JP7801940B2 - Weeding support device - Google Patents

Description

The present invention relates to a weeding assistance device.

Patent Document 1 discloses a technology that divides farmland into multiple subdivisions, obtains images of each subdivision, and then determines the presence or absence of weeds in each subdivision, and then injects herbicide into all subdivisions that contain weeds.

Japanese Patent Application Publication No. 9-81750

The technology disclosed in Patent Document 1 had the problem of being unable to perform precise weed control that was tailored to the specific growth conditions of weeds in the subdivided areas.

A weeding support device according to a preferred aspect of the present disclosure includes a first identification unit and a first determination unit. The first identification unit identifies the number of weed stalks in each area based on captured images of each area obtained by dividing farmland into multiple areas. The first determination unit determines a target area from among the multiple areas to be subjected to weeding work, based on the number of weed stalks in each area identified by the first identification unit.

A weeding support device according to another preferred aspect of the present disclosure includes a second identification unit and a third determination unit. The second identification unit identifies the area of the region where weeds have grown for each of the multiple areas based on captured images of each area obtained by dividing farmland into multiple areas. The third determination unit determines, among the multiple areas, an area where the ratio of the area identified by the second identification unit to the total area is equal to or greater than a predetermined threshold as a target area for weeding work.

A weeding support device according to another preferred aspect of the present disclosure includes a third identification unit and a fourth determination unit. The third identification unit identifies the area of bare ground where no grass or weeds are growing for each of the multiple areas based on captured images of each area obtained by dividing farmland into multiple areas. The fourth determination unit determines, as target areas for weeding work, areas among the multiple areas where the ratio of the area of bare ground identified by the third identification unit to the total area is equal to or greater than a predetermined threshold.

The weeding support device disclosed herein enables meticulous weeding in accordance with the detailed growth conditions of weeds, on an area-by-area basis obtained by dividing farmland into multiple areas.

FIG. 1 is a block diagram showing an example of the configuration of a weeding system 1A including a weeding support device 20A according to a first embodiment. FIG. 1 is a diagram illustrating an example of farmland A and an area R(n, m). FIG. 2 is a block diagram showing an example of the configuration of a weeding support device 20A. FIG. 10 is a diagram for explaining the operation of a first determination unit 212. 10 is a flowchart showing the flow of a weeding support method executed by a processing device 210 of a weeding support device 20A according to a program PR1. FIG. 10 is a block diagram showing an example configuration of a weeding support device 20B according to a second embodiment of the present disclosure. FIG. 10 is a block diagram showing a configuration example of a weeding support device 20C according to a third embodiment of the present disclosure.

(A: First embodiment)
1 is a diagram showing an example configuration of a weeding system 1A including a weeding support device 20A according to a first embodiment of the present disclosure. The weeding system 1A is an information system for weeding weeds that occur in farmland. In addition to the weeding support device 20A, the weeding system 1A also includes an imaging drone 10, a weeding device 30A, and a weeding device 30B.

In this embodiment, the farmland A that is the target of weeding work is pastureland. As shown in Figure 2, the farmland A is divided into multiple areas R(n, m) in a matrix of N rows and M columns. In the example shown in Figure 2, N is 4 and M is 3. Furthermore, n is any natural number between 1 and N, and m is any natural number between 1 and M. In this embodiment, the need for weeding is determined for each area R(n, m). Hereinafter, areas R(n, m) that are determined to require weeding will be referred to as target areas.

Weeding device 30A and weeding device 30B are devices that spray herbicides over a target area. Weeding device 30A is a drone that has the function of spraying herbicides. Weeding device 30B is a tractor that has the function of spraying herbicides. In this embodiment, weeding device 30A or weeding device 30B is used to spray herbicides over a target area.

Under the control of a user device used by the user of the weeding system 1A, the imaging drone 10 captures images of each area (n, m) obtained by dividing the farmland A into multiple areas. Specific examples of user devices include a smartphone or tablet used by the user of the weeding system 1A.

The weeding support device 20A is a device equipped with the function of wirelessly communicating with the imaging drone 10. Note that communication between the weeding support device 20A and the imaging drone 10 may be via a user device. For each of multiple areas R(n, m), the weeding support device 20A acquires image data D(n, m) representing an image of the area (n, m) from the imaging drone 10. Based on the acquired image data D(n, m), the weeding support device 20A identifies the number of weeds occurring in the area (n, m) for each type of weed.

The type of weeds for which the number of plants is specified for each area (n, m) by the weeding support device 20A (i.e., the type of weeds to be weeded) varies depending on the type of farmland A. In this embodiment, farmland A is pasture, and specific examples of weeds to be weeded include dandelion, Rumex gracilis, and thistle. Note that when the weeding system 1A is applied to support weeding in paddy fields, i.e., when farmland A is a paddy field, specific examples of weeds to be weeded include sedge and goldenrod.

In this embodiment, the herbicidal effects of the target plants for weeding, dandelion, Rumex gracilis, and Rumex japonica, vary depending on the type of herbicide. Specifically, herbicide Y1 has the highest herbicidal effect on dandelion. Herbicide Y2 has the highest herbicidal effect on Rumex gracilis. Herbicide Y3 has the highest herbicidal effect on Rumex japonica.

For each area R (n, m) obtained by dividing farmland A into multiple areas, weeding support device 20A identifies the number of dandelion, Rumex gracilis, and thistle plants growing within the area. Weeding support device 20A then determines the target area and the type of herbicide to be sprayed on the target area based on the number of dandelion, Rumex gracilis, and thistle plants growing within the area. Furthermore, weeding support device 20A determines the equipment to spray the herbicide on the target area from weeding device 30A and weeding device 30B.

Figure 3 is a block diagram showing an example configuration of the weeding support device 20A. As shown in Figure 3, the weeding support device 20A has a processing device 210, a communication device 220, a display device 230, an input device 240, and a storage device 250.

The processing device 210 includes one or more central processing units (CPUs). A CPU is an example of a computer. The processing device 210 functions as the control center of the weeding support device 20A by executing the program PA stored in the storage device 250.

The communication device 220 is hardware (transmission/reception device) for communicating with the imaging drone 10, the weeding support device 20A, the weeding device 30A, or the weeding device 30B. The communication device 220 is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc.

The display device 230 is, for example, a liquid crystal display. The display device 230 displays various images under the control of the processing device 210. The input device 240 is, for example, a pointing device such as a mouse, or a keyboard. The input device 240 accepts user operations and outputs data indicating the operations to the processing device 210.

The storage device 250 is a recording medium readable by the processing device 210. The storage device 250 includes, for example, non-volatile memory and volatile memory. Non-volatile memory is, for example, ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory). Volatile memory is, for example, RAM (Random Access Memory). The non-volatile memory included in the storage device 250 stores the program PA in advance. The volatile memory included in the storage device 250 is used by the processing device 210 as a work area when executing the program PA.

The processing device 210 reads the program PA from the storage device 250. By executing the program PA, the processing device 210 functions as the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214 shown in FIG. 3. In other words, the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214 shown in FIG. 3 are software modules realized by operating a computer in accordance with software. The functions of the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214 are as follows:

The first identification unit 211 identifies the number of weeds occurring in area R(m,n) for each type of weed based on image data D(m,n), where n is a natural number between 1 and N and m is a natural number between 1 and M. As mentioned above, the weeds to be removed in this embodiment are dandelion, Rumex gracilis, and thistle. Therefore, the first identification unit 211 identifies the number of dandelion, Rumex gracilis, and thistle plants occurring in area R(m,n) based on image data D(m,n).

More specifically, the first identification unit 211 divides the image data D(m, n) into multiple sub-image data pieces, each having a predetermined pixel size. The first identification unit 211 identifies the number of weeds present for each type of weed by performing image recognition using a learning model trained on the image characteristics of weeds for each type of weed for each of the multiple sub-image data pieces. In this embodiment, the first identification unit 211 identifies the number of dandelion plants, Rumex spp., and Rumex spp. for each sub-image data piece by performing image recognition using a learning model trained on the image characteristics of dandelions, Rumex spp., and Rumex spp. for each type of weed. The first identification unit 211 then aggregates the number of weed plants identified based on each sub-image data piece for each type of weed, thereby identifying the number of weeds present in area R(m, n) for each type of weed. Note that existing technologies may be appropriately employed for generating the learning model trained on the image characteristics of weeds for each type of weed, and for image recognition using this learning model.

The first determination unit 212 determines the target area for weeding work based on the number of weeds of each type identified by the first identification unit 211. More specifically, the first determination unit 212 determines the target area for each type of weed by comparing the number of weeds identified by the first identification unit 211 with a threshold value that is predetermined for that type of weed.

For example, suppose the threshold for the number of dandelion plants is th1, the threshold for the number of Rumex plants is th2, and the threshold for the number of thistle plants is th3. Furthermore, suppose the numbers of dandelion, Rumex, and thistle plants identified by the first identification unit 211 for area R(n,m) are Z1, Z2, and Z3, respectively. In this embodiment, the first determination unit 212 determines area R(n,m) as the target area if Z1≧th1, Z2≧th2, and Z3≧th3. Figure 4 shows an example in which areas R(1,1) and R(4,3) have been determined as target areas. In the example shown in Figure 4, target areas are hatched, and non-target areas are outlined.

The first determination unit 212 may cause the display device 230 to display an image showing the distribution of target areas in farmland A. A user who views this image may operate the input device 240 to exclude the target areas determined by the first determination unit 212 from the areas subject to weeding work, or may change areas that were not subject to weeding work to target areas.

The second determination unit 213 determines the type of herbicide to be sprayed in the target area determined by the first determination unit 212 based on the number of weeds of each type identified by the first identification unit 211.

For example, if Z1 is the largest among Z1, Z2, and Z3 identified for area R(n, m), the second determination unit 213 determines the type of herbicide to be sprayed on area R(n, m) to be herbicide Y1, which has the highest herbicidal effect against dandelions. Similarly, if Z2 is the largest among Z1, Z2, and Z3, the second determination unit 213 determines the type of herbicide to be sprayed to be herbicide Y2, which has the highest herbicidal effect against Rumex. Furthermore, if Z3 is the largest among Z1, Z2, and Z3, the second determination unit 213 determines the type of herbicide to be sprayed to be herbicide Y3, which has the highest herbicidal effect against thistle.

The fifth determination unit 214 determines the equipment to be used for weeding work from weeding device 30A and weeding device 30B based on the proportion of the total area of farmland A that is the sum of the areas of each target area determined by the first determination unit 212.

In this embodiment, if the sum of the areas of the target areas determined by the first determination unit 212 accounts for 60% or more of the total area of farmland A, the fifth determination unit 214 determines the weeding device 30B as the device to be used for weeding. On the other hand, if the sum of the areas of the target areas determined by the first determination unit 212 accounts for less than 60% of the total area of farmland A, the fifth determination unit 214 determines the weeding device 30A as the device to be used for weeding. The greater the proportion of the sum of the areas of the target areas to the total area of farmland A, the more efficient the weeding will be by using weeding device 30B. On the other hand, the smaller the proportion of the sum of the areas of the target areas to the total area of farmland A, the more pinpointed weeding can be performed using weeding device 30A, thereby reducing the cost of weeding.

If the fifth decision unit 214 decides that the equipment to be used for weeding work is weeding device 30A, it generates weeding information indicating the flight path of weeding device 30A relative to farmland A and the type of herbicide to be sprayed in each target area, and transmits the generated weeding information to weeding device 30A using the communication device 220. If the fifth decision unit 214 decides that the equipment to be used for weeding work is weeding device 30B, it generates weeding information indicating the position of each target area in farmland A and the type of herbicide to be sprayed in each target area, and transmits the generated weeding information to weeding device 30B using the communication device 220.

For example, as shown in Figure 4, assume that area R (1, 1) and area R (4, 3) are determined as target areas by the first determination unit 212. In this case, the proportion of the sum of the areas of the target areas to the total area of farmland A is 2/12, or approximately 17%, so the fifth determination unit 214 determines that the equipment to be used for weeding work will be weeding device 30A and transmits weeding information to weeding device 30A.

Furthermore, the processing device 210, operating in accordance with the program PA, executes the weeding support method of the present disclosure. Figure 5 is a flowchart showing the flow of this weeding support method. As shown in Figure 5, this weeding support method includes the processes of steps SA110 to SA140.

In step SA110, the processing device 210 functions as a first identification unit 211. In step SA110, the processing device 210 identifies the number of weeds occurring in area R(m,n) for each type of weed based on image data D(m,n).

In step SA120, the processing device 210 functions as the first determination unit 212. In step SA120, the processing device 210 determines the target area for weeding work based on the number of weeds of each type identified by the first identification unit 211.

In step SA130, the processing device 210 functions as the second determination unit 213. In step SA130, the processing device 210 determines the type of herbicide to be sprayed for each target area based on the number of weeds of each type identified by the first identification unit 211.

In step SA140, the processing device 210 functions as a fifth determination unit 214. In step SA140, the processing device 210 determines which equipment to use for the weeding work, from weeding device 30A and weeding device 30B, based on the proportion of the total area of farmland A that is the sum of the areas of the target areas determined by the first determination unit 212.

The weeding support device 20A of the first embodiment determines whether or not weeding is necessary based on the number of weeds of each type that have emerged for each area R (n, m) obtained by dividing farmland A into multiple areas. Because the need for weeding is determined for each area R (n, m), the amount of herbicide sprayed is reduced compared to spraying herbicide evenly over the entire farmland A.

In addition, the weeding support device 20A of the first embodiment precisely determines the type of herbicide to be sprayed in each target area based on the number of weeds of each type that have grown in the target area, allowing the herbicide with the highest weed-killing effect to be sprayed in each target area.

Furthermore, with the weeding support device 20A of the first embodiment, the equipment to be used for weeding work can be determined based on the proportion of the target area relative to the farmland A, improving the efficiency of weeding work.

As explained above, the weeding support device 20A of the first embodiment can efficiently perform detailed weeding in accordance with the growth conditions of weeds in each target area obtained by dividing farmland A into multiple areas.

(B: Second embodiment)
A weeding support device 20B shown in FIG. 6 may be used instead of the weeding support device 20A. FIG. 6 is a block diagram showing an example of the configuration of the weeding support device 20B. In FIG. 6, the same components as those in FIG. 3 are denoted by the same reference numerals. As is clear from comparing FIG. 6 with FIG. 3, the weeding support device 20B differs from the weeding support device 20A in that a program PB is stored in the storage device 250 instead of the program PA. The processing device 210 of the weeding support device 20B executes the program PB to function as the second identification unit 216, the third determination unit 217, and the fifth determination unit 214 shown in FIG. 6. The second identification unit 216 and the third determination unit 217 are software modules, similar to the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214.

The second identification unit 216 performs a process for each area R(n,m) based on the image data D(n,m) to identify the area of the region where weeds have grown in the area R(n,m). The third determination unit 217 determines, as the target area, an area where the ratio of the area identified by the second identification unit 216 to the area of the entire area R(n,m) is equal to or greater than a predetermined threshold.

In this embodiment, the fifth determination unit 214 determines which equipment to use for weeding work, from among weeding equipment 30A and weeding equipment 30B, based on the proportion of the total area of farmland A that the sum of the areas of each target area determined by the third determination unit 217 occupies. In this embodiment, the number of weeds of each type that have emerged in each target area is not specified, so a common herbicide is sprayed on each target area. In this embodiment, the herbicide sprayed in common on each target area may be any one of herbicide Y1, herbicide Y2, and herbicide Y3, or a mixture of multiple herbicides selected from herbicide Y1, herbicide Y2, and herbicide Y3.

The second embodiment of the weeding support device 20B can weed areas obtained by dividing farmland A into multiple areas, where the ratio of the area where weeds have grown to the total area is equal to or greater than a predetermined threshold. Even if there is only one weed in area R(n,m), if the weed is large, the area of the weed-growing area in area R(n,m) will be large. This embodiment can weed weeds that have grown into large stalks, even if the number of weeds is small.

(C: Third embodiment)
Instead of the weeding support device 20B, a weeding support device 20C shown in FIG. 7 may be used. FIG. 7 is a diagram showing an example of the configuration of the weeding support device 20C according to a third embodiment of the present disclosure. In FIG. 7, the same components as those in FIG. 6 are assigned the same reference numerals. As is clear from a comparison of FIG. 7 with FIG. 6, the weeding support device 20C differs from the weeding support device 20B in that a program PC is stored in the storage device 250 instead of the program PB. The processing device 210 of the weeding support device 20C executes the program PC to function as a third identification unit 218, a fourth determination unit 219, and a fifth determination unit 214. The third identification unit 218 and the fourth determination unit 219 are software modules, similar to the second identification unit 216 and the third determination unit 217.

The third identification unit 218 identifies the area of the area R(n,m) where no grass or weeds are growing (i.e., bare ground) based on the image data D(n,m). The fourth determination unit 219 determines as the target area an area where the ratio of the bare ground area to the total area is equal to or greater than a predetermined threshold.

In this embodiment, the fifth determination unit 214 determines the equipment to be used for weeding from weeding device 30A and weeding device 30B based on the proportion of the total area of farmland A that the sum of the areas of each target area determined by the fourth determination unit 219 occupies. In this embodiment, as in the second embodiment, the number of weeds of each type that have emerged in each target area is not specified, so a common herbicide is sprayed on each target area. In this embodiment, too, the herbicide sprayed in common on each target area may be any one of herbicide Y1, herbicide Y2, and herbicide Y3, or a mixture of multiple herbicides selected from herbicide Y1, herbicide Y2, and herbicide Y3.

The third embodiment of the weeding support device 20C can weed areas obtained by dividing farmland into multiple areas, where the ratio of bare ground area to the total area is equal to or greater than a predetermined threshold.

(D: Modified Example)
The present disclosure is not limited to the above-described exemplary embodiments. Specific variations are as follows: Two or more of the following exemplary embodiments may be combined.
(D-1: Modification 1)
The second determination unit 213 may determine the concentration of the herbicide to be sprayed for each target area according to the number of weeds of each type identified by the first identification unit 211, or may determine both the type and concentration of the herbicide to be sprayed according to the number of weeds of each type identified by the first identification unit 211. Note that if the type and concentration of the herbicide to be sprayed in the target area are fixed, the second determination unit 213 may be omitted. In an aspect in which the second determination unit 213 is omitted, the first identification unit 211 may identify the number of weeds that have grown in the area regardless of the type of weed, and in this case, the first determination unit 212 may determine the target area to be subjected to weeding work according to the number of weeds identified regardless of the type of weed.

(D-2: Modification 2)
When the weeding device to be used for spraying the herbicide is predetermined to be either the weeding device 30A or the weeding device 30B, the fifth determination unit 214 may be omitted.

(D-3: Modification 3)
In the first embodiment, the program PA is stored in the storage device 250 of the weeding support device 20A, but the program PA may also be manufactured or sold separately. When selling the program PA, the program PA may be provided to a purchaser by writing it to a computer-readable recording medium such as a flash ROM and distributing it, or by downloading it via a telecommunications line. Similarly, the program PB in the second embodiment and the program PC in the third embodiment may also be manufactured or sold separately.

(D-4: Modification 4)
In the first embodiment, the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214 are software modules. However, any one, more than one, or all of the first identification unit 211, the first determination unit 212, the second determination unit 213, and the fifth determination unit 214 may be hardware modules. Specific examples of hardware modules include a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), and a field programmable gate array (FPGA). Similarly, either or both of the second identification unit 216 and the third determination unit 217 may be hardware modules, and either or both of the third identification unit 218 and the fourth determination unit 219 may be hardware modules.

(E: Other)
(1) In the above-described embodiment, the storage device 250 is exemplified by ROM and RAM, but the storage device 250 may be a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory device (e.g., a card, a stick, a key drive), a CD-ROM (Compact Disc-ROM), a register, a removable disk, a hard disk, a floppy (registered trademark) disk, a magnetic strip, a database, a server, or any other suitable storage medium. The program may also be transmitted from a network via a telecommunications line. The program may also be transmitted from a communications network via a telecommunications line.

(2) In the above-described embodiments, the described information, signals, etc. may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

(3) In the above-described embodiment, input and output information may be stored in a specific location (e.g., memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

(4) In the above-described embodiment, the determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a comparison of numerical values (e.g., comparison with a predetermined value).

(5) The order of the process procedures, sequences, flowcharts, etc. illustrated in the above-described embodiments may be changed as long as it is consistent. For example, the methods described in this disclosure present elements of various steps using an exemplary order, and are not limited to the particular order presented.

(6) There are no particular limitations on the method of realizing each functional block illustrated in Figures 3, 6, and 7. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are connected directly or indirectly (e.g., using a wired or wireless connection) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

(7) The programs exemplified in the above-described embodiments should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., regardless of whether software is called software, firmware, middleware, microcode, hardware description language, or by other names.

Software, instructions, information, etc. may also be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and/or wireless technologies (such as infrared, microwave), these wired and/or wireless technologies are included within the definition of transmission media.

(8) In each of the above embodiments, the terms "system" and "network" are used interchangeably.

(9) The information, parameters, etc. described in this disclosure may be expressed using absolute values, relative values from a predetermined value, or corresponding other information.

(10) In the above-described embodiments, the user equipment may be a mobile station (MS). Those skilled in the art may also refer to a mobile station as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable term. In addition, in this disclosure, terms such as "mobile station," "user terminal," "user equipment (UE)," and "terminal" may be used interchangeably.

(11) In the above-described embodiments, the terms "connected," "coupled," or any variations thereof refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using at least one of one or more wires, cables, and printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

(12) In the above embodiments, the phrase "based on" does not mean "based only on," unless otherwise specified. In other words, the phrase "based on" means both "based only on" and "based at least on."

(13) As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching a table, database, or other data structure), and regarding ascertaining as a "determining." Furthermore, "determining" and "determining" may include regarding receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory) as a "determining." Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judgment" or "decision." In other words, "judgment" and "decision" can include regarding some action as having been "judgment" or "decision." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

(14) In the above embodiments, when the words "include," "including," and variations thereof are used, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, the term "or" as used in this disclosure is not intended to mean an exclusive or.

(15) In this disclosure, where articles are added by translation, such as a, an, and the in English, this disclosure may include the noun following these articles being plural.

(16) In this disclosure, the term "A and B are different" may mean "A and B are different from each other." Note that this term may also mean "A and B are each different from C." Terms such as "separate" and "combined" may also be interpreted in the same way as "different."

(17) Each aspect/embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, notification of specified information (e.g., notification that "X is true") is not limited to being done explicitly, but may also be done implicitly (e.g., by not notifying the specified information).

(F: Aspects understood from the above-described embodiments or modifications)
Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure. The following aspects can be understood from at least one of the above-described embodiments or modifications.

A weeding support device according to a first aspect includes a first identification unit and a first determination unit. The first identification unit identifies the number of weeds present in each area based on captured images of each area obtained by dividing farmland into multiple areas. The first determination unit determines which of the multiple areas is to be the target area for weeding work, based on the number of weeds present in each area identified by the first identification unit. The weeding support device according to the first aspect can determine whether or not weeding is necessary, based on the number of weeds present in each area obtained by dividing farmland into multiple areas.

In a second aspect (an example of the first aspect), the first identification unit may identify the number of emerging weeds for each type of weed in each of the multiple areas. In this second aspect, the first determination unit may determine the target area for each type of weed by comparing a threshold value determined according to the type of weed with the number of emerging weeds for each type of weed identified by the first identification unit. The weeding support device according to the second aspect can determine whether or not weeding is necessary based on the number of emerging weeds for each type of weed, for each area obtained by dividing farmland into multiple areas.

The weeding support device in a third aspect (an example of the second aspect) may further include a second determination unit that determines at least one of the type and concentration of herbicide to be sprayed in the target area based on the number of stalks of each type of weed identified by the first identification unit. The weeding support device according to the third aspect can determine at least one of the type and concentration of herbicide to be sprayed in the target area based on the number of stalks of each type of weed that has grown in the target area.

A weeding support device according to a fourth aspect may include a second identification unit and a third determination unit. The second identification unit identifies the area of the area where weeds have grown for each of a plurality of areas based on captured images of each area obtained by dividing farmland into the plurality of areas. The third determination unit determines, among the plurality of areas, an area where the ratio of the area identified by the second identification unit to the total area is equal to or greater than a predetermined threshold, as a target area for weeding work. The weeding support device according to the fourth aspect can determine, for each area obtained by dividing farmland into the plurality of areas, whether weeding is necessary based on the ratio between the total area of the area and the area where weeds have grown within the area.

A weeding support device according to the fifth aspect comprises a third identification unit and a fourth determination unit. The third identification unit identifies the area of bare ground where no grass or weeds are growing for each of a plurality of areas based on captured images of each area obtained by dividing farmland into multiple areas. The fourth determination unit determines, among the multiple areas, an area where the ratio of the area of bare ground identified by the third identification unit to the total area is equal to or greater than a predetermined threshold, as a target area for weeding work. The weeding support device according to the fifth aspect can determine whether or not weeding is necessary for each area obtained by dividing farmland into multiple areas, based on the ratio of the total area to the area of bare ground.

The weeding support device according to the sixth aspect (an example of the first aspect) may further include a fifth determination unit that determines the equipment to be used for the weeding work based on at least one of the distribution of the target areas in the farmland and the proportion of the farmland occupied by the target areas. Because the weeding support device according to the sixth aspect can determine the equipment to be used for the weeding work based on at least one of the distribution of the target areas in the farmland and the proportion of the target areas occupied by the target areas, the cost-effectiveness of the weeding work is improved.

1A...weeding system, 10...imaging drone, 20A, 20B, 20C...weeding support device, 30A, 30B...weeding device, 210...processing device, 220...communication device, 230...display device, 240...input device, 250...storage device, 211...first identification unit, 212...first decision unit, 213...second decision unit, 214...fifth decision unit, 216...second identification unit, 217...third decision unit, 218...third identification unit, 219...fourth decision unit.

Claims (6)

a first identification unit that identifies the number of weeds that have emerged in each area based on captured images of each area obtained by dividing the farmland into a plurality of areas;
a first determination unit that determines a target area to be subjected to weeding work among the plurality of areas according to the number of weeds in each area identified by the first identification unit;
A weeding support device comprising: the first identification unit identifies the number of weeds occurring for each type of weed in each of the plurality of areas;
the first determination unit determines the target area by comparing, for each type of weed, a threshold value determined according to the type of weed with the number of weeds of each type of weed identified by the first identification unit.
The weeding assistance device according to claim 1 . a second determination unit that determines at least one of the type and concentration of the herbicide to be sprayed in the target area in accordance with the number of weeds of each type identified by the first identification unit;
The weeding assistance device according to claim 2. a second identification unit that identifies the area of a region where weeds have occurred for each of the plurality of areas based on captured images of each area obtained by dividing the farmland into the plurality of areas;
a third determination unit that determines, among the plurality of areas, an area where a ratio of the area identified by the second determination unit to an area of the entire area is equal to or greater than a predetermined threshold, as a target area to be subjected to weeding work;
a fifth determination unit that determines equipment to be used for the weeding work based on at least one of a distribution of the target areas in the farmland and a proportion of the target areas to the farmland;
A weeding support device comprising : a third identification unit that identifies, based on captured images of each area obtained by dividing the farmland into a plurality of areas, an area of bare land where no grass or weeds are growing for each of the plurality of areas;
a fourth determination unit that determines, among the plurality of areas, an area in which a ratio of the area of bare ground identified by the third determination unit to the area of the entire area is equal to or greater than a predetermined threshold, as a target area to be subjected to weeding work;
a fifth determination unit that determines equipment to be used for the weeding work based on at least one of a distribution of the target areas in the farmland and a proportion of the target areas to the farmland;
A weeding support device comprising : a fifth determination unit that determines equipment to be used for the weeding work based on at least one of a distribution of the target areas in the farmland and a proportion of the target areas to the farmland;
The weeding assistance device according to claim 1 .