Method for transmitting and processing sensing values of work vehicle based on edge device and edge device implementing the same

Abstract

One embodiment of the present invention discloses a method for processing the transmission of work vehicle sensing values ​​based on an edge device.

Description

Technology Field

[0001] The present invention relates to a method for processing the transmission of work vehicle sensing values ​​based on an edge device and an edge device implementing the same. More specifically, it relates to a technology for receiving sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifying them by importance based on variable priority, allocating bandwidth according to the classified importance, and transmitting them to a cloud server. Background Technology

[0002] Recently, in the agricultural sector, there has been a trend of equipping various work vehicles, such as autonomous tractors, rice transplanters, and combines, with multiple sensors including high-resolution cameras, LiDAR, GNSS modules, and IMUs to generate large amounts of data. These work vehicles generate sensing data amounting to several gigabytes (GB) per second to implement precision agriculture, and technology to process and transmit this data in real time is required.

[0003] However, most agricultural sites are located in communication blind spots far from urban areas, so LTE or 5G coverage is often unstable. Conventional data transmission methods adopt a First-In-First-Out (FIFO) method, which transmits data in the order it is generated. This has resulted in a problem where, if large volumes of video data occupy the communication network, subsequent emergency safety signals are also delayed.

[0004] Consequently, there is a limitation in that emergency signals are delayed by several minutes in the event of an agricultural machinery rollover accident, which can lead to casualties. Furthermore, conventional technology suffers from inefficiency because it unconditionally deletes the oldest data when storage space is insufficient, resulting in the loss of economically valuable data such as work area or yield while retaining unnecessary footage. Moreover, conventional technology has the limitation of failing to adapt to changing conditions by processing data with a fixed priority regardless of the status of the work vehicle. Prior art literature

[0005] Republic of Korea Published Patent Application No. 10-2025-0179407 (Published Dec. 30, 2025) The problem to be solved

[0006] The technical problem that the present invention aims to solve is to provide an edge device-based method for transmitting and processing work vehicle sensing values ​​and an edge device that implements the same. means of solving the problem

[0007] A method according to an embodiment of the present invention for solving the above technical problem comprises: a step of receiving a sensing value through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors; a step of classifying the sensing value by importance based on a variable priority in which the priority can be changed when a variable condition is established; and a step of allocating bandwidth according to the classified importance of the sensing value and transmitting it to a cloud server.

[0008] In the above method, the step of classifying by importance allows an AI model that has learned the variable priority to classify the sensing values ​​by importance.

[0009] In the above method, the plurality of sensors may include a GNSS module, a camera, an impact detection sensor, a LiDAR, and an IMU.

[0010] In the above method, the different channels may include a CAN communication-based channel, an RS232-based channel, and a channel for AHD video transmission.

[0011] In the above method, the step of classifying by importance may, when an impact amount exceeding a reference impact value is detected by an impact detection sensor included in the work vehicle, be considered as having established the variable condition, and generate a control command to increase the resolution of the image generated by the camera of the work vehicle and transmit it to the camera.

[0012] In the above method, the method may further include: a step of determining the communication quality status with the cloud server; and a step of sequentially deleting the sensing values ​​of the group with the lowest importance classified from the memory if the communication quality status is below a threshold and the memory usage exceeds a reference storage device.

[0013] In the above method, the work vehicle may be one of an autonomous tractor, an autonomous rice transplanter, an autonomous planter, an autonomous combine, or an autonomous boom sprayer.

[0014] One embodiment of the present invention may provide a computer-readable recording medium storing a program for executing the above method.

[0015] An edge device according to an embodiment of the present invention for solving the above technical problem comprises: a memory in which at least one program is stored; and a processor that performs calculations by executing the at least one program, wherein the processor receives a sensing value through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifies the sensing value by importance based on a variable priority in which the priority can change when a variable condition is established, and allocates a bandwidth according to the classified importance of the sensing value and transmits it to a cloud server.

[0016] In the above device, the processor can classify the sensing values ​​by importance using an AI model that has learned the variable priority.

[0017] In the above device, the plurality of sensors may include a GNSS module, a camera, an impact detection sensor, a LiDAR, and an IMU.

[0018] In the above device, the different channels may include a CAN communication-based channel, an RS232-based channel, and a channel for AHD video transmission.

[0019] In the above device, when an impact amount exceeding a reference impact value is detected by an impact detection sensor included in the work vehicle, the processor may consider that the variable condition has been established and generate a control command to increase the resolution of the image generated by the camera of the work vehicle and transmit it to the camera.

[0020] In the above device, the processor determines the communication quality status with the cloud server, and if the communication quality status is below a threshold and the memory usage exceeds the reference storage device, it can sequentially delete the sensing values ​​from the memory starting from the group with the lowest importance classified.

[0021] In the above device, the work vehicle may be one of an autonomous tractor, an autonomous rice transplanter, an autonomous planter, an autonomous combine, or an autonomous boom sprayer. Effects of the invention

[0022] According to the present invention, even in harsh environments where communication bandwidth is extremely narrow, it is ensured that emergency data directly related to life and safety is transmitted with the highest priority without being pushed aside by large volumes of general data.

[0023] In addition, according to the present invention, the loss of core data can be prevented by determining the value of data when communication is interrupted and selectively deleting data of low importance first.

[0024] Furthermore, according to the present invention, an autonomous management system can be implemented that independently recognizes the situation of a work vehicle and dynamically resets data importance.

[0025] In addition, according to the present invention, when an event occurs in a work vehicle, the resolution of the video can be dynamically switched to secure evidence video for analyzing the cause of the accident. Brief explanation of the drawing

[0026] FIG. 1 is a conceptual diagram showing the overall configuration of a cloud edge computing system according to one embodiment of the present invention. FIG. 2 is a conceptual diagram showing the connection relationship between a work vehicle, an edge device, and a cloud server according to one embodiment of the present invention. FIG. 3 is a block diagram showing the internal configuration of an edge device according to one embodiment of the present invention. FIG. 4 is a block diagram showing the detailed configuration of a processor of an edge device according to one embodiment of the present invention. FIG. 5 is a flowchart illustrating a method for transmitting work vehicle sensing values ​​based on an edge device according to an embodiment of the present invention. FIG. 6 is a flowchart showing the operation flow of an intelligent deletion policy according to one embodiment of the present invention. FIG. 7 is a flowchart illustrating an event-based image resolution dynamic switching method according to an embodiment of the present invention. Specific details for implementing the invention

[0027] The present invention is capable of various modifications and may have various embodiments; specific embodiments are illustrated in the drawings and described in detail in the detailed description. The effects and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various forms.

[0028] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. When describing with reference to the drawings, identical or corresponding components are given the same reference numerals, and redundant descriptions thereof will be omitted.

[0029] In the following embodiments, terms such as first, second, etc. are used not in a limiting sense, but for the purpose of distinguishing one component from another component.

[0030] In the following embodiments, singular expressions include plural expressions unless the context clearly indicates otherwise.

[0031] In the following embodiments, terms such as "include" or "have" mean that the features or components described in the specification are present, and do not preclude the possibility that one or more other features or components may be added.

[0032] Where an embodiment can be implemented differently, a specific process sequence may be performed differently from the order described. For example, two processes described consecutively may be performed substantially simultaneously or proceed in the reverse order of the description.

[0033] FIG. 1 is a conceptual diagram showing the overall configuration of a cloud edge computing system according to one embodiment of the present invention.

[0034] Referring to FIG. 1, a cloud edge computing system (10) according to one embodiment of the present invention may include a dedicated tablet (100), a cloud server (130), a plurality of work vehicles (140, 150, 160, 170), and an edge device (200).

[0035] The dedicated tablet (100) functions as a user terminal and can process the specification data and driving data of multiple work vehicles (140, 150, 160, 170) into matching data of a single account and transmit it to a cloud server (130) through a dedicated channel. In one embodiment, the dedicated tablet (100) performs user login authentication and can manage multiple work vehicles (140, 150, 160, 170) in an integrated manner based on the authenticated user account.

[0036] The cloud server (130) stores and manages matching data on a per-user account basis and can perform high-computation processing such as path calculation and work log generation. The cloud server (130) analyzes the sensing values ​​received from the edge device (200) to monitor the status of the work vehicle and can send control commands to the edge device (200) if necessary.

[0037] A plurality of work vehicles (140, 150, 160, 170) may include at least one of an autonomous tractor, an autonomous rice transplanter, an autonomous combine harvester, an autonomous planter, and an autonomous boom sprayer. Each work vehicle (140, 150, 160, 170) is equipped with an autonomous driving terminal (140T, 150T, 160T, 170T) to perform autonomous driving control and sensor interface functions.

[0038] An edge device (not shown) according to the present invention is a core device that implements cloud edge computing by being located between a work vehicle (140, 150, 160, 170) and a cloud server (130). The edge device (200) receives sensing values ​​from the work vehicle (140, 150, 160, 170), classifies them by importance based on variable priority, and then allocates bandwidth according to the classified importance to transmit them to the cloud server (130). A detailed description of the functions of the edge device according to the present invention will be provided later through FIGS. 2 to 7.

[0039] FIG. 2 is a conceptual diagram showing the connection relationship between a work vehicle, an edge device, and a cloud server according to one embodiment of the present invention.

[0040] Below, the explanation will be made with reference to Fig. 1.

[0041] The edge unit (20) can implement the method according to the present invention while communicating with the cloud server (130). The edge unit (20) may include an autonomous tractor (140) and an edge device (200). As shown in FIG. 2, the edge device (200) is installed adjacent to a work vehicle such as an autonomous tractor (140). In the present invention, since the image generated from the camera of the work vehicle is transmitted to the edge device (200) via an AHD transmission method, the edge device (200) may be installed by being attached to or mounted on the work vehicle, or placed in an adjacent area, taking into account the realistic length of the existing coaxial cable.

[0042] Referring to FIG. 2, a plurality of sensors may be attached to the autonomous tractor (140). The plurality of sensors may include a GNSS module, a camera, an impact detection sensor, a LiDAR, and an IMU. The GNSS module generates high-precision position information, the camera generates image data, and the impact detection sensor can detect an impact applied to the autonomous tractor (140) and generate an impact amount and a rollover risk signal. Additionally, the LiDAR generates results of generating 3D spatial recognition data, and the IMU can generate attitude, acceleration, and angular velocity information of the autonomous tractor (140). Although only an autonomous tractor (140) is shown in FIG. 2 for convenience of explanation, it will be obvious to a person skilled in the art that the edge device (200) according to the present invention, as shown in FIG. 1, is compatible not only with the autonomous tractor (140) but also with work vehicles such as an autonomous rice transplanter (150), an autonomous planter (not shown), an autonomous combine (160), and an autonomous boom sprayer (170).

[0043] Sensing values ​​generated from multiple sensors can be transmitted to an edge device (200) through different channels depending on the type of sensor. Here, the different channels may include a CAN communication-based channel, an RS232-based channel, and a channel for transmitting AHD video. For example, in-vehicle sensors such as an impact detection sensor, an IMU, and a LiDAR can transmit sensing values ​​through a CAN communication-based channel, a GNSS module can transmit sensing values ​​through an RS232-based channel, and a camera can transmit video data through a channel for transmitting AHD video.

[0044] In this way, the edge device (200) according to the present invention provides a transmission path optimized for the data characteristics of each sensor attached / installed to the work vehicle, thereby enabling efficient data transmission suitable for the characteristics of each sensor, such as bandwidth, real-time performance, and data size.

[0045] FIG. 3 is a block diagram showing the internal configuration of an edge device according to one embodiment of the present invention.

[0046] Referring to FIG. 3, the edge device (200) may include a communication unit (210), a processor (230), and a memory (250).

[0047] The communication unit (210) implements various wired / wireless communications such as WiFi, Bluetooth, LAN, LTE / 5G, and satellite communication, and can communicate with work vehicles (140, 150, 160, 170) and a cloud server (130) through a dedicated channel. The communication unit (210) can perform the function of receiving sensing values ​​from multiple sensors through different channels and transmitting classified sensing values ​​to the cloud server (130).

[0048] The processor (230) can perform core operations such as receiving, classifying, transmitting, and deleting sensing values ​​by executing a program stored in memory (250). The processor (230) can classify sensing values ​​by importance based on variable priority and allocate bandwidth according to the classified importance to transmit to the cloud server (130).

[0049] The memory (250) can perform the function of temporarily storing sensing values ​​and storing programs. The memory (250) can be implemented in various forms such as RAM, ROM, SSD, flash memory, etc.

[0050] FIG. 4 is a block diagram showing the detailed configuration of a processor of an edge device according to one embodiment of the present invention.

[0051] Referring to FIG. 4, the processor (230) may include a first processing unit (231), a second processing unit (233), a third processing unit (235), a fourth processing unit (237), and a fifth processing unit (239).

[0052] The first processing unit (231) can perform the function of receiving sensing values ​​from a plurality of sensors through different channels. The first processing unit (231) can receive sensing values ​​from each sensor through a CAN communication-based channel, an RS232-based channel, and a channel for AHD video transmission.

[0053] The second processing unit (233) can perform the function of classifying sensing values ​​by importance based on variable priority.

[0054] In one embodiment, the second processing unit (233) can automatically classify sensing values ​​by utilizing an AI model. Here, the AI ​​model is based on deep learning technology and can be optimized to run on the limited resources of the edge device (200) through model compression technology (quantization, pruning, etc.). Additionally, according to the embodiment, the AI ​​model may be capable of real-time deep learning inference by utilizing hardware accelerators such as GPUs, TPUs, and VPUs.

[0055] The second processing unit (233) can classify the sensing values ​​according to their importance grade. The second processing unit (233) can use variable priority as a classification criterion for classifying the sensing values ​​according to their importance grade. Variable priority is data pre-set in the second processing unit (233), and when sensing values ​​are collected from multiple types of sensors installed on the work vehicle, each sensing value can be assigned an importance grade according to the variable priority. For example, rollover detection signals, collision warnings, engine overheating alarms, and emergency stop signals identified through the work vehicle's sensing values ​​can be classified as High (Urgent) grade according to the variable priority. As another example, work area data, fertilizer / pesticide application amount, harvest yield data, or the work vehicle's sensing values ​​required to calculate such data can be classified as Medium (Important) grade. Other sensing values, such as real-time CCTV footage generated by cameras, general driving logs, and weather sensor data, may be classified as Low (General) grade based on variable priority.

[0056] Here, the variable priority has the characteristic that the priority can change when a predetermined variable condition is established. For example, a low-resolution image generated by the camera of a work vehicle under normal circumstances is a sensing value classified as Low grade, but if the work vehicle collides with a rock while driving and the collision detection sensor detects an impact amount exceeding a predetermined impact threshold, it is considered that a variable condition has been established, and the image generated by the camera of the work vehicle can become a sensing value classified as High grade. At this time, the image classified as High grade may be a high-resolution image, unlike under normal circumstances, and this process will be described later in Fig. 7.

[0057] The third processing unit (235) can perform the function of transmitting sensing values ​​to the cloud server (130) by allocating bandwidth according to classified importance. As an example, the third processing unit (235) can logically implement an intelligent priority queue by allocating a wider bandwidth to a channel transmitting high-importance sensing values, a medium bandwidth to a channel transmitting medium-importance sensing values, and a relatively narrowest bandwidth to a channel transmitting low-importance sensing values, so that when the communication quality between the edge device (200) and the cloud server (130) deteriorates, only the sensing values ​​corresponding to the widest bandwidth can be transmitted to the cloud server (130) with higher priority than other sensing values. Meanwhile, the third processing unit (235) transmits all importance data (all sensing values) when the communication status is good.

[0058] The fourth processing unit (237) can perform the function of determining the communication quality status with the cloud server (130) in real time. The fourth processing unit (237) can determine whether the communication quality status between the edge device (200) and the cloud server (130) is good or bad in various ways. At this time, the fourth processing unit (237) stores reference information in advance for determining the good or bad state of the communication quality status.

[0059] For example, the fourth processing unit (237) can determine the state of communication quality by analyzing network performance indicators. The fourth processing unit (237) can send a test packet to the cloud server (130) to check the response and measure the latency, and if the latency increases rapidly, it can determine that the state of communication quality is poor. In addition, the fourth processing unit (237) can calculate the packet loss rate and determine that the state of communication quality is poor if the packet loss rate exceeds a certain value, and can determine how inconsistent and irregular the response speed of the packet is through jitter.

[0060] As another example, the fourth processing unit (237) may determine the communication quality status by monitoring the radio link quality. The fourth processing unit (237) calculates the RSSI (Received Signal Strength Indicator), SNR (Signal-to-Noise Ratio), and RSRQ (Reference Signal Received Quality), and determines the communication quality status by determining how much each calculated value differs from a preset value.

[0061] In addition, the fourth processing unit (237) may determine whether the current state is within the normal range by calculating the average of the communication speeds over the past 10 minutes, or predict in advance that communication will be cut off or significantly slowed down in a short time based on the current GPS location of the work vehicle (e.g., the entrance to a mountain valley which is a communication dead zone).

[0062] The fifth processing unit (239) can perform the function of sequentially deleting the sensing values ​​with lower importance among the various sensing values ​​stored in the memory of the edge device (200) when communication quality deteriorates or memory capacity is exceeded. Unlike the existing FIFO method, the fifth processing unit (239) can determine the sensing values ​​to be deleted by calculating the priority and the data generation time (Age) in combination.

[0063] In one embodiment, the memory (250) may be logically divided by the fifth processing unit (239) into a deleteable area (first area) and a non-deletable area (second area). The most important sensing values ​​may be stored in the second area and maintained in a preserved state. For example, an engine warning message generated one hour ago may not be deleted considering its high importance and the time of creation, while a general image generated two hours ago may be deleted considering its low importance and the fact that it was created a long time ago. The process of deleting sensing values ​​by the fifth processing unit (239) will be described later with reference to FIG. 6.

[0064] As an optional embodiment, the fifth processing unit (239) may generate a control command that causes the second area corresponding to the logical area of ​​the memory to gradually increase when the communication disconnection state persists. Additionally, according to another embodiment of the present invention, the edge device (200) may receive a control command from the dedicated tablet (100). Accordingly, in addition to the sensing value, data from the dedicated tablet (100) may be received and processed.

[0065] FIG. 5 is a flowchart illustrating a method for transmitting work vehicle sensing values ​​based on an edge device according to an embodiment of the present invention.

[0066] Referring to FIG. 5, an edge device-based work vehicle sensing value transmission processing method according to one embodiment of the present invention may include a sensing value reception step (S510), a classification step by importance (S520), and a transmission step (S530).

[0067] In the sensing value reception step (S510), the edge device (200) can receive sensing values ​​from a work vehicle (140, 150, 160, 170) equipped with a plurality of sensors through different channels depending on the type of sensor. The different channels may include a CAN communication-based channel, an RS232-based channel, and a channel for AHD video transmission.

[0068] In the classification step by importance (S520), the edge device (200) can classify the sensing values ​​by importance based on a variable priority that can change when a variable condition is established. When a variable condition is established, the priority of the corresponding sensing value can change dynamically.

[0069] In the transmission step (S530), the edge device (200) can transmit the sensing values ​​to the cloud server (130) by allocating bandwidth according to the classified importance. Sensing values ​​with higher importance may be allocated a wider bandwidth and transmitted preferentially.

[0070] FIG. 6 is a flowchart showing the operation flow of an intelligent deletion policy according to one embodiment of the present invention.

[0071] Referring to FIG. 6, the intelligent deletion policy may include a memory storage step (S610), a communication quality detection step (S620), a memory capacity check step (S630), and a sequential deletion step (S640).

[0072] In the memory storage step (S610), the edge device (200) can store the received sensing value in the memory (250).

[0073] In the communication quality detection step (S620), the edge device (200) can determine the communication quality status with the cloud server (130). If the communication quality status is above a threshold value, the sensing value can be transmitted normally.

[0074] In the memory capacity check step (S630), the edge device (200) can check whether the usage of memory (250) exceeds the reference storage when the communication quality state is below a threshold. If the usage of memory (250) does not exceed the reference storage, the sensing value can be stored and maintained.

[0075] In the sequential deletion step (S640), if the communication quality status of the edge device (200) is below a threshold and the usage of the memory (250) exceeds the reference storage, the edge device (200) may sequentially delete the sensing values ​​starting from the group with the lowest classified importance. When deleting the sensing values, the edge device (200) may determine the targets for deletion by considering both the importance and the time of generation of the sensing values. If the usage of the memory (250) becomes less than the reference storage due to the deletion of the sensing values, the edge device (200) may stop the deletion process until the usage of the memory (250) exceeds the reference storage again.

[0076] FIG. 7 is a flowchart illustrating an event-based image resolution dynamic switching method according to an embodiment of the present invention.

[0077] Referring to FIG. 7, the event-based dynamic image resolution switching method may include a low-resolution image reception step (S710), an event occurrence determination step (S720), a resolution up command transmission step (S730), and a high-resolution image reception step (S740).

[0078] In the low-resolution video reception step (S710), the edge device (200) can normally receive low-resolution (Low Quality) video. The low-resolution video can be transmitted to the cloud server (130) by allocating a first bandwidth according to the first importance. Through this, bandwidth can be saved.

[0079] In the event occurrence determination step (S720), the edge device (200) can determine whether an event has occurred on the work vehicle (140, 150, 160, 170). For example, if an impact amount exceeding a reference impact value is detected by an impact detection sensor, it can be determined that an event has occurred.

[0080] In the resolution up command transmission step (S730), if an event occurs, the edge device (200) considers that a variable condition has been established and can generate and transmit a control command to the camera to increase the resolution of the image generated by the camera. The camera installed on the work vehicle can generate a high-resolution image for a predetermined period of time based on the control command received from the edge device (200).

[0081] In the high-resolution video reception step (S740), the edge device (200) can receive high-resolution (High Quality) video. The high-resolution video can be transmitted to the cloud server (130) by allocating a second bandwidth wider than the first bandwidth according to the second importance.

[0082] In this way, according to the edge device (200) of the present invention, in normal circumstances, low-quality video is transmitted to save bandwidth, and when an impact or accident is detected, the resolution of the video is immediately switched to high quality to secure evidence video for analyzing the cause of the accident.

[0083] Various embodiments according to one embodiment of the present invention are described below.

[0084] In one embodiment, the edge device (200) receives sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifies the sensing values ​​by importance based on a variable priority that can change when a variable condition is established, and allocates bandwidth according to the classified importance of the sensing values ​​and transmits them to a cloud server.

[0085] In one embodiment, in the step of classifying by importance, the edge device (200) can classify the sensing values ​​by importance using an AI model that has learned variable priority.

[0086] In one embodiment, a plurality of sensors may include a GNSS module, a camera, an impact detection sensor, LiDAR, and an IMU.

[0087] In one embodiment, different channels formed between the edge device (200) and the work vehicle may include a CAN communication-based channel, an RS232-based channel, and a channel for AHD video transmission.

[0088] In one embodiment, during the process of implementing the step of classifying by importance, if an impact amount exceeding a reference impact value is detected by an impact detection sensor included in the work vehicle, the edge device (200) may consider that a variable condition has been established and may generate and transmit a control command to the camera to increase the resolution of the image generated by the camera of the work vehicle.

[0089] In one embodiment, the edge device (200) determines the communication quality status with the cloud server (130), and if the communication quality status is below a threshold and the memory usage exceeds the reference storage device, it can sequentially delete the sensing values ​​from the memory (250), starting from the group with the lowest importance classified.

[0090] In one embodiment, the work vehicle may be one of an autonomous tractor, an autonomous rice transplanter, an autonomous planter, an autonomous combine, or an autonomous boom sprayer.

[0091] According to the present invention, even in harsh environments where communication bandwidth is extremely narrow, it is ensured that emergency data directly related to life and safety is transmitted with the highest priority without being pushed aside by large volumes of general data.

[0092] In addition, according to the present invention, the loss of core data can be prevented by determining the value of data when communication is interrupted and selectively deleting data of low importance first.

[0093] Furthermore, according to the present invention, an autonomous management system can be implemented that independently recognizes the situation of a work vehicle and dynamically resets data importance.

[0094] In addition, according to the present invention, when an event occurs in a work vehicle, the resolution of the video can be dynamically switched to secure evidence video for analyzing the cause of the accident.

[0095] The embodiments according to the present invention described above may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded on a computer-readable medium. In this case, the medium may include a magnetic medium such as a hard disk, a floppy disk, and a magnetic tape, an optical recording medium such as a CD-ROM and a DVD, a magneto-optical medium such as a floptical disk, and a hardware device specifically configured to store and execute program instructions, such as a ROM, RAM, or flash memory.

[0096] Meanwhile, the above-mentioned computer program may be one specifically designed and configured for the present invention, or one known and available to those skilled in the art of computer software. Examples of computer programs may include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0097] The specific embodiments described in this invention are examples and do not limit the scope of the invention in any way. For the sake of brevity of the specification, descriptions of prior electronic configurations, control systems, software, and other functional aspects of said systems may be omitted. Additionally, the connections of lines or connecting members between components shown in the drawings are illustrative of functional connections and / or physical or circuit connections, and may be replaced or additionally represented as various functional connections, physical connections, or circuit connections in actual devices. Furthermore, unless specifically stated as “essential,” “importantly,” etc., a component may not be strictly necessary for the application of the invention.

[0098] In the specification of the present invention (particularly in the claims), the use of the term “above” and similar descriptive terms may be in both singular and plural. Furthermore, where a range is described in the present invention, it is to include the invention to which individual values ​​belonging to said range are applied (unless otherwise stated), and is equivalent to describing each individual value constituting said range in the detailed description of the invention. Finally, regarding the steps constituting the method according to the present invention, unless explicitly stated in order or otherwise stated, said steps may be performed in a suitable order. The present invention is not necessarily limited by the order in which said steps are described. The use of all examples or exemplary terms (e.g., etc.) in the present invention is merely for the purpose of describing the present invention in detail, and the scope of the present invention is not limited by said examples or exemplary terms unless limited by the claims. Furthermore, those skilled in the art will understand that various modifications, combinations, and changes may be made according to design conditions and factors within the scope of the claims or equivalents to which they are added. Explanation of the symbols

[0099] 200: Edge device 210: Communications Department 230: Processor 250: Memory

Claims

Claim 1 delete Claim 2 delete Claim 3 delete Claim 4 A method for processing the transmission of sensing values ​​from an edge device-based work vehicle, comprising: receiving sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with multiple sensors; classifying the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established; and allocating bandwidth according to the classified importance of the sensing values ​​and transmitting them to a cloud server, wherein the different channels include a CAN communication-based channel, an RS232-based channel, and a channel for transmitting AHD video. Claim 5 A method for processing the transmission of sensing values ​​from an edge device-based work vehicle, comprising: receiving sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with multiple sensors; classifying the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established; and allocating bandwidth according to the classified importance of the sensing values ​​and transmitting them to a cloud server, wherein the step of classifying by importance includes, when an impact amount exceeding a reference impact value is detected by an impact detection sensor included in the work vehicle, considering that the variable condition is established, generating a control command to increase the resolution of an image generated by the camera of the work vehicle, and transmitting it to the camera. Claim 6 A method for processing the transmission of sensing values ​​from an edge device-based work vehicle, comprising: receiving sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with multiple sensors; classifying the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established; allocating bandwidth according to the classified importance of the sensing values ​​and transmitting them to a cloud server; determining the communication quality status with the cloud server; and, if the communication quality status is below a threshold and the memory usage exceeds a reference storage device, sequentially deleting the sensing values ​​from the memory starting from the group with the lowest classified importance. Claim 7 A method for processing the transmission of sensing values ​​from an edge device-based work vehicle, comprising: receiving sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with multiple sensors; classifying the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established; and allocating bandwidth according to the classified importance of the sensing values ​​and transmitting them to a cloud server, wherein the work vehicle is one of an autonomous tractor, an autonomous rice transplanter, an autonomous planter, an autonomous combine, or an autonomous boom sprayer. Claim 8 A computer-readable, non-transient recording medium storing a program for executing a method according to any one of paragraphs 4 through 7. Claim 9 delete Claim 10 delete Claim 11 delete Claim 12 An edge device implementing a method for processing work vehicle sensing values ​​transmission, comprising: a memory in which at least one program is stored; and a processor that performs operations by executing the at least one program, wherein the processor receives sensing values ​​from a work vehicle equipped with a plurality of sensors through different channels according to the type of sensor, classifies the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established, allocates bandwidth according to the classified importance of the sensing values, and transmits them to a cloud server, wherein the different channels include a CAN communication-based channel, an RS232-based channel, and a channel for transmitting AHD video. Claim 13 An edge device implementing a method for processing the transmission of work vehicle sensing values, comprising: a memory in which at least one program is stored; and a processor that performs operations by executing the at least one program, wherein the processor receives sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifies the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established, allocates bandwidth according to the classified importance of the sensing values, and transmits them to a cloud server, wherein if an impact amount exceeding a reference impact value is detected by an impact detection sensor included in the work vehicle, the processor considers that the variable condition is established, generates a control command to increase the resolution of an image generated by the camera of the work vehicle, and transmits it to the camera. Claim 14 An edge device implementing a method for processing work vehicle sensor values ​​transmission, comprising: a memory in which at least one program is stored; and a processor that performs operations by executing the at least one program, wherein the processor receives sensor values ​​through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifies the sensor values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established, allocates bandwidth according to the classified importance of the sensor values ​​and transmits them to a cloud server, and determines the communication quality status with the cloud server, and if the communication quality status is below a threshold and the memory usage exceeds a reference storage device, sequentially deletes the sensor values ​​from the memory starting from the group with the lowest classified importance. Claim 15 An edge device implementing a method for transmitting work vehicle sensing values, comprising: a memory in which at least one program is stored; and a processor that performs operations by executing the at least one program, wherein the processor receives sensing values ​​through different channels according to the type of sensor from a work vehicle equipped with a plurality of sensors, classifies the sensing values ​​by importance based on a variable priority in which the priority can be changed when a variable condition is established, allocates bandwidth according to the classified importance of the sensing values, and transmits them to a cloud server, wherein the work vehicle is one of an autonomous tractor, an autonomous rice transplanter, an autonomous planter, an autonomous combine, or an autonomous boom sprayer.

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