KR20240045191A - Agricultural Product Production and Distribution Management Method based on Block-Chain and Agricultural Product Production and Distribution Management System based on Block-Chain - Google Patents

Abstract

The present invention relates to a blockchain-based agricultural product production and distribution management method and a blockchain-based agricultural product production and distribution management system. According to the present invention, each terminal and server are composed of nodes in a blockchain network, and the system performs calculations accordingly. Since it is impossible to falsify or falsify growth information, distribution information, contract history, etc., it is possible to establish a management system for domestically produced agricultural products.

Description

Blockchain-based agricultural product production and distribution management method, and blockchain-based agricultural product production and distribution management system {Agricultural Product Production and Distribution Management Method based on Block-Chain and Agricultural Product Production and Distribution Management System based on Block-Chain}

The present invention relates to a blockchain-based agricultural product production and distribution management method and a blockchain-based agricultural product production and distribution management system.

Agricultural products are a general term for plants cultivated in fields and their by-products.

Unlike industrial products, the quality of agricultural products is greatly affected by the surrounding environment, such as the cultivation environment, sowing date, climatic conditions, and harvest time. Therefore, even among the same type of agricultural product, there are many differences in quality and nutrition.

Meanwhile, although agricultural products were of excellent quality at the time of harvest, many problems occur during distribution to consumers, including incorrect storage and deterioration during delivery.

Recently, as living standards have improved and interest in health and the environment has increased, interest in the quality of agricultural products and the distribution process has increased.

To ensure safe food, a food traceability management system has been introduced and operated at the national level. However, due to a lack of research on information of high interest to consumers, such as production stage information and distribution stage information, the public's heightened expectations for food safety have not been met. It is not responding.

In addition, the information on the production stage and distribution stage mentioned above is often forged or altered, so the reliability of the history itself displayed on the food is also not high.

Additionally, currently, in order for consumers to purchase agricultural products, unless they visit the production site directly and purchase directly from the producer, it is common to purchase them through an intermediate distributor. However, since consumer prices reflect not only agricultural product production costs but also distribution costs, not only was the burden on consumers large, but actual agricultural product producers did not receive much benefit.

In order to establish a safe food system, many technologies have been researched and developed, but the relevant information in the system is not highly reliable against forgery and falsification. There was a downside.

Korean Patent Document No. 10-1871468 (2018.06.26) Korean Patent Publication No. 10-2020-0001812 (2020.01.07) Korean Patent Document No. 10-2039351 (2019.11.01) Korean Patent Publication No. 10-2020-0021900 (2020.03.02)

The present invention was created to solve the above problems.

Specifically, each terminal and server are composed of nodes in the blockchain network, and as a result, the growth information, distribution information, contract history, etc. calculated in the system are distributed and stored in each node, so forgery and falsification of information is impossible, making traceability difficult. The purpose is to provide a system and method that enables the construction of a system that can be used quickly and even by the elderly.

In addition, the aim is to provide a system and method that can provide highly reliable information by calculating growth information of agricultural products using various production history data and calculating distribution information in distribution means using various distribution history data. It has a purpose.

In addition, the purpose is to provide a system and method that can calculate the growth information of agricultural products and distribution information in distribution means with high accuracy using a machine learning model, thereby providing highly reliable information.

In addition, the purpose is to provide a system and method that enables direct contracts between producers and buyers without going through a distributor, allowing both producers and buyers to obtain economic benefits.

In addition, the purpose is to provide a system and method that makes it possible to establish a management system for domestically produced agricultural products by making the production and distribution processes transparent.

One embodiment of the present invention for solving the above problems includes a production terminal 110 that receives first production history data including one or more of the crop identifier of the agricultural product, the crop sowing location, the number of hairs, and the genetic marker, and A production node 100 including a production site sensor unit 120 that is installed at the production site where the agricultural products are produced and collects second production history data, and is mounted on a distribution means for distributing agricultural products produced at the production site and distributed. A distribution node 200 including a distribution terminal 210 that receives first distribution history data including a crop identifier and a distribution sensor unit 220 installed in the distribution means to collect second distribution history data, The production node 100 and the distribution node 200 are communicated with each other through a blockchain communication network, calculate growth information of the agricultural product using the first production history data and the second production history data, and calculate the growth information of the agricultural product using the first production history data and the second production history data. 1 Management node 300 that calculates distribution information in the distribution means using distribution history data and the second distribution history data, maximum temperature suitable for growth, minimum temperature suitable for growth, maximum humidity suitable for growth, and optimum growth temperature for each crop identifier. Standard production history data including minimum humidity, solar radiation, soil temperature, soil EC (electrical conductivity), and soil moisture are stored in one-to-one matching, and standard distribution history data including distribution process temperature and distribution process humidity for each crop identifier is one-to-one. A purchase terminal (400) that is connected to a matching and stored database (370) and the management node (300) through the blockchain communication network, and outputs the growth information and distribution information calculated by the management node (300). ), wherein sales contract data including the crop identifier and sales price of the agricultural product to be sold through the production terminal 110 are input, and the purchase node is input. Purchase contract data including the crop identifier and purchase price of the agricultural product to be purchased is input through the terminal 400, and the method includes (a) the temperature, humidity, and Collecting the second production history data including production site location, solar radiation, soil temperature, soil electrical conductivity, soil moisture, and measurement date and time; (b) The distribution site sensor unit 220 collects the second distribution history data including temperature, humidity, movement time, movement path, and movement location in the distribution means loaded with agricultural products produced in the production area. step; (c) The management node 300 compares reference production history data matching the crop identifier included in the first production history data with the first production history data and the second production history data, and provides the comparison result. calculating growth information of the agricultural product based on it; (d) The management node 300 compares standard distribution history data matching the crop identifier included in the first distribution history data with the first distribution history data and the second distribution history data, and based on the comparison result. calculating distribution information of the agricultural product; (e) when the sales contract data matches the purchase contract data, a contract is established, and the management node 300 generates a history of the established contract; And (f) when a contract history is created in step (e), transmitting the growth information and the distribution information to the purchase terminal 400 where the purchase contract data is input; including, production and distribution of agricultural products. Provides management methods.

In one embodiment, in step (c), the management node 300 determines the temperature, the humidity, the location of the production site, the amount of solar radiation, the soil temperature, the soil electrical conductivity, the soil moisture, and the crop identifier. , Production history data including one or more of the crop sowing location, the number of stands, and the genetic marker, and the growth information score predetermined according to the production history data as learning data, the first production in a machine learning model learned. It may further include inputting the history data and the second production history data to calculate the output growth information score.

In one embodiment, in step (d), the management node 300 includes one or more of the temperature, the humidity, the movement time, the movement path, and the movement location in the distribution means. By inputting the first distribution history data and the second distribution history data into a machine learning model learned using history data, the crop identifier, and the distribution history data and the distribution information score predetermined according to the crop identifier as learning data, A step of calculating the output distribution information score may be further included.

In one embodiment, in step (e), the management node 300 barcodes the growth information calculated in step (c) and the distribution information calculated in step (d) into a barcode. Step; further comprising, when the barcode is scanned by the purchase terminal 400, the growth information and the distribution information may be output to the purchase terminal 400.

In one embodiment, distribution contract data including the crop identifier and purchase price of the agricultural product to be distributed is further input through the distribution terminal 210, and in step (e), the sales contract data and the distribution If the contract data is matched, a contract is established, and the management node 300 further includes the step of generating a history of the established contract, wherein step (f) is performed when the contract history is generated in step (e). In this case, the step of transmitting the growth information and the distribution information to the distribution terminal 210 into which the distribution contract data is input may be further included.

In one embodiment, the production node 100 further includes an agricultural machine sensor unit 130 that is installed on an agricultural machine for producing the agricultural product and collects the working position of the agricultural machine, and the production terminal 110. Through this, agricultural machine control data further including one or more of machine information and work information of the agricultural machine are input, and the method includes the management node 300, the work location collected from the agricultural machine sensor unit 130, and , using the machine information and the work information to calculate agricultural machine control information including a seeding path, a harvest path, a harvest amount, and energy efficiency and operation rate of the agricultural machine.

In one embodiment, the production history data includes producer identifier, producer name, producer address, producer phone number, cultivation area, harvest time, harvest area, harvest amount, shipment date, shipper phone number, business phone number, seller identifier, It further includes production location distribution metadata including seller name, seller phone number, shipment amount, traceability management number, authentication number, and inventory storage amount, and the distribution history data includes logistics organization identifier, logistics organization name, logistics organization address, and logistics. Logistics meta further includes organization phone number, import date, consignment destination identifier, consignment destination name, consignment destination phone number, import quantity, delivery date, delivery destination identifier, delivery destination name, delivery destination phone number, delivery volume, logistics pattern, and inventory storage amount. Additional data may be included.

In one embodiment, the growth information, distribution information, and generated contract history calculated in the management node 300 are distributed to the production node 100, the distribution node 200, the management node 300, and It can be distributed and stored in the purchase node.

Additionally, the present invention provides an agricultural product production and distribution management system for performing the above-described agricultural product production and distribution management method.

Additionally, the present invention provides a program stored in a computer-readable recording medium to execute the above-described agricultural product production and distribution management method.

According to the present invention described above, the following effects are achieved.

Each terminal and server are composed of nodes in the blockchain network, and as a result, the growth information, distribution information, and contract history calculated in the system are distributed and stored in each node, making it impossible to forge or falsify the information, thereby managing domestically produced agricultural products. It is possible for a system to be built.

In addition, by calculating the growth information of agricultural products using various production history data and calculating distribution information in distribution means using various distribution history data, it is possible to provide highly reliable information.

In addition, using a machine learning model, growth information of agricultural products and distribution information from distribution means can be calculated with high accuracy, making it possible to provide highly reliable information.

In addition, direct contracts between producers and buyers are possible without going through a distributor, making it possible for both producers and buyers to obtain economic benefits.

Additionally, the production and distribution processes become transparent, making it possible to establish a management system for domestically produced agricultural products.

Figure 1 is a schematic block diagram to explain a blockchain-based agricultural product production and distribution management system according to an embodiment of the present invention.
Figure 2 is a flowchart illustrating a blockchain-based agricultural product production and distribution management method according to an embodiment of the present invention.
Figure 3 is a flowchart illustrating a blockchain-based agricultural product production and distribution management method according to another embodiment of the present invention.
Figure 4 is a diagram to explain production history data, distribution history data, and contract history data distributed and stored in each node through a blockchain communication network in the system of Figure 1.
Figures 5 and 6 are schematic block diagrams to explain in more detail the process performed in the system of Figure 1.
Figure 7 is a diagram showing the two-dimensional barcode of growth information and distribution information and the information output when the barcode is scanned at the purchase terminal.
FIG. 8 is a diagram for explaining information included in the barcode of FIG. 7.
Figure 9 is a diagram to explain how a contract between a producer and a buyer is established in the system of Figure 1, and Figure 10 is a diagram to explain how a contract is established between a producer and a distributor in the system of Figure 1.
FIG. 11 is a diagram for explaining agricultural machinery control information calculated in the system of FIG. 1.
Figure 12 is a diagram for explaining growth information calculated based on production history data in the system of Figure 1.
13 to 19 are diagrams for explaining the system according to the present invention implemented as a program and the execution screen of the implemented program.
Figure 20 is a diagram explaining the process of assembling the production site sensor unit applied to the system according to the present invention.
Figure 21 is a diagram showing the process of collecting production history data by installing the production site sensor unit assembled in Figure 20 on actual soil.
Figure 22 is a diagram for explaining the principle of measuring location information of the sensor unit by the GPS module in the present invention.

In some cases, in order to avoid ambiguity of the concept of the present invention, well-known structures and devices may be omitted or may be shown in block diagram form focusing on the core functions of each structure and device.

Throughout the specification, when a part is said to “comprise or include” a certain element, this means that it does not exclude other elements but may further include other elements, unless specifically stated to the contrary. do. In addition, terms such as "... unit", "... unit", and "module" used in the specification refer to a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software. there is. In addition, the terms "a or an", "one", "the", and similar related terms are used in the context of describing the invention (particularly in the context of the claims below) as used herein. It may be used in both singular and plural terms, unless indicated otherwise or clearly contradicted by context.

In describing embodiments of the present invention, if a detailed description of a known function or configuration is judged to unnecessarily obscure the gist of the present invention, the detailed description will be omitted. The terms described below are terms defined in consideration of functions in the embodiments of the present invention, and may vary depending on the intention or custom of the user or operator. Therefore, the definition should be made based on the contents throughout this specification.

1. Blockchain-based agricultural product production and distribution management system

Hereinafter, the present invention will be described in detail with reference to the attached drawings.

The agricultural product production and distribution management system according to an embodiment of the present invention may include a production node, a distribution node, a management node, and a purchasing node, and each node communicates with each other through a communication network, more specifically, a blockchain communication network 10. connected.

In the case of blockchain, rather than storing and managing data on a centralized server, individual servers participating in transactions gather to maintain and manage the network. These individual servers are called nodes.

In other words, in the agricultural product production and distribution management system according to the embodiment of the present invention, the production node, management node, distribution node, and purchasing node maintain and manage the blockchain network, and the information calculated at each node and the establishment between each node As the contract history, etc. are distributed and stored in each node that communicates with each other through the blockchain communication network, the problem of each information being forged or altered is prevented.

First, the production node will be described in detail.

The production node side is equipped with a production terminal 110, a production site sensor unit 120, and an agricultural machinery sensor unit 130.

The production terminal 110 is a terminal carried by the agricultural product producer or provided at the production site where the agricultural product is produced, and the producer can access the agricultural product distribution and management program through the production terminal 110. The form of the production terminal 110 may be a mobile device that the user can carry, such as a smartphone or tablet PC, but is not particularly limited thereto.

Production history data related to agricultural product production is input through the production terminal 110. For convenience, the production history data input to the production terminal 110 is referred to as first production history data.

That is, production history data such as crop identifier, crop sowing location, number of seedlings, and genetic marker of the crop of the agricultural product currently being produced are input through the production terminal 110. The production history data input through the production terminal 110 is later used to calculate growth information by the growth information calculation unit 340.

Additionally, sales contract data including the type (crop identifier) of the agricultural product to be sold and the sales price are further entered through the production terminal 110. The sales contract data entered through the production terminal 110 is later used to create a contract history depending on whether it matches the purchase contract data entered through the purchase terminal 400.

The production site sensor unit 120 is installed at the production site where agricultural products are produced and collects production history data at the installed location. For convenience, the production history data collected by the production site sensor unit 120 is referred to as second production history data.

Production history data collected through the production site sensor unit 120 includes temperature of the production site, dew point temperature, humidity, relative humidity, ambient temperature, ambient humidity, location of the production site, solar radiation, soil ground temperature, soil electrical conductivity (EC), soil moisture, and It includes the measurement date and time, and for this purpose, the production site sensor unit 120 includes a temperature sensor, a humidity sensor, a position sensor including a GPS module, a solar radiation measurement sensor, and a soil measurement sensor. The production history data collected by the production site sensor unit 120 is data directly related to the growth of agricultural products, and is later used to calculate growth information by the growth information calculation unit 340.

In order to continuously collect production history data from the production site sensor unit 120, power supply is required. To this end, the production site sensor unit 120 according to the present invention includes a solar panel made of a bendable material, and the solar panel may be configured in the form of a solar cell that generates power by incident sunlight.

That is, the production site sensor unit 120 includes the above-mentioned sensors, a case 121, a battery 122, a communication module 123, and a solar panel 124, and the solar panel 124 is the case 121. It is installed outside and electrically connected to the battery 122 (see Figure 20). Accordingly, the power charged (generated) by the solar panel 124 is supplied to the battery 122, and the battery 122 is configured to supply power to the sensor while moving the production site sensor unit 120. It is possible to sense certain information.

The agricultural machinery sensor unit 130 is installed on agricultural machinery that assists in the production of agricultural products and collects the working location of the installed agricultural machinery. For this purpose, the agricultural machine sensor unit 130 includes a position sensor. Here, agricultural machinery refers to all equipment that assists in the production of agricultural products, and includes cultivators, seeders, harvesters, etc. The agricultural machinery sensor unit 120 also requires power supply in order to continuously collect agricultural machinery control data, and the same bendable solar panel 124 configuration as that of the production site sensor unit 120 can be applied.

In addition, agricultural machine control data including machine information of the agricultural machine to which the agricultural machine sensor unit 130 is attached and operation information of the current agricultural machine (e.g., seeding operation, weeding operation, harvest operation, etc.) are further input through the production terminal 110. do.

The work location collected by the agricultural machine sensor unit 130, the machine information and work information input through the production terminal 110 are later used to calculate agricultural machine control information by the agricultural machine control information calculation unit 360.

The position sensor attached to agricultural machinery includes a GPS module. The GPS module preferably has an error range of less than 10 cm, and more specifically, it is preferably an RTK (Real-Time Kinematic) GPS module.

In other words, it is desirable for the GPS module to output real-time GPS information of agricultural machinery or distribution vehicles equipped with a position sensor in conjunction with a satellite, and it is desirable for the error between the actual location and the GPS information output from the GPS module to be within 10 cm.

In addition, the precision of the position sensor according to the present invention is preferably 10 cm (i.e., within an error range of 10 cm), and the IMU (Inertial Measurement) performance is preferably less than 0.01. Information on the center point of three GNSS RTK RTLS (Global Navigation Satellite System Real-Time Kinematic Real-Time Locating System) satellites, agricultural machinery, and RTK base stations is acquired using each location information, and the heading (heading) of each component is acquired. ) Considering the angle, the signals of each RTLS are collected for a set period of time, then the information of each RTLS collected is selected using the heading information to calculate the average value, and the change in direction information is judged to be greater than the standard value. , the corresponding heading information is not used, but heading information calculated from another RTLS is used (generally, heading information may be distorted due to the influence of magnetic force). In this process, the error can be reduced by applying the Extended Kalman Filter (EKF) to each RTLS and heading information. The final information calculated is the center position coordinates and heading information, and thus the real-time location information, direction and angle of movement of the agricultural machinery. Information can be confirmed (see FIG. 22).

Next, the distribution node will be described in detail.

The distribution node side is provided with a distribution terminal 210 and a distribution sensor unit 220.

The distribution terminal 210 is a terminal carried by an agricultural product distributor or provided at a distribution location where agricultural products are distributed, and the distributor can access the agricultural product distribution and management program through the distribution terminal 210. The form of the distribution terminal 210 may be a mobile device that the user can carry, such as a smartphone or tablet PC, but is not particularly limited thereto.

Distribution history data related to agricultural product distribution is input through the distribution terminal 210. For convenience, the distribution history data input to the distribution terminal 210 is referred to as first distribution history data.

That is, distribution history data (logistics metadata, see FIG. 15) such as the crop identifier of the agricultural product to be distributed, agricultural product input and output information, distribution vehicle information, and delivery information are input through the distribution terminal 210, and the distribution terminal 210 The distribution history data entered through ) is later used to calculate distribution information by the distribution information calculation unit 350.

Distribution contract data including the type (crop identifier), quantity, and purchase price of the agricultural product to be distributed is input through the distribution terminal 210. The distribution contract data entered through the distribution terminal 210 is used to create a contract history depending on whether it matches the sales contract data entered into the production terminal 110.

Additionally, sales contract data including the type (crop identifier) and sales price of the agricultural product to be distributed through the distribution terminal 210 are further input. The sales contract data entered through the distribution terminal 210 is later used to create a contract history depending on whether it matches the purchase contract data entered through the purchase terminal 400.

The distribution location sensor unit 220 is installed in a distribution means for distributing agricultural products and collects distribution history data at the installed location. Here, the means of distribution may include all means of transportation for the distribution of agricultural products, and is a concept that includes vehicles, etc. For convenience, the distribution history data collected by the distribution sensor unit 220 is referred to as second distribution history data.

The distribution site sensor unit 220 is preferably installed in a space where agricultural products are actually stored (for example, an agricultural product storage space in a vehicle).

Distribution history data collected through the distribution sensor unit 220 includes the temperature, humidity, movement time, movement path, and movement location of the distribution means. For this purpose, the distribution sensor unit 220 includes a temperature sensor, a humidity sensor, and a position sensor.

The distribution history data collected by the distribution sensor unit 220 is data directly related to the quality of agricultural products during the distribution process, and is later used to calculate distribution information by the distribution information calculation unit 350.

Next, the management node will be described in detail.

On the management node side, there is a production history data collection unit 310, a distribution history data collection unit 320, an agricultural machinery control data collection unit 330, a growth information calculation unit 340, a distribution information calculation unit 350, and an agricultural machinery control information calculation unit 360. ), a database 370, a barcode generator 380, and a contract history generator 390 are provided.

The production history data collection unit 310 collects production history data collected from the production site sensor unit 120 or input to the production terminal 110, and the distribution history data collection unit 320 collects production history data from the distribution site sensor unit 220. Distribution history data collected or input to the distribution terminal 210 is collected, and the agricultural machinery control data collection unit 330 collects agricultural machinery control data collected by the agricultural machinery sensor unit 130 or input to the production terminal 110.

The database 370 contains standard production history data that is the standard for determining the growth information of agricultural products, standard distribution history data that is the standard in determining the distribution information of agricultural products, and standard control data that is the standard in determining the control information of agricultural machinery. It is saved.

The standard production history data is one-to-one matched for each crop identifier and stored in the database 370, including information on the highest temperature suitable for growth, the lowest temperature suitable for growth, the highest humidity suitable for growth, and the lowest humidity suitable for growth.

The standard distribution history data is the distribution process temperature and distribution process humidity information are matched one-to-one for each crop identifier and stored in the database 370.

The standard control data is stored in the database 370 with energy efficiency and operation rate according to movement route matched one-to-one for each agricultural machinery identifier.

Based on the information stored in the database 370, growth information, distribution information, and agricultural machinery control information are calculated by the growth information calculation unit 340, distribution information calculation unit 350, and agricultural machinery control information calculation unit 360.

The growth information calculation unit 340 collects production history data collected from the production history data collection unit 310 (production history data such as crop identifier entered into the production terminal, crop sowing location, number of seedlings, and genetic markers, and from the production site sensor unit). Growth information of agricultural products using collected production history data such as temperature, dew point temperature, humidity, relative humidity, ambient temperature, ambient humidity, location of production site, solar radiation, soil temperature, soil electrical conductivity, soil moisture, and measurement date) Calculate .

In one embodiment of the present invention, the growth information calculation unit 340 provides growth information for the corresponding agricultural product by comparing the production history data collected in the production history data collection unit 310 with the standard production history data stored in the database 370. is calculated.

For example, if the agricultural product matching the crop identifier included in the production history data is onion, the temperature among the production history data collected by the production history data collection unit 310 is the highest temperature suitable for growth of the onion stored in the database 370. If it is higher or lower than the minimum temperature suitable for growth, the growth information may be calculated as 'bad', but is not particularly limited to this and the growth information may be calculated as a score.

The growth information calculation unit 340 of the present invention does not calculate growth information using only one piece of production history data, but rather uses a plurality of production history data directly related to the growth of agricultural products as the standard production history pre-stored in the database 370. Since growth information is calculated through comparison with data, the accuracy of growth information calculated by the growth information calculation unit 340 is improved.

Additionally, in another embodiment of the present invention, the growth information calculation unit 340 may calculate growth information using a machine learning model learned using production history data and the resulting growth information score as learning data.

*In other words, temperature, dew point temperature, humidity, relative humidity, ambient temperature, ambient humidity, solar radiation, soil temperature, soil electrical conductivity, soil moisture, location of production site (climate varies depending on the location of the production site, and the climate determines the growth of agricultural products) (Directly related to), production history data including one or more of crop identifier, crop sowing location and number of stands, and genetic marker, and a predetermined growth information score accordingly as learning data. A machine learning model will be provided. Growth information can be calculated by inputting production history data input to the production terminal 110 and production history data collected from the production site sensor unit 120 into the machine learning model.

The machine learning models include Deep Neural Network (DNN), Convolutional Neural Network (CNN), Deep Convolutional Neural Network (DCNN), Recurrent Neural Network (RNN), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), and SSD ( It may be an artificial neural network model based on Single Shot Detector, MLP (Multi-layer Perceptron), or Attention Mechanism, but is not particularly limited thereto.

The distribution information calculation unit 350 collects distribution history data collected from the distribution history data collection unit 320 (distribution history data such as crop identifiers of agricultural products entered through the distribution terminal, and the temperature of the distribution means collected from the distribution sensor unit). , distribution history data such as humidity, movement time, movement route, and movement location) are used to calculate distribution information for agricultural products.

In one embodiment of the present invention, the distribution information calculation unit 350 compares the distribution history data collected in the distribution history data collection unit 320 with the standard distribution history data stored in the database 370 to provide distribution information for the corresponding agricultural product. is calculated.

For example, if the agricultural product matching the crop identifier included in the distribution history data is garlic, the humidity among the distribution history data collected by the distribution history data collection unit 320 is higher than the distribution process humidity of garlic stored in the database 370. If it is higher or lower or higher than the distribution process temperature, the distribution information may be calculated as 'bad', but is not particularly limited to this and the distribution information may be calculated as a score.

The distribution information calculation unit 350 of the present invention does not calculate distribution information using only any one distribution history data, but rather uses a plurality of distribution history data directly related to the quality of agricultural products as the standard distribution history pre-stored in the database 370. Since distribution information is calculated through comparison with data, the accuracy of distribution information calculated by the distribution information calculation unit 350 is improved.

Additionally, in another embodiment of the present invention, the distribution information calculation unit 340 may calculate distribution information using a machine learning model learned using distribution history data and the corresponding distribution information score as learning data.

*In other words, the temperature, humidity, and location of the distribution means (climate may vary depending on the location, which may affect the quality of agricultural products loaded on the distribution means), and travel time (the longer the travel time, the worse the quality of agricultural products). may be provided), a machine learning model learned using distribution history data including one or more of the movement paths, and a distribution information score predetermined accordingly as learning data may be provided, and the machine learning model may include a distribution terminal ( Distribution information can be calculated by inputting the distribution history data input into 210) and the distribution history data collected from the distribution sensor unit 220.

The agricultural machinery control information calculation unit 360 collects agricultural machinery control data collected from the agricultural machinery control data collection unit 330 (agricultural machinery control data such as mechanical information of agricultural machinery and operation information of agricultural machinery input through the production terminal, and collected from the agricultural machinery sensor unit). The control information of agricultural machinery is calculated using agricultural machinery control data such as the working location of agricultural machinery.

In one embodiment of the present invention, the agricultural machinery control information calculation unit 360 controls the control of the agricultural machinery by comparing the agricultural machinery control data collected by the agricultural machinery control data collection unit 330 with the standard agricultural machinery control data stored in the database 370. information is calculated.

That is, the agricultural machinery control information calculation unit 360 calculates the energy efficiency of the agricultural machinery and the operation rate according to the movement route by comparing the agricultural machinery control data collected by the agricultural machinery control data collection unit 330 with the standard agricultural machinery control data ( 11), the seeding distance can be calculated using the movement path of the agricultural machinery, and information such as the number of seeds can be further calculated by multiplying the calculated seeding distance by the unit seeding number. In addition, the yield can be calculated based on the calculated number of seeds, and it is also possible to further calculate agricultural machinery control information on the weeding path.

The barcode generator 380 barcodes the growth information calculated by the growth information calculation unit 340 and the distribution information calculated by the distribution information calculation unit 350.

For example, as shown in FIG. 8, the barcode generator 380 can barcode growth information and distribution information into one dimension and generate a two-dimensional barcode by merging them.

The two-dimensional barcode generated by the barcode generator 380 is transmitted to the purchase terminal 400, so that the buyer can check the growth information and distribution information of the agricultural product by scanning the barcode. In another embodiment, The barcode generated by the barcode generator 380 is attached to agricultural product packaging boxes, etc., and it is possible to check growth information and distribution information by scanning the barcode of the purchase terminal 400. The barcode generated by the barcode generator 380 includes genetic markers of agricultural products, and when the barcode is scanned, the name of the variety corresponding to the genetic marker included in the barcode may also be output.

The contract history generation unit 390 generates contract history for established contracts.

In the embodiment of the present invention, the establishment of contract history is largely divided into three types.

First, it is a contract established between the production node and the purchasing node.

The crop identifier of the agricultural product to be sold and the desired sales price are entered into the production terminal 110, and the entered sales contract data is transmitted to the agricultural product distribution and management program. The crop identifier of the agricultural product to be purchased and the purchase amount to be purchased can be entered through the purchase terminal 400, and the entered purchase contract data is also transmitted to the agricultural product distribution and management program. If the sales contract data and the purchase contract data match (here, matching means that the crop identifier in the sales contract data and the crop identifier in the purchase contract data are the same, and the sales price is less than the purchase price), the contract is established. As such, the corresponding contract history is created.

According to this, consumers can purchase agricultural products directly from producers without going through the distribution stage, so they can purchase agricultural products at a lower price, and producers can also sell agricultural products at a higher price than they sell to distributors. It is beneficial to both parties.

Second, it is a contract established between the production node and the distribution node.

The crop identifier of the agricultural product to be sold and the desired sales price are entered into the production terminal 110, and the entered sales contract data is transmitted to the agricultural product distribution and management program. The crop identifier of the agricultural product to be distributed and the purchase price to be purchased can be entered through the distribution terminal 210, and the entered distribution contract data is also transmitted to the agricultural product distribution and management program. If the sales contract data and distribution contract data match (here, matching means that the crop identifier in the sales contract data and the crop identifier in the distribution contract data are the same and the sales price is less than the purchase price), the contract is established. As such, the corresponding contract history is created.

Third, it is a contract established between the distribution node and the purchasing node.

The crop identifier of the agricultural product to be sold and the desired sales price are entered into the distribution terminal 210, and the entered sales contract data is transmitted to the agricultural product distribution and management program. The crop identifier and purchase price of the agricultural product to be purchased can be entered through the purchase terminal 400, and the entered purchase contract data is also transmitted to the agricultural product distribution and management program. If the sales contract data and the purchase contract data match (here, matching means that the crop identifier in the sales contract data and the crop identifier in the purchase contract data are the same, and the sales price is less than the purchase price), the contract is established. As such, the corresponding contract history is created.

Contract histories generated by the contract history generator 390 can be transmitted to each node through the blockchain communication network 10, and each contract history can form one block. In this way, according to an embodiment of the present invention, established contract histories are stored in the form of blocks to prevent forgery and alteration.

The purchase terminal 400 is a terminal carried by the consumer, and the consumer can access the agricultural product distribution and management program through the purchase terminal 400. The form of the purchase terminal 400 may be a mobile device that the user can carry, such as a smartphone or tablet PC, but is not particularly limited thereto.

2. Blockchain-based agricultural product distribution and management method

With reference to FIG. 2, a blockchain-based agricultural product distribution and management method according to an embodiment of the present invention will be described in detail.

Production history data including crop identifier, crop sowing location, number of seedlings, and genetic markers are input through the production terminal 110, and the temperature, humidity, location of production site, solar radiation, and soil temperature of the production site are input from the production site sensor unit 120. , production history data including soil electrical conductivity, soil moisture, and measurement date and time are collected, and the production history data collection unit 310 of the management server 300 collects the production history data.

Next, the growth information calculation unit 340 of the management server 300 calculates the growth information of agricultural products in the above-described manner using the collected production history data, and the calculated growth information is transmitted to the blockchain communication network and each node It is saved in

Sales contract data including the crop identifier of the agricultural product to be sold and the desired sales price are input through the production terminal 110, and the input sales contract data is transmitted to the management server 300, and the purchase terminal 400 Purchase contract data including the crop identifier of the agricultural product to be purchased and the purchase price to be purchased are input, and the input purchase contract data is transmitted to the management server 300.

When the sales contract data and the purchase contract data are matched, a contract is established and the contract history generator 380 generates a contract history for the established contract and transmits it to the blockchain communication network, and the transmitted contract history is also stored in each node. do.

The above purchase contract data may include delivery address information.

It is necessary to deliver agricultural products using distribution methods from the production site to the consumer's residence.

At this time, the distribution sensor unit 220 installed in the distribution means collects the temperature, humidity, and location of the space where agricultural products are stored, and the distribution terminal 210 collects information on arrival and departure of goods requiring delivery, distribution vehicle information, Delivery information is transmitted to the management server 300, and the distribution history data collection unit 320 of the management server 300 collects the distribution history data.

Next, the distribution information calculation unit 350 of the management server 300 calculates the distribution information of agricultural products in the above-described manner using the collected distribution history data, and the calculated distribution information is transmitted to the blockchain communication network and each node It is saved in

From the perspective of a consumer carrying the purchase terminal 400, they can check the growth information of the agricultural product they wish to purchase, conclude a contract for delivery directly from the producer to the delivery location at a low price, and also check the distribution process in real time, providing convenience. This improves. The growth information and distribution information calculated by the management server 300 are transmitted and stored in each node of the blockchain communication network, and since forgery and falsification are impossible, it is possible to implement a safe food system.

With reference to FIG. 3, a blockchain-based agricultural product distribution and management method according to an embodiment of the present invention will be described in detail.

Compared to Figure 2, there is a difference in that the first contract is concluded between the producer and the distributor, and then the contract between the distributor and the consumer is concluded, rather than a direct contract between the producer and the consumer.

*Production history data including crop identifier, crop sowing location, number of stands, and genetic markers are input through the production terminal 110, and the temperature, humidity, location of production site, solar radiation, and soil of the production site are input from the production site sensor unit 120. Production history data including ground temperature, soil electrical conductivity, soil moisture, and measurement date and time are collected, and the production history data collection unit 310 of the management server 300 collects the production history data.

Next, the growth information calculation unit 340 of the management server 300 calculates the growth information of agricultural products in the above-described manner using the collected production history data, and the calculated growth information is transmitted to the blockchain communication network and each node It is saved in

Sales contract data including the crop identifier of the agricultural product to be sold and the desired sales price are input through the production terminal 110, and the input sales contract data is transmitted to the management server 300, and the distribution terminal 210 Distribution contract data including the crop identifier of the agricultural product to be distributed and the purchase price to be purchased are input, and the input distribution contract data is transmitted to the management server 300.

When the sales contract data and distribution contract data match, a contract is established and the contract history generator 380 generates a contract history for the established contract and transmits it to the blockchain communication network, and the transmitted contract history is also stored in each node. do.

The above distribution contract data may include delivery address information.

A delivery process for agricultural products using distribution means is required from the production site to the distributor's distribution site.

At this time, the distribution sensor unit 220 installed in the distribution means collects the temperature, humidity, and location of the space where agricultural products are stored, and the distribution terminal 210 collects information on arrival and departure of goods requiring delivery, distribution vehicle information, Delivery information is transmitted to the management server 300, and the distribution history data collection unit 320 of the management server 300 collects the distribution history data.

Next, the distribution information calculation unit 350 of the management server 300 calculates the distribution information of agricultural products in the above-described manner using the collected distribution history data, and the calculated distribution information is transmitted to the blockchain communication network and each node It is saved in

Next, sales contract data including the crop identifier of the agricultural product to be sold and the desired sales price are input through the distribution terminal 210, and the input sales contract data is transmitted to the management server 300. In addition, purchase contract data including the crop identifier of the agricultural product to be purchased and the purchase price to be purchased are input through the purchase terminal 400, and the entered purchase contract data is transmitted to the management server 300.

The above-mentioned purchase contract data may include delivery address information.

A delivery process for agricultural products using distribution means is required from the distribution point to the buyer's delivery point.

At this time, the distribution sensor unit 220 installed in the distribution means collects the temperature, humidity, and location of the space where agricultural products are stored, and the distribution terminal 210 collects information on arrival and departure of goods requiring delivery, distribution vehicle information, Delivery information is transmitted to the management server 300, and the distribution history data collection unit 320 of the management server 300 collects the distribution history data.

Next, the distribution information calculation unit 350 of the management server 300 calculates the distribution information of agricultural products in the above-described manner using the collected distribution history data, and the calculated distribution information is transmitted to the blockchain communication network and each node It is saved in

3. Description of data

The types of data used in the present invention will be described in detail.

Production history data collected from the production site sensor unit 120 includes crop identifier (plant_id), temperature (temperature), relative humidity (relative_humidity), ambient temperature (ambient_temp), ambient humidity (ambient_humidity), leaf humidity (leaf_humidity), and soil temperature. (soil_temp), soil humidity (soil_humidity), and production history data input to the production terminal 110 includes crop sowing location and number of stands, genetic marker (dna_marker), and crop identifier (plant_id).

The standard production history data stored in the database 370 includes crop identifier (plant_id), scientific name (plant_scientific_name), variety name (cultivar_name), maximum temperature suitable for growth (growing_temp_max), minimum temperature suitable for growth (growing_temp_min), and maximum humidity suitable for growth (growing_RH_max). ), including the minimum humidity suitable for growth (growing_RH_min).

Producer distribution metadata includes producer identifier (producer_id), producer name (producer_name), producer address (producer_address), producer phone number (producer_tel_number), item code (item_code), cultivated area (cultivated_area), harvest time (harvest_time), and harvested area. (harvest_area), harvest amount (harvest_amount), distributed crop identifier (distrib_crop_id), shipping date (shipping_date), shipper number (shipr_regist_no), business number (MNG_REGIST_NO), seller identifier (buyer_id), seller (buyer_name), seller phone number (buyer_tel_number) ), shipment amount (shipping_amount), traceability number (traceability_number), certification number (cetify_cd), and inventory storage amount (inventory_amount).

Logistics metadata includes logistics organization identifier (logistics_org_id), logistics organization name (logistics_org_name), logistics organization address (logistics_org_add), logistics organization phone number (logistics_org_tel_num), distributed crop identifier (distrib_crop_id), incoming date (incoming_date), and consignment destination identifier ( consignment_org_id), consignment name (consignment_org_name), consignment phone number (consignment_org_tel_number), incoming quantity (incoming_amount), delivery date (shipping_date), shipping address identifier (shipping_org_id), shipping address name (shipping_org_name), shipping address phone number (shipping_org_tel_number), delivery Includes quantity (shipping_amount), logistics pattern (logistics_pattern), inventory storage amount (inventory_amount), temperature, relative humidity (relative_humidity), and location information (geolocation).

The blockchain-based agricultural product distribution and management method of the present invention described above can be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and constructed for the present invention or may be known and usable by those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to carry out the operations of the present invention, and vice versa.

According to the present invention described above, the following effects are achieved.

Each terminal and server is composed of a node of the blockchain network, and as a result, it is impossible to falsify or falsify growth information, distribution information, contract history, etc. calculated in the system, making it possible to establish a management system for domestically produced agricultural products.

In addition, by calculating the growth information of agricultural products using various production history data and calculating distribution information in distribution means using various distribution history data, it is possible to provide highly reliable information.

In addition, using a machine learning model, growth information of agricultural products and distribution information from distribution means can be calculated with high accuracy, making it possible to provide highly reliable information.

In addition, direct contracts between producers and buyers are possible without going through a distributor, making it possible for both producers and buyers to obtain economic benefits.

Additionally, the production and distribution processes become transparent, making it possible to establish a management system for domestically produced agricultural products.

Above, the present invention has been described with reference to the embodiments shown in the drawings so that those skilled in the art can easily understand and reproduce the present invention, but these are merely illustrative examples, and various modifications and equivalent alternatives can be made by those skilled in the art from the embodiments of the present application. It will be appreciated that embodiments are possible. Therefore, the scope of protection of this application should be determined by the claims.

10: Blockchain communication network
100: production node
110: production terminal
120: Production site sensor unit
130: Agricultural machinery sensor unit
200: distribution node
210: Distribution terminal
220: Distribution sensor unit
300: Management node (management server)
310: Production history data collection unit
320: Distribution history data collection department
330: Agricultural machinery control data collection department
340: Growth information calculation unit
350: Distribution information calculation unit
360: Agricultural machinery control information calculation unit
370: database
380: Barcode generation unit
390: Contract history creation unit
400: Purchase terminal

Claims (10)

A production terminal 110 that receives first production history data including the crop identifier of the agricultural product and includes the crop sowing location, number of stands, and genetic markers, and is installed at the production site where the agricultural product is produced to collect second production history data. A production node 100 including a production site sensor unit 120, a distribution terminal that is mounted on a distribution means for distributing agricultural products produced in the production site and receives first distribution history data including the crop identifier of the agricultural product being distributed ( 210) and a distribution node 200 including a distribution sensor unit 220 installed in the distribution means to collect second distribution history data, the production node 100, the distribution node 200, and a blockchain communication network are connected to each other in communication and calculate growth information of the agricultural product using the first production history data and the second production history data, and the distribution means using the first distribution history data and the second distribution history data A management node 300 that calculates distribution information, and the management node 300 is communicated with and connected to each other through the blockchain communication network, and the growth information and distribution information calculated by the management node 300 are output. A method using an agricultural product production and distribution management system including a purchase node including a purchase terminal 400, wherein sales contract data including the crop identifier and sales price of the agricultural product to be sold through the production terminal 110 Purchase contract data including the crop identifier and purchase price of the agricultural product to be purchased through the purchase terminal 400 is entered, and the method includes:
(a) The production site sensor unit 120 collects the second production history data including temperature, humidity, production site location, solar radiation, soil temperature, soil electrical conductivity, soil moisture, and measurement date and time at the installed production site. ;
(b) The second distribution sensor unit 220 includes the temperature and humidity of the space of the distribution means where the agricultural products produced at the production site are stored, the movement time, movement path, and movement location of the distribution means. collecting historical data;
(c) The management node 300, the temperature, the humidity, the production site location, the solar radiation, the soil ground temperature, the soil electrical conductivity, the soil moisture, the crop identifier, the crop sowing location, the number of seedlings, and The first production history data and the second production history data are applied to a machine learning model learned using production history data including one or more of the genetic markers and growth information scores predetermined according to the production history data as learning data. Computing the input and output growth information scores;
(d) the management node 300, the distribution history data and the crop identifier including one or more of the temperature, humidity, movement time, movement path, and movement location in the distribution means, and the distribution Inputting the first distribution history data and the second distribution history data into a learned machine learning model using the distribution information score predetermined according to the history data and the crop identifier as learning data to calculate the output distribution information score;
(e) when the sales contract data matches the purchase contract data, a contract is established, and the management node 300 generates a history of the established contract; and
(f) when a contract history is created in step (e), transmitting the growth information and the distribution information to the purchase terminal 400 where the purchase contract data is input;
The growth information, distribution information, and generated contract history calculated in the management node 300 are distributed and stored in the production node 100, the distribution node 200, the management node 300, and the purchase node. felled,
Methods for managing the production and distribution of agricultural products.
According to paragraph 1,
In step (e),
Further comprising the step of the management node 300 generating a history of the established contract without going through the distribution node 200,
Methods for managing the production and distribution of agricultural products.
According to paragraph 1,
The system is,
For each crop identifier, standard production history data is stored in one-to-one matching, including the highest growth temperature, lowest temperature for growth, lowest temperature for growth, highest humidity for growth, and lowest humidity for growth, and standards including distribution process temperature and distribution process humidity for each crop identifier. It further includes a database 370 in which distribution history data is stored in one-to-one matching,
In step (c),
The management node 300 compares standard production history data matching the crop identifier included in the first production history data with the first production history data and the second production history data, and produces the agricultural product based on the comparison result. Further comprising; calculating growth information of
Methods for managing the production and distribution of agricultural products.
According to paragraph 3,
In step (d),
The management node 300 includes distribution history data and the crop identifier including one or more of the temperature, humidity, movement time, movement path, and movement location in the distribution means, the distribution history data, and Inputting the first distribution history data and the second distribution history data into a learned machine learning model using the distribution information score predetermined according to the crop identifier as learning data, further comprising calculating the output distribution information score. ,
Methods for managing the production and distribution of agricultural products.
According to paragraph 1,
The step (e) further includes the step of the management node 300 barcoding the growth information calculated in the step (c) and the distribution information calculated in the step (d) into a barcode, ,
When the barcode is scanned by the purchase terminal 400, the growth information and the distribution information are output to the purchase terminal 400,
Methods for managing the production and distribution of agricultural products.
According to clause 5,
Through the distribution terminal 210, distribution contract data including the crop identifier and purchase price of the agricultural product to be distributed is further input,
In step (e),
When the sales contract data and the distribution contract data match, a contract is established, and the management node 300 further includes the step of generating a history of the established contract,
In step (f),
When a contract history is created in step (e), transmitting the growth information and the distribution information to the distribution terminal 210 into which the distribution contract data is input; further comprising,
Methods for managing the production and distribution of agricultural products.
According to paragraph 1,
The production node 100 is,
It further includes an agricultural machine sensor unit 130 that is installed on the agricultural machine for producing the agricultural product and collects the working position of the agricultural machine,
Through the production terminal 110, agricultural machine control data further including one or more of machine information and operation information of the agricultural machine is input,
The above method is,
The management node 300 uses the work location collected by the agricultural machine sensor unit 130, the machine information, and the work information to determine the seeding path, harvest path, yield, and energy efficiency and operation rate of the agricultural machine. Further comprising: calculating agricultural machinery control information,
Methods for managing the production and distribution of agricultural products.
According to paragraph 1,
The production history data is,
Producer identifier, producer name, producer address, producer phone number, cultivation area, harvest time, harvest area, harvest amount, shipment date, shipper phone number, business phone number, seller identifier, seller name, seller phone number, shipment volume, traceability management It further includes production and distribution metadata including number, authentication number, and inventory storage amount,
The distribution history data is,
Logistics organization identifier, logistics organization name, logistics organization address, logistics organization phone number, import date, consignment destination identifier, consignment destination name, consignment destination phone number, import quantity, delivery date, delivery destination identifier, delivery destination name, delivery destination phone number, delivery Further comprising logistics metadata including quantity, logistics pattern, and inventory storage amount,
Methods for managing the production and distribution of agricultural products.
To carry out the agricultural product production and distribution management method according to any one of paragraphs 1 to 8,
Agricultural product production and distribution management system.
Stored in a computer-readable recording medium to execute the agricultural product production and distribution management method according to any one of claims 1 to 8,
computer program.