Ai remote-assisted smart farm device, driving method therefor, and ai remote-assisted smart farm system

Abstract

The present invention relates to an artificial intelligence (AI) remote-assisted smart farm device, a driving method therefor, and an AI remote-assisted smart farm system, and the AI remote-assisted smart farm device according to an embodiment of the present invention may include: a storage unit for storing an AI model that has pre-learned all data related to agriculture for operating a smart farm based on AI; and a control unit that, when an RAS command for controlling the operation of the equipment constituting a smart farm is provided through a messenger-based chatting service from a user terminal device of a user managing the smart farm, executes the AI model and provides the AI model to a local device operating the equipment according to a (pre-)received RAS command to control the equipment.

Description

AI remote assistance smart farm device and its operation method, and AI remote assistance smart farm system

[0001] The present invention relates to an AI remote assistance smart farm device and a method for operating the device, and an AI remote assistance smart farm system, and more particularly, to an AI remote assistance smart farm device and a method for operating the device, and an AI remote assistance smart farm system, which operates in the agricultural field and assists farmers in farming based on an AI engine, and not only provides users with specific information that can be customized, but also provides an AI-based interface that can control equipment in the field.

[0002] In general, a smart farm is an intelligent agricultural system that integrates information and communication technology (ICT) in the production, processing, and distribution stages of agriculture, forestry, livestock, and aquatic products. It utilizes technologies such as the Internet of Things, big data, and artificial intelligence (AI) to appropriately maintain and manage the growing environment of crops, livestock, and aquatic products, and can be automatically managed remotely using PCs and smartphones, thereby increasing not only production efficiency but also convenience. In addition, smart farm technology utilizing ICT technology enables precise management and prediction of each growth stage based on accurate data on information (e.g., temperature, relative humidity, light, carbon dioxide concentration, soil, etc.) and growth information, thereby improving yields, quality, etc., and increasing profitability. In addition, production costs can be reduced by efficiently managing labor and energy. For example, while previously, when irrigating crops, one had to manually open the valve and operate the motor, in a smart farm, not only can the electronic valve automatically irrigate according to the set value, but smart farms can also manage detailed production information history of agricultural, forestry, livestock, and fishery products, which can increase consumer trust.

[0003] However, in a smart farm environment, control commands are executed by comparing the optimal growth environment data for each crop that has been input in advance with measurement data from various sensors installed in the greenhouse. However, there is a problem that the greenhouse environment often does not reach the set target value even after the control command is executed.

[0004] This is because not only is the climate of the region where the greenhouse is located different and the configuration of control elements (e.g. motors, pumps, etc.) are all different, but the optimal growing environment for the crops being grown can also vary depending on various conditions such as the type of seeds used by the farm, the nursery conditions, and the unique environment of each greenhouse. However, the current smart farm environment has the problem of not sufficiently considering these uncertainties.

[0005] Accordingly, there is a need to develop a system that can create added value by providing new solutions by integrating information and communication technology (ICT), big data, and artificial intelligence (AI) with traditional agricultural technologies.

[0006] [Prior Art Literature]

[0007] [Patent Document]

[0008] Korean Patent Publication No. 10-2300229 (September 3, 2021)

[0009] Korean Patent Publication No. 10-2369167 (February 24, 2022)

[0010] Korean Patent Publication No. 10-2018-0076766 (July 6, 2018)

[0011] Korean Patent Publication No. 10-2023-0056082 (April 27, 2023)

[0012] Korean Patent Publication No. 10-2023-0069279 (May 19, 2023)

[0013] Korean Patent Publication No. 10-2024-0005477 (January 12, 2024)

[0014]

[0015] The purpose of the present invention is to provide an AI remote assistance smart farm device and an operating method thereof, and an AI remote assistance smart farm system, which operates in an agricultural field and assists farmers in farming based on an AI engine, and provides not only customized specific information to users but also an AI-based interface for controlling equipment in the field.

[0016] The tasks of the present invention are not limited to the tasks mentioned above, and other tasks not mentioned will be clearly understood by those skilled in the art from the description below.

[0017] An AI remote assistance smart farm device according to an embodiment of the present invention includes a storage unit that stores an AI model that has learned various agricultural data for operating a smart farm based on artificial intelligence (AI), and a control unit that, when a Remote Assistant Smart-Farming (RAS) command for controlling the operation of equipment constituting the smart farm is provided as a messenger-based chat service from a user terminal device of a user managing the smart farm, executes the AI ​​model and provides it to a local device that operates the equipment according to the received RAS command, thereby controlling the equipment.

[0018] The above control unit can train the AI ​​model with RAS sensor data of the sensors constituting the smart farm and question data related to equipment as the agricultural data.

[0019] The above control unit can exchange or share data related to the operation of a smart farm between a local device at a first location and a local device at a second location.

[0020] The above control unit checks the mode of the chatbot when the receiving number of the user terminal device passes the authentication process, and if the checked mode is simple or chatbot, the control unit can change the mode and operate according to the user's mode change command.

[0021] The above control unit determines the string of the RAS command and controls the operation of the equipment in a single mode according to the determination result, and can conduct a conversation with a chatbot in a chatbot mode.

[0022] In addition, a method for operating an AI remote assistance smart farm device according to an embodiment of the present invention includes a step of storing an AI model that has learned various agricultural data for operating a smart farm based on artificial intelligence (AI) by a storage unit, and a step of providing a RAS command for controlling the operation of equipment constituting the smart farm to a local device that executes the AI ​​model and operates the equipment according to the received RAS command when a RAS command for controlling the operation of the equipment constituting the smart farm is provided as a messenger-based chat service from a user terminal device of a user managing the smart farm, thereby controlling the equipment.

[0023] The above driving method may further include a step in which the control unit trains the AI ​​model with RAS sensor data of sensors constituting the smart farm and question data related to equipment as the agricultural data.

[0024] The above driving method may further include a step in which the control unit exchanges or shares data related to the operation of the smart farm between a local device at a first location and a local device at a second location.

[0025] The above driving method may further include a step of checking the mode of the chatbot when the receiving number of the user terminal device passes the authentication process, and a step of changing the mode and operating according to a mode change command of the user when the checked mode is simple or chatbot.

[0026] The step of changing the above mode and operating comprises judging the string of the RAS command and controlling the operation of the equipment in a single mode based on the judgment result, and performing a conversation with a chatbot in a chatbot mode.

[0027] Furthermore, the AI ​​remote assistance smart farm system according to an embodiment of the present invention includes a local device that controls the operation of equipment constituting the smart farm based on the analysis results of sensing data acquired by sensors installed in the smart farm, and an AI remote assistance smart farm device that stores an AI model that has learned various agricultural-related data for operating the smart farm based on artificial intelligence (AI), and when a RAS command for controlling the operation of the equipment is provided as a messenger-based chat service from a user terminal device of a user managing the smart farm, executes the AI ​​model and controls the operation of the equipment according to the received RAS command.

[0028] The above AI remote assistance smart farm device can operate in at least one of a global manner in which it is connected to the local device remotely through an external communication network and operates remotely, and a manner in which it is connected to the local device locally through an internal communication network in the smart farm and operates.

[0029] The above AI remote assistance smart farm device, when operating on a local basis, communicates with the local device and the sensor, and can provide a messenger-based AI chat service to the user terminal device through the communication.

[0030] When the local device and the AI ​​remote assistance smart farm device are configured such that the AI ​​remote assistance smart farm device is omitted when operating on the local basis, the local device can provide the communication and AI chat service.

[0031] When the local device and the AI ​​remote assistance smart farm device operate in a hybrid manner combining the global method and the local-based method, the main and sub-operation subjects for data processing can be set and the data can be processed by operating according to the settings.

[0032] According to an embodiment of the present invention, when operating a smart farm based on AI, it may be possible to assist farmers in their farming, and also to bridge the gap between information provided by the network and farmers, and to provide easy access to crop, environment, soil characteristics, weather, fertilizer, and user-specific information.

[0033] In addition, the embodiment of the present invention can easily control equipment such as pumps that constitute a smart farm remotely, and in the process, control of equipment within the field can be made easier by using a messenger-based chat service.

[0034] The effects according to the present invention are not limited to those exemplified above, and more diverse effects are included in this specification.

[0035] Figure 1 is a drawing showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to an embodiment of the present invention;

[0036] Figure 2 is a diagram schematically showing the system of Figure 1;

[0037] Figure 3 is a drawing for explaining the local server of Figure 1;

[0038] Figure 4 is a drawing for explaining the chatbot training installed in the AI ​​remote assistance smart farm device of Figure 1.

[0039] Figure 5 is a flowchart showing the operation process of the chatbot trained by Figure 4.

[0040] Figures 6 and 7 are drawings for explaining the operation process of a remote assistance smart farm system equipped with artificial intelligence according to an embodiment of the present invention.

[0041] Figure 8 is a block diagram illustrating the detailed structure of the AI ​​remote assistance smart farm device of Figure 1.

[0042] Figure 9 is a flowchart showing the operation process of the AI ​​remote assistance smart farm device of Figure 1.

[0043] FIG. 10 is a drawing showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to the second embodiment of the present invention; and

[0044] FIG. 11 is a drawing showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to a third embodiment of the present invention.

[0045] The present invention is not limited to the embodiments described below, but can be implemented in various different forms. These embodiments are merely illustrative of the contents of the present invention and are provided to provide those skilled in the art with a detailed understanding of the scope of the invention. The present invention is defined solely by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

[0046] Embodiments described herein will be described with reference to cross-sectional and / or plan views, which are ideal examples of the present invention. In the drawings, the illustrated regions are expressed for the effective explanation of the technical contents. Therefore, the regions illustrated in the drawings have a schematic nature, and the shapes of the regions illustrated in the drawings are intended to illustrate specific forms of the device regions and are not intended to limit the scope of the invention. Although terms such as first, second, and third are used to describe various components in various embodiments of the present specification, these components should not be limited by such terms. These terms are used only to distinguish one component from another. The embodiments described and illustrated herein also include complementary embodiments thereof.

[0047] The terminology used herein is for the purpose of describing embodiments only and is not intended to be limiting of the present invention. In this specification, the singular also includes the plural unless specifically stated otherwise. As used herein, the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components, steps, operations, and / or elements to the mentioned components, steps, operations, and / or elements.

[0048] Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used in their common sense to those of ordinary skill in the art to which the present invention pertains. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0049] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0050] FIG. 1 is a diagram showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to an embodiment of the present invention, FIG. 2 is a diagram schematically showing the system of FIG. 1, FIG. 3 is a diagram for explaining the local server of FIG. 1, FIG. 4 is a diagram for explaining chatbot training installed in the AI ​​remote assistance smart farm device of FIG. 1, and FIG. 5 is a flowchart showing the operation process of the chatbot trained by FIG. 4.

[0051] As illustrated in FIG. 1, a remote assistance smart farm system (hereinafter, remote assistance smart farm system) (90) equipped with artificial intelligence (AI) according to an embodiment of the present invention includes a part or all of a smart farm equipment device (100), a user terminal device (110), a communication network (120), and an AI remote assistance smart farm device (130).

[0052] Here, “including some or all” means that some components, such as a user terminal device (110), are omitted so that a remote assistance smart farm system (90) is configured, or some or all of the components constituting the AI ​​remote assistance smart farm device (130) can be integrated into a network device (e.g., a wireless switching device, a gateway, etc.) constituting a communication network (120), etc. In order to help a sufficient understanding of the invention, it is explained as including all.

[0053] Smart farm equipment (100) may include various types of devices for operating a farm, or more precisely, a farm by incorporating Internet of Things (IoT) or artificial intelligence technology. It may be called a "smart farm" because it is operated smartly compared to existing farms, and devices such as sensors that enable the operation of such a smart farm or computers or servers that process the data obtained from such sensors may be smart farm equipment (100). For example, temperature, humidity, lighting, and sunlight may be considered very important in a farm. Accordingly, the data acquired through sensors may be analyzed to detect the current cultivation status of plants, etc., and the operation of various devices for adjusting temperature, humidity, lighting, and sunlight may be controlled based on the detection results.

[0054] In the embodiment of the present invention, a smart farm equipment device (100) is briefly illustrated as including sensors (101) and a local server (105) as shown in FIG. 2, but various other equipment may be configured. Here, the sensors may include various types of sensors to enable easy access to crops, the environment, soil characteristics, weather, fertilizer, and user-specific information. For example, in relation to the weather, a solar radiation (measurement) sensor for sensing solar radiation and an illuminance (measurement) sensor for measuring illuminance may be used. The sensing data acquired by these sensors may be provided to and managed by a local server (105) managed by a smart farm, i.e., a farm manager. Here, the local server (105) may be a control device operated by the farm manager, and may also include a manager's computer linked to the control device. Of course, the smart farm equipment (100) may be further equipped with water supply facilities to provide water or nutrients to crops on the farm, and accordingly, pumps or electronic valves may be installed to control these facilities. The control device or local server (105) may also be capable of controlling the operation of the pumps or electronic valves.

[0055] According to an embodiment of the present invention, the local server (105) may be used as an edge device for collecting and analyzing sensing data from sensors as a computing device. For example, if an existing control device simply controlled the operation of a specific facility according to a control command from a remote AI remote assistance smart farm device (130), the edge device may of course also be capable of such operations, but it may also be capable of collecting and analyzing sensing data from sensors and transmitting the analysis results to a remote AI remote assistance smart farm device (130). Since data analysis is performed primarily, the load on the network, i.e., the communication network (120), can be reduced, and it may also be possible to reduce the load (e.g., computational processing burden, etc.) on the hardware (H / W) and software (S / W) resources of the AI ​​remote assistance smart farm device (130).

[0056] Above all, the smart farm equipment device (100) according to the embodiment of the present invention can be remotely controlled automatically by artificial intelligence, such as a pump, according to a method preset by the farm manager, or more precisely, even without the manager's settings, to ensure crop cultivation in an optimal environment. For example, even when the same crop is cultivated, the cultivation environment can vary depending on the region where the crop is cultivated and the current cultivation area. Therefore, it is desirable to perform remote control by artificial intelligence by comprehensively considering such different environments. Of course, during such remote control, a report can be sent to the user terminal device (110) carried by the manager.

[0057] Figure 3 briefly illustrates the operation of the local server (105) of Figure 2. The local server (105) constituting the smart farm equipment device (100) plays an important role in information exchange between the RAS and the chatbot. The local server (105) receives equipment control commands from the RAS and transmits them to equipment (e.g., pumps, etc.). The server constituting the AI ​​remote assistance smart farm device (130) also receives sensor data from nodes (e.g., boards on which sensors are configured, etc.) and sends them to the local server (105). The local server (105) can access all RAS components for data exchange.

[0058] The user terminal device (110) may include various types of terminal devices possessed by managers operating smart farms. The user terminal device (110) may include not only PC-based terminal devices such as desktop computers or laptop computers, but also mobile-based terminal devices such as smartphones, tablet PCs, and wearable devices worn on the wrist. In the embodiment of the present invention, a mobile-based terminal device capable of utilizing a messenger-based AI chatbot service is preferred, but is not particularly limited thereto. For example, a smart farm manager can receive answers to questions related to the farm he or she manages through an AI chatbot service such as ChatGPT, and can also perform actions for remote control of the farm. For example, the user terminal device (110) may receive specific information that can be customized to the user and may be provided with an AI-based interface that enables on-site equipment control. For example, if a user requests "TURN ON PUMP" to the AI ​​engine mounted on the AI ​​remote assistance smart farm device (130) of FIG. 1 through the AI ​​interface, the pump will start operating, and feedback that the pump is turned on will also be provided to the user terminal device (110), allowing the manager to share the situation.

[0059] The communication network (120) can be configured in various forms. The communication network (120) can include both wired and wireless communication networks. For example, a wired or wireless Internet network can be used or linked as the communication network (120). Here, the wired network includes an Internet network such as a cable network or a public switched telephone network (PSTN), and the wireless communication network includes a CDMA, WCDMA, GSM, EPC (Evolved Packet Core), LTE (Long Term Evolution), Wibro network, etc. Of course, the communication network (120) according to the embodiment of the present invention is not limited thereto, and can be used as an access network of a next-generation mobile communication system to be implemented in the future, for example, a cloud computing network in a cloud computing environment, a 5G network, a 6G network, etc. For example, if the communication network (120) is a wired communication network, an access point within the communication network can connect to a telephone exchange, etc., but if it is a wireless communication network, data can be processed by connecting to an SGSN or GGSN (Gateway GPRS Support Node) operated by a communication company, or data can be processed by connecting to various relays such as a BTS (Base Transceiver Station), NodeB, or e-NodeB.

[0060] The communication network (120) may include an access point. The access point may include a small base station, such as a femto or pico base station, which is often installed inside a building. Here, the femto or pico base station may be classified according to the maximum number of smart farm equipment (100) or user terminal devices (110) of FIG. 1 that can be connected to the small base station. Of course, the communication network (120) may include a short-range communication module for performing short-range communication, such as Zigbee or Wi-Fi, with the smart farm equipment (100) or user terminal devices (110). The access point may use TCP / IP or RTSP (Real-Time Streaming Protocol) for wireless communication. Here, short-range communication can be performed using various standards such as Bluetooth, Zigbee, infrared (IrDA), radio frequency (RF) such as ultra high frequency (UHF) and very high frequency (VHF), and ultra wideband (UWB) in addition to Wi-Fi. Accordingly, the access point extracts the location of the data packet, designates the best communication path for the extracted location, and forwards the data packet along the designated communication path to the next device, such as the AI ​​remote assistance smart farm device (130). The access point can share multiple lines in a general network environment, and may include, for example, a router, a repeater, and a repeater.

[0061] The AI ​​remote assistance smart farm device (130) may include, for example, a cloud server and a database (130a) linked to the server. The AI ​​remote assistance smart farm device (130) according to an embodiment of the present invention is equipped with an AI engine and can provide chatbot services through it. Based on the AI ​​engine, the chatbot can assist farmers in farming or operate in agricultural fields. This bridges the gap between network-provided information and farmers. The AI ​​remote assistance smart farm device (130) enables users to easily access crop, environment, soil characteristics, weather, fertilizer, and user-specific information. It can be considered the first engine that allows humans to interact with an agricultural AI engine. The AI ​​remote assistance smart farm device (130) not only provides users with customized information but also provides an AI-based interface for controlling equipment in the field. As mentioned above, when a user requests "TURN ON PUMP" from the engine, the pump is turned on. Feedback indicating that the pump is turned on is also shared with the user. Users can ask any information they want to know to an AI chatbot (e.g., ChatGPT) embedded in the AI ​​remote assistance smart farm device (130), and simultaneously control equipment within the field. Queries can be made in a messenger-based chat format. Figure 2 briefly illustrates this process.

[0062] The AI ​​engine installed in the AI ​​remote assistance smart farm device (130), or more precisely, the chatbot model (or program) for providing the chatbot service, is preferably trained (or learned) with learning data for providing the smart farm service according to an embodiment of the present invention, and the chatbot model built through such training is preferably used. Figure 4 illustrates the chatbot training of the chatbot model. The first step in all AI-based processes is to generate data for model training (S400 to S420). Frequently asked questions (FAQs) from numerous farms across the country are collected and verified answers are organized (S410). The answers may utilize data provided by agricultural experts, for example. This FAQ can be stored in a JSON file (S420). While the JSON file is a document written in JavaScript Object Notation, the present invention is not limited to this format. The file also contains several general questions related to agriculture, smart farming company policies, government rules and regulations, and other possible questions. The training data also includes questions related to RAS sensor data and equipment. This data is imported into the AI ​​model and trained. The training process is closely monitored to ensure maximum accuracy and fast model operation. The process is clearly illustrated in Figure 4, and the model generated through this process is created (or output), stored, and used to respond to user queries (S430, S440).

[0063] The AI ​​remote assistance smart farm device (130) can perform chatbot operations, such as those illustrated in FIG. 5, after being equipped with an AI model trained according to the process illustrated in FIG. 4. For example, a user (e.g., a farm manager, etc.) inputs a query, or inquiry, and sends it to the chatbot engine (131) (S500). The recipient and message pass through a validation and inspection process (S510). For example, in order to use the service, a user or manager of a user terminal device (110) can register user information when registering for the service, and validation can be performed by comparing it with previously registered user information. Upon successful completion of the validation and inspection process, the query is transmitted through an AI model that selects an answer that is almost identical to the query, and then the system, i.e., the AI ​​remote assistance smart farm device (130), sends it to the user. The user's user terminal device (110) can receive an answer to the query. More specifically, the AI ​​engine (131) can process a response to a query according to the processes of S520 to S525 if the validation and verification process is successfully completed. On the other hand, if the query is denied, the AI ​​engine (131) can notify the denial according to the processes of S530 and S535.

[0064] In addition to the above, the contents related to the smart farm equipment (100), user terminal device (110), communication network (120), and AI remote assistance smart farm device (130) of FIG. 1 will be continuously covered in the following, so detailed contents will be replaced with those contents.

[0065] FIG. 6 and FIG. 7 are drawings for explaining the operation process of a remote assistance smart farm system equipped with artificial intelligence according to an embodiment of the present invention.

[0066] Referring to Figures 6 and 7, the process begins when a user requests some information from the AI ​​engine or chatbot. This process may consist of several steps, including sending a query to the Signal API and then passing it through a security layer (e.g., encryption). This process is clearly illustrated in Figure 7.

[0067] A user writes and transmits a user query (e.g., via the user terminal device (110) of FIG. 1) (S700). The user writes a query (on the service screen), which may be a FAQ, i.e., a knowledge-based question, or a RAS command. Here, the RAS command may be a command for controlling the operation of equipment (e.g., a pump) that constitutes a smart farm.

[0068] The query is transmitted to the signal server, and the query can be input from the signal server to the code engine via the API of the RAS processor (S701). Here, the signal server can be, for example, a communication server (or communication device) for communicating with the user terminal device (110) of FIG. 1. The sender's number (e.g., phone number or device identification information of the terminal device) and the message are transmitted to the code engine. The code engine is where all of the chatbot's functions are implemented.

[0069] The code engine (133) receives data and can detect the input language of the message (S702). If the code engine (133) cannot detect any language, it determines the incoming message as invalid and deletes it. If the input language is detected as Korean, English, or another language, it proceeds to the next step.

[0070] In the next step, user authentication can be performed (S703). The recipient number is verified by comparing it with a list of approved numbers. For example, the recipient number may be provided upon service registration and stored in a pre-stored list. If the number is not in this list, the engine (133) stops processing the number and sends a message indicating that the user is not authorized.

[0071] In addition, the code engine (133), such as the AI ​​engine, can perform mode classification operations upon completion of user authentication (S705). If the recipient number passes the authentication process, the chatbot mode is checked. If the mode is simple (or first mode) or chatbot (or second mode), the user can also change the mode by sending a mode change command. The mode change command can be received from the user terminal device (110) (S710). Here, the mode can be a button or command preset so that a series of operations are performed sequentially at once. For example, if operations a, b, c, and d can be performed in simple mode, operations e, f, and g can be performed (sequentially) in chatbot mode.

[0072] In simple mode according to an embodiment of the present invention, the user must send a specific string to perform a specific task. For example, to obtain node information, the user sends "Node info." The chatbot responds with the node information. The user can also activate farm equipment in this mode. In chatbot mode, the user can converse with the chatbot and ask questions and information about the farm and the company. The user can also request node and sensor information in this mode.

[0073] The AI ​​engine or code engine (133) according to an embodiment of the present invention may configure a response generator (135) for responding. The response generator (135) may be configured using hardware, software, or a combination thereof. In this step, a response to the user is generated. The response includes information requested by the user and may be transmitted to a specific user or a list of users, depending on the user's selection.

[0074] In addition, the AI ​​remote assistance smart farm device (130) of FIG. 1 according to an embodiment of the present invention can also perform data exchange operations (S730). For example, farmers cultivating the same crop in the same region, although not necessarily in the same region, can exchange or share data related to the crops or smart farm operations. Even for the same crop, the smart farm environment can vary significantly, such as cultivation area or weather conditions in a specific region. It is entirely possible to provide data related to the surrounding environment of the smart farm during data exchange.

[0075] In addition, the AI ​​remote assistance smart farm device (130) of FIG. 1 according to an embodiment of the present invention can process and provide data to suit the cultivation environment of a specific farmer when, for example, two farmers are operating the same crops but the cultivation environment, for example, the environment of the smart farm, is different, or it is entirely possible to notify related information through an AI chatbot while providing data. Through this, farmers can receive (or learn) smart farm operation know-how from other farmers and operate their own smart farms with ease. Of course, the AI ​​remote assistance smart farm device (130) can automatically remotely control equipment within the smart farm when sharing data if control operation is required, and it is entirely possible to remotely control equipment after receiving prior approval from the farm user.

[0076] Fig. 8 is a block diagram illustrating a detailed structure of the AI ​​remote assistance smart farm device of Fig. 1.

[0077] As illustrated in FIG. 8, the AI ​​remote assistance smart farm device (130) according to an embodiment of the present invention includes part or all of a communication interface unit (800), a control unit (810), a smart farm AI remote assistance unit (820), and a storage unit (830).

[0078] Here, “including some or all” means that some components, such as the storage unit (830), may be omitted to configure the AI ​​remote assistance smart farm device (130), or some components, such as the smart farm AI remote assistance unit (820), may be integrated into other components, such as the control unit (810), and in order to help a sufficient understanding of the invention, it is described as including all.

[0079] The communication interface unit (800) communicates with the smart farm equipment (100) and the user terminal device (110) via the communication network (120) of Fig. 1. During the communication process, the communication interface unit (800) can perform operations such as modulation / demodulation, encoding / decoding, muxing / demuxing, encryption / decryption, and scaling to convert resolution, which are obvious to those skilled in the art and thus will not be further described.

[0080] The communication interface unit (800) can receive sensing data for sensing the environment of the smart farm from the local server (105) constituting the smart farm equipment device (100) and transmit the data to the control unit (810). In addition, the communication interface unit (800) can provide a messenger-based AI chatbot service when a service request is made from a user terminal device (110). When a RAS command is provided from the user terminal device (110), the command can be provided to the control unit (810), and a control command for controlling equipment such as a pump constituting the smart farm according to the RAS command can be transmitted to the local server (105). Here, the control command can be information in the form of binary bits.

[0081] The control unit (810) can perform the overall control operations of the communication interface unit (800), the smart farm AI remote assistance unit (820), and the storage unit (830) of FIG. 8. For example, when a user's service request signal is received through the communication interface unit (800), the control unit (810) can execute a graphic (GUI) program installed in the smart farm AI remote assistance unit (820) to provide a service screen, and the service screen may be an AI chatbot service. In addition, when a RAS command is received through the chatbot service, the control unit (810) can provide the command of the command to the smart farm AI remote assistance unit (820) and perform an operation requested by the smart farm AI remote assistance unit (820) based on the analysis result. In this process, the smart farm AI remote assistance unit (820) can generate and provide control commands related to the control of equipment constituting the smart farm, and accordingly, the control unit (810) can control the communication of the communication interface unit (800) to transmit the commands to the smart farm equipment device (100) of FIG. 1.

[0082] In addition, the control unit (810) can perform an operation to train various agricultural data after installing the AI ​​engine, i.e., the AI ​​model, installed in the smart farm AI remote assistance unit (820). Here, the agricultural data includes various types of data. It can include several general questions related to agriculture, smart agricultural company policies, government rules and regulations, and other possible questions. In addition, the training (or learning) data can also include questions related to RAS sensor data and equipment. Such data can be temporarily stored in the storage unit (830) under the control of the control unit (810) and then provided to the smart farm AI remote assistance unit (820). Furthermore, such data and the analysis results thereof can be systematically classified and stored in the DB (130a) of FIG. 1 under the control of the control unit (810). In this process, the communication of the communication interface unit (800) can be controlled so that the data can be stored and managed in the DB (130a) through a dedicated network such as an intranet without separate data processing.

[0083] The smart farm AI remote assistance unit (820) may be equipped with an AI engine or model for smart farm AI remote assistance according to an embodiment of the present invention. The AI ​​engine may provide a service to the user terminal device (110) of FIG. 1 in a state in which it has pre-learned the various types of data mentioned above. For example, the user terminal device (110) of FIG. 1 may transmit a query, which may be a knowledge-based question or a RAS command, via a chat service. The smart farm AI remote assistance unit (820) may determine the language in the process of analyzing the received query, and may also determine in which mode it should operate. Here, the mode may include whether it is a chatbot mode or a simple mode, and if a RAS command of "TURN ON PUMP" is received, it may operate in the simple mode to control the operation of the pump constituting the smart farm. Operation in the simple mode may be possible by determining a specific string.

[0084] For example, when a RAS command is received, the smart farm AI remote assistant (820) may request the user terminal device (110) to select a mode change. In other words, if the simple mode is selected for the above RAS command, the corresponding RAS command can be analyzed accordingly. If the chatbot mode is selected for the RAS command, a corresponding answer can be found in the library and provided. Of course, the method for selecting the mode can be implemented in various ways. For example, two buttons (e.g., simple mode, chatbot mode, red button, blue button, etc.) can be activated and displayed around the chat window. An action can be performed by selecting these buttons. Of course, it is also possible to select the mode first and then transmit the command.

[0085] Furthermore, the smart farm AI remote assistant (820) can operate to enable users of farms cultivating the same crop to exchange or share data related to the operation of the smart farm. In other words, smart farms cultivating the same crop may differ in many aspects, such as their scale and facilities. Climatic conditions may also vary by region. Therefore, the smart farm AI remote assistant (820) can easily check the smart farm-related information of the user receiving the data during data exchange and process and provide the data to suit the environment. Alternatively, it can provide data related to the smart farm environment of the user providing the data for reference when utilizing the data. For example, the smart farm AI remote assistant (820) can receive information related to a specific user's smart farm (e.g., scale or facility equipment information) when signing up for the service, and can make judgments based on this information.

[0086] The storage unit (830) can temporarily store various types of data processed under the control of the control unit (810). The storage unit (830) can receive sensing data (e.g., temperature, humidity, illuminance, amount of sunlight, etc.) acquired (or generated) from various types of sensors provided in the smart farm, store the data, and then provide the data to the smart farm AI remote assistance unit (820) for data analysis.

[0087] In addition to the above, the communication interface unit (800), control unit (810), smart farm AI remote assistance unit (820), and storage unit (830) of FIG. 8 can perform various operations, and other detailed information has been sufficiently explained above, so those contents will be used instead.

[0088] Meanwhile, the communication interface unit (800), control unit (810), smart farm AI remote assistance unit (820), and storage unit (830) of FIG. 8 according to an embodiment of the present invention are configured as physically separate hardware modules, but each module may store and execute software for performing the above operations therein. However, the software is a collection of software modules, and each module may be formed of hardware, so there will be no particular limitation on the configuration such as software or hardware. For example, the storage unit (830) may be hardware such as storage or memory. However, since it is also possible to store information (repository) in software, there will be no particular limitation on the above.

[0089] In addition, as another embodiment of the present invention, the control unit (810) may include a CPU and a memory, and may be formed as a single chip. The CPU may include a control circuit, an operation unit (ALU), a command interpretation unit, and a registry, and the memory may include a RAM. The control circuit may perform a control operation, the operation unit may perform an operation of binary bit information, and the command interpretation unit may perform an operation of converting a high-level language into machine language and vice versa, including an interpreter or a compiler, and the registry may be involved in software data storage. According to the above configuration, for example, at the initial operation of the AI ​​remote assistance smart farm device (130) of FIG. 1, the program stored in the smart farm AI remote assistance unit (820) may be copied and loaded into the memory, i.e., RAM, and then executed, thereby rapidly increasing the data operation processing speed. In the case of a deep learning model, it may be loaded into the GPU memory instead of the RAM and executed by accelerating the execution speed using the GPU.

[0090] Figure 9 is a flowchart showing the operation process of the AI ​​remote assistance smart farm device of Figure 1.

[0091] For convenience of explanation, referring to FIG. 9 together with FIG. 1, the AI ​​remote assistance smart farm device (130) according to an embodiment of the present invention stores an AI model that has learned various agricultural-related data for operating a smart farm based on artificial intelligence (S900). The AI ​​model may be configured to include a code engine and a chatbot model. The code engine may perform operations such as language detection, user authentication, and mode classification, and the chatbot model may be used to operate in chatbot mode to provide answers to user queries.

[0092] In addition, when a RAS command for controlling the operation of equipment constituting a smart farm is provided as a messenger-based chat service from a user terminal device (110) of a user managing a smart farm, the AI ​​remote assistance smart farm device (130) can operate to control the equipment by providing it to a local device such as a server that operates the equipment according to the received RAS command by executing an AI model (S910).

[0093] For example, the user terminal device (110) of Fig. 1 may transmit a query such as "node information" or "TURN ON PUMP" according to a service request. The AI ​​remote assistance smart farm device (130) may analyze the received query to determine a specific string for performing a specific task and operate in a simple mode to respond with respect to the node information. In this mode, the AI ​​remote assistance smart farm device (130) may perform an operation to activate the equipment of the farm.

[0094] Of course, the mode of the chatbot mentioned above is checked, and if the checked mode is simple or a chatbot, the operations of changing the mode according to the user's mode change command can be used in an integrated (or fused) manner according to an embodiment of the present invention, so the embodiment of the present invention will not be particularly limited to any one form. Here, integration may mean that two modes can be performed in one program module.

[0095] In addition to the above, the AI ​​remote assistance smart farm device (130) of FIG. 1 can perform various operations, and other detailed information has been sufficiently explained above, so it will be replaced with that information.

[0096] FIG. 10 is a drawing showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to a second embodiment of the present invention.

[0097] As illustrated in FIG. 10, a remote assistance smart farm system (990) equipped with artificial intelligence (AI) according to the second embodiment of the present invention includes a smart farm equipment device (1001, 1003) including a main device such as a sensor (1001) and main software (SW) (1003), a user terminal device (1010), and a server (1030) such as a computer (PC), in part or in whole, and may further include a chatbot device (1035) included in or linked to the server (1130). Here, “including part or all” is not significantly different from the meaning described above, and therefore, the contents thereof will be replaced.

[0098] In Fig. 10, a server-based system that operates locally is referred to, and the system does not require an external communication network such as the Internet. For example, communication can be made through a dedicated network such as an intranet installed in a smart farm. In addition, a client, i.e., a user terminal device (1010), can connect to the server from any local network device. Here, the server can be a computer or server operated by a smart farm manager. In addition, the sensor (1001) can communicate through a wireless / wired network. Such communication can be made possible through a setting method set in advance by an administrator or system designer. The communication path for communication is designated in advance. The sensor (1001) can communicate directly or indirectly with the server or main system in various ways, for example, direct communication and P2P (Peer to Peer) communication can be made. For this communication, Bluetooth, LoRa communication, and RF (radio frequency) communication can be performed.

[0099] The chatbot (device) (1035) communicates with the server (1030) via a wireless / wired network. The chatbot (1035) is an AI robot capable of messenger-based chatting. As this has been sufficiently explained above, further explanation will be omitted.

[0100] FIG. 11 is a drawing showing a remote assistance smart farm system equipped with artificial intelligence (AI) according to a third embodiment of the present invention.

[0101] As illustrated in FIG. 11, a remote assistance smart farm system (1090) equipped with artificial intelligence (AI) according to the third embodiment of the present invention is a system without a server that operates locally as in FIG. 10, and includes a smart farm equipment device (1101, 1103) including a main device such as a sensor (1101) or a main SW (1103), a user terminal device (1110), and a part or all of a chatbot (device) (1105), where “including a part or all” does not differ significantly from the meaning described above.

[0102] Comparing the system (1090) of FIG. 11 with the system (990) of FIG. 10, the system of FIG. 11 can be configured by omitting the server (1030) as in FIG. 10. In other words, for example, a device such as a computer or server that constitutes a smart farm equipment device (1101, 1103) can perform the operation of the server (1130) as in FIG. 10. Accordingly, the chatbot (1105) of FIG. 11 can communicate with a smart farm equipment device such as the main device (1103) that executes the main SW. Configuring a dual system as in FIG. 10 or a unified system as in FIG. 11 locally can be appropriately configured and operated according to the needs of a system designer or smart farm manager when reducing the burden of computational processing or when fast data processing is required.

[0103] More specifically, in the case of Fig. 11, as in Fig. 10, the system is configured and operates on a local basis, not a global basis as in Fig. 1, and can be viewed as operating without a server. As described in Fig. 10, in the case of the system (1090) of Fig. 11, an external communication network such as the Internet is not necessary, and a client, i.e., a user terminal device (1110), can directly connect to the system through an app. Of course, Bluetooth, Wi-Fi, and RF communication may be possible in this regard. The sensor (1101) can directly communicate through P2P communication of Bluetooth, LoRa, and RF. Of course, the sensor (1101) here may include peripheral circuits such as a communication module for communication in addition to the sensor. Therefore, the sensor (1101) may also be referred to as a sensor module. The chatbot (1105) is built into the device, so there is no need to transmit data outside the device. For example, when a user requests a chatbot service from a terminal device (1110), a chatbot (1105) is executed under the mediation of the main device (1103) to provide the service and provide relevant answers or assistance to the inquiry. This has been previously explained, so we will refer to that description instead.

[0104] Meanwhile, in another embodiment of the present invention, the fourth embodiment, it is entirely possible to operate a smart farm by configuring an Internet-powered system that operates on a server basis, or more precisely, an Internet-powered system that operates on a server basis. For example, sensor data is transmitted to a server, such as a remote cloud server. Nodes then directly transmit data to the server, and post-processing is performed on the server. The nodes transmit data to a central controller (e.g., a local server or a main device), which then transmits all data to the server. Here, the nodes can be the sensor nodes of FIG. 1, and the central controller can be the local server of FIG. 1. The client receives this data upon request or continuously. A chatbot and system algorithm engine are installed on the server. The chatbot can communicate with the online server.

[0105] In addition, in another embodiment of the present invention, that is, the fifth embodiment, it is entirely possible to operate a smart farm by configuring a hybrid system that combines local and Internet (e.g., global) systems. These hybrid systems can be broadly categorized into three categories. Category 1 is a system that combines a local network and an Internet-based system. For example, the local network may operate as the main system, and the Internet-based system may operate as a sub-system. Main processing, such as sensor data, may be performed locally, while only auxiliary processing, such as data storage and management, may be performed globally. Category 2 is a system that combines an Internet-based system and a local network. The Internet-based system operates as the main system, and the local network operates as a sub-system, but the local network may include a chatbot. Category 3 is a system that combines an Internet-based system and a local network, but the local network may be a combination of the main system and a chatbot.

[0106] First, in Category 1 (Local Network + Internet-based), the local network can be server-based. Clients can connect to the server from any local network device. Sensors communicate with the server via wireless or wired networks. Sensors can communicate directly via peer-to-peer (P2P) communication such as Bluetooth, LoRa, or RF. Furthermore, in Internet-based networks, chatbots communicate with the system via an online server. This allows clients to access the system from anywhere and take advantage of the low cost and reliability of a local-based system. Internet-based and local-based systems have been fully explained previously with reference to Figures 10 and 11.

[0107] In Category 2 (Internet-based + Local Network), sensors operating on the Internet transmit sensor data to a server. Nodes transmit data directly to the server, and post-processing is performed on the server. Nodes also transmit data to a central controller, which then transmits all data to the server. The server then transmits data directly to client devices, where clients can seed and interact with the data. In contrast, in a local network, the chatbot engine of a chatbot runs on a local server to avoid additional costs or heavy computations on an online server. However, because the chatbot system is connected to the online server, the chatbot and sensors can communicate with each other in this way.

[0108] Furthermore, in Category 3 (Internet-based + Local Network), Internet-based sensors transmit sensor data to a server. Nodes then transmit data directly to the server. The server then transmits the data to the client's main system for post-processing. Conversely, in a local network, the main system receives data from the server, processes it, and prepares it for the user. Users can also access the local network to view and interact with the data. The chatbot engine of a chatbot in a local network can run on a local server to avoid the additional costs and cumbersome computations of an online server. However, because the chatbot system is connected to an online server, the chatbot and sensors can communicate (or converse) with each other in this way.

[0109] Regarding the embodiments of the present invention described so far, it is necessary to examine them in more detail, including (1) the software engine and computing power, (2) data flow and communication, and (3) the GUI. First, the software engine and computing power can be categorized into locally powered, Internet-based, and hybrid. In the local mode, all software engines and computing power are provided on the local machine. While no online connection is required to operate the system, the hardware must be powerful enough to run the software engine. In contrast, in the Internet mode, all software engines and computing power are located on an online server. The system requires minimal hardware but cannot operate without a connection to the online server. Finally, in the hybrid mode, the system runs on shared resources between the local machine and the online server. While the system can operate without an online connection, some functionality may be lost without one. Regarding data flow and communication, routerless communication involves data flow through a direct connection from the sensor to the software engine. Examples include Bluetooth, USB, Radio waves, LoRa, RS48265, Modbus, CAN, Wi-Fi, I2C, serial, SPI, and all similar technologies and communication protocols. In a server-based approach, data flows from sensors to a server, and a software engine processes the data from the server. Regarding the GUI, the communication type involves software (e.g., a GUI program) located on the user device and providing an interface to the user. The software resides on a local device connected to the user device and provides the interface to the user. The software interface resides on a remote device connected to the user device and provides the interface to the user.

[0110] In addition to the above, the contents related to the third to fifth embodiments of the present invention have been sufficiently explained above, so detailed contents will be replaced with those contents.

[0111] Meanwhile, even though all components constituting the embodiments of the present invention have been described as being combined or operating in combination, the present invention is not necessarily limited to such embodiments. That is, within the scope of the purpose of the present invention, all of the components may be selectively combined and operated one or more times. In addition, although all of the components may be implemented as individual independent hardware, some or all of the components may be selectively combined and implemented as a computer program having program modules that perform some or all of the functions of the combined hardware in one or more pieces. The codes and code segments constituting the computer program can be easily inferred by those skilled in the art of the present invention. Such a computer program may be stored in a non-transitory computer-readable storage medium and read and executed by a computer, thereby implementing the embodiments of the present invention.

[0112] Here, the non-transitory readable storage medium refers to a medium that permanently stores data and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, the above-described programs may be stored and provided on a non-transitory readable storage medium, such as a CD, DVD, hard disk, Blu-ray disc, USB, memory card, or ROM.

[0113] Although the preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above, and various modifications may be made by those skilled in the art without departing from the spirit or scope of the present invention as claimed in the claims. Furthermore, such modifications should not be understood individually from the technical idea or prospect of the present invention.

Claims

1. A storage unit that stores an AI model that has learned various agricultural data for operating a smart farm based on artificial intelligence (AI); and When a RAS (Remote Assistant Smart-Farming) command for controlling the operation of equipment constituting the smart farm is provided as a messenger-based chat service from a user terminal device of a user managing the smart farm, a control unit that executes the AI ​​model and provides the AI ​​model to a local device that operates the equipment according to the received RAS command so that the equipment is controlled; AI remote assistance smart farm device including.

2. In paragraph 1, The above control unit is an AI remote assistance smart farm device that trains the AI ​​model with RAS sensor data and equipment-related question data of the sensors that constitute the smart farm as the above agricultural-related general data.

3. In paragraph 1, The above control unit is an AI remote assistance smart farm device that exchanges or shares data related to the operation of a smart farm between a local device at a first location and a local device at a second location.

4. In paragraph 1, The above control unit is an AI remote assistance smart farm device that checks the mode of the chatbot when the receiving number of the user terminal device passes the authentication process, and if the checked mode is simple or chatbot, changes the mode according to the user's mode change command and operates.

5. In paragraph 4, The above control unit determines the string of the RAS command and controls the operation of the equipment in a single mode according to the determination result, and performs a conversation with a chatbot in a chatbot mode, which is an AI remote assistance smart farm device.

6. A step for storing an AI model that has learned various agricultural data for operating a smart farm based on artificial intelligence (AI). A step in which the control unit provides a RAS command for controlling the operation of equipment constituting the smart farm from a user terminal device of a user managing the smart farm as a messenger-based chat service, and executes the AI ​​model to provide the AI ​​model to a local device that operates the equipment according to the received RAS command so that the equipment is controlled; A method for operating an AI remote assistance smart farm device, including:

7. In paragraph 6, A method for operating an AI remote assistance smart farm device, further comprising: a step of the control unit teaching the AI ​​model RAS sensor data of sensors constituting the smart farm and question data related to equipment as the agricultural data; 8. In paragraph 6, A method for operating an AI remote assistance smart farm device, further comprising: a step of exchanging or sharing data related to the operation of a smart farm between a local device at a first location and a local device at a second location, by the control unit.

9. In paragraph 6, A step of checking the mode of the chatbot when the receiving number of the user terminal device passes the authentication process; and If the mode confirmed above is simple or chatbot, a step of changing the mode and operating according to the user's mode change command; A method for operating an AI remote assistance smart farm device, further comprising:

10. In paragraph 9, The steps to operate by changing the above mode are: A method for operating an AI remote assistance smart farm device that judges the string of the above RAS command, controls the operation of the device in a single mode according to the judgement result, and conducts a conversation with a chatbot in a chatbot mode.

11. A local device that controls the operation of equipment constituting the smart farm based on the analysis results of sensing data acquired by sensors installed in the smart farm; and An AI remote assistance smart farm device that stores an AI model that has learned various agricultural data for operating the smart farm based on artificial intelligence (AI), and when a RAS command for controlling the operation of the equipment is provided as a messenger-based chat service from a user terminal device of a user managing the smart farm, executes the AI ​​model and controls the operation of the equipment according to the received RAS command; AI remote assistance smart farm system including.

12. In paragraph 11, The AI ​​remote assistance smart farm system, wherein the AI ​​remote assistance smart farm device operates in at least one of a global manner in which the device is connected to the local device remotely through an external communication network and operates remotely, and a manner in which the device is connected to the local device locally through an internal communication network in the smart farm and operates.

13. In paragraph 12, An AI remote assistance smart farm system in which the AI ​​remote assistance smart farm device communicates with the local device and the sensor when operating on the local basis, and provides a messenger-based artificial intelligence (AI) chat service to the user terminal device through the communication.

14. In paragraph 13, An AI remote assistance smart farm system in which the local device provides the communication and AI chat service when the AI ​​remote assistance smart farm device is configured to be omitted when the local device and the AI ​​remote assistance smart farm device operate on the local basis.

15. In paragraph 12, An AI remote assistance smart farm system in which the local device and the AI ​​remote assistance smart farm device operate in a hybrid manner combining the global method and the local-based method, and the main and sub-operation subjects for data processing are set and the data is processed by operating according to the settings.

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