WO2021256621A1 - Système de transaction de récolte de ferme intelligente utilisant une intelligence artificielle, et procédé associé - Google Patents

Système de transaction de récolte de ferme intelligente utilisant une intelligence artificielle, et procédé associé Download PDF

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Publication number
WO2021256621A1
WO2021256621A1 PCT/KR2020/015402 KR2020015402W WO2021256621A1 WO 2021256621 A1 WO2021256621 A1 WO 2021256621A1 KR 2020015402 W KR2020015402 W KR 2020015402W WO 2021256621 A1 WO2021256621 A1 WO 2021256621A1
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WIPO (PCT)
Prior art keywords
crop
crops
artificial intelligence
smart farm
maturity
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PCT/KR2020/015402
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English (en)
Korean (ko)
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이창훈
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주식회사 글로벌코딩연구소
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Publication of WO2021256621A1 publication Critical patent/WO2021256621A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions

Definitions

  • the present invention relates to a smart farm crop trading system and method using artificial intelligence, and more particularly, to a trading system in which the status of crops is continuously checked and transactions are made by providing the cultivation status of cultivated plants to consumers.
  • the dictionary definition of smart farm is an intelligent farm created by grafting information and communication technology (ICT) to agricultural technology.
  • ICT Internet of Things
  • These smart farms use the Internet of Things (IoT) technology to measure and analyze the temperature, humidity, sunlight, carbon dioxide, soil, etc. of the crop cultivation facility, and drive the control device according to the analysis result to change it to an appropriate state. .
  • IoT Internet of Things
  • the conventional direct transaction of agricultural products on the Internet is structured so that consumers can view and purchase agricultural products when the seller takes pictures of the agricultural products to be sold on the website.
  • the conventional method of direct trading of agricultural products has a structure in which the consumer has no choice but to trust the seller and transact with the seller because it is impossible to check the cultivation environment and cultivation process of the crops from the point of view of the consumer.
  • a smart farm crop trading system and method using artificial intelligence that can purchase reliable crops by providing data so that the cultivation status of crops can be checked in real time and confirming it by the consumer is required.
  • An object of the present invention is to provide a smart farm crop trading system and method using artificial intelligence so that the cultivation status of crops can be checked using artificial intelligence and provided to consumers to increase the transparency of cultivation and transaction efficiency. .
  • the smart farm crop trading method using artificial intelligence includes the steps of taking a picture of the crop, analyzing the maturity of the crop through image analysis, to the prospective consumer Transmitting the sales information including the maturity level of the crop and receiving a reply from the preliminary consumer whether to purchase.
  • the step of analyzing the maturity includes the steps of black processing around the crop, measuring the RGB value of the color part of the crop, and determining the maturity based on the size of the crop in the preset first level range, and
  • the two-level range may include analyzing maturity based on the color of the crop.
  • the step of analyzing the maturity includes the steps of black processing around the crop, measuring the RGB value of the color part of the crop, and determining the maturity based on the size of the crop in the preset first level range, and
  • the two-level range may include analyzing maturity based on the color of the crop.
  • the sending of the sales information may include at least one of a maturity level of a crop, an expected harvest time, a minimum price, and a minimum quantity.
  • Smart farm crop transaction system and method using artificial intelligence according to the present invention using artificial intelligence to check the cultivation status of crops and provide them to consumers to increase transparency of cultivation and transaction efficiency using artificial intelligence There is an effect that can be provided of the farm crop trading system and the method.
  • FIG. 1 is an operation flowchart illustrating a smart farm crop trading method using artificial intelligence according to an embodiment of the present invention.
  • FIG. 2 is a flowchart illustrating in detail an embodiment of a step of taking a picture of a crop among the steps of FIG. 1 .
  • FIG. 3 is a flowchart illustrating in detail an embodiment of a step of analyzing maturity among the steps of FIG. 1 .
  • FIG. 1 is an operation flow diagram showing a smart farm crop trading method using artificial intelligence according to an embodiment of the present invention
  • FIG. It is a flowchart
  • FIG. 3 is a flowchart illustrating in detail an embodiment of the step of analyzing maturity among the steps of FIG. 1 .
  • the smart farm crop trading method using artificial intelligence may be performed through the following steps.
  • step (S110) it is possible to take a picture of the crop.
  • a plurality of pictures of crops may be taken, and one or more selected images among a plurality of photographed images may be used for the following analysis.
  • step S110 an embodiment of the detailed configuration of step S110 will be described in more detail with reference to FIG. 2 .
  • step S111 a plurality of pictures of the crops may be taken.
  • step S112 when an overlapping portion between the plurality of photos is searched, a portion having a high color value among the overlapping portions may be treated as an effective portion, and a portion having a relatively low color value may be subjected to noise processing.
  • step S113 the plurality of photos are synthesized, but the overlapping part can be synthesized by composing an effective part.
  • step S120 the maturity level of crops may be analyzed through image analysis.
  • step S120 an embodiment of the detailed configuration of step S120 will be described in more detail with reference to FIG. 3 .
  • step S121 the surrounding crop is blacked
  • step S122 the RGB value of the color part of the crop is measured
  • step S123 the size of the crop is based on a preset first level range. to determine the maturity level, and in the preset second level range, the maturity level may be analyzed based on the color of the crop.
  • maturity levels 1 to 10 may be determined based on size, and maturity levels 11 to 20 may be determined based on color.
  • step (S130) it is possible to send the sales information including the maturity level of the crop to the prospective consumer.
  • the information sent to the preliminary consumer may include at least one of the maturity level of the crop, the expected harvest time, the minimum price, and the minimum quantity.
  • step (S140) it is possible to receive a reply whether to purchase from the preliminary consumer.
  • a smart farm crop trading method using artificial intelligence can be implemented by a smart farm crop trading system using artificial intelligence, and an example thereof will be described below.
  • the crop trading system of the present invention is a system that brokers the trade of crops produced in a plurality of production sites (producer A, producer B, .. producer C).
  • a plurality of producers access the crop trading system through a wired or wireless network (eg, a network for Internet connection), and publish the crops they produce on the crop trading system.
  • a wired or wireless network eg, a network for Internet connection
  • Buyers (Buyer 1, Buyer 2, .. Buyer N) access the crop trading system via a wired or wireless network (eg a network for internet connection) and reserve the purchase of the desired crops among the crops posted by the producers. do.
  • a wired or wireless network eg a network for internet connection
  • Producer A uses the producer terminal (P) to display the images of the reserved crops on the crop image server from the first image of cultivation to the image of the expected harvest date. It is filmed every day (or a specific period) and sent (ie, uploaded).
  • the growth image transmission server 300 transmits the uploaded image by date to the terminal C of the purchaser A as it is or through a predetermined editing process.
  • Producer A sends the harvested crop to Buyer 1 to complete the transaction process.
  • the crop image server receives and stores images of crops grown in crop production areas. Since the crop image server stores images of crops, storage for image storage is included, but storage is omitted since it is a self-explanatory configuration.
  • the crop image server may include a same crop determination unit and a standard image recording unit.
  • the same crop determination unit determines whether the crop image received on a specific day is the same crop image as that of the first crop by comparing the received images of crops by date.
  • the size and shape of crops gradually change according to the growth process, and the same crop determination unit compares the received images by date and examines the similarity to determine whether the received image of the crop is an image of the same crop.
  • the standard image recorder stores the average growth image of crops.
  • the average growth image corresponds to an image in which all images of crops previously grown by producer A are collected.
  • the crop video server captures images by date taken when Producer A cultivates mushrooms for the first time, and shoots for the second time cultivating mushrooms. It stores both the image by date of cultivation and the image by date taken during cultivation for the N times.
  • the standard image recording unit may extract the size of crops for each day from the 1st to Nth images and select an image of a crop having an average size as a standard image (ie, an average growth image).
  • the 'average growth image' is used in the output calculation unit, which will be described later.
  • the reservation server uses the image of the crop stored in the crop image server to initiate sales information of the corresponding crop, and receives a reservation for the purchase of the crop from the purchaser terminal (C).
  • the configuration of the reservation server is similar to that of a typical online shopping mall, a detailed description thereof will be omitted.
  • the growth image transmission server transmits the image of the crop reserved for purchase to the purchaser terminal C with the purchase reservation.
  • the image of the crop reserved for purchase may be directly transmitted from the producer terminal P to the purchaser terminal C, but predetermined image processing may be performed to further increase the reliability of the crop cultivation process.
  • the growth image transmission server may transmit images of crops reserved for purchase by date, among images of a plurality of crops stored in the crop image server, to the purchaser terminal C having a purchase reservation.
  • the pricing server calculates the expected yield by reflecting the risks that occur in the process of crop growth and calculates the unit selling price of the crop.
  • growth conditions may change depending on weather conditions, so crop yields may change, and yields may change depending on conditions such as the germination success rate of crops.
  • the risk may be applied only to a specific production site (for example, Producer A), or it may be applied to all production sites (Producer A to Producer C).
  • the price calculation server may include a yield calculation unit and a risk calculation unit.
  • the yield calculation unit calculates the expected yield of the crop. Specifically, it calculates the expected yield of the crop by analyzing the image of the crop by date received from the crop image server. For example, the image of the crop by date received from the crop image server is compared with the average growth image stored in the standard image recorder, and the expected yield is calculated based on the similarity between the two sides.
  • the risk calculator adjusts the initial selling price disclosed in the reservation server based on the expected yield for each producer (producer A, producer B to producer C) calculated by the yield calculator. At this time, whether to change or maintain the contract price of Buyer 1, who is the reservation purchaser, may be changed according to risk setting.
  • the crop image server is set to receive the image of the crop photographed through a dedicated application installed in the mobile terminal (ie, the producer terminal (P)) of the producer who produces the crop.
  • the dedicated application is installed in the producer terminal (P).
  • the dedicated application can access the crop trading system after authenticating the producer.
  • the dedicated application captures images of specific crops by capturing images in batches of rows or furrows in which crops are grown by video shooting, and extracting images of individual crops from the captured images.
  • the video is processed in a dedicated application and extracted as an individual video of each crop. Then, the crop images extracted as individual images are uploaded to the crop image server.

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  • Accounting & Taxation (AREA)
  • Finance (AREA)
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  • Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
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  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L'invention concerne un système de transaction de récolte de ferme intelligente utilisant une intelligence artificielle, et un procédé associé. Le procédé de transaction de récolte de ferme intelligente utilisant une intelligence artificielle comprend les étapes suivantes : prendre une photographie d'une récolte; analyser le moelleux de la récolte par l'intermédiaire d'une analyse d'image; transmettre des informations de ventes comprenant le moelleux de la récolte à un consommateur préliminaire; et recevoir une réponse indiquant s'il faut acheter en provenance du consommateur préliminaire.
PCT/KR2020/015402 2020-06-18 2020-12-03 Système de transaction de récolte de ferme intelligente utilisant une intelligence artificielle, et procédé associé WO2021256621A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2020-0073993 2020-06-18
KR20200073993 2020-06-18

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WO2021256621A1 true WO2021256621A1 (fr) 2021-12-23

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9888081B1 (en) * 2014-02-18 2018-02-06 Smart Farm Systems, Inc. Automation apparatuses, systems and methods
US20180150344A1 (en) * 2016-11-28 2018-05-31 Electronics And Telecommunications Research Institute Method and apparatus for diagnosing error of operating equipment in smart farm
KR20180076766A (ko) * 2016-12-28 2018-07-06 농업회사법인 만나씨이에이 주식회사 인공지능 스마트팜 관리 시스템
KR102097660B1 (ko) * 2019-01-29 2020-05-26 추봉수 스마트팜을 이용한 농산물 분양 시스템
KR102121734B1 (ko) * 2019-11-18 2020-06-12 이민우 스마트 팜 통합관리 플랫폼 시스템 및 이의 운영방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9888081B1 (en) * 2014-02-18 2018-02-06 Smart Farm Systems, Inc. Automation apparatuses, systems and methods
US20180150344A1 (en) * 2016-11-28 2018-05-31 Electronics And Telecommunications Research Institute Method and apparatus for diagnosing error of operating equipment in smart farm
KR20180076766A (ko) * 2016-12-28 2018-07-06 농업회사법인 만나씨이에이 주식회사 인공지능 스마트팜 관리 시스템
KR102097660B1 (ko) * 2019-01-29 2020-05-26 추봉수 스마트팜을 이용한 농산물 분양 시스템
KR102121734B1 (ko) * 2019-11-18 2020-06-12 이민우 스마트 팜 통합관리 플랫폼 시스템 및 이의 운영방법

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