KR102532651B1 - Greenhouse crop management system - Google Patents

Abstract

The present invention relates to a greenhouse crop management system. The greenhouse crop management system comprises: a plurality of crop beds arranged inside a greenhouse; an automatic collection device which transmits crop images generated by photographing actual crops grown in the plurality of crop beds; and a greenhouse crop management device, wherein the greenhouse crop management device includes: a collection unit which collects crop images from the automatic collection device and stores them in an image DB; an analysis unit which preprocesses the crop image stored in the image DB and identifies crops in the image included in the preprocessed crop image through image analysis of the preprocessed crop image; and a crop management unit which stores and manages information on crops in the identified video in the crop DB. Accordingly, the present invention enables recording and management of crop information quickly and efficiently without hassle.

Description

Greenhouse Crop Management System {GREENHOUSE CROP MANAGEMENT SYSTEM}

The present invention relates to a greenhouse crop management system.

BACKGROUND OF THE INVENTION In the agricultural field where crop production, cultivation, harvesting, distribution, etc. are performed, as the number of managed crops is vast, technology capable of efficiently and efficiently managing these crops is essential.

However, in the prior art, when the number of crops to be managed is vast and the types of crops to be managed are diverse, in particular, in recording and managing the information of the harvested crop after harvesting a specific crop, the user selects the variety of the harvested crop, It was necessary to pay attention to what kind of crop it was and check it individually, and after checking the variety and type of crop, whenever the user wants to input crop information thereafter, the crop information recording device fixed at a specific location (for example , desktop PC, etc.), search for crops identified in the crop information recording device, and input information related to the searched crops. There was a (cumbersome) aspect.

The background technology of the present invention is disclosed in Korean Patent Registration No. 10-1070144.

The present invention is to solve the above-mentioned problems of the prior art, in which a user harvests a specific crop and records and manages information about the harvested crop, so that the crop information can be recorded and managed quickly and efficiently without trouble (convenience). It aims to provide a viable greenhouse crop management system.

However, the technical problems to be achieved by the embodiments of the present invention are not limited to the technical problems described above, and other technical problems may exist.

As a technical means for achieving the above technical problem, the greenhouse crop management system according to an embodiment of the present invention includes a plurality of crop beds disposed inside the greenhouse; an automatic collecting device for transmitting crop images generated by photographing actual crops grown in the plurality of crop beds; and a greenhouse crop management device, wherein the greenhouse crop management device includes: a collection unit that collects crop images from the automatic collection device and stores them in an image DB; an analyzer for identifying crops included in the preprocessed crop image through image analysis of the preprocessed crop image obtained by preprocessing the crop image stored in the image DB; and a crop management unit that stores and manages information on the identified crops in the image in a crop DB.

In addition, the automatic collection device generates a crop image through photographing while moving the plurality of crop beds, detects identification information of the crop bed through a bed identification tag attached to each crop bed, and identifies the bed After recognizing the dragon tag, while moving with respect to the plurality of crop beds, the upper side of each of the plurality of crop beds is photographed at regular time intervals, and at least some of the crops grown in the plurality of crop beds are photographed in time-sequential manner. Images can be created and transmitted.

In addition, the analysis unit divides the plurality of crop images stored in the image DB into crop images related to each crop bed in consideration of the identification information of the crop bed recognized before capturing the crop image in the automatic collection device, and Based on the related crop images for each crop bed, preprocessing including feature point comparison and image matching between related crop images is performed for each crop bed to generate one integrated integrated crop image data as the preprocessed crop image for each crop bed, , Then, by performing image analysis on each of the integrated crop image data for each crop bed, crops in the image included in each integrated crop image data can be identified.

In addition, the crops in the image are crops in the image corresponding to the actual crops, and the crop management unit assigns an individual crop ID to each of the crops in the image identified by the analysis unit, and each of the crops in the image Regarding, the individual crop ID information assigned to the crop in the image, the identification information of the crop bed in which the crop in the image is accommodated, and the information linking the image including the crop in the image to each other are stored in the crop DB as crop information in the image. can be stored and managed.

In addition, the analysis unit, when there is an additional crop image additionally collected by the collection unit, determines whether a QR code exists in the additional crop image through image analysis, and if the QR code exists as a result of the determination, the QR code is present. The attachment position of the code is identified, and the crop management unit, based on the attachment position of the QR code identified by the analysis unit, determines the attachment position of the identified QR code among information on crops in the image stored in the crop DB. The crop information in the corresponding image is identified as crop information in the QR corresponding image, and the URL information pre-stored in the QR code is further included in the crop information in the identified QR corresponding image to be further stored and managed in the crop DB. can do.

In addition, the greenhouse crop management system further includes a user terminal possessed by a user, and the user terminal is located in a region of a packaging material in which a real harvest crop, which is any one real crop harvested by the user among the real crops, is packaged. After photographing the prepared QR code, input and upload growth information of the harvested real crop on a web page provided by photographing the QR code, and the crop management unit, when the growth information is uploaded from the user terminal, the Identify crop information in an image having matching URL information that matches the URL information corresponding to the web page in which the growth information uploaded from the crop DB is input, and the information of the crop in the image having the matching URL information In the case of crop information in the identified QR-corresponding image, the uploaded growth information may be further included in crop information in the identified QR-corresponding image to be further stored and managed in the crop DB.

In addition, the greenhouse crop management system further includes a pair of QR codes provided for the actual harvested crop when any one of the real crops is a real harvested crop harvested by a user, and A pair of QR codes is provided in the form of a sticker containing the same URL information, and any one of the pair of QR codes is used for the harvesting on the plurality of crop beds after the harvested real crop is harvested. It is attached to the location where the real crop is harvested, and the other QR code of the pair of QR codes will be attached to one area of the packaging material of the harvested real crop that is packed after the harvested real crop is packed with the packaging material. can

The above-described means for solving the problems is only illustrative and should not be construed as limiting the present invention. In addition to the exemplary embodiments described above, additional embodiments may exist in the drawings and detailed description of the invention.

According to the above-described problem solving means of the present invention, by providing a greenhouse crop management system, the user harvests a specific crop and records and manages information on the harvested crop quickly and efficiently without effort (convenience). It can be recorded and managed.

According to the above-described problem solving means of the present invention, by providing a greenhouse crop management system, while automatically collecting crop images using various sensors (image sensors) in commercial farms, automatically assigning IDs for each crop, and providing a user ( The growth information of the harvested crop, which is manually entered by the grower) directly measuring the harvested crop, is easily recorded in the crop DB, and converts it to the crop image data (i.e., crop image or integrated crop of the harvested crop) video data) and combined (linked) to be recorded and managed together.

However, the effects obtainable in the present invention are not limited to the effects described above, and other effects may exist.

1 is a diagram showing a schematic configuration of a greenhouse crop management system according to an embodiment of the present invention.
2 to 6 are views for explaining a greenhouse crop management system according to an embodiment of the present invention.
7 is an operational flowchart of a greenhouse crop management method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail so that those skilled in the art can easily practice the present invention with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification of the present invention, when a part is said to be “connected” to another part, it is not only “directly connected”, but also “electrically connected” or “indirectly connected” with another element in between. It also includes cases where it is "connected to".

Throughout the specification of the present invention, when a member is said to be located “on”, “above”, “on top”, “below”, “below”, or “below” another member, this means that a member is positioned “on” another member. This includes not only the case in contact with a member but also the case where another member exists between two members.

Throughout the specification of the present invention, when a part "includes" a certain component, it means that it may further include other components without excluding other components unless otherwise stated.

1 is a diagram showing a schematic configuration of a greenhouse crop management system 1 according to an embodiment of the present invention. 2 to 6 are views for explaining a greenhouse crop management system 1 according to an embodiment of the present invention.

Hereinafter, for convenience of description, the greenhouse crop management system 1 according to an embodiment of the present invention will be referred to as the present system 1. In addition, matters shown (described) in FIGS. 1 to 6 may be equally applied to descriptions of the present system 1 and the present apparatus 10 even if omitted below.

1 to 6, the system 1 includes a greenhouse crop management device 10, a plurality of crop beds 20 (21, 22, ...), an automatic collection device 30, and a user terminal 40. and a pair of QR codes 50 (51, 52).

The greenhouse crop management device 10 may refer to a device for storing (recording) and managing various information about real crops grown in a plurality of crop beds 20 .

The greenhouse crop management device 10 is a greenhouse crop management device 10 according to an embodiment of the present invention, and will be referred to as the present device 10 for convenience of explanation. The device 10 may provide, for example, a web page, app page, program, or application related to management of greenhouse crops to a user terminal 40 possessed by a user using the device 10, through which the user can It is possible to efficiently manage a large number of cultivated crops (actual crops) (ie, record, check, manage information of greenhouse crops, etc.).

That is, the device 10 may be, for example, a device that can be implemented in the form of a program or application (application, app) installed on the user terminal 40. In other words, provided through the device 10 The greenhouse crop management method may be implemented in the form of a program or application and provided to the user through the user terminal 40 . However, it is not limited to this, and as another example, the device 10 may be provided in the form of a server capable of transmitting and receiving data with the user terminal 40, and the device 10 provided in the form of a server, It is possible to control the operation (for example, screen display) of the user terminal 40 connected to the application provided by (10). In the description with reference to FIG. 1 , the device 10 will be described as being provided in the form of a server as an example. In this case, the device 10 is a greenhouse crop management server, server (or main server), etc. can be referred to.

In addition, the application (app, app) provided by the device 10 in the present invention is a greenhouse crop management application, which may be referred to as this app for convenience of explanation. The device 10 may provide a greenhouse crop management platform (this platform) through the provision of this app.

A plurality of crop beds 20 (21, 22, ...) may be arranged inside the greenhouse (inside the greenhouse). A plurality of crop beds 20 (21, 22, ...) may refer to members (trays) on which crops are grown. The plurality of crop beds 20 may include a first crop bed 21 , a second crop bed 22 , and the like. In each of the plurality of crop beds 20, a plurality of actual crops may be spaced apart from each other and cultivated.

In the present invention, the crops (crops) grown in the plurality of crop beds 20 may be otherwise referred to as actual crops (real crops). Crops (actual crops) considered in the present invention may include, but are not limited to, various types of crops that can be cultivated in greenhouses, commercial farms, and the like. The specific shape, material (material), etc. of the plurality of crop beds 20 are not particularly limited, and various crop beds previously known or developed in the future (crop beds capable of cultivating a plurality of crops) may be applied. .

In describing the present invention, the description of any one crop bed among the plurality of crop beds 20 can be equally applied to the description of each of the plurality of crop beds 20, even if omitted below. Similarly, the description of any one real crop among the real crops grown in the plurality of crop beds 20 will be equally applied to the description of each of the real crops (a plurality of real crops), even if omitted below. can

As shown in FIG. 3, each of the plurality of crop beds 20 in the present invention may have a bed identification tag for identifying crop beds in one area. The bed identification tag is a tag capable of recognizing identification information (unique identification information) of each crop bed differently assigned to each crop bed through wireless communication, and may be, for example, a tag such as RFID, beacon, or NFC. The bed identification tag is implemented in the form of a sticker, for example, and can be attached to each of the plurality of crop beds 20 . That is, the plurality of bed identification tags attached in a 1:1 correspondence with each of the plurality of crop beds 20 may include identification information of the crop bed to which each bed identification tag is attached.

When acquiring a crop image of a real crop, the automatic collection device 30 recognizes a tag for identifying the bed attached to the crop bed where the real crop is located, thereby obtaining identification information of the crop bed where the corresponding real crop is located. And, the identification information of the acquired crop bed may be linked to the acquired crop image and transmitted to the apparatus 10. To this end, a reader (tag reader, not shown) for recognizing a tag for identifying a bed attached to a crop bed may be provided in one area of the automatic collection device 30 .

The automatic collecting device 30 transmits crop images generated by photographing real crops grown in the plurality of crop beds 20 (in particular, at least some real crops among all real crops) to the device 10. can transmit The automatic collection device 30 may include an image sensor 31 provided in one area. The automatic collecting device 30 may generate a crop image by photographing at least some real crops among the real crops grown in the plurality of crop beds 20 through the image sensor 31, and view the generated crop image. It can be transmitted over the network 2 to the device 10.

For example, the image sensor 31 may mean a sensor capable of acquiring images such as RGB, depth (distance/depth), hyperspectral, and thermal images. That is, the image sensor 31 may include, for example, at least one of an RGB sensor, a vision sensor capable of obtaining a depth image, a hyperspectral sensor, and a thermal image sensor. The image sensor 31 may be otherwise referred to as an image sensor, a camera, or an image capture device.

The automatic collecting device 30 automatically photographs at least some real crops of the real crops grown in the plurality of crop beds 20 while moving inside the greenhouse, and transmits the crop image generated by the photographing to the apparatus 10. It may mean a device provided. Such an automatic collection device 30 may be implemented as a gantry system or a mobile robot, as shown in FIG. 2 , for example. That is, the automatic collection device 30 may be a gantry system or a mobile robot.

The automatic collection device 30 moves to various locations in the greenhouse through automatic control (eg, through automatic control by the control unit 16) and captures and obtains crop images of at least some real crops, thereby providing the apparatus 10 ) can be transmitted (provided). The automatic collection device 30 acquires (recognizes) the identification information of the crop bed through the recognition of a tag (eg RFID) for identifying the bed attached to each crop bed with a reader (not shown) while moving inside the greenhouse. (10) can be sent.

In particular, the automatic collection device 30 can take crop images while moving along the longitudinal direction of the crop bed (for example, the direction in which more real crops are arranged on the crop bed) with respect to the plurality of crop beds 20. . For example, the longitudinal direction of the crop bed may mean, for example, 'between 1 o'clock and 2 o'clock' - 'between 7 o'clock and 8 o'clock' based on the drawing shown in FIG. 3 .

The user terminal 40 may refer to a terminal possessed by a user who cultivates real crops with a plurality of crop beds 20 . A user possessing the user terminal 40 may be otherwise referred to as a redisan or the like.

The user terminal 40 is, for example, PCS (Personal Communication System), GSM (Global System for Mobile communication), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication )-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (WCode Division Multiple Access), Wibro (Wireless Broadband Internet) terminal, smartphone, smartpad, tablet PC, laptop, wearable It may include all types of wired and wireless communication devices such as devices and desktop PCs, but is not limited thereto. In the present invention, it may be preferable that the user terminal 40 is a portable terminal such as a smart phone that can be moved and carried. Hereinafter, the user terminal 40 will be described as a portable terminal such as a smart phone.

A pair of QR codes 50, 51 and 52 are provided for the convenience of harvest management for real crops and for the convenience of inputting information on the harvested real crops (ie, growth information to be described later). , It may be provided in the form of a sticker. The pair of QR codes 50, 51 and 52 may include a first QR code 51 and a second QR code 52, and each of the pair of QR codes 50 has the same URL information as each other. Can be granted (included).

In the present invention, a pair of QR codes 50 may be provided in plurality as many as the number of actual crops grown in the plurality of crop beds 20 or as many as the number of harvested crops. That is, when the number of real crops (or the number of harvested crops) is 2000, 2000 pairs of QR codes 50 may be provided in the present system 1. In the present invention, for example, even if crops are equally grown in a crop bed, some crops may die or not be harvested because cultivation is not normally performed, so preferably a pair of QR codes 50 are harvested crops (harvested real thing) It may be desirable to provide as many as the number of crops). According to this, a pair of QR codes 50 may be assigned to each harvested real crop (ie, harvested real crop), and a specific utilization method of the pair of QR codes 50 will be described in more detail later. do.

The device 10 may transmit/receive data by interworking with each of the automatic collection device 30 and the user terminal 40 through the network 2 . In addition, the apparatus 10 may transmit and receive data by interlocking with each of the plurality of crop beds 20 through the network 2 .

The network 2 is, for example, a 3rd Generation Partnership Project (3GPP) network, a Long Term Evolution (LTE) network, a World Interoperability for Microwave Access (WIMAX) network, the Internet, a Local Area Network (LAN), and a Wireless LAN (Wireless). Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), Bluetooth (Bluetooth) network, NFC (Near Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc. It may include, but is not limited thereto, and may include various wired/wireless communication networks.

Based on the above description, the present device 10 will be described in detail as follows.

At this time, in one example of the present invention, when the automatic collection device 30 shoots a crop image and transmits it to the device 10, the device 10 performs 'comparison of feature points based on the crop image, image matching, and integrated crop image' It is exemplified as processing (performing) the process of generating data and assigning individual crop IDs, but this is only one example to help understanding of the present invention, and is not limited thereto. As another example, the process of 'comparison of feature points based on crop images, image matching, generation of integrated crop image data, and assignment of individual crop IDs', which is exemplified by the apparatus 10, is carried out by the automatic collection device 30 (Especially in a control unit (not shown) in the automatic collection device), and in this case, the automatic collection device 30 provides information on each of the crops in the image to which individual crop IDs are assigned (ie, information on crops in the image) ) is transmitted to the device 10, the crop management unit 15 may directly store it in the crop DB 14.

Specifically, referring to FIGS. 1 to 6, the device 10 includes a collection unit 11, an image DB 12, an analysis unit 13, a crop DB 14, a crop management unit 15, and a control unit 16 ) may be included.

The collection unit 11 may collect crop images from the automatic collection device 30 and store them in the image DB 12 (step 1).

Here, the automatic collection device 30, for example, as shown in FIG. 3, moves a plurality of crop beds 20 at predetermined predetermined moving intervals (for example, at intervals of 50 cm) to at least some real crops. A crop image is generated by performing a photographing of the crop, but when the photographing is performed, the identification information of the crop bed is detected (recognized, obtain) can be obtained. That is, the automatic collection device 30 recognizes the tag for identification of the bed and moves with respect to the plurality of crop beds 20, while moving by a predetermined moving interval (ie, an interval of 50 cm in one example), a plurality of crops each time it moves. By photographing the upper side of each bed 20 , crop images may be acquired in time series (in real time), and the obtained crop images may be provided to the apparatus 10 . At this time, when the automatic collection device 30 provides the obtained crop image to the present device 10, the identification information of the detected crop bed is linked to the crop image by recognizing the tag for identifying the bad when the crop image is acquired. It can be provided as-is.

Through this, the collection unit 11 may obtain (collect) crop images in real time (time-sequentially) from the automatic collection device 30 and store them in the image DB 12 . At this time, a plurality of crop images may be stored in the image DB 12, and in each crop image, crop bed identification information obtained from the automatic collection device 30 (ie, crop bed identification information included in the crop image) ) may be linked together and stored.

The analysis unit 13 may identify (recognize) crops included in the preprocessed crop image through image analysis of the preprocessed crop image obtained by preprocessing the crop image stored in the image DB 12 . Here, the crops in the image may mean crops in an image (crop image) that correspond 1:1 to actual crops.

At this time, the analysis unit 13 considers the identification information of the crop bed recognized before capturing the crop image in the automatic collection device 30 in order to generate a preprocessed crop image, and stores a plurality of images stored in the image DB 12. Crop images may be divided into crop images related to each crop bed. Thereafter, the analysis unit 13 performs preprocessing including feature point comparison and image registration among crop images related to each crop bed based on the crop images related to each crop bed, thereby integrating one crop bed for each crop bed. integrated crop image data may be generated as a preprocessed crop image (step 2). Thereafter, the analysis unit 13 performs image analysis on each of the integrated crop image data for each crop bed, so that the crops in the image included in each integrated crop image data (ie, the crops in the image corresponding to real crops) ) can be identified (in particular, individually identified, individually recognized) (step 3).

As an example, suppose that there are 20 crop beds 20 and 10 crop images are taken for each crop bed, so that a total of 200 crop images are stored as a plurality of crop images in the image DB 12.

In this case, the analysis unit 13 considers the identification information of the recognized crop bed as an example, i) in the case of the 1st to 10th crop images among 200 crop images stored in the image DB 12, the first Real crops grown in the crop bed 21 are divided into crop images (ie, crop images related to the first crop bed) obtained by photographing, and ii) in the case of the 11th to 20th crop images, the second Real crops grown in the crop bed 22 are divided into crop images obtained by photographing (ie, crop images related to the second crop bed), iii) in the case of the 21st to 30th crop images, the third A plurality of crop images stored in the image DB 12 are divided into crop images (that is, crop images related to a third crop bed) obtained by photographing real crops grown in a crop bed (not shown). It can be divided into crop images related to each bed.

Thereafter, the analysis unit 13, for example, i) extracts feature points between the crop images related to the first crop bed (ie, the first crop image to the tenth crop image), and then performs preprocessing including a comparison process and an image matching process. , generates first integrated crop image data (ie, the first pre-processed crop image) corresponding to the first crop bed 21, and ii) crop images related to the second crop bed (ie, 11th to 10th crop images) 20 crop images) by performing pre-processing including a comparison process and an image matching process after extracting feature points, thereby generating second integrated crop image data (ie, second pre-processed crop image) corresponding to the second crop bed 22 As such, integrated crop image data (ie, pre-processed crop image) may be generated for each of the plurality of crop beds 20 (step 2). According to this, in the integrated crop image data for each crop bed generated through the preprocessing, the first integrated crop image data corresponding to the first crop bed 21 and the second integrated crop corresponding to the second crop bed 22 Image data, third integrated crop image data corresponding to a third crop bed (not shown), . . . , n-th integrated crop image data corresponding to the n-th crop bed) may be included. Here, the value of n may be a value corresponding to the total number of crop beds included in the present system 1 (ie, the number of a plurality of crop beds). An example of generating integrated crop image data may be more easily understood with reference to FIG. 4 .

After performing step 2, the analysis unit 13 performs image analysis on each of the generated integrated crop image data (that is, the first integrated crop image data to the n-th integrated crop image data) for each crop bed, thereby generating each integrated crop image. It is possible to identify (individually recognize) the crops in the image included in the data (that is, each of the integrated crop image data for each crop bed). At this time, the crops in the image identified by the analysis unit 13 are in the image included in the plurality of integrated crop image data corresponding to the plurality of crop beds 20 (that is, the entire integrated crop image data for each crop bed). This means crops, which may mean crops in the image that correspond (1:1 correspondence) to actual crops grown in the plurality of crop beds 20 . For example, if the total number of real crops grown in the plurality of crop beds 20 is 2000, the number of crops in the image identified by the analysis unit 13 may also be 2000.

In addition, as the image analysis in step 2, various video (image) analysis (processing) techniques known or developed in the future may be applied, and for example, an object identification technique (object recognition technique) may be applied.

In addition, the analysis unit 13 applies a deep learning model to the generated integrated crop image data for each crop bed (that is, applies image analysis using a deep learning model), thereby included in each integrated crop image data for each crop bed. It is possible to identify (individual recognition) crops (ie, crops in the image) that are present.

Here, the deep learning model may mean an artificial intelligence (AI) algorithm model, a machine learning (machine learning) model, a neural network model (artificial neural network model), a neuro fuzzy model, and the like. In addition, the deep learning model is conventionally known or developed in the future, such as a Convolution Neural Network (CNN), a Recurrent Neural Network (RNN), and a Deep Neural Network, by way of example. Various neural network models may be applied.

That is, the analysis unit 13 can identify (individual recognition) the crops in the images included in each of the integrated crop image data for each crop bed using a pre-learned deep learning model, and through the identification (individual recognition) Cultivation location information of each of the crops in the identified image may be derived.

Here, the cultivation location information may mean information on which point (which row and which column) the crop in the image is located in which crop bed. That is, the cultivation position information of a crop in the first image, which is a crop in any one image among crops in the image corresponding to real crops (1: 1 correspondence), is a real crop corresponding to the crop in the first image (ie, multiple crops). It may refer to row/column information on a crop bed in which a first real crop among real crops) is grown. Illustratively, a total of 300 actual crops corresponding to 6 (rows) x 50 (columns) are grown in the first crop bed 21, and at this time, the first actual crops are grown on the first crop bed 21 at 5 In the case of a crop being grown in a third column of a row, cultivation location information of the crop in the first image corresponding to the first real crop may be expressed as (5,3), for example.

After the analyzer 13 identifies (individually recognizes) the crops in the image in step 2 described above and derives the cultivation location information of each of the crops in the image, the crop management unit 15 then identifies the crops identified in the analyzer 13 Information on the crops in the image (each of the crops in the image) can be stored and managed in the crop DB 14 .

Specifically, as shown in FIG. 4 , the crop management unit 15 may assign an individual crop ID to each of the crops in the image identified by the analysis unit 13 (step 3), and then to each crop in the image. , individual crop ID information assigned to the crop in the image, identification information of the crop bed in which the crop in the image is accommodated (that is, where the actual crop corresponding to the crop in the image is grown), and the image including the crop in the image Information linked to each other can be stored and managed in the crop DB 14 as crop information in the image, and through this, the construction of the crop DB 14 can be completed.

That is, information on each of the crops in the image identified by the analysis unit 13 (information on the crop in the image) may be stored in the crop DB 14 . Information on crops in images stored in the crop DB 14 may be as shown in FIG. 4 , for example. In other words, in the crop DB 14, for example, as shown in FIG. 4, each of the actual crops (or each of the crops in the identified image), [individual crop ID-bad number (ie, identification information of the crop bed) )-image information (ie, crop image or integrated crop image data)] may be stored and managed.

For example, information on crops in a first image, which is a crop in any one image among information on crops in an image stored in the crop DB 14 (that is, information on crops in a plurality of images), is individually assigned to the crop in the first image. Individual crop ID information that is the crop ID information obtained, identification information of the crop bed in which the crop in the first image is accommodated, and images including the crop in the first image may be stored in association with each other. Here, the individual crop ID information of the crop in the first image is, for example, unique identification information assigned to the crop in the first image and cultivation position information of the crop in the first image derived by the analysis unit 13 (that is, row / column information). The identification information of the crop bed of the crop in the first image is identification information of the crop bed in which the real crop corresponding to the crop in the first image is grown. It may refer to information obtained (detection, identification) by recognizing , which is included in (stored in association with) an image (crop image or integrated crop image data) in which crops exist in the first image. It may be information obtained by extracting identification information of . An image including crops in the first image may mean a crop image including crops in the first image or integrated crop image data.

In the above description, the description of the crops in the first image may be equally applied to the description of each of the crops in the image, even if omitted below.

That is, in the crop DB 14 , for each of the real crops grown in the plurality of crop beds 20 , information on the crop in the image corresponding to each real crop may be stored. If the number of real crops is 2000, since the number of crops in the image is also 2000, information on 2000 real crops (ie, crop information in the image) can be stored and managed in the crop DB 14. Through this process, the crop DB 14 may be constructed (construction completed).

For example, in the crop DB 14, a DB may be established for each individual crop ID. In other words, the crop DB 14 may include a plurality of individual DBs generated in a 1:1 correspondence to each individual crop ID (ie, to each actual crop).

After the crop DB 14 is built, the automatic collecting device 30 may photograph real crops every day during the growing period of the real crops and transmit crop images generated by the photographing to the apparatus 10 .

At this time, for example, the crop management unit 15 performs image analysis on crop images collected (obtained) daily from the automatic collection device 30 (ie, additional crop images additionally collected), and individual crops of the crops in the image. It is possible to identify the ID and store and manage crop images collected in consideration of the identified individual crop ID information in an individual DB related to the corresponding crop image. That is, the crop management unit 15 may classify, store, and manage crop images collected from the automatic collection device 30 in a plurality of individual DBs based on identified individual crop IDs.

In addition, referring to FIG. 6 , after storing information on crops in an image identified as an example in the crop DB 14 (that is, after construction of the crop DB 14 is completed), the analysis unit 13 is a collection unit. If there is an additional crop image additionally collected in (11), it is possible to determine whether a QR code 51 exists in the additional crop image through image analysis of the additional crop image. At this time, as a result of the determination, if the QR code 51 exists, the analysis unit 13 determines the attachment position of the QR code 51 by applying image analysis (eg, image analysis using a deep learning model) to the additional crop image. can be identified. Here, the attachment position of the identified QR code 51 is the attachment position of the QR code on the crop bed to which the QR code 51 is attached, meaning row/column information to which the QR code is attached on the corresponding crop bed. can do.

Thereafter, the crop management unit 15, based on the attachment position of the QR code 51 identified by the analysis unit 13, identifies the identified QR code 51 among information on crops in the image stored in the crop DB 14. ) is identified as crop information (ie, individual crop ID information) in the image corresponding to the attachment position of ) as crop information in the QR-corresponding image, and the information of the crop in the identified QR-corresponding image is actually used by the user (the grower). It is determined that the harvested crop information is harvested, and the URL information pre-stored in the QR code 51 is further included (linked) in the crop information in the identified QR corresponding image to be stored and managed in the crop DB 14. can do. Here, the URL information pre-stored in the QR code 51 may be information automatically identified (obtained) by the analyzer 13 recognizing the QR code 51 included in the additional crop image.

According to this, as described above, in the crop DB 14, information is stored in a form in which [individual crop ID-bad number-image information] is linked to each other for each real crop (or for each crop in the identified image) In this case, in the case of a real harvested crop harvested by a user, QR code information is further added so that [individual crop ID-bad number-image information-QR code information (i.e., URL information)] is mutually Information can be stored and managed in an associated form. That is, among the information of crops in the image corresponding to the real crops stored in the crop DB 14, information on the crop in the image corresponding to the real crop harvested as an example is a QR code ( 51) can be referred to as crop information in the corresponding QR image, which is in the form of [individual crop ID-bad number-image information-QR code information (i.e., URL information)] linked to each other. can be stored and managed.

In addition, the present system 1 may include a user terminal 40 possessed by the user. At this time, the user terminal 40 packs a harvested real crop (for example, a first harvested real crop), which is any one real crop harvested by the user among real crops grown on the plurality of crop beds 20. After photographing the QR code 52 provided on one area of the packaging material, manually input the growth information of the harvested real crop (first harvested real crop) on the web page provided by the photographing of the QR code 52 can be uploaded.

In other words, when it is detected that the user has photographed the QR code 52 provided in one area of the packaging material, the user terminal 40 recognizes the photographed QR code 52 and the URL information stored in the recognized QR code 52. A web page corresponding to may be displayed on the screen of the user terminal 40 . That is, the control unit 16 can control the operation (screen display) of the user terminal 40. For example, when the user terminal 40 detects the shooting of the QR code 52, the web page is displayed on the user terminal. The operation of the user terminal 40 can be controlled to be displayed (exposed) on the screen of (40).

Thereafter, the user measures the growth information of the actual harvested crop (ie, the first harvested actual crop) accommodated in the packaging material to which the QR code 52 is attached, and then the web page displayed on the screen of the user terminal 40. It is possible to manually input the growth information measured in (for example, directly input by typing) and press the save completion button. Accordingly, the user terminal 40 may upload (transmit, provide) the growth information received from the user through the web page to the device 10 in response to the user's click input on the storage completion button.

Here, the growth information is growth information about the actual harvested crop, and may include fresh weight (FW, live weight) information, dry weight (dry weight) information, and leaf area information. can

Fresh weight information is the most commonly measured indicator of cell growth (ie, one of the simplest measurable growth indicators), and refers to information about the weight of a real harvested crop in its current state. Dry weight information refers to information about the weight of a sample after performing an operation of removing water by an appropriate method. The leaf area information means information on the area (leaf area) of a leaf composed according to the size of the leaf, that is, the size of leaf length and leaf width.

At this time, as the method of measuring information such as fresh weight, dry weight and side area considered in the present invention, various methods of measuring growth information in the past or developed in the future may be applied, and detailed descriptions are omitted. do it with

When the growth information is uploaded from the user terminal 40, the crop management unit 15 is configured to input the growth information uploaded from the crop DB 14 (ie, among the information on crops in images stored in the crop DB). Identify crop information in an image having matching URL information that is matched with URL information corresponding to a page, and crop information (ie, individual crop ID information) in an image having matching URL information corresponds to the identified QR In the case of crop information in the image, the uploaded growth information may be further included (linked) in the information of the crop in the identified QR-corresponding image to be stored and managed in the crop DB 14.

That is, among information of crops in the image corresponding to real crops stored in the crop DB 14, information on crops in the image harvested by the user and input of growth information (i.e., information on crops in the QR-compatible image) The crop information in the image in which the growth information was input) can be stored and managed in a form in which [individual crop ID-bad number-image information-QR code information (i.e., URL information)-growth information] is linked to each other. .

On the other hand, the present system (1), when any one of the real crops is a harvested real crop harvested by the user, a pair of QR codes 50, 51, 52 provided for the harvested real crop can include

Here, the pair of QR codes 50, 51 and 52 may include a first QR code 51 and a second QR code 52, and may be provided in the form of a sticker including the same URL information.

Here, any one of the pair of QR codes 50 may mean the first QR code 51. One QR code (ie, the first QR code 51) of the pair of QR codes 50 indicates that after the harvested actual crop is harvested by the user, the harvested actual crop on the plurality of crop beds 20 is It may be attached to the location where it was harvested (ie, the location where the actual harvested crop was grown).

On the other hand, another one of the pair of QR codes 50 may mean the second QR code 52. Another QR code (ie, the second QR code 52) of the pair of QR codes 50 is the outer surface of the packaging material of the actual harvested crop harvested by the user after being packaged in the packaging material. It may be attached to one area of.

In one example of the present invention, the harvesting of at least one real crop among the real crops is illustrated as being made by the user (ie, done manually by the user) as an example, but this is one way to help understand the present invention. It is only an example of, but is not limited thereto, and harvesting of real crops may be performed automatically through a separately prepared harvesting device (harvesting device).

In addition, the harvested actual crops, which are real crops harvested in the present invention, may be packaged in a packaging material by a user (or a separately provided packaging device), for example. Here, the packaging material may be, for example, a zipper bag, but is not limited thereto, and the packaging material is a member capable of packaging (eg, airtight packaging) of harvested crops (real crops) such as a zipper bag, disposable vinyl, packaging container, disposable container, etc. Anything can be applied.

In addition, as described above, in the present invention, a pair of QR codes 50 are assigned to each crop harvested among real crops grown in a plurality of crop beds 20, and in this system 1 A pair of QR codes 50 may be provided in the same number as the number of actual harvested crops.

Hereinafter, the operating process of the present system 1 after the crop DB 14 is constructed in step 4 described above will be described in detail. That is, a specific utilization method of a pair of QR codes 50 will be described as follows.

After the crop DB 14 is built in step 4, as described above, the automatic collection device 30 photographs the actual crops every day during the growing period of the actual crops, and the device 10 that views the crop image generated by the photographing can be sent to At this time, for example, the crop management unit 15 performs image analysis on crop images collected (obtained) daily from the automatic collection device 30 (ie, additional crop images additionally collected), and individual crops of the crops in the image. It is possible to identify the ID and store and manage crop images collected in consideration of the identified individual crop ID information in an individual DB related to the corresponding crop image.

At this time, as shown in FIG. 5, for example, the user checks the growth state of real crops grown in the plurality of crop beds 20, and harvests real crops that need to be harvested among these real crops as real crops. can (step 5). At this time, it is assumed that a first real crop, which is one of the real crops, is harvested in step 5. This harvested first physical crop may be otherwise referred to by the term first harvested physical crop.

After the first real crop is harvested in step 5, the user then prepares a pair of QR codes 50, and then the location on the crop bed where the first real crop is harvested (ie, the crop bed where the first harvested real crop is harvested) The first QR code 51, which is one of the pair of QR codes 50 (51, 52), is attached to (step 6), and the first harvested real crop, which is the first real crop harvested thereafter, After packaging in a packaging material (for example, a zipper bag), a second QR code 52, which is the remaining QR code among the pair of QR codes 50, 51 and 52, may be attached to one area of the outer surface of the packaging material (step 7 ). At this time, steps 6 and 7 may be performed (progressed) by changing the order of each other.

Next, referring to FIG. 6, after the process of step 7 is performed, the automatic collection device 30 additionally (newly) at least some of the real crops grown in the crop bed to which the first QR code 51 is attached. ), and a new crop image generated by additional shooting may be generated as an additional crop image and transmitted to the device 10 . At this time, the automatic collection device 30 acquires the identification information of the crop bed by recognizing the tag for identification of the bed attached to one area of the crop bed to which the first QR code 51 is attached with a reader (not shown). After that, an additional crop image including identification information of the acquired crop bed may be transmitted to the device 10 .

Thereafter, when the additional crop image including the image of the first QR code 51 is collected (received) from the automatic collection device 30, the analyzer 13 analyzes the image of the collected additional crop image. 1 Identify the attachment location of the QR code 51 (ie, row/column information to which the QR code is attached on the crop bed), and identify the attachment location of the identified first QR code 51 to harvest the first harvest real crop It may be determined that the location (ie, the cultivation location on the crop bed where the first crop was grown before harvesting). Thereafter, the crop management unit 15 determines the first QR code 51 among information on crops in the image stored in the crop DB 14 based on the attachment position of the first QR code 51 identified by the analysis unit 13. The crop information in the image having the individual crop ID information corresponding to the attachment position of the crop is identified as crop information in the QR-corresponding image, and the crop information in the identified QR-corresponding image is actually harvested by the user (grower). It is determined that the information is of a real harvested crop, and the URL information pre-stored in the first QR code 51 is further included (linked) in the information of the crop in the identified QR corresponding image to be stored and managed in the crop DB 14. You can (step 8).

That is, in step 8, the analysis unit 13 identifies the attachment position of the first QR code 51 included in the additional crop image, and through this, the first QR code 51 harvested at the corresponding position is attached. After identifying (recognizing) the harvesting location of the actual harvested crop (that is, the cultivation location where the first harvested actual crop was grown), the crop management unit 15 then analyzes the image of the additional crop image and recognizes the first QR. The URL information of the code 51 corresponds to the attachment position of the identified first QR code 51 among the information on crops in the image stored in the crop DB 14 (or the harvest position of the identified first harvest real crop) It can be stored in association with crop information in images having individual crop ID information.

Thereafter, the user can measure the growth information of the first harvest real crops after taking the first harvest real crops packed in the packaging material out of the packaging material (step 9). Then, in order to record (save) the measured growth information of the actual crop of the first harvest in the crop DB 14 of the apparatus 10, the user may use the material attached to the outer surface of the packaging material in which the actual crop of the first harvest was wrapped. By photographing the second QR code 52 with the user terminal 40 possessed by the user, it is possible to access a web page corresponding to the URL included in the second QR code 52 (step 10). That is, when the user terminal 40 captures the second QR code 52 by the user, the web page corresponding to the URL information of the captured second QR code 52 is displayed on the screen of the user terminal 40. can be displayed on

Thereafter, the user may input (write) the growth information of the actual crop of the first harvest measured in step 9 into the web page displayed on the screen of the user terminal 40 (step 11). Thereafter, when the user clicks input on the storage completion button in the user terminal 40, the user terminal 40 can upload the growth information of the actual crop of the first harvest input from the web page to the device 10. there is.

Thereafter, the crop management unit 15 may store and manage the growth information uploaded from the user terminal 40 (growth information of the actual crop of the first harvest) in the crop DB 14 by linking it to the corresponding individual crop ID information. (step12). That is, in step 12, the crop management unit 15, when the growth information of the first harvest real crop is uploaded from the user terminal 40, in the crop DB 14 (ie, among the information of crops in the image stored in the crop DB) Matching URL information (that is, the first QR code (that is, the first QR code (that is, the first QR code After identifying the information of the crop in the image (that is, the information of the crop in the image corresponding to the individual crop ID information of the first harvest real crop) having the URL information of 51), uploaded to the information of the crop in the identified image The growth information of the actual crops of the first harvest may be stored and managed in the crop DB 14 by linking them together.

According to this, by utilizing a pair of QR codes 50 (51, 52), the device 10 transmits the growth information on the real crops harvested by the user to the second QR code using the user terminal 40 ( 52), and furthermore, the entered growth information can be automatically recorded (saved) in the crop DB 14 of the present device 10 and converted into a database so that it can be managed.

The control unit 16 may control the operation of each unit included in the device 10 . In addition, the control unit 16 can control the operation of the automatic collection device 30 interlocked with the device 10 through the network 2, and interlocked with the device 10 through the network 2. Operation of the user terminal 40 (for example, screen display) may be controlled.

In other words, in the present system 1, the automatic collection device 30 recognizes the crop bed using RFID, and then the automatic collection device 30 takes a crop image (eg, a video or image) while moving, and the device (10) can be sent. In this case, the crop image may be an image (image) related to at least one of RGB, depth, hyperspectral, and thermal images.

Thereafter, the collection unit 11 may store crop images collected from the automatic collection device 30 in the image DB 12, and for example, when the collected crop images are videos, key frames are extracted from the videos at regular intervals. and stored in the image DB 12. Thereafter, the analysis unit 13 extracts feature points from adjacent crop images (ie, adjacent key frames) from the crop images stored in the image DB 12 (in other words, a plurality of key frames), compares them, and performs image matching. By performing this, it is possible to generate one mosaic image for each of the plurality of crop beds 20 . Here, the mosaic image may be otherwise referred to as the above-described integrated crop image data. That is, the analysis unit 13 may generate one mosaic image (ie, integrated crop image data) for each crop bed through preprocessing (image preprocessing process) such as comparison and image matching after feature point extraction. Illustratively, in each of the plurality of crop beds 20, 1200 actual crops corresponding to 200 horizontally and 6 vertically may be cultivated.

The analysis unit 13 individually recognizes each of the crops (ie, crops in the image) in the integrated crop image data for each crop bed by applying a deep learning model and performing image processing on the integrated crop image data for each crop bed ( can be identified). At this time, by applying a deep learning model and applying image processing, row/column information for each of the crops (crops in the image) included in the integrated crop image data for each crop bed can be identified (recognized), This may be the same as the image corresponding to step 3 in FIG. 3 . That is, the screen as a result of recognizing rows and columns of individual crops in the integrated crop image data by applying the deep learning model may be the same as the image shown in step 3 of FIG. 3 . Thereafter, the crop management unit 15 may assign an individual crop ID to each of the crops in the individually recognized image (ie, assign an ID for each individual crop).

In the above-described example of the present invention, when the automatic collection device 30 captures a crop image and transmits it to the device 10, the device 10 performs 'comparison of feature points based on the crop image, image matching, and integrated crop image' Although the process of generating data and assigning individual crop IDs has been exemplified as processing, this is only an example to help understanding of the present invention, but is not limited thereto. As another example, the process of 'comparison of feature points based on crop images, image matching, generation of integrated crop image data, and assignment of individual crop IDs', which is exemplified by the apparatus 10, is carried out by the automatic collection device 30 In this case, when the automatic collection device 30 transmits information on each of the crops in the image to which individual crop IDs have been assigned (ie, information on crops in the image) to the device 10, it is transmitted to the crop management unit ( 15) may directly store the corresponding information in the crop DB 14.

As mentioned above, in the crop DB 14 in the apparatus 10, individual DBs may be built for each individual crop ID. In addition, the apparatus 10 may obtain time-sequentially data such as crop images collected through the automatic collection device 30 every day during the growth period of real crops, store them in the crop DB 14, and manage them. The apparatus 10 may build data based on individual crop IDs.

The user may select crops to be harvested for each growth of the crops at random in consideration of the growth conditions of actual crops, and then harvest the crops. Then, the user prepares a pair of QR code 50 stickers, attaches the first QR code 51 of the pair of QR codes 50, 51, 52 to the harvested part of the real crop, and then After putting the harvested real crop into a packaging material (for example, a zipper bag), the second QR code 52, which is the remaining QR code, may be attached to the outer surface of the packaging material.

Thereafter, the automatic collection device 30 recognizes the first QR code 51 in the automatic collection device 30 to recognize the location of the harvested real crop, and provides related information (eg URL of the first QR code 51). information) to the device 10. Thereafter, the device 10 may further store and manage related information obtained from the automatic collection device 30 in the crop DB 14 .

Thereafter, the grower can take out the crop contained in the packaging material, measure the growth information, photograph the second QR code 52 attached to the packaging material with the user terminal 40, and access the corresponding web page. Then, the user can fill in the growth information on the web page and then upload it, and through this, the crop management unit 15 transmits the uploaded growth information to the crop DB 14 corresponding to the corresponding growth information (i.e., the actual harvested product). Crops) can be further stored and managed by linking them to individual crop IDs.

This present system 1 is a greenhouse crop management system, and may be otherwise referred to as a greenhouse crop data collection system.

This system 1 and this device 10 automatically collect crop images using various image sensors 31 in commercial farms, automatically assign individual IDs for each crop (by actual crop), and then For each of the actual crops to which individual IDs have been assigned, the growth information, which is manually measured by the user (the grower), is easily stored in the crop DB 14, especially with related images (crop image or integrated crop image data). It can be stored and managed in a combined (associated) state.

In the present invention, the crop image captured by the automatic collection device 30 is an image (image) captured by various sensors (image sensor), and may be, for example, at least one of RGB, depth, hyperspectral, and thermal images. there is.

In addition, in the present invention, the growth information stored in the crop DB 14 is obtained by a user (grower) directly harvesting a real crop, measuring the growth information, and then manually inputting the data through the user terminal 40 ( That is, manual data). As described above, such growth information may include information such as live weight, dry weight, and leaf area of crops (actual crops).

Several beds (that is, a plurality of crop beds 20) may be provided inside the greenhouse considered in this system 1, and in each crop bed, tens to hundreds of crops (actual crops) are accommodated/cultivated. It can be.

As described above, the automatic collecting device 30 may be a gantry system or a mobile robot, and may capture and collect crop images. The automatic collection device 30 may collect data (crop images) while moving to various locations within the greenhouse through automatic control by the controller 16. RFID may be previously attached to each bed, and the automatic collection device 30 may recognize unique identification information of each bed through RFID recognition while moving.

In this system 1, the automatic collection device 30, for example, captures (collects) images of crops in time series while automatically assigning IDs (ie, individual crop IDs) to crops (actual crops) in the greenhouse. )can do. In addition, the automatic collection device 30 may collect crop images while moving several beds, and recognize the identification information of the corresponding bed through the recognition of the RFID previously attached to each bed. In addition, the automatic collection device 30 takes, for example, a crop image (eg, a video), and then extracts a specific frame from the captured crop image and creates a mosaic image (ie, integration) for each bed through image registration. By generating crop image data) and performing image analysis (deep learning analysis) on the mosaic image, an individual crop ID can be automatically assigned to each crop in the image (ie, each real crop). Thereafter, after the automatic collection device 30 completes identification (individual recognition) of crops in the image through image processing (or deep learning analysis) and assignment of individual crop IDs, each crop (ie, crops in the image) Each or each of the actual crops) can be determined (identified, grasped) at which point (row/column) within which bed.

In addition, the automatic collection device 30 captures additional crop images through the image sensor 31 of the QR code (ie, the first QR code 51) attached by the user (the grower) after harvesting a specific real crop. It can be recognized through image analysis of the image, and through this, it is possible to automatically identify (recognize, discriminate) which actual crops with individual crop IDs have been harvested.

The apparatus 10 transmits manual data (manually inputted growth information, in particular, measured growth information) entered by a user (grower) after harvesting a real crop to the user terminal 40. It can be collected from and stored in the crop DB 14. At this time, when the user enters the measured growth information, the device 10 does not need to separately care about the individual crop ID given to the harvested actual crop corresponding to the measured growth information, and the individual crop ID It is possible to easily upload and store the growth information of the corresponding crop (harvested actual crop) to the crop DB 14 by photographing the QR code (particularly, the second QR code 52) without worrying about what is.

To this end, in the present invention, QR codes may be provided in the form of stickers, and configured in pairs of two to include the same content (ie, the same URL information). That is, in the present invention, a pair of QR codes 50, 51 and 52 may be provided. Such a pair of QR codes 50 may be otherwise referred to as a pair of QR code stickers or the like.

The user (grower) manually selects and harvests the crop (actual crop) whose growth information is to be measured, and then harvests one QR code (ie, the first QR code 51) of the pair of QR codes 50. It is attached to one spot (ie, the harvesting position on the crop bed), and the remaining QR code (ie, the second QR code 52) is attached to the packaging material (eg, zipper bag, plastic bag, etc.) containing the harvested crop. can The user (grower) may measure the growth information of the harvested crop and input (write) the corresponding information (measured growth information) by taking a second QR code 52 using the user terminal 40 . At this time, when the user captures the second QR code 52 with the user terminal 40, in response to this, the user terminal 40 is connected to the server and the screen of the user terminal 40 displays a web page for writing growth information. (That is, a web page corresponding to URL information in the second QR code) may be displayed (exposed).

Since the automatic collection device 30 has already recognized the QR code (ie, the first QR code) attached to the crop bed 20, the device 10 determines the ID (individual crop ID) assigned to the real crop harvested by the user. ), just fill in the growth information measured on the web page displayed on the screen of the user terminal 40 and press the save completion button without having to worry about what the user terminal 40 is. Data (i.e., growth information input by the user) can be stored (recorded) and managed in the crop DB (14) by being automatically linked to the individual crop ID of the relevant crop (i.e., actual harvested crop). there is. In particular, in the apparatus 10, when the user presses the storage completion button, the growth information input by the user is stored in an individual DB (i.e., It can be automatically linked and stored (recorded) in individual DB) of actual harvested crops.

This system 1 and this device 10 enable the user to record and manage crop information quickly and efficiently without the hassle (convenience) of harvesting a specific crop and recording and managing the harvested crop information. can make it In addition, the device 10 may provide the following functions.

For example, in the previous example, when the second QR code 52 is photographed in the user terminal 40, the control unit 16 sends a web page corresponding to the URL information stored in the second QR code 52 to the user terminal. As displayed on the screen of (40), it is exemplified that the user can input (write) the growth information of the harvested real crop through the web page, but this is not limited thereto. As another example, the control unit 16 determines whether the user's selection input for the information providing button provided in one area of the screen of the user terminal 40 is made when the second QR code 52 is captured by the user terminal 40. Depending on whether or not, the type of data displayed (exposed) on the screen of the user terminal 40 may be differently controlled.

Specifically, the controller 16 may display an information providing button on one area of the screen of the user terminal 40 when the user terminal 40 is in a QR code recognition mode (ie, camera activation state).

At this time, the control unit 16 requests input (write) of growth information when the second QR code 52 is photographed without the user's selection (click) input for the information providing button in the user terminal 40. Recognized as a signal, a web page corresponding to the URL information stored in the second QR code 52 can be displayed on the screen of the user terminal 40, and through this, input of growth information measured for the actual harvested crop in the packaging material can make this possible.

On the other hand, if the second QR code 52 is photographed after the user selects (clicks) the information providing button in the user terminal 40, the control unit 16 converts it into information stored in the crop DB 14 ( Recognize it as a signal requesting the provision of all information recorded in relation to the actual harvested crop contained in the packaging material to which the second QR code 52 is attached (i.e., information on the actual harvested crop) among the information of the crops in the image), Extract information of the crop in the image having matching URL information that matches the URL information of the second QR code 52 in the crop DB 14 (ie, information stored in association with individual crop ID information of the actual harvested crop) It can be displayed (exposed) on the screen of the user terminal 40. According to this, the user separately accesses and logs in to the device 10 to view stored records (for example, record history information such as growth information or image information) of the actual crop to be harvested, and directly searches for the ID of the actual crop to be harvested. Without the hassle of confirming by simply clicking the information provision button and then taking a picture of the second QR code 52, the information about the harvested real crop stored in the crop DB 14 (record s) can be easily provided to the user terminal 40 (portable terminal such as a smart phone) and immediately checked.

That is, when the second QR code 52 is captured without clicking the information providing button in the user terminal 40, the control unit 16 provides a web page where growth information can be entered, while after clicking the information providing button, the second QR code 52 is provided. When the QR code 52 is photographed, information of the actual harvested crop stored in the crop DB 14 may be provided.

In addition, the control unit 16 may generate a growth diagnosis list that allows the user to self-diagnose (check, check) the growth status of crops (actual crops) grown by the user, and provide the generated list to the user terminal 40. there is. The growth diagnosis list may be pre-generated by the control unit 16 based on abnormal state information for each crop type collected online. Such a growth diagnosis list may refer to a list including items (questions) that need to be checked (checked) in order for the user to self-diagnose whether there is a disease, abnormality, problem, symptom, etc. for each crop type. Such a growth diagnosis list may be pre-generated according to the characteristics of each crop type.

At this time, in diagnosing (checking) the current state or abnormality of the crops (actual crops) that the user cultivates through this growth diagnosis list, the user's diagnosis convenience (ie, the convenience of deriving self-diagnosis results) To this end, the controller 16 may provide a growth diagnosis list as follows.

As described above, the user terminal 40 may be, for example, a portable wireless communication device such as a smart phone, a smart pad, a tablet PC, a laptop computer, or a wearable device.

Specifically, the control unit 16 may control the operation (for example, screen display) of the user terminal 40 . At this time, the control unit 16, when a list provision request is made from the user terminal 40 (for example, when the user clicks a list provision button displayed on one area of the screen), the controller 16 sends the previously generated growth diagnosis list to the user terminal 40. ) is displayed on the screen, but one screen of the user terminal 40 among the plurality of items is displayed on the screen of the user terminal 40 in consideration of the screen liquid crystal size of the user terminal 40 and the number of letters in the plurality of items in the growth diagnosis list. The maximum number of items exposed to can be adjusted differently. The user can self-diagnose the current state or abnormality of actual crops being cultivated based on the growth diagnosis list provided by the control unit 16 .

Information on the items in the growth diagnosis list (number of items, content of items, etc.) may be set, changed, and managed by, for example, a manager who manages the apparatus 10 . Items in the growth diagnosis list may be referred to differently by terms such as diagnosis items, diagnosis check items, and diagnosis items. The growth diagnosis list may include a plurality of items (for example, a plurality of quality information), and as examples of the plurality of items, 'if the crop is cabbage, are there black spots distributed on the outer surface?', 'the crop is spinach In the case of , are the leaves of spinach yellow?'

At this time, when displaying (displaying) the growth diagnosis list on the screen of the user terminal 40, the controller 16 displays the growth diagnosis list as the first standard if the screen liquid crystal size of the user terminal 40 falls within the first criterion. If the screen LCD size belongs to the second criterion larger than the first criterion, the growth diagnosis list is displayed in the second display method, and if the screen LCD size belongs to the third criterion larger than the second criterion, The growth diagnosis list can be displayed in a third display method. Here, the screen liquid crystal size of the user terminal 40 may mean the size of the liquid crystal panel of the display screen of the user terminal 40 .

In addition, the first display method is a method of sequentially displaying each of the plurality of items in the growth diagnosis list on the screen one by one, and the second display method is an item displayed on one screen of the user terminal 40 It is a method of displaying on the screen as many items as the number of items so that the total number of characters is less than a preset maximum number of characters (eg 50 characters), and the third display method is a method of displaying all of the plurality of items on the user terminal 40 It may mean a method of displaying within one screen of.

In addition, the first criterion is a range corresponding to the size of the screen liquid crystal of the user terminal 40, which is less than 10 inches, and the second criterion is a range corresponding to a size of 10 inches or more and less than 19 inches. range, and the third criterion may be a range corresponding to the screen liquid crystal size of 19 inches or more. At this time, specific examples of numerical values mentioned in the present invention are only one example to help understanding of the present invention, and specific numerical values can be set and changed in various ways by an administrator who manages the device 10 .

Further, in the growth diagnosis list, a response field for each of the plurality of items may be provided in a form in which, for example, one option among a plurality of options is selected. Illustratively, the plurality of options may include a first option for selecting 'YES' and a second option for selecting 'NO'.

Mobile terminals such as smartphones (cell phones) that people usually carry exist in various sizes such as 6-inch, 7-inch, and 8-inch screen liquid crystals, and tablet PCs or laptops such as the Galaxy Tab are portable, but rather than mobile phones. The size of the screen liquid crystal is larger and has a screen liquid crystal size of 10 inches or 11 inches, and desktop PCs tend to have a relatively large screen liquid crystal size compared to mobile phones and tablet PCs such as 19 inches or more.

As such, each user who uses the device 10 may have a different screen liquid crystal size of a terminal he or she possesses. However, without considering the characteristics of terminals having various screen liquid crystal sizes, the growth diagnosis list is simply fixed to a single display method for the user terminal 40 (eg, all information of the growth diagnosis list is displayed on one screen). If it is provided in a display method in which all items are displayed), a user possessing a user terminal 40 having a relatively small screen liquid crystal size, the contents of each item included in the growth diagnosis list through the user terminal 40 When checking the items, the text in each item is too small to understand at a glance, so there was inconvenience (convenience) of having to make a gesture such as enlarging the screen separately.

Accordingly, when displaying the growth diagnosis list on the screen of the user terminal 40, the controller 16 considers the size of the screen liquid crystal of the user terminal 40 and the number of letters of a plurality of items in the growth diagnosis list. The number of items displayed on one screen of (40) can be flexibly adjusted differently.

Exemplarily, for the second display method, for example, a total of 15 items are included in the growth diagnosis list, the number of letters in the first item is 8, the number of letters in the second item is 10, and the number of letters in the third item is 8. Suppose that the number of characters in is 9 characters, the number of characters in the 4th item is 15 characters, the number of characters in the 5th item is 10 characters, and so on. At this time, the controller 16 may display the growth diagnosis list on the screen of the user terminal 40 in the second display method when the screen liquid crystal size of the user terminal 40 is 12 inches. At this time, since the total number of characters by adding all the numbers of characters from the first item to the fifth item is 52 characters, which exceeds the preset maximum number of characters (for example, 50 characters), the control unit 16 determines the preset maximum number of characters. Only up to four items (ie, the first to fourth items) are displayed on one screen of the user terminal 40 on the first page in relation to the growth diagnosis list in order to be displayed on the screen by the number of items that are less than or equal to the number of items. can do. The controller 16 may differently control the number of items displayed on one screen in this way.

In addition, in a state where the growth diagnosis list is displayed on the screen of the user terminal 40 in the first display method, the control unit 16 provides a response to the first item in relation to the first item displayed on the screen among the plurality of items. When an input (press input) is made to press any one of the plurality of options corresponding to item 1 for more than a preset time (eg, 1.5 seconds), the screen for the second item located next to the first item in the growth diagnosis list The second item may be displayed on the screen of the user terminal 40 by determining the display request signal.

In addition, when the controller 16 displays the growth diagnosis list on the screen in the first display method (that is, when only one item among a plurality of items is displayed on one screen), each item is displayed on the user terminal. (40) can be displayed in a full form on one screen (ie, a form that can be displayed large on one screen by increasing the number of characters as much as possible).

Regarding the first display method, for example, after the first item is displayed on the screen of the user terminal 40, the user presets the option 'YES' in the response column as a response to the first item. It can be pressed and released for more than a time (eg, 1.5 seconds). In this case, the controller 16 recognizes this as a request signal to display the second item located next to the first item in the growth diagnosis list on the screen, The second item, which is the next item, may be automatically displayed on the screen of the user terminal 40 . The controller 16 can display each of the plurality of items in the growth diagnosis list on the screen one by one as described above.

According to this, the controller 16 displays the growth diagnosis list in various types (first to third display methods) in consideration of the size of the screen liquid crystal of the user terminal 40 and the number of letters of each item in the growth diagnosis list. It can be displayed so that the user can conveniently and quickly input responses to each item (selective input, check) without the hassle of separately expanding or reducing the screen, and can check each item without any inconvenience. there is.

That is, the present device 10 can provide a user with a faster, hassle-free and convenient way to check each of a plurality of (for example, 40) items included in the growth diagnosis list. As a result, the user It can provide the convenience of self-diagnosis of the current state (whether there is an abnormality) of various types of crops grown by oneself, and the current state of the cultivated crops can be quickly checked (checked) to take action if there is an abnormality can be taken quickly.

Also, the controller 16 may display (provide) a store information providing button on one area of the screen of the user terminal 40 . Here, the store information provision button is a button requesting the provision of information on the store, and at this time, the store refers to the related products (eg, crop beds, non-pesticides, It may mean an offline store (ie, an agricultural material store) that sells crop seeds, temperature sensors, humidity sensors, etc.).

For example, when a user clicks a store information providing button displayed on one area of the screen after selecting the type of product desired to be purchased on the user terminal 40, the control unit 16 in response to this selects the store DB in the device 10 ( (not shown) information on a plurality of agricultural material stores pre-registered (in particular, information on a plurality of agricultural material stores that sell the type of product the user wants to purchase) may be provided.

The sales store DB (not shown) may store the company name, business hours, address, etc. of the agricultural material store as information on the agricultural material store. The store DB may be provided in the device 10 . When providing information on a plurality of agricultural material stores to the screen of the user terminal 40, the control unit 16 may display a store display map in which locations of the plurality of agricultural material stores are indicated by mark icons on the screen. .

When displaying the store display map, the control unit 16, based on the selection time when the user selects (clicks) the store information providing button, corresponds to an available agricultural material store that can be used at the time of selection among a plurality of agricultural material stores. The mark icon may be displayed in a form that is easier to identify than a mark icon corresponding to an unavailable agricultural material store that is unavailable at the time of selection.

At this time, displaying the mark icon corresponding to the available agricultural material store in a form that is easier to identify than the unavailable agricultural material store is, for example, a form displayed in a different color, a visually emphasized form (eg, available It may mean displaying at least one of a form in which the color or thickness of the border line of the mark icon corresponding to the agricultural material store is darker and thicker) and a form in which the size is expanded.

For example, the user selects (clicks) a store information provision button in order to be provided with information on agricultural material stores located around the user based on their current location (current GPS location information of the user terminal 40) Suppose that there are three agricultural material stores located around the current location of the user. In this case, the control unit 16 displays a store display map on the screen in which the locations of three agricultural material stores (ie, the first agricultural material store to the third agricultural material store) are displayed as mark icons as a plurality of agricultural material stores. can do.

Here, each agricultural material store has business hours (for example, the first agricultural material store is 24 hours, the second agricultural material store is 6:00 to 23:00, the third agricultural material store is 5:00 to 23:00, etc. ), etc., may be different. In addition, each agricultural material store may have different closing times (business hours) due to personal circumstances (personal circumstances of the president who runs each agricultural material store), vacation period schedule differences, and the like.

For example, at the time when the user selects the store information provision button (corresponding time zone), the first agricultural material store and the second agricultural material store are operating normally, and the third agricultural material store is not currently operating due to personal circumstances. Let's call it a state. In this case, the controller 16 may recognize the first agricultural material store and the second agricultural material store as usable agricultural material store, and recognize the third agricultural material store as unavailable agricultural material store.

Accordingly, the control unit 16 converts the mark icon corresponding to the available agricultural material store (ie, the first/second agricultural material store) to the mark icon corresponding to the unavailable agricultural material store (ie, the third agricultural material store) In contrast, it can be displayed on a store display map in a form that is easier to recognize or identify. Illustratively, the control unit 16 displays a mark icon corresponding to an available agricultural material store in a larger size, a darker color, or a flickering icon corresponding to an unavailable agricultural material store compared to a mark icon corresponding to an unavailable agricultural material store. You can change the display by adding a difference, such as adding an effect.

In this way, the control unit 16 considers the closing time (sudden closing time) due to personal circumstances and vacation period schedule differences for each agricultural material store based on the time point (selection time) when the user selects the store information providing button. Considering the set business hours, the currently available agricultural material store and the currently unavailable agricultural material store are distinguished and displayed differently at the time of selection when the store information provision button is selected, so that the user is operating at the current time. Since it is possible to more intuitively grasp information on available agricultural material stores, it is possible to help users find and use available agricultural material stores quickly without wandering.

Here, the closing time (sudden closing time) information (that is, whether the door is closed due to personal circumstances, whether the door is closed due to a vacation period, etc.) for a specific agricultural material store is, for example, the corresponding agriculture It can be determined through real-time analysis of social data uploaded by a plurality of users on the Internet in relation to a material store. This closing time information may refer to information on closing time separately from the business hours registered in the store DB (not shown). Social data may refer to data such as posts uploaded to Instagram and Facebook, blogs such as Naver, and news articles, for example.

According to this, the user can easily find, for example, an agricultural material store located close to his or her current location or a specific location directly designated by the user through a store display map in which the locations of a plurality of agricultural material stores are displayed.

In particular, the user can more easily and quickly find and use an available agricultural material store that is currently immediately available among a plurality of agricultural material stores displayed on the store display map. For example, the user can use a specific agricultural material store (eg If you visit a store that sells crop beds, a store that sells crop seeds, etc.) and cannot use it because the door is closed due to vacation, etc., you can solve the inconvenience of having to go to another agricultural material store again. In addition, there is no need for the user to call the corresponding agricultural material store one by one and inquire whether it is currently available (ie, whether a specific product can be purchased), etc. Information on available agricultural material stores can be grasped and used more intuitively and quickly.

In addition, the analysis unit 13 performs image analysis using a pre-learned deep learning model on each of the integrated crop image data for each crop bed, thereby identifying (individually recognizing) the crops in the image from the integrated crop image data for each crop bed. Among them, it is possible to analyze whether there is a crop in the abnormal image, which is a crop in the image with an abnormality.

Here, the analysis unit 13 compares, for example, the 'size of a crop in a certain image' among the crops in an image with the 'average of the sizes of crops in a neighboring image' adjacent to it (that is, the crop in a certain image). Therefore, if it is out of the preset allowable size range, it is determined (detected, identified) that the crop in any one image outside the preset allowable size range is an abnormal (in particular, slow-growing) crop in the image. Can be. Here, the size of the crop in the image may be, for example, information derived based on the pixel area (number of pixels) occupied by the crop in the corresponding image in the integrated crop image data. Illustratively, in the case of a crop in the image located in 3 rows and 3 columns on the first crop bed 21, the number of crops in the neighboring image is 8 in total (ie, 2 rows and 2 columns, 2 rows and 3 columns, 2 rows and 4 columns, 3 rows and 2 columns, 3 rows and 4 columns, 4 rows and 2 columns, 4 rows and 3 columns, and 4 rows and 4 columns respectively), and the analysis unit 13 may be these crops in the image. By comparing the average value of the sizes of crops in eight neighboring images with the size of crops in any one image, it is possible to determine whether a crop in any one image is a crop in an abnormal image.

At this time, if the analysis unit 13 analyzes that crops in the abnormal image exist, the control unit 16 may generate notification information about the existence of crops in the abnormal image and provide the notification information to the user terminal 40 . At this time, the notification information may include notification text information, abnormal symptom information of crops in the abnormal image, and cultivation location information of the crop in the abnormal image (ie, row/column information on the crop bed where the crop in the abnormal image is located). there is. Here, the notification information may exemplarily be information such as 'Please check that the actual crops grown in the 5th row and 68th column of the second crop bed appear to have slow growth (growth)'. Thereafter, the user can check the notification information provided through the user terminal 40, visit the inside of the greenhouse, directly check the state of the crop in the abnormal image, and take action if necessary.

That is, the user receiving the notification information from the control unit 16 directly checks the state of the crop in the abnormal image corresponding to the notification information (ie, the crop in the abnormal image, which is a real crop with abnormality). You can visit inside the greenhouse, where it is located.

At this time, when the controller 16 detects that the user who has received the notification information activates the camera of the user terminal 40 to ON and positions the camera so that the space inside the greenhouse is displayed on the user terminal 40 ( That is, when it is detected that the greenhouse interior image for the space inside the greenhouse is displayed on the screen of the user terminal 40), on the greenhouse interior image displayed on the screen of the user terminal 40, corresponding to the notification information The operation of the user terminal 40 may be controlled so that the location of the crop (or the ideal real crop) in the ideal image is displayed.

That is, the control unit 16, when the user who has been provided with the notification information uses the user terminal 40 possessed to illuminate the interior space of the greenhouse with a camera, the user displays the inside of the greenhouse displayed on the screen of the user terminal 40. It is recognized as a signal requesting display of the location of the crop in the abnormal image corresponding to the crop in the abnormal image on the image, and marks the part corresponding to the crop in the abnormal image on the image inside the greenhouse displayed on the user terminal 40 (for example, displaying a circle, blinking the corresponding area, etc.), or information on the remaining separation distance from the current position of the user terminal 40 to the position of the crop in the abnormal image (ie, movement path information about how many meters are left, etc.) etc.) can be overlaid on the inside image of the greenhouse being displayed (exposed) on the screen of the user terminal 40 to be displayed. Here, the current location of the user terminal 40 may be obtained using a GPS sensor built into the user terminal 40 .

At this time, when the control unit 16 displays a part corresponding to the crop in the abnormal image as a mark on the image inside the greenhouse, the controller 16 determines which of the plurality of crop beds 20 the crop in the abnormal image is located in and which crop bed is located in the corresponding crop bed. Comprehensively considering cultivation location information such as which row/column it is located in, current location information of the user terminal 40, and orientation information of the camera based on posture information of the user terminal 40, etc. A part (region) corresponding to the crop in the abnormal image may be displayed as a mark.

By providing this function, the device 10 receives notification information and when the user actually visits the space inside the greenhouse where the abnormal real crop is being grown in order to directly check the abnormal real crop corresponding to the crop in the abnormal image. At this time, by turning on the camera and illuminating the space inside the greenhouse, you can determine where the actual crop corresponding to the crop in the ideal image (i.e., the abnormal real crop) is located (i.e., the cultivation location of the ideal real crop) within the space inside the greenhouse. ) can be recognized/identified more intuitively and quickly, and accordingly, it is possible to provide prompt symptom checks and actions for crops in abnormal images, and to provide users with the convenience of managing a vast amount of cultivated crops. there is.

Hereinafter, based on the details described above, the operation flow of the present invention will be briefly reviewed.

7 is an operational flowchart of a greenhouse crop management method according to an embodiment of the present invention.

The greenhouse crop management method shown in FIG. 7 may be performed by the apparatus 10 described above. Therefore, even if the content is omitted below, the description of the device 10 can be equally applied to the description of the greenhouse crop management method.

Referring to FIG. 7 , in step S11, the collection unit may collect crop images from the automatic collection device and store them in an image DB.

Next, in step S12, the analysis unit may identify crops included in the preprocessed crop image through image analysis of the preprocessed crop image obtained by preprocessing the crop image stored in the image DB.

Next, in step S13, the crop management unit may store and manage information on the identified crops in the image in a crop DB.

In the foregoing description, steps S11 to S13 may be further divided into additional steps or combined into fewer steps, depending on an embodiment of the present invention. Also, some steps may be omitted if necessary, and the order of steps may be changed.

The greenhouse crop management method according to an embodiment of the present invention may be implemented in the form of program commands 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. alone or in combination. Program instructions recorded on the medium may be those specially designed and configured for the present invention or those known and usable to those skilled in 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 hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to act as one or more software modules to perform the operations of the present invention, and vice versa.

In addition, the greenhouse crop management method described above may be implemented in the form of a computer program or application stored in a recording medium and executed by a computer.

The above description of the present invention is for illustrative purposes, and those skilled in the art can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts should be construed as being included in the scope of the present invention. do.

1: Greenhouse crop management system
10: greenhouse crop management device
11: collection unit 12: image DB
13: analysis unit 14: crop DB
15: crop management unit 16: control unit

Claims (5)

A plurality of crop beds disposed inside the greenhouse; an automatic collecting device for transmitting crop images generated by photographing actual crops grown in the plurality of crop beds; greenhouse crop management devices; And when any one of the real crops is a harvested real crop harvested by a user, a pair of QR codes provided for the harvested real crop,
The greenhouse crop management device,
a collection unit that collects crop images from the automatic collection device and stores them in an image DB;
Through image analysis of the pre-processed crop image obtained by pre-processing the crop image stored in the image DB, crops in the image included in the pre-processed crop image are identified, and a QR code is generated in the additional crop image additionally collected by the collection unit. an analysis unit that determines whether or not the QR code exists and identifies an attachment position of the QR code if the QR code exists as a result of the determination;
Store and manage the information of the identified crops in the image in the crop DB, but based on the attachment position of the QR code identified in the analysis unit, URL information pre-stored in the QR code is further stored and managed in the crop DB a crop management unit configured to further store and manage the uploaded growth information in the crop DB when growth information of a harvested real crop among the real crops is uploaded from a user terminal; and
Including a control unit for controlling the operation of the user terminal,
The pair of QR codes is provided in the form of a sticker containing the same URL information,
After the first real crop, which is any one of the real crops, is harvested, the first QR code, which is any one of the pair of QR codes, is then harvested by the user. The second QR code, which is the remaining QR code among the pair of QR codes, is attached to one area of the outer surface of the packaging material in which the first real crop, which is the first real crop harvested by the user, is packed,
The analysis unit,
When the additional crop image including the image of the first QR code is collected from the automatic collection device, the attachment position of the first QR code is identified through image analysis of the collected additional crop image, and the identified first QR code Determining the attachment position of the first harvested actual crop as being the harvested position,
The crop management unit, based on the attachment location of the first QR code identified by the analysis unit, crops in the image having individual crop ID information corresponding to the attachment location of the first QR code among information on crops in the image stored in the crop DB The information of the crop is identified as the information of the crop in the QR corresponding image, and the information of the identified crop in the QR corresponding image is determined to be the information of the actual harvested crop that has been actually harvested by the user, and is pre-stored in the first QR code. Store and manage the URL information in the crop DB by further linking the URL information to the information of the crop in the identified QR-compatible image,
The user terminal measures the growth information of the first harvest real crop after the user removes the first harvest real crop packaged in the packaging material from the packaging material, and records the measured growth information of the first harvest real crop in the crop DB. When the second QR code attached to the outer surface of the packaging material in which the first crop was packaged is photographed, a web page corresponding to the URL information of the captured second QR code is displayed on the screen, and the measured When the user clicks on the storage completion button after inputting the growth information of the actual crops of the first harvest on the web page, the growth information of the actual crops of the first harvest input from the web page is uploaded to the greenhouse crop management device. do,
When the growth information of the actual crop of the first harvest is uploaded from the user terminal, the crop management unit matches URL information corresponding to the web page in which the growth information of the actual crop of the first harvest uploaded in the crop DB is input. After identifying crop information in the image with URL information, the growth information of the first harvest real crop uploaded to the crop information in the identified image is linked together to store and manage in the crop DB,
The control unit,
When the second QR code is captured by the user terminal, the type of data displayed on the screen of the user terminal is controlled differently depending on whether the user's selection input is made to the information providing button provided in one area of the screen of the user terminal. ,
When the second QR code is captured without the user's selection input for the information providing button in the user terminal, it is recognized as a signal requesting input of growth information, and the web page corresponding to the URL information stored in the second QR code is displayed to the user. It is displayed on the screen of the terminal so that it is possible to input the growth information measured for the actual crop harvested in the packaging material,
When the second QR code is photographed after the user's selection input for the information providing button at the user terminal, the information recorded in relation to the harvested actual crop contained in the packaging material to which the second QR code is attached among the information stored in the crop DB Recognizing it as a signal requesting provision, extracting crop information in an image having matching URL information matching the URL information of the second QR code in the crop DB and displaying it on the screen of a user terminal, greenhouse crop management system. According to claim 1,
The analysis unit,
The plurality of crop images stored in the image DB are divided into crop images related to each crop bed, and based on the crop images related to each crop bed, one integrated crop image data for each crop bed is converted to the preprocessed crop image. create as,
A greenhouse crop management system that identifies crops in the image by performing image analysis on each of the integrated crop image data for each crop bed. According to claim 2,
The crop management department,
Assigning an individual crop ID to each of the crops in the image identified by the analysis unit,
For each of the crops in the image, individual crop ID information assigned to the crop in the image, identification information of the crop bed in which the crop in the image is accommodated, and information linking the images including the crop in the image are combined with each other. A greenhouse crop management system that is stored and managed in a crop DB as information of. delete delete

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