KR20240083261A - System for managing artificial intelligence smart farm - Google Patents

Abstract

The present invention relates to an artificial intelligence smart farm management system, which includes one or more sensor units installed in a specific space to generate sensing information; A database that stores sensing information, control information, and data related to the efficacy of active ingredients in medicinal materials according to the sensing information, and a sensor unit that collects sensing information at a preset cycle during the growth period of medicinal ingredients in a specific space, and A main control unit that generates optimal control information that maximizes the efficacy of the active ingredient using an environmental control algorithm according to data related to the efficacy of the active ingredient in the medicine, and an artificial intelligence algorithm using sensing information and optimal control information. A server including an update unit that learns and updates an environmental control algorithm; and a device control unit that controls a plurality of controlled devices connected by wire according to optimal control information.

Description

Artificial Intelligence Smart Farm Management System{SYSTEM FOR MANAGING ARTIFICIAL INTELLIGENCE SMART FARM}

The present invention relates to an artificial intelligence smart farm management system, and in particular, generates optimal control information that maximizes the efficacy of the active ingredient by using an environmental control algorithm according to data related to the efficacy of the active ingredient in the medicine according to the sensing information, thereby generating multiple It is about an artificial intelligence smart farm management system that controls controlled devices.

The matters described in this background art section are written to improve understanding of the background of the invention, and may include matters that are not prior art already known to those skilled in the art in the field to which this technology belongs.

In general, smart farms, a concept introduced to maximize the production and quality of agricultural products through precise environmental control, are attracting attention as a solution to the food security crisis facing humanity. Here, the smart farm mainly controls the temperature, humidity, amount of light, and carbon dioxide concentration inside the greenhouse. In the case of farms using hydroponic cultivation, the temperature, pH, electrical conductivity of the nutrient solution, or even the concentration of individual nutrients that make up the nutrient solution are controlled. However, it is unclear to what extent this smart farm environmental control system increases crop production and quality in the long term. First, the smart farm environmental control system issues control commands by comparing pre-entered optimal growth environment data for each crop with measurement data from various sensors installed in the greenhouse. In many cases, even after the control command is executed, the greenhouse environment remains the same. It is understood that the target value has not been reached, and this is because the climate of the area where the greenhouse is located and the configuration of the control elements (motor, pump, etc.) are all different. In addition, the optimal growth environment for cultivated crops can also vary depending on various conditions, such as the type of seed used in the farm, the state of seedlings, and the unique environment of each greenhouse.

However, the current smart farm environmental control system has a problem in that it does not sufficiently consider these uncertainties.

Therefore, there is a need for an environmental control system that can efficiently manage smart farms by utilizing artificial intelligence technology, which has recently achieved rapid technological progress.

Korean Patent Publication No. 10-2300229

The present invention generates optimal control information that maximizes the efficacy of the active ingredient according to data related to the efficacy of the active ingredient in the medicine according to the sensing information, and controls a plurality of control target devices to supply medicine with maximized efficacy of the active ingredient. The purpose is to provide an artificial intelligence smart farm management system.

The present invention uses a user terminal to receive and display sensing information, control information, and data related to the efficacy of the active ingredient in the medicinal product according to the sensing information, and scores and inputs data related to the efficacy of the effective ingredient in the medicinal product according to the sensing information to determine the effectiveness of the active ingredient. The purpose is to provide an artificial intelligence smart farm management system that allows optimal control information with maximized efficacy to be conveniently generated using a user terminal.

In the present invention, when the main control unit generates optimal control information, the user terminal stores the optimal control information, so that the user can easily obtain data related to the efficacy of the active ingredient in the medicine according to the sensing information based on the already stored optimal control information. The purpose is to provide an artificial intelligence smart farm management system that can compare, score, and input data.

The purpose of the present invention is to provide an artificial intelligence smart farm management system that allows the user to evaluate and manage the efficacy of medicines by scoring and entering data related to the efficacy of active ingredients in medicines according to sensing information through a user terminal.

The purpose of the present invention is to provide an artificial intelligence smart farm management system that allows users to easily check current optimal drug efficacy data anytime, anywhere using a user terminal.

An artificial intelligence smart farm management system according to an embodiment of the present invention includes one or more sensor units installed in a specific space to generate sensing information; A database that stores sensing information, control information, and data related to the efficacy of active ingredients in medicinal materials according to the sensing information, and a sensor unit that collects sensing information at a preset cycle during the growth period of medicinal ingredients in a specific space, and A main control unit that generates optimal control information that maximizes the efficacy of the active ingredient using an environmental control algorithm according to data related to the efficacy of the active ingredient in the medicine, and an artificial intelligence algorithm using sensing information and optimal control information. A server including an update unit that learns and updates an environmental control algorithm; and a device control unit that controls a plurality of controlled devices connected by wire according to optimal control information.

Here, it further includes a user terminal that is connected to the database and extracts and displays sensing information, control information, and data related to the efficacy of the active ingredient in the medicine according to the sensing information, and the data related to the efficacy of the active ingredient in the medicine according to the sensing information are: Scores are entered into the user terminal and stored in the database.

In addition, when the main control unit generates optimal control information, it transmits sensing information, optimal control information, and data related to the efficacy of the active ingredients in the medicine according to the sensing information to the user terminal, and the user terminal receives the input and performs the processing according to the sensing information. Data related to the efficacy of the active ingredient in the medicinal product are updated and stored as data related to the efficacy of the active ingredient in the medicinal ingredient with optimal control information.

According to the present invention, optimal control information that maximizes the efficacy of the active ingredient is generated according to data related to the efficacy of the active ingredient in the medicine according to the sensing information, and a plurality of control target devices are controlled to control the medicine with the maximum efficacy of the active ingredient. can be supplied.

According to the present invention, by using a user terminal, sensing information, control information, and data related to the efficacy of the active ingredient in the medicine according to the sensing information are received and displayed, and data related to the efficacy of the active ingredient in the medicine according to the sensing information are scored and entered. Optimal control information that maximizes the efficacy of active ingredients can be conveniently created using a user terminal.

According to the present invention, when the main control unit generates optimal control information, the user terminal stores the optimal control information, so that the user can obtain data related to the efficacy of the active ingredient in the medicine according to the sensing information based on the already stored optimal control information. You can easily compare, score, and enter.

According to the present invention, the user can evaluate and manage the efficacy of a medicine by scoring and inputting data related to the efficacy of the active ingredient in the medicine according to the sensing information through the user terminal.

According to the present invention, users can easily obtain optimal drug efficacy data anytime, anywhere using a user terminal.

Figure 1 is a block diagram of an artificial intelligence smart farm management system according to an embodiment of the present invention.
Figure 2 is a block diagram showing a server according to an embodiment of the present invention.
Figure 3 is a block diagram of an artificial intelligence smart farm management system according to another embodiment of the present invention.
Figure 4 is a block diagram showing a state in which a user terminal is connected to a server according to another embodiment of the present invention.
Figure 5 is a screen of a user terminal evaluating the efficacy of betaine and linolenic acid in goji berry according to sensing information according to an embodiment of the present invention.
Figure 6 is a screen of a user terminal requesting to update the efficacy of betaine and linolenic acid in goji berry according to sensing information according to an embodiment of the present invention.
Figure 7 is a flowchart showing the operation process of the artificial intelligence smart farm management system according to this embodiment.

The advantages and features of the present invention and methods for achieving them will become clear with reference to the embodiments described below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. Only the examples are provided to make the disclosure of the present invention complete and to fully convey the scope of the invention to those skilled in the art to which the present invention pertains, and that the present invention is defined by the scope of the claims. It's just that.

Figure 1 is a block diagram showing an artificial intelligence smart farm management system according to an embodiment of the present invention. Figure 2 is a block diagram showing a server according to an embodiment of the present invention. Figure 3 is a block diagram of an artificial intelligence smart farm management system according to another embodiment of the present invention. Figure 4 is a block diagram showing a state in which a user terminal is connected to a server according to another embodiment of the present invention.

1 and 3 have a difference in whether the user terminal 500 is included, and FIGS. 2 and 4 also have a difference in whether the user terminal 500 is included. The user terminal 500 is not an essential configuration and can be configured as needed.

Referring to FIGS. 1 and 3, the artificial intelligence smart farm management system 1000 includes a sensor unit 100, a server 200, a device control unit 300, a gateway 400, and a user terminal 500. ) may include. The sensor unit 100, server 200, device control unit 300, gateway 400, and user terminal 500 are connected to each other through a network.

Here, the network refers to a wired or wireless communication network such as the Internet, or a combination thereof. In one embodiment of the present invention, the network has no particular limitations and can be interpreted to include both the conventional Internet and mobile communication networks. .

For example, the artificial intelligence smart farm management system 1000 includes a sensor unit 100, a server 200, a device control unit 300, a gateway 400, and a user terminal 500 connected to a conventional network such as an Internet network or a mobile communication network. It should be noted that it can be combined by various network combinations, and there are no special restrictions on this.

Users can receive artificial intelligence smart farm management services by downloading and installing the artificial intelligence smart farm management service application on their terminals and then connecting to the artificial intelligence smart farm management system 1000.

Then, below, we will look at each configuration of the artificial intelligence smart farm management system (1000).

One or more sensor units 100 are installed in a specific space and generate sensing information. The specific space may be a house, but is not limited thereto. If there are four sensor units 100, let's say they are a first sensor unit, a second sensor unit, a third sensor unit, and a fourth sensor unit.

At this time, the first sensor unit may be configured to sense at least one of the external temperature, external humidity, wind direction, wind speed, rainfall, and light amount of the specific space, and the second sensor unit may be configured to sense one of the internal temperature, internal humidity, and internal carbon dioxide concentration of the specific space. It may be configured to sense at least one. In addition, the third sensor unit may be configured to detect at least one of the amount of internal light in a specific space and the electrical conductivity (EC) and acidity (pH) of the chemical solution supplied to the medium, and the fourth sensor unit may be configured to detect the electrical conductivity (EC) and acidity (pH) of the chemical solution supplied to the medium. It may be configured to detect at least one of conductivity and acidity.

The server 200 may include a database 210, a main control unit 220, and an update unit 230, and details will be described below with reference to FIGS. 2 and 4.

The device control unit 300 controls a plurality of controlled devices connected by wire according to optimal control information. Here, the plurality of controlled devices may be devices located in a specific space, such as a heating device, a motor that controls the opening and closing operation of a side window or skylight, an LED (Light Emitting Diode) lighting device, and a humidifier, but are not limited thereto.

The gateway 400 connects communication between the sensor unit 100, the server 200, and the device control unit 300. That is, the gateway 400 is connected to the sensor unit 100, the server 200, and the device control unit 300 through a communication network to transmit and receive data.

The user terminal 500 is connected to the database 210 and extracts and displays sensing information, control information, and data related to the efficacy of the active ingredient in the medicine according to the sensing information. Data related to the efficacy of the active ingredients in the medicine according to the sensing information are scored and entered into the user terminal 500 by the user and stored in the database. Scoring may be a percentage (%), but is not limited thereto. The higher the percentage scored by the user, the higher the efficacy of the active ingredient in the medicine.

When the main control unit 220 generates optimal control information, it transmits sensing information, optimal control information, and data related to the efficacy of the active ingredient in the medicine according to the sensing information to the user terminal 500. At this time, the user terminal 500 Receives input and updates and stores data related to the efficacy of the active ingredient in the medicine according to the sensing information into data related to the efficacy of the active ingredient in the medicine with optimal control information.

In this way, the user can easily obtain the optimal drug efficacy data anytime, anywhere using the user terminal.

Referring to FIGS. 2 and 4 , the server 200 includes a database 210, a main control unit 220, and an update unit 230. The user terminal 500 may be connected to the database 210.

The database 210 stores sensing information, control information, and data related to the efficacy of active ingredients in medicinal ingredients according to the sensing information. Here, the medicinal ingredients may include, but are not limited to, wolfberry, angelica root, licorice, ginseng, reishi, Schisandra chinensis, Cheonggung, and Astragalus. The active ingredients in the herbal medicine may include, but are not limited to, saponin, flavonoids, tannin, potassium, vitamins, comarin, minerals, acondoside D, cobalt nitrate, palmitic acid, elotheroside E, and sesamin. The efficacy of the active ingredient may include, but is not limited to, appetite enhancement, anti-aging, anticancer effect, nerve stability, immune enhancement, and antibacterial effect.

The main control unit 220 collects sensing information from the sensor unit 100 at a preset period during the growth period of the medicinal material in a specific space. For example, the main control unit 220 collects sensing information every 6 hours for 6 months, which is the growth period of the medicinal material.

In addition, the main control unit 220 generates optimal control information that maximizes the efficacy of the active ingredient using an environmental control algorithm according to the sensing information and data related to the efficacy of the active ingredient in the medicinal product according to the sensing information. The environmental control algorithm receives sensing information as input and calculates control information, which is the most appropriate output value, according to the sensing information. Here, the control information may include at least one of ON/OFF control, motor drive direction control, step control, and time control.

Additionally, the main control unit 220 stores the collected sensing information and control information in the database 210.

In addition, when generating optimal control information, the main control unit 220 transmits sensing information, optimal control information, and efficacy-related data of the active ingredients in the medicine according to the sensing information to the user terminal 500.

The update unit 230 learns and updates the environmental control algorithm through an artificial intelligence algorithm using sensing information and control information.

Here, artificial intelligence technology is represented by a group of representative technologies such as machine learning and deep learning, and is a technology that utilizes vast amounts of data to make decisions about new inputs.

Machine learning, a field of artificial intelligence, literally involves machines learning and can predict the future by analyzing large-scale big data. Machine learning can design complex algorithms or programming and can be applied to a variety of fields. Three methods are used to create machine learning algorithms.

First of all, it is a supervised learning method in which the user inputs pre-created data and then produces output. Since the supervised learning method increases accuracy as much as the input data, it produces more reliable output values as the amount of data increases.

Next, it is an unsupervised learning method that models patterns with only input without output. The unsupervised learning method is a method in which a computer learns on its own and then applies it to derive the desired output value. It requires a high level of computing power and is used in data mining techniques.

Lastly, it is a reinforcement learning method, which is a method of creating an algorithm by re-learning the feedback generated after the computer learns a large amount of data on its own.

Machine learning learns data through the three methods above, analyzes patterns, and then has the ability to make direct decisions based on ever-changing situations.

In addition, deep learning is composed of several layers of artificial neural networks and is one of the learning methods belonging to machine learning. Deep learning can judge various situations on its own without having to learn them directly.

In order for deep learning to be used effectively, a lot of data must be accumulated to produce reliable results. Deep learning can identify certain patterns using big data and analyze not only shapes and forms but also abstract objects.

The update unit 230 updates the medicinal material data by learning an environmental control algorithm through an artificial intelligence algorithm in addition to the sensing information, control information, and data related to the efficacy of the active ingredient in the medicinal material according to the sensing information stored in the database 210. Here, the medicinal material data may include at least one of type data, state data at the time of purchase, state data of seedlings, production data according to state, growth period data, and quality data.

The update unit 230 updates the environmental control algorithm through an artificial intelligence algorithm using sensing information and control information about medicinal materials grown in a specific space based on medicinal material data, and data related to the efficacy of active ingredients in medicinal ingredients according to the sensing information. Learn and update.

For example, the update unit 230 provides an environment for cultivating medicinal materials based on at least one medicinal material data of type data, state data at the time of purchase, state data of seedlings, production data according to state, growth period data, and quality data. The environmental control algorithm is learned and updated through an artificial intelligence algorithm using sensing information, control information, and data on the effectiveness of the active ingredients of the medicine.

Figure 5 is a screen of a user terminal evaluating the efficacy of betaine and linolenic acid in goji berry according to sensing information according to an embodiment of the present invention.

Referring to Figure 5, there is a guide on the screen of the user terminal to evaluate the efficacy of betaine and linolenic acid in goji berry according to the sensing information, and it can be seen that the evaluation was 85% based on the user input. When you press the “Enter” button below, the evaluated efficacy is entered.

Figure 6 is a screen of a user terminal requesting to update the efficacy of betaine and linolenic acid in goji berry according to sensing information according to an embodiment of the present invention.

Referring to Figure 6, there is a guide on the screen of the user terminal to update the efficacy of betaine and linolenic acid in goji berry according to the sensing information, and the update is possible on the moved screen.

Figure 7 is a flowchart showing the operation process of the artificial intelligence smart farm management system according to this embodiment.

Referring to FIGS. 1, 2, and 7, the operation process of the artificial intelligence smart farm management system may include S100 to S800.

First, one or more sensor units 100 installed in a specific space generate sensing information (S100). The specific space may be a house, but is not limited thereto. If there are four sensor units 100, let's say they are a first sensor unit, a second sensor unit, a third sensor unit, and a fourth sensor unit.

At this time, the first sensor unit may be configured to sense at least one of the external temperature, external humidity, wind direction, wind speed, rainfall, and light amount of the specific space, and the second sensor unit may be configured to sense one of the internal temperature, internal humidity, and internal carbon dioxide concentration of the specific space. It may be configured to sense at least one. In addition, the third sensor unit may be configured to detect at least one of the amount of internal light in a specific space and the electrical conductivity (EC) and acidity (pH) of the chemical solution supplied to the medium, and the fourth sensor unit may be configured to detect the electrical conductivity (EC) and acidity (pH) of the chemical solution supplied to the medium. It may be configured to detect at least one of conductivity and acidity.

After S100, the main control unit 220 of the server 200 collects sensing information from the sensor unit 100 at a preset period during the growth period of the herb in a specific space (S200). For example, the main control unit 220 collects sensing information every 6 hours for 6 months, which is the growth period of the medicinal material.

After S200, the main control unit 220 of the server 200 generates optimal control information that maximizes the efficacy of the active ingredient using an environmental control algorithm according to the sensing information and data related to the efficacy of the active ingredient in the medicinal ingredient according to the sensing information. Do it (S300). The environmental control algorithm receives sensing information as input and calculates control information, which is the most appropriate output value, according to the sensing information. Here, the control information may include at least one of ON/OFF control, motor drive direction control, step control, and time control.

After S300, the main control unit 220 of the server 200 transmits control information to the device control unit 230 (S400).

After S400, the device control unit 230 controls a plurality of control target devices connected by wire according to the control information received from the main control unit 220 of the server 200 (S500). Here, the plurality of controlled devices may be devices located in a specific space, such as a heating device, a motor that controls the opening and closing operation of a side window or skylight, an LED (Light Emitting Diode) lighting device, and a humidifier, but are not limited thereto.

After S500, the main control unit 220 of the server 200 collects sensing information from the sensor unit 100 at a preset period during the growth period of the herb in a specific space (S600). For example, the main control unit 220 collects sensing information every 6 hours for 6 months, which is the growth period of the medicinal material.

After S600, the update unit 230 of the server 200 learns and updates the environmental control algorithm through an artificial intelligence algorithm (S700). Here, the update unit 230 of the server 200 can learn and update the environmental control algorithm through an artificial intelligence algorithm using herbal medicine data in addition to the sensing information and control information.

After S700, the update unit 230 of the server 200 commands the updated environment control algorithm to be used in S300 (S800).

In FIG. 3, steps S100 to S800 are described as being sequentially executed, but this is merely an illustrative explanation of the technical idea of this embodiment. Those of ordinary skill in the technical field to which this embodiment pertains may change the order shown in FIG. 3 without departing from the essential characteristics of this embodiment, or execute one or more of steps S100 to S800 in parallel. Since it may be applied with various modifications and modifications, FIG. 3 is not limited to a time series order.

The system described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, the devices and components described in the embodiments include a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), and a programmable logic unit (PLU). It may be implemented using one or more general-purpose or special-purpose computers, such as a logic unit, microprocessor, or any other device capable of executing and responding to instructions.

The processing device may execute an operating system (OS) and one or more software applications running on the operating system. Additionally, the processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, there are cases where a single processing device is described as being used, but those skilled in the art will understand that the processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, the processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. The software and/or data may be embodied in any type of machine, component, physical device, computer storage medium or device for the purpose of being interpreted by or providing instructions or data to the processing device. there is. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. At this time, the medium may continuously store a computer-executable program, or temporarily store it for execution or download. In addition, the medium may be a variety of recording or storage means in the form of a single or several pieces of hardware combined. It is not limited to a medium directly connected to a computer system and may be distributed over a network. Examples of media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, And there may be something configured to store program instructions, including ROM, RAM, flash memory, etc. Additionally, examples of other media include recording or storage media managed by app stores that distribute applications, sites or servers that supply or distribute various other software, etc.

The embodiments of the present invention described above have been described with reference to the embodiments shown in the drawings to aid understanding, but these are merely exemplary, and those skilled in the art will be able to make various modifications and other equivalent embodiments therefrom. You will understand that it is possible. Therefore, the true technical protection scope of the present invention should be determined by the appended claims.

100: sensor unit 200: server
210: database 220: main control unit
230: Update unit 300: Device control unit 400: Gateway 500: User terminal
1000: Artificial intelligence smart farm management system

Claims (3)

One or more sensor units installed in a specific space to generate sensing information;
A database that stores the sensing information, control information, and efficacy-related data of the active ingredients in the herbal medicine according to the sensing information, and collects the sensing information from the sensor unit at a preset cycle during the growth period of the herb in a specific space, and the sensing A main control unit that generates optimal control information that maximizes the efficacy of the active ingredient using an environmental control algorithm according to information and data related to the efficacy of the active ingredient in the medicine according to the sensing information, and the sensing information and the optimal control A server including an update unit that learns and updates the environment control algorithm through an artificial intelligence algorithm using information; and
Device control unit that controls multiple controlled devices connected by wire according to the optimal control information
An artificial intelligence smart farm management system comprising:
According to paragraph 1,
It further includes a user terminal that is connected to the database and extracts and displays data related to the efficacy of the active ingredient in the medicine according to the sensing information, the control information, and the sensing information, and displays information related to the efficacy of the active ingredient in the medicine according to the sensing information. A smart farm management system, characterized in that data is scored and entered into the user terminal and stored in the database.
According to paragraph 2,
When generating the optimal control information, the main control unit transmits the sensing information, the optimal control information, and efficacy-related data of the active ingredient in the medicine according to the sensing information to the user terminal,
The user terminal is a smart farm management system characterized by receiving input, updating and storing data related to the efficacy of the active ingredient in the medicinal product according to the sensing information into data related to the efficacy of the active ingredient in the medicinal ingredient with optimal control information.