JP2019082765A - Information processing system and program - Google Patents

Abstract

To provide an information processing system and program, which allow for collecting a large amount of work-related data.SOLUTION: A work data collection unit of a management server belonging to a farm work assistance system comprises: a location identification unit configured to identify a location at which farm work was done in a farm cultivating one or more agricultural products; a type identification unit configured to identify the type of the work done at the location identified by the location identification unit; and a work information generation unit configured to generate work information associated with information indicative of the location identified by the location identification unit and information indicative of the work type identified by the type identification unit.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an information processing system and program.

In recent years, it has been studied to make agriculture more efficient by utilizing unmanned agricultural machinery, sensing technology, information technology (IT) and the like. For example, Non-Patent Document 1 discloses an unmanned small-sized weeding robot. Non-Patent Document 2 discloses a method of adding fertilizer according to a growing state utilizing a sensing technology.
[Prior art document]
[Non-patent literature]
[Non-patent document 1] Naoki Kondo et al., "Development of weeding robot", [on line] [searched on October 18, 2017], Internet <URL: http: //www.aptech.kais.kyoto-u. ac.jp/activity/date/grass_cutter_robot.pdf>
[Non-patent literature 2] Local Independent Administrative Institution Hokkaido Comprehensive Research Organization, List of examination research results, "Results summary report (prepared in January 2006)" [on line] [search on October 18, 2017], Internet <URL : Https://www.hro.or.jp/list/agricultural/center/kenkyuseika/gaiyosho/h18gaiyo/f5/2006508.pdf>

  When using IT to streamline farming operations, it is necessary to collect a large amount of data on farming operations.

  In a first aspect of the present invention, an information processing system is provided. The information processing system described above includes, for example, (i) a position of a worker in the field where the substance is sprayed to a field where one or more agricultural products are grown, with a spraying device for spraying the substance, and (ii) the worker And a spraying position specifying unit for specifying at least one of the positions of the spraying device mounted on the field of the field. The above-described information processing system includes, for example, a spread amount specifying unit that specifies the amount of the material to be spread at the position specified by the spread position specifying unit. The information processing system described above is, for example, work information in which (a) information indicating the position specified by the scattering position specifying unit and (b) information indicating the spreading amount of the substance specified by the scattering amount specifying unit are associated. And a work information generation unit for generating

  The above-described information processing system may include a spraying direction identifying unit that identifies the spraying direction of the substance at the position identified by the spraying position identifying unit. In the above information processing system, the work information generation unit is a work in which (a) information indicating the position specified by the scattering position specifying unit and (c) information indicating the direction specified by the scattering direction specifying unit are associated Information may be generated.

  The information processing system described above is an incidental work identification unit that specifies an operation performed by the worker before spraying the substance or after spraying the substance in association with the spraying of the substance at the position specified by the spraying position identifying unit. May be provided. In the above information processing system, the work information generation unit is a work in which (a) information indicating the position specified by the scattering position specification unit and (d) information indicating the work specified by the incidental work specification unit are associated. Information may be generated.

  The above-described information processing system may include a teacher information generation unit that generates teacher information related to the work of dispersing the substance based on the work information related to the one or more first workers generated by the work information generation unit. The above information processing system may include a soil information acquisition unit that acquires soil information in which information indicating a position in a field and information indicating a characteristic of soil at the position are associated. In the above-mentioned information processing system, the teacher information generation unit may generate teacher information based on the soil information acquired by the soil information acquisition unit and the work information of one or more first workers.

  The above-described information processing system may include a growth information acquisition unit that acquires growth information associated with information indicating a position in a field and information indicating a growth state of one or more agricultural products at the position. In the above information processing system, the teacher information generation unit may generate teacher information based on the growth information acquired by the growth information acquisition unit and the work information of one or more first workers.

  The above-described information processing system may include a harvest information acquisition unit that acquires information indicating a position in a field, and harvest information associated with information on an agricultural product harvested at the position. In the above information processing system, the teacher information generation unit may generate teacher information based on the harvest information acquired by the harvest information acquisition unit and the work information of one or more first workers.

  In the above-described information processing system, the spraying position specifying unit includes at least (i) the position in the field of the second worker who sprays the substance and (ii) the position in the field of the spraying device attached to the second worker. One may be identified. In the above-described information processing system, the spread amount specifying unit may specify the amount of the material that has been spread at the position specified by the spread position specifying unit. In the information processing system described above, the scatter position identifying unit identifies based on (i) the amount of the substance that has already been sprayed specified by the scatter amount identifying unit, and (ii) the teacher information generated by the teacher information generating unit. At the second operator's location, it may comprise an application rate determination unit which determines the amount of substance to be applied. The above information processing system may include a spread amount control unit that controls the spreader based on the amount of the substance to be spread determined by the spread amount determination unit.

  The above-described information processing system may include an image data acquisition unit that acquires data of an image obtained by capturing a state in which at least one of the worker and the distribution device is dispersing the substance. The above-described information processing system may include an imaging position acquisition unit that acquires information indicating a position when an imaging device that captures an image captures an image. In the above-described information processing system, the scattering position specifying unit may analyze the data acquired by the image data acquiring unit to determine the relative positional relationship between the imaging device and at least one of the worker and the scattering device. . In the above information processing system, the scattering position specifying unit is configured to set the position of the worker in the field and the scattering device based on the position of the imaging device indicated by the information acquired by the imaging position acquiring unit and the relative positional relationship. At least one of the positions in the field may be identified.

  In a second aspect of the present invention, an information processing system is provided. The above-described information processing system includes, for example, a position specifying unit that specifies a position at which agricultural work is performed in a field where one or more agricultural products are grown. The above information processing system includes, for example, a content specifying unit that specifies the content of the work at the position specified by the position specifying unit. The above information processing system generates, for example, work information in which (a) information indicating the position specified by the position specifying unit and (b) information indicating the content of the work specified by the content specifying unit are associated with each other. A work information generation unit is provided.

  In a third aspect of the invention, a program is provided. The above program may be a program for causing a computer to function as an information processing system according to the first aspect or the second aspect. A computer readable medium storing the above program may be provided. Computer readable media may be non-transitory computer readable media. The computer readable medium may be a computer readable recording medium.

  Note that the above summary of the invention does not enumerate all the necessary features of the present invention. In addition, a subcombination of these feature groups can also be an invention.

An example of a system configuration of agricultural work support system 100 is shown roughly. An example of an internal structure of the management server 110 is shown roughly. An example of an internal structure of the work data collection part 222 is shown roughly. An example of an internal structure of the analysis part 232 is shown roughly. An example of an internal structure of the work assistance part 234 is shown roughly. An example of a data format of various information stored in storage part 240 is shown roughly. An example of a system configuration of agricultural work robot 120 is shown roughly. An example of the spreading | diffusion unit 150 is shown roughly. An example of the accommodation unit 160 is shown roughly.

  Hereinafter, the present invention will be described through the embodiments of the invention, but the following embodiments do not limit the invention according to the claims. Moreover, not all combinations of features described in the embodiments are essential to the solution of the invention. In the drawings, the same or similar parts may be denoted by the same reference numerals and redundant description may be omitted.

[Overview of Farm Work Support System 100]
FIG. 1 schematically shows an example of a system configuration of the agricultural work support system 100. As shown in FIG. In the present embodiment, the agricultural work support system 100 includes a management server 110. The agricultural work support system 100 may include the agricultural work robot 120. In the present embodiment, the farming robot 120 includes a base unit 130, a moving unit 132, and an imaging unit 134. The farming robot 120 may include one or more sensor units 136. The farming robot 120 may include one or more farming units 138.

  The agricultural work support system 100 may be an example of an information processing system. The management server 110 may be an example of an information processing system. The farming robot 120 may be an example of a mobile body. The farming robot 120 may be an example of a working machine or an unmanned working machine. The farming robot 120 may be an example of an agricultural machine.

  In order to produce agricultural products 30, such as soil sampling, soil analysis, fertilization, establishment, sowing, planting or planting, monitoring of fields, pest control, weeding, thinning or stripping, additional fertilization, determination of harvest time, harvest, etc. Work occurs. The work to produce the produce 30 may be referred to as farming. Farm work may be an example of work. The soil may be an example of the culture medium 30.

  In the present embodiment, the agricultural work support system 100 manages agricultural work related to each of the one or more agricultural products 30. The agricultural work support system 100 may support at least one of the worker 12 engaged in agricultural work and the agricultural work robot 120. For example, the agricultural work support system 100 supports at least one of the worker 12 and the agricultural work robot 120 by instructing at least one of the worker 12 and the agricultural work robot 120 the content of the operation to be performed next.

[Overview of information processing in agricultural work support system 100: collection of information]
According to one embodiment of the farming support system 100, the management server 110 collects information regarding the work of the workers 12. As the information on the work, information on the contents of the work, information on the agricultural products 30 to be subjected to the work, and the like can be exemplified. The management server 110 may collect information on the field where the agricultural product 30 is grown.

  The management server 110 collects the above information by acquiring, via the communication network 10, data of an image captured by an imaging device disposed in a field, work tool, worker 12, agricultural work robot 120, etc. Good. The management server 110 may collect the above information by acquiring observation data of various sensors disposed in the field, work tools, workers 12, the agricultural work robot 120, and the like via the communication network 10. At least one of the image data and the observation data may be transmitted to the management server 110 via at least one of the communication terminal 22 and the farming robot 120.

  In the present embodiment, the farming robot 120 has an autonomous traveling function. The farming robot 120 may have a self position estimation function. The farming robot 120 may store information indicating the time and information indicating the self position in the storage device of the farming robot 120 in association with each other. Thereby, the movement history of the farming robot 120 can be recorded. The farming robot 120 may transmit the information indicating the time and the information indicating the self position to the management server 110 in association with each other. The farming robot 120 may transmit, to the management server 110, information indicating the time and information indicating the self position in association with each other for each predetermined period.

  The unit representing time is not particularly limited. Any unit depending on the purpose may be used as a unit representing time. As a unit representing time, milliseconds, seconds, minutes, hours, days, etc. can be exemplified. When it is intended to specify the position of the worker 12 and the agricultural work robot 120, it is preferable to use a unit “minute” or shorter as a unit representing time, and “second” or shorter More preferably, units are used. When it is intended to specify the position of the produce 30, it is preferable to use a unit "day" or shorter as a unit representing time, and use a unit "minute" or shorter Is preferred. For the purpose of specifying the position of a subject in an image, it is preferable to use "minutes" or shorter units, and more preferable to use "seconds" or shorter units.

  The method of expressing the position is not particularly limited. A position may be represented by a spatial reference (sometimes referred to as a direct reference) by coordinates in any coordinate system, or a spatial reference (sometimes referred to as an indirect reference) by any geographical identifier. May be represented by Examples of the geographical identifier include (i) an address, (ii) a zip code, and (iii) an identifier assigned to a section (sometimes referred to as a mesh or grid) having a predetermined geographical range. can do. As the above-mentioned section, UTM grid or MGRS (Military Grid Reference System) can be exemplified. The information indicating the position may include information indicating the height from the reference position. As the reference position, a point 0 m above sea level, a point representing a field, and the like can be exemplified.

  As a geographic identifier of the agricultural product 30, identification information of a strain in which the agricultural product is grown may be used. In any storage device, identification information of each of one or more stocks and the position of the stock may be stored in association with each other. As a geographic identifier of the agricultural product 30, identification information of a strain in which the agricultural product is grown and information indicating the position of the agricultural product in the strain may be used. The information indicating the position of the agricultural product in the stock may be information indicating the reference position of the stock and the relative position of the agricultural product. The accuracy of the relative position is not particularly limited. The relative position may be represented numerically or may be indicated by a segment indicating the position in the strain. The division indicating the position in the stock is, for example, "upper part", "central part", "lower part" or the like.

  The method of estimating the self position is not particularly limited. As a method of estimating the self position, (i) using an internal sensor that measures internal information of the agricultural work robot 120 such as an encoder, an inertial sensor, or a gyro sensor, the movement amount of the agricultural work robot 120 from the reference position is integrated (Ii) information on landmarks whose absolute positions are known, using an external sensor that observes the environment around the farming robot 120, such as an imaging device or a distance measuring device; Method to estimate self-location based on information from external sensor, (iii) Method to estimate self-location using GPS signals, radio waves from radio base station, etc., (iv) combining them The method etc. which estimate a position can be illustrated.

  In the present embodiment, for example, the agricultural work robot 120 moves so as to be positioned behind the worker 12 in the traveling direction of the worker 12 in operation. The farming robot 120 may move so as to be located in front of the worker 12 in the traveling direction of the worker 12 in operation. The farming robot 120 may move in front of or behind the worker 12 while keeping the distance to the worker 12 constant. The farming robot 120 may approach the worker 12 or move away from the worker 12 based on an instruction of the worker 12. The instruction of the worker 12 may be an instruction by voice or an instruction by gesture.

  While moving in front of or behind the worker 12, the farming robot 120 uses the imaging unit 134 to image at least one of a state in which the worker 12 works and a state of an object of the work. The farming robot 120 may store data of the captured image or an analysis result of the image in a storage device of the farming robot 120. Thereby, the work history of the worker 12 can be recorded. The farming robot 120 may transmit data of a captured image or an analysis result of the image to the management server 110. The image may be a moving image or a still image.

  In one embodiment, the captured image may be associated with the time when the image was captured. Thus, the management server 110 can associate the captured image with the position of the farming robot 120 when the image is captured, using, for example, the time as a key. In another embodiment, the captured image may be associated with the position of the farming robot 120 when the image is captured.

[Outline of information processing in agricultural work support system 100: analysis of information]
According to the present embodiment, the management server 110 relatively easily collects, for example, (i) information on the work of one or more workers 12 and (ii) information on one or more fields relatively easily. can do. The management server 110 may analyze the collected information to generate information for supporting the work of the worker 12 or the farming robot 120. For example, the management server 110 analyzes the collected information to generate one or more analysis models. The analytical model includes (i) a function of one or more parameters, (ii) a function of one or more random variables and one or more parameters, (iii) a mathematical model for numerical analysis, (iv) a machine A learned model by learning or deep learning can be illustrated.

  In one embodiment, the management server 110 analyzes a plurality of data on a particular type of produce in a particular field to generate a field-specific analytical model for the crop. The analysis model described above defines, for example, the relationship between the parameters related to the above-mentioned operations on agricultural products and the parameters related to the growth state of the agricultural products. As a growing condition of agricultural products, a growing stage, a growing condition, etc. can be illustrated.

  For example, in the above analysis model, (i) information indicating the type of agricultural product, (ii) information indicating the target for harvest time, quality, yield of agricultural product, etc., and (iii) current growth state of agricultural product When the information and (iv) information indicating the contents of the work performed on the agricultural product in a specific period are input, the analysis model is (i) the type of work to be performed from now on (ii B) outputting information indicating the position at which the operation is to be performed, and (iii) at least one of the timing at which the operation is to be performed and the operation intensity. Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

  The above-mentioned specific period is, for example, a period from the start of cultivation of agricultural products in the present cultivation cycle to the present. For example, as the work intensity of the spreading work, the spreading amount per time, the spreading frequency and the like can be illustrated.

  In another embodiment, the management server 110 analyzes the plurality of data on a particular type of agricultural product in a plurality of fields, or the data of the agricultural products in a plurality of locations on a single field, and makes the management server 110 generic. Generate an analytical model. The above-mentioned analytical model defines, for example, the relationship between the parameters related to the above-mentioned operations on agricultural products, the parameters related to at least one of soil and weather, and the growth of agricultural products 30.

  For example, in the above analysis model, (i) information indicating the type of agricultural product, (ii) information indicating the target for harvest time, quality, yield of agricultural product, etc., and (iii) current growth state of agricultural product Once information is entered, (iv) information indicating the content of the work performed on the agricultural product during a specific period, and (v) information on at least one of the soil and weather of the field where the agricultural product is grown, The analysis model indicates (i) the type of work to be performed from now on, (ii) the position where the work should be performed, and (iii) at least one of the time when the work should be performed and the work strength. Output information Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

  According to still another embodiment, the management server 110 uses information on the work of the experienced worker 12 as a learning data set (may be referred to as learning data, teacher data, etc.). Perform machine learning or deep learning. The training data set may be an example of teacher information. Thereby, the management server 110 generates a learned model for presenting an appropriate work to the user according to the situation of the user. The above user is, for example, an inexperienced worker 12. The above user may be a worker 12 who is rich in the above experience.

  For example, when a plurality of data on a specific type of agricultural product in a specific field is input as learning data, a field-specific learned model is generated for the agricultural item. For example, (i) information indicating the type of agricultural product, (ii) information indicating the target for harvest time, quality, yield of agricultural product, etc., and (iii) current growth state of agricultural product, in the above-described learned model. When the information to be shown and (iv) the information indicating the contents of the work performed on the agricultural products are input in a specific period, the learned model is (i) the type of the work to be performed from now on, (Ii) outputting information indicating a position at which the operation is to be performed, and (iii) at least one of the timing at which the operation is to be performed and the operation strength. Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

  For example, when a plurality of data regarding a specific type of agricultural product in a plurality of fields or data of the agricultural products in a plurality of locations of a single field are input as learning data, general learning about the agricultural products is completed A model is generated. For example, (i) information indicating the type of agricultural product, (ii) information indicating the target for harvest time, quality, yield of agricultural product, etc., and (iii) current growth state of agricultural product, in the above-described learned model. When information to be shown, (iv) information indicating the contents of work performed on agricultural products during a specific period, and (v) information on at least one of soil and weather of a field where agricultural products are grown are input The learned model includes (i) the type of work to be performed, (ii) the position at which the work is to be performed, and (iii) at least one of the time and the strength of the work. Output information indicating. Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

  Further, in the present embodiment, the management server 110 manages, for each field, a history of work performed at each position of the field. Moreover, the management server 110 manages the history of the growth state of the agricultural products 30 grown at each position of the field, for each field. Furthermore, the management server 110 manages, for each field, at least one of the quality and the yield of the agricultural products 30 harvested at each position of the field.

  Thus, the management server 110 (i) history of work performed at a specific position of a specific field, (ii-1) growth state of the agricultural product 30 grown at the position, (ii-2) The quality of the produce 30 harvested at the location and (ii-3) at least one of the yields of the produce 30 at the location can be correlated. As a result, the management server 110 can evaluate at least a part of the plurality of operations performed on the produce 30. The management server 110 may generate learning data for machine learning or deep learning based on the above evaluation result.

[Specific Example of Information Processing in Farm Work Support System 100: In the Case of Scattering Work]
According to one embodiment shown in FIG. 1, the agricultural work support system 100 collects information on the work performed by the workers 12 engaged in the spreading work. In addition, the agricultural work support system 100 manages the collected information.

  In the present embodiment, the worker 12 sprays substances such as seeds, water, fertilizers, pesticides, etc. while moving the spray unit 150, for example. The spreading unit 150 associates the data indicating the spreading time with the data indicating the spreading amount, and transmits the data to the communication terminal 22, the farming robot 120, or the management server 110. The spreading unit 150 may have a self position estimation function. In this case, the spreading unit 150 may transmit the information indicating the time and the information indicating the self position to the communication terminal 22, the farming robot 120, or the management server 110 in association with each other. The communication terminal 22 and the agricultural work robot 120 may transfer the data received from the distribution unit 150 to the management server 110.

  In another embodiment, the spraying unit 150 may be mounted on the farming robot 120. The farming robot 120 may control the dispensing unit 150 to dispense material. The spreading unit 150 may be an example of the farming unit 138 or an attachment for farming.

  On the other hand, in the present embodiment, the agricultural work robot 120 captures an image of the worker 12 who is performing the dispersing operation while moving in front of or behind the worker 12. The farming robot 120 may image how the substance is sprayed. Thus, for example, when the worker 12 is spraying the pesticide, by analyzing the captured image, information indicating the spraying direction or the spraying destination of the pesticide can be obtained. For example, it is possible to obtain information indicating whether the pesticide is applied to the front side of the leaf, the back side of the leaf, the stem, or the root. In addition, by analyzing the captured image, information about the work performed by the worker 12 can be obtained immediately before the worker 12 spreads the pesticide or immediately after the pesticide is sprayed. The farming robot 120 transmits data of the captured image or an analysis result of the image to the management server 110.

  In the present embodiment, the management server 110 acquires various types of information from at least one of the communication terminal 22, the agricultural work robot 120, and the distribution unit 150, and manages the information. The management server 110 learns information on the spreading operation and generates model data for the spreading operation. In response to a request from the worker 12 or the farming robot 120, the management server 110 presents information such as the time to spray the substance, the position to spray the substance, and the amount of the substance to be sprayed to the position. Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

[Specific example of information processing in the agricultural work support system 100: in the case of harvesting work]
According to another embodiment shown in FIG. 1, the agricultural work support system 100 collects information on the work performed by the workers 12 engaged in the harvesting work. In addition, the agricultural work support system 100 manages the collected information.

  For example, the worker 12 harvests the produce 30 while moving the field. The worker 12 stores the harvested produce 30 in the storage unit 160 of the farming robot 120. In the present embodiment, the accommodation unit 160 has a plurality of accommodation units. Then, the worker 12 judges the quality of the harvested agricultural product 30, and accommodates the harvested agricultural product 30 in the storage unit according to the quality. The housing unit 160 may be an example of the farming unit 138 or an attachment for farming.

  On the other hand, in the present embodiment, the farming robot 120 specifies a storage unit in which the harvested produce 30 is stored among the plurality of storage units. For example, the farming robot 120 measures the mass of the content of each storage unit. Then, when the mass of the content of the one storage unit is increased, the farming robot 120 detects that the agricultural product 30 is stored in the one storage unit. According to the present embodiment, since each accommodation unit is associated with the quality of the produce 30, the farming robot 120 can specify the quality of the harvested produce 30. The farming robot 120 may specify the mass of the harvested produce 30.

  Further, in the present embodiment, the agricultural work robot 120 captures an image of the worker 12 who is performing a harvesting operation while moving in front of or behind the worker 12. The farming robot 120 may image the pre-harvest produce 30 and may image the harvested produce 30. The farming robot 120 transmits data of the captured image or an analysis result of the image to the management server 110. Thereby, information on judgment criteria when harvesting the agricultural products 30 can be obtained. For example, if which part of the agricultural product 30 is in what state, information indicating whether or not the agricultural product 30 should be harvested can be obtained. The farming robot 120 transmits data of the captured image or an analysis result of the image to the management server 110.

  In the present embodiment, the management server 110 acquires various types of information from at least one of the communication terminal 22, the agricultural work robot 120, and the distribution unit 150, and manages the information. In one embodiment, the management server 110 uses information on the quality and / or mass of the harvested produce 30 to generate learning data for various operations. In another embodiment, the management server 110 learns information related to harvesting operations and generates model data for harvesting operations. In response to a request from the worker 12 or the farming robot 120, the management server 110 presents information such as the time to spray the substance, the position to spray the substance, and the amount of the substance to be sprayed to the position. Thus, the worker 12 can appropriately control the growth of the agricultural product 30.

[Overview of each part of the agricultural work support system 100]
In the present embodiment, the management server 110 exchanges information with the farming robot 120 via the communication network 10. The management server 110 may transmit and receive information to and from the communication terminal 22 of the worker 12 via the communication network 10.

  In the present embodiment, the communication network 10 may be a wired communication transmission path, a wireless communication transmission path, or a combination of a wireless communication transmission path and a wired communication transmission path. . The communication network 10 may include a wireless packet communication network, the Internet, a P2P network, a dedicated line, a VPN, a power line communication line, and the like. The communication network 10 may include (i) a mobile communication network such as a mobile telephone network, and (ii) a wireless MAN (for example, WiMAX (registered trademark)), a wireless LAN (for example, WiFi (registered trademark)) ), Bluetooth (registered trademark), Zigbee (registered trademark), wireless LAN such as NFC (Near Field Communication), Bluetooth (registered trademark), Zigbee (registered trademark), and NFC may be an example of near field communication.

  In the present embodiment, the communication terminal 22 exchanges information with the management server 110 via the communication network 10. The communication terminal 22 may send and receive information with the farming robot 120 via the communication network 10. The communication terminal 22 may function as a user interface when the worker 12 accesses the management server 110. The communication terminal 22 may be used for user authentication processing by the management server 110. The communication terminal 22 may function as a user interface when the worker 12 operates the farming robot 120. The communication terminal 22 may be used for user authentication processing by the agricultural work robot 120.

  As the communication terminal 22, a personal computer, a portable terminal, etc. can be illustrated. As a portable terminal, a mobile phone, a smart phone, a PDA, a tablet, a notebook computer or a laptop computer, a wearable computer, etc. can be exemplified.

  In the present embodiment, the management server 110 manages information on one or more agricultural products 30 grown in the field. Examples of agricultural products 30 include cereals, vegetables (including root vegetables), fruits, flowers, leaves and leaves (for example, tea leaves, decorative branches or leaves, etc.), mushrooms or mycelia, etc. .

  In one embodiment, the management server 110 manages at least one of information on the type of the agricultural product 30, information on the growth stage of the agricultural product 30, and information on the growth status of the agricultural product 30, as the information on the agricultural product 30. The information on the growth status may be information indicating an evaluation compared to any standard. The evaluation may be represented by a continuous numerical value or may be represented by a graded division. As the evaluation represented by the graded division, a two-stage evaluation such as "excellent", "good" and "poor", a three-stage evaluation such as "excellent", "good" and "impossible", "excellent", Four-step evaluation such as "Good", "Possible" and "No", Five-step evaluation such as "S", "A", "B", "C", "D" Etc. can be illustrated. The information on the growth state of the agricultural product 30 may be an example of information on the result of the work described below.

  In another embodiment, the management server 110 manages information on the work performed on the agricultural product 30 as the information on the agricultural product 30. Examples of the information regarding the work include at least one of information indicating the time when the work was performed, information indicating the worker 12 who performed the work, information regarding the content of the work, and information regarding the result of the work . Examples of the information on the outcome of the work include at least one of information indicating the quality of the harvest, information indicating the yield, and information indicating the yield.

  In still another embodiment, the management server 110 may manage, as the information on the agricultural product, information on the field where the agricultural product is grown. The information on the field can be exemplified by at least one of information on the soil of the field and information on the weather of the field.

  The management server 110 may divide the field into a plurality of sub areas, and manage information on one or more agricultural products grown in each of the plurality of sub areas. Each subarea may be one of virtually divided areas or one of physically divided areas. Each subarea may have any shape. The positions of the worker 12, the agricultural product 30, the farming robot 120, etc. may be represented by an identification symbol given to the sub area where they exist, and any position that can indicate a specific position inside the sub area It may be represented by coordinates in a coordinate system.

  In the present embodiment, the farming robot 120 may be a machine that performs an arbitrary operation. The agricultural work robot 120 executes, for example, various agricultural work, monitoring work, and the like. The farming robot 120 may be stationary or mobile. The farming robot 120 may have an autonomous traveling function or an autonomous navigation function, may be steered by remote control, and may be steered by a worker who gets in the farming robot 120. The farming robot 120 is preferably an unmanned working machine having an autonomous traveling function or an autonomous navigation function.

The farming robot 120 may be a small robot. For example, the volume of one agricultural work robot 120 may be 2 m ³ or less, 1 m ³ or less, 0.5 m ³ or less, or 0.25 m ³ or less. This allows free movement within the field. In addition, it is possible to observe the agricultural product 30 even from an angle that is difficult for humans.

  In the present embodiment, the base unit 130 holds the moving unit 132, the imaging unit 134, the sensor unit 136 and the farming unit 138. Each of the movement unit 132, the imaging unit 134, the sensor unit 136, and the farming unit 138 may be configured to be removable from the base unit 130. Thus, the farming robot 120 can cope with a plurality of different types of tasks.

  In the present embodiment, the mobile unit 132 moves the farming robot 120. The power of the mobile unit 132 may be electric power, may be an internal combustion engine, or may be a steam engine. Details of the mobile unit 132 will be described later.

  In the present embodiment, the imaging unit 134 images various subjects. For example, the imaging unit 134 images at least one of the worker 12, the farming robot 120, the produce 30, and the surrounding environment of the produce 30. As a surrounding environment of agricultural products 30, the inside of a field or the circumference of a field can be illustrated. The imaging unit 134 may image the soil at the position where the agricultural product 30 is growing as the surrounding environment of the agricultural product 30.

  Data of an image captured by the imaging unit 134 may be stored in the storage device of the agricultural work robot 120 or may be transmitted to the management server 110. The farming robot 120 may analyze data of an image captured by the imaging unit 134 and transmit an analysis result to the management server 110. Details of the imaging unit 134 will be described later.

  In the present embodiment, the sensor unit 136 measures various physical quantities. For example, the sensor unit 136 measures at least one of a physical quantity of the worker 12, a physical quantity of the farming robot 120, a physical quantity of the agricultural product 30, and a physical quantity of the surrounding environment of the agricultural product 30.

  As a physical quantity regarding farm products 30, the color of the farm products 30, shape, size, composition, content of a specific ingredient, hardness, etc. can be illustrated. As a physical quantity about the circumference environment of farm products 30, a physical quantity about soil of a field where farm products 30 are grown, a physical quantity about weather of the field concerned, etc. can be illustrated.

  The measurement results of the sensor unit 136 may be stored in the storage device of the agricultural work robot 120, and may be transmitted to the management server 110. The farming robot 120 may analyze the measurement result of the sensor unit 136 and transmit the analysis result to the management server 110. Details of the sensor unit 136 will be described later.

  In the present embodiment, the farming unit 138 may be an attachment for farming. For example, a farming unit 138 depending on the application is attached to the base unit 130. Thus, the farming robot 120 can perform a plurality of different types of farming work. The details of the farming unit 138 will be described later.

  Each of the farming units 138 may be a unit specialized for one or more farming operations. As the agricultural work unit 138, a chemical solution spraying device for pest control, a fertilizer spraying device for spraying fertilizer, a gas spraying device for spraying gas, a setting device, a seedling dropping device, a seeding device, a tilling device, unnecessary branches and leaves are dispensable , A manipulator with a jig for picking produce, a manipulator with a jig for picking produce, a mowing apparatus (for example, a mowing apparatus for a field which has been left for a long time), a watering apparatus, a bird threat device (for example, voice, It is an apparatus that threatens birds and animals with light), thinning apparatus, flower thinning apparatus, fruit picking apparatus, bag hanging apparatus (for example, a bag hanging apparatus for fruit trees), and the like.

[Specific configuration of each part of agricultural work support system 100]
Each part of agricultural work support system 100 may be realized by hardware, may be realized by software, or may be realized by hardware and software. At least a part of each unit of the agricultural work support system 100 may be realized by a single server or may be realized by a plurality of servers. At least a part of each unit of the agricultural work support system 100 may be realized on a virtual machine or on a cloud system. At least a part of each unit of the agricultural work support system 100 may be realized by a personal computer or a portable terminal. As a portable terminal, a mobile phone, a smart phone, a PDA, a tablet, a notebook computer or a laptop computer, a wearable computer, etc. can be exemplified. Each part of the agricultural work support system 100 may store information using a distributed ledger technology such as a block chain or a distributed network.

  When at least a part of the components constituting the agricultural work support system 100 is realized by software, the components realized by the software define an operation related to the components in the information processing apparatus having a general configuration. It may be realized by activating the software or program. An information processing apparatus having the above general configuration includes (i) a data processing apparatus having a processor such as a CPU or GPU, a ROM, a RAM, a communication interface, etc., and (ii) a keyboard, pointing device, touch panel, camera, voice input Devices, gesture input devices, various sensors, input devices such as GPS receivers, (iii) output devices such as display devices, voice output devices, vibration devices, and (iv) storage devices such as memories, HDDs, and SSDs Storage devices).

  In the information processing apparatus having the above general configuration, the data processing apparatus or the storage device may store the software or the program. The above software or program is executed by the processor to cause the above information processing apparatus to execute an operation defined by the software or program. The above software or program may be stored in a non-transitory computer readable recording medium. The above software or program may be a program for causing a computer to function as the agricultural work support system 100 or a part thereof. The above software or program may be a program for causing a computer to execute information processing in the agricultural work support system 100 or a part thereof.

  In the present embodiment, the case where the management server 110 and the agricultural work robot 120 share and execute information processing in the agricultural work support system 100 has been described. However, the sharing method of information processing in the agricultural work support system 100 is not limited to the present embodiment. In another embodiment, the communication terminal 22 or the agricultural work robot 120 may execute at least a part of the information processing of the management server 110 in the present embodiment, and the communication terminal 22 or the management server 110 performs the agricultural work in the present embodiment. At least a part of the information processing of the robot 120 may be executed.

  FIG. 2 schematically shows an example of the internal configuration of the management server 110. As shown in FIG. In the present embodiment, the management server 110 includes an input / output control unit 212, a work data collection unit 222, a field data collection unit 224, an analysis unit 232, a work support unit 234, and a storage unit 240. In the present embodiment, the storage unit 240 includes a work information storage unit 252, a result information storage unit 254, a soil information storage unit 262, a weather information storage unit 264, a growth information storage unit 266, and a model information storage unit 282. And. The units of the management server 110 may send and receive information to and from each other.

  The work data collection unit 222 may be an example of a work information generation unit, a harvest information acquisition unit, a quality information acquisition unit, a harvest information generation unit, and a breeding condition acquisition unit. The field data collection unit 224 may be an example of a soil information acquisition unit and a growth information acquisition unit. The analysis unit 232 may be an example of an evaluation unit and a teacher information generation unit.

  In the present embodiment, the input / output control unit 212 controls input / output of information of the management server 110. The input / output control unit 212 may receive the information input to the input device. Examples of the input device include a keyboard, a pointing device, a voice input device (for example, a microphone), an image input device (for example, a camera), a voice recognition device, an image recognition device, and the like. The input / output control unit 212 may output information to the output device. As an output device, a display, a printer, a speaker, an ultrasonic wave output device, a vibration output device, etc. can be illustrated.

  The input / output control unit 212 may control communication with an external information processing apparatus. For example, the input / output control unit 212 transmits and receives information to / from at least one of the communication terminal 22, the agricultural work robot 120, the distribution unit 150, and the storage unit 160. The input / output control unit 212 may be a communication interface. The input / output control unit 212 may correspond to one or more communication methods.

  In the present embodiment, the work data collection unit 222 acquires information related to various kinds of work from at least one of the communication terminal 22, the agricultural work robot 120, the distribution unit 150, and the storage unit 160. The work data collection unit 222 analyzes the above information, and generates work information in which information indicating the position at which the work is performed is associated with information indicating the content of the work. For example, the work data collection unit 222 associates the information indicating the position at which the work was performed with the information indicating the content of the work, and stores the information in the work information storage unit 252.

  In the present embodiment, the work data collection unit 222 relates to information indicating the position in the field from at least one of the communication terminal 22, the farming robot 120, the spreading unit 150, and the containing unit 160, and the agricultural products 30 harvested at the position. The information associated with the information is acquired. The work data collection unit 222 acquires, for example, quality information indicating the quality of the harvested produce 30 from the farming work robot 120. The work data collection unit 222 acquires, for example, mass information indicating the mass of the harvested produce 30 from the agricultural work robot 120.

  In the present embodiment, the work data collection unit 222 generates harvest information in which information indicating the position at which the produce 30 is harvested and information indicating at least one of the quality and the mass of the harvested produce 30 are associated. . For example, the work data collection unit 222 associates the information indicating the position at which the agricultural product 30 was harvested with the information indicating at least one of the quality and the mass of the harvested agricultural product 30, and stores them in the outcome information storage unit 254. .

  In the present embodiment, the field data collection unit 224 acquires information on a field. As the information on the field, at least one of the information on the agricultural product 30 grown in the field and the information on the surrounding environment of the agricultural product 30 can be exemplified. Information on the soil of the field, information on the weather of the field (sometimes referred to as weather data), and the like can be exemplified as the information on the surrounding environment of the agricultural product 30. As weather data, weather, air temperature, water temperature, humidity, rainfall, wind speed, wind direction, amount of sunshine, statistical value of these, etc. can be illustrated.

  In one embodiment, the field data collection unit 224 acquires soil information associated with information indicating the position in the field and information indicating the characteristics of the soil at the position. In another embodiment, the field data collection unit 224 acquires growth information in which information indicating the position in the field and information indicating the growth state of one or more agricultural products 30 at the position are associated. Examples of the information indicating the growth state of the agricultural product 30 include information indicating the growth stage of the agricultural product 30, information indicating the growth state of the agricultural product 30, and the like.

  The field data collection unit 224 acquires information on the field from, for example, at least one of the communication terminal 22, the farming robot 120, and a sensor disposed in the field. In the field, a plurality of types of sensors may be disposed. The field data collection unit 224 may obtain, from an information distribution device that distributes weather data, weather data regarding an area including each field. The weather data may be information on past weather or information on future weather prediction.

  In the present embodiment, the analysis unit 232 generates a learning data set for machine learning or deep learning in the work support unit 234. The analysis unit 232 may generate a learning data set using at least a part of data acquired or generated by at least one of the work data collection unit 222 and the field data collection unit 224. From the data acquired or generated by the work data collection unit 222, the analysis unit 232 extracts data corresponding to the purpose or use of the learned model generated by the work support unit 234, and processes the extracted data. To generate a training data set.

  The analysis unit 232 may generate a learning data set related to a specific operation based on the harvest information acquired or generated by the operation data collection unit 222. For example, from the data acquired or generated in the past, the analysis unit 232 extracts data as a result when the quality and yield of the harvested material satisfy a specific condition, and generates a learning data set. Do. The analysis unit 232 may generate a learning data set related to a specific operation based on the information indicating the growth state of the agricultural product 30 acquired by the field data collection unit 224. For example, from the data acquired or generated in the past, the analysis unit 232 extracts data when the growth state of the agricultural product 30 consequently satisfies a specific condition, and generates a learning data set.

  For example, the analysis unit 232 generates a learning data set related to a specific work based on the work information on the one or more first workers generated by the work data collection unit 222. As a specific operation, a spreading operation, a harvesting operation, etc. can be exemplified. According to one embodiment, as the above-mentioned first worker, a worker who is experienced in the above-mentioned specific work is selected. According to another embodiment, as the above-mentioned first worker, a worker whose growth state of the produce 30 grown by the worker is good or bad is selected. According to still another embodiment, in the past harvesting work, a worker whose quality or yield of produce 30 grown by the worker is good or bad is selected.

  The analysis unit 232 may generate a learning data set based on the work information of the one or more first workers and the soil information acquired by the field data collection unit 224. The analysis unit 232 may generate a learning data set based on the work information of the one or more first workers and the growth information acquired by the field data collection unit 224. The analysis unit 232 may generate a learning data set based on the work information of the one or more first workers and the soil information and the growth information acquired by the field data collection unit 224. The analysis unit 232 may generate a learning data set based on the work information of the one or more first workers and the harvest information acquired by the work data collection unit 222. The analysis unit 232 is based on the work information of the one or more first workers, the soil information and the growth information obtained by the field data collection unit 224, and the harvest information obtained by the work data collection unit 222. And may generate a training data set.

  In the present embodiment, the analysis unit 232 performs multivariate analysis or sensitivity analysis using at least a part of data acquired or generated by at least one of the work data collection unit 222 and the field data collection unit 224. The analysis unit 232 may determine an explanatory variable having a large influence on the objective variable among the one or more explanatory variables related to the objective variable. As the objective variable, the growth state of the agricultural product 30, the quality of the harvest, the mass of the harvest, and the like can be exemplified.

  In the present embodiment, the analysis unit 232 may correct the information acquired by at least one of the work data collection unit 222 and the field data collection unit 224 based on the result of the above-described multivariate analysis or sensitivity analysis. The analysis unit 232 may generate the learning data set using the corrected data according to the same procedure as in the case of generating the learning data set using the data before correction. The analysis unit 232 may use corrected data with respect to some types of information among the plurality of types of information used for the learning data set.

  In the present embodiment, the work support unit 234 provides, to at least one of the worker 12 and the farming robot 120, information for supporting the work of at least one of the worker 12 and the farming robot 120. The work support unit 234 provides information for supporting the work of at least one of the worker 12 and the agricultural work robot 120 based on the information acquired or generated by at least one of the work data collection unit 222 and the field data collection unit 224. You may

  The work support unit 234 may provide information for supporting the work of at least one of the worker 12 and the agricultural work robot 120 using a method of machine learning or deep learning. The work support unit 234 supports the work of at least one of the worker 12 and the farming robot 120 using the information related to the magnitude or sensitivity of the influence of the explanatory variable on the target variable calculated by the analysis unit 232. Information may be provided.

  In the present embodiment, the storage unit 240 stores various types of information. In the present embodiment, the work information storage unit 252 associates and stores information indicating the position at which various works on the produce 30 are performed, and information indicating the contents of the work. For example, the work information storage unit 252 stores the work information generated by the work data collection unit 222. In the present embodiment, the result information storage unit 254 stores result information indicating the results of various operations on the agricultural product 30. For example, the result information storage unit 254 stores the harvest information generated by the work data collection unit 222.

  In the present embodiment, the soil information storage unit 262 stores, for each of one or more fields, information on the soil of the field. The soil information storage unit 262 may store, for each of the one or more fields, information indicating a geographical distribution regarding one or more characteristics of the soil. For example, the soil information storage unit 262 stores the soil information acquired by the field data collection unit 224.

  In the present embodiment, the weather information storage unit 264 stores, for each of one or more fields, information related to the weather of the field. For example, the weather information storage unit 264 stores the weather information acquired by the field data collection unit 224.

  In the present embodiment, the growth information storage unit 266 associates and stores information indicating the position of the produce 30 and information indicating the growth state of the produce 30. For example, the growth information storage unit 266 acquires the growth information acquired by the field data collection unit 224.

  In the present embodiment, the model information storage unit 282 stores a learned model (including a second-order model, a third-order model, and the like) obtained by machine learning or deep learning. The model information storage unit 282 stores, for example, a learned model generated by the work support unit 234. The model information storage unit 282 may store information on the magnitude or sensitivity of the influence of the explanatory variable on the target variable calculated by the analysis unit 232.

  FIG. 3 schematically shows an example of the internal configuration of the work data collection unit 222. As shown in FIG. In the present embodiment, the work data collection unit 222 includes a work position specification unit 310, a work content specification unit 322, an accompanying work specification unit 324, a result information acquisition unit 326, and a work information generation unit 332. In the present embodiment, the work position specifying unit 310 includes an image data acquisition unit 312, an imaging position specifying unit 314, a relative position specifying unit 316, and an absolute position specifying unit 318. The units of the work position specification unit 310 may send and receive information to and from each other.

  The work position specifying unit 310 may be an example of a position specifying unit, a scatter position specifying unit, and a harvest position specifying unit. The image data acquisition unit 312 may be an example of a first image data acquisition unit and a second image data acquisition unit. The work content specification unit 322 may be an example of a content specification unit, a distribution amount specification unit, and a distribution direction specification unit.

  In the present embodiment, the work position specifying unit 310 specifies, for each of the one or more works performed on the produce 30, the positions at which the works are performed. For example, the work position specifying unit 310 specifies at least one of the position of the worker 12 in the field and the position of the work place in the field. In one embodiment, when the worker 12 wears the spraying unit 150 and carries out the spraying operation, the work position specifying part 310 is at least the position of the worker 12 in the field and the nozzle position of the spraying unit 150. Identify one. In another embodiment, if the worker 12 is performing a crop 30 harvesting operation, the location at which the crop 30 was harvested may be identified.

  In the present embodiment, the image data acquisition unit 312 acquires data of an image obtained by capturing a situation in which a work is being performed. In one embodiment, when the worker 12 wears the spraying unit 150 and performs the spraying operation, the image data acquisition unit 312 is a state in which at least one of the worker 12 and the spraying unit 150 is spraying the substance. Acquires the data of the captured image. In another embodiment, when the worker 12 is carrying out a harvest operation of the produce 30, the image data acquisition unit 312 may obtain data of the image of the produce 30 captured before being harvested. In addition, the image data acquisition unit 312 may acquire data of an image obtained by capturing an aspect of the crop 30 being harvested.

  In the present embodiment, the imaging position specifying unit 314 acquires information indicating the position when the imaging device that has captured the image captures an image. For example, when the imaging unit 134 mounted on the farming robot 120 captures the above image, the imaging position specifying unit 314 sets the representative point of the farming robot 120 or the imaging unit 134 when the above image is captured. Get information that indicates the position. The imaging position specifying unit 314 may output the position of the representative point of the agricultural work robot 120 as the position of the imaging unit 134.

  In the present embodiment, the farming robot 120 has a self position estimation function, and associates and records information indicating a time and information indicating a self position at the time. In addition, the imaging unit 134 records the imaging time and the image in association with each other. Thereby, the imaging position specifying unit 314 can specify the position of the representative point of the agricultural work robot 120 when the above-described image is captured. Further, the relative positional relationship (which may be referred to as a relative position) between the representative point of the agricultural work robot 120 and the imaging unit 134 is known. Therefore, the imaging position specifying unit 314 can also specify the position of the imaging unit 134 as needed.

  In the present embodiment, the relative position specifying unit 316 analyzes the data of the image acquired by the image data acquisition unit 312, and the relative positional relationship between the imaging device that has captured the image and the position at which the work was performed. Decide.

  In one embodiment, when the worker 12 wears the spreading unit 150 and performs the spreading operation, and the imaging unit 134 captures an image, the relative position specifying unit 316 includes the imaging unit 134 and the worker The relative position with at least one of 12 and the spreading unit 150 is determined. The relative position specifying unit 316 may output the relative position between the representative point of the imaging unit 134 or the agricultural work robot 120 and the worker 12 as the relative position of the imaging unit 134 and the scattering unit 150.

  In another embodiment, when the worker 12 is carrying out the harvesting operation of the agricultural product 30 and the imaging unit 134 is imaging an image, the relative position specifying unit 316 determines that at least one of the imaging unit 134 and the agricultural product 30 is Determine the relative position with. The relative position specifying unit 316 may output the relative position between the representative point of the imaging unit 134 or the agricultural work robot 120 and the worker 12 as the relative position of the imaging unit 134 and the produce 30.

  In the present embodiment, the absolute position specifying unit 318 specifies the position where the operation is performed based on the position of the imaging device specified by the imaging position specifying unit 314 and the relative position specified by the relative position specifying unit 316. .

  In one embodiment, when the worker 12 wears the spreading unit 150 and performs the spreading operation and the imaging unit 134 captures an image, the absolute position identifying unit 318 identifies the imaging position identifying unit 314. Based on the position of the imaging unit 134 and the relative position specified by the relative position specifying unit 316, at least one of the position of the worker 12 in the field and the position of the spreading unit 150 in the field is specified.

  In another embodiment, when the worker 12 is carrying out the harvesting operation of the agricultural product 30 and the imaging unit 134 captures an image, the absolute position specifying unit 318 determines the imaging unit specified by the imaging position specifying unit 314. Based on the position of 134 and the relative position which the relative position identification part 316 identified, the position where produce 30 was harvested in a field is pinpointed.

  In the present embodiment, the work content specification unit 322 specifies the content of the work. For example, the work content specification unit 322 specifies the content of the work based on at least one of the information acquired by the work data collection unit 222 and the information acquired by the field data collection unit 224. The work content specification unit 322 may specify at least one of the work performed by the worker 12 and the work performed on the produce 30. The contents of the work can be exemplified by the purpose of the work, the type of the work, the strength of the work, the procedure of the work, the type of material used in the work, the type of equipment used in the work, and the like.

  In one embodiment, when the worker 12 carries out the spraying operation (which may include the case where the worker 12 is carrying out the spraying operation), the operation content specifying unit 322 specifies the operation position specifying unit 310. In place, identify the amount of substance sprayed. The work content specification unit 322 may specify, for each predetermined period, an accumulated value of the amount of the substance dispersed in the period. The work content specification unit 322 may specify the spreading direction of the substance at the position specified by the work position specification unit 310. The work content specification unit 322 acquires, for example, measurement data of a flow meter disposed in the distribution unit 150, and specifies the distribution amount of the substance.

  In another embodiment, when the worker 12 carries out the harvesting work (may include the case where the worker 12 is carrying out the harvesting work), the work content specifying unit 322 specifies the work position specifying unit 310. In the selected position, at least one of the quality and mass of the harvested produce 30 is identified. The work content specification unit 322 may specify, for each predetermined period, the accumulated value of the mass of the produce 30 harvested in the period. The work content specification unit 322 acquires, for example, measurement data of a mass meter disposed in the storage unit 160, and specifies at least one of the quality and the mass of the harvested produce 30.

  In the present embodiment, the work content specification unit 322 analyzes the data acquired by the image data acquisition unit 312, and (i) features of the harvested area of the agricultural product 30, and (ii) the periphery of the harvested area Feature information indicative of at least one feature of the non-harvest part of the produce 30. The above-described feature information may be an example of information indicating work content.

  In the present embodiment, at the position specified by the work position specifying unit 310, the incidental work specifying unit 324 causes the worker 12 to carry out the specified work before or after performing the specified work in addition to the specified work. Identify the work that has been carried out (sometimes referred to as incidental work). The incidental work specifying unit 324 may identify an incidental work by analyzing an image obtained by capturing an appearance of the work. For example, when the worker 12 carries out the spraying operation, the worker 12 (i) checks the appearance of the back side of the leaves before carrying out the spraying operation, or (ii) carries out the spraying operation, Check the wetness of

  In the present embodiment, the result information acquisition unit 326 acquires result information indicating the result of the work. In one embodiment, the result information acquisition unit 326 acquires growth information indicating the growth state of the agricultural product 30. The result information acquisition unit 326 may acquire the growth information from the field data collection unit 224. In another embodiment, the result information acquisition unit 326 acquires quality information indicating the quality of the agricultural product 30. The result information acquisition unit 326 may acquire the quality information from the farming robot 120 via the communication network 10. In yet another embodiment, the result information acquisition unit 326 acquires mass information indicating the mass of the agricultural product 30. The result information acquisition unit 326 may acquire mass information from the farming robot 120 via the communication network 10.

  In the present embodiment, the work information generation unit 332 generates work information in which information indicating the position at which the work is performed and information indicating the content of the work are associated. The work information generation unit 332 includes (i) information indicating the position specified by the work position specification unit 310, (ii-1) information indicating the work content specified by the work content specification unit 322, and (ii-2) The work information may be generated in which at least one piece of information indicating the work content of the accompanying work identified by the accompanying work identification unit 324 is associated.

  For example, when the worker 12 carries out the spreading work, information indicating the spreading amount, information indicating the spreading direction, and the like can be illustrated as the information indicating the work content. In this case, the work information generation unit 332 may generate work information in which the information indicating the position at which the spreading work is performed, and the information indicating the spreading amount and / or the information indicating the spreading direction are associated with each other.

  In another embodiment, when the worker 12 performs a harvesting operation, (i) information indicating the position specified by the work position specifying unit 310, and (ii-1) quality information acquired by the result information acquiring unit 326, And (ii-2) harvest information in which at least one of the mass information acquired by the outcome information acquisition unit 326 is associated may be generated.

  FIG. 4 schematically shows an example of the internal configuration of the analysis unit 232. As shown in FIG. In the present embodiment, the analysis unit 232 includes a data analysis unit 410. In the present embodiment, the analysis unit 232 includes a condition determination unit 420 and a learning data generation unit 430. In the present embodiment, the learning data generation unit 430 includes a correction unit 432, a merge unit 434, an extraction unit 436, and a shaping unit 438. The respective units of the analysis unit 232 may send and receive information to each other without being limited by the direction of the arrow and the presence or absence of the arrow in the drawing.

  In the present embodiment, the data analysis unit 410 analyzes the information acquired or generated by at least one of the work data collection unit 222 and the field data collection unit 224. The data analysis unit 410 may store the analysis result in the storage unit 240. The data analysis unit 410 may transmit the analysis result to the correction unit 432. The data analysis unit 410 may transmit the analysis result to the work support unit 234.

  In one embodiment, the data analysis unit 410 performs multivariate analysis or sensitivity analysis using at least a part of data acquired or generated by at least one of the work data collection unit 222 and the field data collection unit 224. The analysis unit 232 may determine an explanatory variable having a large influence on the objective variable among the one or more explanatory variables related to the objective variable.

  The target variable may be any parameter related to produce 30. The objective variable can be exemplified by the growth state of the agricultural product 30, the quality of the harvest, the mass of the harvest, or the occurrence status of pests or a combination thereof. As the quality, color, shape, size, composition, content of specific components, hardness and the like can be exemplified.

  The explanatory variable may be any parameter related to work. As the explanatory variables, at least one of the type of work, the timing of the work, the strength of the work, the interval of the work, the frequency of the work, the precision of the work and the skill of the worker, and combinations thereof Can. The explanatory variable may be any parameter related to the produce 30 or the surrounding environment of the produce 30. As explanatory variables, types of agricultural products 30, parameters related to soil characteristics, parameters related to weather, and the like can be illustrated.

  In one embodiment, for at least one of the one or more explanatory variables, the analysis unit 232 indicates information (the degree of influence, the contribution rate, the influence function, etc.) indicating the magnitude of the influence of the explanatory variable on the target variable. There is a case to decide. In another embodiment, the analysis unit 232 determines, for at least one of the one or more explanatory variables, information (sometimes referred to as sensitivity) indicating how the objective variable changes with respect to the change of the explanatory variable. Do.

  The analysis unit 232 may determine an explanatory variable having a large influence on the objective variable among the one or more explanatory variables based on the magnitude or sensitivity of the above-mentioned influence. For example, when the magnitude or sensitivity of the above-mentioned influence on a specific explanatory variable satisfies a predetermined condition, the analysis unit 232 determines the specific explanatory function as an explanatory variable having a large influence on the objective variable. Do. Examples of the predetermined condition include a condition that it is larger than a predetermined threshold value, a condition that it falls within a predetermined range, and a condition that it does not fall within a predetermined range.

  The analysis unit 232 may collectively handle a plurality of pieces of work information related to the same type of work as a single work group. The analysis unit 232 may handle a plurality of pieces of work information related to the same type of work performed at the same position or area as a single work group. The area may be a plurality of fields, a single field, or part of a plurality or a single field. The analysis unit 232 may collectively handle a plurality of pieces of work information related to the same type of work performed in the same time zone at the same position or area, and handle the information as a single work group. The analysis unit 232 may select an arbitrary period of the day as the above-mentioned time zone. The analysis unit 232 may handle a plurality of pieces of work information related to the same type of work performed at the same position or area as a single work group at predetermined intervals. The predetermined period may be one day, one week, or one month. In this case, the analysis unit 232 may execute multivariate analysis or sensitivity analysis using any parameter related to the work group as an explanatory variable.

  The parameters relating to the work group include (a) statistics of work strength indicated by each of a plurality of work information constituting the work group, and (b) a work indicated by each of a plurality of work information constituting the work group The statistics of time can be illustrated. The parameter relating to the work group may be (c) a feature of a periodic pattern of work intensity indicated by each of a plurality of pieces of work information constituting the work group. As a feature of the periodic pattern, the period, amplitude, etc. of the pattern can be exemplified.

  The statistics of work strength include (i) representative values of work strength, (ii) indexes indicating the degree of dispersion or distribution of work strength, and (iii) dispersion or distribution of work strength due to differences in the position at which work is performed. (Iv) indicators of dispersion or distribution of work intensity due to differences in time zone or period during which work was performed, (v) work intensity is predetermined in a predetermined period It is possible to illustrate the number or frequency of exceeding a threshold or range. The variation or distribution of the work intensity due to the difference in the position where the work was performed may be the variation or distribution of the work intensity plotted along the movement path of the worker 12. An average value, a median value, etc. can be illustrated as said representative value. Standard deviation, a coefficient of variation, etc. can be illustrated as a parameter | index which shows the condition of said dispersion | distribution or distribution.

  The statistical value of the work time may be (i) a representative value of the time or time zone at which the work was performed, and (ii) an indicator indicating the degree of variation or distribution of the time or time zone at which the work was performed. it can. An average value, a median value, etc. can be illustrated as said representative value. Standard deviation, a coefficient of variation, etc. can be illustrated as a parameter | index which shows the condition of said dispersion | distribution or distribution.

  The analysis unit 232 may group together a plurality of pieces of task information related to a plurality of types of tasks, and handle the information as a single task group. In this case, the analysis unit 232 may execute multivariate analysis or sensitivity analysis using any parameter related to the work group as an explanatory variable. The analysis unit 232 may collectively handle a plurality of pieces of task information related to a plurality of types of tasks performed at the same position or area as a single task group. The analysis unit 232 may collectively handle a plurality of pieces of work information related to a plurality of types of work performed in the same time zone at the same position or area, and handle the information as a single work group. The analysis unit 232 may collectively handle a plurality of pieces of work information related to a plurality of types of work performed at the same position or area for each predetermined period, and handle the information as a single work group. The parameters for the work group may be as described above.

  In one embodiment, when the types of a plurality of tasks constituting the task group A are the same as the types of a plurality of tasks constituting the task group B, the order of the plurality of tasks constituting the task group A, When the order of the plurality of tasks constituting the task group B is different, the task group A and the task group B may be handled as different task groups. In another embodiment, in the case where the types of a plurality of tasks constituting task group A and the types of a plurality of tasks constituting task group B are the same, the order of the plurality of tasks constituting task group A and Even when the order of the plurality of tasks constituting task group B is different, task group A and task group B may be handled as the same task group.

  In another embodiment, the data analysis unit 410 may evaluate the work indicated by each of the plurality of work information. The data analysis unit 410 may evaluate the work indicated by each of the plurality of pieces of work information based on one or more pieces of result information. For example, each of the task information and the outcome information includes information indicating a position. Thus, the data analysis unit 410 extracts one or more pieces of work information corresponding to one or more pieces of result information from among the plurality of pieces of work information, using the information indicating the position as a key. Further, the data analysis unit 410 evaluates the extracted one or more pieces of work information according to the corresponding result information.

  In the present embodiment, the condition determination unit 420 determines the conditions for the learning data generation unit 430 to generate a learning data set. The condition determination unit 420 may determine the above condition based on the information indicating the purpose or use of the learned model generated by the work support unit 234. The condition determination unit 420 acquires, for example, from the input / output control unit 212, information indicating the use purpose or use of the learned model.

  In one embodiment, the condition determining unit 420 generates a condition indicating whether the data needs to be corrected and a condition indicating a target of the data correction process, and transmits the generated conditions to the correcting unit 432. In another embodiment, the condition determining unit 420 generates a condition indicating whether or not data needs to be merged, and a condition indicating the type of information to be merged, and transmits the generated condition to the merging unit 434. The types of information described above include (i) the type of information to be included in learning data for generating a field-specific learned model, and (ii) generating a learned model specific to the type of agricultural product 30. Type of information to be included in learning data for (iii) type of information to be included in learning data for generating a learned model specific to a field and type of agricultural products 30 grown in the field And (iv) the type of information to be included in the learning data for generating a general-purpose learned model that does not depend on the field and the type of agricultural products 30 grown in the field can be exemplified.

  In yet another embodiment, the condition determination unit 420 generates a condition for the extraction unit 436 to extract data, and transmits the generated condition to the extraction unit 436. For example, the objective of learning is to output the desired work content at the position or the desired work content at the relevant agricultural product, using the current and past conditions of the agricultural product 30 at its specific location and its surrounding environment and the goal for the agricultural product 30 as input. If it is to build a learned model for: (i) working information about experienced workers 12, (ii) working information when produce 30 of excellent quality is harvested, (iii) produce 30 The extraction condition is determined such that work information when the harvest amount of the crop 30 is good, and (iv) work information other than when the harvest amount of the agricultural product 30 is defective are extracted.

  The conditions for extracting the data may include the conditions for the worker 12, the conditions for the farming robot 120, the conditions for the agricultural product 30, and the conditions for the surrounding environment of the agricultural product 30. As conditions regarding the worker 12, conditions regarding the experience or proficiency level of a specific operation, conditions regarding the produce 30 grown by the worker 12, and the like can be exemplified. As the conditions relating to the agricultural work robot 120, conditions relating to the type of attachment, conditions relating to moving speed, conditions relating to work speed, conditions relating to frequency of use, and the like can be exemplified.

  The conditions relating to the position of the agricultural product 30 as the conditions relating to the agricultural product 30, the conditions relating to the method of cultivating the agricultural product 30 (organic cultivation, low agricultural chemical cultivation and the like can be exemplified as the method of cultivation) Conditions relating to work, conditions relating to the growth of agricultural products 30 (for example, growth rate, conditions of growth, etc.), conditions relating to the quality or mass of agricultural products 30, and the like can be exemplified. As the conditions related to the surrounding environment of the agricultural product 30, conditions related to the soil of the field where the agricultural product 30 is grown, conditions related to the weather during the growing period of the agricultural product 30, and the like can be exemplified.

  In the present embodiment, the learning data generation unit 430 generates a learning data set for machine learning or deep learning. The learning data generation unit 430 may generate a learning data set according to the use purpose or application of the learned model generated by the work support unit 234. For example, the learning data generation unit 430 is (i) a learning data set for generating a learned model specific to a field, (ii) a learning data set for generating a learned model specific to the type of the produce 30. A data set, (iii) a training data set for generating a learned model specific to the field and the type of agricultural products 30 grown in the field, and (iv) a field and the agricultural products 30 grown in the field Generate at least one training data set for generating a general-purpose trained model which is not dependent on type.

  In the present embodiment, the correction unit 432 corrects the information stored in the storage unit 240. For example, the correction unit 432 corrects the information in consideration of the influence of the difference in the field condition, the influence of the difference in the weather condition, the influence of the difference in the growth state, and the like on the information to be corrected. The correction unit 432 may correct the information stored in the storage unit 240 based on the analysis result of the data analysis unit 410.

  In one embodiment, the correction unit 432 corrects the information indicating the outcome included in the one or more outcome information, using the information indicating the degree of influence or the sensitivity calculated by the data analysis unit 410. In another embodiment, the correction unit 432 corrects the information indicating the growth state included in the one or more growth information, using the information indicating the degree of influence or the sensitivity calculated by the data analysis unit 410.

  Information in the correction unit 432 is an example in which the sensitivity in the case where the parameter relating to the characteristics of the soil is used as an explanatory variable and the parameter indicating the quality or mass of the harvested material is used as an objective variable by the analysis processing of the data analysis unit 410 An example of the process will be described more specifically. For example, the correction unit 432 generates, from the condition determination unit 420, result information indicating an amount of harvest when the ratio of humus is increased at a specific position based on the result information stored in the storage unit 240. Receive the order of

  The correction unit 432 refers to the storage unit 240 and extracts result information and soil information at a specific position. Further, the correction unit 432 acquires, from the data analysis unit 410, information on the sensitivity of the yield to the composition of the soil. Based on the information on the composition of the soil at the specific position and the information on the sensitivity of the yield to the composition of the soil, the amount of change in the yield when the composition of the soil is changed at the specific position is calculated.

  The correction unit 432 corrects the result information based on the above calculation result. In one embodiment, the correction unit 432 rewrites the result information stored in the storage unit 240 with the corrected result information. In another embodiment, the correction unit 432 stores the corrected result information in the storage unit 240 as information different from the original result information. In yet another embodiment, the correction unit 432 transmits the corrected result information to the merge unit 434.

  In the present embodiment, the merging unit 434 merges (may be referred to as merging) a plurality of pieces of information. For example, work information (may include information related to an attached work) stored in the storage unit 240, outcome information, soil information, weather information, and growth information include information indicating a position. Therefore, the merging unit 434 merges at least two of work information, outcome information, soil information, weather information, and growth information, using information indicating the position as a key. The merging unit 434 may merge the information corrected by the correcting unit 432 with other information.

  The merging unit 434 determines which information and which information to merge according to the conditions determined by the condition determining unit 420, for example. In one embodiment, when the learning data generation unit 430 generates learning data for generating a learned model specific to a field, the merging unit 434 does not have to merge soil information. On the other hand, when the learning data generation unit 430 generates learning data for generating a learned model specific to agricultural products or a general-purpose learned model, the merging unit 434 merges soil information.

  In the present embodiment, the extraction unit 436 extracts merge information that configures a learning data set from among a plurality of pieces of information (sometimes referred to as merge information) generated by the merge processing of the merge unit 434. For example, the extraction unit 436 extracts, from among the plurality of pieces of merge information, merge information that matches the condition determined by the condition determination unit 420 as merge information that configures the learning data set. The extraction unit 436 transmits the extracted one or more pieces of merge information to the shaping unit 438.

  In the present embodiment, the shaping unit 438 acquires one or more pieces of merge information extracted by the extraction unit 436. The shaping unit 438 arranges the data format of one or more pieces of merge information, and outputs it as a learning data set. For example, the formatter 438 deletes unnecessary data from each of the one or more pieces of merge information, and generates a learning data set.

  In the present embodiment, the merge unit 434 merges various data after the correction unit 432 corrects various data as needed. In addition, the extraction unit 436 extracts the data configuring the learning data set using the data merged by the merge unit 434. However, the method of generating the learning data set in the learning data generation unit 430 is not limited to this embodiment.

  In another embodiment, the merging unit 434 may merge the specific type of data extracted by the extracting unit 436 with other types of data. For example, first, the extraction unit 436 extracts outcome information indicating a specific outcome from among the plurality of outcome information stored in the storage unit 240. Each of the one or more outcome information extracted by the extraction unit 436 includes information indicating a position. Next, the extraction unit 436 extracts work information corresponding to each piece of result information from among the plurality of pieces of work information stored in the storage unit 240, using the information indicating the position as a key. Next, the merging unit 434 uses the information indicating the position as a key, one or more operation information extracted by the extracting unit 436, information indicating the characteristic of the soil included in the corresponding soil information, and the corresponding weather information. Merge with included weather data. Note that the extraction unit 436 does not extract outcome information indicating a specific outcome from among the plurality of outcome information stored in the storage unit 240, but instead, from among the plurality of growth information stored in the storage unit 240, Growth information indicating a specific growth state may be extracted.

  In still another embodiment, the learning data generation unit 430 may repeat the merging by the merging unit 434 and the extraction by the extraction unit 436 to generate a learning data set. In yet another embodiment, the correction unit 432 may correct data as needed after the merging unit 434 merges.

  FIG. 5 schematically shows an example of the internal configuration of the work support unit 234. As shown in FIG. In the present embodiment, the work support unit 234 includes a learning unit 510 and a work content determination unit 520. The work content determination unit 520 may be an example of the spread amount determination unit.

  In the present embodiment, the learning unit 510 generates a learned model according to a specific purpose by machine learning or deep learning. The learning unit 510 outputs a learned model, for example, using the learning data set generated by the analysis unit 232 as an input. The learning unit 510 may store the generated learned model in the model information storage unit 282.

  The learning unit 510 may generate a plurality of types of learned models having different purposes of use or usage according to the information included in the learning data set input to the learning unit 510. As a learned model, (i) a field-specific learned model, (ii) an agricultural-specific learned model, (iii) a field- and agricultural-specific learned model, (iv) not dependent on the field and agricultural products , A general purpose learned model etc. can be illustrated.

  In the present embodiment, the work content determination unit 520 uses the learned model generated by the learning unit 510 to support at least one of the work of the worker 12 and the agricultural work robot 120 (when referred to as support information) Output). The worker 12 may be an example of a second worker.

  For example, when the input / output control unit 212 receives a support request for requesting support information from at least one of the communication terminal 22, the agricultural work robot 120, and the distribution unit 150, the work content determination unit 520 generates the support information. Start. The input / output control unit 212 may obtain, for example, a goal related to a specific agricultural product 30 input by the worker 12 to the communication terminal 22, the farming robot 120, or the distribution unit 150. As a goal for the agricultural product 30, the growth state of the agricultural product 30 at a specific time, the quality of the harvest, the mass of the harvest, and the like can be exemplified.

  For example, the work content determination unit 520 refers to the storage unit 240 and acquires work information on a specific position. Thus, the work content determination unit 520 can acquire information on the history of the work performed on the specific agricultural product 30. For example, the work content determination unit 520 refers to the storage unit 240 and acquires soil information and weather information regarding a specific position. Thereby, the work content determination part 520 can acquire the information regarding the periphery environment of the specific agricultural product 30. For example, the work content determination unit 520 refers to the storage unit 240 to acquire growth information on a specific position. By this. The work content determination unit 520 can acquire information on the current growth state or growth history of a specific agricultural product 30.

  For example, the work content determination unit 520 refers to the model information storage unit 282 and acquires a learned model according to the content of the support request. The work content determination unit 520 may acquire an appropriate learning model based on the type of the input data. The work content determination unit 520 inputs the data input to the work content determination unit 520 into the learned model.

  In one embodiment, the work content determination unit 520 transmits, as support information, the data output from the learned model to the communication terminal 22 that has transmitted the support request, the farming robot 120, or the distribution unit 150. In another embodiment, the work content determination unit 520 corrects the data output from the learned model using the information indicating the degree of influence or the sensitivity calculated by the data analysis unit 410. The work content determination unit 520 transmits the corrected data as support information to the communication terminal 22 that has transmitted the support request, the farming robot 120, or the distribution unit 150. The communication terminal 22 or the farming robot 120 that has received the support information may transfer the support information to the distribution unit 150.

  For example, when the worker 12 carries out the spraying operation, the operation information includes information for specifying at least one of the position of the worker 12 in the field and the position of the spreading unit 150 in the field. Also, in this case, the work information includes information for specifying the amount of the substance that has already been sprayed at the above-mentioned position. In the work content determination unit 520, when the work information including the above information is input to the learned model, the amount of the substance to be dispersed from this is output at the position specified by the work information. At least one of the worker 12, the agricultural work robot 120, and the spraying unit 150 sprays the substance based on the spraying amount of the substance determined by the work content determination unit 520. Thereby, growth of agricultural products 30 can be controlled.

  FIG. 6 schematically illustrates an example of a data format of various information stored in the storage unit 240. In the present embodiment, the work information 652 is, for example, information associated with a field ID, a sub area ID, a work date, a worker ID, a work content, and a URI of data of an image obtained by capturing the state of the work. It is. Field ID and sub area ID may be an example of information which shows a position where work was carried out.

  In the present embodiment, the field ID may be identification information for identifying each of one or more fields. The sub area ID may be identification information for identifying each of one or more sub areas set in each field. In one embodiment, the sub-area ID may be identification information for identifying each of one or more strains grown in each field. In another embodiment, multiple strains may be grown within a single sub-area. The work information 652 may include information indicating coordinates of a position at which the work is performed, instead of or in addition to the sub area ID.

  The worker ID may be identification information for identifying the worker who has performed the work. The information indicating the work content includes, for example, information on the type of work, the strength of the work, the procedure of the work, the type of material used in the work, the type of equipment used in the work, and the work content of the accompanying work.

  In the present embodiment, the result information 654 includes, for example, field ID, sub area ID, date and time of harvest, kind of harvest, quality of harvest, mass of harvest (may be referred to as yield), and harvest. It is the information to which the URI of the data of the image in which the mode of the work was imaged was matched. In the result information 654, the quality of the harvest may be associated with the harvest amount for each quality of the harvest. As quality, a color, a shape, a magnitude | size, a composition, content of a specific component, etc. can be illustrated. The outcome information 654 may be an example of harvest information.

  In the present embodiment, the soil information 662 is, for example, information in which a field ID, a sub area ID, and a characteristic of the soil are associated with each other. As the characteristics of the soil, the composition of the soil, the condition of drainage, the condition of holding the fertilizer, the hardness, the content of the specific component, and the like can be exemplified. As said specific component, the substance which comprises soil, a fertilizer substance, an agrochemical substance etc. can be illustrated.

  In the present embodiment, the weather information 664 is, for example, information in which a field ID, a sub area ID, a date and time, and weather data are associated. As weather data, air temperature, water temperature, precipitation, wind direction, wind speed, sunshine time, temperature near produce 30, humidity near produce 30, illuminance near produce 30, etc. can be illustrated. The weather data may be past data or future forecast data. The date and time may be observation date and time or predicted date and time.

  In the present embodiment, the growth information 666 may be information indicating the growth state of the agricultural product 30. The growth information 666 includes, for example, the date and time when the agricultural product 30 was observed, the field ID and sub area ID in which the agricultural product 30 is grown, the type of agricultural product 30, the growth stage of agricultural product 30, the growth status of agricultural product 30, and It is the information to which the URI of the data of the image by which the mode was imaged was matched.

  In the present embodiment, the learning data 672 is, for example, information in which the type of agricultural product 30, the growth stage of agricultural product 30, the content of the operation performed for agricultural product 30, the state of the surrounding environment of agricultural product 30 are associated. is there. As the state of the surrounding environment of the agricultural product 30, weather data, characteristics of soil, etc. can be exemplified.

[Description of each part of the agricultural work robot 120]
FIG. 7 schematically illustrates an example of a system configuration of the farming robot 120. As described with reference to FIG. 1, in the present embodiment, the farming robot 120 includes a base unit 130, a moving unit 132, an imaging unit 134, a sensor unit 136, and a farming unit 138. Further, in the present embodiment, the farming robot 120 includes a control unit 720, a power supply unit 730, a vibration control unit 750, and a balance adjustment unit 780. The movement unit 132, the imaging unit 134, the sensor unit 136, the agricultural work unit 138, the vibration control unit 750, and the balance adjustment unit 780 may be an example of an attachment for agricultural work.

  In the present embodiment, the base unit 130 includes a control unit 720 and a power supply unit 730. The control unit 720 and the power supply unit 730 may be incorporated in the base unit 130. At least one of the control unit 720 and the power supply unit 730 may be detachably disposed on the base unit 130. In one embodiment, at least one of the control unit 720 and the power supply unit 730 is detachably disposed inside the base unit 130. In another embodiment, at least one of the control unit 720 and the power supply unit 730 is detachably disposed outside the base unit 130.

  In the present embodiment, the base unit 130 detachably holds at least one of the mobile unit 132, the farming unit 138, and the balancing unit 780. The base unit 130 may detachably hold at least one of the damping unit 750, the imaging unit 134, and the sensor unit 136.

  In the present embodiment, the control unit 720 controls the farming robot 120. In one embodiment, the control unit 720 communicates with each unit and controls the operation of the unit depending on the type of the unit. Control unit 720 may control the operation of one or more units depending on the combination of the plurality of units.

  For example, control unit 720 is in communication with at least one of mobile unit 132, farming unit 138, and balancing unit 780. The communication method may be wired communication or wireless communication. When the communication scheme between the control unit 720 and the other units is wired communication, the base unit 130 may be referred to as a communication path (a bus) for transmitting information between the control unit 720 and the other units. ) May be included. The above communication path may be an example of the communication unit.

  In another embodiment, the control unit 720 communicates with the management server 110 and transmits information about the farming robot 120 to the management server 110. For example, the control unit 720 acquires position information of the farming robot 120 and transmits the position information to the management server 110. According to another example, the control unit 720 associates the position information of the agricultural work robot 120 with the information acquired by the sensor unit 136 at the position indicated by the position information, and transmits the information to the management server 110.

  The position information may be any information indicating the position of the farming robot 120, and the content and the method of obtaining the position information are not particularly limited. The control unit 720 may identify the position of the farming robot 120 by any self-position estimation method. The control unit 720 may receive GPS signals and determine the position of the farming robot 120 based on the GPS signals. The control unit 720 may receive a beacon signal from a beacon transmitter installed around the farmland and specify the position of the farming robot 120 based on the beacon signal. The position of the farming robot 120 may be determined based on the radio wave intensity of the radio wave. The control unit 720 analyzes the image around the farming robot 120 captured by the imaging unit 134, and identifies the position of the farming robot 120 from the angles formed by the plurality of landmarks whose positions are known and the farming robot 120. It is also good.

  The control unit 720 may acquire information for controlling the farming robot 120 from the management server 110. The information for controlling the farming robot 120 may be information on a task to be performed by the farming robot 120 from now. The control unit 720 may control the operation of the unit related to the information based on the information acquired from the management server 110.

  In the present embodiment, the power supply unit 730 supplies power to drive at least one of the mobile unit 132, the farming unit 138, and the balancing unit 780. The base unit 130 power supply unit 730 may supply power to at least one of the damping unit 750, the imaging unit 134, and the sensor unit 136.

  In the present embodiment, the damping unit 750 controls the vibration. For example, the damping unit 750 controls at least one vibration of the imaging unit 134, the sensor unit 136, and the farming unit 138. The vibration control unit 750 may control the vibration in accordance with a command from the control unit 720. Damping unit 750 may have a power source generating power for driving damping unit 750 using the power supplied from power supply unit 730. As a power source, a motor, an actuator, etc. can be illustrated.

  In the present embodiment, the balance adjustment unit 780 has a weight. The balance adjustment unit 780 is detachably held by the base unit 130. Depending on the weight of the unit attached to the base unit 130 and the position of the center of gravity of the unit, the weight balance of the farming robot 120 is deteriorated, and the farming robot 120 becomes unstable. Therefore, by mounting the balance adjustment unit 780 at an appropriate position of the base unit 130, the weight balance of the farming robot 120 can be adjusted.

  The balance adjustment unit 780 may be a manipulator having a weight at its tip. The position of the center of gravity of the farming robot 120 can be changed by the manipulator changing the relative position of the weight and the base unit 130. The manipulator may be an example of a power source.

  In the present embodiment, the mobile unit 132 converts the power supplied from the power supply unit 730 into motive power and moves the agricultural robot 120. The mobile unit 132 may have a power source that generates power using the power supplied from the power source unit 730. As a power source, a motor, an actuator, etc. can be illustrated.

  In one embodiment, the mobile unit 132 includes a wheel for moving on land and a power source for driving the wheel. In another embodiment, the mobile unit 132 comprises an endless track for moving on land and a power source for driving the endless track. In still another embodiment, the transfer unit 132 may include a screw for moving on or in water and a power source for driving the screw. The moving unit 132 may further include a buoyancy material for obtaining buoyancy. In yet another embodiment, the mobile unit 132 may include a propeller for moving in the air and a power source for driving the propeller. The transfer unit 132 may further comprise a balloon or bladder for floating in the air.

  In the present embodiment, the imaging unit 134 images the periphery of the farming robot 120. Thereby, environmental information on the environment around the farming robot 120 can be acquired. The imaging unit 134 may be disposed forward of the base unit 130 in the direction of travel, or may be disposed rearward of the base unit 130 in the direction of travel. The imaging unit 134 may be disposed on the side of the farming robot 120. The imaging unit 134 may be disposed on the upper surface of the base unit 130 or may be disposed on the lower surface of the base unit 130. The farming robot 120 may include a plurality of imaging units 134. The imaging unit 134 may have a light that emits illumination light. The light may be an example of a lighting unit.

  The imaging unit 134 can preferably capture a moving image, and may be a visible light camera or an infrared camera. The imaging unit 134 may have a manipulator and an imaging device attached to the tip of the manipulator. The manipulator can use the power supplied from the power supply unit 730 to direct the imaging device in any direction. The manipulator may be an example of a power source.

  The sensor unit 136 acquires environmental information on the environment around the farming robot 120. Thereby, information on the growth environment of the agricultural product can be obtained. As environmental information, information on soil, information on air, information on light intensity, etc. can be exemplified. As information on soil, pH, temperature, moisture content, particle size distribution, hardness, and components contained in soil, bacteria and viruses can be exemplified. As a component contained in soil, organic substance (carbon), nitrogen, phosphorus, potassium, magnesium, calcium, sulfur, iron, manganese, boron, zinc, molybdenum, copper, chlorine, etc. can be illustrated. As information on the atmosphere, air temperature, pressure, humidity, carbon dioxide concentration, nitrogen concentration, oxygen concentration, wind direction and air volume can be exemplified.

  In one embodiment, the sensor unit 136 has a soil sensor that obtains information on the condition of the soil around the farming robot 120. Sensor unit 136 may have a plurality of soil sensors. As the soil sensor, (i) an optical sensor such as "N-sensor" manufactured by Yara Co., Ltd. (for example, a spectroscopic sensor for visible light region or near infrared light region), (ii) real time insertion into soil Various sensors (for example, electrical conductivity sensors) that analyze the components contained in the soil in real time, (iii) an extract obtained by adding water to the sampled soil to extract water-soluble components in the soil Various sensors to be analyzed can be illustrated. As analysis items of the above-mentioned extract, pH, calcium ion concentration, magnesium ion concentration, potassium ion concentration, nitrate ion concentration, nitrite ion concentration, phosphate ion concentration, sulfate ion concentration, chloride ion concentration, etc. are exemplified. be able to. The soil sensor may include a depth gauge, a soil cutting resistance sensor, and the like.

  In the present embodiment, the case where the imaging unit 134 and the sensor unit 136 are detachably disposed outside the base unit 130 has been described. However, in the imaging unit 134 and the sensor unit 136, the imaging unit 134 and the sensor unit 136 are not limited to this embodiment. In another embodiment, the imaging unit 134 and the sensor unit 136 may be disposed at the agricultural attachment. In still another embodiment, the imaging unit 134 and the sensor unit 136 may be incorporated into the control unit 720.

  In the present embodiment, the farming unit 138 is a unit specialized for one or more farming operations. As the agricultural work unit 138, a chemical solution spraying device for pest control, a fertilizer spraying device for spraying fertilizer, a gas spraying device for spraying gas, a setting device, a seedling dropping device, a seeding device, a tilling device, unnecessary branches and leaves are dispensable , A manipulator with a jig for picking produce, a manipulator with a jig for picking produce, a mowing apparatus (for example, a mowing apparatus for a field which has been left for a long time), a watering apparatus, a bird threat device (for example, voice, It is an apparatus that threatens birds and animals with light), thinning apparatus, flower thinning apparatus, fruit picking apparatus, bag hanging apparatus (for example, a bag hanging apparatus for fruit trees), and the like.

  In the present embodiment, the farming unit 138 is detachably held by the base unit 130. The farming unit 138 has a power source that generates power for driving the farming unit 138 using the power supplied from the power supply unit 730. As a power source, a motor, an actuator, etc. can be illustrated.

  FIG. 8 schematically illustrates an example of the spreading unit 150. In the present embodiment, the distribution unit 150 includes a housing 810, a tank 812, a distribution nozzle 814, and a pipe 816. In the present embodiment, the distribution unit 150 includes a transfer unit 822, a flow rate adjustment unit 824, a flow meter 826, and a controller 832. The controller 832 may be an example of a spread rate control unit.

  In the present embodiment, the tank 812 is disposed inside the housing 810 and stores the material to be sprayed. In the present embodiment, the spray nozzle 814 is disposed outside the housing 810 and sprays the substance. The spray nozzle 814 is connected to the tank 812 via a pipe 816. In the present embodiment, a transfer unit 822, a flow rate adjustment unit 824, and a flow meter 826 are disposed in a pipe 816 connecting the tank 812 and the distribution nozzle 814.

  The transfer unit 822 transfers the substance stored in the tank 812 toward the spray nozzle 814. A powder feeder, a blower, a pump etc. can be illustrated as the transfer part 822. The flow rate adjustment unit 824 adjusts the transfer amount of the substance. As the flow rate adjustment unit 824, an automatic valve, a flow rate adjustment valve, a combination thereof, and the like can be exemplified. The flow meter 826 measures the transfer amount of the substance.

  The controller 832 controls the transfer of substances. The controller 832 may control the transfer of material based on the measurements of the flow meter 826. The controller 832 may adjust the transfer amount of the substance based on the amount of the substance to be sprayed determined by the work content determination unit 520. The information indicating the amount of substance to be sprayed may be included in the support information from the management server 110, for example.

  More specifically, the controller 832 controls, for example, at least one of the transfer unit 822 and the flow rate adjustment unit 824 to adjust the transfer amount of the substance. Thereby, for example, even if the worker 12 appropriately shakes the spray nozzle, the appropriate amount of the substance according to the position is sprayed. In addition, even inexperienced workers 12 can ensure the same work quality as experienced workers 12.

  The controller 832 may send and receive information to and from the management server 110 via the communication network 10. For example, the controller 832 transmits the measurement value of the flow meter 826 to the management server 110. When the spreading unit 150 includes an imaging device, the controller 832 may transmit data of an image captured by the imaging device to the management server 110. The imaging device is disposed, for example, in the housing 810 or the spray nozzle 814. The controller 832 may receive the assistance information from the management server 110.

  FIG. 9 schematically illustrates an example of the accommodation unit 160. In the present embodiment, the housing unit 160 includes a housing 910, and a housing portion 922, a housing portion 924 and a housing portion 926 which are separated by the partition wall 912 and the partition wall 914. The containing unit 160 includes a mass scale 932, a mass scale 934, and a mass scale 936. Each of the mass scale 932, the mass scale 934, and the mass scale 936 measures the mass of the content accommodated in each of the accommodation portion 922, the accommodation portion 924, and the accommodation portion 926. Each of the mass scale 932, the mass scale 934, and the mass scale 936 may be an example of a quality information acquisition unit and a mass information acquisition unit.

  For example, the harvested produce 30 is accommodated in the accommodation portion 922, the accommodation portion 924, and the accommodation portion 926. In the present embodiment, each of the accommodation portion 922, the accommodation portion 924 and the accommodation portion 926 accommodates the produce 30 of different quality. Thus, by measuring the mass of the contents of each of the housing portion 922, the housing portion 924 and the housing portion 926, it is possible to specify what quality of produce 30 has been harvested and how much. Each of mass meter 932, mass meter 934 and mass meter 936 may transmit the measurement result to control unit 720. The control unit 720 may transmit the measurement results of each of the mass meter 932, the mass meter 934 and the mass meter 936 to the management server 110.

  In the present embodiment, the case where the operator 12 determines the quality based on vision has been described. However, the method of determining the quality is not limited to this embodiment. In another embodiment, the worker 12 may determine the quality based on the information of senses other than visual sense (for example, touch, hearing, smell, etc.). In yet another embodiment, the quality may be determined based on the measurement results of the measurement device.

  As mentioned above, although this invention was demonstrated using embodiment, the technical scope of this invention is not limited to the range as described in the said embodiment. It is apparent to those skilled in the art that various changes or modifications can be added to the above embodiment. Further, the matters described in the specific embodiment can be applied to the other embodiments as long as no technical contradiction arises. It is also apparent from the scope of the claims that the embodiments added with such alterations or improvements can be included in the technical scope of the present invention.

  The execution order of each process such as operations, procedures, steps, and steps in the apparatuses, systems, programs, and methods shown in the claims, the specification, and the drawings is particularly “before”, “preceding” It is to be noted that “it is not explicitly stated as“ etc. ”and can be realized in any order as long as the output of the previous process is not used in the later process. With regard to the flow of operations in the claims, the specification and the drawings, even if it is described using “first,” “next,” etc. for convenience, it means that it is essential to carry out in this order. It is not a thing.

For example, the following matters are described in the present specification.
[Item 1-1]
(I) The position in the said field of the worker who applies the spreading device which spreads the substance to the field which wears the spreading device which spreads the substance and grows one or more agricultural products, and (ii) the above-mentioned spreading which was mounted to the worker A scattering position specifying unit for specifying at least one of the positions of the device in the field;
A spray amount specifying unit that specifies the amount of the substance that has been sprayed at the position specified by the spray position specifying unit;
(A) Work information generation for generating work information associated with information indicating the position specified by the spreading position specifying unit and (b) information indicating the spreading amount of the substance specified by the spread amount specifying unit Department,
An information processing system comprising:
[Item 1-2]
A spraying direction identifying unit for identifying the spraying direction of the substance at a position identified by the spraying position identifying unit;
And further
The work information generation unit generates the work information associated with (a) information indicating the position specified by the spreading position specifying unit and (c) information indicating the direction specified by the spreading direction specifying unit. Do,
An information processing system according to item 1-1.
[Item 1-3]
At the position specified by the spraying position identifying unit, the attendant specifies an operation performed before or after spraying the substance in association with the spraying of the substance;
And further
The work information generation unit includes the work information associated with (a) information indicating the position specified by the scattering position specification unit, and (d) information indicating the work specified by the incidental work specification unit. Generate,
An information processing system according to item 1-1 or item 1-2.
[Item 1-4]
A teacher information generation unit that generates teacher information related to the work of dispersing the substance based on the work information about the one or more first workers generated by the work information generation unit;
Further comprising
An information processing system according to any one of items 1-1 to 1-3.
[Item 1-5]
A soil information acquisition unit that acquires soil information associated with the information indicating the position in the field and the information indicating the characteristic of the soil at the position;
And further
The teacher information generation unit generates the teacher information based on the soil information acquired by the soil information acquisition unit and the work information of the one or more first workers.
The information processing system according to Item 1-4.
[Item 1-6]
A growth information acquisition unit that acquires growth information associated with information indicating the position in the field and information indicating the growth state of the one or more agricultural products at the position;
And further
The teacher information generation unit generates the teacher information based on the growth information acquired by the growth information acquisition unit and the work information of the one or more first workers.
The information processing system according to Item 1-4 or Item 1-5.
[Item 1-7]
A harvest information acquisition unit that acquires harvest information associated with information indicating the position in the field and information on agricultural products harvested at the position,
And further
The teacher information generation unit generates the teacher information based on the harvest information acquired by the harvest information acquisition unit and the operation information of the one or more first workers.
The information processing system according to any one of items 1-4 to 1-6.
[Item 1-8]
The spray position specifying unit includes at least one of (i) a position in the field of the second worker who sprays the substance, and (ii) a position in the field of the spray device attached to the second worker. To identify
The spread amount specifying unit specifies the amount of the substance that has been spread at the position specified by the spread position specifying unit,
The above information processing system is
(I) the amount of the substance that has already been dispersed, specified by the spread amount specifying unit, and (ii) the above-described specified value of the spread position specifying unit based on the teacher information generated by the teacher information generation unit. An application rate determination unit for determining the amount of the substance to be applied at the position of the second worker,
Further comprising
The information processing system according to any one of items 1-4 to 1-7.
[Item 1-9]
The system further comprises a spread amount control unit that controls the spreader based on the amount of the substance to be spread determined by the spread amount determination unit.
The information processing system according to Item 1-8.
[Item 1-10]
An image data acquisition unit for acquiring data of an image obtained by capturing a state in which at least one of the worker and the spraying device is spraying the substance;
An imaging position acquisition unit that acquires information indicating a position when the imaging device that has captured the image captures the image;
And further
The scatter position identification unit
Analyzing the data acquired by the image data acquisition unit to determine a relative positional relationship between the imaging device and at least one of the worker and the scattering device;
At least one of the position of the worker in the field and the position of the spreading device in the field based on the position of the imaging device indicated by the information acquired by the imaging position acquisition unit and the relative positional relationship. To identify
The information processing system according to any one of items 1-1 to 1-9.
[Item 1-11]
A position specifying unit that specifies a position at which farming is performed in a field where one or more agricultural products are grown;
A content specifying unit for specifying the content of the agricultural work at the position specified by the position specifying unit;
(A) information indicating the position specified by the position specifying unit; and (b) a work information generating unit generating work information associated with information indicating the content of the agricultural work specified by the content specifying unit;
An information processing system comprising:
[Item 1-12]
A program for causing a computer to function as an information processing system according to any one of items 1-1 to 1-11.

For example, the following matters are described in the present specification.
[Item 2-1]
In a field where one or more agricultural products are grown, a harvest position identification unit that identifies the position where one agricultural product was harvested,
A quality information acquisition unit that acquires quality information indicating the quality of the above-mentioned agricultural product;
(A) information indicating the position specified by the harvest position identification unit; and (b) a harvest information generation unit that generates harvest information associated with the quality information acquired by the quality information acquisition unit;
An information processing system comprising:
[Item 2-2]
A mass information acquisition unit that acquires mass information indicating the mass of the one agricultural product,
And further
The harvest information generation unit acquires (a) information indicating the position specified by the harvest position identification unit, (b) the quality information acquired by the quality information acquisition unit, and (c) the mass information acquisition unit. Generate harvest information associated with the above-mentioned mass information,
The information processing system according to Item 2-1.
[Item 2-3]
A first image data acquisition unit for acquiring data of the image of the one agricultural product imaged before being harvested;
The data acquired by the first image data acquisition unit is analyzed, and (i) characteristics of the harvested area of the agricultural product, and (ii) the surrounding image of the harvested area, A feature information generation unit that generates feature information indicating at least one of the features of unharvested parts of agricultural products;
Further comprising
An information processing system according to item 2-1 or item 2-2.
[Item 2-4]
A training condition acquisition unit that acquires work information indicating a work history related to the one agricultural product;
An evaluation unit that evaluates at least a part of the work included in the work history based on the information acquired by the breeding condition acquisition unit and the harvest information generated by the harvest information generation unit;
Further comprising
The information processing system according to any one of items 2-1 to 2-3.
[Item 2-5]
The above-mentioned breeding condition acquisition unit further acquires weather information in at least a part of the growth period of the above-mentioned one agricultural product,
The information processing system according to Item 2-4.
[Item 2-6]
A second image data acquisition unit that acquires data of an image obtained by capturing an image of the harvest of the one agricultural product;
An imaging position acquisition unit that acquires information indicating a position when the imaging device that has captured the image captures the image;
And further
The harvest position identification unit
Analyzing the data acquired by the second image data acquisition unit to determine a relative positional relationship between the imaging device and the agricultural product;
The position where the one produce is harvested in the field is specified based on the position of the imaging device indicated by the information acquired by the imaging position acquisition unit and the relative positional relationship.
The information processing system according to any one of items 2-1 to 2-5.
[Item 2-7]
The imaging device is mounted on a mobile unit moving inside the field;
The mobile unit is
(A) a plurality of storage units for storing one or more agricultural products, each harvested;
(B) when the one agricultural product is accommodated in any of the plurality of accommodation units, the quality determining unit determines the quality of the one agricultural product according to the accommodation unit in which the one agricultural product is accommodated ,
(C) a transmitting unit for transmitting the quality information indicating the quality of the one agricultural product determined by the quality determining unit to the quality information acquiring unit;
Have
The quality information acquisition unit acquires the quality information from the mobile body via a communication network.
An information processing system according to item 2-6.
[Item 2-8]
The movable body further includes (d) at least one mass measuring unit that measures the mass of the container contained in at least one of the plurality of containers.
The transmission unit transmits the mass information indicating the mass of the one agricultural product measured by the at least one mass measurement unit to the mass information acquisition unit.
The mass information acquisition unit acquires the mass information from the mobile body via a communication network.
An information processing system according to Item 2-7.
[Item 2-9]
The movable body is moved to be positioned behind the worker in the traveling direction of the worker who harvests the one agricultural product.
The information processing system according to Item 2-7 or Item 2-8.
[Item 2-10]
The movable body moves so as to be located in front of the worker in the traveling direction of the worker who harvests the one agricultural product.
The information processing system according to Item 2-7 or Item 2-8.
[Item 2-11]
A program for causing a computer to function as the information processing system according to any one of Items 2-1 to 2-10.
[Item 2-12]
A mobile having an autonomous mobile function,
(A) a plurality of storage units for storing one or more agricultural products, each harvested;
(B) a quality determination unit that determines the quality of the one agricultural product according to the accommodation unit in which the one agricultural product is accommodated, when the one agricultural product is accommodated in any of the plurality of containers;
(C) a transmitting unit for transmitting the quality information indicating the quality of the one agricultural product determined by the quality determining unit to an external information processing apparatus;
With a mobile.

  10 communication network, 12 workers, 22 communication terminals, 30 agricultural products, 100 agricultural work support system, 110 management server, 120 agricultural work robots, 130 base units, 132 mobile units, 134 imaging units, 136 sensor units, 138 agricultural work units, 150 spraying Unit, 160 accommodation unit, 212 input / output control unit, 222 operation data collection unit, 224 field data collection unit, 232 analysis unit, 234 operation support unit, 240 storage unit, 252 operation information storage unit, 254 result information storage unit, 262 Soil information storage unit, 264 weather information storage unit, 266 growth information storage unit, 282 model information storage unit, 310 work position identification unit, 312 image data acquisition unit, 314 imaging position identification unit, 316 relative position identification unit, 318 absolute position Fixed part, 322 Work content specification part, 324 Accompanying work specification part, 326 Result information acquisition part, 332 Work information generation part, 410 Data analysis part, 420 Condition determination part, 430 Learning data generation part, 432 Correction part, 434 Merge Department, 436 Extraction Department, 438 Shaping Department, 510 Learning Department, 520 Work Content Determination Department, 652 Work Information, 654 Achievement Information, 662 Soil Information, 664 Weather Information, 666 Growth Information, 672 Learning Data, 720 Control Unit, 730 Power supply unit, 750 vibration control unit, 780 balance adjustment unit, 810 housing, 812 tank, 814 dispersion nozzle, 816 piping, 822 transfer unit, 824 flow control unit, 826 flow meter, 832 controller, 910 housing, 912 partition, 914 partition , 922 housing unit, 924 Housing, 926 Housing, 932 Mass, 934 Mass, 936 Mass

Claims (12)

(I) The position in the said field of the worker who applies the spreading device which spreads the substance to the field which wears the spreading device which spreads the substance, and grows one or more agricultural products, and (ii) the spreading which is mounted on the worker A scattering position specifying unit for specifying at least one of the positions of the device in the field;
A spread amount specifying unit that specifies the amount of the substance that has been sprayed at the position specified by the spread position specifying unit;
(A) Information indicating the position specified by the spread position specifying unit, and (b) Work information generation to generate work information associated with information indicating the spread amount of the substance specified by the spread amount specifying unit Department,
An information processing system comprising: A spraying direction identifying unit for identifying the spraying direction of the substance at a position identified by the spraying position identifying unit;
And further
The work information generation unit generates the work information associated with (a) information indicating the position specified by the scattering position specifying unit, and (c) information indicating the direction specified by the spreading direction specifying unit. Do,
The information processing system according to claim 1. An accompanying work specifying unit for specifying an operation performed by the worker before or during the application of the substance in association with the application of the substance at the position specified by the application position specifying part;
And further
The work information generation unit includes (a) information indicating a position specified by the scattering position specification unit, and (d) the work information associated with information indicating the work specified by the accompanying work specification unit. Generate,
The information processing system according to claim 1 or 2. A teacher information generation unit that generates teacher information related to the work of dispersing the substance based on the work information about the one or more first workers generated by the work information generation unit;
Further comprising
The information processing system according to any one of claims 1 to 3. A soil information acquisition unit that acquires soil information associated with information indicating a position in the field and information indicating a characteristic of soil at the position;
And further
The teacher information generation unit generates the teacher information based on the soil information acquired by the soil information acquisition unit and the work information of the one or more first workers.
The information processing system according to claim 4. A growth information acquisition unit that acquires growth information associated with information indicating a position in the field and information indicating a growth state of the one or more agricultural products at the position;
And further
The teacher information generation unit generates the teacher information based on the growth information acquired by the growth information acquisition unit and the work information of the one or more first workers.
The information processing system according to claim 4 or 5. A harvest information acquisition unit that acquires harvest information associated with information indicating a position in the field and information on agricultural products harvested at the position;
And further
The teacher information generation unit generates the teacher information based on the harvest information acquired by the harvest information acquisition unit and the work information of the one or more first workers.
The information processing system according to any one of claims 4 to 6. The spray position specifying unit is at least one of (i) a position in the field of a second worker who sprays the substance, and (ii) a position in the field of the spray device attached to the second worker. To identify
The spread amount specifying unit specifies the amount of the substance that has already been spread at the position specified by the spread position specifying unit;
The information processing system is
(I) the amount of the substance that has already been dispersed specified by the spread amount specifying unit; and (ii) the specified portion of the spread position specified unit based on the teacher information generated by the teacher information generation unit. An application rate determination unit for determining the amount of said substance to be applied at the second worker's location,
Further comprising
The information processing system according to any one of claims 4 to 7. The system further includes a spread rate control unit that controls the spreader based on the amount of the substance to be spread determined by the spread rate determination unit.
The information processing system according to claim 8. An image data acquisition unit configured to acquire data of an image obtained by capturing a state in which at least one of the worker and the spraying device is spraying the substance;
An imaging position acquisition unit that acquires information indicating a position when an imaging device that has captured the image captures the image;
And further
The scattering position identification unit
Analyzing the data acquired by the image data acquisition unit to determine a relative positional relationship between the imaging device and at least one of the worker and the scattering device;
At least one of the position of the worker in the field and the position of the spreader in the field based on the position of the imaging device indicated by the information acquired by the imaging position acquisition unit and the relative positional relationship. To identify
The information processing system according to any one of claims 1 to 9. A position specifying unit that specifies a position at which farming is performed in a field where one or more agricultural products are grown;
A content specifying unit for specifying the content of the agricultural work at the position specified by the position specifying unit;
(A) information indicating the position specified by the position specifying unit; and (b) a work information generating unit generating work information associated with information indicating the content of the agricultural work specified by the content specifying unit;
An information processing system comprising:   A program for causing a computer to function as the information processing system according to any one of claims 1 to 11.