KR20110067791A - System for diagnosing diseases and insects of crops and method thereof - Google Patents

Abstract

PURPOSE: A disease and insect pest diagnostic system of crops, and a method thereof are provided to diagnose the crops whether diseases and insect pests are occurred, and to offer subsequent actions in real time. CONSTITUTION: A disease and insect pest diagnostic system of crops comprises the following: a sensor module(102), a sensor management module(104), a crop image collecting block(106), a characteristic vector extraction block(108), a disease and insect pest diagnostic block(110), a disease and insect pest database(112), a controlling block(114), a display block(116), an alarm block(118), a growth environment control device(120), and a communication block(122).

Description

Pest diagnosis system of crops and its method {SYSTEM FOR DIAGNOSING DISEASES AND INSECTS OF CROPS AND METHOD THEREOF}

The present invention relates to a pest diagnosis technique of crops, and more particularly, to a pest diagnosis system and method for crops suitable for diagnosing the occurrence of pests of crops growing in a greenhouse using a pest database.

Recently, crop cultivation management systems that combine agricultural technology with u-IT technology have been developed and applied to agricultural sites one after another. In particular, these crop cultivation management systems have been widely used in the field of plant crop cultivation (greenhouse cultivation).

This crop cultivation management system is equipped with various control devices such as lighting, window opening, water supply, shading curtain, and ventilation fan to adjust the growth environment of the crop appropriately, thereby controlling the output per unit area in the plant crop. It is greatly increasing. Here, the plant crops may be, for example, vegetables, flowers, fruits and the like.

In addition, the crop cultivation management system constructs a pest database with pest information on various crops and pest control information for each crop, and retrieves the pest database through the user interface whenever necessary. By providing them, services are provided to properly respond to pests that may occur during the growth of facility crops.

In general, pests that can occur in a crop is very variable in the rate of spread depending on the type of crop and the growing environment of the greenhouse (facilities). For example, pests in crops can spread throughout the entire crop in the greenhouse in a few hours, or slowly spread over tens of hours.

On the other hand, the conventional crop cultivation management system provides a pest information search service for crops only through a user interface, so considering the above-mentioned pest occurrence environment, the manager (or pest control specialist) who grows the crops You will need to visit from time to time to check the growth of your crops.

In particular, the rapid follow-up of pest outbreaks, given that pests with a relatively high rate of spread may occur in the crop or that a growing environment may be formed in the greenhouse which allows the rate of spread of the pest to the crop to be relatively rapid. Even for the actions, managers (or pest control specialists) were forced to visit the greenhouse more often.

Therefore, in consideration of such a conventional problem, it is diagnosed in real time whether pests occur in the crops growing in the greenhouse, and when the occurrence of pests is diagnosed, the growth environment of the crops in the greenhouse is controlled to control the spread of pests, In addition, there is a real need for new crop management techniques that can alert crop managers to crop managers in real time and quickly. However, any proposals for these new crop management techniques are proposed. There is no situation.

According to one aspect of the present invention, there is provided a system for diagnosing pest occurrence in crops in a greenhouse, comprising: a pest database storing a plurality of pest image data for each crop, and a crop for the crops in the greenhouse. A crop image acquisition block for acquiring an image and converting the crop image data into a crop image data, a feature vector extraction block for extracting a feature vector from the crop image data using a feature vector extraction algorithm, and searching for the pest database; A pest diagnosis block for diagnosing the occurrence of pests for the crop by checking whether there is a particular pest image data matching the vector, a control block for performing audiovisual alarm control when the pest occurrence is diagnosed; In response to audiovisual alarm control It provides a diagnostic system of the crop pests comprising the audio-visual alarm means for audio-visual alarm pests occur.

The present invention is a system for diagnosing the occurrence of pests in a crop in a greenhouse, according to another aspect of the present invention, which stores a plurality of pest image data for each crop, and a pest spreading suppression environment for preventing the spread of each pest A pest database for storing information, a crop image acquisition block for obtaining crop images of crops in the greenhouse and converting them into crop image data, and a feature vector extracting feature vector from the crop image data using a feature vector extraction algorithm A pest diagnosis block for diagnosing the occurrence of pests for the crops by checking a vector extraction block, the pest database, and checking whether there is specific pest image data matching the extracted feature vector; From the pest database when A pest diagnosis system for crops including a control block for adjusting the growth environment of the greenhouse to a predetermined pest spreading suppression environment based on the extracted corresponding pest spreading suppression environment information.

The present invention, according to another aspect of the present invention, as a system for diagnosing the occurrence of pests in a crop in a greenhouse, storing a plurality of pest image data for each crop, and suppressing pest spread for preventing the spread of each pest A pest database for storing environmental information, a crop image acquisition block for obtaining crop images of crops in the greenhouse and converting them into crop image data, and extracting feature vectors from the crop image data using a feature vector extraction algorithm. A pest diagnosis block for diagnosing the occurrence of pests on the crops by searching for a feature vector extraction block and searching for the pest database, and checking whether there is specific pest image data matching the extracted feature vectors; A disease comprising the crop image when diagnosed Generates a charging alert message and transmits it to a predetermined portable terminal through a wireless communication network, and when an environmental control command is received from the predetermined portable terminal, on the basis of the corresponding pest spread suppression environment information retrieved from the pest database. It provides a pest diagnosis system of a crop comprising a control block for adjusting the growth environment of the greenhouse to a predetermined pest spreading suppression environment.

According to another aspect, the present invention provides a method for diagnosing a pest in a greenhouse crop, the process of obtaining a crop image of the crop in the greenhouse, and converting the obtained crop image into crop image data. Extracting a feature vector from crop image data, matching the extracted feature vector with each pest image data by searching a pest database storing a plurality of pest image data for the crop; Provided is a pest pest diagnosis method including a process of diagnosing a pest occurrence when specific pest image data matching a vector exists.

According to the present invention, a pest type data for each crop and a plurality of pest image data for each pest type are constructed in a database as pest information, a feature vector is extracted from crop image data obtained by photographing crops, and a pest data database is constructed. By matching pest image data and extracted feature vectors of crops to diagnose whether pests have occurred in the crop, and providing follow-up measures necessary when diagnosed as the occurrence of pests in crops, the yield of crops due to pest occurrence The reduction can be effectively suppressed.

The technical gist of the present invention is different from the above-described prior art which provides a search service for pest information on crops only through a user interface, and provides a database of pest information for each pest type and a plurality of pest image data for each pest type as pest information. Extracts the feature vector from the crop image data obtained by photographing the crop, and diagnoses whether a pest has occurred in the crop by matching the pest image data of the crop constructed in the pest database with the extracted feature vector. By providing in real time the follow-up necessary when diagnosed with the development of a pest, the present invention can effectively solve the problems in the conventional manner through such technical means.

Here, the follow-up provided in real time may mean, for example, the real-time control of the crop growth environment in the greenhouse to the pest spread control environment, or it may mean that the pest occurrence is audio-visually or real-time online alert.

In addition, the present invention diagnoses whether the degree of matching between the pest image data and the feature vector falls within the preset range of pest suspicion, and generates a pest suspicion warning message including crop images when diagnosed as suspected pests, wireless communication network It may further include a technical idea to transmit to a predetermined portable terminal through.

Hereinafter, with reference to the accompanying drawings will be described in detail a preferred embodiment of the present invention.

In addition, in the following description of the present invention, if it is determined that a detailed description of a known function or configuration may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted. In addition, terms to be described below are terms defined in consideration of functions in the present invention, which may be changed according to intention or custom of a user, an operator, or the like. Therefore, the definition should be made based on the technical idea described throughout this specification.

1 is a block diagram of a pest diagnosis system of a crop according to the present invention, the sensor module 102, sensor management module 104, crop image acquisition block 106, feature vector extraction block 108, pest diagnosis block 110, the pest database 112, the control block 114, the display block 116, the alarm block 118, the growth environment control device 120, the communication block 122, and the like. Here, reference numeral 126 may refer to a mobile terminal, for example, a mobile terminal such as a mobile phone, a DMB phone, a smartphone, a PDA, a PMP, etc., which can be connected to the pest diagnosis system of the present invention through a network 124 including a wired / wireless communication network. have.

The sensor module 102 may include a temperature sensor 1022, a humidity sensor 1024, a soil sensor 1026, an illumination sensor 1028, and the like, and the sensor management module 104 may include a sensor management block 1042. ), A sensor DB 1044, and the like, and the growth environment control device 120 may include a temperature controller 1201, a humidity controller 1203, a soil temperature controller 1205, a soil humidity controller 1207, and a lighting controller. (1209) and the like.

Referring to FIG. 1, the sensor module 102 provides various sensing values to the sensor management module 104 through a wireless sensor network, and the temperature sensor 1022 measures the temperature sensing value in the greenhouse and the humidity sensor 1024. ) Measures the humidity detection value in the greenhouse, the soil sensor 1026 measures the temperature and humidity detection value in the greenhouse soil, and the light sensor 1028 measures (detects) the light detection value in the greenhouse at predetermined intervals, respectively. Each wireless transmission to 104. Here, the various sensors employed in the sensor module 102 are sensors that are well known in the art.

Next, the sensor management block 1042 in the sensor management module 104 converts each detected value wirelessly received from each sensor in the sensor module 102 into a digital data value, and stores it in the sensor DB 1044. Each sensing value stored in the sensor DB 1044 is provided to a control block 114 to be described below as an element value necessary for controlling the growth environment in the greenhouse.

The crop image acquisition block 106 acquires a crop image received from the outside, that is, a crop image photographed by a camera of a crop in a greenhouse, is converted into crop image data, and then transferred to the feature vector extraction block 108. Provides the functionality of Here, the crop image is taken by one or multiple cameras installed at a specific location in the greenhouse or by a camera mounted on a mobile terminal (eg, a mobile phone, a DMB phone, a smartphone, a PDA, a PMP, etc.), and then wirelessly. It may be a crop image transmitted via communication (eg, Bluetooth, Zigbee, RF, binary CDMA, etc.).

In addition, the feature vector extraction block 108 extracts the feature vector from the crop image data using a feature vector extraction algorithm well known in the art, and transfers the extracted feature vector to the pest diagnosis block 110. To provide such functions. At this time, the crop image is stored in the pest database 112, and such crop image is automatically deleted from the pest database 112 after a predetermined time (for example, 1 day, 1 week, 1 month, etc.). Storing the image in the pest database 112 for a predetermined time is because it may be necessary for monitoring the growth of crops in the greenhouse or for monitoring the occurrence of pests.

Next, the pest diagnosis block 110 functions as a feature vector indexer, and searches the pest database 112 to check whether there is a particular pest image data that matches the feature vector extracted from the crop image data, and then the pest. Diagnosing the occurrence of, i.e. extracting a plurality of candidate pest image data that is similarly matched with the extracted feature vector, and among the extracted candidate pest image data, the candidate pest having the greatest similarity with the extracted feature vector Image data is determined, and when the degree of matching between the determined candidate pest image data and the feature vector is equal to or more than a preset matching range, the control block 114 diagnoses that the pest has occurred and then generates a pest in the corresponding crop growing in the greenhouse. Notify.

In addition, when the pest diagnosis block 110 determines that the degree of matching between the determined candidate pest image data and the feature vector is included in the preset pest suspicion range, the pest diagnosis block 110 diagnoses this as a pest suspicion and indicates that the pest suspicion has occurred. Notify by. For example, the case where the matching degree of the feature vector is 90% or more can be set to diagnose a pest occurrence, and the case where the matching degree of the feature vector is 70-89% can be set to diagnose it as a pest suspect.

To this end, the pest database 112 includes pest-related information for each crop, that is, pest type information for each crop, multiple pest image data for each pest of the crop, and pest spreading suppression environment for preventing the spread of each pest. Information, corresponding control method information for each pest of each crop are stored, and the obtained crop image data is temporarily stored for a certain period of time. As such, the pest-related information for each crop stored in the pest database 112 may be additionally registered or updated through download from a remote server (server providing a pest-related service for crops) accessible through a network.

For example, assuming that there are three known pest types for crop A, multiple pest image data for each of the three pests of crop A, and three pest spreads to prevent the spread of three pests of crop A. Environmental information, three corresponding control information for the three pests of crop A will be stored respectively.

Herein, the environmental information for controlling pest spreading is used to control greenhouse temperature, greenhouse humidity, soil temperature, soil humidity, lighting, etc. so that the spread can be suppressed as much as possible in the presence of pests in crops. The pest spreading environment information can be information obtained through numerous pest control environment experiments for each crop.

Next, the control block 114 includes, for example, a microprocessor for performing overall operation control of the pest diagnosis system and the like, and will be described later by using respective detection values stored in the sensor DB 1044 in the sensor management module 104. By controlling the operation of the various controllers provided in the growth environment control device 120 to provide a function such as controlling the growth environment of the crops in the greenhouse to an optimal state.

In addition, the control block 114 adjusts the growth environment of the greenhouse to a preset pest spreading control environment or visually alarms the occurrence of pests when the pest occurrence is notified from the pest diagnosis block 110, and also the pest diagnosis block ( When a suspicion of a pest is notified from 110), a suspicion of a pest is provided through an online alert (transmitting a suspicion of a pest suspicion alert message to a mobile terminal) or an audio-visual alert, which will be described in more detail below.

That is, the control block 114, according to one embodiment of the present invention, performs a corresponding visual and auditory alarm control when a pest occurrence or a suspected pest is notified, that is, the crop image from the pest database 112. And extract the image image and the corresponding control method information of the pest image data corresponding thereto, and construct a visual alarm screen (pest occurrence time alarm screen or pest suspect time alarm screen), and transmit the visual alarm screen configured as described above to the display block 116. As a result, a visual alert screen is displayed through a monitor (or display panel) in the display block 116, so that the administrator (or pest control expert) can visually recognize the occurrence or suspicion of the pest.

In addition, the control block 114 generates an auditory control signal for generating an audible alarm sound corresponding to a pest occurrence or a suspected pest at the same time as the above-described visual alarm, and transmits it to the alarm block 118, as a result. This alarm allows the administrator (or pest control specialist) to audibly recognize the occurrence or suspicion of a pest by generating an audible alarm for pest outbreaks or pest suspects. At this time, as an alarm, LED, a buzzer, etc. can be used, for example.

Here, each of the display block 116 and the alarm block 118 may be mounted on the pest diagnosis system side or communicate with the pest diagnosis system via wired or wirelessly in a specific area (eg, a station located somewhat away from the greenhouse or House).

And, the control block 114 is a pest occurrence warning message (eg SMS message, MMS message, etc.) means that the pest has occurred in the crops growing in the greenhouse, such as crop image data, corresponding pest image data and the corresponding pest Generate an alarm message including control method information for the control and transmit it to the designated mobile terminal 126 (manager or pest control expert) via the communication block 122 and the network 124 (on-line notification of pest occurrence) or in the crop A pest suspicious alarm message indicating that a pest is suspected may be generated and transmitted to the designated mobile terminal 126 through the communication block 122 and the network 124 (online notification of suspicious pest).

Next, the control block 114, as another embodiment of the present invention, on the basis of the corresponding pest-corresponding growth environment information retrieved from the pest database 112, the spread of pests generated in the crops can be suppressed as much as possible. To generate a control signal for increasing or decreasing at least one or a plurality of elements of the internal temperature, internal humidity, soil temperature, soil humidity, lighting of the greenhouse to transmit to the growth environment control device 120 side.

Therefore, each controller in the growth environment control device 120, that is, the temperature controller 1201, the humidity controller 1203, the soil temperature controller 1205, the soil humidity controller 1207, the lighting controller 1209, and the like are controlled by the control block ( In response to the control signal provided from 114), by selectively increasing or decreasing the relevant factors (internal temperature, internal humidity, soil temperature, soil humidity, lighting, etc.), the growth environment in the greenhouse is controlled to a predetermined pest spreading suppression environment. Here, since each controller in the growth environment control device 120 means various control devices that are well known in the art, a description of functions for each of these controllers is omitted here.

In addition, the control block 114 generates an environmental control result message indicating that the pests are generated in the crops growing in the greenhouse to adjust the growth environment of the greenhouse to a preset pest spreading suppression environment, thereby communicating the communication block 122 and the network ( 124 may be transmitted to a predetermined mobile terminal 126 (online notification of automatic environmental control according to a pest occurrence). Here, the environmental control result message may include, for example, a crop image, a corresponding pest image, control station information, and the like.

Further, the control block 114, as another embodiment in the present invention, when the pest occurrence is notified, the pest including an image image of the pest image data corresponding to the crop image (crop image of the pest occurrence) An outbreak alert message may be generated and transmitted via the communication block 122 and the network 124 to a predetermined mobile terminal 126 (online notification of pest outbreak), wherein the pest outbreak alert message is, for example, crop image data. It may include a pest control image data, and corresponding pest image data and control method information on the pest, and may include a suppression item for selecting a pest spread control command.

Subsequently, the control block 114 responds to the withdrawal from the pest database 112 when an environmental control command generated through the mobile terminal user's interface (eg, click or select suppression item) is received via the communication block 122. Control signal for increasing or decreasing at least one or a plurality of elements of the internal temperature, the internal humidity, the soil temperature, the soil humidity, and the lighting of the greenhouse so that the spread of the pests generated in the crops can be suppressed to the maximum, based on the growth environment information corresponding to the pests. Generated and delivered to the growth environment control device 120 side.

As a result, each controller in the growth environment control device 120, that is, the temperature controller 1201, the humidity controller 1203, the soil temperature controller 1205, the soil humidity controller 1207, the lighting controller 1209, and the like are controlled by the control block. In response to the control signal provided from 114, by selectively increasing or decreasing the relevant factors (internal temperature, internal humidity, soil temperature, soil humidity, lighting, etc.), the growth environment in the greenhouse is adjusted to the preset pest spreading suppression environment. .

In addition, the control block 114 adjusts the growth environment of the greenhouse to the preset pest spreading suppression environment, and generates an environmental control result message corresponding thereto, and the environmental control result message thus generated is communicated with the communication block 122 and the network. A function of transmitting to the portable terminal 126 through 124 is provided.

Finally, the communication block 122 includes an internet communication protocol that can be connected to a network 124 including wired / wireless communication networks, and includes a pest occurrence warning message, a pest suspicion warning message transmitted from the control block 114, Transmits an environmental control result message to the mobile terminal 126 through the network 124, and transmits an environmental control command signal generated from the mobile terminal 126 and received through the network 124 to the control block 114. In addition, it provides a function such as passing to the control block 114 when the pest-related information of a particular crop is received (downloaded) from a remote server.

On the other hand, the pest diagnosis system of the present invention can be built on the basis of the WSN and XML, by providing a pest prediction notification function based on the pest occurrence conditions through the WSN, by building a pest database based on XML technology XML document structure The structure indexer for information can be designed to provide information retrieval service for pests with various search query types. Also, text indexer for text information such as pest symptoms and disease conditions can be used to search for pests through text. It can be designed to provide information retrieval services.

In addition, the pest diagnosis system of the present invention can perform a pest diagnosis to determine the occurrence of pests in a predetermined period (pest diagnosis cycle) by comparing the pest image constructed in the database by acquiring the crop image in the greenhouse However, the pest diagnosis cycle can be variably determined according to the growth cycle characteristics of the crop. For example, it may be set to a period of several minutes to several tens of minutes, several hours to several tens of hours, several days to several tens of days, and such a pest diagnosis cycle may be a preset cycle according to a pest diagnosis profile or a manager (or pest control expert) Can be any specified period.

In addition, the present invention, unlike the above, when the manager (or pest control specialist) transfers the crop image photographed through the camera of the mobile terminal to the pest diagnosis system through the short-range communication to request the diagnosis of the pest, the above-mentioned pest diagnosis The pest diagnosis may be performed on the crop image received from the camera of the mobile terminal irrespective of the cycle, and in this case, when it is determined that the pest has occurred in the crop requested for diagnosis, as described above, the pest diagnosis system It would be desirable to perform a remote diagnostic service model that transmits the diagnostic results to the mobile terminal.

That is, according to the present invention, the manager of a greenhouse or a pest control expert checks whether a pest occurs on a crop at any time through a method of taking a crop image through a camera of a mobile terminal and transmitting it to a pest diagnosis system. )can do.

Next, a series of procedures for diagnosing the occurrence of pests in crops growing in a greenhouse using the pest diagnosis system of the present invention having the above-described configuration will be described.

[First Embodiment]

Figure 2 is a flow chart illustrating the main process of diagnosing pests in a crop in a greenhouse according to a first embodiment of the present invention.

Referring to FIG. 2, in the crop image acquisition block 106, when an image photographed through a camera or a mobile terminal installed at a predetermined position in a greenhouse is acquired (step 202), the crop image is converted into crop image data (step 202). Step 204, the crop image data thus converted is transferred to the feature vector extraction block 108.

Next, the feature vector extraction block 108 extracts the feature vector from the crop image data using a feature vector extraction algorithm well known in the art, and the extracted feature vector together with the crop image data is used to detect a pest diagnosis block ( 110) (step 206).

In response, the pest diagnosis block 110 searches the pest database 112 and checks whether there is specific pest image data matching the extracted feature vector to diagnose whether or not the pest is generated or suspected (step 208). . For example, a plurality of candidate pest image data that are similarly matched to the extracted feature vector are extracted, and among the extracted plurality of candidate pest image data, the candidate pest image data having the largest similarity with the extracted feature vector is determined. When it is determined that the degree of matching between the determined candidate pest image data and the feature vector falls within the preset range of suspected pests, the diagnosis is diagnosed as a suspected pest (step 210), and the degree of matching between the determined candidate pest image data and the feature vector is determined. It is diagnosed as a pest occurrence when it is over the set matching range (step 212), and the diagnosis result is notified to the control block 114.

In this case, crop images (crop image data) are stored in the pest database 112, and such crop images are automatically deleted from the pest database 112 after a predetermined time (eg, 1 day, 1 week, 1 month, etc.) passes. For example, the case where the matching degree of the feature vector is 90% or more may be diagnosed as the occurrence of pests, and the case where the matching degree of the feature vector is 70 to 89% may be set as the diagnosis of the pest.

If it is determined that the matching degree between the determined candidate pest image data and the feature vector is included in the preset pest suspicion range as a result of the check in step 210, the control block 114 detects the pest suspicion by an audiovisual alarm. That is, the image of the pest image data corresponding to the crop image and the corresponding control method information is extracted from the pest database 112 to construct a suspected visual warning screen for pests, and displays the suspected visual warning screen configured as described above. To the monitor (or display panel), and at the same time generates an auditory control signal for generating an audible alarm sound corresponding to the suspected pest and transmits it to the alarm block 118 to hear the suspected pest through the alarm. By generating an alarm sound, Thereby perform acoustic alarm (step 214).

Therefore, managers (or pest control specialists) inside or around the greenhouse can visually recognize the suspicion of pests in crops in the greenhouse through audiovisual alarms.

The control block 114 then generates an audiovisual alert for suspected pests and then generates a pest suspected alert message and transmits it to the predetermined mobile terminal 126 via the communication block 122 and the network 124 (pest suspected). Online notification) (step 216), so that managers or pest control specialists can respond quickly to pest suspicions in crops in the greenhouse, even when not in or near the greenhouse. Here, the pest suspicious alert message may include, for example, a crop image, a corresponding pest image, control station information, and the like.

On the other hand, if it is determined that the degree of matching between the determined candidate pest image data and the feature vector is greater than or equal to a preset matching range as a result of the check in the step 212, the control block 114 determines that the pest is generated by an audiovisual alarm, That is, a pest occurrence time alarm screen is constructed by extracting the image image and the corresponding control method information of the pest image data corresponding to the crop image from the pest database 112, and displays the pest occurrence time alarm screen configured as described above to the display block 116. It transmits and displays through a monitor (or display panel), and at the same time generates an auditory control signal for generating an audible alarm sound corresponding to the occurrence of the pest, and delivers it to the alarm block 118, an acoustic alarm for the occurrence of the pest through the alarm. By generating sound, audiovisual for pest outbreaks Thereby performing the alarm (step 218).

Therefore, managers (or pest control specialists) inside or around the greenhouse can visually recognize pest outbreaks in crops in the greenhouse through audiovisual alarms.

Subsequently, the control block 114 generates an audiovisual alarm for the occurrence of the pest, and then generates a pest occurrence alarm message and transmits it to the predetermined mobile terminal 126 through the communication block 122 and the network 124 (pest generation). Online notification) (step 220), so that managers or pest control specialists can respond quickly to pest outbreaks in greenhouse crops, even when they are not in or near the greenhouse. Here, the pest occurrence warning message may include, for example, a crop image, a corresponding pest image, control station information, and the like.

That is, according to the present embodiment, when a suspicion of a pest is detected in a greenhouse crop or when a pest occurrence is detected, an audiovisual alarm or an online notification is notified in real time to an administrator, or a pest control expert to suspect a pest. Alternatively, rapid follow-up can be taken for pest outbreaks.

Meanwhile, in the pest diagnosis method of the present embodiment, when a pest occurrence in a greenhouse crop is detected, the audio visual alarm of the pest occurrence is first performed, and then the pest occurrence in the greenhouse is notified online. However, the present invention is not limited thereto, but the order of audiovisual warning and online notification of pest occurrence may be changed.

Second Embodiment

3 is a flowchart illustrating a main process of diagnosing pests in a crop in a greenhouse according to a second embodiment of the present invention.

First, the pest diagnosis method of the present embodiment is different from the above-described first embodiment in which online notification is sent to the mobile terminal together with an audiovisual alarm when a suspected pest or pest occurrence is detected. There is a difference in that it automatically adjusts to a predetermined pest spreading environment. To this end, the pest database 112 stores pest spreading suppression environment information corresponding to each pest of the crop.

Referring to FIG. 3, the processing of each step of steps 302 to 316 is substantially the same as the processing of the corresponding steps 202 to 216 shown in FIG. Therefore, in order to avoid unnecessary duplication for the sake of brevity of the specification, the description of the processing steps in steps 302 to 316 is omitted here.

Therefore, if it is determined that the matching degree between the determined candidate pest image data and the feature vector is greater than or equal to the preset matching range as a result of the check in step 312, the control block 114 determines that the pest occurrence is an audiovisual alarm, that is, From the pest database 112, the image image of the pest image data corresponding to the crop image and the corresponding control method information are extracted to construct a pest occurrence time alarm screen, and the pest occurrence time alarm screen configured as described above is transferred to the display block 116. Display through a monitor (or a display panel), and at the same time, generate an auditory control signal for generating an audible alarm sound corresponding to the occurrence of the pest, and transmit it to the alarm block 118 to transmit the audible alarm sound for the pest occurrence through the alarm device. By generating an audiovisual Thereby performing the alarm (step 318).

Therefore, managers (or pest control specialists) inside or around the greenhouse can visually recognize pest outbreaks in crops in the greenhouse through audiovisual alarms.

Next, the control block 114 extracts the pest-corresponding growth environment information corresponding to the pest from the pest database 112, and adjusts the growth environment in the greenhouse to the preset pest spread suppression environment.

That is, at least one or more of the internal temperature, the internal humidity, the soil temperature, the soil humidity, and the lighting of the greenhouse are increased or decreased on the basis of the pest growth environment information so that the spread of pests generated in the greenhouse crops can be suppressed as much as possible. Generates a control signal to the growth environment control device 120, and in response to the temperature controller 1201, humidity controller 1203, soil temperature controller 1205, soil humidity in the growth environment control device 120 The controller 1207, the lighting controller 1209 and the like selectively control the related factors (internal temperature, internal humidity, soil temperature, soil humidity, lighting, etc.) to adjust the growth environment in the greenhouse to a preset pest spreading suppression environment. (Step 320).

Subsequently, the control block 114 generates an environmental control result message indicating that pests are generated in the crops in the greenhouse to automatically adjust the growth environment of the greenhouse to the preset pest spreading suppression environment, thereby communicating the communication block 122 and the network 124. In step 322, the mobile station 126 transmits the data to the predetermined mobile terminal 126. Here, the environmental control result message may include, for example, a crop image, a corresponding pest image, control station information, and the like.

Therefore, managers or pest control specialists can identify in real time the occurrence of pests in the greenhouse crops and their growth environment control, even when they are not in or around the greenhouse, thereby quickly following up on the need for follow-up. It can be processed.

On the other hand, in the pest diagnosis method of the present embodiment, when the occurrence of pests in the greenhouse crops is detected by first performing an audio-visual alarm of the occurrence of pests, it has been described as automatically adjusting the growth environment of the greenhouse to a predetermined pest spreading suppression environment, This is merely an exemplary presentation for the convenience of explanation and enhancement of understanding, and the present invention is not necessarily limited thereto, and the order of audiovisual warning and growth environment control of pest occurrence may be changed.

Third Embodiment

4 is a flowchart illustrating a main process of diagnosing pests in a crop in a greenhouse according to a third embodiment of the present invention.

First, the pest diagnosis method of the present embodiment is different from the above-described second embodiment in which the growth environment in the greenhouse is automatically adjusted to the preset pest spreading suppression environment together with an audiovisual alarm when a suspected pest or a pest occurrence is detected. When this is detected, the mobile terminal is notified online, and when the environmental control command generated according to the user interface is received from the portable terminal, the growth environment in the greenhouse is adjusted to a preset pest spreading suppression environment.

Referring to FIG. 4, the processing of each step of steps 402 to 418 is substantially the same as the processing of the corresponding steps 302 to 318 shown in FIG. Therefore, in order to avoid unnecessary duplication for the sake of brevity, the description of the processing in steps 402 to 418 is omitted here.

Therefore, after the occurrence of a pest in a greenhouse crop is diagnosed and an audiovisual alarm is generated, the control block 114 generates a corresponding pest occurrence alarm message to establish a communication block 122 and a network 124. After transmission (on-line notification of the occurrence of pests) to the designated mobile terminal 126 via (step 420), it waits for reception of an environmental control command signal from the mobile terminal 126 (step 422). The pest occurrence warning message may include, for example, crop image data, corresponding pest image data, control method information for the pest, and an inhibition item for selecting a pest spreading control command.

Subsequently, when the environmental control command signal generated from the mobile terminal 126 is received through the communication block 122, in response to the control block 114, the pest control plant growth environment information corresponding to the pest from the pest database 112 in response thereto. By extracting, the growth environment in the greenhouse is adjusted to a predetermined pest spreading suppression environment.

That is, at least one or more of the internal temperature, the internal humidity, the soil temperature, the soil humidity, and the lighting of the greenhouse are increased or decreased on the basis of the pest growth environment information so that the spread of pests generated in the greenhouse crops can be suppressed as much as possible. Generates a control signal to the growth environment control device 120, and in response to the temperature controller 1201, humidity controller 1203, soil temperature controller 1205, soil humidity in the growth environment control device 120 The controller 1207, the lighting controller 1209 and the like selectively control the related factors (internal temperature, internal humidity, soil temperature, soil humidity, lighting, etc.) to adjust the growth environment in the greenhouse to a preset pest spreading suppression environment. (Step 424).

Subsequently, the control block 114 generates an environmental control result message indicating that the growth environment of the greenhouse is adjusted to a preset pest spreading suppression environment according to an environmental control instruction generated according to the user interface, thereby generating a communication block 122 and a network ( In step 426, the mobile terminal 126 transmits the information to the mobile terminal 126.

Therefore, the manager or pest control expert can control the greenhouse's growth environment according to his / her choice, when the pest occurrence is detected in the greenhouse, even if he / she is not in or around the greenhouse. It can effectively suppress the spread of pests in crops and can quickly handle the follow-up that is needed.

On the other hand, in the pest diagnosis method of the present embodiment, when a pest occurrence in a greenhouse crop is detected, an audiovisual alarm of pest occurrence is first performed, and then an online notification for inquiring whether to adjust the growth environment of the greenhouse to a preset pest spread suppression environment. Although described as going through, but this is merely an illustrative presentation for the convenience of explanation and enhancement of the understanding, the present invention is not necessarily limited to this, the order of the online notification inquiry for the control of the audio-visual warning and growth environment of pest occurrence Of course, you can also change the mutual.

In the above description has been described by presenting a preferred embodiment of the present invention, but the present invention is not necessarily limited to this, and those skilled in the art to which the present invention pertains within a range without departing from the technical spirit of the present invention It will be readily appreciated that branch substitutions, modifications and variations are possible.

1 is a block diagram of a pest diagnosis system of a crop according to the present invention,

Figure 2 is a flow chart showing the main process of diagnosing pests in crops in the greenhouse according to the first embodiment of the present invention,

3 is a flow chart showing the main process of diagnosing pests in a crop in a greenhouse according to a second embodiment of the present invention,

Figure 4 is a flow chart showing the main process of diagnosing pests in a crop in a greenhouse according to a third embodiment of the present invention.

Description of the Related Art

102: sensor module 104: sensor management module

106: crop image acquisition block 108: feature vector extraction block

110: pest diagnosis block 112: pest DB

114: control block 116: display block

118: alarm block 120: growth environment control device

1022: temperature sensor 1024: humidity sensor

1026 soil sensor 1028 light sensor

1042: sensor management block 1044: sensor DB

1201: temperature controller 1203: humidity controller

1205 soil temperature controller 1207 soil humidity controller

1209: Lighting Controller

Claims (24)

As a system for diagnosing the occurrence of pests in crops in a greenhouse, A pest database that stores multiple pest image data for each crop, A crop image acquisition block for acquiring crop images of the crops in the greenhouse and converting the crop images into crop image data; A feature vector extraction block for extracting feature vectors from the crop image data using a feature vector extraction algorithm; A pest diagnosis block for diagnosing the occurrence of pests on the crops by searching the pest database and checking whether there is specific pest image data matching the extracted feature vectors; A control block for performing audiovisual alarm control when the pest is diagnosed; Audio-visual alarm means for audio-visual warning of the occurrence of pests on the crop in response to the audio-visual alarm control Pest diagnosis system of crops comprising a. The method of claim 1, The control block, Generating a pest occurrence alarm message indicating the pest occurrence and transmits it to a predetermined mobile terminal through a wireless communication network Pest diagnosis system of crops, characterized in that. The method of claim 1, The pest diagnosis block may be diagnosed as a suspected pest and notify the control block when there is pest image data whose degree of matching with the extracted feature vector is included in a preset pest suspect range. The control block is configured to perform suspicious audiovisual alarm control for suspected pests of the crop in response to diagnosis of the suspected pests. Pest diagnosis system of crops, characterized in that. The method of claim 3, wherein The control block, Generating a pest suspicious alarm message, which means suspicious of the pest, and transmits it to a predetermined mobile terminal through a wireless communication network. Pest diagnosis system of crops, characterized in that. As a system for diagnosing the occurrence of pests in crops in a greenhouse, A pest database for storing a plurality of pest image data for each crop, and storing pest spread control environment information for preventing the spread of each pest; A crop image acquisition block for acquiring crop images of the crops in the greenhouse and converting the crop images into crop image data; A feature vector extraction block for extracting feature vectors from the crop image data using a feature vector extraction algorithm; A pest diagnosis block for diagnosing the occurrence of pests on the crops by searching the pest database and checking whether there is specific pest image data matching the extracted feature vectors; Control block for adjusting the growth environment of the greenhouse to a predetermined pest spreading control environment based on corresponding pest spreading suppression environment information extracted from the pest database when the pest is diagnosed Pest diagnosis system of crops comprising a. The method of claim 5, The pest diagnosis system, Audiovisual alarm means for audiovisual warning of the occurrence of pests in response to audiovisual alarm control from the control block Pest diagnosis system of crops, characterized in that it further comprises. The method of claim 5, The pest diagnosis block may be diagnosed as a suspected pest and notify the control block when there is pest image data whose degree of matching with the extracted feature vector is included in a preset pest suspect range. The control block is configured to perform suspicious audiovisual alarm control for suspected pests of the crop in response to diagnosis of the suspected pests. Pest diagnosis system of crops, characterized in that. The method of claim 7, wherein The control block, Generating a pest suspicious alarm message, which means suspicious of the pest, and transmits it to a predetermined mobile terminal through a wireless communication network. Pest diagnosis system of crops, characterized in that. As a system for diagnosing the occurrence of pests in crops in a greenhouse, A pest database for storing a plurality of pest image data for each crop, and storing pest spread control environment information for preventing the spread of each pest; A crop image acquisition block for acquiring crop images of the crops in the greenhouse and converting the crop images into crop image data; A feature vector extraction block for extracting feature vectors from the crop image data using a feature vector extraction algorithm; A pest diagnosis block for diagnosing the occurrence of pests on the crops by searching the pest database and checking whether there is specific pest image data matching the extracted feature vectors; When a pest occurrence is diagnosed, a pest occurrence alarm message including the crop image is generated and transmitted to a predetermined portable terminal through a wireless communication network, and when an environmental control command is received from the predetermined portable terminal, the pest database Control block for controlling the growth environment of the greenhouse to the predetermined pest spreading control environment based on the corresponding pest spreading suppression environment information extracted from Pest diagnosis system of crops comprising a. The method of claim 9, The pest diagnosis system, Audiovisual alarm means for audiovisual warning of the occurrence of pests in response to audiovisual alarm control from the control block Pest diagnosis system of crops, characterized in that it further comprises. The method of claim 9, The pest diagnosis block may be diagnosed as a suspected pest and notify the control block when there is pest image data whose degree of matching with the extracted feature vector is included in a preset pest suspect range. The control block is configured to perform suspicious audiovisual alarm control for suspected pests of the crop in response to diagnosis of the suspected pests. Pest diagnosis system of crops, characterized in that. The method of claim 11, The control block, Generating a pest suspicious alarm message indicating the pest suspiciousness and transmitting the pest suspicious alarm message to the predetermined portable terminal through the wireless communication network; Pest diagnosis system of crops, characterized in that. As a method of diagnosing the occurrence of pests in crops in a greenhouse, Acquiring crop images of crops in the greenhouse; Converting the obtained crop image into crop image data and extracting a feature vector from the crop image data; Matching the extracted feature vector with each pest image data by searching a pest database storing a plurality of pest image data for the crop; A process of diagnosing pest occurrence when specific pest image data matching the extracted feature vector exists Pest diagnosis method of crops comprising a. The method of claim 13, The pest diagnosis method, A process of audio-visual warning of the occurrence of the pest when diagnosed as the occurrence of the pest Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 14, The audiovisual alarm, A visual alarm for displaying the image image of the specific pest image data, the crop image and the corresponding control method information on the generated pest on a monitor in the system, and an auditory alarm using an alarm installed in or around the greenhouse. Pest diagnosis method of crops comprising a. The method of claim 13, The diagnosis process, Extracting a plurality of candidate pest image data that are similarly matched to the extracted feature vectors; Determining candidate pest image data having a relatively similarity with the extracted feature vector among the extracted plurality of candidate pest image data; Diagnosing the occurrence of the pest when the degree of matching between the determined candidate pest image data and the feature vector is equal to or larger than a preset matching range. Pest diagnosis method of crops comprising a. The method of claim 16, The pest diagnosis method, Diagnosing the pest as suspected when the degree of matching falls within a preset pest suspect range; A process of audio-visual warning of a suspected pest of the crop when the suspected pest is diagnosed Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 17, The pest diagnosis method, After the audio-visual warning of the suspected pests, the process of generating a pest suspicious alarm message including the crop image and transmitting it to a predetermined mobile terminal through a wireless communication network Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 13, The pest diagnosis method, Automatically adjusting the growth environment of the greenhouse to a predetermined pest spreading environment based on corresponding pest spreading suppression environment information extracted from the pest database when the pest occurrence is diagnosed Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 13, The diagnosis process, Extracting a plurality of candidate pest image data that are similarly matched to the extracted feature vectors; Determining candidate pest image data having a relatively similarity with the extracted feature vector among the extracted plurality of candidate pest image data; Diagnosing the occurrence of the pest when the degree of matching between the determined candidate pest image data and the feature vector is equal to or larger than a preset matching range. Pest diagnosis method of crops comprising a. The method of claim 20, The pest diagnosis method, Diagnosing the pest as suspected when the degree of matching falls within a preset pest suspect range; A process of audio-visual warning of a suspected pest of the crop when the suspected pest is diagnosed Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 13, The pest diagnosis method, When the pest occurrence is diagnosed, a process of generating a pest occurrence alarm message including the crop image and transmitting it to a predetermined mobile terminal through a wireless communication network Pest diagnostic method of the crop, characterized in that it further comprises. The method of claim 13, The diagnosis process, Extracting a plurality of candidate pest image data that are similarly matched to the extracted feature vectors; Determining candidate pest image data having a relatively similarity with the extracted feature vector among the extracted plurality of candidate pest image data; Diagnosing the occurrence of the pest when the degree of matching between the determined candidate pest image data and the feature vector is equal to or larger than a preset matching range. Pest diagnosis method of crops comprising a. The method of claim 23, wherein The pest diagnosis method, Diagnosing the pest as suspected when the degree of matching falls within a preset pest suspect range; A process of audio-visual warning of a suspected pest of the crop when the suspected pest is diagnosed Pest diagnostic method of the crop, characterized in that it further comprises.

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