Information processing device, harvesting range selection method, and computer program

Abstract

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 by planting location; and a control device that executes a harvesting range selection process on the basis of the value data. The selection process includes: a process of calculating a harvestable area that can be harvested by a working entity in a predetermined period; and a process of allocating the harvestable area to the planting location where the crop value is at or above a predetermined threshold.

Description

Information processing device, harvest range selection method, and computer program

[0001] This disclosure relates to an information processing device, a method for selecting a harvest range, and a computer program. This application claims priority to Japanese Application No. 2023-106294 filed on June 28, 2023, and incorporates by reference all of the contents of that Japanese application.

[0002] Patent Literature 1 describes an information suggestion system that suggests the harvest time and yield of agricultural crops based on the expected selling price of the crops in the market and the growth state of the crops obtained from image analysis.Patent Literature 2 describes a farming support system that efficiently allocates workers and equipment to work in multiple distant fields from pre-registered workers and equipment.

[0003] International Publication No. 2018 / 158821 Japanese Patent Application Laid-Open No. 2013-254356

[0004] An information processing device according to one aspect of the present disclosure includes a storage device that stores value data representing the crop value of agricultural crops for each planting location, and a control device that executes a harvest range selection process based on the value data, the selection process including a process of calculating a harvestable area in which a worker can be allowed to harvest within a specified period, and a process of allocating the harvestable area to the planting location where the crop value is equal to or greater than a specified threshold.

[0005] The embodiments of the present disclosure may be realized by an apparatus, a system, a method, an integrated circuit, a computer program, or a non-transitory computer-readable recording medium, or any combination thereof. The recording medium may be either volatile or non-volatile. The apparatus may be composed of multiple individual devices. When composed of multiple individual devices, they may be arranged in a single housing or may be arranged separately in two or more separate housings.

[0006] FIG. 1 is a network configuration diagram showing the overall configuration of a work support system. FIG. 2 is a block diagram showing an example of the configuration of a management server. FIG. 3 is an explanatory diagram showing an example of a harvest range selection process. FIG. 4 is an explanatory diagram showing an example of a result characteristic generation process. FIG. 5 is a sequence diagram showing an example of a use of the selection process in a work plan. FIG. 6 is a diagram showing an example of a display screen of the selection results on the management terminal. FIG. 7 is a sequence diagram showing Example 1 of the use of result characteristics in a work plan. FIG. 8 is a sequence diagram showing Example 2 of the use of result characteristics in a work plan. FIG. 9 is an explanatory diagram showing an example of a method for predicting future growth data.

[0007] <Problem to be Solved by the Present Disclosure> Patent Documents 1 and 2 do not anticipate a method for selecting a harvest range for appropriately allocating the labor of workers according to the value of the crops when they are harvested. In view of such conventional problems, the present disclosure aims to enable the appropriate allocation of labor of workers.

[0008] Effect of the Present Disclosure According to the present disclosure, it is possible to appropriately allocate the labor of the work subjects.

[0009] <Outline of Embodiments of the Present Disclosure> The following is a description of outlines of embodiments of the present disclosure: (1) A device according to this embodiment is an information processing device including a storage device that stores value data representing the crop value of agricultural crops for each planting location, and a control device that executes a process of selecting a harvest area based on the value data, wherein the selection process includes a process of calculating a harvestable area in which a worker can perform harvesting within a predetermined period, and a process of allocating the harvestable area to the planting location where the crop value is equal to or greater than a predetermined threshold.

[0010] According to the information processing device of this embodiment, the control device allocates harvestable areas to planting locations where the crop value is equal to or greater than a predetermined threshold, and excludes planting locations where the crop value is less than the threshold from allocation targets, thereby avoiding the harvesting of crops with low crop value. This allows for appropriate allocation of labor among operators.

[0011] (2) In the information processing device of this embodiment, the selection process may include a process of preferentially allocating the harvestable area to the planting locations with high crop value. In this case, the planting locations with the highest crop value are included in the harvest range, allowing crops with high crop value to be harvested early.

[0012] (3) In the information processing device of this embodiment, the selection process may include a process of arbitrarily selecting the first planting location and preferentially allocating the second and subsequent planting locations to the allocation locations closest to the first planting location. In this case, the allocation targets from the second and subsequent planting locations are determined based on distance, so that a harvesting range requiring a short travel distance for the worker can be selected.

[0013] (4) In the information processing device of this embodiment, the selection process may include a process of calculating the harvestable area based on the harvesting time that the worker can perform the harvest, the harvesting efficiency of the worker, and the total number of the worker. In this way, the harvestable area can be accurately calculated according to the labor force that can be input in a predetermined period of time.

[0014] (5) In the information processing device of this embodiment, the storage device may store growth data representing the growth level of the crops for each of the planting locations, and the control device may include a process for converting the growth data into the value data. In this case, the value data is generated from actual growth data, so that the value data can be generated accurately.

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

[0016] (7) In the information processing device of this embodiment, the control device may be capable of calculating a result characteristic that represents the relationship between high-value harvest yield and harvest result, as defined below: High-value harvest yield: The harvest yield when harvesting is performed in order from the highest crop value Harvest result: The cumulative value of the crop value when harvesting is performed in order from the highest crop value In this case, in addition to the above-mentioned harvest range, the result characteristic that represents the characteristics of the harvest result for the high-value harvest yield can be obtained.

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

[0018] (9) In the information processing device of this embodiment, the control device may acquire a target harvest result, which is the harvest result desired by a user, and calculate a 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 result, the high-value harvest amount necessary to achieve the desired harvest result can be notified to the user in advance.

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

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

[0021] <Details of Embodiments of the Present Disclosure> Hereinafter, details of embodiments of the present disclosure will be described with reference to the drawings. Note that at least some of the embodiments described below may be combined in any manner.

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

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

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

[0025] The management user 2 is a user of the farm work support service provided by the management server 40. The management user 2 is registered as a member in advance with the management server 40. The farm field Au in this embodiment is, for example, a vineyard for cultivating grapes 3, which are used to make wine. In the vineyard Au, grapes 3 of the same variety or grapes 3 of different varieties are cultivated.

[0026] In addition to the mobile terminal 20 and the management terminal 30, the management server 40 also communicates with external devices such as an information providing server 50 and a flying device 60. The flying device 60 is connected to a public network 70 via wireless communication with a wireless base station 80. The agricultural work support services of the management server 40 include a service that provides users with a work plan for agricultural work in the vineyard Au. The management server 40 creates a work plan based on specified input information received from the management terminal 30.

[0027] The "work plan" is a group of data that defines a schedule of near-future work (information including the 5W1H content) to be performed by worker 1 in vineyard Au. Agricultural work in vineyard Au includes, for example, pruning, bud removal, training, gibberellin treatment, berry thinning, bagging, and harvesting. When the management terminal 30 accesses the agricultural work support service of the management server 40, it becomes possible to send a creation request to the management server 40 based on input operations by management user 2. The creation request includes predetermined information required for the work plan creation process (for example, the number of workers, work time periods, etc.).

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

[0029] The information provided by the information providing server 50 includes growth data for the vineyard Au. The management server 40 can receive the growth data from the information providing server 50. The growth data is data that indicates the "growth level" of agricultural crops (e.g., grapes 3) for each planting location. As the growth level, for example, a vegetation index such as the NDVI (Normalized Difference Vegetation Index) can be used. The 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 flying device 60 is, for example, a robotic flying object such as a quadcopter or multicopter. The flying device 60 can fly over any area by remote control and is equipped with a digital camera that can switch the shooting direction. The flying device 60 takes pictures of the vineyard Au from above with the 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 of the vineyard Au itself.

[0031] [Configuration Example of Management Server] Figure 2 is a block diagram showing a configuration example 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 (DB) 44 to 46. The multiple types of databases 44 to 46 are electronic data constructed in a predetermined data array in the storage device 42. Note that some or all of the databases 44 to 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 device including a CPU (Central Processing Unit) and RAM (Random Access Memory). The control device 41 may include an integrated circuit such as an FPGA (Field-Programmable Gate Array). The control device 41 reads a computer program 47 stored in the storage device 42 into the main memory (RAM) and executes information processing in accordance with the read program 47. Information processing includes creating a work plan and generating growth data.

[0033] The storage device 42 is an auxiliary storage device including a nonvolatile memory such as a hard disk drive (HDD) and a solid state drive (SSD). The storage device 42 may also include a flash read-only memory (ROM), a universal serial bus (USB) memory, or an SD card. The communication device 43 is a communication interface capable of communicating with external devices via the public network 70.

[0034] The multiple types of databases 44 to 46 include a growth database 44, a value database 45, and a descending order database 46. The growth database 44 stores growth data Gijk (see FIG. 3). The value database 45 stores value data Vijk (see FIG. 3). The descending order database 46 stores descending order data Vijm (see FIG. 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 a "harvesting range selection process" (step S10: see FIG. 3) and a "product characteristic generation process" (step S20: see FIG. 4) as processes associated with the work plan creation process. The harvesting range selection process is a process of selecting a harvesting range for the vineyard Au based on the value data Vijk. The product characteristic generation process is a process of generating a product characteristic F that represents the characteristics of the product (accumulated value) relative to the harvest volume based on the value data Vijk.

[0036] 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, and then the contents of the selection process will be explained.

[0037] (Xi, Yj): Cultivation position The cultivation position (Xi, Yj) is, for example, the location of the trunk of the 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 position. The cultivation position (Xi, Yj) may also be a point (for example, a center of gravity) that represents the locations of multiple tree trunks. "Xi" is the position in the X direction (i is the identification number for the coordinate value in the X direction), and "Yj" is the position in the Y direction (j is the identification number for the coordinate value in the Y direction).

[0038] Gk: Growth Degree The growth degree Gk is an index that indicates the growth degree of the grapes 3. The growth degree is a vegetation index such as NDVI. "k" is an identification number of the growth degree and the value of the next crop value.

[0039] Vk: Crop Value The crop value Vk is an index that represents the current value of the grapes 3. This index may be, for example, the selling price per unit weight of the grapes 3, or the component values ​​of the grapes 3. The component values ​​may be at least one of the sugar content, acidity, and pH value.

[0040] Gijk: Growth Data The growth data Gijk is data that represents the growth level Gk of grapes 3 for each planting position (Xi, Yj). The growth data Gijk is defined by the following three-dimensional vector: Gijk = (Xi, Yj, Gk) The data format of the 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 the growth map is displayed on a display, it may be displayed as a bitmap image that represents the magnitude of the growth level Gk using color or shading, for example, as shown in Figure 3.

[0041] Vijk: Value Data The value data Vijk is data that represents the crop value Vk for each planting position (Xi, Yj). The value data Vijk is defined by the following three-dimensional vector: Vijk = (Xi, Yj, Vk) The data format of the 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 the value map is displayed on a display, it may be displayed as a bitmap image that represents the magnitude of the crop value Vk using color or shading, for example, as shown in Figure 3.

[0042] ΔS: unit area (m ２ The unit area ΔS is an area of ​​a predetermined shape having a unit area that includes the planting position (Xi, Yj). The shape of the area is preferably rectangular, but may be other shapes such as oval or hexagonal. The unit area of ​​the area may be set in advance depending on the planting interval of the grape vines 3, etc.

[0043] ΔH: Unit yield (kg / m ２ ) The unit yield ΔH is the expected yield of grapes 3 in the unit area ΔS (kg / m ２) The unit yield ΔH may be set in advance based on a statistical value (for example, the average or median) of the number of grapes 3 growing on the trees included in the unit area ΔS. The unit yield ΔH may also be set to a different value for each variety of grapes 3.

[0044] Tn: Harvesting time (h) Harvesting time Tn is the time during a predetermined period (for example, one day to one week) that a worker 1 can harvest. "n" is the identification number of the worker 1. Harvesting time Tn can be set to a different value for each worker 1, depending on, for example, the future work time period that the management user 2 has coordinated with each worker 1.

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

[0046] L: Harvestable quantity (kg) The harvestable quantity L is the amount of grapes 3 that can be harvested in a given period (for example, one day to one week). The harvestable quantity L is defined by the following formula: L = Σ(Tn × Rn) (n = 1 to N) ... (1) where "N" is the total number of workers 1 that can be mobilized in a given period.

[0047] S: Harvestable area (m ２ The harvestable area S is the area that can be harvested by the worker 1 in a predetermined period (for example, one day to one 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 a conversion value when the harvestable area S is normalized by the number of pieces in a unit area ΔS. The normalized area M is defined by the following formula: M = S / ΔS = (L / ΔH) / ΔS (3)

[0049] As shown in Fig. 3, the harvest range selection process (step S10 in Fig. 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 a process of converting growth data Gijk into value data Vijk. Specifically, data conversion is a process of converting the growth degree Gk of the growth data Gijk into a 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 defined in advance according to the type of crop value Vk, for example, based on past statistical data.

[0051] (Calculation of normalized area: step S12) Calculation of normalized area M is a process of calculating normalized area M using the above-mentioned formulas (1) to (3). Specifically, calculation of normalized area M includes the following steps. Step 1: Calculate harvestable amount L using formula (1). Of the input information for formula (1), harvest time Tn and total number of workers N are notified from the management terminal 30. Harvesting efficiency Rn of worker 1 is a set value registered in advance in the storage device 42 of the management server 40.

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

[0053] (Allocating the normalized area: step S13) Allocating the normalized area M is a process of allocating the normalized area M, which corresponds to the harvestable area S calculated in step S12, to the planting position (Xi, Yj) of the value data Vijk based on a predetermined allocation logic. The predetermined allocation logic may be, for example, the following logic.

[0054] Logic 1: The unit area ΔS of the planting position (Xi, Yj) where the work value Vk is equal to or greater than a predetermined threshold THv is selected as the allocation target. The threshold THv is registered in advance in the storage device 42 of the management server 40 for each type of crop value Vk, for example, by the management user 2. By adopting Logic 1, the unit area Δ that does not meet the crop value Vk desired by the management user 2 is excluded from the allocation target. This avoids harvesting work on grapes 3 with a low crop value Vk. This allows the labor of the workers 1 to be appropriately allocated.

[0055] Logic 2: Of the unit areas ΔS of the planting positions (Xi, Yj) where the work value Vk is equal to or greater than the threshold value THv, the unit areas Δ of the planting positions (Xi, Yj) where the crop value Vk is high are given priority for allocation. By adopting Logic 2, the planting position (Xi, Yj) with the highest crop value Vk is included in the harvest range, allowing grapes 3 with a high crop value Vk to be harvested early.

[0056] Logic 3: First, select an arbitrary unit area ΔS from among the unit areas ΔS of the planting position (Xi, Yj) where the work value Vk is equal to or greater than the threshold value THv, and from the second onwards, give priority to unit areas ΔS that are closer to the first unit area ΔS as allocation targets. By adopting Logic 3, from the second onwards, allocation targets are determined based on distance, making it possible to select a harvesting range that requires a short travel distance for the worker 1.

[0057] 3 shows an example of value data (value map) Vijk in which the value of the normalized area M is "10" and the closer to the origin of the vineyard Au the higher the crop value Vk. In this case, if the above-mentioned Logic 1 is applied, for example, the harvest range consisting of 10 unit areas ΔS will be allocated in the shape of a right triangle with the origin of the field Au as the right angle point.

[0058] 4 is an explanatory diagram showing an example of the generation process of the result characteristic executed by the control device 41 of the management server 40. Below, the definitions of the parameters used in the generation process of the result characteristic will be explained, and then the contents of the generation process will be explained. However, the explanation of the parameters already mentioned will be omitted.

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

[0060] Vijm: Descending Order Data The descending order data Vijm is data that represents the descending order value Vm at the planting position (Xi, Yj). The descending order data Vijm is defined by the following three-dimensional vector: Vijm = (Xi, Yj, Vm) The data format of the descending order data Vijm may be either a digital map format or a table format. Note that descending order data in digital map format is called a "descending order map."

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

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

[0063] F: Result characteristic The result characteristic F is a parameter that represents the characteristics of the result (cumulative value) relative to the yield of grapes 3. In this embodiment, the result characteristic F is defined as a function that represents the relationship between the high-value yield H and the harvest result VA. That is, the result characteristic F is a function defined by the following equation: VA = F(H) (6) When a graph of the result characteristic F is displayed on a display, it can be displayed as a bitmap image, for example, as shown in FIG. 4, in which the magnitude of the descending value Vm used to calculate the result characteristic F is expressed by color or shading.

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

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

[0066] (Calculation of outcome characteristic: Step S22) Calculation of outcome characteristic F is a process of calculating outcome characteristic F of vineyard Au using descending value Vm obtained in Step S21. Specifically, calculation of outcome characteristic F includes the following steps.

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

[0068] Step 5: Increment the identification number m, and repeat steps 2 to 4. Step 6: When the identification number m reaches its final value, end plotting. Step 7: The line connecting adjacent points in the plotted point cloud with a straight or curved line is set as the outcome characteristic F in equation (6). Note that if either the calculated value of H or the calculated value of VA contains an abnormal value, the abnormal value may be discarded and interpolation processing may be performed.

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

[0070] Calculation process 2: Calculation of "target harvest volume HD" Calculation process 2 is a process for calculating the high-value harvest volume H required to obtain the harvest volume VA desired by the management user 2 in the product characteristic F. Hereinafter, the desired harvest volume VA will be referred to as the "target harvest volume VAD", and the high-value harvest volume H required for this will be referred to as the "target harvest volume HD". Specifically, the target harvest volume HD is calculated using the following formula (8). Note that "F －１ " is the inverse function of the performance characteristic F. HD = F －１ (VAD) ...(8)

[0071] [Example of Use of Selection Processing in Work Planning] Figure 5 is a sequence diagram showing an example of use of the selection processing in work planning. 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 the worker 1, the total number of workers N, and the harvesting time Tn of each worker 1. The identification number n can be determined from identification information such as the name of the worker 1.

[0072] Next, the management server 40 executes a harvesting range selection process (step ST13). Specifically, the control device 41 of the management server 40 executes the aforementioned selection process (FIG. 3) using the received identification number n, total number of people N, and harvesting time Tn as input information to select a harvesting range in the value data Vijk. The control device 41 also outputs a selection result SR to the communication device 43. The selection result SR is, for example, comprised of value data (value map) Vijk including the selected harvesting range.

[0073] Next, the management server 40 transmits a creation response AQ1 including the selection result SR to the management terminal 30 (step ST14). The management server 40 also transmits the work content WN (e.g., harvesting location and time period) for each worker 1 that constitutes the selection result SR to the mobile terminal 20 of each worker 1 (step ST15). However, the management terminal 30 may notify each mobile terminal 20 of the work content WN.

[0074] Next, the management terminal 30 outputs the selection results SR received from the management server 40 (step ST16). This output is, for example, a process of displaying the selection results SR on the display of the management terminal 30. Fig. 6 is a diagram showing an example of a display screen of the selection results SR on the management terminal 30.

[0075] As shown in FIG. 6, the display screen for the selection result SR includes the columns "Date," "Personnel," and "Harvesting Range." The date and personnel columns contain input information set by administrative user 2. In the illustrated example, 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). Also, the working hours of workers A, B, C, and D are as shown in the figure.

[0076] The harvest range column displays a value map Vijl including the harvest range selected by the selection process (Fig. 3). The horizontal axis represents Xi and the vertical axis represents Yj. As an example, Fig. 6 shows the selection result SR of harvest work for a specified period of three days from September 16th to September 18th. Specifically, the following harvest ranges (hatched areas in the figure) are displayed as the harvest ranges to be performed on each schedule:

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

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

[0079] Harvesting 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, if the harvest range selection result (harvest range) SR is superimposed on the value map Vijk of the field Au, the management user 2 can determine at a glance where in the vineyard Au harvesting work should be carried out, resulting in a display format with excellent visibility.

[0081] [Example 1 of Using Product Characteristics in Work Planning] Figure 7 is a sequence diagram showing Example 1 of Using Product Characteristics in Work Planning. As shown in Figure 7, after accessing the support service (step ST21), the management terminal 30 sends a harvest product calculation request RQ2 to the management server 40 (step ST22). The calculation request RQ2 includes the identification number n of the worker 1, the total number of workers N, and the harvesting time Tn of each worker 1. The identification number n can be determined from identification information such as the name of the worker 1.

[0082] Next, the management server 40 executes a process for calculating the possible harvest result 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. The control device 41 also calculates the possible harvest result VAL by applying the calculated possible harvest amount L to equation (7) related to the result characteristic F.

[0083] Next, the management server 40 transmits a calculation response AQ2 including the possible harvest result 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 a process of displaying, for example, the numerical value of the possible harvest result VAL itself or a graph of the result characteristic F including the numerical value of the possible harvest result VAL (see FIG. 4) on the display of the management terminal 30.

[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 management user 2 can be notified in advance of the maximum harvest result VA that can be obtained with the labor currently available.

[0085] [Example 2 of Using Product Characteristics in Work Planning] Figure 8 is a sequence diagram showing Example 2 of using product characteristics in work planning. 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 calculation request RQ3 includes a target harvest result VAD, which is the harvest result VA desired by the management user 2.

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

[0087] Next, the management server 40 transmits a calculation response AQ3 including 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 a process of displaying, for example, the numerical value of the target yield HD itself or a graph of the performance characteristic F including the numerical value of the target yield HD (see FIG. 4) on the display of the management terminal 30.

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

[0089] [Variation 1: Growth Data Prediction Method] In the above-described embodiment, growth data (growth map) Vijk including the growth degree Gk in the relatively near future (e.g., one day later) may be predicted by a model 48 (see FIG. 9 ), which is a learner capable of machine learning. The model 48 is a type of program 47 stored in the storage device 42, and may employ, for example, a neural network including at least one hidden layer between an input layer and an output layer.

[0090] 9 is an explanatory diagram showing an example of a method for predicting future growth data Vijk. In Fig. 9, a model 48 is composed of a learning device that uses yesterday's growth degree Gk at the planting location (Xi, Yj) as input data (teaching data) and today's growth degree Gk at the planting location (Xi, Yj) as output data. Training of the model 48 is performed by adjusting the weighting between nodes in the model 48 so as to minimize the difference between the input data and the output data (learning phase).

[0091] Once the accuracy of the model 48 has been confirmed through training for a predetermined period, the model 48 is used to predict the growth data Vijk for the day after (operation phase). Specifically, today's growth data Vijk is input to the model 48, and tomorrow's growth data Vijk is output from the model 48. Similarly, tomorrow's growth data Vijk is input to the model 48, and the growth data Vijk for two days from now is output from the model 48. The same applies to predictions for three days from now onwards.

[0092] [Variation 2: Labor-saving growth data] In the above-described embodiment, the growth data (growth map) Vijk may be sparsely sampled, and the sampled data may be subjected to predetermined processing such as predetermined TV (Total Variation) regularization, to obtain the growth data Vijk used in the selection process, etc. In this way, the number of source data samples required is reduced, which has the advantage of reducing the storage capacity of the storage device 42 compared to storing growth data Vijk including the growth levels Vk of all planting positions (Xi, Yj).

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

[0094] In the above-described embodiment, the "working entity" who harvests the grapes 3 is not limited to a human worker 1, but may be a harvesting robot that automatically navigates through the vineyard Au. In this case, the harvesting of the grapes 3 by the harvesting robot may be either remotely controlled or automatic. In the above-described embodiment, the crop 3 is not limited to grapes 3, as long as the harvest yield can be estimated approximately accurately for the planting position (Xi, Yj).

[0095] 1 Worker (work subject) 2 Management user 3 Grapes (crop) 20 Mobile terminal 30 Management terminal 40 Management server (information processing device) 41 Control device 42 Storage device 43 Communication device 44 Growth database 45 Value database 46 Descending order database 47 Computer program 48 Model 50 Information providing server 60 Flying device 70 Public network 80 Wireless base station 200 Work support system F Farm Au Field (vineyard) (Xi, Yi) Planting position Vijk Growth data Gijk Value data Gijm Descending order data

Claims

1. An information processing device comprising: a storage device that stores value data representing the crop value of agricultural crops for each planting location; and a control device that executes a harvest range selection process based on the value data, the selection process including: a process of calculating a harvestable area in which a worker can be allowed to harvest within a specified period of time; and a process of allocating the harvestable area to the planting location where the crop value is equal to or greater than a specified threshold.

2. The information processing device according to claim 1, wherein the selection process includes a process of preferentially allocating the harvestable area to the planting locations where the crop value is high.

3. An information processing device according to claim 1, wherein the selection process includes a process of arbitrarily selecting the first planting location, and from the second onwards, preferentially allocating the allocation locations closest to the first planting location.

4. An information processing device as claimed in any one of claims 1 to 3, wherein the selection process includes a process of calculating the harvestable area based on the harvesting time during which the worker can perform harvesting, the harvesting efficiency of the worker, and the total number of the worker.

5. An information processing device according to any one of claims 1 to 3, wherein the storage device stores growth data representing the growth degree of the crop for each planting location, and the control device includes a process for converting the growth data into the value data.

6. An information processing device according to any one of claims 1 to 3, wherein the control device outputs the value data including the selected harvest range as a selection result.

7. The information processing device according to any one of claims 1 to 3, wherein the control device is capable of executing a calculation process of a result characteristic that represents a relationship between a high-value harvest amount and a harvest result, as defined below. High-value harvest amount: A harvest amount when harvesting is performed in order from the crop with the highest crop value. Harvest result: A cumulative value of the crop value when harvesting is performed in order from the crop with the highest crop value.

8. The information processing device according to claim 7, wherein the control device calculates a harvestable amount, which is the yield of the agricultural crop that can be obtained in the specified period, and calculates a possible harvest result, which is the harvest result corresponding to the harvestable amount, based on the harvestable amount and the result characteristics.

9. The information processing device of claim 7, wherein the control device acquires a target harvest result, which is the harvest result desired by a user, and calculates a target harvest volume, which is the high-value harvest volume corresponding to the target harvest result, based on the target harvest result and the result characteristics.

10. A method for selecting a harvesting range executed by an information processing device, comprising: a step of storing value data representing the crop value of agricultural crops for each planting location; and a step of executing a selection process for the harvesting range based on the value data, wherein the selection process includes a step of calculating a harvestable area in which a worker can be allowed to harvest in a specified period of time; and a step of allocating the harvestable area to the planting location where the crop value is equal to or greater than a specified threshold.

11. A computer program that causes a computer to function as an information processing device, causing the computer to function as: a storage device that stores value data representing the crop value of agricultural crops for each planting location; and a control device that executes a harvest range selection process based on the value data, the selection process including: a process of calculating a harvestable area in which a worker can be allowed to harvest in a specified period of time; and a process of allocating the harvestable area to the planting location where the crop value is equal to or greater than a specified threshold.

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