KR102421031B1 - Method and apparatus for analysing soil based on moisture change in soil - Google Patents

Abstract

In an operating method of a control server that performs a soil analysis based on a moisture change in a soil according to one embodiment of the present specification, the operating method may comprise: a step of measuring an amount of moisture in the soil from each of a plurality of sensor nodes based on the location information and depth information of the plurality of sensor nodes installed; a step of determining a soil property based on the amount of moisture in the soil measured from each of the plurality of sensor nodes; and a step of supplying raw water and nutrient solution based on the determined soil property.

Description

Soil analysis method and apparatus based on moisture change in soil

Embodiments relate to a method and apparatus for performing soil analysis based on a change in moisture in the soil. More specifically, it relates to a method and apparatus for detecting a change in moisture in soil through a plurality of sensor nodes in an open-field smart farm, and performing soil analysis based thereon.

Smart farm is a farm that can properly maintain and manage the growing environment of crops or livestock remotely and automatically by grafting Information Communication Technology to existing farming technologies such as plastic houses and livestock. refers to related technologies. By using a smart farm, it is possible to improve the productivity and quality of agricultural products by creating an optimal growth environment based on data on crop growth information and environmental information. In this case, in order to manage the smart farm by grafting information and communication technology, a platform through which the user can access the data of the smart farm and read necessary contents may be required. In addition, since smart farms manage crops in a wide area, a method for efficiently managing them may be required. In addition, there is a need for a method for efficiently supplying raw water to crops located in a wide area. Hereinafter, a method of analyzing the soil by detecting a change in moisture in the soil based on the smart farm will be described.

Korean Patent Registration No. 10-2019-0057220 A

The present specification relates to a method and apparatus for analyzing soil based on a change in moisture in the soil.

The present specification relates to a method and an apparatus for analyzing soil based on a plurality of sensors for detecting a change in moisture in the soil in an open-field smart farm.

The present specification relates to a method and an apparatus for recognizing a plurality of sensor positions in soil based on sample information about a change in moisture in the soil, and analyzing the soil based on the recognized plurality of sensors.

The present specification relates to a method and apparatus for analyzing soil by detecting a change in moisture in the soil based on surrounding environment information.

The problem to be solved in the present specification is not limited to the above, but may be extended to various matters that can be derived by the embodiments of the invention described below.

According to an embodiment of the present specification, in the method of operating a control server for performing soil analysis based on a change in moisture in the land, the soil from each of the plurality of sensor nodes based on location information and depth information in which a plurality of sensor nodes are installed It may include measuring the amount of moisture in the soil, determining a soil characteristic based on the amount of moisture in the soil measured from each of a plurality of sensor nodes, and supplying raw water and a nutrient solution based on the determined soil characteristic.

In addition, according to an embodiment of the present specification, in the control server for performing soil analysis based on the change in moisture in the land, a plurality of installed in the form of a mesh in the smart farm and sensing crop-related information in the smart farm A control server comprising a sensor node, a control unit for performing soil analysis based on sensing values obtained from a plurality of sensor nodes, and an irrigation device for supplying raw water and nutrient solution based on the analyzed characteristics of the soil, a plurality of sensor nodes The amount of moisture in the soil is measured from each of the plurality of sensor nodes based on the location information and the depth information installed, and the soil property is determined based on the amount of moisture in the soil measured from each of the plurality of sensor nodes, and the raw water is and a nutrient solution may be supplied.

In addition, the following may be commonly applied.

According to an embodiment of the present specification, when measuring the amount of moisture in the soil based on the first sensor node among the plurality of sensor nodes, the control server supplies water above the saturated water amount based on the location information and depth information of the first sensor node. and measure the amount of moisture varying in a preset time interval based on the water supply to obtain moisture content change graph information.

In addition, according to an embodiment of the present specification, the control server determines the soil characteristics by comparing the moisture content change graph information with the reference moisture content change graph information, and the reference moisture content change graph information is pre-generated information based on the soil characteristics. can

In addition, according to an embodiment of the present specification, when the moisture content change graph information and the reference moisture content change graph information are compared, soil nutrient information, organic matter information, metal material information, pollutant information, temperature information, and the first sensor node At least one of the location information and the depth information of the first sensor node may be reflected, and based on the reflected information, the moisture content change graph information and the reference moisture content change graph information may be compared.

In addition, according to an embodiment of the present specification, the control server may include an artificial intelligence learning model, and may compare moisture content change graph information with reference moisture content change graph information based on the artificial intelligence learning model.

In addition, according to an embodiment of the present specification, the control server checks whether the location of each of the plurality of sensor nodes is a suitable location based on the crop location information based on the amount of moisture in the soil sensed by each of the plurality of sensor nodes, When the location of each of the plurality of sensor nodes is not a suitable location, the control server may move the location of each of the plurality of sensor nodes by providing a notification to the user terminal or by controlling each of the plurality of sensor nodes.

In addition, according to an embodiment of the present specification, when it is checked whether the location of the first sensor node among the plurality of sensor nodes is appropriate, moisture change amount information and soil-related information are obtained from the first sensor node, and soil-related information It is possible to obtain reference moisture change information based on , and compare the moisture change information obtained from the first sensor node with the reference moisture change information to determine whether the location of the first sensor node is suitable.

In addition, according to an embodiment of the present specification, the control server further checks whether the depth of the first sensor node is suitable, and whether the depth is suitable is determined by further considering the moisture change amount information and temperature information from the first sensor node. It is determined that the temperature information may include air temperature information and temperature information based on the depth of the ground.

In addition, according to an embodiment of the present specification, the control server checks the groundwater inflow information based on the amount of moisture in the soil measured from each of the plurality of sensor nodes, but when the control server checks the groundwater inflow information, the control server Measures moisture content change information for a plurality of sensor node points based on environmental tolerance information, and compares moisture content change information for a plurality of sensor node points by applying a correction value based on environmental tolerance information to check groundwater inflow information can

The present specification may provide a method of analyzing a soil based on a change in moisture in the soil.

The present specification may provide a method of analyzing soil based on a plurality of sensors that detect a change in moisture in the soil in an open-field smart farm.

The present specification may provide a method of recognizing a plurality of sensor positions in soil based on sample information about a change in moisture in the soil, and analyzing the soil based on the recognized plurality of sensors.

The present specification may provide a method of analyzing soil by detecting a change in moisture in the soil based on surrounding environment information.

The problem to be solved in the specification is not limited to the above, but may be extended to various matters that can be derived by the embodiments of the invention described below.

1 is a block diagram of an open-field smart farm control system according to an embodiment.
2A is a conceptual diagram for explaining communication between a smart farm and a server in the smart farm control system for a field according to an embodiment.
FIG. 2B is a conceptual diagram illustrating data transmission/reception between a gateway device of a smart farm and a user device in the smart farm control system for a field according to an embodiment.
3 is a perspective view of a sensor node device communicating with a smart farm control system for a field according to an embodiment.
FIG. 4 is a schematic block diagram of the sensor node device shown in FIG. 3 .
5A is a diagram illustrating a method of supplying raw water and nutrient solution through an irrigation device in an outdoor smart farm according to an embodiment.
5B is a diagram illustrating a method of supplying raw water and nutrient solution through an irrigation device in an outdoor smart farm according to an embodiment.
6 is a diagram illustrating a method of detecting a change in moisture according to an exemplary embodiment.
7 is a view showing effective moisture for each soil according to an embodiment.
8A is a diagram illustrating a change in moisture for each section according to an exemplary embodiment.
8B is a diagram illustrating a change in moisture for each section based on surrounding environment information according to an exemplary embodiment.
9A is a diagram illustrating a method of confirming information measured from a sensor node based on reference data according to an exemplary embodiment.
9B is a diagram illustrating a method of confirming whether a sensor node is properly installed based on a phase difference between reference data and a sensed value according to an exemplary embodiment.
10 is a diagram illustrating a method of confirming a sensing node value based on artificial intelligence (AI) according to an embodiment.
11 is a diagram illustrating a method of analyzing soil based on a change in moisture in the soil according to an exemplary embodiment.

In describing the embodiments of the present specification, if it is determined that a detailed description of a well-known configuration or function may obscure the gist of the embodiment of the present specification, a detailed description thereof will be omitted. And, in the drawings, parts not related to the description of the embodiments of the present specification are omitted, and similar reference numerals are attached to similar parts.

In the embodiments of the present specification, when a component is "connected", "coupled" or "connected" with another component, it is not only a direct connection relationship, but also an indirect relationship where another component exists in the middle. It can also include human connections. Also, when it is said that a component includes "includes" or "has" another component, it means that another component may be further included without excluding other components unless otherwise stated. .

In the embodiments of the present specification, terms such as first, second, etc. are used only for the purpose of distinguishing one component from other components, and unless otherwise specified, do not limit the order or importance between the components. does not Accordingly, within the scope of the embodiments of the present specification, a first component in an embodiment may be referred to as a second component in another embodiment, and similarly, a second component in an embodiment is referred to as a first component in another embodiment. may also be called

In the embodiment of the present specification, the components distinguished from each other are for clearly explaining each characteristic, and the components do not necessarily mean that the components are separated. That is, a plurality of components may be integrated to form one hardware or software unit, or one component may be distributed to form a plurality of hardware or software units. Accordingly, even if not specifically mentioned, such integrated or dispersed embodiments are also included in the scope of the embodiments of the present specification.

In the present specification, the network may be a concept including both wired and wireless networks. In this case, the network may mean a communication network in which data exchange between the device and the system and devices can be performed, and is not limited to a specific network.

Embodiments described herein may have aspects that are entirely hardware, partly hardware and partly software, or entirely software. As used herein, “unit,” “device,” or “system,” or the like, refers to a computer-related entity such as hardware, a combination of hardware and software, or software. For example, as used herein, a part, module, device, or system is a running process, processor, object, executable, thread of execution, program, and/or computer. (computer), but is not limited thereto. For example, both an application running on a computer and a computer may correspond to a part, module, device, or system of the present specification.

In addition, in the present specification, the device may be a mobile device such as a smart phone, a tablet PC, a wearable device, and a head mounted display (HMD), as well as a fixed device such as a PC or a home appliance having a display function. Also, as an example, the device may be an in-vehicle cluster or an Internet of Things (IoT) device. That is, in the present specification, a device may refer to devices capable of an application operation, and is not limited to a specific type. Hereinafter, for convenience of description, a device in which an application operates is referred to as a device.

In the present specification, the communication method of the network is not limited, and the connection between each component may not be connected by the same network method. The network may include not only a communication method using a communication network (eg, a mobile communication network, a wired Internet, a wireless Internet, a broadcasting network, a satellite network, etc.) but also short-range wireless communication between devices. For example, the network may include all communication methods through which an object and an object can network, and is not limited to wired communication, wireless communication, 3G, 4G, 5G, or other methods. For example, a wired and/or network may be a Local Area Network (LAN), a Metropolitan Area Network (MAN), a Global System for Mobile Network (GSM), an Enhanced Data GSM Environment (EDGE), a High Speed Downlink Packet Access (HSDPA), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Zigbee, Wi-Fi, Voice over VoIP Internet Protocol), LTE Advanced, IEEE802.16m, WirelessMAN-Advanced, HSPA+, 3GPP Long Term Evolution (LTE), Mobile WiMAX (IEEE 802.16e), UMB (formerly EV-DO Rev. C), Flash-OFDM, iBurst and MBWA (IEEE 802.20) systems, HIPERMAN, Beam-Division Multiple Access (BDMA), Wi-MAX (World Interoperability for Microwave Access), and one or more communication methods selected from the group consisting of ultrasonic communication can refer to a communication network by However, the present invention is not limited thereto.

Components described in various embodiments do not necessarily mean essential components, and some may be optional components. Accordingly, an embodiment composed of a subset of the components described in the embodiment is also included in the scope of the embodiment of the present specification. In addition, embodiments including other components in addition to the components described in various embodiments are also included in the scope of the embodiments of the present specification.

Hereinafter, embodiments of the present specification will be described in detail with reference to the drawings.

1 is a block diagram of a smart farm control system for a field according to an embodiment.

Referring to FIG. 1 , the smart farm control system 3 for the field according to the present embodiment is one or more located in each region 1 and 2 of the smart farm to enable information communication technology-based control. configured to communicate with the devices.

Each area 1 and 2 in the drawing corresponds to a unit area of a smart farm operated by the same or different users (eg, farm managers). Each region (1, 2) has one or more sensor node devices (11-15, 21-25) for acquiring sensor data for the farm environment, and each region (1, 2) Regional gateway devices 10 and 20 that enable control by region may be located. Also, in one embodiment, irrigation devices 19 and 29 for performing irrigation, such as supply of raw water and nutrient solution in a remote-controlled and automated manner, may be further located in each region 1 and 2 .

In addition, the smart farm control system 3 for the field may communicate with one or more user devices 4 to provide the collected smart farm information to the user. The user device 4 refers to a device used by a user who wants to remotely manage farming in one or more areas 1 and 2 of the smart farm by using the smart farm control system 3 for the field. In the drawings, the user device 4 is shown in the form of a notebook computer and a smart phone, but this is only for illustration, and the user device 4 is a mobile communication terminal, a personal computer, and a personal digital (PDA). assistant), a tablet, a set-top box for IPTV (Internet Protocol Television), etc. may be implemented in the form of any computing device.

In addition, in one embodiment, the smart farm control system 3 for the field is one or a plurality of external servers 5 to obtain environmental information (eg, weather, temperature, humidity data, etc.) affecting the growth of crops. can also communicate with For example, the external server 5 may be a web service server of the Korea Meteorological Administration, but is not limited thereto. In addition, the number of user devices 4 and external servers 5 shown in the drawings is merely exemplary, and does not limit the actual number of devices or servers operating in connection with the smart farm control system 3 for the field. The point will be readily understood by those skilled in the art.

In one embodiment, the smart farm control system 3 for the field includes a database (DB) server 31 , an analysis server 33 , and a web service server 32 .

The devices described herein may be wholly hardware, or may have aspects that are partly hardware and partly software. For example, the smart farm control system for the field 3 and each system, device, server and each module or unit included therein communicating therewith transmit data in a specific format and content in an electronic communication method. A device for receiving and software related thereto may be collectively referred to. As used herein, terms such as “unit”, “module”, “server”, “system”, “platform”, “device” or “terminal” are intended to refer to a combination of hardware and software driven by the hardware. do. For example, the hardware herein may be a data processing device including a CPU or other processor. In addition, software driven by hardware may refer to a running process, an object, an executable file, a thread of execution, a program, and the like.

In addition, in the present specification, each server 31-33 or unit constituting the smart farm control system 3 for the field is not necessarily intended to refer to a physically distinct separate component. That is, in FIG. 1 , each server 31-33 of the smart farm control system 3 for outdoor use is shown as a separate block to be distinguished from each other, but this is the operation performed by the smart farm control system 3 for outdoor use. functionally separated by According to an embodiment, some or all of the aforementioned servers may be integrated in the same single device, or one or more servers may be implemented as separate devices physically separated from other servers. For example, each server of the smart farm control system 3 for the field may be components communicatively connected to each other under a distributed computing environment.

The DB server 31 is configured to receive sensor data of the sensor node devices 11-15 and 21-25 located in the corresponding area from the gateway devices 10 and 20 for each area 1 and 2 of the smart farm. . In one embodiment, the DB server 31 may collect sensor data in a time series DB in a subscriber method using a messaging-based communication protocol, and the control data received from the user device 4 also uses the communication protocol. It can be transmitted to the gateway devices 10 and 20 using a published method.

For example, the DB server 31 may operate based on the MQTT (Message Queue Telemetry Transport) protocol, which will be described later with reference to FIGS. 2A and 2B .

The analysis server 33 serves to process the sensor data stored in the DB server 31 into analysis information for the user to check and provide it to the web service server 32 . At this time, the analysis information may be any type of information that allows the user to check the growth environment of the smart farm based on the sensor data, for example, the analysis information may be a simple processing of the sensor data into a form that the user can easily check , or data obtained secondaryly by numerical calculations based on sensor data, etc. may be included.

In an embodiment, the analysis server 33 includes a data collection unit 331 and a modeling generation unit 333 . Also in one embodiment, the analysis server 33 further includes an error detection unit 332 . Further, in one embodiment, the analysis server 33 further includes a strategy generating unit 334 .

The web service server 32, the user can check the analysis information based on the sensor data by accessing the smart farm control system 3 for the field using the user device 4, and, if necessary, the irrigation device of the smart farm A user interface for inputting control data for controlling (19, 29) and the like is provided. That is, the web service server 32 is a server that provides a web page accessible by a web browser running on the user device 4 , or an application (or app) running on the user device 4 . It may be an application service server that communicates with

The irrigation devices 19 and 29 are configured to remotely control the operation while communicating with the smart farm control system 3 for the field. In addition, the irrigation devices 19 and 29 may be interlocked with the user device 4 based on the smart farm control system 3 for the field, which will be described later. In addition, the watering devices 19 and 29 include a communication module such as a Bluetooth module capable of communicating with the gateway devices 10 and 20, and one or a plurality of valves (not shown) that can be electronically controlled by control data received through the communication module. city) may be included.

2A is a conceptual diagram for explaining communication between a smart farm and a server in the smart farm control system for a field according to an embodiment.

Referring to FIG. 2A , the gateway device 10 located in each region of the smart farm collects sensor data while communicating with the sensor node device 11 installed in the field. In addition, the gateway device 10 may control the supply of water to farmland by transmitting the control data input by the user to the irrigation device 19 . For the above operation, the gateway device 10 may be communicatively connected to the sensor node device 11 and the irrigation device 19 in a Bluetooth manner, but is not limited thereto, and the gateway device 10 is - It may be connected to the sensor node device 11 and the irrigation device 19 through other different local area networks, such as Wi-Fi.

The sensor data collected by the gateway device 10 is transmitted to the DB server 31 . At this time, the communication between the gateway device 10 and the DB server 31 is the aforementioned local area network, or GSM (Global System for Mobile Network), EDGE (Enhanced Data GSM Environment), HSDPA (High Speed Downlink Packet Access), W - It can be achieved through a telecommunication network such as Wideband Code Division Multiple Access (CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), and Long Term Evolution (LTE).

In one embodiment, the DB server 31 may communicate with the gateway device 10 using a publishing and subscription messaging (messaging) protocol, such as MQTT. In addition, the information stored in the DB server 31 may be processed into analysis information for the user to check and transmitted to the web service server 32 using a common Internet communication protocol such as HTTP (Hypertext Transfer Protocol). The user can check the information provided by the smart farm control system 3 for the field by accessing the web service server 32 using the user device. Also, as an example, the user device 4 may also communicate with the sensor node device 11 and the irrigation device 19 through the gateway device 10 based on the above-described protocol, which will be described later.

2B is a conceptual diagram for explaining data transmission/reception between a gateway device of a smart farm and a user device in the smart farm control system for a field according to an embodiment.

In FIG. 2B , an area 200 represents a local area network area of an area in which the gateway device 10 is located, and an area 300 represents a server area corresponding to the smart farm control system for the field.

Referring to FIG. 2B , sensor data transmitted from the gateway device 10 may have the form of an MQTT protocol-based message processed by the MQTT broker 301 of the DB server. At this time, a corresponding topic may be specified for each message, and the subscriber 304 of the DB server collects messages to which the topic is specified by subscribing to a specific topic, and the collected messages are collected from the DB server. is stored in the time series DB 302 of That is, the subscription unit 304 stores the message related to the subscribed topic in the time series DB 302 whenever a message is delivered from the MQTT broker 301 in the form of time-series organized data. In an embodiment, the time series DB 302 may be an influx DB, but is not limited thereto.

The web service server of the smart farm control system for the field may convert the information stored in the time series DB into analysis information that can be checked in the user device 4 through the interface unit 305 . For example, the interface unit 305 may use a visualization tool such as grafana, but is not limited thereto.

Meanwhile, the user may check the analysis information through the user device 4 and, if necessary, input a control input to the smart farm control system for the field. The user's control input is processed by the MQTT broker 301 in the form of an MQTT protocol-based message having a specific topic through the reverse order of the sensor data transmission process described above, and the gateway device 10 by the publisher can be sent to The gateway device 10 may receive control data in the form of a message based on the MQTT protocol and transmit it to the irrigation device of the smart farm.

3 is a perspective view of a sensor node device communicating with a smart farm control system for a field according to an embodiment;

Referring to FIG. 3 , the sensor node device 11 according to the present embodiment includes body parts 100 and 101 in which various sensors are accommodated, and a solar charging panel provided on the surface of the body parts 100 and 101 ( 102). Each part of the body parts 100 and 101 may have a material and structure capable of waterproofing and dustproofing so that it can be installed on the ground. In addition, the body parts 100 and 101 have a surface part 100 positioned on the soil when the sensor node device 11 is installed in the field, and an extension part ( 101) can be distinguished. A communication module for communication with the gateway device and a solar charging module for operation of the solar charging panel 102 may be accommodated in the surface portion 100, and the state inside the soil in the extension 101 One or more sensors for measurement and the like may be accommodated.

In one embodiment, the extension 101 may be inserted into the soil to extend over a plurality of layers 201-203 located at different depths within the soil. In this case, each layer 201-203 means layers in which the environmental conditions of the corresponding layer have meaning in the growth of crops. For example, the first layer 201 is from the soil surface to a depth of 15 cm, the second layer 202 is from the surface to a depth of 15 to 25 cm, and the third layer 203 is from the soil surface to a depth of 25 to 50 cm. It may refer to a section up to, but is not limited thereto.

In this case, one or more sensors located in the extension 101 may be configured to separately collect sensor data related to each layer 201-203 through which the extension 101 passes. For example, by independently measuring the temperature and/or humidity associated with each of the layers 201-203 in the soil, the environmental conditions affecting the growth of crops can be specifically and three-dimensionally grasped. At this time, the arrangement position of each sensor in the extension part 101 may be appropriately determined according to the root depth of the breeding crop to be cultivated in the open field, and by changing the sensor position in the extension part 101, it responds to various breeding crops. It is possible to use the sensor node device 11 .

FIG. 4 is a schematic block diagram of the sensor node device shown in FIG. 3 .

Referring to FIG. 4 , the sensor node device 11 may include a communication module 110 , a solar charging module 120 , and a sensor module 140 . In an embodiment, the sensor node device 11 may further include a Global Positioning System (GPS) module 130 . Also, in an embodiment, the sensor node device 11 may further include a storage module 150 .

The communication module 110 is a device that enables the sensor node device 11 to transmit sensor data to the gateway device 10 that controls a corresponding area, and may be configured as, for example, a Bluetooth module, but is not limited thereto.

The solar charging module 120 operates the solar charging panel 102 (FIG. 3) installed on the surface of the sensor node device 11, and supplies the electric power charged thereby to other parts of the sensor node device 11 as a power source. plays a role

The sensor module 140 includes one or more types of sensors for acquiring environmental information related to the growth of a farm, such as a temperature and humidity sensor 141 and an air pressure sensor 143, as sensor data. For example, each sensor may be disposed in the body of the sensor node device 11 so that the temperature and humidity sensor 141 is inserted into the soil and the air pressure sensor 143 is located on the soil surface, but is not limited thereto.

The GPS module 130 and the acceleration sensor 142 of the sensor module 140 acquire the installation location and state of the sensor node device 11 as sensor data, so that the smart farm control system for the field performs modeling on the crop In this case, it functions to specify and exclude erroneous data. Also, the sensor node device 11 may acquire crop image and surrounding image information based on a camera module (not shown) and other modules. For example, the sensor node device 11 may further utilize the acquired image information to confirm the location of crops in the smart farms 1 and 2, which will be described later.

The storage module 150 serves to store information on a specific condition to be achieved in relation to the growing environment of crops or a critical condition that must not be deviated therefrom. When the sensor data acquired by the sensor module 140 deviates from the above-described specific or critical condition, the sensor node device 11 transmits information related to the deviation of the condition separately from the normal sensor data transmission to the communication module 110 . through the smart farm control system for the field. This does not wait for a large amount of sensor data to be analyzed on the field smart farm control system side or the user to directly check the analysis information, and the sensor data obtained from the specific sensor node device 11 is set in a preset condition. This is to immediately notify the user of the departure.

However, this is an example, and in another embodiment, the sensor node device 11 itself acquires data, and processing of the acquired data is performed only on the server side, and in this case, the storage module 150 may be omitted.

It is possible to manage crops based on a plurality of sensor nodes within the smart farm. As an example, in the following, based on the above-mentioned bar, based on the plurality of sensor nodes 11 to 15 and the irrigation device in the smart farm 1, the location of crops is identified, and a method of supplying raw water and nutrient solution will be described. . As an example, the plurality of sensor nodes 11 to 15 and the irrigation device communicate with the user device 4 and the above-described protocol based on the gateway device 10 and the smart farm control system 3 for the field in the smart farm 1 . can be linked through In this case, the user device 4 may be a computing device. For example, the computing device may include at least one of a memory, a processor, a communication module, and a transceiver. For example, the memory is a non-transitory computer-readable recording medium, and is a non-volatile, high-capacity, non-volatile memory such as random access memory (RAM), read only memory (ROM), disk drive, solid state drive (SSD), and flash memory. It may include a permanent mass storage device. Here, a non-volatile mass storage device such as a ROM, an SSD, a flash memory, a disk drive, etc. may be included in the aforementioned device as a separate permanent storage device distinct from the memory. In addition, an operating system and at least one program code (eg, a code for a browser installed and driven on a user device, or an application installed on a user device to provide a specific service, etc.) may be stored in the memory. These software components may be loaded from a computer-readable recording medium separate from the memory. The separate computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD/CD-ROM drive, and a memory card.

In another embodiment, the software components may be loaded into the memory through a communication module instead of a computer-readable recording medium. For example, the at least one program is a computer program (eg, the application described above) installed by files provided through a network by a developer or a file distribution system (eg, the above-described server) that distributes the installation file of the application. ) can be loaded into memory based on

The processor may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to the processor by a memory or communication module. For example, the processor may be configured to execute instructions received according to program code stored in a recording device such as a memory.

The communication module may provide a function for communicating with a user device or a server via a network.

In addition, the transceiver may be a means for interfacing with an external input/output device (not shown). For example, the external input device may include devices such as a keyboard, mouse, microphone, and camera, and the external output device may include devices such as a display, a speaker, and a haptic feedback device. As another example, the transceiver may be a means for an interface with a device in which functions for input and output are integrated into one, such as a touch screen.

Based on the above description, it is possible to provide a method for controlling irrigation in conjunction with the user device 4 . As an example, FIGS. 5A and 5B are diagrams illustrating a method of supplying raw water and nutrient solution through an irrigation device in an outdoor smart farm according to an embodiment. Referring to FIGS. 5A and 5B , information related to the outdoor smart farm 1 may be acquired from a plurality of sensor nodes 11 to 15 . Here, the plurality of sensor nodes 11 to 15 may be configured as individual devices including respective sensors, and may be the same as in FIGS. 3 and 4 described above. Also, the sensor node may be integrally configured with the watering unit of the watering device 40 . That is, the irrigation device 40 may also be provided with a sensor node, through which it is possible to acquire crop-related information in the smart farm 1 . In addition, the plurality of sensor nodes 11 to 14 and the irrigation device 40 may be interlocked with the user device 4 , whereby the smart farm manager can improve the smart farm 1 management efficiency.

As a specific example, referring to FIGS. 5A and 5B , a plurality of sensor nodes 11 to 15 may be installed in a mesh form in the smart farm 1 . Here, as an example, the number of the plurality of sensor nodes 11 to 15 may be different depending on the size of the smart farm 1 . In addition, the plurality of sensor nodes 11 to 15 may be turned on/off, and on/off may be controlled by the user device 4 . However, it is not limited to a specific embodiment. In addition, the plurality of sensor nodes 11 to 15 may be installed in a fixed position in a mesh form as a specific position in the smart farm 1 . As another example, the plurality of sensor nodes 11 to 15 may be nodes having mobility, and may be moved within the smart farm 1 by the manager of the smart farm 1 . In this case, the plurality of sensor nodes 11 to 15 may acquire crop related information and smart farm 1 related information within the smart farm 1 . For example, the plurality of sensor nodes 11 to 15 may sense temperature, humidity, atmospheric pressure, PH change, and other soil information. Also, as an example, the plurality of sensor nodes 11 to 15 may include a GPS, and location information of each of the plurality of sensor nodes 11 to 15 may be known. Also, as an example, the plurality of sensor nodes 11 to 15 may include a camera and acquire image information, and are not limited to specific types of information. Here, the plurality of sensor nodes 11 to 15 may be configured in a mesh form, and a sensing value sensed by each of the plurality of sensor nodes 11 to 15 may be obtained. The smart farm control system 3 or the user device 4 for the field can recognize the location of the crops 51 to 54 and information related to the crops through the sensing values sensed by each of the plurality of sensor nodes 11 to 15. have. This will be described later. In addition, as an example, the plurality of sensor nodes 11 to 15 are provided with a GPS module, which can be used to recognize the location of the crops 51 to 54 . Here, the watering device 40 may supply raw water based on the positions of the crops 51 to 54 estimated from the plurality of sensor nodes 11 to 15 . At this time, the watering device 40 may be a device that is fixed to the central position of the smart farm 1 as shown in FIG. 5A , and discharges raw water through 360-degree rotation. As an example, the irrigation device 40 may control at least any one or more of the raw water supply direction, raw water discharge range, raw water discharge angle, and raw water amount, and the smart farm control system 3 for outdoor use or user device It can be controlled based on (4).

In addition, as an example, the position at which the raw water is discharged from the irrigation device 40 may be changed, and the position may be controlled so that the raw water is discharged around the crops 51 to 54 . Alternatively, as shown in FIG. 5B , the irrigation device 40 may control not only raw water but also at least one of a direction in which the nutrient solution is supplied, a nutrient solution discharge range, a nutrient solution discharge angle, and an amount of nutrient solution. That is, the irrigation device 40 can control the range, direction, angle, supply amount, and other information of the raw water and nutrient solution discharged based on the location of the crops 51 to 54 and crop-related information, through which the smart farm (1) It is possible to efficiently supply raw water and nutrient solution to the area where the crops 51 to 54 are located.

As a specific example, as described above, a plurality of sensor nodes 11 to 15 may be installed around the crop at regular intervals in each region 1 and 2 of the smart farm. However, the plurality of sensor nodes 11 to 15 are not limited to being installed in each smart farm region 1 and 2, but may be installed at regular intervals in the open field, and are not limited to a specific embodiment.

Here, the plurality of sensor nodes 11 to 15 may sense soil-related information. For example, the plurality of sensor nodes 11 to 15 may receive a sensing value based on soil-related information and perform soil analysis based on the received sensing value. At this time, the smart farm control system 3 for the field may control at least one of the amount of moisture and nutrient solution supplied to the soil based on the analysis result, as described above.

Hereinafter, a method of measuring the amount of moisture in the soil based on the plurality of sensor nodes 11 to 15 and analyzing it to determine the characteristics of the surrounding soil will be described. In this case, the supply of raw water and nutrient solution to the crops may be determined based on the determined characteristics of the soil. However, as an example, the plurality of sensor nodes 11 to 15 may further sense the moisture content as well as other soil-related information for soil analysis. For example, the soil analysis may be performed in consideration of other information such as nutrient information, pollutant information, organic matter information, and metal material information in the soil. As another example, the soil analysis may be performed in consideration of acidity (PH), salinity concentration, organic matter concentration, and other metal material concentrations, and is not limited to a specific embodiment.

At this time, as a specific example, referring to FIG. 6 , soil analysis may be performed based on the amount of moisture with the sensing values measured based on the plurality of sensor nodes 11 to 15 . As an example, water supply may be performed in a specific time period 610 through the irrigation device 40 based on the smart farm control system 3 for outdoor use. At this time, the amount of moisture in the soil may increase rapidly after watering, and the amount of moisture in the soil may decrease as the water is drained. At this time, moisture is provided in excess as abundantly as possible, and the plurality of sensor nodes 11 to 15 may measure how the excessively provided water changes in the soil and analyze the characteristics of the soil based on this. For example, the characteristics of the soil may include information on at least one of whether there is groundwater, the degree of groundwater, soil quality and soil type (ratio of sandy soil, loamy soil, etc.). In more detail, the smart farm control system 3 for an open field may perform a soil analysis based on the decreasing slopes 621 , 622 , 623 , and 624 of the moisture content in the soil in a specific time period 610 . In this case, the decreasing slope of the moisture content may be slopes 621 , 622 , 623 , and 624 derived based on a short time period, and may gradually decrease. The smart farm control system 3 for the field may measure the change in inclination from the highest point to the point where the slope is lowered to a predetermined value or less, and may recognize the point where the slope is lowered to a predetermined value or less as a point of the pavement capacity.

In this case, as an example, referring to FIG. 7 , the type of soil may be recognized based on the above-described gradient change. In more detail, FIG. 7 may be a soil moisture content graph for each type of soil. Referring to FIG. 7 , the maximum moisture content may be a state in which all pores in the soil are filled with water. That is, it may be water-saturated soil. In addition, the amount of pavement water may mean water/gravity water remaining in the pores in the soil by metric potentiation. That is, in FIG. 6 , the point at which the slope becomes less than or equal to a predetermined value as the water is drained after watering may mean a point at which the soil absorbs moisture based on the amount of field water and the remaining moisture is discharged. In addition, the counterfeit point may mean the moisture content of the point at which the plant withers due to lack of moisture. In addition, the effective moisture may mean water that plants can use as the soil moisture between the field water quantity and the counterfeit point, and may be divided into an effective moisture that is easy to use and an effective moisture that is used slowly.

In this case, as an example, referring to FIG. 7 , the effective moisture content and the effective moisture content between the counterfeit point may be different depending on the type of soil. As a specific example, in the case of sandy soil or sandy soil, the gap 711 between the field water quantity and the forgery point may be small, and may not be suitable for crops because the effective moisture content is small. On the other hand, in the case of silt loam, since the gap 712 between the field water quantity and the forging point may be large, the crop may not wither even if there is no water supply for a long time, and thus crop management may be easy. In addition, in loam soil and loam soil, the gap 713 between the pavement water quantity and the forging point may be reduced again. That is, for each type of soil, the amount of water in the field and the distance between the counterfeit points may be different. Accordingly, the smart farm control system 3 for the field may recognize the specific gravity of the soil based on the sensed value and the graph of FIG. 7 and other information. However, as an example, the soil specific gravity may be recognized based on information other than the graph of FIG. 7 . As another example, since the change in the moisture content of the soil may be changed differently based on the type of soil as well as other components included in the soil, the sensing value may recognize the soil specific gravity by further considering other information of the soil. As a specific example, the plurality of sensor nodes 11 to 15 may sense various components of the soil as well as the amount of moisture, and may generate a graph for each soil type based on a change in the amount of moisture based on the sensed information. In this case, as an example, the smart farm control system 3 for the field may perform deep learning through artificial intelligence based on the sensed values sensed from the plurality of sensor nodes 11 to 15 . At this time, a learning model for performing deep learning based on values sensed from the plurality of sensor nodes 11 to 15 and other external information may be built, and the present invention is not limited to a specific embodiment. At this time, the values sensed from the plurality of sensor nodes 11 to 15 may be applied to the sensed values by generating graphs and other information for soil type analysis based on artificial intelligence deep learning, and through this, the soil type and Soil information can be derived. That is, the smart farm control system 3 for the field may perform soil analysis through sensing values sensed from a plurality of sensor nodes 11 to 15, and may perform crop management based on the soil analysis information. .

In this case, as an example, referring to FIG. 8A , based on the soil analysis, the plurality of sensor nodes 11 to 15 may continuously sense the amount of moisture change due to the crop. In this case, the plurality of sensor nodes 11 to 15 may sense the amount of moisture for each predetermined section, and through this, additional soil analysis may be performed. As a specific example, sections A 811-1 and 811-2 in FIG. 8A may be sections in which water is supplied by the irrigation device 40 . Here, the moisture content of the soil may be increased by watering, and the watering may be performed more than the saturated water amount for clear soil analysis. In this case, the B section 812 may be a section in which the water content is higher than the saturated water amount, and thus rapid drainage is performed. In addition, section C (813-1, 813-2, 813-3, 813-4) is a section in which soil moisture decreases due to transpiration of plants during the day, and section D (814-1, 814-2, 814- 3) may be a section where soil moisture naturally decreases due to cessation of transpiration of plants during the night. Here, the smart farm control system 3 for the field detects the change in moisture based on the sensed values through the plurality of sensor nodes 11 to 15 and controls the amount of moisture supplied through the irrigation device 40 . can In addition, as an example, the smart farm control system 3 for the field may control the amount of moisture supplied through the irrigation device 40 in consideration of the sensing information and external information measured from the plurality of sensor nodes 11 to 15 . can As a specific example, referring to FIG. 8B , the temperature of the graph (b) may increase than the temperature of the graph (a). At this time, as an example, the graph (a) may be a moisture content change graph generated by the smart farm control system 3 for the field based on the sensed values sensed through the plurality of sensor nodes 11 to 15 . Also, as an example, the graph (a) may be a moisture content change graph generated based on artificial intelligence. At this time, when the temperature of the graph (b) is higher than that of the graph (a), the transpiration effect of the crop may increase, and due to the increase in the transpiration amount, water shortage may occur when the same amount of water is supplied. Therefore, the smart farm control system 3 for the field can increase the amount of water supplied by utilizing the temperature information. In addition, as an example, the smart farm control system 3 for outdoor use may continuously perform sensing through a plurality of sensor nodes 11 to 15, and based on the obtained sensing value, the moisture change amount may be displayed in a preset graph and You can detect whether they are different. At this time, the smart farm control system 3 for the field is irrigated if the phase difference between the moisture change graph and the preset graph obtained based on the sensing values sensed through the plurality of sensor nodes 11 to 15 is greater than or equal to the threshold value. The amount of water supplied can be adjusted by controlling the device 40 , which will be described later.

As another example, it is necessary to place a plurality of sensor nodes 11 to 15 in consideration of the location of crops in the smart farm areas 1 and 2 or the open field. For example, in order to determine an accurate water absorption amount of a crop root, it is necessary for the sensor node to be located at an appropriate depth and distance to the side of the root. Therefore, it is necessary to adjust the positions of the plurality of sensor nodes 11 to 15 in consideration of the positions of crops in the smart farm areas 1 and 2 or the open field. In this case, as an example, the smart farm control system 3 for outdoor use may determine whether the location of the sensor node is appropriate based on a change in moisture sensed through the sensor node. In this case, when the location of the sensor node is not appropriate, the smart farm control system 3 for the field may provide an alarm for correcting the location of the sensor node to the user terminal 4 . In addition, as an example, the smart farm control system 3 for the field may calibrate the sensor node by itself so that the sensor node is located at an appropriate position and depth with the crop.

As a more specific example, the smart farm control system 3 for the field may control the position of the sensor node during initial setting. For example, the smart farm control system 3 for the field may pre-store the moisture change amount graph information for the crop as described above based on artificial intelligence and other external data. Here, the moisture change graph for the crop may be different based on the type of crop or the nutrients, organic matter, metal material, and other soil-related information contained in the soil, as described above. In this case, the smart farm control system 3 for the field may install the sensor node in consideration of the position and depth of the crop. As an example, the smart farm control system 3 for the field may recognize that a plurality of sensor nodes 11 to 15 are installed in the smart farm 1 and 2 or the field. Thereafter, the smart farm control system 3 for the field may obtain the sensed values sensed from the plurality of sensor nodes 11 to 15 and obtain a moisture change amount graph based thereon. In this case, the plurality of sensor nodes 11 to 15 may further sense soil-related information, and may transmit it to the smart farm control system 3 for outdoor use. In addition, the smart farm control system 3 for the field may further acquire temperature information, crop type information, and other information, and is based on the soil-related information and external information acquired from the plurality of sensor nodes 11 to 15 . Based on the reference moisture change amount graph information can be determined. Thereafter, the smart farm control system 3 for the field generates a moisture change graph based on the sensing value information obtained from each of the plurality of sensor nodes 11 to 15, and compares it with the reference moisture change graph information. . At this time, the smart farm control system for the field 3 compares the moisture change graph based on the mood moisture change graph and the sensing value information obtained from each of the plurality of sensor nodes 11 to 15, and the sensor node is located around the crop. It is possible to check whether or not to do so and an appropriate location, and to provide information on this to the user terminal 4 as a notification. Also, as an example, the smart farm control system 3 for the field may correct the positions of the plurality of sensor nodes 11 to 15 by itself. As an example, each of the plurality of sensor nodes 11 to 15 may include a moving means controlled by the smart farm control system 3 for the field, and the smart farm control system 3 for the field controls the plurality of sensors. The positions of the sensor nodes 11 to 15 may be corrected.

Here, as an example, the smart farm control system 3 for a field may set a preset time period for comparison of the above-described moisture change graph information. For example, since the shorter the preset time period, the lower the accuracy, the preset time period may be equal to or greater than the threshold value. As another example, it is necessary to perform water supply in order to compare the moisture change amount graph, and the smart farm control system 3 for outdoor use may set a preset time interval according to the water supply. As a specific example, the smart farm control system 3 for the field measures the number of times of water supply and a preset time interval according to the water supply at the time of initial setting, and through this, a sensing value is obtained from each of the plurality of sensor nodes 11 to 15, You can create a moisture change graph. Thereafter, by generating a plurality of moisture change graphs according to the number of watering times and comparing them with a reference moisture change graph, the smart farm control system 3 for outdoor use allows the plurality of sensor nodes 11 to 15 to be located at an appropriate location with the crop and You can check whether it is located in the depth or not. At this time, the smart farm control system 3 for the field may check whether the location is appropriate for each sensor node and adjust the location for each sensor node. As another example, the smart farm control system 3 may adjust the positions of the plurality of sensor nodes 11 to 15 based on the moisture change information obtained through the plurality of sensor nodes 11 to 15 in real time. have. For example, the location of the crops in the smart farms 1 and 2 and the field may be preset, but the direction in which the roots of the crops grow may be different as the crops grow. Accordingly, the smart farm control system 3 for the field acquires moisture change information through a plurality of sensor nodes 11 to 15 based on real-time or a predetermined period, and compares it with the reference moisture change information to a plurality of sensor nodes It can be determined whether the ones 11 to 15 are present at an appropriate location. Through this, the smart farm control system 3 for the field can efficiently operate the plurality of sensor nodes 11 to 15 .

As a specific example, comparing FIG. 9A , the first time period 910 of (a) may be a reference graph for the amount of moisture change. In this case, as an example, the reference graph for the moisture change amount may be individually set differently in consideration of the crop type, temperature, and other soil-related information, as described above. Here, the graph of the moisture change amount in the second time period 920 of (b) may be a moisture change amount graph corresponding to the reference graph. Accordingly, it can be expected that the moisture change graph of the second time period 920 is generated in a similar form to the graph of the first time period 910 that is the reference moisture change graph. In this case, as an example, the moisture change amount graph may be generated in the second time period 920 in a different form from the first time period 910 , and through this, the smart farm control system 3 for outdoor use determines that the sensor node is located at an appropriate location. It can be recognized that it is not located in At this time, as an example, the smart farm control system 3 for the field can check whether a difference occurs between the reference graph and the measurement graph by more than a preset value, and when a difference occurs by more than a preset value, the sensor node is located at an appropriate location. It can be judged that it is not located.

As a specific example, the similarity between the first time period 910 and the second time period 920 in FIG. 9A may be less than or equal to a predetermined value, and it may be determined that the sensor node is not located at an appropriate location. For example, it may be ideal that the sensor node is typically located 30 cm from the ground. However, this is only one example, and may be different based on the type of crop or soil-related information. In addition, as an example, it may not be appropriate to install a simple 30 cm based on the location of crop roots, ground slope, and other factors.

In consideration of the above points, the smart farm control system 3 for the field determines whether the similarity between the first time period 910 and the second time period 920 is less than or equal to a predetermined value, so that the sensor node is located at an appropriate location It determines whether or not to do so, and if it is not located in an appropriate location, the sensor node can be moved. Here, as an example, the smart farm control system 3 for a field may acquire a moisture change graph for a third time period (not shown) based on the water supply after the sensor node is moved. That is, after moving the sensor node, the smart farm control system 3 for outdoor use may newly acquire a moisture change amount graph. At this time, as an example, the smart farm control system for a field 3 compares the moisture change graph for the third time period with the moisture change graph of the first time period 910, which is a reference graph, to determine whether the sensor node is at an appropriate location. can be checked Here, if the sensor node is not in an appropriate position even based on the moisture change graph based on the third time period, the smart farm control system 3 for the field is the reference graph of the first time period 910 and the second time period ( 920) may be compared with the moisture change graph of the third time period (not shown). That is, the smart farm control system 3 for the field can check whether the sensor node is located at an appropriate position based on the reference moisture change graph and the moisture change graph measured before moving. In addition, the smart farm control system 3 for the field may determine the direction and depth that the sensor node needs to move in order to be located in an appropriate position based on the above-described information. That is, an appropriate position may be confirmed based on the reference moisture change graph and the moisture change graph based on movement. As a specific example, the smart farm control system 3 for outdoor use may provide the above-described information as an input based on artificial intelligence, and obtain movement direction and depth information as an output as an appropriate location of the sensor node, through which the sensor The location of the node can be determined.

In addition, as an example, the similarity between the reference moisture change graph and the measured moisture change graph may be less than or equal to a predetermined value, and when it is less than or equal to a predetermined value, it may be determined that the sensor node is located at an appropriate location. Here, the predetermined value may be a value taking into account that the moisture change graph is measured differently depending on the environment, which may be determined based on a phase difference from the sensing value of the sensor node. For example, the measured moisture change graph may be measured in a time interval corresponding to the reference moisture change graph, and a phase difference may be checked at each point, and a predetermined value may be calculated through this. For example, the phase difference values for each point may be summed, and a predetermined value may be calculated based on the summed value, but may not be limited to a specific form.

As another example, referring to FIG. 9B , the smart farm control system 3 for a field may check phase difference information on the moisture change amount graph in order to check the appropriate depth of the sensor node. As an example, the smart farm control system 3 for outdoor use includes an algorithm for determining an appropriate depth of a sensor node based on a phase difference between the ground and the atmosphere and temperature, and may recognize an appropriate depth based on this. For example, the atmospheric temperature may record the highest temperature between 2 and 4 o'clock, but a phase difference may occur in the temperature of the sensor node underground depending on the installation depth. In more detail, if the graph 930 by the first sensor and the graph 940 by the second sensor are compared in FIG. 9B , the second sensor is installed more deeply, and a phase difference in the temperature graph may occur. That is, the depth at which the sensor node is installed may be different depending on the phase difference of the temperature according to the atmospheric temperature and the depth of the ground, so the smart farm control system 3 for the field determines the appropriate depth of the sensor node based on the phase difference information described above. The algorithm can determine the appropriate depth of the sensor node.

As another example, the smart farm control system 3 for the field may perform correction on the sensing value measured from the sensor node, which may be performed based on temperature information and other surrounding information or soil-related information. . As an example, the smart farm control system 3 for the field may perform correction on the sensed value in order to check the actual water absorption amount of the root by reflecting environmental factors. As a specific example, the smart farm control system 3 for a field may determine environmental information based on a disparity between a data value of a sensor node installed at a reference location and a data value of a target sensor node. In this case, the environmental acceptance information may include at least one of depth problem information of the sensor node, distance problem information of crops, inclination information of the sensor node, and characteristic information of the soil, and is not limited to the above-described embodiment. At this time, the smart farm control system 3 for outdoor use may determine the environmental tolerance information, bring the determined environmental tolerance-specific correction value from the database or generate it through deep learning, and correct the sensed value measured through this. .

As an example, the smart farm control system 3 for a field may compare the sensing value of the sensor node with a different depth applied to the reference depth based on the correction value with the values of the sensor nodes installed as the reference depth, and reflect this to compare other characteristics. have.

In addition, as an example, the smart farm control system 3 for the field may determine the soil characteristics by estimating the groundwater inflow amount as well as the water supply amount by the irrigation device 40 . For example, the amount of groundwater flowing in may be different based on the location of the soil, and water supply through the irrigation device 40 may be required to reflect this. As a specific example, after performing the same water supply at the first point and the second point, the amount of change in moisture may be compared. In this case, as an example, the moisture change amount at the first point and the second point may be measured based on the same criterion by deriving a correction value based on the above-described environmental tolerance information and reflecting the derived correction value. At this time, for example, when the moisture content of the soil is appropriately reduced in one place but the moisture content of the soil in the other place is extremely small, it can be estimated that the groundwater has risen by comparing the temperatures of the two locations. That is, the smart farm control system 3 for the field may check whether moisture is introduced from the rain or irrigation device 40 at a specific point, or whether it is introduced through groundwater.

In addition, as an example, the smart farm control system 3 for the field may recognize whether or not groundwater is introduced based on a water supply type and a change in temperature in the ground. For example, when moisture is supplied through irrigation or rain, the rate of increase in moisture is rapid and the temperature change in the ground may also be rapid. On the other hand, when moisture flows in through a puddle or groundwater, it may come up from the bottom like a bottom irrigation of a pot, and moisture movement may be slow and temperature change may be small. For example, if the moisture change amount of the sensor node is small after a certain period of time after irrigation at a plurality of points, it may be recognized that the transpiration amount of the crop is insufficient. However, if the moisture change amount at a specific point is small and the soil temperature change is smaller than that of the surrounding sensor node, the temperature characteristics and moisture characteristics may be different based on the groundwater inflow. For example, as described above, if the correction value is reflected according to a plurality of points as environmental acceptance information, it is possible to recognize whether a change in moisture and a change in temperature occur according to the inflow of groundwater, and the smart farm control system 3 for outdoor use is By recognizing this, it is possible to check whether or not the groundwater has been introduced. Thereafter, the smart farm control system 3 for the field can adjust the amount of moisture supplied to the irrigation device 40 based on the groundwater inflow point information, and through this, efficient moisture supply can be performed.

Also, as an example, the above-described operations may be performed through the artificial intelligence learning model 1010 of the smart farm control system 3 for the field. For example, the artificial intelligence learning model 1010 may pre-store information on the amount of change in moisture or the amount of change in temperature based on crop information, temperature information, and other external information. In addition, information on other senseable information may be pre-stored, and the embodiment is not limited thereto. In this case, the smart farm control system 3 for the field may obtain a sensing value from each of the plurality of sensor nodes 11 to 15 and provide it as an input to the artificial intelligence learning model 1010 . Thereafter, the smart farm control system 3 for the field may perform soil analysis and location/depth information analysis of sensor nodes. In addition, as described above, it is possible to check whether or not groundwater is introduced, which is the same as described above. Thereafter, the smart farm control system 3 for the field can control the moisture and nutrient solution supplied through the result information analyzed through the artificial intelligence learning model 1010 ( 1030 ), and the information on this is the artificial intelligence learning model (It may be fed back to 1010 to increase accuracy, and is not limited to the above-described embodiment.

11 is a diagram illustrating a method for a control server to analyze soil based on a change in moisture in the soil according to an embodiment.

Referring to FIG. 11 , the control server may obtain a sensed value from each of a plurality of sensor nodes based on location information and depth information in which the plurality of sensor nodes are installed. (S1110) In this case, the sensed value may be the amount of moisture in the soil. have. Thereafter, the control server may perform soil analysis based on the amount of moisture in the soil measured from each of the plurality of sensor nodes. (S1120) Through this, the control server may determine the soil characteristics, and based on the determined soil characteristics, It is possible to control the amount of water and medicine supplied. (S1130) In this case, as an example, the control server is installed in a mesh form in the open-air smart farm, and a plurality of sensor nodes and a plurality of sensor nodes for sensing crop-related information in the open-air smart farm. It may include a control unit for performing soil analysis based on the sensed value obtained from , and an irrigation device for supplying raw water and nutrient solution based on the analyzed characteristics of the soil, as described above.

Here, when measuring the amount of moisture in the soil based on the first sensor node among the plurality of sensor nodes, the control server performs water supply of more than the saturated water amount based on the location information and depth information of the first sensor node, and based on the water supply Accordingly, it is possible to obtain moisture content change graph information by measuring the moisture content that varies in a preset time interval. Thereafter, the control server may perform soil analysis by comparing the moisture content change graph information with the reference moisture content change graph information. Here, the reference moisture content change graph information may be pre-generated information based on the soil characteristics, as described above.

In addition, as an example, when the moisture content fluctuation graph information and the reference moisture content fluctuation graph information are compared, the soil nutrient information, organic matter information, metal material information, pollutant information, temperature information, location information of the first sensor node, and the first sensor At least any one or more of the depth information of the node may be reflected. That is, the control server may further reflect the surrounding environment information in relation to the reference moisture content change graph, and may perform comparison through this. As another example, the control server may have an artificial intelligence learning model, and may compare the moisture content change graph information and the reference moisture content change graph information based on the artificial intelligence learning model, as described above.

In addition, the control server may determine whether the location of each of the plurality of sensor nodes is a suitable location based on the crop location information, based on the amount of moisture in the soil sensed by each of the plurality of sensor nodes. Here, when the location of each of the plurality of sensor nodes is not a suitable location, the control server may move the location of each of the plurality of sensor nodes by providing a notification to the user terminal or controlling each of the plurality of sensor nodes, which is described above. like a bar At this time, for example, when it is checked whether the location of the first sensor node among the plurality of sensor nodes is appropriate, moisture change information and soil-related information are obtained from the first sensor node, and the reference moisture change amount based on the soil-related information It is possible to obtain information and compare the moisture change information obtained from the first sensor node with the reference moisture change information to determine whether the location of the first sensor node is suitable. In this case, the control server may also check whether the depth of the first sensor node is appropriate, and whether the depth is appropriate may be determined by further considering the moisture change amount information and the temperature information from the first sensor node. For example, the temperature information may be air temperature information and temperature information based on the depth of the ground, through which depth information may be acquired.

Also, as an example, the control server may check information on whether or not groundwater is introduced based on the amount of moisture in the soil measured from each of the plurality of sensor nodes. As an example, when the control server checks the groundwater inflow information, the control server measures moisture content change information for a plurality of sensor node points based on the environmental tolerance information, and applies a correction value based on the environmental tolerance information to a plurality of Information on whether or not groundwater is inflow can be checked by comparing the change information of the moisture content at the sensor node point, as described above.

The embodiments described above may be at least partially implemented as a computer program and recorded in a computer-readable recording medium. A computer-readable recording medium in which a program for implementing the embodiments is recorded includes all types of recording devices in which computer-readable data is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, and optical data storage device. In addition, the computer-readable recording medium may be distributed in network-connected computer systems, and the computer-readable code may be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present embodiment may be easily understood by those skilled in the art to which the present embodiment belongs.

Although the present specification described above has been described with reference to the embodiments shown in the drawings, this is merely exemplary and those skilled in the art will understand that various modifications and variations of the embodiments are possible therefrom. However, such modifications should be considered to be within the technical protection scope of the present specification. Accordingly, the true technical protection scope of the present specification should be defined to include other implementations, other embodiments, and equivalents to the claims by the spirit of the appended claims.

Claims (10)

In the operating method of the control server for performing soil analysis based on the change in moisture in the land,
measuring an amount of moisture in the soil from each of the plurality of sensor nodes based on location information and depth information in which a plurality of sensor nodes are installed;
determining a soil characteristic based on the amount of moisture in the soil measured from each of the plurality of sensor nodes;
determining whether a position and a depth of a first sensor node among the plurality of sensor nodes are suitable based on the determined soil characteristic; and
Including; supplying raw water and nutrient solution based on the determined soil characteristics;
Whether the position and the depth of the first sensor node are appropriate is determined based on the crop position information and the soil characteristics,
When it is determined whether the location of the first sensor node is suitable, reference moisture change amount information is determined based on the soil characteristic of the first sensor node, and moisture based on the water supply provided to the first sensor node The change amount information is measured, and it is determined whether the position of the first sensor node is suitable by comparing the measured moisture change amount information with the crop position information and the reference moisture change amount information,
When it is determined whether the depth of the first sensor node is appropriate, the first sensor by comparing the moisture change amount information measured at the first sensor node with the crop position information, the reference moisture change amount information, and temperature information It is determined whether the depth of the node is suitable, wherein the temperature information includes temperature information based on the depth of the ground set by comparing with atmospheric temperature information,
When it is determined that any one of the position and the depth of the first sensor node is not suitable, the control server provides a notification to the user terminal, and based on the input information of the user terminal, the Changing at least one of the position and the depth, the operating method of the control server.
The method of claim 1,
When the soil characteristic is determined based on the plurality of sensor nodes, the moisture amount is measured by measuring the amount of moisture that varies in each of the plurality of sensor nodes in a preset time interval based on the water supply that is equal to or greater than the saturation water amount, which is the moisture amount greater than or equal to the maximum moisture content of the soil A method of operating a control server to obtain fluctuation graph information.
3. The method of claim 2,
The control server determines the soil characteristics by comparing the moisture content change graph information with reference moisture content change graph information,
The reference moisture content change graph information is pre-generated information based on the soil characteristics, the operating method of the control server.
4. The method of claim 3,
When the moisture content fluctuation graph information and the reference moisture content fluctuation graph information are compared, soil nutrient information, organic matter information, metal material information, pollutant information, temperature information, location information of the first sensor node, and the first sensor node At least any one or more of the depth information of the reflection, based on the reflected information, the moisture content change graph information and the reference moisture content change graph information is compared, the operating method of the control server.
5. The method of claim 4,
The control server includes an artificial intelligence learning model, and comparing the moisture content change graph information with the reference moisture content change graph information based on the artificial intelligence learning model, the operating method of the control server.
delete delete delete The method of claim 1,
The control server checks the groundwater inflow information based on the amount of moisture in the soil measured from each of the plurality of sensor nodes,
When the control server checks the groundwater inflow information, the control server points to a plurality of sensor nodes based on environmental information that is correction information for sensing values measured from each of the plurality of sensor nodes according to the soil characteristics. A method of operating a control server, measuring moisture content change information for a , and comparing the moisture content change information for the plurality of sensor node points by applying a correction value based on the environmental acceptance information to confirm the groundwater inflow information.
In the control server for performing soil analysis based on the change in moisture in the land,
a plurality of sensor nodes installed in the form of a mesh in the open-air smart farm and sensing crop-related information in the open-air smart farm;
a controller for performing soil analysis based on the sensed values obtained from the plurality of sensor nodes; and
As the control server comprising a; irrigation device for supplying raw water and nutrient solution based on the analyzed characteristics of the soil,
Measuring the amount of moisture in the soil from each of the plurality of sensor nodes based on location information and depth information in which the plurality of sensor nodes are installed,
determining a soil characteristic based on the amount of moisture in the soil measured from each of the plurality of sensor nodes,
determining whether a position and a depth of a first sensor node among the plurality of sensor nodes are suitable based on the determined soil characteristic, and
Supply raw water and nutrient solution based on the determined soil characteristics,
Whether the position and the depth of the first sensor node are appropriate is determined based on the crop position information and the soil characteristics,
When it is determined whether the location of the first sensor node is suitable, reference moisture change amount information is determined based on the soil characteristic of the first sensor node, and moisture based on the water supply provided to the first sensor node The change amount information is measured, and it is determined whether the position of the first sensor node is suitable by comparing the measured moisture change amount information with the crop position information and the reference moisture change amount information,
When it is determined whether the depth of the first sensor node is appropriate, the first sensor by comparing the moisture change amount information measured at the first sensor node with the crop position information, the reference moisture change amount information, and temperature information It is determined whether the depth of the node is suitable, wherein the temperature information includes temperature information based on the depth of the ground set by comparing with atmospheric temperature information,
When it is determined that any one of the position and the depth of the first sensor node is not suitable, the control server provides a notification to the user terminal, and based on the input information of the user terminal, the A control server that changes at least one of a position and the depth.

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