Operation method of nutrient solution management system for measuring and modifying components of nutrient solution

Abstract

An operation method of a nutrient solution management system is disclosed. The operation method comprises the steps in which: a sensor device measures component information of a nutrient solution included in a nutrient solution tank by using at least one sensor, and transmits the measured component information to a server; the server selects at least one target component requiring concentration adjustment among components included in the nutrient solution in the nutrient solution tank, the target component being selected on the basis of the component information received from the sensor device; the server transmits a control signal for adjusting the concentration of the target component to a culture solution management device; and the culture solution management device selects a raw material tank, including a raw material required to modify the concentration of the target component, according to the control signal received from the server, and adds the raw material included in the selected raw material tank to the nutrient solution in the nutrient solution tank.

Description

Method of operation of a nutrient solution management system that performs component measurement and correction of nutrient solution

[0001] The present disclosure relates to an operating method of a nutrient solution management system, and more particularly, to an operating method of a nutrient solution management system that performs component measurement and correction of a nutrient solution.

[0002] Recently, smart farms are emerging that apply ICT (Information & Communications Technology) to agriculture and have facilities that control the environment of cultivation facilities to maintain conditions suitable for crop growth.

[0003] Among the various facilities and systems associated with smart farms, nutrient solution management systems are those that supply the appropriate amount of nutrients to crops. Conventional nutrient solution management systems simply measure the pH and electrical conductivity (EC) of the nutrient solution and manage it to maintain these values ​​within a range suitable for crop growth. To ensure the proper supply of nutrients to crops and enhance user convenience, technology is needed that analyzes not only the pH and EC of the nutrient solution but also its components to supplement any missing components.

[0004] The present disclosure provides an operating method of a nutrient solution management system that performs component measurement and correction of nutrient solution.

[0005] The purposes of the present disclosure are not limited to those mentioned above, and other purposes and advantages of the present disclosure not mentioned above can be understood through the following description and will be more clearly understood through the embodiments of the present disclosure. Furthermore, it will be readily apparent that the purposes and advantages of the present disclosure can be realized by the means and combinations thereof set forth in the claims.

[0006] An operating method of a nutrient solution management system according to one embodiment of the present disclosure includes a step in which a sensor device measures component information of a nutrient solution contained in a nutrient solution tank using at least one sensor and transmits the measured component information to a server, a step in which the server selects at least one target component whose concentration needs to be adjusted among the components contained in the nutrient solution of the nutrient solution tank based on the component information received from the sensor device, a step in which the server transmits a control signal for adjusting the concentration of the target component to a nutrient solution management device, and a step in which the nutrient solution management device selects a raw material tank containing a raw material necessary for correcting the concentration of the target component according to the control signal received from the server and adds the raw material contained in the selected raw material tank to the nutrient solution of the nutrient solution tank.

[0007] The step of selecting at least one target component may include a step in which the server identifies necessary component information of a nutrient solution matched with a crop selected according to a user input, and a step in which the server identifies at least one target component whose concentration needs to be adjusted among the components included in the nutrient solution of the nutrient solution tank based on the identified necessary component information of the nutrient solution and the component information received from the sensor device.

[0008] The step of identifying the necessary component information of the above nutrient solution allows the server to obtain the necessary component information of the previously stored nutrient solution that matches the type of crop selected according to user input.

[0009] In addition, the step of identifying the necessary component information of the nutrient solution may be performed by the server inputting the type of crop and the sowing time obtained according to the user input into at least one artificial intelligence model for predicting the component of the nutrient solution required to be supplied to the crop based on the time elapsed since the sowing of the crop, thereby obtaining the necessary component information of the nutrient solution from the artificial intelligence model.

[0010] The step of adding the selected raw material to the nutrient solution of the nutrient solution tank may be performed by the culture solution management device controlling a pump connected to the raw material tank containing the selected raw material to supply the raw material contained in the selected raw material tank to the nutrient solution tank in an amount set according to the control signal.

[0011] The operating method of the above nutrient solution management system may include a step in which the sensor device measures component information of raw materials contained in at least one raw material tank using at least one sensor and transmits the measured component information to the server, and a step in which the server identifies whether the raw materials are defective based on the component information received from the sensor device.

[0012] The step of identifying whether the raw material is defective may include a step in which the server identifies a raw material whose component information is different from the basic component information as a defective raw material based on the component information received from the sensor device and the basic component information pre-stored for each raw material included in the raw material tank, and the operating method of the nutrient solution management system may include a step in which the server identifies at least one defective component that is not included in the basic component information for the defective raw material among the components included in the component information of the defective raw material received from the sensor device, and a step in which the server identifies the concentration of the defective component from the component information of the defective raw material received from the sensor device and identifies the contamination level of the defective raw material based on the concentration of the identified defective component.

[0013] An operating method of a nutrient solution management system according to one embodiment of the present disclosure includes a step in which a sensor device measures component information of a nutrient solution contained in a nutrient solution tank using at least one sensor and transmits the measured component information to a control device, a step in which the control device analyzes the component of the nutrient solution based on the component information and transmits analysis information obtained according to the analysis to the server, a step in which the server selects at least one target component whose concentration needs to be adjusted among the components contained in the nutrient solution of the nutrient solution tank based on the analysis information received from the control device, a step in which the server transmits control information for adjusting the concentration of the target component to the control device, a step in which the control device transmits a control signal for adjusting the concentration of the target component to a nutrient solution management device according to the control information received from the server, and a step in which the nutrient solution management device selects a raw material tank containing a raw material necessary for correcting the concentration of the target component according to the control signal received from the control device and adds the raw material contained in the selected raw material tank to the nutrient solution of the nutrient solution tank.

[0014] The operating method of the nutrient solution management system according to the present disclosure can create optimal cultivation conditions by measuring and correcting the components of the nutrient solution to provide a nutrient solution suitable for the crop.

[0015] In addition, the operating method of the nutrient solution management system according to the present disclosure can predict changes in the components of the nutrient solution over time based on data received from a field where crops are grown, thereby correcting the components of the nutrient solution to prevent deterioration in the quality of the nutrient solution and thereby maintain the quality of the nutrient solution.

[0016] Figure 1 is a block diagram illustrating the configuration of a nutrient solution management system according to one embodiment of the present disclosure;

[0017] FIG. 2 is a flowchart illustrating an operation of a nutrient solution management system to correct components of a nutrient solution according to one embodiment of the present disclosure;

[0018] FIG. 3 is a drawing for explaining a process in which raw materials are supplied from a raw material tank to a nutrient solution tank according to one embodiment of the present disclosure;

[0019] FIG. 4 is a flowchart illustrating an operation of a nutrient solution management system to identify whether a raw material is defective according to an embodiment of the present disclosure.

[0020] FIG. 5 is a block diagram illustrating the configuration of a nutrient management system according to an embodiment of the present disclosure, and

[0021] FIG. 6 is a flowchart illustrating the operation of a nutrient solution management system according to one embodiment of the present disclosure.

[0022] Before describing the present disclosure in detail, the description method of the specification and drawings will be described.

[0023] First, the terms used in this specification and claims are general terms selected based on their functions in the various embodiments of the present disclosure. However, these terms may vary depending on the intentions of those skilled in the art, legal or technical interpretations, and the emergence of new technologies. Furthermore, some terms may have been arbitrarily selected by the applicant. These terms may be interpreted according to the meanings defined in this specification. In the absence of a specific definition, they may be interpreted based on the overall content of this specification and common technical knowledge in the relevant field.

[0024] Additionally, the same reference numbers or symbols in each drawing attached to this specification represent parts or components that perform substantially the same functions. For convenience of explanation and understanding, the same reference numbers or symbols are used in different embodiments. In other words, even if components with the same reference numbers are all depicted in multiple drawings, the multiple drawings do not necessarily represent a single embodiment.

[0025] Additionally, terms including ordinal numbers, such as "first," "second," etc., may be used in this specification and claims to distinguish between components. These ordinal numbers are used to distinguish identical or similar components from each other, and the use of these ordinal numbers should not be interpreted in a limited manner. For example, components associated with these ordinals should not be restricted in their order of use or arrangement by their numbers. If necessary, each ordinal number may be used interchangeably.

[0026] In this specification, singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "comprise" or "consist of" are intended to indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but should be understood not to preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0027] In the embodiments of the present disclosure, terms such as "module," "unit," "part," etc. are terms used to refer to components that perform at least one function or operation, and such components may be implemented as hardware or software, or a combination of hardware and software. In addition, a plurality of "modules," "units," "parts," etc. may be integrated into at least one module or chip and implemented as at least one processor, except in cases where each needs to be implemented as a separate, specific hardware.

[0028] Additionally, in the embodiments of the present disclosure, when a part is said to be connected to another part, this includes not only a direct connection but also an indirect connection through another medium. Furthermore, unless specifically stated otherwise, the statement that a part includes a certain component does not exclude other components, but rather implies that other components may be included.

[0029] FIG. 1 is a block diagram illustrating the configuration of a nutrient solution management system according to one embodiment of the present disclosure.

[0030] Referring to FIG. 1, the nutrient solution management system (1000) may include a sensor device (100), a server (200), and a nutrient solution management device (300).

[0031] The sensor device (100) is a device for measuring various information related to nutrient solution.

[0032] For this purpose, the sensor device (100) may include at least one sensor.

[0033] As an example, the sensor device (100) may include a light source module, a spectroscopic module, and a detection module to measure component information of the nutrient solution (e.g., components included in the nutrient solution (e.g., compounds, ions, trace elements, etc.), concentrations by component, absorbance by component, etc.).

[0034] The light source module is a module for generating light, and the sensor device (100) can generate light through the light source module.

[0035] The light source module can generate light using, but is not limited to, a tungsten-halogen lamp, a deuterium lamp, a xenon lamp, an LED (light emitting diode), etc.

[0036] The spectral module is a module for separating light according to wavelength, and the sensor device (100) can separate light of a desired wavelength range through the spectral module and emit it toward the nutrient solution.

[0037] For example, a spectroscopic module can disperse light generated from a light source module using a diffraction grating, prism, etc., and emit light of a desired wavelength range toward the nutrient solution.

[0038] At this time, the sensor device (100) can use the wavelength range information that is matched and stored for each component.

[0039] For example, the sensor device (100) can obtain wavelength range information matching a component whose concentration needs to be measured, separate light in a wavelength range matching the obtained wavelength range information, and emit the light in the direction of the nutrient solution.

[0040] Meanwhile, the sensor device (100) can also receive and use component-specific wavelength range information from the server (200).

[0041] The detection module is a module for identifying the component information of the nutrient solution by detecting the light received through the nutrient solution, and the sensor device (100) can obtain the component information of the nutrient solution based on the light received through the nutrient solution.

[0042] For example, the detection module may include at least one light sensor for measuring the amount of light.

[0043] A light sensor is a sensor that detects light and converts it into an electrical signal, and may include, but is not limited to, a photodiode, a phototransistor, an InGaAs sensor, etc.

[0044] For example, the sensor device (100) can measure the absorbance for a component matched with the wavelength range separated through the spectroscopic module by comparing the light emitted toward the nutrient solution and the light received by the detection module through the nutrient solution.

[0045] At this time, the sensor device (100) can calculate a concentration value for each component based on the coefficients matched and stored for each component and the absorbance measured for each component.

[0046] In addition, as the sensor device (100) transmits component information of the nutrient solution including the absorbance measured for each component to the server (200), the server (200) can calculate the concentration value for each component based on the component information received from the sensor device (100) and the coefficients matched and stored for each component.

[0047] As a further example, the sensor device (100) may include an ion sensor for measuring the concentration of ions.

[0048] For example, the ion sensor may include an ion selective electrode (ISE) that measures the concentration of ions by utilizing a potential difference generated across a membrane that selectively transmits ions.

[0049] Through this, the sensor device (100) can measure component information of the nutrient solution including the concentration of ions.

[0050] The server (200) is a device for providing control information for correction of the components of the nutrient solution.

[0051] As an example, the server (200) can receive information on the components of the nutrient solution from the sensor device (100) and identify the target components that require concentration correction.

[0052] For example, the server (200) can receive component information including the concentration values ​​of each of a plurality of ions included in the nutrient solution from the sensor device (100) and identify an ion requiring concentration correction as a target component.

[0053] Accordingly, the server (200) can transmit a control signal including information necessary to correct the concentration of the target component (e.g., the amount of raw material to be added, information about the raw material, etc.) to the culture solution management device (300).

[0054] Meanwhile, the server (200) may be implemented as a server device or system including at least one computer. It is also possible for the server (200) to be implemented as a terminal device such as a desktop PC, laptop PC, tablet PC, or smartphone.

[0055] For example, the server (200) may include a memory in which identification information of a raw material, identification information of a raw material tank containing the raw material, and basic ingredient information, which is information on each ingredient of the raw material contained in the raw material tank, are matched and stored.

[0056] The nutrient solution management device (300) can manage the nutrient solution supplied to the crop.

[0057] As an example, the nutrient solution management device (300) can adjust the components of the nutrient solution according to a control signal received from the server (200).

[0058] For example, the culture solution management device (300) can select a raw material tank containing raw materials to be added to the nutrient solution tank according to a control signal received from the server (200), and control a pump connected to the selected raw material tank to supply raw materials to the nutrient solution tank in an amount set according to the control signal.

[0059] Meanwhile, the culture solution management device (300) may include a memory, a processor, a communication unit, etc.

[0060] The memory is configured to store an operating system (OS) for controlling the overall operation of components of the culture solution management device (300) and at least one instruction or data related to components of the culture solution management device (300).

[0061] For example, the memory may include information matching information about the amount of suction and discharge when the metering pump described later operates once, identification information for each raw material, and identification information for the raw material tank containing the raw material.

[0062] Memory may include non-volatile memory such as ROM and flash memory, and may include volatile memory such as DRAM. Memory may also include a hard disk, a solid state drive (SSD), etc.

[0063] The processor is configured to control the culture solution management device (300) as a whole.

[0064] In one embodiment, the processor may include a general-purpose processor such as a CPU (Central Processing Unit), an AP, a DSP (Digital Signal Processor), a graphics-only processor such as a GPU (Graphics Processor Unit), a VPU (Vision Processing Unit), or an AI-only processor such as an NPU (Neural Processing Unit). The AI-only processor may be designed with a hardware structure specialized for training or utilizing a specific AI model.

[0065] The communication department is a component for communicating with the outside world.

[0066] The communication unit may include circuits, modules, chips, etc. for performing communication using various wired and wireless communication methods. The communication unit may also be connected to external devices and servers via various networks.

[0067] Depending on the area or scale, a network may be a personal area network (PAN), a local area network (LAN), or a wide area network (WAN), and depending on the openness of the network, it may be an intranet, an extranet, or the Internet.

[0068] The communication unit can be connected to external devices and servers through various wireless communication methods such as LTE (long-term evolution), LTE-A (LTE Advance), 5G (5th Generation) mobile communication, CDMA (code division multiple access), WCDMA (wideband CDMA), UMTS (universal mobile telecommunications system), WiBro (Wireless Broadband), GSM (Global System for Mobile Communications), DMA (Time Division Multiple Access), WiFi (Wi-Fi), WiFi Direct, Bluetooth, BLE (Bluetooth Low Energy), NFC (near field communication), Zigbee, and LoRa.

[0069] Additionally, the communication unit can be connected to external devices and servers via wired communication methods such as Ethernet, optical network, Universal Serial Bus (USB), and ThunderBolt.

[0070] In addition, the communications department may be structured to utilize various new communication methods / technologies that will be developed in the future.

[0071] FIG. 2 is a flowchart illustrating an operation of a nutrient solution management system to correct components of a nutrient solution according to one embodiment of the present disclosure.

[0072] Referring to FIG. 2, the sensor device (100) can measure component information of the nutrient solution contained in the nutrient solution tank using at least one sensor (S210).

[0073] In one embodiment, the sensor device (100) can measure the absorbance for a component matching the wavelength range of light emitted toward the nutrient solution using at least one sensor.

[0074] At this time, the sensor device (100) can calculate the concentration value for each component based on the coefficients matched and stored for each component and the absorbance measured for each component.

[0075] The sensor device (100) can transmit information on the components of the nutrient solution to the server (200) (S220).

[0076] As an example, the sensor device (100) can transmit component information including the components contained in the nutrient solution and the concentration of each component to the server (200).

[0077] As an additional example, the sensor device (100) may transmit component information of the nutrient solution, including the absorbance measured for each component, to the server (200).

[0078] The server (200) can select at least one target component whose concentration needs to be adjusted among the components included in the nutrient solution based on the component information received from the sensor device (100) (S230).

[0079] At this time, when component information of the nutrient solution including the absorbance measured for each component is received from the sensor device (100), the server (200) can calculate the concentration value for each component based on the component information received from the sensor device (100) and the coefficients matched and stored for each component.

[0080] Meanwhile, the server (200) can identify the necessary ingredient information matching the crop selected according to user input based on the necessary ingredient information of the nutrient solution stored according to the type of crop.

[0081] At this time, the information on the required components of the stored nutrient solution depending on the type of crop may include information on the components of the nutrient solution and the concentration range of each component required to provide nutrients suitable for the growth of each type of crop.

[0082] Through this, the server (200) can identify a component requiring concentration correction as a target component based on the necessary component information matched with the crop selected according to user input and the component information received from the sensor device (100).

[0083] For example, the server (200) can identify a component whose concentration identified according to the component information is below the concentration range set according to the required component information as an additional target component, and can identify a component whose concentration identified according to the component information is above the concentration range set according to the required component information as an additional target component.

[0084] In addition, the server (200) may obtain information on the necessary components of the nutrient solution that needs to be supplied to the crop by using at least one artificial intelligence model to predict information on the components of the nutrient solution that needs to be supplied to the crop based on the time elapsed since the sowing of the crop.

[0085] Specifically, as time passes after sowing the crop and the crop grows, the information on the components of the nutrient solution required to be supplied to the crop changes, so the server (200) can obtain the information on the required components of the nutrient solution by using the first artificial intelligence model for predicting the information on the required components of the nutrient solution according to the type of crop and the time of sowing, which is the time when the cultivation of the crop begins by planting the seeds or sprouts of the crop.

[0086] For example, the server (200) can obtain information on the necessary components of the nutrient solution from the first artificial intelligence model by inputting the type of crop and the sowing time obtained according to the user input into the artificial intelligence model.

[0087] At this time, the server (200) can obtain information on the time elapsed from the time of sowing the crop and the component information of the nutrient solution matched with each elapsed time for each type of crop to configure training data, and train the first artificial intelligence model based on the configured training data.

[0088] At this time, the first artificial intelligence model may be a model based on various learning algorithms such as CNN (Convolution Neural Network), RNN (Recurrent Neural Network), and Transformer, but is not limited thereto.

[0089] Meanwhile, the server (200) may obtain from an external source and use a first artificial intelligence model that has been trained to output information on the required components of nutrient solution according to the time elapsed since sowing of the crop.

[0090] The server (200) can transmit a control signal for controlling the concentration of the target component to the culture solution management device (300) (S240).

[0091] For example, the server (200) can transmit a control signal for adding an additional target component to the culture solution management device (300).

[0092] For example, the server (200) may transmit a control signal including information about raw materials to be added to the nutrient solution tank, such as raw materials containing additional target components, raw materials containing components whose concentrations are expected to change with the addition of raw materials containing additional target components and thus be identified as additional target components, to the culture solution management device (300).

[0093] At this time, information about the raw material may include identification information of the raw material, identification information of the raw material tank containing the raw material, the amount of raw material to be added, etc., and the identification information may be expressed as numbers, letters, symbols, etc., but is not limited thereto.

[0094] To this end, the identification information of each raw material and the identification information of the raw material tank containing the raw material may be matched and stored in the server (200) and the culture solution management device (300).

[0095] Additionally, the server (200) can transmit a control signal for dilution of the dilution target component to the culture solution management device (300).

[0096] For example, the server (200) may transmit a control signal including information about raw materials to be added to the nutrient solution tank, such as raw materials to be added to the nutrient solution tank for dilution of the dilution target component, raw materials containing a component whose concentration is expected to change according to the addition of the raw materials and thus be identified as the target component to be added, to the culture solution management device (300).

[0097] The culture solution management device (300) can select the raw material required to correct the concentration of the target component according to the control signal received from the server (200) (S250).

[0098] As an example, the culture solution management device (300) may select a raw material tank that matches the raw material identification information included in the control signal when the control signal received from the server (200) includes raw material identification information.

[0099] As an additional example, the culture solution management device (300) may select a raw material tank based on the identification information of the raw material tank when the control signal received from the server (200) includes identification information of the raw material tank.

[0100] The culture solution management device (300) can add the selected raw material to the nutrient solution in the nutrient solution tank (S260).

[0101] For example, the culture solution management device (300) can control a pump connected to a selected raw material tank according to a control signal received from the server (200) to supply raw materials contained in the raw material tank to a nutrient solution tank.

[0102] A more detailed explanation related to this will be provided later with reference to Fig. 3.

[0103] Meanwhile, the sensor device (100) may measure at least one of the pH value and the EC (Electrical Conductivity) value of the nutrient solution using at least one sensor.

[0104] For example, the sensor device (100) can measure the pH value of the nutrient solution using a pH sensor for measuring the acidity of the solution.

[0105] A pH sensor is a sensor for measuring the pH value of a solution based on the concentration of hydrogen ions, and may include at least one electrode.

[0106] For example, a pH sensor can calculate a pH value by measuring the difference in potential of an electrode depending on the concentration of hydrogen ions.

[0107] As an additional example, the sensor device (100) can measure the EC value of the nutrient solution using a conductivity sensor for measuring the electrical conductivity of the solution.

[0108] A conductivity sensor is a sensor for measuring the degree to which a solution transfers charge, and may include multiple electrodes.

[0109] For example, a conductivity sensor can supply current to a nutrient solution through electrodes and calculate the EC value of the nutrient solution based on the potential difference between the electrodes.

[0110] At this time, the sensor device (100) can transmit at least one of the pH value and the EC value to the server (200).

[0111] At this time, the server (200) can determine whether to correct at least one of the pH value and EC value of the nutrient solution based on the value received from the sensor device (100).

[0112] In one embodiment, the server (200) may transmit a control signal for correction of an item (e.g., pH, EC) whose value is outside the reference range to the culture solution management device (300) based on the preset pH reference range and EC reference range.

[0113] For example, the server (200) can transmit a control signal including information on raw materials required for correction for items whose values ​​are measured outside the reference range to the culture solution management device (300).

[0114] The culture solution management device (300) can select a raw material tank based on a control signal received from the server (200) and add raw materials contained in the selected raw material tank to the nutrient solution tank.

[0115] FIG. 3 is a drawing for explaining a process in which raw materials are supplied from a raw material tank to a nutrient solution tank according to one embodiment of the present disclosure.

[0116] Referring to FIG. 3, raw materials are stored in a nutrient solution tank (10), and a culture solution management device (300) can control a pump (20) connected to each raw material tank (10) to add raw materials to the nutrient solution tank (30).

[0117] Each raw material tank (10) may contain different raw materials.

[0118] For example, the raw material may include, but is not limited to, a solution containing trace elements (e.g., nitrogen, phosphorus, potassium, etc.), a solution containing at least one ion, raw water, liquid fertilizer, etc.

[0119] The pump (20) may include a quantitative pump for supplying a quantitative amount of raw material.

[0120] A metering pump is a pump that sucks in and discharges a preset amount of fluid.

[0121] For example, a metering pump may include a driving unit (e.g., an electric motor, a cylinder, etc.) for operating the pump and a metering unit (e.g., a piston, a diaphragm, a gear, a rotor, etc.) for controlling the flow of fluid so that a preset amount is sucked in and discharged.

[0122] At this time, as the amount of suction and discharged when the quantitative pump operates once is stored in the culture solution management device (300), the culture solution management device (300) can control the number of times the pump (20) operates in order to add the selected raw material to the nutrient solution tank (30) in an amount set according to the control signal received from the server (200).

[0123] The nutrient solution tank (30) may contain a nutrient solution composed of at least one raw material.

[0124] At this time, the nutrient solution tank (30) may be connected to at least one medium in which crops are grown, but is not limited thereto.

[0125] In one embodiment, when the culture solution management device (300) receives a control signal from the server (200), it selects a raw material tank (10) containing raw materials that need to be added to the nutrient solution tank (30) based on information about the raw materials included in the control signal, and controls a pump (20) connected to the selected raw material tank (10) to add the raw materials to the nutrient solution tank (30).

[0126] At this time, the culture solution management device (300) can set the number of times the pump (20) operates so that a set amount of raw material is added to the nutrient solution tank (30) according to the control signal received from the server (200).

[0127] FIG. 4 is a flowchart illustrating an operation of a nutrient solution management system to identify whether a raw material is defective according to one embodiment of the present disclosure.

[0128] Referring to FIG. 4, the sensor device (100) can measure the component information of the raw material included in the raw material tank (S410).

[0129] For example, the sensor device (100) can measure component information of raw materials contained in at least one raw material tank using at least one sensor.

[0130] The sensor device (100) can transmit information on the composition of raw materials to the server (200) (S420).

[0131] For example, the sensor device (100) can match component information including components contained in the raw material and concentrations of each component with identification information of the raw material or identification information of the raw material tank and transmit the information to the server (200).

[0132] The server (200) can identify whether the raw material is defective based on the component information received from the sensor device (100) (S430).

[0133] As an example, the server (200) can identify whether the raw material is defective based on the component information received from the sensor device (100) and the basic component information pre-stored for each raw material contained in the raw material tank.

[0134] Basic ingredient information for each raw material may include information on the ingredients to be included in the raw material and the range within which the concentration of each ingredient included in the raw material must be maintained.

[0135] Specifically, the server (200) can compare the component information of the raw material identified from the component information received from the sensor device (100) and the basic component information for each raw material, and identify a raw material whose component information is different from the basic component information as a defective raw material.

[0136] For example, the server (200) can identify a defective raw material by comparing at least one component and the concentration of each component included in the component information measured by the sensor device (100) for a raw material with at least one component and the concentration of each component included in the basic component information.

[0137] For example, the server (200) can compare the concentration of each component included in the component information measured by the sensor device (100) for a raw material with the concentration of each component included in the basic component information, and if different concentration values ​​are identified for the same component, the raw material can be identified as a defective raw material.

[0138] At this time, the server (200) can identify a component with a different concentration value as a target component and transmit a signal to the user's terminal notifying that concentration correction of the target component is necessary.

[0139] For example, the server (200) may transmit a signal including identification information of a raw material tank containing defective raw materials or raw material information including identification information of the defective raw materials, and concentration information including at least one of the concentration of the target component measured by the sensor device (100) and the concentration of the target component included in the basic component information to the user's terminal.

[0140] As an additional example, if a defective component is identified that does not match at least one component included in the component information measured by the sensor device (100) for a raw material and at least one component included in the basic component information, the server (200) may identify the raw material as a defective raw material.

[0141] At this time, the server (200) can identify the concentration of each defective ingredient from the ingredient information of the defective ingredient measured by the sensor device (100), and identify the contamination level of the raw material tank containing the defective ingredient based on the identified concentration.

[0142] Specifically, if a component not included in the basic component information of the raw material is identified from the component information measured by the sensor device (100), the server (200) determines that the raw material is contaminated because a component that should not be included in the raw material has been identified, and can identify the degree of contamination of the defective raw material based on the concentration of each defective component.

[0143] For example, if the sum of the concentration values ​​of each defective ingredient (defective concentration value) is greater than or equal to the lowest concentration value (minimum concentration value) among the concentration values ​​of each ingredient included in the basic ingredient information of the defective raw material, the server (200) can identify the contamination level of the defective raw material as 'serious'.

[0144] Additionally, if the defective concentration value is less than the minimum concentration value, the server (200) can identify the contamination level of the defective raw material as 'caution'.

[0145] In addition, the server (200) can also calculate the contamination level of the defective raw material based on the ratio of the defective concentration value to the minimum concentration value.

[0146] For example, the server (200) can calculate the percentage value of the defective concentration value with respect to the minimum concentration value as the contamination level of the defective raw material.

[0147] Meanwhile, the server (200) can generate cultivation data for the cultivation site where the sensor device (100) and the nutrient solution management device (300) are located based on the component information of the nutrient solution and the component information of the raw material received from the sensor device (100), and store the data by matching it with the cultivation site.

[0148] For example, the cultivation data may include information on the composition of the nutrient solution received from the sensor device (100), information included in a control signal transmitted by the server (200) based on the information on the composition of the nutrient solution received from the sensor device (100) (e.g., information on target components, raw materials to be added to the nutrient solution tank, etc.), information on the composition of the raw materials received from the sensor device (100), etc.

[0149] As an example, the server (200) can predict changes in the component information of the nutrient solution over time based on cultivation data.

[0150] Specifically, the server (200) may include a second artificial intelligence model for predicting changes in component information of the nutrient solution over time.

[0151] For example, the server (200) may obtain component information of nutrient solution measured and received at different times from cultivation data and component information of raw materials measured and received at different times to configure training data, and train a second artificial intelligence model based on the training data so that the second artificial intelligence model can predict component information of nutrient solution over time.

[0152] Meanwhile, the second artificial intelligence model may be a model based on various learning algorithms such as RNN (Recurrent Neural Network), CNN (Convolution Neural Network), and Transformer to predict data that changes over time, but is not limited thereto.

[0153] Through this, the server (200) can input the component information of the nutrient solution measured at each of multiple past points in time by the sensor device (100) into the second artificial intelligence model, and obtain the component information of the nutrient solution predicted for a point in time after the point in time at which the component information of the nutrient solution was input into the second artificial intelligence model.

[0154] At this time, the component information of the nutrient solution obtained through the second artificial intelligence model may include component information of the nutrient solution predicted for each of a plurality of future points in time after the point in time when the component information of the nutrient solution was input into the second artificial intelligence model.

[0155] Meanwhile, the server (200) can identify whether there is a component that is outside the concentration range of each component included in the necessary component information (component information matched to the type of crop) among the concentration values ​​of each component included in the component information of the nutrient solution for each of a plurality of future points in time predicted through the second artificial intelligence model.

[0156] Through this, the server (200) can transmit a control signal to the culture solution management device (300) to correct the concentration of the component before the concentration of the component included in the nutrient solution goes beyond the concentration range included in the required component information.

[0157] That is, the server (200) can control the concentration of the component included in the nutrient solution to be maintained within the concentration range included in the required component information by transmitting a control signal to the culture solution management device (300) for correcting the concentration of the component before the concentration of the component that is outside the concentration range included in the required component information reaches the (future) point in time corresponding to the predicted component information.

[0158] In addition, the server (200) can calculate the change in concentration of each component included in the nutrient solution based on the component information of the nutrient solution measured at the last past point in time among the component information of the nutrient solution measured at each of the multiple past points in time input to the second artificial intelligence model and the component information of the nutrient solution predicted for each of the multiple future points in time by the second artificial intelligence model.

[0159] For example, the server (200) can calculate the concentration change amount, which is the difference value between the concentration of each component included in the component information of the nutrient solution measured at the last past point in time and the concentration of each component included in the component information predicted for each of a plurality of future points in time, for each component, and match it with each of a plurality of future points in time.

[0160] At this time, if the server (200) identifies a concentration change amount exceeding a threshold among the concentration changes calculated for each component, it can identify a future point in time that matches the concentration change amount as a warning point for the component.

[0161] Meanwhile, if the server (200) identifies two or more concentration changes exceeding the threshold among the concentration changes calculated for one component, the server can identify the earlier point in time among the points in time that match each concentration change exceeding the threshold as a warning point in time for one component.

[0162] At this time, the server (200) can identify the correlation between two components for which consecutive warning points are identified among the warning points identified for each component.

[0163] For example, if the time between consecutive warning points is less than a threshold time, the server (200) can determine that the component corresponding to the previous warning point affects the concentration change of the component corresponding to the subsequent warning point, and thus identify the two components corresponding to each consecutive warning point as being related.

[0164] Meanwhile, when the number of components associated with one component is two, the server (200) can identify the component corresponding to the previous warning time among the warning times of each component associated with one component as a sensitive component.

[0165] Specifically, if the time between warning points at which the concentration change amount of each of the plurality of components exceeds a threshold is identified as a short time interval (less than the threshold time), the server (200) determines that a change in the concentration of another component has occurred due to a change in the concentration of the component identified as the earliest warning point among the plurality of components, and thus identifies the component that is the start of a chain reaction of concentration changes as a sensitive component.

[0166] For example, if components A and B are identified as being related, and components B and C are identified as being related, the server (200) determines that the concentration of component B changes due to a change in the concentration of component A, and the concentration of component C changes due to a change in the concentration of component B, and thus determines that changes in the concentrations of components B and C occur in a chain reaction due to a change in the concentration of component A, and thus can identify component A as a sensitive component.

[0167] That is, a sensitive component refers to a component that causes a chain reaction of changes in the concentration of two or more components due to a change in the concentration of the sensitive component.

[0168] At this time, the server (200) can change the concentration range of the sensitive component included in the required component information of the nutrient solution.

[0169] For example, the server (200) can narrow the concentration range of the sensitive component by increasing the lower limit value or decreasing the upper limit value of the concentration range of the sensitive component included in the required component information of the pre-stored nutrient solution that matches the type of crop selected according to user input.

[0170] As a result, the server (200) can prevent the concentration of two or more components from changing due to a change in the concentration of the sensitive component.

[0171] Additionally, the server (200) can add necessary component information including the concentration range of the changed sensitive component to the cultivation data by matching it with the type of crop selected according to user input.

[0172] Through this, the server (200) receives information on the components of the nutrient solution from a sensor device (100) located in a cultivation field matched with the cultivation data, and if the type of crop selected according to user input is the same as the type of crop added to the cultivation data, a control signal for adding raw materials can be generated based on the necessary component information including the concentration range of the changed sensitive component and transmitted to the nutrient solution management device (300) located in the cultivation field matched with the cultivation data.

[0173] Meanwhile, the server (200) inputs the component information of the raw material measured at each of multiple past points in time by the sensor device (100) into the second artificial intelligence model, and can obtain the component information of the raw material predicted for a point in time after the point in time at which the component information of the raw material was input into the second artificial intelligence model.

[0174] At this time, the ingredient information of the raw material obtained through the second artificial intelligence model may include ingredient information of the raw material predicted for each of a plurality of future points in time after the point in time when the ingredient information of the raw material was input into the second artificial intelligence model.

[0175] At this time, the server (200) can identify the time at which each raw material is expected to be identified as a defective raw material based on the component information of the raw material predicted for each of a plurality of future time points.

[0176] Specifically, the server (200) can identify, for each raw material, a point in time at which the predicted raw material component information and the basic raw material component information for each of a plurality of future points in time do not match (a point in time at which the raw material is expected to be identified as a defective raw material) through the second artificial intelligence model.

[0177] Accordingly, the server (200) can transmit prediction information including the time at which each raw material is expected to be identified as a defective raw material to the user's terminal.

[0178] Through this, the nutrient solution management system (1000) can help maintain the quality of the nutrient solution and raw materials by controlling the concentration of the components contained in each nutrient solution and raw materials to be maintained within a certain range.

[0179] FIG. 5 is a block diagram illustrating the configuration of a nutrient solution management system according to one embodiment of the present disclosure.

[0180] Referring to FIG. 5, the nutrient solution management system (1000) may include a sensor device (100), a server (200), a nutrient solution management device (300), and a control device (400).

[0181] The control device (400) is a device for controlling the overall nutrient solution management system (1000).

[0182] As an example, the control device (400) may transmit information received from the sensor device (100) and the culture solution management device (300) to the server (200), or transmit information received from the server (200) to the sensor device (100) and the culture solution management device (300).

[0183] Meanwhile, the control device (400) may include at least one control circuit or one or more processors. At this time, the processor may be composed of various units such as a CPU (Central Processing Unit), an AP (Application Processor), a GPU (Graphics Processing Unit), a VPU (Vision Processing Unit), and an NPU (Neural Processing Unit).

[0184] In addition, the control device (400) may include memory. At this time, the memory may include non-volatile memory such as ROM or flash memory, volatile memory composed of DRAM, etc., hard disk, SSD (Solid state drive), etc.

[0185] For example, the control device (400) may be implemented as a PLC (Programmable Logic Controller), but is not limited thereto.

[0186] FIG. 6 is a flowchart illustrating the operation of a nutrient solution management system according to one embodiment of the present disclosure.

[0187] Referring to FIG. 6, the sensor device (100) can measure component information of the nutrient solution contained in the nutrient solution tank (S610).

[0188] In one embodiment, the sensor device (100) can measure the absorbance for a component matching the wavelength range of light emitted toward the nutrient solution using at least one sensor.

[0189] At this time, the sensor device (100) can calculate the concentration value for each component based on the coefficients matched and stored for each component and the absorbance measured for each component.

[0190] The sensor device (100) can transmit information on the components of the nutrient solution to the control device (400) (S620).

[0191] As an example, the sensor device (100) can transmit component information including the components contained in the nutrient solution and the concentration of each component to the control device (400).

[0192] As an additional example, the sensor device (100) may transmit component information of the nutrient solution, including the absorbance measured for each component, to the control device (400).

[0193] The control device (400) can analyze the components of the nutrient solution based on the component information received from the sensor device (100) (S630).

[0194] In one embodiment, when component information of a nutrient solution including absorbance measured for each component is received from a sensor device (100), the control device (400) can analyze the components of the nutrient solution by calculating a concentration value for each component based on the component information received from the sensor device (100) and a coefficient matched and stored for each component.

[0195] The control device (400) can transmit the analysis information obtained through analysis to the server (200) (S640).

[0196] As an example, the control device (400) may transmit analysis information including component information received from the sensor device (100) and component-specific concentration values ​​calculated based on pre-stored coefficients matched for each component to the server (200).

[0197] The server (200) can select at least one target component whose concentration needs to be adjusted among the components included in the nutrient solution of the nutrient solution tank based on the analysis information received from the control device (400) (S650).

[0198] As an example, the server (200) can identify necessary component information matching a crop selected according to user input based on necessary component information of a pre-stored nutrient solution according to the type of crop.

[0199] At this time, the information on the required components of the stored nutrient solution depending on the type of crop may include information on the components of the nutrient solution and the concentration range of each component required to provide nutrients suitable for the growth of each type of crop.

[0200] Through this, the server (200) can identify a component requiring concentration correction as a target component based on the necessary component information matched with the crop selected according to user input and the component information received from the sensor device (100).

[0201] For example, the server (200) can identify a component whose concentration identified according to the component information is below the concentration range set according to the required component information as an additional target component, and can identify a component whose concentration identified according to the component information is above the concentration range set according to the required component information as an additional target component.

[0202] In addition, the server (200) may obtain information on the necessary components of the nutrient solution that needs to be supplied to the crop by using at least one artificial intelligence model to predict information on the components of the nutrient solution that needs to be supplied to the crop based on the time elapsed since the sowing of the crop.

[0203] Specifically, as time passes after sowing the crop and the crop grows, the information on the components of the nutrient solution required to be supplied to the crop changes, so the server (200) can obtain the information on the required components of the nutrient solution by using the first artificial intelligence model for predicting the information on the required components of the nutrient solution according to the type of crop and the time of sowing, which is the time when the cultivation of the crop begins by planting the seeds or sprouts of the crop.

[0204] For example, the server (200) can obtain information on the necessary components of the nutrient solution from the first artificial intelligence model by inputting the type of crop and the sowing time obtained according to the user input into the artificial intelligence model.

[0205] At this time, the server (200) can obtain information on the time elapsed from the time of sowing the crop and the component information of the nutrient solution matched with each elapsed time for each type of crop to configure training data, and train the first artificial intelligence model based on the configured training data.

[0206] Meanwhile, the server (200) may obtain from an external source and use a first artificial intelligence model that has been trained to output information on the required components of nutrient solution according to the time elapsed since sowing of the crop.

[0207] At this time, the first artificial intelligence model may be a model based on various learning algorithms such as CNN (Convolution Neural Network), RNN (Recurrent Neural Network), and Transformer, but is not limited thereto.

[0208] The server (200) can transmit control information for adjusting the concentration of the target component to the control device (400) (S660).

[0209] For example, the server (200) can transmit control information for adding additional target components to the control device (400).

[0210] For example, the server (200) may transmit control information including information about raw materials to be added to the nutrient solution tank for dilution of the diluted component, raw materials containing a component whose concentration is expected to change according to the addition of the raw material and thus be identified as the added component, to the control device (400).

[0211] At this time, information about the raw material may include identification information of the raw material, identification information of the raw material tank containing the raw material, the amount of raw material to be added, etc., and the identification information may be expressed as numbers, letters, symbols, etc., but is not limited thereto.

[0212] At this time, information about the raw material may include identification information of the raw material, identification information of the raw material tank containing the raw material, the amount of raw material to be added, etc., and the identification information may be expressed as numbers, letters, symbols, etc., but is not limited thereto.

[0213] Additionally, the server (200) can transmit control information for dilution of the dilution target component to the control device (400).

[0214] For example, the server (200) may transmit control information including information about the raw material containing the component whose concentration is expected to be diluted and identified as the additional target component according to the addition of the raw material for the dilution of the target component to be diluted, to the control device (400).

[0215] The control device (400) can transmit a control signal to the culture solution management device (300) to adjust the concentration of the target component according to the control information received from the server (200) (S670).

[0216] For example, the control device (400) can transmit a control signal to the culture solution management device (300) to adjust the concentration of the target component according to control information for adding additional target components received from the server (200).

[0217] In addition, the control device (400) can transmit a control signal for adjusting the concentration of the target component according to the control information for dilution of the target component received from the server (200) to the culture solution management device (300).

[0218] Meanwhile, when control information including identification information of a raw material is received from the server (200), the control device (400) can transmit a control signal including identification information of a raw material tank matched with the identification information of the raw material to the culture solution management device (300).

[0219] To this end, the identification information of each raw material and the identification information of the raw material tank containing the raw material may be matched and stored in the control device (400).

[0220] The culture solution management device (300) can select a raw material tank containing the raw material required to correct the concentration of the target component according to a control signal received from the control device (400) (S680).

[0221] As an example, the culture solution management device (300) can select a raw material tank based on identification information of the raw material tank included in a control signal received from the control device (400).

[0222] The culture solution management device (300) can add the raw material contained in the selected raw material tank to the nutrient solution in the nutrient solution tank (S690).

[0223] As an example, the culture solution management device (300) can control a pump connected to a selected raw material tank according to a control signal received from the server (200) to supply raw materials contained in the raw material tank to a nutrient solution tank.

[0224] For example, the culture solution management device (300) can control the number of operations of a pump connected to the selected raw material tank to add a set amount of raw material contained in the selected raw material tank to the nutrient solution tank according to a control signal received from the server (200).

[0225] Meanwhile, the various embodiments described above may be implemented in a recording medium readable by a computer or similar device using software, hardware, or a combination thereof.

[0226] In terms of hardware implementation, the embodiments described in the present disclosure may be implemented using at least one of Application Specific Integrated Circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions.

[0227] In some cases, the embodiments described herein may be implemented within the processor itself. In a software implementation, the embodiments described herein, such as the procedures and functions described herein, may be implemented as separate software modules. Each of the software modules described above may perform one or more of the functions and operations described herein.

[0228] Meanwhile, computer instructions for performing processing operations in electronic devices and the like according to the various embodiments of the present disclosure described above may be stored in a non-transitory computer-readable medium. When the computer instructions stored in such a non-transitory computer-readable medium are executed by a processor of a specific device, they cause the specific device to perform processing operations according to the various embodiments described above.

[0229] A non-transitory computer-readable medium refers to a medium that permanently stores data and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specific examples of non-transitory computer-readable media include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0230] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person having ordinary skill in the art to which the present disclosure pertains without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

Claims

1. In the operating method of the nutrient solution management system, A step of a sensor device measuring component information of a nutrient solution contained in a nutrient solution tank using at least one sensor and transmitting the measured component information to a server; A step in which the server selects at least one target component whose concentration needs to be adjusted among the components contained in the nutrient solution of the nutrient solution tank based on the component information received from the sensor device; The step of the server transmitting a control signal for controlling the concentration of the target component to the culture medium management device; and An operating method of a nutrient solution management system, comprising: a step of selecting a raw material tank containing raw materials necessary for correcting the concentration of the target component according to a control signal received from the server, and adding the raw materials contained in the selected raw material tank to the nutrient solution in the nutrient solution tank; 2. In paragraph 1, The step of selecting at least one target component comprises: The step of the server identifying the necessary component information of the nutrient solution matched with the selected crop according to user input; and A method of operating a nutrient solution management system, comprising: a step of identifying, by the server, at least one target component whose concentration needs to be adjusted among the components included in the nutrient solution of the nutrient solution tank, based on the necessary component information of the identified nutrient solution and the component information received from the sensor device; 3. In paragraph 2, The step of identifying the necessary component information of the above nutrient solution is: An operating method of a nutrient solution management system, wherein the server obtains information on the required components of a pre-stored nutrient solution that matches the type of crop selected according to user input.

4. In paragraph 2, The step of identifying the necessary component information of the above nutrient solution is: A method of operating a nutrient solution management system, wherein the server inputs the type of crop and the sowing time obtained according to user input into at least one artificial intelligence model for predicting the components of the nutrient solution required to be supplied to the crop based on the elapsed time since the sowing of the crop, and obtains information on the required components of the nutrient solution from the artificial intelligence model.

5. In paragraph 1, The step of adding the selected raw material to the nutrient solution in the nutrient solution tank is: An operating method of a nutrient solution management system, wherein the culture solution management device controls a pump connected to a raw material tank containing the selected raw material to supply the raw material contained in the selected raw material tank to the nutrient solution tank in an amount set according to the control signal.

6. In paragraph 1, The operating method of the above nutrient management system is as follows: A step in which the sensor device measures the component information of raw materials contained in at least one raw material tank using at least one sensor and transmits the measured component information to the server; and A method of operating a nutrient solution management system, comprising: a step of identifying whether a raw material is defective based on component information received from the sensor device; 7. In paragraph 6, The step of identifying whether the above raw materials are defective is as follows: The server identifies raw materials whose component information is different from the basic component information as defective raw materials based on the component information received from the sensor device and the basic component information stored for each raw material contained in the raw material tank. The operating method of the above nutrient management system is as follows: The server identifies at least one defective ingredient that is not included in the basic ingredient information for the defective raw material among the ingredients included in the ingredient information of the defective raw material received from the sensor device; and A method of operating a nutrient solution management system, comprising: a step in which the server identifies the concentration of the defective ingredient from the component information of the defective ingredient received from the sensor device, and identifies the contamination level of the defective ingredient based on the identified concentration of the defective ingredient.

8. In the operating method of the nutrient solution management system, A step of a sensor device measuring component information of a nutrient solution contained in a nutrient solution tank using at least one sensor and transmitting the measured component information to a control device; A step in which the control device analyzes the components of the nutrient solution based on the component information and transmits the analysis information obtained according to the analysis to the server; A step in which the server selects at least one target component whose concentration needs to be adjusted among the components included in the nutrient solution of the nutrient solution tank based on the analysis information received from the control device; A step in which the server transmits control information for adjusting the concentration of the target component to the control device; A step in which the control device transmits a control signal to the culture medium management device for adjusting the concentration of the target component according to the control information received from the server; and An operating method of a nutrient solution management system, comprising: a step of selecting a raw material tank containing raw materials necessary for correcting the concentration of the target component according to a control signal received from the control device, and adding the raw materials contained in the selected raw material tank to the nutrient solution in the nutrient solution tank;

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