Adhesion state determination system, adhesion state determination method, adhesion state determination program, and optimal pest control timing prediction system

Abstract

To accurately determine the adhesion state of insects on crops.SOLUTION: An adhesion state determination system comprises: a vibration pattern acquisition unit that acquires vibration pattern information indicating vibration patterns of a determination target crop growing in a field; an adhesion determination unit that determines, on the basis of the vibration pattern information, the adhesion state of a prescribed insect on the determination target crop; and an output unit that outputs information on the determined adhesion state.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an adhesion status determination system, an adhesion status determination method, an adhesion status determination program, and a control optimum timing prediction system. [Background technology]

[0002] Conventionally, there have been known methods that utilize information processing technology for managing farm fields, particularly for predicting the occurrence of pests.

[0003] For example, the pest occurrence prediction system described in Patent Document 1 includes a terminal device and a server device connected to the terminal device via a network. The terminal device includes a camera that photographs an insect trapping sheet (a sheet coated with an adhesive to trap pests) and obtains image data, a position information acquisition unit that obtains position information of the insect trapping sheet, and a control unit that creates insect trapping sheet information including the image data and position information and transmits the insect trapping sheet information to the server device. The server device includes an image analysis unit that receives the insect trapping sheet information from the terminal device, analyzes the image data included in the insect trapping sheet information for each insect trapping sheet, counts the number of pests for each insect trapping sheet, and creates basic information including the number of pests and position information, and a prediction unit that predicts the occurrence of pests based on the basic information for each of a plurality of insect trapping sheets. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-154732 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the capture status of the insect trapping sheet can be affected not only by the growth status of the pests, but also by factors such as the installation position of the insect trapping sheet and the adhesive strength of the sheet. Therefore, the capture status of the insect trapping sheet may not match the growth status of the insects in the field, and in that case, the system cannot accurately predict the occurrence of pests.

[0006] Therefore, an object of the present invention is to determine the insect infestation state in crops with high accuracy. [Means for solving the problem]

[0007] An adhesion status determination system according to one embodiment of the present invention includes a vibration pattern acquisition unit that acquires vibration pattern information indicating the vibration pattern of a target crop inhabiting a field, an adhesion determination unit that determines the adhesion status of a specified insect in the target crop based on the vibration pattern information, and an output unit that outputs information related to the determined adhesion status.

[0008] In addition, a system for predicting the optimal control time according to one embodiment of the present invention includes a vibration pattern acquisition unit that acquires vibration pattern information indicating the vibration pattern of a target crop inhabiting the field, an attachment determination unit that determines the attachment status of a specified insect in the target crop based on the vibration pattern information, a habitat prediction unit that predicts the future habitat status of the specified insect in the field based on the determined attachment status, and an optimal control time prediction unit that predicts an appropriate timing for control treatment of the specified insect in the field based on the prediction. Effect of the Invention

[0009] According to the present invention, the insect infestation state in crops can be determined with high accuracy. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing an overview of processing in an adhesion state determination system 100 according to an embodiment of the present invention. [Diagram 2] 1 is a diagram showing a configuration of an adhesion state determination system 100 according to an embodiment of the present invention. [Figure 3A] FIG. 11 is a diagram showing an example of vibration pattern information. [Figure 3B] FIG. 11 is a diagram showing an example of vibration pattern information. [Figure 4A] 11 is a diagram showing an example of the result of analysis processing by a frequency analysis unit 150. FIG. [Figure 4B] 11 is a diagram showing an example of the result of analysis processing by a frequency analysis unit 150. FIG. [Diagram 5] 4 is a diagram showing an example of growth prediction information stored in a storage unit 110. FIG. [Figure 6] 4 is a flowchart showing an example of processing in the adhesion state determination system 100. [Figure 7] FIG. 1 is a diagram showing a configuration of a pest control optimum timing prediction system 101 according to one embodiment of the present invention. [Figure 8] FIG. 4 is a diagram showing an example of optimal control timing prediction information stored in a storage unit 110. [Figure 9] 1 is a flowchart showing an example of processing in the pest control optimum timing prediction system 101. [Figure 10] FIG. 1 illustrates an example of a hardware configuration of a computer 1000. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described with reference to the accompanying drawings, in which: Fig. 1 is a diagram showing an overview of processing in an adhesion state determination system 100 according to an embodiment of the present invention.

[0012] The infestation state determination system 100 is an information processing system realized by an infestation state determination program. The infestation state determination system 100 determines the infestation state of a given insect in a subject crop based on the vibration pattern of the subject crop living in a farm field, and predicts the future growth state of the given insect.

[0013] First, the adhesion state determination system 100 acquires vibration pattern information indicating a vibration pattern of a target crop inhabiting a farm field (S101). The adhesion state determination system 100 may acquire the vibration pattern information through a predetermined device (for example, a vibration pattern acquisition device).

[0014] The attachment status determination system 100 determines the attachment status of a specific insect in the target crop based on the vibration pattern information and generates attachment status information (S102). At this time, the attachment status determination system 100 may determine the communication status of the specific insect based on the vibration pattern information, generate communication status information, and determine the attachment status of the specific insect based on the communication status information.

[0015] The attachment state determination system 100 predicts the future habitation state of the specified insect in the field based on the attachment state information, and generates growth prediction information (S103). Then, the attachment state determination system 100 outputs at least one of the attachment state information and the growth prediction information to the user device 200 (S104).

[0016] Here, the crop to be judged is not particularly limited, but may be, for example, rice. The predetermined insect is not particularly limited, but may be, for example, a pest that attaches to rice, and may be, in particular, for example, a planthopper.

[0017] Furthermore, "communication" in this embodiment may include not only mutual communication between multiple specified insects, but also one-way communication (in other words, sending or transmitting, or in other words, calling for communication) by one specified insect to another specified insect.

[0018] More specifically, consider a case where a given insect communicates reciprocally between males and females, but does not communicate reciprocally between insects of the same sex. When both males and females of the given insect are included in a given space, the given insect communicates reciprocally between males and females, and when only the same sex of the given insect is included in the given space, the given insect may communicate unidirectionally with another given insect (e.g., of the opposite sex). That is, "communication" in this embodiment includes reciprocal communication between males and females (hereinafter, simply referred to as "communication between opposite sexes") that occurs when both males and females are included in the given space, and unidirectional communication with another given insect (e.g., of the opposite sex) that occurs when only the same sex is included in the given space (hereinafter, simply referred to as "communication between same sexes"). The other given insects may be unspecified or an unspecified number of insects.

[0019] 2 is a diagram showing the configuration of an adhesion state determination system 100 according to one embodiment of the present invention. The adhesion state determination system 100 is communicably connected to a user device 200 via a network such as the Internet. Details of the adhesion state determination system 100 will be described later.

[0020] The user device 200 is an information processing device used by a user of the adhesion state determination system 100, and is a computer, a smartphone, a tablet terminal, a personal computer, or the like.

[0021] The user uses the user device 200 to obtain information (e.g., communication status information, adhesion status information, or growth prediction information) output by the adhesion status determination system 100. The user refers to the information obtained from the adhesion status determination system 100 to, for example, manage a farm field, in particular, manage the growth status of crops and perform pest control treatment for crops.

[0022] Although one user device 200 is shown in FIG. 2, a plurality of user devices 200 may be provided.

[0023] Next, details of the adhesion state determination system 100 will be described. The adhesion state determination system 100 includes a storage unit 110, a vibration pattern acquisition unit 120, a noise vibration pattern acquisition unit 130, a noise removal unit 140, a frequency analysis unit 150, a communication determination unit 160, an adhesion determination unit 170, a growth prediction unit 180, and an output unit 190. Each unit shown in Fig. 2 can be realized, for example, by using a storage area or by a processor executing a program stored in the storage area.

[0024] The storage unit 110 stores information to be processed in the adhesion state determination system 100. The storage unit 110 can store, for example, vibration pattern information, communication state information, adhesion state information, and growth prediction information, which will be described later.

[0025] The vibration pattern acquisition unit 120 acquires vibration pattern information indicating the vibration pattern of the target crop that grows in the field, and stores the vibration pattern information in the storage unit 110.

[0026] The vibration pattern acquisition unit 120 can acquire the vibration pattern information from, for example, an external device. In this case, the external device may be, for example, a predetermined device that measures the vibration pattern of the target crop, or may be an information processing system that acquires the vibration pattern information through the predetermined device.

[0027] The vibration pattern information is, for example, information indicating a vibration pattern of a predetermined part (e.g., a leaf or a stem) of the crop to be determined within a predetermined time (e.g., several tens of seconds). The vibration pattern information may be, for example, information in which a measurement time is associated with a vibration speed at the measurement time.

[0028] The vibration indicated by the vibration pattern information may be, for example, a vibration measured by a predetermined device (for example, a laser Doppler vibrometer).

[0029] The vibration pattern information may be, for example, vibration pattern information of a target crop in a predetermined section of a farm field. Here, the predetermined section may be, for example, a corner or a center of the farm field, or may be a section specially provided for obtaining the vibration pattern information.

[0030] A specific insect (e.g., aphids) communicates, for example, between males and females. Furthermore, a specific insect (e.g., aphids) will communicate, for example, with an opposite sex (one-sided communication) even in a space where only insects of the same sex are present. Therefore, communication between opposite sexes or same sexes by a specific insect causes the crop to which the specific insect is attached to vibrate. Therefore, the attachment status determination system 100 acquires the vibration pattern of the crop to be determined and determines the communication status and attachment status of the specific insect based on the vibration pattern.

[0031] 3A and 3B are diagrams showing examples of vibration pattern information. The vibration pattern information shown in Fig. 3A and Fig. 3B shows an example in which the target crop is rice and the specified insect is a planthopper. The vibration pattern information shown in Fig. 3A shows vibration pattern information in the case where male and female planthoppers are attached to rice. Fig. 3B shows vibration pattern information in the case where only male planthoppers are attached to rice.

[0032] 3A and 3B, the vibration pattern information is, for example, information in which the measurement time is associated with the vibration speed. It can also be seen that there is a difference in the vibration pattern between the case where both male and female planthoppers are attached to the rice plant and the case where only male planthoppers are attached to the rice plant.

[0033] The noise vibration pattern acquisition unit 130 acquires noise vibration pattern information indicating a pattern of vibration of the target crop caused by a noise factor other than a predetermined insect, which is measured in advance, and stores the information in the storage unit 110 .

[0034] The noise vibration pattern acquisition unit 130 can acquire the noise vibration pattern information from, for example, an external device. At this time, the external device may be, for example, a predetermined device that measures the vibration pattern of the target crop, or may be an information processing system that acquires the vibration pattern information through the predetermined device.

[0035] Noise factors other than the specified insect may include, for example, wind. That is, the noise vibration may include, for example, vibration caused by wind. This allows the insect adhesion status determination system 100 to determine the insect adhesion status while eliminating the influence of the vibration pattern caused by wind.

[0036] Furthermore, noise factors other than the predetermined insect may include, for example, the ground. That is, the noise vibration may include, for example, vibration caused by vibration of the ground. The ground vibration may be, for example, ground vibration caused by the movement of a vehicle passing near the crop. In this way, the attachment status determination system 100 can determine the attachment status of the predetermined insect while eliminating the influence of the vibration pattern originating from the ground.

[0037] The noise vibration pattern information may be, for example, information indicating a vibration pattern of a target crop to which a specific insect is not attached. More specifically, the noise vibration pattern information may be, for example, information indicating at least one of a vibration pattern of a vibration caused by wind and a vibration caused by ground vibration in a target crop to which a specific insect is not attached. This allows the attachment status determination system 100 to determine the attachment status of a specific insect by taking into account the influence of the attachment of the specific insect.

[0038] The noise vibration pattern information may be, for example, noise vibration pattern information of a crop to be evaluated in a specified section of a field, or may be noise vibration pattern information of a crop to be evaluated in a specified section of a location other than a field (for example, within a specified facility).

[0039] The noise vibration pattern information is, for example, information indicating a pattern of vibration of a predetermined part (e.g., leaf, stem) of a target crop within a predetermined time (e.g., several tens of seconds) caused by a noise factor other than a predetermined insect. The noise vibration pattern information may be, for example, information in which a measurement time is associated with a vibration speed at the measurement time.

[0040] The vibration indicated by the noise vibration pattern information may be, for example, a vibration measured by a predetermined device (for example, a laser Doppler vibrometer).

[0041] Furthermore, the crop to be determined in the vibration pattern information and the crop to be determined in the noise vibration pattern information may be, for example, the same or different strains, or the same or different species of crops.

[0042] The noise removal unit 140 removes the influence of vibrations resulting from noise factors in the vibration pattern information based on the vibration pattern information and the noise vibration pattern information.

[0043] The noise removal unit 140 may remove the influence of vibrations resulting from noise factors, for example, by calculating the difference between the vibration pattern information and the noise vibration pattern information.

[0044] The vibration pattern indicated by the vibration pattern information may include vibrations caused by noises other than the communication of the specified insects, in addition to vibrations caused by the communication of the specified insects. Therefore, the noise removal unit 140 can generate vibration pattern information of vibrations caused by the communication of the specified insects by removing the influence of vibrations caused by noise factors.

[0045] The frequency analysis unit 150 analyzes the frequency components of the vibration based on the vibration pattern information.

[0046] The frequency analysis section 150 may analyze the frequency components of the vibration based on the vibration pattern information from which the influence of vibrations resulting from noise factors has been removed by the noise removal section 140.

[0047] The frequency analysis section 150 may analyze the frequency components of the vibration using, for example, a Fourier transform.

[0048] Figures 4A and 4B are diagrams showing examples of the results of analysis processing by the frequency analysis unit 150. Figures 4A and 4B show examples of the results of analysis based on the vibration pattern information in Figures 3A and 3B, respectively.

[0049] 4A and 4B, the frequency analysis unit 150 analyzes the power of each frequency for each measurement time by analyzing the time-frequency characteristics of the power spectrum based on the vibration pattern information. It can also be seen that there is a difference between the power of each frequency of the vibration pattern when both male and female planthoppers are attached to rice plants and the power of each frequency of the vibration pattern when only male planthoppers are attached to rice plants.

[0050] The communication determination unit 160 determines the communication status of a predetermined insect in the target crop based on the vibration pattern information, generates communication status information indicating the result of the determination, and stores it in the storage unit 110.

[0051] The communication status information output by the communication determination unit 160 may include, for example, information in which section information indicating a section to be determined in a farm field is associated with a determination result of the communication status. The determination result of the communication status may include, for example, at least any of the following: whether or not there is communication between predetermined insects in the determination target crop, whether or not there is communication between male and female predetermined insects, whether or not there is communication between males of predetermined insects, whether or not there is communication between females of predetermined insects, and the number of predetermined insects that are communicating.

[0052] Furthermore, the communication determination section 160 can determine the communication state based on the pattern of frequency components obtained by analyzing the vibration pattern information.

[0053] The communication determination unit 160 can determine the communication status of a predetermined insect in the target crop, for example, based on first correspondence information indicating the correspondence between the vibration pattern (or the pattern of frequency components) and the communication status of a predetermined insect.

[0054] Here, the first correspondence information may be, for example, information indicating the correspondence between a predetermined communication situation of a predetermined insect, which is measured in advance in a farm field or a predetermined facility, and a vibration pattern (or a pattern of frequency components) of a target crop having the communication situation. The first correspondence information may also be, for example, a learning model that is learned based on a predetermined communication situation of a predetermined insect, which is measured in advance in a farm field or a predetermined facility, and a vibration pattern (or a pattern of frequency components) of a target crop having the communication situation. In other words, the first correspondence information may be, for example, a learning model that outputs the presence or absence of a communication situation of a predetermined insect when vibration pattern information (or a pattern of frequency components) is input.

[0055] The first correspondence relationship information may be generated, for example, by acquiring a vibration pattern (or a pattern of frequency components) of a target crop on which predetermined insects with a predetermined male / female ratio are attached.

[0056] The predetermined communication status of the predetermined insect in the first correspondence relationship information may include, for example, the communication status of the male and female of the predetermined insect. That is, in this case, the predetermined communication status of the predetermined insect may include, for example, a communication status in which the male and female of the predetermined insect are communicating, a communication status in which only the female of the predetermined insect is communicating, a communication status in which only the male of the predetermined insect is communicating, and a communication status in which the predetermined insect is not communicating. This allows the attachment status determination system 100 to determine the communication status of the male and female of the predetermined insect.

[0057] Furthermore, the communication status of the predetermined insects in the first correspondence information may include, for example, the communication status of a predetermined number of predetermined insects. That is, in this case, the attachment status of the predetermined number of predetermined insects may include, for example, a communication status in which 0 predetermined insects are communicating (a communication status in which no insects are communicating), a communication status in which 5 predetermined insects are communicating, and a communication status in which 10 predetermined insects are communicating. This allows the attachment status determination system 100 to determine the number of attached predetermined insects.

[0058] Furthermore, the communication status of the predetermined insects in the first correspondence information may include, for example, communication statuses of males and females of a predetermined number of predetermined insects.

[0059] Note that the crop to be determined that has been measured in advance in the first correspondence information and the crop to be determined in the vibration pattern information may be, for example, the same or different strains, or the same or different kinds of crops.

[0060] The adhesion determination unit 170 determines the adhesion state of a predetermined insect in the crop to be determined based on the vibration pattern information, generates adhesion state information indicating the result of the determination, and stores it in the storage unit 110.

[0061] Furthermore, the adhesion determining unit 170 can determine the adhesion state based on the pattern of frequency components obtained by analyzing the vibration pattern information.

[0062] The adhesion determination section 170 can determine the adhesion state of a specified insect in the target crop, for example, based on second correspondence information indicating the correspondence between the vibration pattern (or the pattern of frequency components) and the adhesion state of a specified insect.

[0063] Here, the second correspondence information may be, for example, information indicating the correspondence between a predetermined attachment state of a predetermined insect, which is measured in advance in a farm field or a predetermined experimental facility, and a vibration pattern (or a pattern of frequency components) of a target crop having the attachment state. The second correspondence information may be, for example, a learning model that is learned based on a predetermined attachment state of a predetermined insect, which is measured in advance in a farm field or a predetermined experimental facility, and a vibration pattern (or a pattern of frequency components) of a target crop having the attachment state. In other words, the second correspondence information may be, for example, a learning model that outputs the presence or absence of an attachment state of a predetermined insect when vibration pattern information (or a pattern of frequency components) is input.

[0064] The specified attachment state of the specified insect in the second correspondence information may include, for example, the attachment state of the male and female of the specified insect. That is, in this case, the specified attachment state of the specified insect may include, for example, an attachment state where both male and female of the specified insect are attached, an attachment state where only female of the specified insect is attached, an attachment state where only male of the specified insect is attached, and an attachment state where no specified insect is attached. This allows the attachment state determination system 100 to determine the attachment state of the male and female of the specified insect.

[0065] Furthermore, the attachment status of the predetermined insects in the second correspondence relationship information may include, for example, the attachment status of a predetermined number of predetermined insects. That is, in this case, the attachment status of the predetermined number of predetermined insects may include, for example, an attachment status where 0 predetermined insects are attached (an attachment status where no insects are attached), an attachment status where 5 predetermined insects are attached, and an attachment status where 10 predetermined insects are attached. This allows the attachment status determination system 100 to determine the number of attached predetermined insects.

[0066] Furthermore, the attachment status of the predetermined insects in the second correspondence information may include, for example, the attachment status of males and females of a predetermined number of the predetermined insects.

[0067] Furthermore, the adhesion determining section 170 may determine the adhesion state based on the vibration pattern information from which the influence of vibrations resulting from noise factors has been removed by the noise removing section 140.

[0068] Furthermore, the adhesion determining unit 170 may determine the adhesion state based on the determined communication state.

[0069] At this time, if the communication determination unit 160 determines that "a male and female of a specified insect are communicating," the adhesion determination unit 170 can determine that a male and female of a specified insect are attached to the crop being evaluated.

[0070] The adhesion status information generated by the adhesion determination unit 170 may include, for example, information in which section information indicating a section to be determined in a farm field is associated with a determination result of the adhesion status. The determination result of the adhesion status may include, for example, at least any of the following: presence or absence of a specific insect in the determination target crop, presence or absence of male and female specific insects, presence or absence of male specific insects, presence or absence of female specific insects, and the number of specific insects attached.

[0071] In this way, the adhesion determination unit 170 can determine the adhesion state of the predetermined insects that are actually attached to the crop to be determined based on the vibration pattern information. In this regard, for example, when a trap for capturing the predetermined insects is used and the adhesion state of the predetermined insects is determined based on the number of the predetermined insects captured by the trap, factors other than the adhesion state of the predetermined insects, such as the installation position of the trap and the trapping ability (e.g., adhesive strength) of the trap, may affect the determination result. However, the adhesion state determination system 100 determines the adhesion state of the predetermined insects that are actually attached to the crop to be determined based on the vibration pattern information caused by the communication of the predetermined insects that are actually attached to the crop to be determined. Therefore, the adhesion state determination system 100 can determine the adhesion state of the predetermined insects with higher accuracy.

[0072] The growth prediction unit 180 predicts the future habitation state of the specified insect in the field based on the determined attachment state, generates growth prediction information indicating the result of the prediction, and stores it in the storage unit 110.

[0073] The growth prediction unit 180 can predict the future habitation status of a given insect in a farm field, for example, based on a growth prediction model set in advance.

[0074] The growth prediction model may be, for example, a model that outputs the future habitation status of a specific insect in a farm field when the attachment status of the specific insect is input. The growth prediction model may be, for example, a model that predicts that the number of the specific insects will increase in the future as the number of males and females of the specific insects attached increases, or a model that predicts that the number of the specific insects will not increase in the future when only males of the specific insects are attached.

[0075] The growth prediction information generated by the growth prediction unit 180 is, for example, information indicating the growth status of a specific insect in a field after a certain period of time. The growth status of a specific insect in a field after a certain period of time may be, for example, information indicating the total number of specific insects growing in the field or the number or ratio of males and females after a certain period of time.

[0076] 5 is a diagram showing an example of growth prediction information stored in the storage unit 110. The growth prediction information stored in the storage unit 110 includes, for example, a growth prediction ID, block information, and growth prediction content information. The growth prediction ID is information for identifying the growth prediction information stored in the storage unit 110. The growth prediction content information is information indicating the content of the prediction result by the growth prediction unit 180, and is, for example, information indicating the growth status of a specific insect in a field after a certain period of time.

[0077] The output unit 190 outputs information related to the determined adhesion state. More specifically, the output unit 190 can output the adhesion state information generated by the adhesion determination unit 170, for example.

[0078] Furthermore, the output unit 190 can output, for example, communication determination information generated by the communication determination unit 160 and growth prediction information generated by the growth prediction unit 180.

[0079] The output unit 190 can output information on the determined adhesion state to, for example, the user device 200. At this time, the output unit 190 may output the information directly to the user device 200, for example, or may output the information through a predetermined information processing device that provides a predetermined information processing service to the user device 200. The predetermined information processing device may be, for example, an information processing device that provides a service for managing the growth state of crops in a field to the user device 200.

[0080] FIG. 6 is a flowchart showing an example of the process in the adhesion state determination system 100.

[0081] First, the noise vibration pattern acquisition unit 130 acquires noise vibration pattern information (S601). The vibration pattern acquisition unit 120 acquires vibration pattern information (S602). The noise removal unit 140 removes the influence of vibration caused by noise factors in the vibration pattern information based on the vibration pattern information and the noise vibration pattern information (S603). The frequency analysis unit 150 analyzes the frequency components of the vibration pattern information from which noise has been removed (S604).

[0082] The communication determination unit 160 determines the communication state of the predetermined insect based on the noise-removed vibration pattern information or the analyzed frequency component pattern (S605). The attachment determination unit 170 determines the attachment state of the predetermined insect based on the communication state of the predetermined insect (S606).

[0083] The growth prediction unit 180 predicts the future growth state based on the result of the adhesion state determination (S607). The output unit 190 outputs at least one of the communication determination information, the adhesion state information, and the growth prediction result information (S608).

[0084] Next, a control optimum timing prediction system 101, which is a modified example of the adhesion state determination system 100, will be described.

[0085] The optimal control timing prediction system 101 is an information processing system that predicts the optimal timing for control treatment of a specific insect in a field, based on the future growth status of the specific insect, which is predicted based on the attachment status of the specific insect in the crop being evaluated in the field.

[0086] FIG. 7 is a diagram showing the configuration of a pest control optimum timing prediction system 101 according to one embodiment of the present invention.

[0087] The control optimum timing prediction system 101 is connected to the user device 200 via a network such as the Internet in a manner that allows communication therebetween, similar to the adhesion state determination system 100. Similarly to the adhesion state determination system 100, the control optimum timing prediction system 101 includes a memory unit 110, a vibration pattern acquisition unit 120, a noise vibration pattern acquisition unit 130, a noise removal unit 140, a frequency analysis unit 150, a communication determination unit 160, an adhesion determination unit 170, a growth prediction unit 180, and an output unit 190. Unless otherwise specified, the processing of each unit included in the control optimum timing prediction system 101 is the same as the processing of the corresponding unit in the adhesion state determination system 100.

[0088] The storage unit 110 stores information processed in the pest-control optimum timing prediction system 101. The storage unit 110 can store, for example, vibration pattern information, communication status information, adhesion status information, growth prediction information, and pest-control optimum timing prediction information, which will be described later.

[0089] The pest control optimum timing prediction system 101 further includes a pest control optimum timing prediction unit 185.

[0090] The optimal control timing prediction unit 185 predicts the timing suitable for pest control treatment of a specified insect in the field based on the prediction by the growth prediction unit 180, generates optimal control timing prediction information indicating the results of the prediction, and stores it in the memory unit 110.

[0091] The optimal control timing prediction unit 185 can predict, based on the prediction by the growth prediction unit 180, for example, the timing (e.g., date) when the growth number (total number, number of females, or number of males) of a specified insect exceeds a specified threshold value as an appropriate timing for control treatment of the specified insect.

[0092] 8 is a diagram showing an example of pest control optimum time prediction information stored in the storage unit 110. The pest control optimum time prediction information stored in the storage unit 110 includes, for example, an optimum time prediction ID, section information, and optimum time prediction content information. The optimum time prediction ID is information for identifying the pest control optimum time prediction information stored in the storage unit 110.

[0093] The optimum timing prediction content information is information indicating the contents of the prediction result by the optimum control timing prediction unit 185, for example, information indicating the timing suitable for control treatment. Note that the timing suitable for control treatment may be information indicating a specific date, such as "July 10th", or may be information indicating the timing of the optimum control period relatively, such as "3 days later".

[0094] The output unit 190 can output information on the optimum control timing prediction.

[0095] The user device 200 acquires information output by the pest control optimum timing prediction system 101 (for example, communication status information, adhesion status information, growth prediction information, or pest control optimum timing prediction information).

[0096] Fig. 9 is a flowchart showing an example of processing in the optimal control time prediction system 101. The processing of S901 to S907 is the same as S601 to S607 in Fig. 6. Next, the optimal control time prediction unit 185 predicts the optimal control time based on the predicted growth state (S908). Then, the output unit 190 outputs at least one of communication judgment information, adhesion state information, growth prediction result information, and optimal control time prediction information (S909).

[0097] Next, an example of a hardware configuration in the case where the adhesion state determination system 100 is realized by a computer 1000 will be described with reference to Fig. 10. Fig. 10 is a diagram showing an example of a hardware configuration of the computer 1000.

[0098] As shown in FIG. 10, a computer 1000 includes, for example, a processor 1001, a memory 1002, a storage device 1003, an input I / F unit 1004, a data I / F unit 1005, a communication I / F unit 1006, and a display device 1007.

[0099] The computer 1000 may be, for example, a server computer, a personal computer (e.g., a desktop, laptop, tablet, etc.), a media computing platform (e.g., a cable, satellite set-top box, digital video recorder, etc.), a handheld computing device (e.g., a PDA, email client, etc.), or some other type of computing or communications platform.

[0100] The processor 1001 is a control unit that controls various processes in the computer 1000 by executing programs stored in the memory 1002 .

[0101] The memory 1002 is a storage medium such as a RAM (Random Access Memory), etc. The memory 1002 temporarily stores the program code of the program executed by the processor 1001 and data required when the program is executed.

[0102] The storage device 1003 is a non-volatile storage medium such as a hard disk drive (HDD), a flash memory, etc. The storage device 1003 stores an operating system and various programs for implementing the above-mentioned components.

[0103] The input I / F unit 1004 is a device for receiving input from a user. The input I / F unit 1004 is, for example, a keyboard, a mouse, a touch panel, various sensors, a wearable device, etc. The input I / F unit 1004 may be connected to the computer 1000 via an interface such as a USB (Universal Serial Bus).

[0104] The data I / F unit 1005 is a device for inputting data from outside the computer 1000. The data I / F unit 1005 is, for example, a drive device for reading data stored in various storage media. The data I / F unit 1005 may be provided outside the computer 1000. When the data I / F unit 1005 is provided outside the computer 1000, the data I / F unit 1005 is connected to the computer 1000 via an interface such as a USB.

[0105] The communication I / F unit 1006 is a device for performing data communication via a network such as the Internet, either wired or wirelessly, with an external device of the computer 1000. The communication I / F unit 1006 may be provided outside the computer 1000. When the communication I / F unit 1006 is provided outside the computer 1000, the communication I / F unit 1006 is connected to the computer 1000 via an interface such as a USB.

[0106] The display device 1007 is a device for displaying various types of information. The display device 1007 is, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, a display of a wearable device, or the like. The display device 1007 may be provided outside the computer 1000. When the display device 1007 is provided outside the computer 1000, the display device 1007 is connected to the computer 1000 via, for example, a display cable. Furthermore, when a touch panel is adopted as the input I / F unit 1004, the display device 1007 may be configured integrally with the input I / F unit 1004.

[0107] An embodiment of the present invention has been described above. The attachment state determination system 100 acquires vibration pattern information, determines the attachment state of a specific insect based on the vibration pattern information, and outputs information related to the determined attachment state. This allows the attachment state determination system 100 to determine the attachment state of insects in a crop with high accuracy.

[0108] Furthermore, the attachment status determination system 100 can determine the communication status of a specific insect based on the vibration pattern information, and can determine the attachment status of the specific insect based on the determined communication status. This allows the attachment status determination system 100 to determine the communication status of a specific insect and determine the attachment status of the specific insect with high accuracy.

[0109] Furthermore, the attachment status determination system 100 can predict the future growth status of a specific insect based on the determined attachment status. This allows the attachment status determination system 100 to predict the future growth status of a specific insect with high accuracy.

[0110] Furthermore, the adhesion state determination system 100 can analyze the frequency components of the vibration based on the vibration pattern information and determine the adhesion state based on the pattern of the analyzed frequency components. This allows the adhesion state to be determined with high accuracy by evaluating the difference in frequency components of the vibration pattern information according to the difference in adhesion state.

[0111] Furthermore, the adhesion state determination system 100 can analyze the frequency components of the vibration based on the vibration pattern information and determine the communication state based on the pattern of the analyzed frequency components. This allows the communication state to be determined with high accuracy by evaluating the difference in the pattern of the frequency components of the vibration pattern information according to the difference in adhesion state.

[0112] Furthermore, the adhesion state determination system 100 can acquire noise vibration pattern information, remove the influence of vibrations originating from noise factors in the vibration pattern information, and determine the adhesion state based on the vibration pattern information from which the noise factors have been removed. This allows the adhesion state determination system 100 to remove the influence originating from noise factors and determine the adhesion state with high accuracy.

[0113] In addition, the system for predicting optimal control timing 101 can acquire vibration pattern information, determine the adhesion state based on the vibration pattern information, predict the future growth state based on the determined adhesion state, and predict the timing suitable for control treatment of a predetermined insect in a farm field based on the predicted growth state. As a result, the system for predicting optimal control timing 101 can predict the timing suitable for control treatment with high accuracy, and minimize the number of control treatments and the amount of chemical used in the control treatment.

[0114] It should be noted that the present embodiment is provided to facilitate understanding of the present invention, and is not intended to limit the present invention. The present invention may be modified or improved without departing from the spirit of the present invention, and equivalents thereof are also included in the present invention.

[0115] In the present invention, a "unit" does not simply mean a physical means, but also includes cases where the functions of the "unit" are realized by software. Furthermore, the functions of one "unit" or device may be realized by two or more physical means, devices, or software, and the functions of two or more "units" or devices may be realized by one physical means, device, or software. [Explanation of symbols]

[0116] 100 Adhesion status determination system, 101 Control optimum timing prediction system, 110 Memory unit, 120 Vibration pattern acquisition unit, 130 Noise vibration pattern acquisition unit, 140 Noise removal unit, 150 Frequency analysis unit, 160 Communication determination unit, 170 Adhesion determination unit, 180 Growth prediction unit, 185 Control optimum timing prediction unit, 190 Output unit, 200 User device

Claims

1. a vibration pattern acquisition unit that acquires vibration pattern information indicating a vibration pattern of a target crop that grows in a farm field; an adhesion determination unit for determining an adhesion state of a predetermined insect in the target crop based on the vibration pattern information; an output unit that outputs information regarding the determined adhesion state; An adhesion status determination system comprising:

2. a communication determination unit that determines a communication state of the predetermined insect in the target crop based on the vibration pattern information, The adhesion determination unit determines the adhesion state based on the determined communication state. The adhesion state determination system according to claim 1 .

3. The attachment status determination system according to claim 1 or 2, further comprising a habitat prediction unit that predicts a future habitat status of the specified insect in the field based on the determined attachment status.

4. A frequency analysis unit that analyzes a frequency component of the vibration based on the vibration pattern information, The adhesion determination unit determines the adhesion state based on a pattern of the frequency components. The adhesion state determination system according to claim 1 .

5. A frequency analysis unit that analyzes a frequency component of the vibration based on the vibration pattern information, The communication determination unit determines the communication state based on the frequency component. The adhesion state determination system according to claim 2 .

6. a noise vibration pattern acquisition unit that acquires noise vibration pattern information indicating a pattern of vibration of the target crop caused by a noise factor other than the predetermined insect, the noise vibration pattern information being measured in advance; a noise removal unit that removes an influence of vibration caused by the noise factor in the vibration pattern information based on the vibration pattern information and the noise vibration pattern information; Further equipped with The adhesion determination unit determines the adhesion state based on the vibration pattern information from which the removal has been performed. The adhesion state determination system according to claim 1 or 2.

7. The crop to be determined is rice, The predetermined insect is a pest that attaches to rice. The adhesion state determination system according to claim 1 or 2.

8. a vibration pattern acquisition unit that acquires vibration pattern information indicating a vibration pattern of a target crop that grows in a farm field; an adhesion determination unit for determining an adhesion state of a predetermined insect in the target crop based on the vibration pattern information; A habitat prediction unit that predicts a future habitat state of the predetermined insect in the field based on the determined attachment state; A control optimum timing prediction unit that predicts a suitable timing for the control treatment of the predetermined insect in the field based on the prediction; A pest control optimum timing prediction system.

9. The computer acquiring vibration pattern information indicating a vibration pattern of a target crop inhabiting the field; determining a state of attachment of a predetermined insect to the target crop based on the vibration pattern information; outputting information regarding the determined adhesion state; Method for determining adhesion status.

10. On the computer, a vibration pattern acquisition unit that acquires vibration pattern information indicating a vibration pattern of a target crop that grows in a farm field; an adhesion determination unit for determining an adhesion state of a predetermined insect in the target crop based on the vibration pattern information; an output unit that outputs information regarding the determined adhesion state; A program for determining adhesion status to achieve this.

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