Information processing device, method for selecting harvest range, and computer program

Abstract

To appropriately distribute a labor force of a working entity.SOLUTION: A device according to the present disclosure is an information processing device comprising: a storage device that stores value data representing crop values of crops for each planting location; and a control device that executes harvesting range selection processing on the basis of the value data. The selection processing includes processing of: calculating a harvestable area that can be harvested by a working entity in a predetermined period; and allocating the harvestable area to the planting location where the crop value is at or above a predetermined threshold.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to an information processing apparatus, a harvesting range selection method, and a computer program. [Background Art]

[0002] Patent Literature 1 describes an information proposal system that proposes the harvesting time and harvest amount of crops based on the expected selling price of the crops in the market and the growth status of the crops obtained from image analysis. Patent Literature 2 describes a farming support system that efficiently allocates workers and equipment for working in a plurality of fields at distant positions from pre-registered workers and equipment. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] International Publication No. 2018 / 158821 [Patent Document 2] Japanese Unexamined Patent Publication No. 2013-254356 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] Patent Literature 1 and Patent Literature 2 do not consider a harvesting range selection method for appropriately allocating the labor force of a work entity in accordance with the crop value when harvesting crops. In view of such conventional problems, an object of the present disclosure is to enable appropriate allocation of the labor force of a work entity. [Means for Solving the Problem]

[0005] An information processing device according to one aspect of the present disclosure includes a storage device for storing value data representing the crop value of crops for each planting location, and a control device for performing a harvest range selection process based on the value data, wherein the selection process includes a process for calculating a harvestable area in which a worker can perform harvesting within a predetermined period, and a process for allocating the harvestable area to the planting location in which the crop value is equal to or greater than a predetermined threshold.

[0006] Embodiments of the present disclosure may be implemented by apparatus, systems, methods, integrated circuits, computer programs, or computer-readable non-temporary recording media, or any combination thereof. The recording medium may be either volatile or non-volatile. The apparatus may consist of multiple individual devices. If it consists of multiple individual devices, they may be arranged in a single enclosure or in two or more separate enclosures. [Effects of the Invention]

[0007] According to this disclosure, the labor force of the work entity can be appropriately allocated. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a network diagram showing the overall configuration of the work support system. [Figure 2] Figure 2 is a block diagram showing an example configuration of the management server. [Figure 3] Figure 3 is an explanatory diagram showing an example of the process for selecting the harvest area. [Figure 4] Figure 4 is an explanatory diagram showing an example of the process for generating outcome characteristics. [Figure 5] Figure 5 is a sequence diagram illustrating an example of the use of the selection process in a work plan. [Figure 6] Figure 6 shows an example of the display screen for the selection results on the management terminal. [Figure 7] Figure 7 is a sequence diagram showing example 1 of the use of outcome characteristics in a work plan. [Figure 8] FIG. 8 is a sequence diagram illustrating a second usage example of outcome characteristics in a work plan. [Figure 9] FIG. 9 is an explanatory diagram illustrating an example of a method for predicting future growth data. MODE FOR CARRYING OUT THE INVENTION

[0009] <Outline of Embodiments of the Present Disclosure> An outline of embodiments of the present disclosure will be listed and described below. (1) An information processing apparatus according to the present embodiment, comprising: a storage device that stores value data representing a crop value of an agricultural crop for each planting position; and a control device that executes harvesting range selection processing based on the value data, wherein the selection processing includes: processing for calculating a harvestable area that allows a work subject to perform harvesting within a predetermined period; and processing for allocating the harvestable area to the planting positions where the crop value is equal to or greater than a predetermined threshold.

[0010] According to the information processing apparatus of the present embodiment, the control device allocates the harvestable area to planting positions where the crop value is equal to or greater than the predetermined threshold, so planting positions where the crop value is less than the threshold are excluded from allocation targets, and harvesting work for agricultural crops with low crop value can be avoided. Therefore, the labor of the work subject can be appropriately allocated.

[0011] (2) In the information processing apparatus of the present embodiment, the selection processing may include processing of preferentially allocating the harvestable area to the planting positions with higher crop value. In this case, since the planting positions with the highest crop value are included in the harvesting range, agricultural crops with high crop value can be harvested at an early stage.

[0012] (3) In the information processing apparatus of the present embodiment, the selection processing may include processing of arbitrarily selecting the first planting position, and preferentially allocating, from the second position onward, allocation positions that are closer in distance to the first planting position. In this case, since allocation targets are determined based on a distance criterion from the second one onward, a harvesting range that shortens the travel distance of the working entity can be selected.

[0013] (4) In the information processing apparatus of the present embodiment, the selection process may include a process of calculating the harvestable area based on the harvest time during which the working entity can perform harvesting, the harvesting efficiency of the working entity, and the total number of working entities. According to this configuration, the harvestable area can be accurately calculated according to the labor force that can be input in a predetermined period.

[0014] (5) In the information processing apparatus of the present embodiment, the storage device may store growth data representing the growth degree of the agricultural crop for each planting position, and the control device may include a process of converting the growth data into the value data. In this case, since value data is generated from actual growth data, accurate value data can be generated.

[0015] (6) In the information processing apparatus of the present embodiment, the control device may output the value data including the selected harvesting range as a selection result. In this case, for example, by displaying the output selection result (value data including the harvesting range) on a display, the user can determine at a glance from which part of the farm field the harvesting operation should be performed.

[0016] (7) In the information processing apparatus of the present embodiment, the control device may be capable of executing a process of calculating outcome characteristics representing a relationship between a high-value harvest volume and a harvesting outcome as defined below. High-value harvest volume: the harvest volume when harvesting is performed in order from agricultural crops having higher crop value Harvesting outcome: the cumulative value of crop value when harvesting is performed in order from agricultural crops having higher crop value In this case, in addition to the above-described harvesting range, the above-described outcome characteristics representing characteristics of the harvesting outcome with respect to the high-value harvest volume can be acquired.

[0017] (8) In the information processing device of this embodiment, the control device may calculate the yield amount, which is the amount of crops that can be obtained during the predetermined period, and calculate the possible yield, which is the harvest result corresponding to the yield amount, based on the yield amount and the result characteristics. In this case, by notifying the user of the calculation results, it is possible to inform the user in advance of the maximum yield that can be obtained with the labor force currently available.

[0018] (9) In the information processing device of this embodiment, the control device may acquire the target harvest result which is the harvest result desired by the user, and calculate the target harvest amount which is the high-value harvest amount corresponding to the target harvest result based on the target harvest result and the result characteristics. In this case, by notifying the user of the calculation results, the amount of high-value harvest needed to achieve the desired harvest can be notified to the user in advance.

[0019] (10) The method according to this embodiment is a method for selecting the harvest range that is performed by the information processing device described in (1) to (9) above. Therefore, the selection method of this embodiment has the same effects as the information processing devices described in (1) to (9) above.

[0020] (11) The computer program according to this embodiment is a computer program that causes the computer to function as an information processing device as described in (1) to (9) above. Therefore, the computer program of this embodiment has the same effects as the information processing devices described in (1) to (9) above.

[0021] <Details of the embodiments of this disclosure> The embodiments of this disclosure will be described in detail below with reference to the drawings. At least some of the embodiments described below may be combined in any way.

[0022] [Overall System Configuration] Figure 1 is a network configuration diagram showing the overall configuration of the work support system 200. The work support system 200 shown in Figure 1 (hereinafter also referred to as the "support system") is a system in which a mobile terminal 20, a management terminal 30, and a management server 40 work together to support agricultural work performed by worker 1. Accordingly, the support system 200 includes at least the mobile terminal 20, the management terminal 30, and the management server 40 as communication nodes for information exchange.

[0023] The mobile terminal 20, the management terminal 30, and the management server 40 are connected via a public network 70, including the Internet. However, the mobile terminal 20 is connected to the public network 70 via wireless communication with a wireless base station 80. Mobile terminal 20 is a communication terminal assigned to worker 1. Mobile terminal 20 can be, for example, a smartphone, a tablet computer, or a notebook computer. In the example diagram, only one worker 1 is depicted, but there may be multiple workers.

[0024] The management terminal 30 is a terminal device assigned to the manager (hereinafter referred to as "management user") 2 of farm F, which includes multiple field Au (u=1, 2, ...). In the example shown, one farm F contains nine field Au, but the number of field Au is arbitrary and only needs to be one or more. The management terminal 30 is, for example, a desktop computer. The management terminal 30 may also be a mobile device such as a smartphone, tablet computer, or notebook computer.

[0025] Administrator User 2 is a user of the agricultural support service provided by the management server 40. Administrator User 2 is pre-registered as a member on the management server 40. In this embodiment, field Au is, for example, a vineyard for cultivating grapes 3, which are used as raw materials for wine. In vineyard Au, either the same variety of grapes 3 or different varieties of grapes 3 are cultivated.

[0026] The management server 40 communicates with external devices such as the information provision server 50 and the flight device 60, in addition to the mobile terminals 20 and the management terminal 30. The flight device 60 is connected to the public network 70 via wireless communication with the wireless base station 80. The farm work support service of the management server 40 includes a service that provides users with a work plan for farm work at vineyard Au. The management server 40 creates a work plan based on predetermined input information received from the management terminal 30.

[0027] The "Work Plan" is a set of data that defines the schedule (including information on the 5W1H) of work that worker 1 will perform in the near future at vineyard Au. Farm work at vineyard Au includes, for example, pruning, bud removal, training, gibberellin treatment, thinning, bagging, and harvesting. When the management terminal 30 accesses the agricultural work support service of the management server 40, it can send a creation request to the management server 40 based on the input operations of the management user 2. The creation request includes predetermined information necessary for the work plan creation process (for example, the number of workers and the work time).

[0028] The management server 40 creates a work plan for vineyard Au in response to a creation request from the management terminal 30, and sends the created work plan to the management terminal 30. Furthermore, the management server 40 transmits the work details of worker 1, based on the created work plan, to each worker 1's mobile terminal 20. However, the management terminal 30 may also notify each mobile terminal 20 of the work details.

[0029] The information provided by the information server 50 includes growth data for vineyard Au. The management server 40 can receive the growth data from the information server 50. The growth data represents the "growth level" of the crop (e.g., grapes 3) for each planting location. As a measure of plant growth, vegetation indices such as NDVI (Normalized Difference Vegetation Index) can be used. NDVI is an index that expresses the state of vegetation using a relatively simple calculation formula based on the light reflection characteristics of plants.

[0030] The flight device 60 is, for example, a robotic flying object such as a quadcopter or a multicopter. The flight device 60 can fly over any area via remote control and is equipped with a digital camera whose shooting direction can be switched. The flying device 60 takes aerial photographs of the vineyard Au with a digital camera and transmits the acquired image data to the management server 40. The management server 40 can also use the received image data to generate all or part of the growth data for the vineyard Au itself.

[0031] [Example configuration of the management server] Figure 2 is a block diagram showing an example configuration of the management server 40. As shown in Figure 2, the management server 40 is a type of information processing device that includes a control device 41, a storage device 42, a communication device 43, and multiple types of databases (DBs) 44 to 46. The multiple types of databases 44-46 are electronic data constructed in the storage device 42 in a predetermined data arrangement. Note that some or all of the databases 44-46 may be constructed in an external storage device (not shown) connected to the management server 40.

[0032] The control device 41 is an arithmetic processing unit that includes a CPU (Central Processing Unit) and RAM (Random Access Memory). The control device 41 may also include an integrated circuit such as an FPGA (Field-Programmable Gate Array). The control device 41 reads the computer program 47 stored in the storage device 42 into the main memory (RAM) and performs information processing according to the read program 47. Information processing includes creating work plans and generating growth data.

[0033] The storage device 42 is an auxiliary storage device that includes non-volatile memory such as an HDD (Hard Disk Drive) and an SSD (Solid State Drive). The storage device 42 may include flash ROM (Read Only Memory), USB (Universal Serial Bus) memory, or an SD card. The communication device 43 is a communication interface that enables communication with external devices via the public network 70.

[0034] The multiple types of databases 44-46 include the growth database 44, the value database 45, and the descending order database 46. The growth database 44 stores growth data Gijk (see Figure 3). The value database 45 stores value data Vijk (see Figure 3). The descending order database 46 stores descending order data Vijm (see Figure 4). Details of these data, Gijk, Vijk, and Vijm, will be described later.

[0035] The computer program 47 includes a program that causes the control device 41 to execute the "harvesting range selection process" (step S10: see Figure 3) and the "output characteristic generation process" (step S20: see Figure 4) as processes associated with the work plan creation process. The harvest range selection process is the process of selecting the harvest range for vineyard Au based on the value data Vijk. The outcome characteristic generation process is the process of generating outcome characteristics F, which represent the characteristics of the outcome (cumulative value) in relation to the yield, based on the value data Vijk.

[0036] [Selection process for harvest area] Figure 3 is an explanatory diagram showing an example of the harvest range selection process executed by the control device 41 of the management server 40. Below, the definitions of the parameters used in the harvest range selection process will be explained, followed by a description of the contents of the selection process.

[0037] (Xi, Yj): Planting location The planting location (Xi, Yj) is, for example, the location of the trunk of grapevine 3, and is defined in an absolute coordinate system such as latitude and longitude, or in a relative coordinate system based on a predetermined location. The planting location (Xi, Yj) may be a point that represents the location of multiple tree trunks (for example, the centroid). "Xi" is the position in the X direction (i is the identification number of the coordinate value in the X direction), and "Yj" is the position in the Y direction (j is the identification number of the coordinate value in the Y direction).

[0038] Gk: Growth rate The growth level Gk is an index representing the growth stage of grape 3. Growth level is a vegetation index such as NDVI. "k" is an identification number for the growth level and the following crop value.

[0039] Vk: Crop Value The crop value Vk is an indicator representing the current value of grapes 3. This indicator could include, for example, the selling price per unit weight of grapes 3, and the component values ​​of grapes 3. The component values ​​could be at least one of the following: sugar content, acidity, and pH value.

[0040] Gijk: Growth Data The growth data Gijk represents the growth degree Gk of grapes 3 for each planting location (Xi, Yj). The growth data Gijk is defined by the following three-dimensional vector. Gijk=(Xi,Yj,Gk) The data format for growth data Gijk may be either a digital map format or a table format. Growth data in digital map format is called a "growth map." When displaying a growth map on a display, it may be displayed as a bitmap image, for example, as shown in Figure 3, where the size of the growth degree Gk is represented by color or shading.

[0041] Vijk: Value Data The value data Vijk represents the crop value Vk for each planting location (Xi, Yj). The value data Vijk is defined by the following three-dimensional vector. Vijk=(Xi,Yj,Vk) The data format for value data (Vijk) may be either a digital map format or a table format. Value data in digital map format is referred to as a "value map." When displaying a value map on a screen, it may be displayed as a bitmap image, for example, as shown in Figure 3, where the size of the crop value (Vk) is represented by color or shade.

[0042] ΔS: Unit area (m 2 ) The unit area ΔS is a predetermined shape area with a unit area that includes the planting location (Xi, Yj). The shape of the area is preferably a rectangle, but other shapes such as an ellipse or hexagon may also be used. The unit area of ​​the area can be predetermined according to the planting interval of the grapevines 3.

[0043] ΔH: Yield per unit area (kg / m²) 2 ) The unit yield ΔH is the expected yield of grapes (kg / m²) in a unit area ΔS. 2 The unit yield ΔH can be predetermined according to a statistical value (e.g., mean or median) of the number of grapes 3 that grow on the vines in a unit area ΔS. Furthermore, the unit yield ΔH may be set to a different value for each grape variety 3.

[0044] Tn: Harvest time (h) The harvest time Tn is the amount of time during a given period (e.g., 1 day to 1 week) during which worker 1 can perform harvesting. "n" is the identification number of worker 1. The harvest time Tn may be set to a different value for each worker 1, depending on, for example, the upcoming work time slots that management user 2 has coordinated with each worker 1.

[0045] Rn: Harvesting efficiency (kg / h) Harvesting efficiency Rn is the amount of harvest that one worker can harvest per unit of time. The harvesting efficiency Rn may be set to a different value for each worker 1 according to each worker's skill level, for example, by management user 2. The harvesting efficiency Rn may also be set to a different value for each variety.

[0046] L: Harvest yield (kg) The yield L is the amount of grapes 3 that can be harvested in a given period (e.g., 1 day to 1 week). The yield L is defined by the following formula: L = Σ(Tn × Rn) (n = 1 to N) ……(1) However, "N" represents the total number of workers 1 that can be mobilized during the specified period.

[0047] S: Harvestable area (m²) 2 ) The harvestable area S is the area over which worker 1 can perform harvesting within a predetermined period (e.g., 1 day to 1 week). The harvestable area S is defined by the following formula. S = L / ΔH ……(2)

[0048] M: Normalized area (pieces) The normalized area M is the converted value obtained when the harvestable area S is normalized by the number of unit areas ΔS. The normalized area M is defined by the following formula. M = S / ΔS = (L / ΔH) / ΔS ……(3)

[0049] As shown in Figure 3, the harvest range selection process (step S10 in Figure 2) includes the following steps. Step S11: Data conversion Step S12: Calculation of normalized area Step S13: Allocation of normalized area

[0050] (Data conversion: Step S11) Data conversion is the process of converting growth data (Gijk) into value data (Vijk). Specifically, the data conversion is the process of converting the growth degree Gk of the growth data Gijk into the crop value Vk using a predetermined conversion formula (Vk=f(Gk)). The predetermined conversion formula is, for example, an approximation formula that represents the correlation between the growth degree Gk and the crop value Vk. The approximation formula is predefined according to the type of crop value Vk, for example, based on past statistical data.

[0051] (Calculation of normalized area: Step S12) The calculation of the normalized area M is a process that uses equations (1) to (3) above to calculate the normalized area M. Specifically, the calculation of the normalized area M includes the following steps. Step 1: Calculate the yield L using formula (1). Of the input information in equation (1), the harvest time Tn and the total number of workers N are notified from the management terminal 30. The harvest efficiency Rn of worker 1 is a setting value that is pre-registered in the storage device 42 of the management server 40.

[0052] Step 2: Calculate the harvestable area S using equation (2). The unit yield ΔH, which is input information in equation (2), is a setting value that is pre-registered in the storage device 42 of the management server 40. Step 3: Calculate the normalized area M using equation (3). The unit area ΔS, which is the input information in equation (3), is a setting value that is pre-registered in the storage device 42 of the management server 40.

[0053] (Normalized area allocation: Step S13) The allocation of normalized area M is the process of allocating the normalized area M, which corresponds to the harvestable area S calculated in step S12, to the planting locations (Xi, Yj) of the value data Vijk based on a predetermined allocation logic. For example, the following logic can be adopted as the predetermined allocation logic.

[0054] Logic 1: The unit area ΔS of a planting location (Xi, Yj) where the work value Vk is equal to or greater than a predetermined threshold THv is to be allocated. The threshold THv is pre-registered in the storage device 42 of the management server 40 for each type of crop value Vk by, for example, management user 2. If logic 1 is adopted, unit areas Δ that do not meet the crop value Vk desired by management user 2 will be excluded from allocation. Therefore, harvesting of grapes 3, which have a low crop value Vk, will be avoided. Consequently, the labor of worker 1 can be appropriately allocated.

[0055] Logic 2: Among the unit area ΔS of planting locations (Xi, Yj) where the work value Vk is equal to or greater than the threshold THv, unit area Δ of planting locations (Xi, Yj) with a high crop value Vk will be given priority for allocation. By adopting Logic 2, the planting location (Xi, Yj) with the highest crop value Vk is included in the harvest range, allowing for an early harvest of grapes (V3), which have a high crop value Vk.

[0056] Logic 3: First, an arbitrary unit area ΔS is selected from among the unit areas ΔS of the planting location (Xi, Yj) where the work value Vk is equal to or greater than the threshold THv. For subsequent units, priority is given to assigning unit areas ΔS that are shorter in distance from the first unit area ΔS. If logic 3 is adopted, the allocation target will be determined based on distance from the second worker onward, so it will be possible to select a harvesting area where the travel distance for worker 1 is short.

[0057] In the example in Figure 3, the value of the normalized area M is "10," and the value data (value map) Vijk is shown as an example where the crop value Vk increases the closer you are to the origin of the vineyard Au. In this case, for example, applying logic 1 described above, the harvest area, which consists of 10 unit areas ΔS, will be assigned in the shape of a right triangle with the origin of field Au as the right angle point.

[0058] [Process for generating outcome characteristics] Figure 4 is an explanatory diagram showing an example of the output characteristic generation process executed by the control device 41 of the management server 40. The definitions of the parameters used in the output characteristic generation process will be explained below, followed by a description of the process itself. However, explanations of the parameters already mentioned will be omitted.

[0059] Vm: Descending Value The descending value Vm is data obtained by sorting the crop value Vk in descending order. "m" is the identification number of the descending value.

[0060] Vijm: Descending data The descending data Vijm represents the descending value Vm at the planting location (Xi, Yj). The descending data Vijm is defined by the following three-dimensional vector. Vijm=(Xi,Yj,Vm) The descending order data format for Vijm may be either a digital map format or a table format. The descending order data in digital map format is referred to as a "descending order map".

[0061] H: High-value harvest yield (kg) The high-value yield H is the yield when harvesting is carried out in order from the highest-value grapes (3), that is, the yield when harvesting is carried out starting from the unit area ΔS with the highest descending value Vm. The high-value yield H is defined by the following equation. H=Σ(ΔH×m)(m=1,2……) ……(4)

[0062] VA: Harvest results The harvest result VA is the cumulative value when harvesting is carried out in order from the highest-value grapes (3), that is, the cumulative value of the descending value Vm when harvesting is carried out starting from the unit area ΔS with the highest descending value Vm. The harvest result VA is defined by the following formula. VA=Σ(Vm)(m=1,2……) ……(5)

[0063] F: Outcome characteristics The outcome characteristic F is a parameter that represents the characteristics of the outcome (cumulative value) in relation to the yield of grapes 3. In this embodiment, the outcome characteristic F is defined as a function that represents the relationship between the high-value yield H and the harvest outcome VA. That is, the outcome characteristic F is a function defined by the following equation. VA = F(H) ……(6) When displaying the graph of the outcome characteristic F on a display, it can be displayed as a bitmap image, for example, as shown in Figure 4, which represents the magnitude of the descending value Vm used to calculate the outcome characteristic F using colors or shades of gray.

[0064] As shown in Figure 4, the process for generating outcome characteristics (step S20 in Figure 2) includes the following steps. Step S21: Data conversion Step S22: Calculation of Outcome Characteristics

[0065] (Data conversion: Step S21) The data transformation is the process of converting value data Vijk into descending order data Vijm. Specifically, the data transformation includes the following steps: Step 1: Sort the value data Vijk in descending order of crop value Vk. Step 2: Replace identification number k with identification number m to generate descending value Vm. Step 3: The data containing the descending value Vm for each planting location (Xi, Yj) is set as descending data Vijm.

[0066] (Calculation of outcome characteristics: Step S22) The calculation of the outcome characteristic F is a process that uses the descending value Vm obtained in step S21 to calculate the outcome characteristic F of vineyard Au. Specifically, the calculation of the outcome characteristic F includes the following steps.

[0067] Step 1: Set the identification number m of the descending value Vm to its initial value (=1). Step 2: Calculate the high-value yield H using equation (4). Step 3: Calculate the harvest yield VA using equation (5). Step 4: Plot the calculated values ​​of H and VA on a Cartesian coordinate system with H on the horizontal axis and VA on the vertical axis.

[0068] Step 5: Increment identification number m and repeat steps 2 through 4. Step 6: When identification number m reaches its final value, the plotting is terminated. Step 7: The lines connecting adjacent points in the plotted point cloud with straight or curved lines are defined as the outcome characteristic F in equation (6). If either the calculated value of H or the calculated value of VA contains an outlier, the outlier may be discarded and interpolated.

[0069] The harvest characteristic F in Figure 4 can be used in the following calculation processes. Calculation process 1: Calculation of "Possible harvest yield VAL" Calculation process 1 is the process of calculating the harvest yield VA for the yieldable amount L in the result characteristic F. Hereinafter, the harvest yield VA for the yieldable amount L will be referred to as "possible harvest yield VAL". Specifically, the possible harvest yield VAL is calculated by the following formula (7). VAL = F(L) ……(7)

[0070] Calculation process 2: Calculation of "Target yield HD" Calculation process 2 is the process of calculating the high-value harvest quantity H required to obtain the harvest result VA desired by management user 2 in the result characteristic F. Hereinafter, the desired harvest result VA will be referred to as "target result VAD," and the high-value harvest quantity H required for it will be referred to as "target harvest quantity HD." Specifically, the target harvest quantity HD is calculated by the following formula (8). Note that "F -1 This is the inverse function of the outcome characteristic F. HD View -1 (VAD) ... (8)

[0071] [Examples of using selection processes in work planning] Figure 5 is a sequence diagram illustrating an example of the use of the selection process in a work plan. As shown in Figure 5, after accessing the support service (step ST11), the management terminal 30 sends a work plan creation request RQ1 to the management server 40 (step ST12). The creation request RQ1 includes the identification number n of worker 1, the total number of workers N, and the harvest time Tn for each worker 1. The identification number n can be determined from identification information such as the name of worker 1.

[0072] Next, the management server 40 performs the harvest range selection process (step ST13). Specifically, the control device 41 of the management server 40 selects the harvest range in the value data Vijk by executing the selection process described above (Figure 3) using the received identification number n, total number of people N, and harvest time Tn as input information. The control device 41 also outputs the selection result SR to the communication device 43. The selection result SR consists, for example, of the value data (value map) Vijk that includes the selected harvest range.

[0073] Next, the management server 40 sends a creation response AQ1 containing the selection result SR to the management terminal 30 (step ST14). Furthermore, the management server 40 transmits the work details WN (e.g., harvest location and time) for each worker that constitutes the selected SR to each worker's mobile terminal 20 (step ST15). However, the notification of the work details WN to each mobile terminal 20 may be performed by the management terminal 30.

[0074] Next, the management terminal 30 outputs the selection result SR received from the management server 40 (step ST16). This output is, for example, displayed on the management terminal 30's display. Figure 6 shows an example of the display screen for the selection result SR on the management terminal 30.

[0075] As shown in Figure 6, the display screen for the selection results SR includes fields for "Date," "Personnel," and "Harvesting Area." The date and personnel fields will display the input information set by administrator user 2. In the example diagram, the personnel on September 16th are workers A, B, and C (all names), the personnel on September 17th are workers B, C, and D (all names), and the personnel on September 18th are workers A, B, C, and D (all names). Furthermore, the working hours for workers A, B, C, and D are as shown in the diagram.

[0076] The harvest range column displays the value map Vijl, which includes the harvest range selected through the selection process (Figure 3). The horizontal axis represents Xi and the vertical axis represents Yj. Figure 6 shows an example of the selection results SR for harvesting work when the specified period is three days, from September 16th to September 18th. Specifically, the harvesting area to be carried out on each day is shown as follows (the hatched area in the figure).

[0077] Harvest range for September 16th Planting location (X1, Y1) → Worker A Planting location (X2, Y1) → Worker B Planting location (X1, Y2) → Worker C

[0078] Harvest range for September 17th Planting location (X1, Y3) → Worker B Planting location (X2, Y2) → Worker C Planting location (X3, Y1) → Worker D

[0079] Harvest range for September 18th Planting location (X1, Y4) → Worker A Planting location (X2, Y3) → Worker B Planting location (X3, Y2) → Worker C Planting location (X4, Y1) → Worker D

[0080] As shown in Figure 6, by overlaying the harvest area selection result (harvest area) SR onto the value map Vijk of field Au, the managing user 2 can determine at a glance where in the vineyard Au the harvesting work should be carried out, resulting in a display format with excellent visibility.

[0081] [Example 1 of using outcome characteristics in work planning] Figure 7 is a sequence diagram showing example 1 of the use of outcome characteristics in a work plan. As shown in Figure 7, after accessing the support service (step ST21), the management terminal 30 sends a request RQ2 for calculating harvest results to the management server 40 (step ST22). The calculation request RQ2 includes the identification number n of worker 1, the total number of workers N, and the harvest time Tn for each worker 1. The identification number n can be determined from identification information such as the name of worker 1.

[0082] Next, the management server 40 performs the calculation process for the possible harvest yield VAL (step ST23). Specifically, the control device 41 of the management server 40 calculates the possible harvest amount L using the received identification number n, total number of people N, and harvest time Tn as input information. Furthermore, the control device 41 calculates the possible harvest yield VAL by applying the calculated harvest yield L to equation (7) relating to the result characteristics F.

[0083] Next, the management server 40 sends a calculated response AQ2, which includes the possible harvest yield VAL, to the management terminal 30 (step ST24). Next, the management terminal 30 outputs the possible harvest result VAL received from the management server 40 (step ST25). This output is, for example, displayed on the management terminal 30's display as the numerical value of the possible harvest result VAL itself, or as a graph of the result characteristic F that includes the numerical value of the possible harvest result VAL (see Figure 4).

[0084] In this way, by transmitting the possible harvest result VAL, which is the harvest result VA corresponding to the harvestable amount L in the result characteristic F, to the management terminal 30, the maximum harvest result VA that can be obtained with the labor force currently available can be notified to the management user 2 in advance.

[0085] [Example 2 of using outcome characteristics in work planning] Figure 8 is a sequence diagram showing example 2 of the use of outcome characteristics in a work plan. As shown in Figure 8, after accessing the support service (step ST31), the management terminal 30 sends a harvest yield calculation request RQ3 to the management server 40 (step ST32). The proposal request RQ3 includes the target harvested outcome VAD, which is the harvested outcome VA desired by the management user 2.

[0086] Next, the management server 40 performs the calculation process for the target yield HD (step ST33). Specifically, the control device 41 of the management server 40 calculates the target yield HD by applying the received target yield VAD to equation (8) relating to the inverse function of the result characteristic F.

[0087] Next, the management server 40 sends a calculated response AQ3, which includes the target yield HD, to the management terminal 30 (step ST34). Next, the management terminal 30 outputs the target yield HD received from the management server 40 (step ST35). This output is used to display, for example, the numerical value of the target yield HD itself, or a graph of the performance characteristics F that includes the numerical value of the target yield HD (see Figure 4), on the display of the management terminal 30.

[0088] In this way, by transmitting the target harvest amount HD, which is the high-value harvest amount H corresponding to the target harvest result VAD in the outcome characteristic F, to the management terminal 30, the management user 2 can be notified in advance of the high-value harvest amount H necessary to achieve the desired harvest result VA.

[0089] [Variation 1: Method for predicting growth data] In the above embodiment, growth data (growth map) Vijk, which includes the growth stage Gk in the relatively near future (for example, one day later), may be predicted using Model 48 (see Figure 9), which is a machine learning-capable learner. Model 48 is a type of program 47 stored in memory device 42, and may employ, for example, a neural network that includes at least one hidden layer between the input layer and the output layer.

[0090] Figure 9 is an explanatory diagram illustrating an example of a method for predicting future growth data (Vijk). In Figure 9, Model 48 consists of a learner that uses yesterday's growth rate Gk at planting location (Xi, Yj) as input data (training data) and today's growth rate Gk at planting location (Xi, Yj) as output data. Training of Model 48 is performed by adjusting the weights between nodes within Model 48 so that the difference between the input data and the output data is minimized (learning phase).

[0091] Once the accuracy of Model 48 is confirmed through a predetermined training period, Model 48 is used to predict the growth data Vijk for the following day (operational phase). Specifically, today's growth data Vijk is input into Model 48, and tomorrow's growth data Vijk is output to Model 48. Similarly, tomorrow's growth data Vijk is input into Model 48, and the growth data Vijk for two days later is output to Model 48. The same process is followed for predictions three days and beyond.

[0092] [Modification 2: Labor-saving in growth data collection] In the above embodiment, growth data (growth map) Vijk may be sampled sparsely, and the sampled data may be subjected to predetermined processing such as TV (Total Variation) regularization, and this data may be used as growth data Vijk for selection processing and the like. This method reduces the number of source data samples required, which has the advantage of reducing the storage capacity in the storage device 42 compared to storing growth data Vijk that includes the growth degree Vk for all planting locations (Xi, Yj).

[0093] [Other variations] The embodiments disclosed herein are illustrative in all respects and are not restrictive. The scope of the present invention is not limited to the embodiments described above, and includes all modifications within the scope equivalent to the configurations described in the claims.

[0094] In the above-described embodiment, the "working entity" that harvests the grapes 3 is not limited to a human worker 1, but may also be a harvesting robot that automatically travels through the vineyard Au. In this case, the harvesting of the grapes 3 by the harvesting robot may be done by remote control or by automatic harvesting. In the above-described embodiment, the crop 3 can be any crop whose yield can be predicted with approximately accuracy for a given planting location (Xi, Yj), and is not limited to grapes 3. [Explanation of symbols]

[0095] 1. Workers (Main Workers) 2. Administrator User 3. Grapes (agricultural crop) 20 Mobile devices 30 Management terminals 40. Management Server (Information Processing Unit) 41 Control device 42 Storage device 43 Communication equipment 44 Growth Database 45 Value Database 46 Descending Database 47 Computer Programs 48 Models 50 Information Provision Server 60 Flight device 70 Public Networks 80 Wireless base stations 200 Work Support Systems F farm Au vineyard (vineyard) (Xi, Yi) Planting location Vijk growth data Gijk Value Data Gijm descending data

Claims

1. A memory device that stores value data representing the crop value of agricultural products for each planting location, The system includes a control device that performs a harvest range selection process based on the aforementioned value data, The aforementioned selection process is, A process for calculating the harvestable area that can be harvested by the main workforce within a predetermined period, A process of allocating the harvestable area to the planting location where the crop value is above a predetermined threshold, A process of preferentially allocating the harvestable area to the planting location where the crop value is high, Information processing device including

2. The aforementioned selection process is, The information processing apparatus according to claim 1, comprising the process of arbitrarily selecting the first planting location and preferentially assigning subsequent planting locations to those closest in distance from the first planting location.

3. The aforementioned selection process is, The information processing apparatus according to claim 1 or claim 2, comprising a process for calculating the harvestable area based on the harvesting time during which the work entity can perform harvesting, the harvesting efficiency of the work entity, and the total number of the work entity.

4. The aforementioned storage device is The system stores growth data representing the growth stage of the crops at each planting location. The control device is The information processing apparatus according to claim 1 or claim 2, comprising a process for converting the growth data into value data.

5. The control device is The information processing apparatus according to claim 1 or claim 2, which outputs the value data including the selected harvest range as a selection result.

6. The control device is The information processing apparatus according to claim 1 or claim 2, which is capable of performing a calculation process for performance characteristics that represent the relationship between high-value yield and harvest results as defined below. High-value yield: The yield obtained when harvesting crops in order of their value, starting with the most valuable crops. Harvest yield: The cumulative value of crops when harvesting is carried out in order of crop value, starting with the highest-value crops.

7. A memory device that stores value data representing the crop value of agricultural products for each planting location, The system includes a control device that performs a harvest range selection process based on the aforementioned value data, The aforementioned selection process is, A process for calculating the harvestable area that can be harvested by the main workforce within a predetermined period, The process includes allocating the harvestable area to the planting location where the crop value is above a predetermined threshold, The control device is an information processing device capable of performing a calculation process for performance characteristics that represent the relationship between high-value yield and harvest results, as defined below. High-value yield: The yield obtained when harvesting crops in order of their value, starting with the most valuable crops. Harvest yield: The cumulative value of crops when harvesting is carried out in order of crop value, starting with the highest-value crops.

8. The control device is The yield, which is the amount of crop that can be obtained during the predetermined period, is calculated. An information processing device according to claim 6 or 7, which calculates the possible harvest result, which is the harvest result corresponding to the harvest amount, based on the harvestable amount and the result characteristics.

9. The control device is The system obtains the target harvest result, which is the harvest result desired by the user. An information processing apparatus according to claim 6 or 7, which calculates a target harvest amount, which is the high-value harvest amount corresponding to the target harvest amount, based on the target harvest amount and the characteristics of the harvest amount.

10. A method for selecting the harvest range to be performed by an information processing device, A step of storing value data representing the crop value of agricultural products for each planting location, The step includes performing a harvest range selection process based on the value data, The aforementioned selection process is, A process for calculating the harvestable area that can be harvested by the main workforce within a predetermined period, A process of allocating the harvestable area to the planting location where the crop value is above a predetermined threshold, A process of preferentially allocating the harvestable area to the planting location where the crop value is high, A method for selecting the harvest range, including [specific details omitted].

11. A computer program that makes a computer function as an information processing device, The aforementioned computer, A storage device that stores value data representing the crop value of agricultural products for each planting location, and It functions as a control device that performs a harvest range selection process based on the aforementioned value data, The aforementioned selection process is, A process for calculating the harvestable area that can be harvested by the main workforce within a predetermined period, A process of allocating the harvestable area to the planting location where the crop value is above a predetermined threshold, A process of preferentially allocating the harvestable area to the planting location where the crop value is high, A computer program that includes this.

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