JP2022075389A - Information processing apparatus, information processing method and program - Google Patents

Abstract

To provide an information processing apparatus, an information processing method and a program that can provide a variety of services for supporting agricultural work to an operator.SOLUTION: In an agricultural work support system in which an agricultural work management server, a weather information management server, a know-how management server, a matching service management server, one or more communication terminals, one or more imaging devices, one or more measurement devices, and one or more agricultural work robots are connected through a network, an agricultural work management server 142 comprises: an input reception unit 310; a screen generation unit 320; a work plan generation unit 330; and a storage unit 340. The storage unit 340 comprises: a log data storage unit 352; a standard data storage unit 354; a work recording storage unit 362; a growth recording storage unit 364; a harvest recording storage unit 366; a shipment recording storage unit 368; a setting data storage unit 372; and an evaluation data storage unit 374.SELECTED DRAWING: Figure 3

Description

The present invention relates to an information processing apparatus, an information processing method and a program.

Patent Document 1 discloses an agricultural support system provided with a production know-how database that stores information on agricultural product production know-how.
[Prior Art Document]
[Patent Document]
[Patent Document 1] Japanese Unexamined Patent Publication No. 2007-072787

In the first aspect of the present invention, an information processing apparatus is provided. The information processing apparatus described above includes, for example, a tracking information acquisition unit that acquires information indicating at least one of a speed, an acceleration, and an angular acceleration of a moving body that moves following the worker performing the work. The information processing apparatus described above includes, for example, a tracking abnormality detecting unit that detects at least one abnormality of speed, acceleration, and angular acceleration acquired by the tracking information acquisition unit. The information processing apparatus described above includes, for example, a question generation unit that generates a question regarding an abnormality when the tracking abnormality detection unit detects at least one abnormality of velocity, acceleration, and angular acceleration.

The above information processing device may include a cause estimation unit for estimating the cause of the abnormality. In the above information processing apparatus, the question generation unit may determine the content of the question based on the cause estimated by the cause estimation unit. The above-mentioned information processing device may include an action information collecting unit that acquires information indicating the contents of actions taken by the worker in order to deal with the cause. The above information processing device includes a coping information generation unit that generates coping information in which information indicating the content of the behavior acquired by the behavior information collecting unit and information indicating the cause estimated by the cause estimation unit are associated with each other. good.

In the above information processing device, the question generation unit may generate a question for asking the worker why the worker has selected an action. As the information indicating the cause estimated by the cause estimation unit, the response information generation unit receives the response information including the information indicating the content of the answer to the question, or (ii) the content of the action acquired by the behavior information collection unit. It is possible to generate coping information in which the information shown, the information indicating the cause estimated by the cause estimation unit, and the information indicating the content of the answer to the question are associated with each other.

In the above information processing apparatus, the cause estimation unit may have an object determination unit that determines whether or not the abnormality is caused by the first object that is the object of the worker's work. In the above information processing apparatus, the question generation unit may determine the content of the question based on whether or not the abnormality is caused by the first object. In the above information processing apparatus, the object determination unit may acquire voice data in which the voice of the worker is recorded. The object determination unit may analyze the worker's voice recorded in the voice data. The object determination unit may estimate (i) the event that causes the abnormality and (ii) the participants involved in the event.

In the above information processing apparatus, the cause estimation unit may acquire information on the work of another worker who has performed the same or similar work as the worker before the time when the abnormality is detected. In the above information processing apparatus, the cause estimation unit may estimate the cause of the abnormality based on the work contents of other workers. In the above information processing apparatus, the work of other workers is extracted from the work performed at a position where the distance from the worker's position at the time when an abnormality is detected is smaller than a predetermined value. good. In the above information processing apparatus, the question generation unit may generate a question when the position of the worker is included in a predetermined geographical range. The question generator does not have to generate the question if the worker's location is not within the geographical range.

In the second aspect of the present invention, an information processing method is provided. The information processing method described above includes, for example, a tracking information acquisition step of acquiring information indicating at least one of a speed, an acceleration, and an angular acceleration of a moving body that moves following the worker performing the work. The above information processing method has, for example, a tracking abnormality detecting step of detecting at least one abnormality of velocity, acceleration, and angular acceleration acquired in the tracking information acquisition step. The above information processing method has, for example, a question generation step of generating a question about anomalies when at least one anomaly of velocity, acceleration and angular acceleration is detected in the follow-up anomaly detection step.

In the third aspect of the invention, the program is provided. The above program may be a program for causing the computer to function as the information processing apparatus according to the first embodiment. The above program may be a program for causing a computer to execute the information processing method according to the second embodiment. A computer-readable medium for storing the above program may be provided. The computer-readable medium may be a non-temporary computer-readable medium. The computer-readable medium may be a computer-readable recording medium.

The outline of the above invention does not list all the necessary features of the present invention. A subcombination of these feature groups can also be an invention.

An example of the system configuration of the agricultural work support system 100 is shown schematically. An example of the internal configuration of the agricultural work robot 120 is schematically shown. An example of the internal configuration of the agricultural work management server 142 is schematically shown. An example of the internal configuration of the know-how management server 146 is schematically shown. An example of the data table 500 is shown schematically. An example of the flowchart 600 is shown schematically. An example of the internal configuration of the know-how data generation unit 440 is schematically shown. An example of the internal configuration of the question unit 770 is shown schematically. An example of the internal configuration of the question generation unit 830 is shown schematically. An example of the system configuration of the computer 3000 is shown schematically.

Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention to which the claims are made. Also, not all combinations of features described in the embodiments are essential to the means of solving the invention. In the drawings, the same or similar parts may be given the same reference number to omit duplicate explanations.

[Overview of Agricultural Work Support System 100]
FIG. 1 schematically shows an example of the system configuration of the agricultural work support system 100. In the present embodiment, the agricultural work support system 100 includes, for example, one or more communication terminals 102, one or more imaging devices 114, one or more measuring devices 116, and one or more agricultural work robots 120. In the present embodiment, the agricultural work support system 100 includes, for example, an agricultural work management server 142, a weather information management server 144, a know-how management server 146, and a matching service management server 148.

In the present embodiment, the details of the agricultural work support system 100 will be described by taking as an example the case where the agricultural product 22 is cultivated in the field 20. Examples of the agricultural product 22 include cereals, vegetables, fruits, tea, mushrooms, hyphae and the like.

In this embodiment, the agricultural product 22 is cultivated by the worker 40. The worker 40 may be a natural person, a corporation, or a group. For example, the worker 40 uses the farm work robot 120 to produce the agricultural product 22. The worker 40 can send and receive information to and from each part of the agricultural work support system 100 via the communication network 10 by using the communication terminal 102.

In this embodiment, the agricultural product 22 is consumed by the consumer 50. The consumer 50 may be a natural person, a corporation, or a group. The consumer 50 can use the communication terminal 102 to send and receive information to and from each part of the agricultural work support system 100 via the communication network 10.

In the present embodiment, the agricultural work support system 100 provides the worker 40 with various services for supporting the agricultural work. In one embodiment, the agricultural work support system 100 supports the creation of a work plan (sometimes referred to as a work schedule, process plan, etc.). In another embodiment, the agricultural work support system 100 supports the management of the work history of the worker 40. For example, the agricultural work support system 100 supports the creation of work records, growth records, harvest records and / or shipping records. In another embodiment, the agricultural work support system 100 mediates the transaction of materials between each of one or more workers 40 and each of one or more material providers (not shown).

In yet another embodiment, the agricultural work support system 100 supports the management of know-how regarding agricultural work. For example, the agricultural work support system 100 supports the collection and organization of know-how. The agricultural work support system 100 may store the collected know-how as data in a format that can be presented to the worker 40 as a flowchart. The farm work support system 100 may store the collected know-how as data in a format that can be executed by the farm work robot 120. In another embodiment, the agricultural work support system 100 supports the search and / or sharing of know-how. The farm work support system 100 may transmit data of know-how according to the situation of the farm work robot 120 to the farm work robot 120.

[Overview of each part related to the agricultural work support system 100]
In the present embodiment, the communication network 10 may be a transmission line for wired communication, a transmission line for wireless communication, or a combination of a transmission line for wireless communication and a transmission line for wired communication. .. 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 phone network, and (ii) a wireless MAN (eg, WiMAX®), a wireless LAN (eg, WiFi (registered trademark)). ), Bluetooth®, Zigbee®, NFC (Near Field Communication) and other wireless communication networks may be included. Wireless LAN, Bluetooth®, Zigbee®, and NFC may be examples of short-range wireless communication.

In the present embodiment, the communication terminal 102 transmits / receives information to / from each part of the agricultural work support system 100 via the communication network 10. Examples of the communication terminal 102 include a personal computer and a mobile terminal. Examples of the mobile terminal include a mobile phone, a smartphone, a PDA, a tablet, a notebook computer or a laptop computer, a wearable computer, and the like.

The communication terminal 102 may function as a user interface when the worker 40 or the consumer 50 accesses the agricultural work support system 100. The communication terminal 102 may be used for user authentication processing by the agricultural work support system 100.

The communication terminal 102 may send and receive information to and from the agricultural work robot 120 via the communication network 10. The communication terminal 102 may function as a user interface when the worker 40 operates the farm work robot 120. The communication terminal 102 may be used for user authentication processing by the agricultural work robot 120.

The communication terminal 102 includes, for example, a communication device, an input device, an output device, a self-position estimation device, a line-of-sight detection device, and the like. 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, and an image recognition device. The image input device may capture a still image or may capture a moving image. The image input device may record images and sounds. Examples of the output device include a display, a projector, a speaker, an ultrasonic output device, a vibration output device, a printer, and the like. Examples of the self-position estimation device include a GPS signal receiver, an acceleration sensor, and an angular acceleration sensor.

In the present embodiment, the imaging device 114 is installed at an arbitrary position in the field 20. The image pickup device 114 is preferably arranged at a position where the agricultural product 22 can be imaged. The image pickup apparatus 114 captures, for example, (i) the voice of the worker 40 performing the work, and (ii) at least one of the state of the work by the worker 40. The appearance of the work by the worker 40 includes (i) the appearance of the worker 40, (ii) the appearance of the field 20 or the agricultural product 22 to be worked, and (ii) the appearance of birds and beasts, pests, weeds, etc. to be worked. Is exemplified. The image data of the image captured by the image pickup device 114 is transmitted to the agricultural work support system 100 via the communication network 10. As described above, the image data may be data in which an image with sound is recorded.

In the present embodiment, the measuring instrument 116 is installed at an arbitrary position in the field 20. The measuring device 116 is preferably arranged in the vicinity of the agricultural product 22. The measuring device 116 measures, for example, the state of the surrounding environment of the agricultural product 22. The surrounding environment of the agricultural product 22 includes (i) the water content of the medium in the vicinity of the cultivation position of the agricultural product 22, (ii) the amount of pesticide component, fertilizer component or trace element contained in the medium, and (iii) the medium. (Iv) Temperature, humidity, wind speed, illuminance, amount of sunshine or amount of rain in the vicinity of the cultivation position of the agricultural product 22 are exemplified. The measurement data showing the measurement result of the measuring device 116 is transmitted to the agricultural work support system 100 via the communication network 10.

In the present embodiment, the agricultural work robot 120 includes, for example, a base unit 130 and various units (sometimes referred to as attachments) used by being attached to the base unit 130. For example, in the present embodiment, the agricultural work robot 120 includes one or more mobile units 132, one or more sensor units 136, and one or more agricultural work units 138.

The agricultural work robot 120 can send and receive information to and from each part of the agricultural work support system 100 via the communication network 10. The agricultural work robot 120 has an autonomous movement function. For example, the agricultural work robot 120 moves following the worker 40. Details of the agricultural work robot 120 will be described later.

In the present embodiment, the farm work management server 142 manages farm work performed by one or more workers 40. The farm work management server 142 may manage the farm work for each worker 40, may manage the farm work for each field 20, or may manage the farm work for each farm product 22. In one embodiment, the agricultural work management server 142 manages the work plan. In another embodiment, the agricultural work support system 100 manages the work history. For example, the agricultural work management server 142 manages work records, growth records, harvest records and / or shipping records. Details of the agricultural work management server 142 will be described later.

In the present embodiment, the weather information management server 144 manages the weather information. The weather information management server 144 stores, for example, the information indicating the date and time, the information indicating the position, the date and time, and the weather information at the position in association with each other. Examples of the meteorological information include information showing actual values of past meteorological conditions and information showing predicted values of future meteorological conditions. The weather information management server 144 receives, for example, (i) a search request from the agricultural work management server 142 or the know-how management server 146, and (ii) the position indicated by the request at the date and time or period indicated by the search request. Alternatively, the weather information of the area is extracted, and (iii) the extracted information is transmitted to the sender of the request.

In the present embodiment, the know-how management server 146 manages know-how related to agricultural work. The agricultural work management server 142 may manage the know-how for each worker 40, or may share the know-how among a plurality of pre-registered workers 40. The farm work management server 142 may manage know-how for each field 20 or may manage know-how for each region. The agricultural work management server 142 may manage know-how for each type of agricultural product 22 (sometimes referred to as an item). Details of the know-how management server 146 will be described later.

In this embodiment, the matching service management server 148 mediates the transaction of materials between each of one or more workers 40 and each of one or more material providers (not shown). The matching service management server 148 may mediate a transfer contract or a lease contract. Examples of materials include pesticides, fertilizers, packaging supplies, agricultural supplies (sheets, stakes, irrigation supplies, seedling raising pots, etc.), sensors, equipment that operates in conjunction with sensors, agricultural machinery, attachments for agricultural work robots 120, and the like. Will be done.

[Example of function of matching service management server 148]
For example, in the matching service management server 148, information on a material provider who can provide the material is registered for each type of material. Examples of the method of providing materials include sales, lending, and leasing. The matching service management server 148 provides various services by using the information of the material provider registered in the matching service management server 148. The matching service management server 148 may provide various services by using the information regarding the demand for materials provided by the farm work management server 142 and / or the know-how management server 146.

For example, the matching service management server 148 may access the farm work management server 142 and / or the know-how management server 146 to use information indicating demand for a particular type of material and / or a particular type of material. Get information about the high-ranking worker 40. The type of the above-mentioned material may be determined based on the request from the specific worker 40, or may be determined based on the demand situation of each material.

For example, the matching service management server 148 accesses the farm work management server 142 and / or the know-how management server 146 to indicate the type of material whose expected or estimated demand in a specific period is larger than a predetermined value. Get information. The predicted value or estimated value described above is determined based on, for example, a work plan of one or more workers 40. The above predicted value or estimated value may be determined based on the work plan of one or more workers 40 and the know-how data on one or more kinds of agricultural products 22 cultivated by one or more workers 40.

The matching service management server 148 searches for information registered in the matching service management server 148, and extracts one or more material providers capable of providing the above-mentioned types of materials. The matching service management server 148 may include (i) information indicating demand for a particular type of material, (ii) information about a worker 40 who is likely to use a particular type of material, and (iii) a particular type. Various information distribution services are provided by using one or more material providers who can provide the materials of.

In one embodiment, the matching service management server 148 may use the extracted material provider with information about the demand for the particular type of material and / or the particular type of material described above. Notify information about the high-ranking worker 40. The above-mentioned information on the demand for materials may be information indicating the demand amount for each period, may be information indicating the demand amount for each region, and may be information indicating the demand amount for each period and region. May be good. The information regarding the demand for the material may include information regarding the specifications or quality of the material, and may include information regarding the price or price range of the material. The information about the worker 40 includes (i) anonymized identification information of the worker 40, (ii) at least a part of the name, name, abbreviation or nickname of the worker 40, and (iii) the field 20 of the worker 40. Examples include the area where the worker 40 exists, (iv) the specifications or quality desired for the material by the worker 40, (v) the amount of the material desired by the worker 40, (vi) the price of the material desired by the worker 40, and the like. Will be done.

In another embodiment, the matching service management server 148 provides information about the extracted material provider to the worker 40 who is likely to use the particular material described above. Information about the material provider includes (i) anonymized material provider identification information, (ii) at least part of the material provider's name, name, abbreviation or nickname, and (iii) the material provider. Region to ship, (iv) specifications or quality of materials provided by the material provider, (v) quantity of materials available by the material provider, (vi) price of materials available by the material provider, (vii). An example is when a material provider can provide materials.

[Other examples of matching service management server 148 functions]
In the above embodiment, the matching service management server 148 distributes information based on the demand amount of each material. However, the matching service management server 148 is not limited to the above embodiment. In another embodiment, the matching service management server 148 distributes information based on the content of the demand for each material. For example, the matching service management server 148 distributes information regarding the content of the demand for each material to the material provider. The matching service management server 148 may (i) deliver information that matches the request in response to a request from a specific material provider, and (ii) at a predetermined timing of each material provider. Information that matches the situation may be delivered.

Examples of the content of the demand for each material include the usage mode of each material, the state of the worker 40 using each material, and the request of the worker 40 using each material for the material. Examples of the usage mode of each material include the situation in which each material is used, the amount used per time, and the usage time per time. Examples of the situation in which each material is used include the state of the field 20 in which each material is used, the meteorological environment in which each material is used, and the like. Examples of the state of the worker 40 include the movement of the worker 40 during work, the line of sight, and the like. The matching service management server 148 may request (i) a worker 40 who uses each material to send a request for the material, and (ii) a state of the worker 40 who uses each material. The above-mentioned request may be extracted or determined by analyzing the image captured by the user or the voice of the worker 40 who uses each material.

For example, the matching service management server 148 may access the farm work management server 142 and / or the know-how management server 146 to (i) information indicating the usage mode of a specific type of material, and (ii) a specific type of material. Acquire at least one of the information indicating the state of the worker 40 who uses the material. The matching service management server 148 may store information acquired from the farm work management server 142 and / or the know-how management server 146 in an appropriate storage device.

Further, the material provider accesses the matching service management server 148 by using the communication terminal 102, and requests information indicating the usage mode of the desired type of material and / or the state of the worker who uses the material. Upon receiving the above request, the matching service management server 148 extracts information indicating the usage mode of the material and / or the state of the worker who uses the material for the material of the type indicated by the above request. .. The matching service management server 148 transmits the extracted information to the communication terminal 102 used by the material provider.

As a result, the material provider can acquire information indicating what kind of environment and how the above materials are used. As a result, the material provider can improve the above materials or develop new materials.

The procedure in which the matching service management server 148 provides information indicating the usage mode of the material and / or the state of the worker who uses the material is not limited to the above procedure. In another embodiment, when the matching service management server 148 receives the above request from the communication terminal 102 used by the material provider, the matching service management server 148 accesses the agricultural work management server 142 and / or the know-how management server 146. Then, at least one of (i) information indicating the usage mode of the type of material indicated by the above request and (ii) information indicating the state of the worker 40 using the material may be acquired.

[Specific configuration of each part of the agricultural work support system 100]
Each part of the 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 part 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 part of the agricultural work support system 100 may be realized on a virtual machine or a cloud system. At least a part of each part of the agricultural work support system 100 may be realized by a personal computer or a mobile terminal. Examples of the mobile terminal include a mobile phone, a smartphone, a PDA, a tablet, a notebook computer or a laptop computer, a wearable computer, and the like. Each part of the agricultural work support system 100 may store information by using a distributed ledger technique such as a blockchain 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 the operation related to the components in an information processing device having a general configuration. It may be realized by starting the software or program. The information processing device having the above general configuration includes (i) a data processing device having a processor such as a CPU and GPU, a ROM, a RAM, and a communication interface, and (ii) a keyboard, a pointing device, a touch panel, a camera, and voice input. Input devices such as devices, gesture input devices, various sensors, GPS receivers, output devices such as (iii) display devices, audio output devices, vibration devices, and storage devices such as (iv) memory, HDD, SSD (external). It may include a storage device).

In the information processing device having the above general configuration, the data processing device or the storage device may store the software or the program. The software or program described above causes the information processing apparatus described above to execute the operation specified by the software or program by being executed by the processor. The software or program described above may be stored on a non-temporary computer-readable recording medium. The above software or program may be a program for making a computer function as a farm work support system 100 or a part thereof. The above software or program may be a program for causing a computer to execute an information processing method in the agricultural work support system 100 or a part thereof.

The above information processing method may be an information processing method executed by the know-how management server 146. The above information processing method is based on, for example, (i) the voice of the worker performing the work and (ii) at least one of the state of the work by the worker, during the work implementation period. It has an action estimation stage that estimates one or more actions performed. The above information processing method is, for example, (i) the voice of the worker, (ii) the state of the work, (iii) the matters input in the work record of the work, and (iv) at least the state of the work environment of the work. Based on one, it has a standard estimation stage that estimates a condition that is a criterion for determining whether or not an action should be executed.

The above-mentioned information processing method has, for example, a vital information acquisition step of acquiring information indicating a vital sign of a worker who performs a work. The above information processing method has, for example, a vital abnormality detection stage for detecting an abnormality in vital signs acquired in the vital information acquisition stage. The above information processing method has, for example, a question generation step of generating a question regarding an abnormality when an abnormality of vital signs is detected in the vital abnormality detection step.

The information processing method described above includes, for example, a tracking information acquisition step of acquiring information indicating at least one of a speed, an acceleration, and an angular acceleration of a moving body that moves following the worker performing the work. The above information processing method has, for example, a tracking abnormality detecting step of detecting at least one abnormality of velocity, acceleration, and angular acceleration acquired in the tracking information acquisition step. The above information processing method has, for example, a question generation step of generating a question about anomalies when at least one anomaly of velocity, acceleration and angular acceleration is detected in the follow-up anomaly detection step.

The agricultural work support system 100 may be an example of an information processing device. The agricultural work robot 120 may be an example of a moving body. The know-how management server 146 may be an example of an information processing device. Agricultural work may be an example of work.

[Example of another embodiment]
In the present embodiment, the details of the agricultural work support system 100 will be described by taking as an example the case where the measuring device 116 is installed at an arbitrary position in the field 20. However, the measuring device 116 is not limited to this embodiment.

In another embodiment, the measuring device 116 may be attached to the worker 40. In this case, examples of the measuring device 116 include various sensors, cameras, microphones, and the like mounted on the wearable terminal mounted on the worker 40.

In the present embodiment, the details of the agricultural work support system 100 will be described by taking as an example the case where the agricultural work robot 120 is a machine for agricultural work having an autonomous movement function (sometimes referred to as an agricultural machine). However, the agricultural work support system 100 is not limited to this embodiment.

In another embodiment, the agricultural work support system 100 holds or attaches the same information as the information collected via the agricultural work robot 120 to (i) the equipment arranged in the field 20 and (ii) the worker 40. It may be collected from the equipment and at least one of the agricultural machines that do not have (iii) autonomous mobility. Further, the agricultural work support system 100 transfers the same information as the information transmitted to the agricultural work robot 120 to (i) the equipment arranged in the field 20, (ii) the equipment held or attached to the worker 40, and (Iii) It may be transmitted to at least one of the agricultural machines having no autonomous movement function.

Agricultural machinery that does not have an autonomous movement function has a communication function and may be operated by the worker 40. The agricultural machine having no autonomous movement function may be operated by the worker 40 who is on board the agricultural machine, or may be remotely controlled by the worker 40.

FIG. 2 schematically shows an example of the system configuration of the agricultural work robot 120. As described in relation to FIG. 1, in the present embodiment, the agricultural work robot 120 includes a base unit 130, a mobile unit 132, an image pickup unit 134, a sensor unit 136, and an agricultural work unit 138.

As shown in FIG. 2, in the present embodiment, the agricultural work robot 120 includes a control unit 220, a power supply unit 230, a vibration damping unit 250, and a balance adjustment unit 280. The agricultural work robot 120 may include a plurality of control units 220. The agricultural work robot 120 may include a plurality of power supply units 230. The agricultural work robot 120 may include a plurality of vibration damping units 250. The agricultural work robot 120 may include a plurality of balance adjusting units 280.

In the present embodiment, the agricultural work robot 120 may be a work machine that carries out arbitrary work. The farm work robot 120 carries out various farm work, monitoring work, and the like, for example. The agricultural work robot 120 may be a fixed type or a mobile type. The agricultural work robot 120 may have an autonomous traveling function or an autonomous navigation function, may be operated by remote control, or may be operated by a worker who has boarded the agricultural work robot 120. The agricultural work robot 120 is preferably an unmanned work machine having an autonomous traveling function or an autonomous navigation function.

The agricultural work robot 120 may be a small robot. For example, the volume per 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. As a result, it is possible to move freely in the field. In addition, the agricultural product 22 can be observed from an angle that is difficult for humans.

In the present embodiment, the base unit 130 holds a mobile unit 132, an image pickup unit 134, a sensor unit 136, an agricultural work unit 138, a control unit 220, a power supply unit 230, a vibration control unit 250, and a balance adjustment unit 280. In the present embodiment, the base unit 130 detachably holds at least one of the mobile unit 132, the image pickup unit 134, the sensor unit 136, the agricultural work unit 138, the vibration damping unit 250, and the balance adjustment unit 280. As a result, the agricultural work robot 120 can handle a plurality of different types of work.

In this embodiment, the base unit 130 has a control unit 220 and a power supply unit 230. The control unit 220 and the power supply unit 230 may be built in the base unit 130. At least one of the control unit 220 and the power supply unit 230 may be detachably arranged on the base unit 130. In one embodiment, at least one of the control unit 220 and the power supply unit 230 is detachably arranged inside the base unit 130. In another embodiment, at least one of the control unit 220 and the power supply unit 230 is detachably arranged outside the base unit 130.

In the present embodiment, the moving unit 132 moves the farm work robot 120. The power of the mobile unit 132 may be electric power, an internal combustion engine, or a steam engine. For example, the mobile unit 132 converts the electric power supplied from the power supply unit 230 into power to move the agricultural work robot 120. In the present embodiment, the mobile unit 132 may include a power source that generates power by using the electric power supplied from the power supply unit 230. Examples of the power source include a motor and an actuator.

In one embodiment, the moving unit 132 includes wheels for moving on land and a power source for driving the wheels. In another embodiment, the mobile unit 132 comprises an endless track for traveling on land and a power source for driving the endless track. In yet another embodiment, the moving unit 132 may include a screw for moving on or under 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 mobile unit 132 may further include a balloon or air sac for floating in the air.

In the present embodiment, the image pickup unit 134 images various subjects. For example, the image pickup unit 134 captures at least one of (i) a worker 40, (ii) an agricultural work robot 120, (iii) agricultural product 22, and (iv) agricultural product 22's surrounding environment. As the surrounding environment of the agricultural product 22, the inside of the field 20 or the periphery of the field 20 can be exemplified. The image pickup unit 134 may take an image of a medium (for example, soil) in which the agricultural product 22 is cultivated as the surrounding environment of the agricultural product 22. For example, the image pickup unit 134 images the position where the agricultural product 22 is growing and / or the vicinity of the position in the above medium.

In one embodiment, the imaging unit 134 is detachably arranged outside the base unit 130. In another embodiment, the imaging unit 134 is arranged in another unit. For example, the image pickup unit 134 is incorporated in the farm work unit 138. The image pickup unit 134 may be incorporated in the control unit 220.

The image pickup unit 134 may be arranged in front of the traveling direction of the base unit 130, or may be arranged behind in the traveling direction of the base unit 130. The image pickup unit 134 may be arranged on the side surface of the agricultural work robot 120. The image pickup unit 134 may be arranged on the upper surface of the base unit 130, or may be arranged on the lower surface of the base unit 130. The image pickup unit 134 may have a light that emits illumination light. The light may be an example of a lighting unit that emits illumination light.

In the present embodiment, the image pickup unit 134 captures at least one of a still image and a moving image. It is preferable that the image pickup unit 134 can capture a moving image. The image pickup unit 134 may be a visible light camera or an infrared camera. The image pickup unit 134 may have a manipulator and an image pickup device attached to the tip of the manipulator. The manipulator can use the electric power supplied from the power supply unit 230 to point the image pickup device in any direction.

The image data captured by the image pickup unit 134 may be stored in the storage device of the farm work robot 120 or may be transmitted to the farm work management server 142. The farm work robot 120 may analyze the data of the image captured by the image pickup unit 134 and transmit the analysis result to the farm work management server 142.

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 related to the worker 40, a physical quantity related to the agricultural work robot 120, a physical quantity related to the agricultural product 22, and a physical quantity related to the surrounding environment of the agricultural product 22. As a result, information on the growing environment of the agricultural product 22 can be obtained.

Examples of the physical quantity of the agricultural product 22 include the color, luster, shape, pattern, size, weight or mass, composition, content of a specific component, hardness, elasticity, and the like of the agricultural product 22. As the physical quantity related to the surrounding environment of the agricultural product 22, information on soil, information on the atmosphere, information on light intensity, and the like can be exemplified. Information about the soil can be exemplified by pH, temperature, water content, particle size distribution, hardness, and components, bacteria and viruses contained in the soil. Examples of the components contained in the soil include organic substances (carbon), nitrogen, phosphorus, potassium, magnesium, calcium, sulfur, iron, manganese, boron, zinc, molybdenum, copper, and chlorine. As information on the atmosphere, temperature, atmospheric pressure, humidity, carbon dioxide concentration, nitrogen concentration, oxygen concentration, wind direction, air volume, and the like can be exemplified.

In one embodiment, the sensor unit 136 is detachably arranged outside the base unit 130. In another embodiment, the sensor unit 136 is arranged in another unit. For example, the sensor unit 136 is incorporated in the agricultural work unit 138. The sensor unit 136 may be incorporated in the control unit 220.

The measurement result of the sensor unit 136 may be stored in the storage device of the farm work robot 120 or may be transmitted to the farm work management server 142. The farm work robot 120 may analyze the measurement result of the sensor unit 136 and transmit the analysis result to the farm work management server 142.

In the present embodiment, the agricultural work unit 138 may be an attachment for agricultural work. For example, an agricultural work unit 138 according to the application is attached to the base unit 130. Thereby, the farm work robot 120 can carry out a plurality of different types of farm work.

In the present embodiment, the agricultural work unit 138 may be a unit specialized for one or a plurality of agricultural operations. As the agricultural work unit 138, a chemical spraying device for pest control, a fertilizer spraying device for spraying fertilizer, a gas spraying device for spraying gas, a ridge raising device, a seedling dropping device, a seed sowing device, a tilling device, and unnecessary branches and leaves are summarized. Manipulators with jigs for harvesting, manipulators with jigs for picking agricultural products, mowing equipment (eg, mowing equipment for abandoned fields), watering equipment, bird and beast threatening equipment (eg voice, Examples thereof include a device that threatens birds and beasts with light), a thinning device, a flower-picking device, a fruit tree-picking device, and a bag-hanging device (for example, a bag-hanging device for fruit trees).

In the present embodiment, the agricultural work unit 138 is detachably held by the base unit 130. The agricultural work unit 138 may include a power source for generating power for driving the agricultural work unit 138 by using the electric power supplied from the power supply unit 230. Examples of the power source include a motor and an actuator.

In the present embodiment, the agricultural work unit 138 includes an information processing device that executes firmware 294 and controls the agricultural work unit 138. The above information processing device may be a processor such as a CPU or GPU. The above information processing devices include (i) a data processing device having a processor such as a CPU and GPU, a ROM, a RAM, and a communication interface, and (ii) a keyboard, a pointing device, a touch panel, a camera, a voice input device, and a gesture input device. , Various sensors, input devices such as GPS receivers, (iii) display devices, audio output devices, vibration devices and other output devices, and (iv) memory, HDD, SSD and other storage devices (including external storage devices). ) And may be provided.

The latest version of firmware 294 is managed by, for example, the farm work management server 142. The farm work management server 142 transmits, for example, the latest version of the firmware 294 to the farm work unit 138 or the control unit 220 in response to a request from the farm work unit 138 or the control unit 220. As a result, the farm work unit 138 or the control unit 220 can update the firmware 294.

In the present embodiment, the control unit 220 controls the farm work robot 120. In one embodiment, the control unit 220 communicates with each unit and controls the operation of the unit according to the type of the unit. The control unit 220 may control the operation of one or a plurality of units according to the combination of the plurality of units.

For example, the control unit 220 communicates with at least one of the mobile unit 132, the farm work unit 138 and the balance adjustment unit 280. The communication method may be wired communication or wireless communication. When the communication method between the control unit 220 and the other unit is wired communication, the base unit 130 may be referred to as a communication path (sometimes referred to as a bus) for transmitting information between the control unit 220 and the other unit. .) May have. The above communication path may be an example of a communication unit.

In another embodiment, the control unit 220 may communicate with at least one of the farm work management server 142 and the know-how management server 146. For example, the control unit 220 transmits information about the farm work robot 120 to at least one of the farm work management server 142 and the know-how management server 146. For example, the control unit 220 acquires the position information of the farm work robot 120 and transmits the position information to at least one of the farm work management server 142 and the know-how management server 146. For example, the control unit 220 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 at least one of the agricultural work management server 142 and the know-how management server 146. do.

In the present embodiment, the control unit 220 includes an information processing device that executes the control program 222 and controls the agricultural work robot 120. The above information processing device may be a processor such as a CPU or GPU. The above information processing devices include (i) a data processing device having a processor such as a CPU and GPU, a ROM, a RAM, and a communication interface, and (ii) a keyboard, a pointing device, a touch panel, a camera, a voice input device, and a gesture input device. , Various sensors, input devices such as GPS receivers, (iii) display devices, audio output devices, vibration devices and other output devices, and (iv) memory, HDD, SSD and other storage devices (including external storage devices). ) And may be provided.

In this embodiment, the control program 222 may operate on the OS 224. One or more control programs 222 may run on one or more OS 224s. The OS 224 controls the farm work robot 120 via one or a plurality of drivers 226 for controlling various hardware included in the farm work robot 120. For example, the OS 224 recognizes a specific unit (for example, a mobile unit 132, an agricultural work unit 138, etc.) or controls the operation of the unit via a specific driver 226. By updating at least one of the control program 222, the OS 224, and the driver 226, for example, the farm work robot 120 can use a new unit, or the farm work robot 120 can use the unit efficiently. do.

The latest version of the control program 222, OS 224, and driver 226 are managed by, for example, the farm work management server 142. The agricultural work management server 142 transmits, for example, at least one of the latest version of the control program 222, the OS 224, and the driver 226 to the control unit 220 in response to a request from the control unit 220. As a result, the control unit 220 can update at least one of the control program 222, the OS 224, and the driver 226.

The position information may be any information indicating the position of the agricultural work robot 120, and the content and acquisition method of the position information are not particularly limited. The control unit 220 may specify the position of the agricultural work robot 120 by an arbitrary self-position estimation method. The control unit 220 may receive a GPS signal and identify the position of the agricultural work robot 120 based on the GPS signal. The control unit 220 may receive a beacon signal from a beacon transmitter installed around the farmland and specify the position of the farm work robot 120 based on the beacon signal. The position of the agricultural work robot 120 may be determined based on the radio wave intensity of the radio wave. The control unit 220 analyzes the image around the farm work robot 120 captured by the image pickup unit 134, and identifies the position of the farm work robot 120 from the angle formed by the plurality of landmarks whose positions are known and the farm work robot 120. May be good.

The control unit 220 may acquire information for controlling the agricultural work robot 120 from the agricultural work management server 142. The information for controlling the farm work robot 120 may be information about the work to be performed by the farm work robot 120 from now on. The information for controlling the farm work robot 120 may be control data uploaded to the farm work management server 142. The information for controlling the farm work robot 120 may be a trained learning model. The information for controlling the agricultural work robot 120 may be data indicating the contents of the know-how managed by the know-how management server 146. The control unit 220 may control the operation of the unit related to the information based on the information acquired from the farm work management server 142.

In the present embodiment, the power supply unit 230 supplies electric power for driving the mobile unit 132, the agricultural work unit 138, and the balance adjustment unit 280 to at least one of them. The power supply unit 230 may supply electric power to at least one of the vibration damping unit 250, the image pickup unit 134, and the sensor unit 136.

In the present embodiment, the vibration damping unit 250 controls vibration. For example, the vibration damping unit 250 controls at least one vibration of the image pickup unit 134, the sensor unit 136, and the farm work unit 138. The vibration damping unit 250 may control the vibration according to a command from the control unit 220. The vibration damping unit 250 may have a power source for generating power for driving the vibration damping unit 250 by using the electric power supplied from the power supply unit 230. Examples of the power source include a motor and an actuator.

In this embodiment, the balance adjustment unit 280 has a weight. The balance adjustment unit 280 is detachably held by the base unit 130. Depending on the weight of the unit mounted on the base unit 130 and the position of the center of gravity thereof, the weight balance of the agricultural work robot 120 becomes poor, and the agricultural work robot 120 becomes unstable. Therefore, the weight balance of the agricultural work robot 120 can be adjusted by mounting the balance adjusting unit 280 at an appropriate position of the base unit 130.

The balance adjustment unit 280 may be a manipulator having a weight at the tip. By changing the relative position of the weight and the base unit 130 by the manipulator, the position of the center of gravity of the agricultural work robot 120 can be changed. The manipulator may be an example of a power source.

FIG. 3 schematically shows an example of the internal configuration of the agricultural work management server 142. In the present embodiment, the agricultural work management server 142 includes an input receiving unit 310, a screen generation unit 320, a work plan generation unit 330, and a storage unit 340. In the present embodiment, the storage unit 340 includes a log data storage unit 352, a standard data storage unit 354, a work record storage unit 362, a growth record storage unit 364, a harvest record storage unit 366, and a shipping record storage unit 368. And a setting data storage unit 372 and an evaluation data storage unit 374.

In the present embodiment, the input receiving unit 310 receives an input from the worker 40 or the consumer 50. The worker 40 inputs various information about the field 20, for example. The worker 40 may input information indicating the position and range of the field 20. The worker 40 inputs, for example, the work plan and the work history of the agricultural product 22. The worker 40 inputs, for example, know-how regarding cultivation of the agricultural product 22. Worker 40 and / or consumer 50 enter, for example, an assessment for produce 22. Examples of the evaluation items for the evaluation of the agricultural product 22 include quality, yield, and suitability for a specific use. Examples of the quality of the agricultural product 22 include appearance, size, taste, and content of a specific component. Examples of the above-mentioned uses include the types of animals that consume the agricultural products 22, the types of dishes in which the agricultural products 22 are used, and the types of processing of the agricultural products 22.

For example, the input receiving unit 310 receives an input of an instruction to the agricultural work management server 142. Examples of the above instructions include registration of settings, creation or update of work plans, creation or update of work history, registration of evaluations, and the like. The input receiving unit 310 outputs information indicating the content of the input instruction to the screen generation unit 320.

Further, the input receiving unit 310 accepts the input of the information registered in the database. Examples of the above information include information indicating the contents of various settings related to the agricultural work management server 142, information indicating the contents of the work plan, information indicating the contents of the work history, information indicating the contents of the evaluation, and the like. The input receiving unit 310 stores the input information in the storage unit 340.

In the present embodiment, the screen generation unit 320 generates various screens. For example, the screen generation unit 320 acquires information indicating the content of the instruction received by the input reception unit 310 from the input reception unit 310. The screen generation unit 320 generates information (sometimes referred to as screen data) for presenting a screen corresponding to the content of the above instruction to the instructor. The above screen may be various input screens. The screen generation unit 320 transmits the generated screen data to the communication terminal 102 used by the instructor of the above instruction.

In the present embodiment, the screen generation unit 320 may generate the above screen in cooperation with the know-how management server 146. In one embodiment, the screen generation unit 320 generates a screen for the know-how management server 146 to request the worker 40 to confirm the contents of the know-how created by the know-how management server 146. In another embodiment, the know-how management server 146 generates a screen for requesting the worker 40 to answer a question for creating know-how regarding agricultural work.

In the present embodiment, the work plan generation unit 330 generates a work plan. The work plan generation unit 330 may generate a work plan for each worker 40, a work plan for each field 20, or a work plan for each agricultural product 22. The work plan generation unit 330 may store the generated work plan in the setting data storage unit 372.

The work plan may be information in which information indicating the date and time is associated with the content of the work to be performed on the date and time. The information indicating the date and time may be (i) information indicating the date and time, or (ii) information indicating the date and time.

The work plan may include basic information about the field 20 in which the work is carried out. The basic information about the field 20 includes identification information of the field 20, information indicating the position and range of the field 20, identification information of the worker 40 working in the field 20, and information indicating the items cultivated in the field 20. , Information indicating the characteristics of the soil of the field 20, information indicating the characteristics of the weather of the field 20, and the like are exemplified.

The cultivation work of the agricultural product 22 includes one or more steps. Each of one or more steps comprises one or more work items. To carry out each work item, the worker 40 performs one or more actions. The contents of the work included in the work plan may be created at the process level, the work item level, or the action level.

It should be noted that a process in which a work plan is created at the process level and a process in which a work plan is created at the work item level may be mixed. Further, a process in which a work plan is created at the process level, a process in which a work plan is created at the work item level, and a process in which a work plan is created at the action level may be mixed. For example, for a process in which the length of the remaining period until the scheduled implementation date and time is smaller than a predetermined value, a work plan is created at the work item level or the action level. On the other hand, for a process in which the length of the remaining period until the scheduled implementation date and time is larger than a predetermined value, a work plan is created at the process level.

The work plan generation unit 330 may manage the progress of the work. For example, the work plan generation unit 330 has information (when referred to as a work history) in which information indicating the date and time and information indicating the content of the work performed by the agricultural work robot 120 at the date and time are associated with each other from the agricultural work robot 120. There is.) To get. Further, for example, the work plan generation unit 330 acquires the work history of the worker 40 from the communication terminal 102 of the worker 40. The work plan generation unit 330 compares the work plan and the work history, and calculates the progress of the work. As a result, the work plan generation unit 330 can manage the progress of the work.

The work plan generation unit 330 may update the work plan. For example, the work plan generation unit 330 acquires information indicating the date and time from the agricultural work robot 120 and information indicating the status of the field 20 and the agricultural product 22 at the date and time. For example, the work plan generation unit 330 acquires information indicating the date and time from the communication terminal 102 of the worker 40 and information indicating the status of the field 20 and the agricultural product 22 at the date and time. For example, the work plan generation unit 330 updates the work plan based on at least one of (i) the situation of the field 20, (ii) the situation of the agricultural products 22, and (iii) the progress of the work.

In the present embodiment, the storage unit 340 stores various types of information. In one embodiment, the storage unit 340 stores information input by the worker 40 or the consumer 50 into the farm work support system 100. In another embodiment, the storage unit 340 acquires various information from an external server that operates a platform or database related to agricultural data, and stores the information. Examples of agricultural data include meteorological data, soil data, map data, agricultural land data, material data, work time prediction data, and growth prediction data.

In the present embodiment, the log data storage unit 352 associates information indicating a time or period with information indicating work items performed by the worker 40 at the time or period for each of one or more workers 40. Stores the information (sometimes called a work log). The work log is (i) information indicating the position of the worker 40 at each time or period, and (ii) information indicating work items scheduled to be performed at each time or period in the work plan of the worker 40. , And (iii) may include at least one piece of information indicating the status of the worker 40 at each time or period. Examples of the status of the worker 40 include working, resting, moving, out of working hours, and inability to work. The work log may include identification information of the worker 40 (sometimes referred to as a user ID) or may include identification information of the farm work robot 120 (sometimes referred to as a robot ID).

The log data storage unit 352 may acquire information about the work plan of the worker 40 from the work plan generation unit 330. The log data storage unit 352 may acquire information indicating the position of the worker 40 from the communication terminal 102 or the agricultural work robot 120 used by the worker 40. The log data storage unit 352 may acquire information about the work performed by the worker 40 from the communication terminal 102 or the agricultural work robot 120 used by the worker 40.

For example, before starting the work, the worker 40 inputs the identification information of the work to be performed by the worker 40 into the communication terminal 102. The worker 40 may input the identification information of the work performed by the worker 40 into the communication terminal 102 during the work. After the work is completed, the worker 40 may input the identification information of the work performed by the worker 40 into the communication terminal 102. Examples of the work identification information include names, abbreviations, and identification symbols. The worker 40 may (i) input the work identification information by voice input, or (ii) may input the work identification information by using a keyboard, a pointing device, a touch device, or the like.

The agricultural work robot 120 carries out the work based on, for example, a work plan or an instruction from the worker 40. The agricultural work robot 120 may carry out the work while generating a work log or a part thereof. The farm work robot 120 may transmit the work log to the farm work management server 142 at an arbitrary timing or a predetermined timing.

In the present embodiment, the log data storage unit 352 associates information indicating a time or period with information regarding the behavior of the worker 40 during the time or period for each of the one or more workers 40 (information indicating the time or period). It is sometimes called an action log.) Is stored. Examples of the information regarding the behavior of the worker 40 include identification information for identifying the type of the behavior, information indicating the content of the behavior, and image data of the worker 40 performing the behavior.

The log data storage unit 352 may acquire information on the behavior of the worker 40 from the communication terminal 102 or the farm work robot 120 used by the worker 40. For example, the worker 40 inputs the identification information for identifying the type of the above action and the information indicating the content of the above action into the communication terminal 102. The above input method and input timing are not particularly limited. Further, the farm work robot 120 may carry out the work while generating an action log or a part thereof. The farm work robot 120 may transmit the action log to the farm work management server 142 at an arbitrary timing or a predetermined timing.

In the present embodiment, the standard data storage unit 354 stores information (sometimes referred to as standard data) indicating the contents of standard work specified for each cultivated item. Standard data includes information on standard processes, standard work items, standard actions, standard times when each process is performed, standard times when each work item is performed, and the like. The standard time for each step to be performed may be (i) expressed as a particular month, week or day, (ii) as a condition for the meteorological environment, (iii) other steps or It may be expressed as a period after the work item is carried out. Similarly, the standard time for each work item to be carried out may be expressed as (i) a particular month, week or day, (ii) as a condition for the meteorological environment, (iii) et al. It may be expressed as a period after the process or work item of the above is carried out.

The standard data storage unit 354 may store standard data for each region. As a result, the work plan generation unit 330 can generate an appropriate work plan according to the area where the agricultural product 22 is cultivated. The standard data storage unit 354 may store standard data for each worker 40. As a result, the work plan generation unit 330 can generate a work plan that reflects the unique know-how of the worker 40. The standard data storage unit 354 may store standard data for each weather condition. As a result, the work plan generation unit 330 can generate an appropriate work plan according to the weather conditions of each year.

In one embodiment, standard data is obtained from a server operating a platform or database for agricultural data. In another embodiment, the standard data is created based on the past work history of a plurality of workers 40 cultivating the same type of agricultural product 22. The standard data for each region is created based on the past work history of a plurality of workers 40 who cultivate the same kind of agricultural products 22 in the same region. The standard data for each worker 40 may be generated based on the past work history of each worker 40, or may be generated based on the work plan created by the worker 40.

In the present embodiment, the work record storage unit 362 stores the work record of the worker 40. The work record of the worker 40 may be created based on the information input by the worker 40 to the farm work support system 100 via the communication terminal 102, or based on the work history of the farm work robot 120 used by the worker 40. It may be created.

In the present embodiment, the growth record storage unit 364 stores the growth record of the agricultural product 22. The growth record of the agricultural product 22 may be created based on the information input by the worker 40 to the agricultural work support system 100 via the communication terminal 102, and the agricultural product 22 imaged or measured by the agricultural work robot 120 used by the worker 40. It may be created based on the data of.

In the present embodiment, the harvest record storage unit 366 stores the harvest record of the agricultural product 22. The harvest record of the agricultural product 22 may be created based on the information input by the worker 40 to the agricultural work support system 100 via the communication terminal 102, and the agricultural product 22 imaged or measured by the agricultural work robot 120 used by the worker 40. It may be created based on the data of.

In the present embodiment, the shipping record storage unit 368 stores the shipping record of the agricultural product 22. The shipment record of the agricultural product 22 may be created based on the information input by the worker 40 to the agricultural work support system 100 via the communication terminal 102, and the agricultural product 22 imaged or measured by the agricultural work robot 120 used by the worker 40. It may be created based on the data of.

In the present embodiment, the setting data storage unit 372 stores information (sometimes referred to as setting data) regarding various settings. Examples of the setting data include a work plan created by the work plan generation unit 330, a unit price for calculating the production cost of the agricultural product 22, and a predicted value of the selling price of the agricultural product 22. Other examples of the setting data include information on the experience of each worker, information on the farmland owned or worked by each worker, and the like. Information on the worker's experience includes (i) the combination of the type of work and the number of years of experience of the work, (ii) the type of qualification that the worker has, and (iii) the type of award that the worker has received. , (Iv) The time of acquisition of the qualification or award is exemplified. Examples of the information regarding the agricultural land include identification information of the agricultural land, identification information of the area where the agricultural land is located, and the type or characteristics of the soil or medium of the agricultural land.

In the present embodiment, the evaluation data storage unit 374 stores information (sometimes referred to as evaluation data) indicating the content of the evaluation regarding the agricultural product 22. The evaluation data may be created based on the information input by the consumer 50 to the agricultural work support system 100 via the communication terminal 102.

FIG. 4 schematically shows an example of the internal configuration of the know-how management server 146. In the present embodiment, the know-how management server 146 includes, for example, a work plan acquisition unit 422, a voice data acquisition unit 432, an image data acquisition unit 434, a history data acquisition unit 436, and an environment data acquisition unit 438. In the present embodiment, the know-how management server 146 includes, for example, a know-how data generation unit 440 and a know-how database 450. In the present embodiment, the know-how management server 146 includes, for example, a request receiving unit 460 and a request processing unit 470.

In the present embodiment, the work plan acquisition unit 422 accesses the setting data storage unit 372 and acquires information indicating the work plan of the worker 40. The work plan acquisition unit 422 outputs information indicating the work plan of the worker 40 to the know-how data generation unit 440.

In the present embodiment, the voice data acquisition unit 432 acquires data (sometimes referred to as voice data) in which the voice of the worker 40 is recorded. The voice data acquisition unit 432 may acquire voice data during the period in which the worker 40 is carrying out farm work. The voice data acquisition unit 432 acquires voice data from at least one of the communication terminal 102, the image pickup device 114, and the agricultural work robot 120, for example. The voice data acquisition unit 432 outputs the acquired voice data to the know-how data generation unit 440.

In the present embodiment, the image data acquisition unit 434 acquires image data (sometimes referred to as image data) in which the state of work by the worker 40 is captured. The state of the work by the worker 40 may be the state of the worker 40 or the state of the work target of the worker 40. As described above, examples of the work target include (i) a field 20, (ii) an agricultural product 22, and (iii) birds and beasts, pests, or weeds located in the vicinity of the agricultural product 22. In the image data, in addition to the image data of the captured subject, data indicating at least one of (i) the voice of the worker 40 and (ii) the gaze position of the worker 40 can be recorded.

The image data acquisition unit 434 may acquire image data during the period in which the worker 40 is carrying out farm work. The image data acquisition unit 434 acquires image data from at least one of the communication terminal 102, the image pickup device 114, and the agricultural work robot 120, for example. The image data acquisition unit 434 outputs the acquired image data to the know-how data generation unit 440.

In the present embodiment, the history data acquisition unit 436 acquires information (sometimes referred to as history data) indicating various histories regarding the worker 40 or the agricultural work robot 120. The history data acquisition unit 436 outputs the acquired history data to the know-how data generation unit 440.

In one embodiment, the history data acquisition unit 436 acquires data indicating the fluctuation history of the vital signs of the worker 40 from the communication terminal 102 used by the worker 40. Examples of the vital signs of the worker 40 include the respiratory rate, the breathing pattern, the body temperature, the blood pressure, the pulse rate, the pulse pattern, the blood oxygen concentration, the frequency of blinking, and the amount of sweating. The vital sign of the worker 40 is measured by, for example, a sensor mounted on the worker 40 and transmitted to the communication terminal 102 via short-range wireless communication. Thereby, for example, the vital signs of the worker 40 or the abnormality of the psychological state can be detected. The sensor for measuring the vital signs of the worker 40 is built in, for example, a wearable terminal worn by the worker 40.

In another embodiment, the history data acquisition unit 436 acquires data indicating the work history of the worker 40 or the agricultural work robot 120 from the agricultural work robot 120. Thereby, the content of the work actually performed by the worker 40 or the farm work robot 120 can be compared with the content of the work described in the work plan. As a result, deviations from the work plan can be detected.

In another embodiment, the history data acquisition unit 436 may perform data other than (i) data indicating the time when the worker 40 executes a specific action from the agricultural work robot 120 or (ii) a predetermined action by the worker 40. Data indicating the time when the action is executed may be acquired. Thereby, for example, the abnormal behavior of the worker 40 can be detected.

In another embodiment, the history data acquisition unit 436 may acquire data indicating at least one fluctuation history of the velocity, acceleration, and angular acceleration of the agricultural work robot 120 from the agricultural work robot 120. The history data acquisition unit 436 may acquire data indicating the time when the agricultural work robot 120 suddenly accelerates or decelerates suddenly from the agricultural work robot 120. As a result, the abnormal behavior of the agricultural work robot 120 can be detected. When the farm work robot 120 is set to move following the worker 40, the abnormal behavior of the worker 40 can be detected by detecting the abnormal behavior of the farm work robot 120.

In the present embodiment, the environmental data acquisition unit 438 acquires information (sometimes referred to as environmental data) indicating the state of the surrounding environment of the agricultural product 22. The environmental data acquisition unit 438 acquires environmental data from at least one of the measuring device 116 and the agricultural work robot 120, for example. The environmental data acquisition unit 438 may acquire environmental data from the weather information management server 144. The environmental data acquisition unit 438 may acquire environmental data from an external server that operates a platform or database related to agricultural data. The environmental data acquisition unit 438 outputs the acquired environmental data to the know-how data generation unit 440.

In the present embodiment, the know-how data generation unit 440 generates information (sometimes referred to as know-how data) indicating know-how regarding agricultural work. The know-how data generation unit 440 uses information acquired by at least one of a work plan acquisition unit 422, an audio data acquisition unit 432, an image data acquisition unit 434, a history data acquisition unit 436, and an environmental data acquisition unit 438, to provide know-how data. To generate.

For example, the know-how data generation unit 440 generates know-how data regarding at least one of one or more work items included in at least one of the one or more steps for producing the agricultural product 22. The know-how data generation unit 440 may generate know-how data for each work item. The know-how data generation unit 440 may generate a single know-how data for a single work item, or may generate a plurality of know-how data for a single work item.

For example, the know-how data generation unit 440 uses a part or all of the voice data acquired by the voice data acquisition unit 432 as know-how data. The know-how data generation unit 440 may use a part or all of the image data acquired by the image data acquisition unit 434 as know-how data.

For example, the know-how data generation unit 440 analyzes at least one of the voice data acquired by the voice data acquisition unit 432 and the image data acquired by the image data acquisition unit 434 to generate the know-how data. Specifically, the know-how data generation unit 440 is based on (i) the voice of the worker 40 performing the farm work and (ii) at least one of the state of the work by the worker 40, and the implementation period of the farm work. Estimate one or more actions performed by the worker 40 during. Further, the know-how data generation unit 440 estimates, for each of the one or more actions executed by the worker 40, a condition that serves as a criterion for determining whether or not the action should be executed.

Next, the know-how data generation unit 440 generates know-how data by associating each of the above-mentioned one or more actions with the above-mentioned conditions related to each action. In one embodiment, the know-how data generation unit 440 generates know-how data in a format capable of presenting the contents of the know-how to the worker 40 as a flowchart. In another embodiment, the know-how data generation unit 440 generates know-how data in a format in which the farm work robot 120 can operate the farm work robot 120 according to the contents of the know-how by executing the know-how data. Details of the know-how data generation unit 440 will be described later.

In the present embodiment, the know-how database 450 stores the know-how data generated by the know-how data generation unit 440. The know-how database 450 may store know-how data for each item, may store know-how data for each field, may store know-how data for each region or district, and may store know-how data for each worker 40. May be stored, or know-how data may be stored for each group of workers 40.

In the present embodiment, the request receiving unit 460 receives a request from the worker 40 or the agricultural work robot 120. For example, the request receiving unit 460 receives a search request for know-how data. The request reception unit 460 outputs information indicating the content of the accepted request to the request processing unit 470.

In the present embodiment, the request processing unit 470 executes the processing corresponding to the request received by the request receiving unit 460. For example, when the request receiving unit 460 receives a search request for know-how data, the request processing unit 470 accesses the know-how database 450 and extracts the know-how data that matches the conditions indicated by the search request. The request processing unit 470 transmits the extracted know-how data to the source of the above search request.

Thereby, for example, when the worker 40 wants to know the know-how of a specific process or work item, the worker 40 can acquire the know-how data related to the specific process or work item. Further, when data such as the work history by the worker 40 or the farm work robot 120, the state of the field 20, and the state of the agricultural product 22 are stored in the farm work management server 142, the worker 40 is in the state of the field 20 or the farm product 22. It is possible to acquire the corresponding know-how. As a result, the worker 40 can appropriately execute the specific step or work item depending on the state of the field 20 or the agricultural product 22.

Further, when the farm work robot 120 transmits a search request for know-how data, the know-how data is read into the control program 222 of the farm work robot 120. As a result, the agricultural work robot 120 can appropriately execute the specific process or work item according to the state of the field 20 or the agricultural product 22.

The voice data acquisition unit 432 may be an example of the data acquisition unit. The image data acquisition unit 434 may be an example of a data acquisition unit. The know-how data generation unit 440 may be an example of an information processing device. The surrounding environment of the agricultural product 22 may be an example of a working environment. The know-how data may be an example of know-how information. The image data may be an example of audio data.

The history data acquisition unit 436 may be an example of the vital information acquisition unit. The history data acquisition unit 436 may be an example of the tracking information acquisition unit.

The details of the know-how data will be described with reference to FIGS. 5 and 6. FIG. 5 schematically shows an example of the data table 500. Each of the one or more records included in the data table 500 may be an example of the know-how data stored in the know-how database 450. FIG. 6 schematically shows an example of the flowchart 600 shown by the know-how data. The flowchart 600 shows the content of the know-how presented by a plurality of records corresponding to a single work item stored in the data table 500.

[Know-how data expressed in table format]
As shown in FIG. 5, in the present embodiment, the data table 500 stores information 502 indicating an item, information 504 indicating a process, information 506 indicating a work item, and information 508 indicating know-how in association with each other. do. The number of know-how associated with a single work item may be one or two or more.

In the present embodiment, the information 504 indicating the process includes, for example, information indicating the order in which the process is performed and identification information of the process for each of one or more processes constituting the cultivation operation of the agricultural product 22. .. As the process identification information, for example, the name or abbreviation of the process is used.

In the present embodiment, the information 506 indicating the work item includes, for example, information indicating the order in which the work item is executed and identification information of the work item for each of one or more work items constituting each process. include. As the identification information of the work item, for example, the name or abbreviation of the work item is used.

In the present embodiment, the information 508 indicating the know-how includes information indicating the purpose of the know-how or the problem achieved by the know-how, information indicating the content of the know-how, and information indicating the conditions under which the content of the know-how is executed. Includes URI of image data related to the know-how. The information indicating the content of the know-how may include at least one of the information indicating the content of the action when the above condition is satisfied and the information indicating the content of the action when the above condition is not satisfied.

The above conditions may be conditions based on current facts, conditions based on past facts, or conditions based on matters planned in the future. Examples of the current facts include the current state of the field 20 and the current state of the agricultural product 22. Examples of past facts include the past state of the field 20, the past state of the agricultural product 22, the contents of the work performed in the past on the field 20 or the agricultural product 22 and the like. Examples of matters planned in the future include the meteorological environment indicated by the weather forecast, the process or work item indicated by the work plan, and the like.

Examples of the purpose of the know-how are the purpose of expanding profits and the purpose of suppressing losses. Examples of the purpose of the know-how are related to quality, yield, cost, profit, delivery date, adjustment of working time, adjustment of execution time of subsequent work, and the like. For example, as know-how for the purpose of improving quality, know-how for producing agricultural products 22 having a specific quality and expanding profits, and suppressing loss by minimizing the influence on quality due to unseasonable weather. Know-how for this is exemplified.

According to this embodiment, the process or work item and the know-how are managed in association with each other. Further, as described above, for example, in the work plan generated by the work plan generation unit 330, the process or work item is managed in association with the scheduled implementation time of the process or work item. Therefore, according to the present embodiment, the know-how regarding the process or work item can be managed in association with the scheduled implementation time of the process or work item. Thereby, for example, the screen generation unit 320 can generate a screen in which the know-how regarding the process or the work item is associated with the scheduled implementation time of the process or the work item.

[Specific examples of know-how data]
For example, when cultivating "paddy rice", the contents of the process include (i) ordering or reservation of materials, (ii) operation check and repair of facilities or equipment or agricultural machinery arranged in the field, (iii) fertilization, (ii). iv) Scraping, (v) Water filling, (vi) Planting, (vii) Weeding or pesticide spraying, (viii) Installation of bird and beast prevention equipment, (ix) drainage, (x) harvesting, (xi) drying, (xii) Examples include threshing and (xiii) storage. Moreover, each step may be carried out in this order. The contents and order of the above steps may be different for each field. The content and order of the above steps may differ from region to region. The contents and order of the above steps may differ depending on the meteorological environment.

Also, each step includes one or more work items. For example, the above-mentioned process of ordering or reserving materials includes a plurality of work items such as ordering seedlings, ordering trays, and reserving rice transplanter rental. Further, each record in the data table 500 stores know-how data related to each work item. Multiple know-how data may be stored for a single work item. For example, as know-how regarding the work item of ordering seedlings, know-how for the purpose of maximizing profit and know-how for the purpose of producing rice having a specific quality are exemplified. ..

[Know-how data expressed in flowchart format]
As shown in FIG. 6, the flow chart format know-how can be expressed by a plurality of records associated with a specific work item. The flow chart format know-how may be stored in each record of the data table 500 as the "purpose" of the information 508 indicating the know-how, the "condition" of the information 508 indicating the know-how, and the "content" of the information 508 indicating the know-how. ..

In one embodiment, the screen generator 320 provides an operator a flowchart 600 as shown in FIG. 6 based on the information stored in the "purpose", "condition" and "content" of each record in the data table 500. Generate a screen to present to 40. In another embodiment, the screen generation unit 320 has one or a plurality of "contents" shown in the flowchart 600 that match the current situation, based on the information acquired from the worker 40 or the agricultural work robot 120. Extract the "contents" of. The screen generation unit 320 generates a screen for presenting the extracted "contents" to the worker 40 as know-how regarding the specific work item.

According to the present embodiment, when the purpose of the specific work item or the process including the work item is P1, there is know-how having the contents of A1, A2 and A3. Further, in this case, how to carry out a specific work item is determined based on the conditions C1 and C2. As mentioned above, whether or not conditions C1 and C2 are satisfied can be determined based on the current facts, past facts, or future plans.

Specifically, when the condition C1 is satisfied, the content A1 is extracted as know-how suitable for the current situation. Further, when the condition C1 is not satisfied and the condition C2 is satisfied, the content A2 is extracted as know-how suitable for the current situation. Further, when the conditions C1 and C2 are not satisfied, the content A3 is extracted as know-how suitable for the current situation.

On the other hand, when the purpose of the specific work item or the process including the work item is P2, the know-how of A4 and A5 exists. Further, in this case, how to carry out a specific work item is determined based on the condition C3. Specifically, when the condition C3 is satisfied, the content A4 is extracted as know-how suitable for the current situation. If the condition C3 is not satisfied, the content A5 is extracted as know-how suitable for the current situation.

According to this embodiment, the know-how is expressed by the conditions and the contents. Thereby, appropriate know-how can be automatically extracted according to the state of the field 20 or the agricultural product 22. Therefore, as described above, as a result, the worker 40 or the agricultural work robot 120 can appropriately execute the specific process or work item according to the state of the field 20 or the agricultural product 22.

More specifically, when the worker 40 or the farm work robot 120 carries out the work item for the purpose P1, when the condition C1 is satisfied, the worker 40 or the farm work robot 120 carries out the work item according to the content A1. .. On the other hand, when the condition C1 is not satisfied, the worker 40 or the agricultural work robot 120 determines whether or not the condition C2 is satisfied. Then, when the condition C2 is satisfied, the worker 40 or the agricultural work robot 120 carries out the work item according to the content A2. When the condition C2 is not satisfied, the worker 40 or the farm work robot 120 carries out the work item according to the content A3.

Similarly, when the worker 40 or the farm work robot 120 carries out the work item for the purpose P2, when the condition C3 is satisfied, the worker 40 or the farm work robot 120 carries out the work item according to the content A4. On the other hand, when the condition C3 is not satisfied, the worker 40 or the farm work robot 120 carries out the work item according to the content A5.

If the purpose is not specified, or if the purpose is not registered in the know-how database 450, standard actions or points to be noted when carrying out the work item may be presented. The above standard actions or points of concern are extracted, for example, with reference to the standard data storage unit 354.

FIG. 7 schematically shows an example of the internal configuration of the know-how data generation unit 440. In the present embodiment, the know-how data generation unit 440 includes, for example, a text data generation unit 720 and a data editing unit 730. In the present embodiment, the know-how data generation unit 440 is, for example, a shared setting unit 740, a work content estimation unit 752, a purpose estimation unit 754, a condition estimation unit 756, a condition quantification unit 758, and a data integration unit 760. And prepare. In the present embodiment, the know-how data generation unit 440 includes, for example, a question unit 770.

In the present embodiment, the text data generation unit 720 recognizes the voice recorded in the voice data acquired by the voice data acquisition unit 432 and generates text data indicating the content of the voice. The text data generation unit 720 recognizes the voice recorded in the image data acquired by the image data acquisition unit 434 and generates text data indicating the content of the voice. The text data generation unit 720 may associate the generated text data with the original voice data or image data and store the generated text data in a storage device (not shown) of the know-how management server 146.

In the present embodiment, the data editing unit 730 edits text data, voice data, and image data. In one embodiment, the data editing unit 730 cuts a part of the audio data and the image data. The data editing unit 730 may cut a part of the text data. For example, in the data editing unit 730, (i) the position where the voice of the worker 40 is recorded in the voice data and the image data, and (ii) the position where the action of the worker 40 is recorded in the voice data and the image data remain. As such, a part of the audio data and the image data is cut. As a result, data that is relatively unlikely to contain the know-how of the worker 40 is deleted. As a result, the process of generating know-how data can be speeded up.

In another embodiment, when the image data includes the image data captured and the information indicating the gaze position of the worker, the data editing unit 730 has the image and the icon indicating the gaze position of the worker 40. Generate a composited composite image. As a result, the viewer of the image of the know-how data can browse the image centering on the gaze position.

In the present embodiment, the sharing setting unit 740 sets the sharing range of the know-how data. The sharing setting unit 740 sets the sharing range of the know-how data according to the instruction from the worker 40 who provided the know-how, for example. The scope of sharing includes 40 workers who provided the know-how, 40 other workers who provided the know-how, 40 who paid the usage fee of the know-how, and 40 who provided the know-how. The other worker 40 who cultivates the same kind of agricultural product 22 as the other worker 40 who does not cultivate the same kind of agricultural product 22 as the worker 40 who provided the know-how, and the same worker 40 who provided the know-how. Or another worker 40 who cultivates the agricultural product 22 in the neighboring area, another worker 40 who does not cultivate the agricultural product 22 in the same or neighboring area as the worker 40 who provided the know-how, and the above-mentioned worker. An example is an agricultural work robot 120 to be used.

In the present embodiment, the work content estimation unit 752 performs the work implementation period based on (i) the voice of the worker 40 performing the work and (ii) at least one of the state of the work by the worker 40. Estimate one or more actions performed by the worker 40 during. For example, the work content estimation unit 752 includes voice data in which the voice of the worker 40 during work is recorded, image data in which the state of work of the worker 40 during work is recorded, and the text data generation unit 720 described above. At least one of the text data generated by processing the voice data and the image data of the above is analyzed, and one or more actions performed by the worker 40 during the execution period of the work are estimated.

In the present embodiment, the purpose estimation unit 754 includes (i) the voice of the worker 40, (ii) the matters input by the worker 40 in the work record, and (iii) the question inquired by the question unit 770 to the worker 40. Based on at least one of the responses from the worker 40 to the above, the purpose of the action of the worker 40 estimated by the work content estimation unit 752 is estimated.

In the present embodiment, the condition estimation unit 756 has (i) the voice of the worker 40, (ii) the state of the work by the worker 40, (iii) the matters input by the worker 40 in the work record, and (iv). Based on at least one of the conditions of the surrounding environment of the agricultural product 22, the condition that is the criterion for determining whether or not the action of the worker 40 estimated by the work content estimation unit 752 should be executed is estimated. The condition estimation unit 756 may estimate at least a part of the above conditions based on the answer from the worker 40 to the question inquired by the question unit 770 to the worker 40.

In the present embodiment, the condition quantification unit 758 determines whether or not the action should be executed based on at least one of the items input in the work record of the work and the state of the surrounding environment of the agricultural product 22. Estimate the threshold value. In one embodiment, when there are a plurality of data in which a single worker 40 performs the same work item, the condition quantification unit 758 analyzes the correspondence between the condition and the action indicated by the plurality of data. By doing so, the threshold value when the action is executed or the threshold value when the action is not executed may be determined. In another embodiment, when there are a plurality of data in which a plurality of workers 40 perform the same work item, the condition quantification unit 758 analyzes the correspondence between the condition and the action indicated by the plurality of data. By doing so, the threshold value when the action is executed or the threshold value when the action is not executed may be determined.

In the present embodiment, the data integration unit 760 generates know-how data by associating each of one or more actions estimated by the work content estimation unit 752 with the conditions related to each action estimated by the condition estimation unit 756. The data integration unit 760 associates each of one or more actions estimated by the work content estimation unit 752 with the conditions related to each action estimated by the condition estimation unit 756 and the purpose of each action estimated by the purpose estimation unit 754. And you may generate know-how data.

The data integration unit 760 stores the generated know-how data in the know-how database 450. The data integration unit 760 may store the generated know-how data in the know-how database 450 in association with the information indicating the sharing range determined by the sharing setting unit 740.

In the present embodiment, the question unit 770 generates information (sometimes referred to as question data) indicating the content of the question to the worker 40. When the question unit 770 detects an abnormality related to the worker 40, the question unit 770 generates a question for confirming the cause or reason of the abnormality. For example, if (i) the worker 40 takes an action that deviates from the standard behavior for each work item, (ii) the worker 40 deviates from the past behavior of the worker 40 for each work item. (Iii) When an abnormality is detected in the vital sign of the worker 40, (iv) When the worker 40 or the farm work robot 120 causes an abnormal behavior, a question regarding the reason why the behavior is taken. To generate.

In one embodiment, the question unit 770 transmits question data to the communication terminal 102 used by the worker 40. Further, the question unit 770 acquires information (sometimes referred to as answer data) indicating the answer of the worker 40 to the above question from the communication terminal 102. In another embodiment, the question unit 770 transmits the question data to the farm work management server 142. For example, when the farm work management server 142 generates the input screen of the work record, the farm work management server 142 generates the input screen including the contents of the question generated by the question unit 770. As a result, the work record including the answer to the above question is stored in the work record storage unit 362. The question unit 770 accesses the work record storage unit 362 to acquire information indicating the answer of the worker 40 to the above question. The details of the question section 770 will be described later.

The data editing unit 730 may be an example of the editing unit. The work content estimation unit 752 may be an example of the behavior estimation unit. The condition estimation unit 756 may be an example of the reference estimation unit. The condition quantification unit 758 may be an example of the threshold value estimation unit. The data integration unit 760 may be an example of the know-how information generation unit. The question unit 770 may be an example of an abnormality detection unit or a question information generation unit. The question unit 770 may be an example of a cause estimation unit. The question data may be an example of question information.

FIG. 8 schematically shows an example of the internal configuration of the question unit 770. In the present embodiment, the question unit 770 includes, for example, a work abnormality detection unit 822, a vital abnormality detection unit 824, a behavior abnormality detection unit 826, and a question generation unit 830.

In the present embodiment, the work abnormality detection unit 822 determines whether or not the behavior of the worker 40 or the farm work robot 120 estimated by the work content estimation unit 752 deviates from the reference behavior. The work abnormality detection unit 822 outputs information indicating the determination result to the question generation unit 830.

For example, the work abnormality detection unit 822 acquires information indicating the content of one or more actions estimated by the work content estimation unit 752 from the work content estimation unit 752. The work abnormality detection unit 822 accesses the standard data storage unit 354 of the agricultural work management server 142, and acquires information indicating the content of a standard action predetermined for each work item.

The work abnormality detection unit 822 may access the setting data storage unit 372 of the agricultural work management server 142 to acquire information indicating the content of the action independently determined by the worker 40 for each work item. For example, the work abnormality detection unit 822 acquires information indicating the content of a specific action described in the work plan. The work abnormality detection unit 822 may access the know-how database 450 of the know-how management server 146 to acquire the know-how data of the worker 40. The work abnormality detection unit 822 may consider the action independently determined by the worker 40 for each work item and the action defined by the know-how data of the worker 40 as the above-mentioned standard action.

The work abnormality detection unit 822 determines whether or not the degree of difference between the content of one or more actions estimated by the work content estimation unit 752 and the content of the above standard action exceeds a predetermined standard. .. When it is determined that the degree of the above difference exceeds a predetermined standard, the work abnormality detection unit 822 determines that the behavior of the worker 40 deviates from the standard behavior. In this case, the work abnormality detection unit 822 transmits, for example, information indicating that an abnormality (sometimes referred to as a work abnormality) related to the work procedure or content has been detected to the question generation unit 830.

The work abnormality detection unit 822 may transmit information indicating that a work abnormality has been detected to the question generation unit 830 when the position of the worker 40 is included in the field 20. When the position of the worker 40 is not included in the field 20, the work abnormality detection unit 822 does not have to transmit the information indicating that the work abnormality has been detected to the question generation unit 830.

In the present embodiment, the vital abnormality detection unit 824 detects an abnormality related to the worker 40. The vital abnormality detection unit 824 detects an abnormality related to the vital signs of the worker 40 (sometimes referred to as a vital abnormality). For example, when the value or fluctuation pattern of the vital signs of the worker 40 matches a predetermined standard, the vital abnormality detection unit 824 detects the vital abnormality.

When a vital abnormality is detected, the vital abnormality detection unit 824 transmits, for example, information indicating that the vital abnormality has been detected to the question generation unit 830. The vital abnormality detection unit 824 may transmit information indicating that the vital abnormality has been detected to the question generation unit 830 when the position of the worker 40 is included in the field 20. When the position of the worker 40 is not included in the field 20, the vital abnormality detection unit 824 does not have to transmit the information indicating that the vital abnormality has been detected to the question generation unit 830.

In the present embodiment, the behavior abnormality detection unit 826 detects an abnormality related to the behavior of the worker 40. For example, the behavior abnormality detection unit 826 detects at least one of an abnormality related to the remarks of the worker 40 and an abnormality related to the behavior of the worker 40. Abnormalities related to the behavior of the worker 40 include sudden stop, sudden start, yelling, showing a state of panic or upset, stopping for a long time, performing actions that deviate significantly from the work plan or know-how, and standard work. For example, performing work different from that.

Actions that deviate significantly from the work plan or know-how include, for example, (i) the absolute value of the difference between the amount of work specified in the work plan or know-how and the amount of work actually performed is greater than the predetermined value. (Ii) The number of work items that are not carried out according to the procedure specified in the work plan or know-how is larger than the predetermined value. For example, when the absolute value of the difference between the amount of fertilizer or pesticide actually sprayed by the worker 40 and the sprayed amount determined by the work plan is larger than the predetermined value, the work specified in the work plan. It is determined that the absolute value of the difference between the amount and the amount of work actually performed is larger than a predetermined value.

Examples of the work different from the standard work include the work specified by the above-mentioned standard data, the standard action for each work item described above, and the like. For example, when the worker 40 excessively sprays the drug, the behavior abnormality detection unit 826 detects an abnormality related to the behavior of the worker 40.

In the present embodiment, the behavior abnormality detection unit 826 detects an abnormality related to the behavior of the agricultural work robot 120. For example, the behavior abnormality detection unit 826 detects at least one abnormality of the speed, acceleration, and angular acceleration of the agricultural work robot 120. Abnormalities related to the behavior of the agricultural work robot 120 include sudden start, sudden stop, sudden acceleration, sudden deceleration, collision, execution of movements that deviate greatly from the work plan or know-how, and execution of work different from standard work. Illustrated. An action that deviates significantly from the work plan or know-how may be the same as an action that deviates significantly from the work plan or know-how described above. Specific examples of work different from standard work may be as described above. For example, when the agricultural work robot 120 excessively sprays the drug, the behavior abnormality detection unit 826 detects an abnormality related to the behavior of the agricultural work robot 120.

When an abnormality related to the behavior of the worker 40 or the behavior of the farm work robot 120 (sometimes referred to as a behavior abnormality) is detected, the behavior abnormality detection unit 826 indicates, for example, information indicating that the behavior abnormality has been detected. Is transmitted to the question generation unit 830. The speech / behavior abnormality detection unit 826 may transmit information indicating that the speech / behavior abnormality is detected to the question generation unit 830 when the position of the worker 40 is included in the field 20. When the position of the worker 40 is not included in the field 20, the behavior abnormality detection unit 826 does not have to transmit the information indicating that the behavior abnormality has been detected to the question generation unit 830.

In the present embodiment, the question generation unit 830 generates a question regarding the abnormality when the above-mentioned various abnormalities are detected. For example, the question generation unit 830 generates a question for inquiring the worker 40 about the cause or reason of the abnormality. The above question may be a standard question such as "What happened?" Or a question according to the type or content of the detected abnormality, and the situation of the worker 40 or the agricultural work robot 120. It may be a question according to.

In one embodiment, when it is determined that the behavior of the worker 40 deviates from the standard behavior, a question for asking the worker 40 about the reason for the behavior is generated. In another embodiment, when an abnormality related to the vital signs of the worker 40 is detected, a question for inquiring whether or not an abnormality has occurred in the field 20 or the agricultural product 22 and the content of the abnormality is generated. In another embodiment, when an abnormality related to the behavior of the worker 40 or the behavior of the farm work robot 120 is detected, a question for inquiring the worker 40 about the reason for the behavior or behavior is generated.

In the present embodiment, the question generation unit 830 executes a process for presenting the above question to the worker 40. The mode of presenting the question is not particularly limited.

In one embodiment, the question generation unit 830 transmits the question data to the communication terminal 102 of the worker 40 or the farm work robot 120 arranged in the vicinity of the worker 40. When the communication terminal 102 of the worker 40 or the farm work robot 120 arranged in the vicinity of the worker 40 receives the question data, the farm work robot 120 presents the question to the worker 40 by using an arbitrary output device. Examples of the output device include a display, a projector, and a speaker.

In another embodiment, the question generation unit 830 transmits the question data to the agricultural work management server 142. When the farm work management server 142 receives the question data, for example, when the worker 40 executes the input processing of the work record, the farm work management server 142 generates an input screen including the contents of the above question, and the input screen is sent to the worker 40. Present.

In the present embodiment, the question generation unit 830 acquires information indicating the answer of the worker 40 to the above question. For example, the question generation unit 830 acquires the information that the worker 40 has answered to the above question from the communication terminal 102 of the worker 40. The question generation unit 830 may acquire voice data of the worker 40 who answers the above question from the image pickup device 114 or the agricultural work robot 120 arranged in the vicinity of the worker 40.

The question generation unit 830 may generate a new question according to the answer from the worker 40. The question generation unit 830 executes a process for presenting a new question to the worker 40. At this time, the question generation unit 830 may transmit the question data including the above answer or the information related to the question (related information) to the communication terminal 102 or the agricultural work robot 120 used by the worker 40.

Related information includes (i) know-how shown by the know-how data accessible to the worker 40, (ii) the contents described in the work plan of the worker 40, and (iii) the work plan for the field 20 in the vicinity. The contents described in at least one of the work record, the growth record, the harvest record and the shipping record are exemplified. The neighboring field 20 may be the field of the worker 40 or the field of another worker 40.

When various abnormalities related to the worker A are detected, the question generation unit 830 may present a question to the worker A or may present a question to another worker B. For example, when the question generation unit 830 detects various abnormalities related to the worker A and the abnormality is related to the quality or the yield of the agricultural product 22 to be worked by the worker A, the question generation unit 830 may use the question generation unit 830. Present a question to worker A. On the other hand, when various abnormalities related to the worker A are detected and the abnormality is related to the quality or the yield of the agricultural product 22 to be worked by the worker B, the question generation unit 830 asks the worker B. Present the question.

In the present embodiment, the question generation unit 830 determines the question generation process and the question based on at least one of the situation of the worker A in which various abnormalities are detected and the situation of the worker B in which the question is presented. Determine the necessity of presentation processing. The question generation unit 830 may determine the mode of presenting the question based on at least one of the situation of the worker A in which various abnormalities are detected and the situation of the worker B in which the question is presented.

Examples of the above situations include location, status, type of work item being performed, and the like. For example, the question generation unit 830 executes the question generation process and the question generation process only when the worker A exists inside the field 20. As a result, the generation of questions unrelated to the farm work is suppressed, and the consumption of resources of the farm work support system 100 is suppressed.

The work abnormality detection unit 822 may be an example of an abnormality detection unit or a determination unit. The vital abnormality detection unit 824 may be an example of the abnormality detection unit. The behavior abnormality detection unit 826 may be an example of the abnormality detection unit. The question generation unit 830 may be an example of the question information generation unit or the question generation unit. The standard behavior for each work item may be an example of the standard behavior.

In the embodiments described in connection with FIGS. 7 and 8, when the question unit 770 detects an abnormality related to the worker 40, the question unit 770 generates a question for confirming the cause or reason of the abnormality. As an example, an example of a method of constructing know-how data in which the content of the action of the worker 40 or the farm work robot 120 and the condition for the worker 40 or the farm work robot 120 to execute the action are associated with each other has been described. .. However, the know-how data is not limited to this embodiment. Further, the method of constructing the know-how data is not limited to this embodiment.

FIG. 9 schematically shows an example of the internal configuration of the question generation unit 830. In the present embodiment, the question generation unit 830 includes, for example, an abnormality detection signal receiving unit 910, an abnormality level estimation unit 920, a statement content analysis unit 930, an abnormality cause estimation unit 940, a question determination unit 950, and answer acquisition. A unit 960, a coping data generation unit 970, a worker characteristic determination unit 982, and a worker characteristic storage unit 984 are provided.

In the present embodiment, the abnormality detection signal receiving unit 910 receives a signal (sometimes referred to as an abnormality detection signal) indicating that various abnormalities have been detected. When the abnormality detection signal receiving unit 910 receives the abnormality detection signal, the abnormality detection signal receiving unit 910 obtains, for example, information indicating the type of the detected abnormality by the abnormality level estimation unit 920, the statement content analysis unit 930, and the abnormality cause estimation. Output to unit 940. As a result, the question generation process is started.

In one embodiment, the abnormality detection signal receiving unit 910 receives an abnormality detection signal indicating that a work abnormality has been detected from the work abnormality detection unit 822. The above-mentioned abnormality detection signal is, for example, the user ID of the worker 40 performing the work in which the abnormality is detected, the robot ID of the agricultural work robot 120 performing the work in which the abnormality is detected, and the abnormality detected. Includes at least one of the user IDs of the worker 40 using the farm work robot 120 performing the work. The above abnormality detection signal may include information regarding the work in which the abnormality is detected. Information regarding the above work includes (i) at least one of the work item, process and work item, (ii) the time or period during which the work was carried out, and (iii) the location or field where the work was carried out. Etc. are exemplified.

In another embodiment, the abnormality detection signal receiving unit 910 receives an abnormality detection signal indicating that the vital abnormality has been detected from the vital abnormality detecting unit 824. The above-mentioned abnormality detection signal includes, for example, the user ID of the worker 40 in which the abnormality is detected. The above abnormality detection signal may include information regarding vital signs in which an abnormality is detected. Examples of the above-mentioned information regarding vital signs include the types of vital signs and the numerical values of vital signs.

In still another embodiment, the abnormality detection signal receiving unit 910 receives an abnormality detection signal indicating that the behavior abnormality has been detected from the behavior abnormality detection unit 826. The above abnormality detection signal is, for example, a work using the user ID of the worker 40 in which the abnormality is detected, the robot ID of the agricultural work robot 120 in which the abnormality is detected, and the agricultural work robot 120 in which the abnormality is detected. Includes at least one of the user IDs of the person 40. The above-mentioned abnormality detection signal may include information regarding the behavior in which the abnormality is detected. The above-mentioned information regarding words and actions includes the content of the statement of the worker 40, the psychological state or type of the worker 40 at the time of the statement, the content or type of the action of the worker 40, and the content or type of the action of the agricultural work robot 120. Etc. are exemplified.

The psychological state of the worker 40 at the time of speaking is determined, for example, based on the vital signs of the worker 40 or the analysis result of the speaking. The psychological state of the worker 40 at the time of speech is, for example, the type of exclamation word included in the speech of the worker 40, the volume of the speech, the intonation pattern of the speech, and at least the vital sign of the worker 40 at the time of speech. Determined on the basis of one.

In the present embodiment, the abnormality level estimation unit 920 estimates the degree of the detected abnormality. The abnormality level estimation unit 920 estimates the degree of the abnormality based on, for example, the type of the detected abnormality and at least one of the contents of the abnormality. The degree of anomaly is determined, for example, depending on the magnitude of the effect that the anomaly can have on at least one of the quality and yield of produce 22. For example, the abnormality level estimation unit 920 determines the degree of abnormality so that the greater the influence that can affect at least one of the quality and the yield of the agricultural product 22, the greater the degree of abnormality. Thereby, the degree of abnormality can be estimated.

The anomaly level estimation unit 920 may estimate the degree of anomaly using an estimation model generated by machine learning. For example, the anomaly level estimation unit 920 uses an anomaly detection signal using an estimation model generated by machine learning to estimate the degree of the anomaly from a feature amount indicating at least one of the type of anomaly and the content of the anomaly. The degree of abnormality is output from at least one of the type of abnormality indicated by and the content of the abnormality.

The abnormality level estimation unit 920 may estimate the degree of the detected abnormality based on the analysis result of the vital signs or remarks of the worker 40. For example, the abnormality level estimation unit 920 first analyzes the vital signs or utterances of the worker 40 to estimate the degree of abnormality (sometimes referred to as a subjective level) felt by the worker 40.

The subjective level is determined, for example, by whether at least one of the vital sign values and the variation pattern meets the predetermined criteria corresponding to each of the one or more levels. The subjective level is, for example, whether at least one of the types of exclamation words contained in the remark, the volume of the remark, and the intonation pattern of the remark meets the predetermined criteria according to each of the one or more levels. Is determined by.

The above subjective level may be an index indicating the psychological state of the worker 40. Examples of the psychological state of the worker 40 include a positive psychological state and a negative psychological state. Examples of positive psychological states include joy and enjoyment. Examples of negative psychological states include anger, sadness, anxiety, worry, remorse, fear, and startle.

Next, the abnormality level estimation unit 920 converts, for example, the above subjective level into an objectively evaluable degree of abnormality (sometimes referred to as an objective level). As mentioned above, the objective level is determined, for example, depending on the magnitude of the effect that the anomaly can have on at least one of the quality and yield of produce 22.

For example, the abnormality level estimation unit 920 refers to the worker characteristic storage unit 984 and has one or more parameters (referred to as worker characteristics) for converting the subjective level of the worker 40 into an objective level. In some cases.) Is obtained. Each of the above one or more parameters may be one or more coefficients contained in a function or model used to transform a subjective level into an objective level. The abnormality level estimation unit 920 converts the subjective abnormality level felt by the worker 40 into an objective abnormality level by using the above-mentioned one or more parameters.

The abnormality level estimation unit 920 outputs information indicating the estimated degree of abnormality to at least one of the question determination unit 950 and the question determination unit 950, for example. In the abnormality level estimation unit 920, the information indicating the degree of the abnormality may be information indicating a subjective level or information indicating an objective level.

In the present embodiment, the remark content analysis unit 930 analyzes the remark content of the worker 40. For example, the speech content analysis unit 930 acquires voice data in which the voice of the worker 40 is recorded. The remark content analysis unit 930 analyzes the voice of the worker 40 recorded in the voice data, and estimates (i) the event that causes the abnormality and (ii) the participants involved in the event. The above-mentioned participants may include a worker 40 who has spoken (sometimes referred to as a worker A), and one or more other workers 40 (with a worker B) different from the worker 40 who has spoken. It may be referred to.).

In one embodiment, when the worker A discovers that the pest is attached to the agricultural product 22 (sometimes referred to as the agricultural product X) cultivated in the field 20 of the worker A, the worker An abnormality is detected in A's vital signs. In this case, (i) the event that causes the abnormality is that the pest is attached to the agricultural product X, and (ii) the person involved in the event is worker A.

In another embodiment, when the worker A says "Oh, that's no good" while observing the state of the farm work of the worker B, an abnormality is detected in the statement of the worker A. In this case, (i) the event that causes the abnormality is the agricultural product 22 (sometimes referred to as agricultural product Y) cultivated in the field 20 of the worker B, or the behavior of the worker B. (Ii) The person involved in the event is worker B.

The remark content analysis unit 930 is based on the information indicating the analysis result of the remarks of the worker 40 and the information regarding the work of the worker A and the worker B, (i) an event causing an abnormality, and (ii). ) At least one of the participants involved in the event may be estimated. Examples of work-related information include work plans, work logs, action logs, work records, growth records, harvest records, and shipping records.

For example, the remark content analysis unit 930 analyzes the remark content of the worker A and estimates at least one of the position, work content, and status of the above-mentioned participants. The statement content analysis unit 930 analyzes the information recorded in the work plan, work log, or action log, and obtains at least one of the current position, current work content, and current status of each of one or more workers 40. Get the information shown. The remark content analysis unit 930 acquires information indicating at least one of the positions, work contents, and status of one or more workers 40 at a specific time based on the information recorded in the work record or the growth record. You may. The remark content analysis unit 930 extracts a worker 40 that matches at least one of the position, work content, and status of the participant estimated by the analysis of the remark content as the participant or a candidate thereof.

As a result, the statement content analysis unit 930 determines, for example, whether or not the abnormality indicated by the abnormality detection signal received by the abnormality detection signal receiving unit 910 is caused by the agricultural product X which is the target of the work of the worker A. be able to. Further, the statement content analysis unit 930 determines whether the abnormality indicated by the abnormality detection signal received by the abnormality detection signal receiving unit 910 is caused by the agricultural product X of the worker A or the agricultural product Y of the other worker B. Can be determined. Whether or not the above abnormality is caused by agricultural product X or agricultural product Y may be an example of an event that causes the abnormality.

The statement content analysis unit 930 may estimate an event that causes an abnormality by using an estimation model generated by machine learning. Further, the speech content analysis unit 930 may estimate the participants involved in the event by using the estimation model generated by machine learning.

For example, the speech content analysis unit 930 was generated by machine learning to estimate (i) an event that causes an abnormality and (ii) at least one of the participants involved in the event from the feature amount of the speech content. Using the estimation model, from the voice data recorded by the voice of the worker 40 or the text data of the voice, (i) at least one of the event causing the abnormality and (ii) the participants involved in the event is shown. Output information. The remark content analysis unit 930 is based on the feature amount of the remark content and the information related to the above-mentioned work (work plan, work log, action log, etc.), (i) an event causing an abnormality and (ii). Using an estimation model generated by machine learning to estimate at least one of the participants involved in the event, the voice data of the worker 40 or the text data of the voice and the text data of the voice are present in the field 20. From the information on the work of one or more workers 40, information indicating (i) an event causing an abnormality and (ii) at least one of the participants involved in the event is output.

The remark content analysis unit 930 outputs (i) information indicating the event causing the abnormality and (ii) the party involved in the event to the abnormality cause estimation unit 940. The statement content analysis unit 930 may output information indicating whether or not the above abnormality is caused by the agricultural product X to the abnormality cause estimation unit 940. Information indicating whether or not the above abnormality is caused by the agricultural product Y may be output to the abnormality cause estimation unit 940.

In the present embodiment, the abnormality cause estimation unit 940 estimates the cause of the abnormality indicated by the abnormality detection signal received by the abnormality detection signal reception unit 910. In one embodiment, the abnormality cause estimation unit 940 may estimate the cause of the above abnormality based on the content of the statement of the worker A in the period including the time when the abnormality is detected. For example, the abnormality cause estimation unit 940 determines that the event that causes the abnormality estimated by the statement content analysis unit 930 is the cause of the above abnormality.

In another embodiment, the abnormality cause estimation unit 940 may estimate the cause of the abnormality based on an image in which the state of the worker A during the period including the time when the abnormality is detected is recorded. The abnormality cause estimation unit 940 may estimate the cause of the abnormality based on the image in which the state of the worker A is recorded and the image in which the state of the worker B is recorded in the above period. For example, the abnormality cause estimation unit 940 determines that the behavior of the worker A and the state of the agricultural product 22 that is the work target of the worker A are the causes of the above abnormality. For example, when the worker A is facing the direction of the worker B, the abnormality cause estimation unit 940 determines that the behavior of the worker B and the state of the agricultural product 22 which is the work target of the worker B are the above-mentioned abnormalities. Determined to be the cause.

In still another embodiment, the abnormality cause estimation unit 940 may estimate the cause of the above abnormality based on the work plan, work log, and action log of the worker A during the period including the time when the abnormality is detected. .. For example, in the abnormality cause estimation unit 940, the work plan of the worker A, the behavior of the worker A indicated by the work log or the action log, and the state of the agricultural product 22 which is the work target of the worker A are described above. Determined to be the cause of the abnormality.

The abnormality cause estimation unit 940 may estimate the cause of the above abnormality based on the work plan, work log, and action log of the worker 40 other than the worker A during the period including the time when the abnormality is detected. For example, the abnormality cause estimation unit 940 estimates the cause of the above abnormality based on the work plan, work log, and action log of the participants estimated by the statement content analysis unit 930. More specifically, the abnormality cause estimation unit 940 describes the behavior of the participant indicated by the work plan, work log or action log of the participant, and the state of the agricultural product 22 which is the work target of the participant. Judged as the cause of the abnormality.

In still another embodiment, the abnormality cause estimation unit 940 may estimate the cause of the above abnormality based on the degree of abnormality estimated by the abnormality level estimation unit 920. For example, the abnormality cause estimation unit 940 first determines the degree of abnormality caused by each of the events presumed to be the cause of the abnormality in the above-mentioned one or more embodiments. Next, the abnormality cause estimation unit 940 determines that an event that causes an abnormality having the same or similar degree as the degree of abnormality estimated by the abnormality level estimation unit 920 is the cause of the above abnormality.

In the above embodiment, the details of the abnormality cause estimation unit 940 have been described by taking as an example the case where the abnormality cause estimation unit 940 estimates the cause of the abnormality based on the information at the time when the abnormality is detected. However, the abnormality cause estimation unit 940 is not limited to the above embodiment. In another embodiment, the abnormality cause estimation unit 940 estimates the cause of the abnormality based on the information at the time before the time when the abnormality is detected.

For example, the abnormality cause estimation unit 940 first acquires information on the work of another worker 40 who has performed the same or similar work as the worker A before the time when the above abnormality is detected. Next, the abnormality cause estimation unit 940 estimates the cause of the abnormality based on the contents of the work of the other worker 40 described above. The work of the other worker 40 may be extracted from the work performed at a position where the distance from the position of the worker A at the time when the abnormality is detected is smaller than a predetermined value.

More specifically, the abnormality cause estimation unit 940 accesses, for example, the agricultural work management server 142, and the worker C cultivating the agricultural product X in the field 20 arranged in the vicinity of the field 20 of the worker A. Obtain work records or growth records of. When it is recorded in the above work record or growth record that a pest has occurred, the abnormality cause estimation unit 940 presumes that the cause of the abnormality related to the worker A is the occurrence of the pest. Similarly, the abnormality cause estimation unit 940 may access the farm work management server 142 and acquire the work plan of the worker C. In this case, when the plan to spray the pesticide is recorded in the above work plan, the abnormality cause estimation unit 940 estimates that the cause of the abnormality related to the worker A is the occurrence of pests.

The method by which the abnormality cause estimation unit 940 estimates the cause of the abnormality is not limited to these embodiments. For example, the abnormality cause estimation unit 940 estimates the cause of the abnormality by combining the above-mentioned plurality of embodiments. The abnormality cause estimation unit 940 may estimate the cause of the abnormality by using the estimation model generated by machine learning. For example, the abnormality cause estimation unit 940 may include (i) a feature amount of the worker's remarks, (ii) a feature amount of an image in which the state of the worker is captured, and (iii) information (work) related to the above-mentioned work. (I) The voice of the worker 40 was recorded using an estimation model generated by machine learning to estimate the cause of the anomaly from at least one of the plan, work log, action log, etc.). At least one of voice data or text data of the voice, (ii) image data in which the state of work of the worker 40 is recorded, and (iii) information on the work of one or more workers 40 existing in the field 20. Outputs information indicating the cause of the abnormality.

In the present embodiment, the question determination unit 950 generates question data. The question determination unit 950 transmits question data to at least one of the communication terminal 102 and the agricultural work robot 120 used by the worker 40. The question determination unit 950 may send question data to the farm work management server 142.

The question determination unit 950 starts the process of generating question data for the specific worker 40 in response to the abnormality detection signal receiving unit 910 receiving the abnormality detection signal for the specific worker 40. When the position of the specific worker 40 is not included in the field 20, the question determination unit 950 does not have to execute the question generation process and the question transmission process, and the question determination unit 950 performs the question transmission process. You don't have to do it.

Thereby, if the position of the worker 40 is within a predetermined geographical range, a question is generated or transmitted, and if the position of the worker 40 is not within the geographical range, the question is asked. Is not generated or transmitted. As a result, the consumption of resources of the agricultural work support system 100 can be suppressed.

In the present embodiment, the question determination unit 950 determines at least one of (i) the worker 40 in which the question is presented, (ii) the content of the question, and (iii) the presentation mode of the question. For example, the question determination unit 950 determines the participants estimated by the remark content analysis unit 930 as the worker 40 to which the question is presented. More specifically, when the abnormality relating to the worker A is caused by the agricultural product X, the question determination unit 950 decides to present the question to the worker A. On the other hand, when the abnormality regarding the worker A is caused by the agricultural product Y, the question determination unit 950 decides to present the question to the worker B.

For example, the question determination unit 950 determines the content of the question based on the cause estimated by the abnormality cause estimation unit 940. The question determination unit 950 may determine the content of the question based on whether or not the abnormality related to the worker A is caused by the agricultural product X, and is based on whether or not the abnormality related to the worker A is caused by the agricultural product Y. You may decide the content of the question. If the abnormality cause estimation unit 940 cannot estimate the cause of the abnormality, or if the accuracy of the abnormality cause estimated by the abnormality cause estimation unit 940 does not meet the predetermined criteria, the question determination unit 950. May determine the content of the question from a predetermined fixed phrase.

In another embodiment, the question determination unit 950 determines the content of the new question based on the answer to the previous question. For example, when the cause of the abnormality is identified by the response from the worker 40, the question determination unit 950 describes the action taken by the worker 40 for the worker 40 in order to deal with the cause of the above abnormality. Generate a new question to get information that indicates. When the question determination unit 950 identifies an action for coping with the cause of the abnormality from the response from the worker 40, the question determination unit 950 selects the action for the worker 40 as to the reason why the worker 40 selects the action. Generate a new question to query.

For example, the question determination unit 950 determines whether or not to present the question in real time or whether or not to present the question after the fact. For example, if the status of the worker 40 on which the question is presented is working, or if the position of the worker 40 on which the question is presented is contained within the field 20, the question determination unit 950 asks the question in real time. Decide to present. For example, in cases other than the above, the question determination unit 950 decides to present the question after the fact.

When it is determined to present the question in real time, the question determination unit 950 transmits the question data to, for example, the communication terminal 102 or the agricultural work robot 120 used by the worker 40 to whom the question is presented. On the other hand, when it is decided to present the question after the fact, the question determination unit 950 transmits the question data to the agricultural work management server 142. When the input screen generation unit 320 of the agricultural work management server 142 generates the input screen of the work record, the question determination unit 950 issues an instruction for generating an input screen including the content of the question indicated by the question data. It may be transmitted to the management server 142.

In the present embodiment, the answer acquisition unit 960 acquires information indicating the content of the answer from the worker 40 who is presented with the question. The answer acquisition unit 960 outputs information indicating the content of the answer to, for example, at least one of the question determination unit 950 and the coping data generation unit 970.

In the present embodiment, the coping data generation unit 970 is information obtained from the worker 40 who is presented with a question from, for example, the answer acquisition unit 960, and is the information obtained from the worker 40 in order to deal with the cause of the above abnormality. Acquires information indicating the content of the actions taken by. The coping data generation unit 970 generates information (sometimes referred to as coping data) in which the information indicating the content of the above action and the information indicating the cause of the above abnormality are associated with each other. The coping data generation unit 970 may generate coping data in which information indicating the content of the above action, information indicating the cause of the above abnormality, and information indicating the content of the answer to the question are associated with each other. The cause of the above abnormality may be (i) an event estimated by the abnormality cause estimation unit 940, and (ii) the event answered by the worker 40 who was presented with the question as the cause of the above abnormality. You may.

The coping data generation unit 970 outputs the coping data to the know-how data generation unit 440. The know-how data generation unit 440 may generate know-how data by using the coping data. The cause of the anomaly included in the coping data and / or the reason why the worker 40 chose an action is a criterion for determining whether or not the action taken by the worker 40 to deal with the anomaly should be executed. The condition is shown. As a result, the know-how data generation unit 440 can generate more accurate know-how data.

In the present embodiment, the worker characteristic determination unit 982 determines one or more parameters (sometimes referred to as worker characteristics) for converting the subjective level of the worker 40 into an objective level. do. The worker characteristic determination unit 982 may determine the above-mentioned one or more parameters for each of the one or more workers 40.

As mentioned above, each of the above one or more parameters may be one or more coefficients contained in the function or model used to convert the subjective level to the objective level. The above parameters are, for example, (i) the type of exclamation word included in the remark of the worker 40, the volume of the remark, the intonation pattern of the remark, and the vital sign of the worker 40 at the time of remark regarding a plurality of cases. It is determined based on the correlation between at least one of the above and (ii) the level of anomaly.

In the present embodiment, the worker characteristic storage unit 984 stores the worker characteristics determined by the worker characteristic determination unit 982. For example, the worker characteristic storage unit 984 extracts the worker characteristics of the worker 40 indicated by the request in response to the request from the abnormality level estimation unit 920, and outputs the extraction result to the abnormality level estimation unit 920.

The abnormality detection signal receiving unit 910 may be an example of a vital abnormality detecting unit or a tracking abnormality detecting unit. The statement content analysis unit 930 may be an example of an object determination unit. The abnormality cause estimation unit 940 may be an example of a vital information acquisition unit, a follow-up information acquisition unit, or a cause estimation unit. The question determination unit 950 may be an example of the question generation unit. The coping data generation unit 970 may be an example of the behavior information collection unit or the coping information generation unit. The coping data may be an example of coping information. Agricultural products 22 may be the target of agricultural work. Agricultural product X may be an example of the first object. Agricultural product Y may be an example of the second object.

The question unit 770 may be an example of an information processing device. The vital abnormality detection unit 824 may be an example of a vital information acquisition unit or a vital abnormality detection unit. The behavior abnormality detection unit 826 may be an example of a tracking information acquisition unit or a tracking abnormality detection unit. The question generation unit 830 may be an example of an information processing device or a question generation unit.

FIG. 10 shows an example of a computer 3000 in which a plurality of aspects of the present invention may be embodied in whole or in part. At least a part of the agricultural work support system 100 may be realized by the computer 3000. For example, at least a part of the farm work management server 142 is realized by the computer 3000. For example, at least a part of the know-how management server 146 is realized by the computer 3000. At least a part of the agricultural work robot 120 may be realized by the computer 3000. At least a part of the communication terminal 102 may be realized by the computer 3000.

The program installed on the computer 3000 causes the computer 3000 to function as one or more "parts" of the operation or the device associated with the device according to the embodiment of the invention, or the operation or the one or more "parts". A unit can be run and / or a computer 3000 can be run a process according to an embodiment of the invention or a step in the process. Such a program may be executed by the CPU 3012 to cause the computer 3000 to perform a specific operation associated with some or all of the blocks of the flowcharts and block diagrams described herein.

The computer 3000 according to this embodiment includes a CPU 3012, a RAM 3014, a GPU 3016, and a display device 3018, which are interconnected by a host controller 3010. The computer 3000 also includes an input / output unit such as a communication interface 3022, a hard disk drive 3024, a DVD-ROM drive 3026, and an IC card drive, which are connected to the host controller 3010 via the input / output controller 3020. The computer also includes legacy input / output units such as ROM 3030 and keyboard 3042, which are connected to the input / output controller 3020 via an input / output chip 3040.

The CPU 3012 operates according to a program stored in the ROM 3030 and the RAM 3014, thereby controlling each unit. The GPU 3016 acquires the image data generated by the CPU 3012 in a frame buffer or the like provided in the RAM 3014 or itself so that the image data is displayed on the display device 3018.

The communication interface 3022 communicates with other electronic devices via the network. The hard disk drive 3024 stores programs and data used by the CPU 3012 in the computer 3000. The DVD-ROM drive 3026 reads the program or data from the DVD-ROM 3001 and provides the program or data to the hard disk drive 3024 via the RAM 3014. The IC card drive reads the program and data from the IC card and / or writes the program and data to the IC card.

The ROM 3030 stores in it a boot program or the like executed by the computer 3000 at the time of activation, and / or a program depending on the hardware of the computer 3000. The input / output chip 3040 may also connect various input / output units to the input / output controller 3020 via a parallel port, a serial port, a keyboard port, a mouse port, and the like.

The program is provided by a computer-readable storage medium such as a DVD-ROM 3001 or an IC card. The program is read from a computer-readable storage medium, installed in a hard disk drive 3024, RAM 3014, or ROM 3030, which is also an example of a computer-readable storage medium, and executed by the CPU 3012. The information processing described in these programs is read by the computer 3000 and provides a link between the program and the various types of hardware resources described above. The device or method may be configured to implement the operation or processing of information in accordance with the use of computer 3000.

For example, when communication is executed between the computer 3000 and an external device, the CPU 3012 executes a communication program loaded in the RAM 3014, and performs communication processing on the communication interface 3022 based on the processing described in the communication program. You may order. Under the control of the CPU 3012, the communication interface 3022 reads and reads transmission data stored in a transmission buffer area provided in a recording medium such as a RAM 3014, a hard disk drive 3024, a DVD-ROM 3001, or an IC card. The data is transmitted to the network, or the received data received from the network is written to the reception buffer area or the like provided on the recording medium.

Further, the CPU 3012 makes the RAM 3014 read all or necessary parts of the file or the database stored in the external recording medium such as the hard disk drive 3024, the DVD-ROM drive 3026 (DVD-ROM3001), and the IC card. Various types of processing may be performed on the data on the RAM 3014. The CPU 3012 may then write back the processed data to an external recording medium.

Various types of information such as various types of programs, data, tables, and databases may be stored in recording media and processed. The CPU 3012 describes various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, and information retrieval described in various parts of the present disclosure with respect to the data read from the RAM 3014. Various types of processing may be performed, including / replacement, etc., and the results are written back to RAM 3014. Further, the CPU 3012 may search for information in a file, database, or the like in the recording medium. For example, when a plurality of entries each having an attribute value of the first attribute associated with the attribute value of the second attribute are stored in the recording medium, the CPU 3012 is the first of the plurality of entries. The attribute value of the attribute of is searched for the entry that matches the specified condition, the attribute value of the second attribute stored in the entry is read, and the attribute value of the second attribute is changed to the first attribute that satisfies the predetermined condition. You may get the attribute value of the associated second attribute.

The program or software module described above may be stored on or near computer 3000 in a computer-readable storage medium. Further, a recording medium such as a hard disk or RAM provided in a dedicated communication network or a server system connected to the Internet can be used as a computer-readable storage medium, whereby the above program can be transmitted via the network. Provided to computer 3000.

Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes or improvements can be made to the above embodiments. Further, to the extent that there is no technical contradiction, the matters described for the specific embodiment can be applied to other embodiments. It is clear from the description of the claims that the form with such changes or improvements may be included in the technical scope of the present invention.

The order of execution of each process such as operation, procedure, step, and step in the apparatus, system, program, and method shown in the claims, specification, and drawings is particularly "before" and "prior to". It should be noted that it can be realized in any order unless the output of the previous process is used in the subsequent process. Even if the scope of claims, the specification, and the operation flow in the drawings are explained using "first", "next", etc. for convenience, it means that it is essential to carry out in this order. It's not a thing.

For example, the specification of the present application discloses the following matters.
[Item A-1]
One or more performed by the worker during the implementation period of the work, based on (i) the voice of the worker performing the work and (ii) at least one of the appearances of the work by the worker. The behavior estimation unit that estimates behavior and the behavior estimation unit
(I) The voice of the worker, (ii) the state of the work, (iii) the matters input in the work record of the work, and (iv) at least one of the states of the work environment of the work. Based on this, the standard estimation unit that estimates the conditions that serve as the criteria for determining whether or not the above action should be executed, and the standard estimation unit.
An information processing device equipped with.
[Item A-2]
It further includes a know-how information generation unit that generates know-how information in which each of the above-mentioned one or more actions estimated by the above-mentioned behavior estimation unit and the above-mentioned conditions for each action estimated by the above-mentioned reference estimation unit are associated with each other.
The information processing apparatus according to item A-1.
[Item A-3]
The above know-how information is
(A) Information indicating the contents of one or more of the above conditions and
(B) (i) The content of the above action when each of the above 1 or more conditions is satisfied, and (ii) the content of the above action when each of the above 1 or more conditions is not satisfied. Information to show and
including,
The information processing apparatus according to item A-2.
[Item A-4]
The know-how information generation unit generates the know-how information regarding at least one of one or more work items included in at least one of one or more steps for producing an agricultural product.
The information processing apparatus according to item A-2 or item A-3.
[Item A-5]
It is determined whether or not the degree of difference between the content of one or more actions estimated by the behavior estimation unit and the content of one or more standard actions predetermined for each work item exceeds a predetermined standard. Judgment unit and
A question information generation unit that generates question information for inquiring the worker about the reason for the difference when it is determined that the degree of the difference exceeds the predetermined standard.
Further prepare,
The information processing apparatus according to item A-4.
[Item A-6]
Anomaly detection unit that detects anomalies related to the above workers,
When the above abnormality is detected, a question information generation unit that generates question information for inquiring the worker about the reason for the abnormality, and a question information generation unit.
Further prepare,
The information processing apparatus according to any one of items A-1 to A-4.
[Item A-7]
A data acquisition unit that acquires at least one of the voice data in which the voice of the worker performing the work is recorded and the image data in which the state of the work by the worker is captured.
The editorial department that cuts a part of the audio data and the image data,
Further prepare,
The information processing apparatus according to any one of items A-1 to A-6.
[Item A-8]
In the voice data and the image data, the editorial unit is (i) a position where the voice of the worker is recorded, and (ii) a position where one or more actions estimated by the action estimation unit are recorded. Cut a part of the audio data and the image data so that
The information processing apparatus according to item A-7.
[Item A-9]
The above image data is
The data of the captured image and
Information indicating the gaze position of the above worker and
Including
The editorial unit generates a composite image in which the image and the icon indicating the gaze position of the worker are combined.
The information processing apparatus according to item A-7 or item A-8.
[Item A-10]
The above standard estimation unit
A threshold value estimation unit that estimates a threshold value as a criterion for determining whether or not the action should be executed based on at least one of the items input in the work record of the work and the state of the work environment of the work.
Have,
The information processing apparatus according to any one of items A-1 to A-9.
[Item A-11]
A program for making a computer function as an information processing device according to any one of items A-1 to A-11.
[Item A-12]
One or more performed by the worker during the implementation period of the work, based on (i) the voice of the worker performing the work and (ii) at least one of the appearances of the work by the worker. The behavior estimation stage for estimating behavior and the behavior estimation stage
(I) The voice of the worker, (ii) the state of the work, (iii) the matters input in the work record of the work, and (iv) at least one of the states of the work environment of the work. Based on the criteria estimation stage that estimates the conditions that serve as the criteria for determining whether or not the above actions should be performed,
Information processing method.

[Item B-1]
The vital information acquisition department that acquires information indicating the vital signs of the worker who carries out the work,
The vital abnormality detection unit that detects the abnormality of the vital signs acquired by the vital information acquisition unit, and the vital abnormality detection unit.
When the vital abnormality detection unit detects an abnormality in the vital signs, a question generation unit that generates a question regarding the abnormality, and a question generation unit.
An information processing device equipped with.
[Item B-2]
Further equipped with a cause estimation unit for estimating the cause of the above abnormality,
The question generation unit determines the content of the question based on the cause estimated by the cause estimation unit.
The information processing apparatus according to item B-1.
[Item B-3]
Further equipped with an action information collecting unit for acquiring information indicating the contents of actions taken by the worker in order to deal with the above causes.
The information processing apparatus according to item B-2.
[Item B-4]
It further includes a coping information generation unit that generates coping information in which the information indicating the content of the behavior acquired by the behavior information collecting unit and the information indicating the cause estimated by the cause estimation unit are associated with each other.
The information processing apparatus according to item B-3.
[Item B-5]
The question generation unit generates a question for asking the worker why the worker chose the action.
The above-mentioned handling information generation unit
(I) As the information indicating the cause estimated by the cause estimation unit, the above-mentioned coping information including the information indicating the contents of the answer to the above-mentioned question, or the above-mentioned coping information, or
(Ii) The information indicating the content of the behavior acquired by the behavior information collecting unit, the information indicating the cause estimated by the cause estimation unit, and the information indicating the content of the answer to the question are associated with each other. Generate action information,
The information processing apparatus according to item B-4.
[Item B-6]
The cause estimation unit has an object determination unit that determines whether or not the abnormality is caused by the first object that is the object of the worker's work.
The question generation unit determines the content of the question based on whether or not the abnormality is caused by the first object.
The information processing apparatus according to any one of items B-2 to B-5.
[Item B-7]
The object judgment unit is
Acquire the voice data in which the voice of the above worker is recorded,
Analyzing the above-mentioned voice of the above-mentioned worker recorded in the above-mentioned voice data,
(I) Estimate the event that causes the above abnormality and (ii) the participants involved in the above event.
The information processing apparatus according to item B-6.
[Item B-8]
The above cause estimation unit is
Prior to the time when the above abnormality was detected, information on the work of other workers who performed the same or similar work as the above worker was acquired.
The cause of the above abnormality is estimated based on the contents of the above work of the above other workers.
The information processing apparatus according to any one of items B-2 to B-7.
[Item B-9]
The work of the other worker is extracted from the work performed at a position where the distance from the position of the worker at the time when the abnormality is detected is smaller than a predetermined value.
The information processing apparatus according to item B-8.
[Item B-10]
The above question generator
If the worker's location is within a predetermined geographic range, generate the question and generate the question.
If the worker's location is not within the geographic range, do not generate the question,
The information processing apparatus according to any one of items B-1 to B-9.
[Item B-11]
A program for making a computer function as an information processing device according to any one of items B-1 to B-10.
[Item B-12]
The vital information acquisition stage to acquire information indicating the vital signs of the worker who carries out the work, and
The vital abnormality detection stage for detecting the abnormality of the vital signs acquired in the vital information acquisition stage, and the vital abnormality detection stage.
When the vital sign abnormality is detected in the vital abnormality detection stage, the question generation stage for generating a question regarding the abnormality and the question generation stage.
Information processing method.

[Item C-1]
A tracking information acquisition unit that acquires information indicating at least one of the speed, acceleration, and angular acceleration of a moving body that moves following the worker performing the work.
A tracking abnormality detecting unit that detects at least one abnormality of the speed, the acceleration, and the angular acceleration acquired by the tracking information acquisition unit.
A question generation unit that generates a question regarding the abnormality when the tracking abnormality detection unit detects at least one abnormality of the speed, the acceleration, and the angular acceleration.
An information processing device equipped with.
[Item C-2]
Further equipped with a cause estimation unit for estimating the cause of the above abnormality,
The question generation unit determines the content of the question based on the cause estimated by the cause estimation unit.
The information processing apparatus according to item C-1.
[Item C-3]
Further equipped with an action information collecting unit for acquiring information indicating the contents of actions taken by the worker in order to deal with the above causes.
The information processing apparatus according to item C-2.
[Item C-4]
It further includes a coping information generation unit that generates coping information in which the information indicating the content of the behavior acquired by the behavior information collecting unit and the information indicating the cause estimated by the cause estimation unit are associated with each other.
The information processing apparatus according to item C-3.
[Item C-5]
The question generation unit generates a question for asking the worker why the worker chose the action.
The above-mentioned handling information generation unit
(I) As the information indicating the cause estimated by the cause estimation unit, the above-mentioned coping information including the information indicating the contents of the answer to the above-mentioned question, or the above-mentioned coping information, or
(Ii) The information indicating the content of the behavior acquired by the behavior information collecting unit, the information indicating the cause estimated by the cause estimation unit, and the information indicating the content of the answer to the question are associated with each other. Generate action information,
The information processing apparatus according to item C-4.
[Item C-6]
The cause estimation unit has an object determination unit that determines whether or not the abnormality is caused by the first object that is the object of the worker's work.
The question generation unit determines the content of the question based on whether or not the abnormality is caused by the first object.
The information processing apparatus according to any one of items C-2 to C-5.
[Item C-7]
The object judgment unit is
Acquire the voice data in which the voice of the above worker is recorded,
Analyzing the above-mentioned voice of the above-mentioned worker recorded in the above-mentioned voice data,
(I) Estimate the event that causes the above abnormality and (ii) the participants involved in the above event.
The information processing apparatus according to item C-6.
[Item C-8]
The above cause estimation unit is
Prior to the time when the above abnormality was detected, information on the work of other workers who performed the same or similar work as the above worker was acquired.
The cause of the above abnormality is estimated based on the contents of the above work of the above other workers.
The information processing apparatus according to any one of items C-2 to C-7.
[Item C-9]
The work of the other worker is extracted from the work performed at a position where the distance from the position of the worker at the time when the abnormality is detected is smaller than a predetermined value.
The information processing apparatus according to item C-8.
[Item C-10]
The above question generator
If the worker's location is within a predetermined geographic range, generate the question and generate the question.
If the worker's location is not within the geographic range, do not generate the question,
The information processing apparatus according to any one of items C-1 to C-9.
[Item C-11]
A program for making a computer function as an information processing device according to any one of items C-1 to C-10.
[Item C-12]
A follow-up information acquisition stage for acquiring information indicating at least one of the speed, acceleration, and angular acceleration of a moving body that moves following the worker performing the work.
A follow-up abnormality detection step for detecting at least one abnormality of the speed, the acceleration, and the angular acceleration acquired in the follow-up information acquisition step, and the follow-up abnormality detection step.
When at least one abnormality of the speed, the acceleration, and the angular acceleration is detected in the tracking abnormality detection stage, a question generation stage for generating a question regarding the abnormality, and a question generation stage.
Information processing method.

10 communication network, 20 fields, 22 agricultural products, 40 workers, 50 consumers, 100 agricultural work support system, 102 communication terminals, 114 imaging equipment, 116 measuring equipment, 120 agricultural work robots, 130 base units, 132 mobile units, 134 imaging units 136 sensor unit, 138 agricultural work unit, 142 agricultural work management server, 144 weather information management server, 146 know-how management server, 148 matching service management server, 220 control unit, 222 control program, 224 OS, 226 driver, 230 power supply unit, 250. Vibration control unit, 280 balance adjustment unit, 294 firmware, 310 input reception unit, 320 screen generation unit, 330 work plan generation unit, 340 storage unit, 352 log data storage unit, 354 standard data storage unit, 362 work record storage unit 364 Growth record storage unit, 366 Harvest record storage unit, 368 Shipment record storage unit, 372 Setting data storage unit, 374 Evaluation data storage unit, 422 Work plan acquisition unit, 432 Audio data acquisition unit, 434 Image data acquisition unit, 436 History data acquisition unit, 438 environmental data acquisition unit, 440 know-how data generation unit, 450 know-how database, 460 request reception unit, 470 request processing unit, 500 data table, 502 information, 504 information, 506 information, 508 information, 600 flowchart, 720 text data generation unit, 730 data editing unit, 740 shared setting unit, 752 work content estimation unit, 754 purpose estimation unit, 756 condition estimation unit, 758 condition quantification unit, 760 data integration unit, 770 question unit, 822 work abnormality Detection unit, 824 vital abnormality detection unit, 826 behavior abnormality detection unit, 830 question generation unit, 910 abnormality detection signal reception unit, 920 abnormality level estimation unit, 930 speech content analysis unit, 940 abnormality cause estimation unit, 950 question determination unit, 960 answer acquisition unit, 970 response data generation unit, 982 worker characteristic determination unit, 984 worker characteristic storage unit, 3000 computer, 3001 DVD-ROM, 3010 host controller, 3012 CPU, 3014 RAM, 3 016 GPU, 3018 display device, 3020 I / O controller, 3022 communication interface, 3024 hard disk drive, 3026 DVD-ROM drive, 3030 ROM, 3040 I / O chip, 3042 keyboard

Claims (12)

A tracking information acquisition unit that acquires information indicating at least one of the speed, acceleration, and angular acceleration of a moving body that moves following the worker performing the work.
A tracking abnormality detecting unit that detects at least one abnormality of the speed, the acceleration, and the angular acceleration acquired by the tracking information acquisition unit.
A question generation unit that generates a question regarding the abnormality when the tracking abnormality detection unit detects at least one abnormality of the speed, the acceleration, and the angular acceleration.
An information processing device equipped with. Further equipped with a cause estimation unit for estimating the cause of the abnormality,
The question generation unit determines the content of the question based on the cause estimated by the cause estimation unit.
The information processing apparatus according to claim 1. Further provided with an action information collecting unit for acquiring information indicating the content of the action performed by the worker in order to deal with the cause.
The information processing apparatus according to claim 2. It further includes a coping information generation unit that generates coping information in which the information indicating the content of the behavior acquired by the behavior information collecting unit and the information indicating the cause estimated by the cause estimation unit are associated with each other.
The information processing apparatus according to claim 3. The question generation unit generates a question for asking the worker why the worker chose the action.
The coping information generation unit
(I) As the information indicating the cause estimated by the cause estimation unit, the countermeasure information including the information indicating the content of the answer to the question, or the countermeasure information.
(Ii) The information indicating the content of the behavior acquired by the behavior information collecting unit, the information indicating the cause estimated by the cause estimation unit, and the information indicating the content of the answer to the question are associated with each other. Generate action information,
The information processing apparatus according to claim 4. The cause estimation unit has an object determination unit that determines whether or not the abnormality is caused by a first object that is the object of the worker's work.
The question generation unit determines the content of the question based on whether or not the abnormality is caused by the first object.
The information processing apparatus according to any one of claims 2 to 5. The object determination unit
Acquire the voice data in which the voice of the worker is recorded, and
The voice of the worker recorded in the voice data is analyzed, and the voice is analyzed.
(I) Estimate the event that causes the abnormality and (ii) the participants involved in the event.
The information processing apparatus according to claim 6. The cause estimation unit is
Before the time when the abnormality is detected, information on the work of another worker who has performed the same or similar work as the worker is acquired.
The cause of the abnormality is estimated based on the contents of the work of the other worker.
The information processing apparatus according to any one of claims 2 to 7. The work of the other worker is extracted from the work performed at a position where the distance from the position of the worker at the time when the abnormality is detected is smaller than a predetermined value.
The information processing apparatus according to claim 8. The question generator
If the worker's location is within a predetermined geographic range, the question is generated.
If the worker's location is not within the geographic range, do not generate the question,
The information processing apparatus according to any one of claims 1 to 9. A program for making a computer function as an information processing apparatus according to any one of claims 1 to 10. A follow-up information acquisition stage for acquiring information indicating at least one of the speed, acceleration, and angular acceleration of a moving body that follows the worker performing the work, and
A tracking abnormality detection step for detecting at least one abnormality of the velocity, the acceleration, and the angular acceleration acquired in the tracking information acquisition step, and
A question generation step that generates a question regarding the abnormality when at least one abnormality of the velocity, the acceleration, and the angular acceleration is detected in the tracking abnormality detection step.
Information processing method.

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