and more particularly to an AI-driven LED grow light system for controlled environment agriculture. [Background technology]

[0003] In recent years, there has been a significant shift toward controlled environment agriculture (CEA) methods of farming, driven by the demand for efficient and sustainable food production. Controlled environment agriculture refers to growing crops indoors under precise conditions optimized for plant growth. This method allows farmers to have complete control over factors such as temperature, humidity, light, and nutrients, resulting in higher yields, reduced environmental impact, and better resource utilization.

[0004] Among the various factors that affect plant growth, light is one of the most important. Plants require specific light wavelengths, intensities, and durations for photosynthesis, the process by which light energy is converted into chemical energy that enables plant growth and development. Traditional agricultural lighting systems, such as high-pressure sodium (HPS) lamps and metal halide (MH) lamps, have been used for decades. However, these systems are energy intensive, emit excessive heat, and often lack the precise spectrum necessary for optimal plant growth.

[0005] In conventional grow light panels, the fixed ratio of red to blue light emitted by the fixed LEDs prevents optimal plant growth. Different growth stages of plant growth require varying ratios of red to blue light to increase productivity. Blue light spectrum promotes chlorophyll absorption, photosynthesis, and growth, while red light spectrum stimulates the flowering and germination process. However, existing grow lights available on the market lack the ability to adjust the red-to-blue light ratio, limiting their potential for increasing plant growth productivity.

[0006] In existing grow light systems, all LEDs remain on continuously during operation, leading to inefficient energy use throughout the growth cycle. During the initial seedling stage, when plants are small and require less light, the illumination area from the grow light panel can be reduced, effectively saving energy. Furthermore, current grow lights lack the ability to adjust photosynthetic photon flux (PPF) based on plant height. As crops grow taller, they naturally grow closer to the light source, causing an increase in PPFD (photon flux density). If the received PPFD exceeds the required amount, it results in wasted light energy. Therefore, there is a need for an AI-enabled grow light system that automatically reduces energy output as crops grow taller, ensuring optimal energy utilization and promoting sustainable farming practices. Summary of the Invention [Problem to be solved by the invention]

[0007] The objective of this invention is to integrate artificial intelligence (AI) with LED (light-emitting diode) technology to create an AI-driven LED grow light system. The lighting system combines the energy efficiency and flexibility of LED technology with the intelligence of AI algorithms to provide customized lighting conditions to meet the specific needs of different crops. The AI-enabled grow light system controls the intensity of light reaching plants at different growth stages, manipulates different visible wavelength spectrums to suit different plant species at various growth stages, and optimizes light penetration in controlled environment agriculture to save electrical energy. [Means for solving the problem]

[0008] The present invention provides a system for controlling plant growth, comprising: at least one lighting device, at least one sensor, and a processor, wherein the lighting device irradiates light with variable spectra toward the plant, the sensor is configured to detect a growth parameter of the plant, and the processor is configured to analyze the growth parameter detected by the sensor. The processor is further configured to control different combinations of light spectrums based on the growth parameter, such that the light spectrums are combined in ratios to allow customization of lighting conditions during different stages of plant growth.

[0009] Preferably, the lighting device comprises a plurality of light emitting diodes (LEDs) configured to emit red, green and blue light.

[0010] Preferably, the light emitting diodes are arranged on either or both of the inner and outer sides of the panel of the lighting device.

[0011] Preferably, the inner portion comprises at least three separate blocks of light emitting diodes.

[0012] Preferably, the sensor includes any one or a combination of an ultrasonic sensor, a camera, a humidity sensor, and a temperature sensor.

[0013] Preferably, said growth parameters include, but are not limited to, plant type, plant health, plant growth stage and environmental conditions.

[0014] Preferably, the processor includes a light adjustment module configured to control one or more settings of the lighting device.

[0015] Preferably, the settings include any one or combination of light intensity, light spectrum type, irradiation duration, and light spectrum ratio.

[0016] Preferably, the processor includes an optimization module configured to analyze the detected growth parameters using artificial intelligence.

[0017] Preferably, the optimization module is further configured to optimize and adjust the settings of the lighting devices to the detected growth parameters to generate personalized lighting profiles for different plants.

[0018] The present invention aims to provide a method for controlling plant growth, comprising the steps of detecting a growth parameter of a plant by at least one sensor, analyzing the detected growth parameter by a processor, and irradiating light towards the plant by at least one lighting device, wherein the processor is further configured to control different combinations of light spectrums based on the growth parameter, such that the light spectrums are combined in ratios to allow customization of lighting conditions for different plants.

[0019] Preferably, the method further comprises the step of analysing the growth parameters using artificial intelligence by an optimisation module.

[0020] Preferably, the method further comprises optimizing, by the optimization module, settings of the lighting devices based on the growth parameters to generate customized lighting profiles for different plants.

[0021] Preferably, the method further comprises storing the growth parameter dataset and customized lighting profiles for different plants in a computer readable storage module.

[0022] Preferably, the method further comprises the step of executing, by the processor, instructions for optimizing the settings of the lighting device based on the detected growth parameters.

[0023] Preferably, the method further comprises executing, by the processor, instructions for adjusting a ratio of a light spectrum comprising red light, green light and blue light based on the lighting profile customized for different plants.

[0024] One skilled in the art will readily appreciate that the present invention is well adapted to carry out the objects and attain the ends and advantages mentioned, as well as those inherent therein. The embodiments described herein are not intended to limit the scope of the invention. [Brief explanation of the drawings]

[0025] To facilitate an understanding of the invention, there are illustrated preferred embodiments in the accompanying drawings, and by considering these embodiments in conjunction with the following description, the invention, its construction and operation, and its many advantages will be readily understood and appreciated.

[0026] [Figure 1] FIG. 1 illustrates a system for controlling plant growth according to one embodiment of the present invention. [Figure 2] FIG. 2 is a perspective view of the lighting device used in FIG. 1. [Figure 3]FIG. 10 is a diagram showing the tabulated results showing the relationship between height and illuminance during an experiment demonstrating the present invention. [Figure 4] FIG. 4 is a graph showing the relationship between height and illuminance obtained from the data of FIG. 3. [Figure 5] 10 is a flowchart of a method for turning outer portion LEDs on or off based on detected growth parameters. [Figure 6] 1 is a flow chart of a method for controlling plant growth. DETAILED DESCRIPTION OF THE INVENTION

[0027] [Part 1 Introduction] From this specification, spatially relative terms such as "top," "bottom," "left," "right," "inside," "outside," etc. may be used herein for ease of explanation to describe the relationship of one technical element or feature to another, as shown in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the technical features during use or operation in addition to the orientation depicted in the figures.

[0028] For example, if the technical features in the drawings were inverted, elements described as "above" other elements or features would then be oriented "below" the other elements or features. Thus, the exemplary term "above" can encompass both an orientation of above and below. Devices may be oriented otherwise, and the spatially relative descriptors used herein would be interpreted accordingly.

[0029] For example, if a technical feature in the drawings were flipped horizontally, that element described as being "to the left" of another element or feature would then be oriented to the "right" of that other element or feature. Thus, the exemplary term "left" can encompass both left and right orientations. Devices may be oriented in other directions, and the spatially relative descriptors used herein would be interpreted accordingly.

[0030] The invention will now be described in more detail, by way of example, with reference to the drawings, in which: For ease of reference, a common reference number or series of numbers will be used throughout the figures to refer to the same or similar features common to the figures. [Part 2: Explanation of Figures 1 and 2]

[0031] FIG. 1 illustrates a plant growth control system 10, including several components: at least one lighting device 1 configured to project variable-spectrum light toward plants; at least one sensor 2 positioned to detect relevant growth parameters; and a processor 3 with algorithms for analyzing growth parameter data collected by the sensor. Also shown in FIG. 1 is a computer-readable storage module 4 connected to the sensor 2 and the processor 3. The lighting device 1 is a module containing multiple light-emitting diodes (LEDs) configured to emit light with an adjustable or programmable spectrum. These LEDs can produce a wide range of wavelengths, including, but not limited to, red, blue, and green. The LEDs can be selected from any one or combination of transparent tri-color common-cathode LEDs, diffuse tri-color common-anode LEDs, and diffuse LEDs. The lighting device 1 is positioned in close proximity to plants to effectively illuminate them. The LEDs are positioned on either or both of the inner and outer portions 1b and 1a of the panel of the lighting device 1, as shown in FIG. 2. The inner portion 1b includes at least three separate blocks of LEDs that are separately controlled and operated to conserve energy consumption.

[0032] Preferably, transparent tri-color common-cathode LEDs are incorporated into the lighting device 1 to emit light toward plants. Advantageously, transparent tri-color common-cathode LEDs have a smaller viewing angle than other LEDs, providing excellent uniformity and irradiance, providing concentrated illumination within a specific area, resulting in a higher photosynthetic photon flux density (PPFD) across the illuminated surface while minimizing energy loss, making them ideal for supporting plant growth at various stages. Furthermore, the LED arrangement allows for independent operation of the red, blue, and green plates within a single LED unit. Adjustment can be achieved by coding or by incorporating a variable resistor, facilitating the creation of various RGB (red, green, blue) ratios tailored to specific plant needs. The higher the resistance of the variable resistor, the lower the current, which results in lower irradiance. Conversely, to achieve higher irradiance / PPFD for plants, a lower resistance can be used to pass a larger current. Since there are three colors, three common cathode LEDs can be lit and the intensity of each light color can be varied using three variable resistors.

[0033] By programming the LEDs to vary the intensity of the red, green, and blue light, different RGB ratios can be set for individual LEDs to obtain the desired RGB ratio. Light intensity can be reduced by inputting a smaller current into the LED. The color of the LEDs that light up can be programmed using a microcontroller and code programming. In one exemplary embodiment, if a 2:1 RB ratio is required, for example, for growing lettuce, the intensity of the red light can be set to twice the intensity of the blue light.

[0034] The sensor 2 may include any one or a combination of an ultrasonic sensor, a camera, a humidity sensor, and a temperature sensor that detects plant growth parameters and transmits data to the processor 3. Growth parameters include, but are not limited to, plant type, plant health, plant growth stage, and environmental conditions. The ultrasonic sensor can be used to accurately measure the distance between the sensor and the plant. The ultrasonic sensor provides data on the plant's height and growth rate, allowing the system to adjust the lighting device 1 accordingly. The camera can be used to capture high-resolution images of the plant in the controlled environment. Image processing algorithms analyze the captured images to evaluate the plant's growth parameters. The humidity sensor continuously monitors the plant's moisture level, and the temperature sensor measures the ambient temperature in the controlled environment, which is important for regulating plant metabolism. By analyzing the combined data from the ultrasonic sensor, the camera, the humidity sensor, and the temperature sensor, the plant's growth pattern, health, and environmental conditions can be identified and processed by the processor 3.

[0035] The processor 3 comprises software algorithms tailored to plant growth analysis. The processor 3 receives data from the sensor 2 and processes this information in real time. The processor 3 is programmed to recognize different plant species and their growth parameters detected by the sensor 2 and to control different combinations of light spectra based on the growth parameters, such that the light spectra are combined in ratios to allow customization of lighting conditions during different stages of plant growth.

[0036] The processor 3 includes an optimization module 3a configured to analyze the detected growth parameters using artificial intelligence. The optimization module 3a is further configured to optimize the settings of the lighting device 1 to adjust to the detected growth parameters to generate customized lighting profiles for different plants. Preferably, artificial intelligence algorithms are used to interpret the growth parameters and optimize the settings of the lighting device 1. By way of example, machine learning, data analysis or any other AI techniques can be used to process the data collected by the sensor 2.

[0037] The processor 3 also includes a light adjustment module 3b configured to control one or more settings of the lighting device 1. The settings of the lighting device 1 include any one or combination of light intensity, type of light spectrum, duration of irradiation, and light spectrum ratio. Preferably, the light adjustment module 3b controls light intensity because some plants grow in bright direct light and some plants prefer dim indirect light. Preferably, the light adjustment module 3b can control the range of wavelengths of light emitted by the lighting device 1. Different wavelengths of light have different effects on plant growth. For example, blue light is important for plant growth, while red light is important for flowering and fruiting. By adjusting the type of light spectrum, the lighting system 10 can respond to specific growth stages of plants.

[0038] In one exemplary embodiment, for plants that require extended light exposure, the light adjustment module 3b adjusts the settings to increase the duration of the photoperiod to ensure the plants receive the optimal amount of light for growth. In another exemplary embodiment, if a plant requires a higher ratio of red to blue light, the light adjustment module 3b can adjust the ratio of red to blue wavelengths in the light spectrum, thereby allowing the lighting system to create lighting conditions customized to the needs of the plants.

[0039] The data set of growth parameters detected by the plant's sensors and the customized lighting profile generated by the optimization module 3a are stored in a computer-readable storage module 4 connected to the sensors 2 and the processor 3. Computer-readable storage modules 4 used may include hard disk drives (HDDs) and solid-state drives (SSDs), network-attached storage (NAS), cloud service storage, flash drives and memory cards, as well as databases such as MySQL®, PostgreSQL or MongoDB.

[0040] FIG. 5 illustrates an exemplary embodiment in which an ultrasonic sensor 2 is used to determine a distance d between the sensor and a plant, thereby providing data to a processor 3 to execute instructions for controlling the lighting device 1. As shown in FIG. 5, upon starting the lighting device 1, in step S1, one or more blocks of LEDs in the inner portion 1b of the lighting device 1 are turned on to illuminate the plant. Next, in step S2, the ultrasonic sensor detects the distance d from the plant by transmitting and receiving reflected waves. In step S3, it is determined whether the distance d is greater than 5 cm. If the detected distance is less than 5 cm, the processor 3 executes instructions to turn off the LEDs in the outer portion 1a in step S4. As the plant continues to grow, if the distance d detected by the ultrasonic sensor 2 is greater than 5 cm, the processor 3 executes instructions to turn on the LEDs in the outer portion 1a in step S5.

[0041] 6 shows a flowchart of a method for controlling plant growth according to one embodiment. Upon startup, the system 10 begins a continuous monitoring process by turning on the LEDs of the lighting device 1 in step S11. Next, in step S12, the sensor 2 detects the plant's growth parameters. Next, in step S13, the sensor 2 transmits the growth parameter data to the processor 3. The processor 3 analyzes the growth parameters; for example, the optimization module 3a uses artificial intelligence to analyze the detected growth parameters and interpret the plant's requirements based on its current growth stage. After the optimization module 3a has performed its function, the light adjustment module 3b responds by adjusting the intensity of the LEDs.

[0042] Based on the growth parameters, the optimization module 3a configures the lighting device 1 to generate customized lighting profiles for various plants. Then, a data set of the growth parameters and the customized lighting profiles for various plants is stored in the computer-readable storage module 4. The LEDs are then activated according to the customized lighting profiles, and light is emitted toward the plants. Based on the analyzed growth parameters, the processor 3 controls the lighting device 1 by controlling various combinations of light spectra based on the growth parameters, such that the light spectra are combined in an RGB ratio to customize the lighting conditions for various plants. To perform such growth parameter analysis, in step S15, it is determined whether there is any change in the growth parameters detected by the sensor 2. If there is no change in the growth parameters, the control process returns to step S12 for continuous monitoring; if there is a change in the growth parameters, the control process proceeds to the following step S16.

[0043] For each type of plant illuminated by the lighting device 1, as seen in step S16, the processor 3 accesses the customized lighting profile stored in the computer-readable storage module 4 and customizes the combination of light spectra for each type of plant, thereby ensuring that the illumination meets the precise needs of various species of plants. Next, in step S17, upon detecting the plant growth parameters, the processor 3 executes instructions for irradiating light with a ratio of light spectra including red light, green light, and blue light based on the customized lighting profile for various plants.

[0044] From this specification, the evaluations performed to validate the method of controlling plant growth are briefly described. It should be noted that the parameters defined or determined in these evaluations are not meant to be construed as limitations on the scope of the present invention.

[0045] (Experiment using transparent three-color common cathode LEDs on lettuce) Experiments were conducted to observe the growth of lettuce plants using 13 transparent tri-color common-cathode LEDs as grow lights. To determine the PPFD generated by the grow lights, lux illuminance was measured using a light meter. Considering that lettuce plants can vary greatly in size, shape, and leaf type, but generally have a loose rosette structure, the grow lights were constructed with 13 transparent tri-color common-cathode LEDs to create a spatial structure that provided a wide range of illumination to the lettuce as it grew larger. Both red and blue lights in the LEDs were turned on to create a color combination with a 1:1 R-B ratio. Red light is highly effective in regulating plant growth and development. This helps increase lettuce photosynthesis and promote lettuce growth. Blue light helps plants develop strong stems and produce chlorophyll, which is necessary for plant processes. Although not shown, illuminance was measured using a light meter positioned substantially 5 cm away from the grow lights, and this value was then used to determine the PPFD incident on the plants. The light meter measured 5053 lux, which corresponds to 448.36 μmol / m 2 The PPFD irradiated by the plant growth light was 80 μmol / m at the lettuce seedling stage. 2 / s, 150 μmol / m during the vegetative stage of lettuce 2 / s (PPFD) was greater than the standard requirement.

[0046] (An experiment to study the effectiveness of plant growth lights by sowing lettuce seeds) Lettuce seeds were sown and the pots were sealed to block external light. The seeds germinated well, and seedling leaves grew to more than 2 cm in size in an environment with light only from the grow light. The lettuce seeds germinated and the seedlings grew well under a 439.8 mW grow light constructed with 13 tri-color common-cathode LEDs with a 1:1 Rb / Rb ratio. The illuminance efficacy at a distance of 5 cm from the grow light was 11.49 lux / mW, which proved sufficient for lettuce seeds to germinate and seedling leaves to grow to more than 2 cm in size. This discovery led to the next challenge: constructing a larger grow light with greater power to achieve stronger illuminance.

[0047] The effect of closer grow lights - the closer the grow light, the stronger the light intensity. It was found that the illuminance was stronger when the grow lights were placed closer. When the LEDs were placed 4cm to 10cm apart, the illuminance was weaker. A light meter was used to verify the difference in illuminance with distance. An illuminance of 5053 lux was measured when the grow lights were placed 5cm above the illuminance meter, and 6385 lux was measured when they were placed 3cm above the illuminance meter. Illuminance increased when the grow lights were placed closer.

[0048] (Experimental research to achieve optimization by RB ratio) The R-B ratio requirement changes at different growth stages of lettuce. Therefore, for optimization, the R-B ratio needs to be changed according to the growth stage. There are two ways to achieve this in a transparent tri-color common cathode LED. 1) The delay time of each color is changed by coding. For example, when RB=2, the programmed delay time for red light was twice the programmed delay time for blue light. 2) The light intensity of each color can be changed by coding. For example, if RB=2, the intensity of the red light was programmed to be twice the intensity of the blue light.

[0049] (Experimental research to achieve optimization through energy conservation) An LED-on scheme was devised to optimize energy use. As the lettuce plants grew larger, grow lights 1a in the outer rows were turned on. Just after the seeds were sown, only grow lights 1b in the middle row were turned on. As germination began, and the seedlings' leaves grew larger, LEDs in more rows away from the middle row were turned on to accommodate the growing lettuce plants, which required higher PPFD.

[0050] As the lettuce grew taller, the PPF from the light source decreased. As the lettuce grew taller, it grew closer to the grow light and received a greater amount of PPFD. If the PPFD received was greater than the required amount, it would result in a waste of light energy. Therefore, the grow light should have the ability to reduce energy as the lettuce grew taller. To simulate the lettuce growing taller, a ruler was moved closer to ultrasonic sensor 2. When the ruler was closer to ultrasonic sensor 2, the LEDs became dimmer.

[0051] (Experimental research to achieve optimization through system expansion) Four small modular LED boards were connected to an Arduino microcontroller to allow for additional LED boards to be added to the grow light system as lettuce production increased. The system allowed for expansion of the grow light by connecting more LED boards to the Arduino microcontroller. Conversely, fewer LED boards were connected to the microcontroller when not needed. As the lettuce population grew, more light was needed and more modular LED boards were connected to the Arduino microcontroller without the need for a separate grow light system.

[0052] (An experiment was conducted to verify that the distance between the grow light and the lettuce is an important factor for healthy cultivation.) An experiment was conducted to determine how irradiance changes as the distance between the grow light and the plant is changed. Knowing the required PPFD of the lettuce and the photosynthetic photon flux of the grow light, the distance h between the plant and the grow light could be determined using Equation 1. The value h is important because it determines the required irradiance and, therefore, how far the plant must be from the grow light to receive the PPFD.

[0053] During the early stages of growth, when the seedlings' leaves are still small, the light's illumination area may be small, but it still provides complete coverage for the seedlings. Therefore, the grow light can be placed close to the seedlings to receive a good amount of PPFD. However, as the lettuce grows, its leaves become larger, and the grow light needed to be placed further away from the lettuce to ensure it still provided the lettuce with sufficient illumination coverage. As a result, the illumination intensity became weaker, which resulted in a lower PPFD received by the lettuce. It is important to know the maximum distance between the plant and the grow light to ensure the plant remains within the required range.

[0054] The tabulated results and plots in Figures 3 and 4 show that the experimental results are consistent with the equation derived for the relative illuminance / PPFD and the distance h that the lettuce was away from the grow light, as expressed in Equation 1. Blue light was used in the experiment. The illuminance, measured in lux, at wavelength λ=465 nm is expressed as W / m 2 converted to units of irradiance, then μmol / m 2 converted to PPFD in / s.

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[0055] The graph in Figure 4 shows that the change in illuminance when closer to the grow light was more pronounced than the change in illuminance when further away from the grow light. When closer to the grow light, the change in height caused a larger change in illuminance.

[0056] (An experiment was conducted to examine the growth of lettuce when exposed to red, blue, and green light separately.) A grow-light circuit was constructed using four tri-color common-cathode LEDs. Three such circuits were constructed and programmed to illuminate three pots of lettuce with each color of light from the moment the seeds were sown. A comparison of lettuce growth under red, blue, and green light was conducted 16 days after sowing. Lettuce germinated very well under blue light, but germinated poorly under red and green light.

[0057] The blue LED produced the highest efficacy of 75.6 lux / mW, which aided in germination. The seedlings were 2 cm wide, the largest of the three. Even though the green light produced a high illuminance efficacy of 69.9 lux / mW, it did not aid in the lettuce's successful germination. This is consistent with the information that plants require green light to grow but do not have a high absorption rate for green light. The red light produced an efficacy of 22.1 lux / mW, the lowest of the three colors. The seedlings' stems were found to be very thin and long, and their leaves were very small. This is consistent with the information that plants require red light to grow taller.

[0058] The present disclosure includes what is contained in the appended claims and what is described above. While the present invention has been described in a preferred form with a certain degree of particularity, it will be understood that the present disclosure of the preferred form is made by way of example only, and that many changes to the details of construction and the combination and arrangement of parts are possible without departing from the scope of the invention.

Claims

1. A system for controlling plant growth, comprising at least one lighting device (1), at least one sensor (2), and a processor (3), The lighting device (1) irradiates light with a variable spectrum toward the plant, the sensor (2) is configured to detect a growth parameter of the plant; the processor (3) is configured to analyze the growth parameters detected by the sensor; The system for controlling plant growth, wherein the processor (3) is further configured to control different combinations of light spectra based on the growth parameters, such that the light spectra are combined in ratios to enable customization of lighting conditions during different stages of plant growth.

2. 2. The system of claim 1, wherein the lighting device (1) comprises a plurality of light emitting diodes (LEDs) configured to emit red, green and blue light.

3. 3. The system according to claim 2, wherein the light emitting diodes are arranged on either or both of the inner (1b) and outer (1a) parts of the panel of the lighting device (1).

4. 4. The system of claim 3, wherein the inner part (1b) comprises at least three separate blocks of light emitting diodes.

5. The system according to any one of claims 1 to 4, wherein the sensor (2) comprises any one or a combination of an ultrasonic sensor, a camera, a humidity sensor and a temperature sensor.

6. The system of any one of claims 1 to 5, wherein the growth parameters include, but are not limited to, plant type, plant health, plant growth stage, and environmental conditions.

7. The system according to any one of claims 1 to 6, wherein the processor (3) comprises a light adjustment module (3b) configured to control one or more settings of the lighting device (1).

8. The system of claim 7 , wherein the settings include any one or combination of light intensity, light spectrum type, duration of illumination, and light spectrum ratio.

9. The system according to any one of claims 1 to 8, wherein the processor (3) comprises an optimization module (3a) configured to analyze the detected growth parameters by using artificial intelligence.

10. 10. The system of claim 9, wherein the optimization module (3a) is further configured to optimize and adjust the settings of the lighting device (1) to the detected growth parameters to generate customized lighting profiles for different plants.

11. 11. The system of claim 10, further comprising a computer readable storage module (4) for storing the growth parameter dataset and the customized lighting profile for the plant.

12. 1. A method for controlling plant growth, comprising: detecting a growth parameter of said plant by at least one sensor (2); analyzing, by a processor (3), said detected growth parameters; and irradiating light towards the plants by at least one lighting device (1), 10. The method for controlling plant growth, wherein the processor (3) is further configured to control different combinations of light spectra based on the growth parameters, such that the light spectra are combined in RGB ratios to enable customization of lighting conditions for different plants.

13. 13. The method according to claim 12, further comprising the step of analyzing said growth parameters using artificial intelligence by an optimization module (3a).

14. 14. The method of claim 13, further comprising optimizing, by the optimization module (3a), settings of the lighting device (1) based on the growth parameters to generate customized lighting profiles for different plants.

15. 15. The method of claim 14, further comprising storing the growth parameter datasets and customized lighting profiles for different plants in a computer readable storage module (4).

16. 16. The method according to claim 14 or 15, further comprising the step of executing, by the processor (3), instructions for optimizing the settings of the lighting device (1) based on the detected growth parameters.

17. 17. The method according to any one of claims 14 to 16, further comprising the step of executing, by the processor (3), instructions for adjusting a ratio of a light spectrum comprising red light, green light and blue light based on the lighting profiles customized for different plants.

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