Information processing device, information processing method, and information processing program

Abstract

To allow determination of soil survey points to facilitate efficient surveying within a given area.SOLUTION: An information processing device (10) includes a data acquisition unit (11) that acquires data including predetermined characteristic quantities of land, soil, or plants grown within a predetermined area, and a control unit (13). The control unit executes a segmentation process (S12) that generates correspondence data representing the characteristic quantities corresponding to each of a plurality of segmented areas that divide the predetermined area, a frequency distribution process (S13) that generates frequency distribution data representing the frequency distribution of the predetermined characteristic quantities, and a selection process (S14) that selects a predetermined number of segmented areas from the plurality of segmented areas as soil survey points.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] When planting (e.g., cultivating) plants (e.g., agricultural crops), the condition (soil) of land (e.g., cultivated land) may be investigated. Patent Document 1 discloses a technique for selecting points for soil investigation. This technique classifies multiple types of images of the ground, and selects one or more representative points from within an area with the same classification results. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-140607 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the above-mentioned technology, because a representative point is selected for each region of the image where the classification results are different, it is difficult to say that efficient investigation is easy. That is, if a representative point is selected for each region where the classification results are different, the number of representative points increases, which may complicate the investigation. On the other hand, if the number of representative points is limited, it becomes doubtful whether the selected representative points reflect the characteristics of the entire region being investigated, which may result in a decrease in the quality of the investigation. As such, it is not easy to select an appropriate number of representative points that reflect the characteristics of the entire region being investigated.

[0005] One aspect of the present invention aims to realize an information processing device, an information processing method, and an information processing program that enable determination of soil investigation points that facilitate efficient investigation within a specified area. [Means for solving the problem]

[0006] In order to solve the above problem, an information processing device according to one aspect of the present invention comprises a data acquisition unit that acquires data including predetermined features of land within a predetermined area, the soil of the land, or plants grown within the land, and a control unit, and the control unit executes the following processes via the data acquisition unit: an acquisition process that acquires the data; a division process that generates, based on the data, correspondence data that corresponds each of a plurality of divided areas that divide the predetermined area to the features; a frequency distribution process that generates, based on the correspondence data, frequency distribution data that represents the frequency distribution of the predetermined features; and a selection process that selects a predetermined number of divided areas from the plurality of divided areas as soil investigation points based on the frequency distribution data. [Effects of the Invention]

[0007] According to one aspect of the present invention, it is possible to realize an information processing device, an information processing method, and an information processing program that enable determination of soil investigation points that facilitate efficient investigation within a specified area. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram illustrating an example of an information processing apparatus according to an embodiment of the present invention. [Figure 2] FIG. 1 is a flowchart illustrating an example of a procedure of an information processing method according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram showing an example of land to be surveyed. [Figure 4] FIG. 10 is a diagram illustrating an example of the shortest route for visiting survey points. DETAILED DESCRIPTION OF THE INVENTION

[0009] [Embodiment 1] 1 is a block diagram showing an example of an information processing device 10 according to an embodiment of the present invention. The information processing device 10 includes an input / output unit 11, a storage unit 12, and a control unit 13.

[0010] The input / output unit 11 may have an input mechanism for inputting data and an output mechanism for outputting data. Examples of the input mechanism include a keyboard, a touch panel, an input interface, and a communication interface. Examples of the output mechanism include a display device, a printing device, an output interface, and a communication interface. The communication interface inputs and outputs data through communication with the outside, and functions as both an input mechanism and an output mechanism. The input / output unit 11 functions as a data acquisition unit that acquires data including predetermined characteristic quantities of land within a predetermined area (e.g., a farm field), the soil of the land, or plants grown in the land.

[0011] The storage unit 12 is, for example, a storage device (for example, a memory or a hard disk) that stores a table showing standard work times and movement speeds, which will be described later. The control unit 13 is, for example, configured by a CPU (Central Processing Unit), and executes the following information processing method S10.

[0012] Fig. 2 is a flow diagram showing an example of the procedure of an information processing method S10 according to an embodiment of the present invention. The information processing method includes an acquisition process S11, a classification process S12, a frequency distribution process S13, a selection process S14, a route determination process S15, a process determination process S16, and a display process S17. Fig. 3 is a diagram showing an example of land to be surveyed (e.g., a farm field).

[0013] (1) Acquisition process S11 The control unit 13 executes an acquisition process S11 to acquire data including predetermined feature amounts of land in a predetermined area, the soil of the land, or plants grown in the land via the input / output unit 11 (data acquisition unit).

[0014] The predetermined feature amount is, for example, any one of the plant's leaf color, surface temperature, appearance (disease symptoms, insect damage), vegetation index (one example is NDVI: Normalized Difference Vegetation Index), yield, land elevation difference, soil moisture content, nitrate nitrogen, and electrical conductivity (EC). Note that the plant's leaf color reflects the plant's nutritional state, for example, the quality and quantity of fertilizer components in the soil. Land elevation difference affects the amount of moisture contained in the soil. The plant's surface temperature reflects the amount of transpiration from the plant.

[0015] This data can be obtained mechanically (e.g., drones, agricultural machinery) or manually. For example, by using a drone to capture images of land (e.g., a field) from above using infrared, near-infrared, and visible light, it is possible to obtain plant leaf color, surface temperature, color images of the exterior, and vegetation index (NDVI). In addition, by equipping agricultural machinery with various sensors, it is possible to obtain yield, elevation difference, soil moisture content, nitrate nitrogen, and electrical conductivity (EC) in relation to its position on the land.

[0016] The input / output unit 11 (data acquisition unit) acquires these data in association with location information within the land (field) (a kind of map). The acquired data SD in Figure 3 is a diagram showing an example of data acquired by the input / output unit 11 (data acquisition unit). This acquired data SD represents the distribution of leaf color in a photograph of the field taken from above by a drone or the like. Basically, it represents data on leaf color within a specified area A.

[0017] (2) Segmentation process S12 (meshing) Based on this data, the control unit 13 executes a division process S12 for generating correspondence data representing each of a plurality of division areas R(i, j) that divide the predetermined area A in correspondence with the feature amount.

[0018] The control unit 13, for example, (1) divides a predetermined area A into a plurality of areas R(i,j), and (2) performs an averaging process for each divided area R(i,j) (hereinafter also referred to as "meshing"). These multiple areas R(i,j) may have the same shape and size. The averaging process is for determining a representative value of the feature quantities of each area R(i,j), and does not necessarily require the calculation of an average value. Furthermore, if area A includes a location that is not part of the original field (for example, a passageway), that location may be excluded when determining a representative value (for example, an average value).

[0019] The mesh data MD in Fig. 3 is a diagram showing an example of meshed data. A predetermined area A representing leaf color data is divided into multiple rectangular areas R(i,j), and a leaf color is determined for each area R(i,j).

[0020] Here, as shown in the mesh data MD of FIG. 3, the region R(i, j) is set excluding the outer periphery of the predetermined region A. In other words, the region R(i, j) is set within the region Am that is inside the predetermined region A. Note that the boundary of the region Am may coincide with part of the boundary of the predetermined region A.

[0021] (3) Frequency distribution processing S13 The control unit 13 executes a frequency distribution process S13 to generate frequency distribution data DD representing the frequency distribution of predetermined feature amounts based on the correspondence data (representing each of the partitioned regions R(i, j) in correspondence with the feature amounts).

[0022] At this time, in the frequency distribution process S13, the control unit 13 may generate frequency distribution data by excluding the outer periphery of the predetermined region A. The control unit 13 can generate frequency distribution data by excluding the outer periphery of the predetermined region A by generating frequency distribution data based on the region R(i, j) within the above-mentioned region Am.

[0023] FIG. 3 is a diagram showing an example of frequency distribution data DD. The frequency distribution data DD is expressed based on data averaged for each region R(i,j). The horizontal axis of this frequency distribution data DD represents the magnitude of the feature (e.g., leaf color), and the vertical axis represents the frequency of occurrence of the magnitude of the feature. Here, the data (features) are distributed in a mountain shape centered around the average value AV of the feature.

[0024] (4) Selection process S14 (determination of soil survey points) The control unit 13 executes a selection process S14 of selecting a predetermined number (number of investigation points) of sectional areas R(i,j) as soil investigation points P from the plurality of sectional areas R(i,j) based on the frequency distribution data.

[0025] In the selection process S14, the control unit 13 may determine the predetermined number based on at least one of the area of ​​the predetermined region A, the magnitude of the standard deviation of the frequency distribution data, and the purpose of the soil survey. For example, the control unit 13 determines the predetermined number as in the following (1) to (3).

[0026] (1) If the area of ​​the predetermined area A is within the reference area range, the predetermined number is set to a reference number (for example, 5). If the area of ​​the predetermined area A is smaller than the reference area range, the predetermined number is set to a smaller number than the reference number, and if the area of ​​the predetermined area A is larger than the reference area range, the predetermined number is set to a larger number than the reference number.

[0027] (2) If the standard deviation of the frequency distribution data is within the standard deviation range, the predetermined number is set as the standard number (for example, 5). If the standard deviation of the frequency distribution data is smaller than the standard deviation range, the predetermined number is set smaller than the standard number, and if the standard deviation of the frequency distribution data is larger than the standard deviation range, the predetermined number is set larger than the standard number.

[0028] (3) If the purpose of the soil survey is, for example, soil contamination or pest damage (for example, pathogenic bacteria or nematodes (e.g., potato cyst nematodes)), the predetermined number may be set larger than the standard number, and the number of survey points per unit area may be specified. This number of survey points per unit area can be determined depending on the type of soil contamination or pest damage.

[0029] The storage unit 12 may store a table showing the correspondence between the area of ​​the predetermined region A as described above (1) to (3), the magnitude of the standard deviation of the frequency distribution data, the purpose of the soil survey, and the predetermined number. The control unit 13 can use this table to determine the predetermined number.

[0030] In the selection process S14, the control unit 13 may select, for example, one or more segmented regions from each of a first frequency range that includes the maximum frequency of the frequency distribution data and a plurality of second frequency ranges that do not include the maximum frequency.

[0031] 3, the frequency range W0 of the frequency distribution data DD corresponds to a first frequency range that includes the maximum frequency, and the frequency ranges W1 and W2 correspond to multiple second frequency ranges that do not include the maximum frequency. Here, from the frequency range W0, a survey point P1 corresponding to the average value AV, a survey point P2 that is smaller than the average value AV, and a survey point P3 that is larger than the average value AV are selected, and from the frequency ranges W1 and W2, survey points P4 and P5 that are midway between the frequency ranges W1 and W2 are selected.

[0032] In this way, the distribution data DD is divided into a frequency range W0 of the maximum frequency and two frequency ranges W1 and W2 whose frequencies are smaller than this maximum frequency range W0. This division can be defined, for example, based on σ (standard deviation). For example, the frequency range W0 can be within ±2σ (±2 times the standard deviation), and the frequency ranges W1 and W2 can be outside ±2σ.

[0033] In this example, an upper limit of the frequency range W2 and a lower limit of the frequency range W1 are defined. In this way, the upper and lower limits of the frequency for selecting the sectional area R(i,j) as the soil investigation point P may be restricted. These upper and lower limits may be defined, for example, based on σ (standard deviation). For example, ±3σ (±3 times the standard deviation) may be set as the upper and lower limits of the frequency range for selecting the sectional area R(i,j).

[0034] The selection of the survey points P from the frequency ranges W0, W1, and W2 may be random, or may be specified based on σ (standard deviation). For example, survey point P1 is selected from the frequency range W0 (within ±2σ) where σ0 (i.e., the feature amount is the average AV), and survey points P2 and P3 are selected where σ±1 (±1 times the standard deviation), and survey points P4 and P5 are selected from the frequency range W2 and W3 (outside ±2σ) where σ±2.5 (±2.5 times the standard deviation).

[0035] At this time, the control unit 13 may select multiple segmented areas R(i, j) that are spaced apart by a predetermined distance or more in the selection process S14. For example, if all or some of the segmented areas R(i, j) selected as the soil investigation point P are not spaced apart by a predetermined distance or more from each other (for example, they are close to each other within a predetermined distance), the control unit 13 can reselect one or the other of the adjacent segmented areas R(i, j) so that multiple segmented areas R(i, j) that are spaced apart by a predetermined distance or more from each other are selected.

[0036] The survey point P selected in the above manner can be specified by latitude and longitude, for example, as follows: P1(140.10829,36.00907) P2(140.10809,36.00890) P3(140.10845,36.00869)

[0037] As described above, based on the frequency distribution data, it is possible to take into account the variability of the features and select a relatively small number of survey points P that have different features that affect plant growth and that are representative of the specified area A. As a result, it is possible to efficiently survey the entire specified area A.

[0038] (5) Route determination process S15 The control unit 13 may execute a route determination process S15 to determine the shortest route to visit the survey points P. The control unit 13 determines the shortest route by, for example, changing the order in which the survey points P1 to P5 are visited and calculating the length of the route at that time. At this time, the survey point Pin outside the predetermined area A may be set as the start point and end point of the route.

[0039] 4 is a diagram showing an example of the shortest route for visiting the survey points. This route R starts from survey point Pin outside the predetermined area A and visits survey points P1 to P5 in the order of P2, P4, P3, P1, and P5. Note that the order of survey points P1 to P5 may be reversed.

[0040] (6) Process determination process S16 The control unit 13 may execute a process determination process S16 for determining the estimated work time within the predetermined area A and the work process including the equipment to be used.

[0041] This work includes collecting soil or investigating the soil at the investigation points P1 to P5. When collecting soil, the soil is usually brought back and analyzed using measuring equipment. When investigating soil, measuring equipment is usually brought with the soil and analyzed on-site.

[0042] The work process may include, for example, a point Pin outside the specified area A, survey points P1 to P5 within area A, a route to travel between points Pin and P1 to P5, the length of the route, and an estimated work time. When collecting soil at survey points P1 to P5, the work process may also include the number and weight (e.g., 1 kg) of samples at each point, and the total weight (e.g., 5 kg) of samples at all points. Note that the estimated work time can be calculated by storing the standard work time, travel speed, etc. required for collecting or surveying soil at one location in a table in memory unit 12.

[0043] In the process determination process S16, the control unit 13 may determine a work process that includes collecting or investigating soil in a plurality of predetermined areas Ai.

[0044] The control unit 13 can determine a work process that includes, for example, collecting or investigating soil in each of a plurality of predetermined areas Ai and traveling to other areas Ai. The control unit 13 may also determine a shortest route that includes collecting or investigating soil in each of a plurality of predetermined areas Ai and traveling to other areas Ai. This shortest route may include the shortest route within area Ai that travels to the investigation points Pij in each area Ai, and the shortest route that travels between areas Ai. Route DD in Figure 4 is a diagram showing an example of the shortest route that travels to the investigation points in a plurality of areas A1 to A5.

[0045] The control unit 13 can create a work plan that includes this work process. The work plan may be related to one area A or may span multiple areas Ai. The estimated work time spanning multiple areas Ai can be calculated by adding the travel time between areas Ai to the work time in each area Ai.

[0046] (7) Display process S17 The control unit 13 displays an image showing the predetermined area in correspondence with at least one of the survey points and the route to travel around the survey points on the screen of the input / output unit 11. The control unit 13 may also display the work plan, such as the route, estimated work time, and equipment to be used, on the screen of the input / output unit 11.

[0047] As described above, the control device according to this embodiment comprises a data acquisition unit that acquires data including predetermined features of land within a predetermined area, the soil of the land, or plants grown within the land, and a control unit. The control unit executes the following operations via the data acquisition unit: an acquisition process that acquires the data; a division process that generates, based on the data, correspondence data that corresponds each of a plurality of divided areas that divide the predetermined area to the features; a frequency distribution process that generates, based on the correspondence data, frequency distribution data that represents the frequency distribution of the predetermined features; and a selection process that selects, from the plurality of divided areas, a predetermined number of divided areas as soil investigation points based on the frequency distribution data.

[0048] By selecting a predetermined number of divided areas as soil investigation points from multiple divided areas based on frequency distribution data that represents the frequency distribution of predetermined features, it becomes easy to efficiently investigate a predetermined area. For example, even if the number of investigation points is limited, it is possible to grasp the overall condition of the area.

[0049] In addition, by determining a work process (work plan) including the shortest route to visit the survey points, estimated time, and equipment to be used, and showing this to workers, efficient work becomes possible. Based on the work plan, soil can be efficiently surveyed before planting. Planting plans can be determined based on the soil survey results.

[0050] [Software implementation example] The functions of the information processing device 10 (hereinafter referred to as "device") can be realized by a program that causes a computer to function as the device, and a program that causes a computer to function as the control unit 13 of the device.

[0051] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program, thereby realizing the functions described in each of the above embodiments.

[0052] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0053] Furthermore, some or all of the functions of the control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of the present invention. In addition, the functions of the control blocks can also be realized by, for example, a quantum computer.

[0054] The control device according to each aspect of the present invention may be realized by a computer. In this case, the control program of the control device that realizes the control device by the computer by making the computer operate as each part (software element) of the control device, and the computer-readable recording medium on which the control program is recorded, also fall within the scope of the present invention.

[0055] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of symbols]

[0056] 10. Information processing equipment 11 Input / output section 12 Storage section 13 Control Unit

Claims

1. a data acquisition unit that acquires data including predetermined feature amounts of land within a predetermined area, soil of the land, or plants grown within the land; a control unit, The control unit an acquisition process of acquiring the data via the data acquisition unit; a segmentation process for generating correspondence data representing each of a plurality of segmented regions that segment the predetermined region and the feature amounts in correspondence with each other based on the data; a frequency distribution process for generating frequency distribution data representing a frequency distribution of the predetermined feature amount based on the correspondence data; a selection process for selecting a predetermined number of sectional areas as soil investigation points from the plurality of sectional areas based on the frequency distribution data; An information processing device that executes the above.

2. The control unit, in the frequency distribution processing, The information processing apparatus according to claim 1 , wherein the frequency distribution data is generated by excluding an outer periphery of the predetermined region.

3. In the selection process, the control unit The information processing apparatus according to claim 1 , wherein the predetermined number is determined based on at least one of an area of ​​the predetermined region, a standard deviation of the frequency distribution data, and a purpose of the soil survey.

4. In the selection process, the control unit The information processing device according to claim 1 , wherein one or more partitioned regions are selected from a first frequency range including a maximum frequency of the frequency distribution data and from a plurality of second frequency ranges excluding the maximum frequency.

5. In the selection process, the control unit The information processing apparatus according to claim 1 , wherein the plurality of segmented areas that are spaced apart from each other by a predetermined distance or more are selected.

6. 6. The information processing device according to claim 5, wherein the predetermined feature amount is any one of a leaf color, surface temperature, appearance, vegetation index, yield, land elevation difference, soil water content, nitrate nitrogen, and electrical conductivity of a plant.

7. The control unit The information processing device according to claim 1 , further comprising: a route determination process for determining a shortest route for visiting the survey points;

8. The control unit The information processing apparatus according to claim 7 , further comprising: a process determination process for determining a work process including an estimated work time and equipment to be used within the predetermined area.

9. The control unit, in the process determination processing, The information processing device according to claim 8 , wherein a work process including soil sampling or surveying in a plurality of predetermined areas is determined.

10. an acquisition process for acquiring data including predetermined feature amounts of land within a predetermined area, soil of the land, or plants grown within the land; a segmentation process for generating correspondence data representing each of a plurality of segmented regions that segment the predetermined region and the feature amounts in correspondence with each other based on the data; a frequency distribution process for generating frequency distribution data representing a frequency distribution of the predetermined feature amount based on the correspondence data; a selection process for selecting a plurality of divided areas as soil investigation points from the plurality of areas based on the frequency distribution data; An information processing method, including:

11. The information processing method according to claim 10 , further comprising a display process of displaying an image that shows the predetermined area in correspondence with at least one of the survey points and a route that travels around the survey points.

12. A program for causing a computer to function as the information processing device according to claim 1, an information processing program for causing the control unit to execute the acquisition process, the classification process, the frequency distribution process, and the selection process;

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