WO2022172707A1

WO2022172707A1 - Operation management method, operation management device and storage medium

Info

Publication number: WO2022172707A1
Application number: PCT/JP2022/001741
Authority: WO
Inventors: 俊輔宮内; 拓海吉峰; 拓也近藤
Original assignee: ヤンマーホールディングス株式会社
Priority date: 2021-02-10
Filing date: 2022-01-19
Publication date: 2022-08-18
Also published as: KR20230141767A; CN116802670A; JP7503009B2; JP2022122565A

Abstract

This operation management method involves estimating the operation type of an operation on the basis of work information about an operation device when carrying out an operation in an operation region within a first agricultural field. Further, the operation management method involves outputting an abnormality signal representing that the operation being carried out in the operation region is abnormal when the operation type differs from the scheduled operation type of the operation to be carried out in the operation region. Outputting the abnormality signal may optionally involve determining the scheduled operation type on the basis of the peripheral operation type of operations that have been carried out in peripheral agricultural fields of the operation region, and peripheral time period representing the time period in which the operations of the peripheral operation type were carried out.

Description

Work management method, work management device, and storage medium

The present invention relates to a work management method, a work management device, and a storage medium.

In recent years, research has been conducted on the use of information related to agricultural work in fields for analysis of cultivation management.

Patent Document 1 (Japanese Patent Application Laid-Open No. 2019-020923) discloses a cultivation support device that notifies various farm work suitable for cultivation at a time suitable for a cultivation area along a cultivation calendar. This cultivation support device determines the timing of farm work by correcting the cultivation calendar, which serves as a guideline for the work required for cultivation, according to the area where the field is located.

JP 2019-020923 A

With the technology described in Patent Document 1, even if the worker performs an incorrect task, it is determined that the appropriate task has been performed, and notification is given to perform the task corresponding to the cultivation calendar.

However, workers who perform farm work often own multiple fields, and may mistake the order or number of times they work on each field. In this case, the operator does not realize that he or she has performed an incorrect operation, which can seriously affect the growth of crops.

In view of the above situation, one of the purposes of the present disclosure is to provide a work management device that reduces the impact of incorrect work by determining whether the worker is performing appropriate work. Other objects can be understood from the following description and the description of the embodiments.

A work management method according to one embodiment for achieving the above object includes estimating a work type of work based on operation information of a work device during work in a work area in a first field. . The work management method also includes outputting an anomaly signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area.

A work management device according to one embodiment for achieving the above object includes a work estimation unit and an abnormal work detection unit. The work estimating unit estimates the work type of the work based on the operation information of the work device during work in the work area in the first field. The abnormal work detection unit outputs an abnormal signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area.

A storage medium according to one embodiment for achieving the above object stores a work management program. The work management program causes the arithmetic device to estimate the work type of the work based on the operation information of the work device during work in the work area in the first field. Further, the work management program causes the arithmetic unit to output an abnormality signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area. .

According to the above configuration, the work management device can notify the worker of the possibility that the worker is doing the wrong work.

FIG. 1 is a schematic diagram of a work management system in one embodiment. FIG. 2 is a diagram showing the configuration of cultivation calendar data in one embodiment. FIG. 3 is a diagram showing functional blocks executed by the work management system in one embodiment. FIG. 4 is a flow chart showing processing by the work management system in one embodiment. FIG. 5 is a flowchart showing processing for determining a scheduled work type in one embodiment.

(Embodiment 1)
A work management system 1000 according to this embodiment of the present invention will be described with reference to the drawings. In this embodiment, a work management system 1000 includes a work management device 100 and a terminal 200, as shown in FIG. The work management device 100 is communicably connected to the terminal 200 and the work vehicle 30 via a network 20, for example, the Internet.

The work management device 100 acquires field operation information from the work vehicle 30, and estimates information related to the work, such as the work period, work type, and work area, based on the acquired operation information. The work type indicates the type of work performed in the field, such as plowing, leveling, fertilizing, and planting. The work area represents an area in which work has been performed, for example, an area in which work has been performed in a field or an entire field in which work has been performed. In addition, the work management device 100 determines the type of scheduled work to be performed in the estimated work area based on work data and cultivation calendar regarding work performed in the past. When the estimated work type is different from the determined scheduled work type, the work management apparatus 100 notifies the user, for example, Notify workers, field owners, etc. In this way, the work management system 1000 can assist the user in performing work reliably. Further, when the user intentionally performs a work different from the scheduled work type, the user registers the estimated work type in the terminal 200 as the correct work. As a result, the work management system 1000 can detect changes in cultivation methods by recording changes in artificial work.

The operation information acquired from the work vehicle 30 includes information representing the state of the work vehicle 30 during work in the field, such as the speed of the work vehicle 30, the steering angle, the engine speed, and the ON state of various clutches. It includes information representing the /OFF status, location information of the work vehicle 30 at each time, work period, and the like. When the work vehicle 30 is a vehicle that tows the work machine, for example, a tractor, the operation information includes the PTO (power take-off) number of revolutions when power is transmitted to the work machine, the hitch height indicating the attitude of the work machine, and the height of the hitch. Information such as lift arm angle may also be included.

The configuration of the work management device 100 will be explained. The work management device 100 includes an input/output device 110 , an arithmetic device 120 , a communication device 130 and a storage device 140 . Work management device 100 is, for example, a computer. Input/output device 110 receives input of information for arithmetic device 120 to execute processing. The input/output device 110 also outputs the result of the processing executed by the arithmetic device 120 . The input/output device 110 includes various input devices and output devices, such as keyboards, mice, microphones, displays, speakers, and touch panels. Input/output device 110 may be omitted.

The communication device 130 is electrically connected to the network 20 and communicates with each device via the network 20 . The communication device 130 transfers the operation information acquired from the work vehicle 30 to the arithmetic device 120 . Also, the signal generated by the arithmetic device 120 is transferred to the terminal 200 . The communication device 130 includes various interfaces such as NIC (Network Interface Card) and USB (Universal Serial Bus).

The storage device 140 stores various data for estimating the type of work, such as work data 300, cultivation calendar data 310, and work management program 320. The storage device 140 is used as a non-transitory tangible storage medium for storing the work management program 320 . The work management program 320 may be provided as a computer program product recorded on the computer-readable storage medium 1, or may be provided as a computer program product downloadable from a server.

The work data 300 includes data related to field work, such as data calculated from operation information from the work vehicle 30 . For example, the work data 300 includes work period information representing a work period, work area information representing a work area, and work type information representing a work type. The work period information, the work area information, and the work type information are registered in association with the work data 300 . The work period represents the time when the work on the field was started and the time when the work was finished. The working area represents the area in which the field work has been performed, eg the position and shape. The work type indicates the type of work performed in the field, such as plowing, leveling, fertilizing, and planting.

The cultivation calendar data 310 represents the crops to be cultivated, the cultivation calendar according to the region, for example, the calendar work type that is the work type of the work performed for cultivation, and the calendar time that is the time to perform the work. For example, the growing calendar data 310, as shown in FIG. 2, represents calendar times according to the crops grown and the region. In the example shown in FIG. 2, when 'soybean' is cultivated in Hokkaido, 'plowing' is performed in the middle of May, and 'rowing' and 'fertilization (primary fertilizer)' are performed in the end of May. It also indicates that "seeding" is performed in early June and "weeding" is performed in the middle of June.

The work data 300 and the cultivation calendar data 310 are read by the computing device 120 shown in FIG. 1 and used for various data processing for detecting abnormalities in the work performed in the field. The computing device 120 reads out the work management program 320 from the storage device 140 and executes it to detect an abnormality in the work performed in the field. For example, the arithmetic unit 120 includes a central processing unit (CPU; Central Processing Unit).

By reading and executing the work management program 320, the computing device 120 implements a data holding unit 150, a work estimation unit 160, and an abnormal work detection unit 170, as shown in FIG. The data holding unit 150 holds work data 300 and cultivation calendar data 310 . The work estimation unit 160 estimates the work type based on the operation information obtained from the work vehicle 30 and registers it in the work data 300 . The abnormal work detection unit 170 detects an abnormality in the work performed by comparing the scheduled work type of the work to be performed in the field with the estimated work type.

Next, the configuration of terminal 200 will be described. The terminal 200 includes an input/output device 210, an arithmetic device 220, a communication device 230, and a storage device 240, as shown in FIG. Terminals 200 include, for example, computers, tablets, mobile phones, and the like. Input/output device 210 receives information for arithmetic device 220 to execute processing. Also, the input/output device 210 outputs the result of the processing executed by the arithmetic device 220 . The input/output device 210 includes various input devices and output devices, such as keyboards, mice, microphones, displays, speakers, and touch panels.

The communication device 230 is electrically connected to the network 20 and communicates with each device via the network 20 . The communication device 230 transfers information included in the work data 300 acquired from the work management device 100 to the arithmetic device 220 . Also, the signal generated by the computing device 220 is transferred to the work management device 100 . The communication device 230 includes various interfaces such as NIC (Network Interface Card) and USB (Universal Serial Bus).

The storage device 240 stores various data for notifying the user of work abnormalities detected by the work management device 100, such as a notification program 330. The storage device 240 is used as a non-transitory tangible storage medium for storing the notification program 330 . The notification program 330 may be provided as a computer program product recorded on the computer-readable storage medium 2, or may be provided as a computer program product downloadable from a server. The notification program 330 may be recorded on the storage medium 1 and provided.

By reading and executing the notification program 330, the arithmetic device 220 cooperates with the input/output device 210 as shown in FIG. Realize The notification unit 250 acquires information indicating a work abnormality detected by the work management apparatus 100 and notifies the user of the work abnormality. The notification unit 250 displays the work type estimated by the work management device 100 . The notification unit 250 updates information registered in the work data 300 by user's operation.

(Operation of work management device)
When the operation information is received from the work vehicle 30, the arithmetic device 120 of the work management device 100 reads and executes the work management program 320. FIG. By executing the work management program 320, the computing device 120 executes the processing shown in FIG.

In step S<b>110 , the work estimation unit 160 implemented by the arithmetic device 120 estimates the work period and work area based on the operation information received from the work vehicle 30 . For example, the work estimation unit 160 estimates the work period from the time when the work vehicle 30 is started to the time when the work vehicle 30 is stopped. Further, the work estimation unit 160 estimates the work period based on the time when the work of the work vehicle 30 is started and the time when the work is finished, for example, the time when the work machine towed by the work vehicle 30 is driven and stopped. good too. The work period may be estimated based on the time when the work vehicle 30 enters the field and the time when it leaves the field. Also, the work period may be estimated based on the time when the engine of the work vehicle 30 starts and the time when the work vehicle 30 stops, for example, the engine stops. The work estimation unit 160 registers the estimated work period in the work data 300 .

The work estimation unit 160 estimates the work area based on the position information of the work vehicle 30 during the estimated work period. Specifically, the work vehicle 30 is equipped with a positioning device, for example, a GNSS (Global Navigation Satellite System) receiver, and acquires position information representing the position at each time it moves during the work period. The acquired position information is transmitted from the work vehicle 30 to the arithmetic device 120 of the work management device 100 . A work estimating unit 160 implemented by the computing device 120 estimates a work area based on the acquired position information. For example, the work area is represented by any closed figure, such as a polygon or rectangle, including the position represented by the acquired position information. For example, the work area is represented by a figure that encloses all of the acquired position information. The work estimation unit 160 registers the estimated work area in the work data 300 in association with the corresponding work period. The work area is thereby associated with the determined work duration.

In step S<b>120 , the work estimation unit 160 estimates the work type based on the operation information received from the work vehicle 30 . For example, the work estimation unit 160 estimates the work type using a learned model obtained by machine learning. In this case, the trained model is trained so as to estimate the work type from the operation information. Moreover, the work estimation unit 160 may estimate the work type based on the model of the work vehicle 30 or the work machine. In this case, the data holding unit 150 stores and holds in the storage device 140 work correspondence data that associates the model of the work vehicle 30 or work machine with the work type. The work estimation unit 160 estimates the work type based on the work correspondence data.

The work estimation unit 160 registers the estimated work type in the work data 300 in association with the corresponding work period. Thus, the work type is associated with the work period and work area estimated in step S110.

In step S130, the abnormal work detection unit 170 determines the scheduled work type of work to be performed in the estimated work area during the estimated work period based on the work period and work area estimated by the work estimation unit 160. do. The abnormal work detection unit 170 may determine one or more scheduled work types. The method by which the abnormal work detection unit 170 determines the scheduled work type will be described later.

In step S140, the abnormal work detection unit 170 determines whether the work type estimated by the work estimation unit 160 is included in the determined scheduled work type. When the work type is included in the scheduled work type, the abnormal work detection unit 170 determines that the work performed by the work vehicle 30 is normal, and terminates the process. When the work type is not included in the scheduled work type, the abnormal work detection unit 170 determines that the work performed by the work vehicle 30 may be abnormal, and executes the process of step S150.

In step S150, the abnormal work detection unit 170 generates and outputs an abnormal signal indicating that the work performed by the work vehicle 30 is abnormal. The notification unit 250 of the terminal 200 notifies the user that the work is abnormal based on the abnormality signal. For example, the notification unit 250 displays a notification image for notifying an operation abnormality on the input/output device 210 of the terminal 200 shown in FIG. The notification image represents the estimated work period, work area, and work type. By viewing the notification image, the user can confirm the work period, work area, and work type, and can confirm whether there was an error in the work performed in the field. The notification unit 250 may output a warning sound to notify the abnormality from the input/output device 210 of the terminal 200 . Based on the warning sound, the user can confirm the possibility that there was a mistake in the work performed in the field.

When the estimated work type is incorrect, the user inputs a correction operation for correcting the work type to the input/output device 210 of the terminal 200 . The notification unit 250 generates a correction signal for correcting the work type based on the input operation. The data holding unit 150 of the work management device 100 corrects the work type registered in the work data 300 based on the correction signal.

When the user intentionally performs the estimated work type, the user inputs a confirmation operation to the input/output device 210 of the terminal 200 indicating that the work has been performed normally. The notification unit 250 generates a normal work signal indicating that normal work has been performed based on the input operation. The data holding unit 150 of the work management device 100 registers normal work in the work data 300 based on the normal work signal. In this way, the data holding unit 150 records artificial changes in the type of work performed when cultivating. By recording changes in the cultivation method in the work data 300, the work management system 1000 can detect changes in the cultivation method.

When the user performs the estimated work type incorrectly, the user inputs an erroneous work operation indicating that the wrong work was performed to the input/output device 210 of the terminal 200 . The notification unit 250 generates an erroneous work signal indicating that an incorrect work has been performed based on the input operation. The data holding unit 150 of the work management device 100 registers the wrong work in the work data 300 based on the erroneous work signal. In this way, the data holding unit 150 records the work type of the work that was done by mistake. The abnormal work detection unit 170 determines the scheduled work type without using the work type of the wrongly performed work. As a result, the abnormal work detection unit 170 can reduce the influence of an erroneously performed work on the determination of the scheduled work type.

(Method for estimating scheduled work type)
In step S130 shown in FIG. 4, the abnormal work detection unit 170 executes the processing shown in FIG. 5 to determine the scheduled work type. In step S210, the abnormal work detection unit 170 determines whether the work area is included in the area registered as the agricultural field. The work data 300 records fields in which the user has worked in the past. The abnormal work detection unit 170 extracts from the work data 300 a field corresponding to the work area estimated by the work estimation unit 160 . When the corresponding farm field is included in the work data 300, the abnormal work detection unit 170 determines that the estimated work area is registered as a farm field, and executes the process of step S230. When the corresponding farm field is not included in the work data 300, the abnormal work detection unit 170 determines that the estimated work area is not registered as a farm field, and executes the process of step S220.

In step S220, the abnormal work detection unit 170 determines the scheduled work type based on the peripheral work type representing the work type of the work performed in the surrounding field existing around the estimated work area. The abnormal work detection unit 170 searches the work data 300 for fields existing around the estimated work area. For example, the abnormal work detection unit 170 searches the work data 300 for fields existing within 10 km from the estimated work area. The abnormal work detection unit 170 extracts the peripheral work type of the work performed in the searched field at the peripheral time representing the time corresponding to the estimated work period, and uses the extracted peripheral work type as the scheduled work type. judge. For example, the abnormal work detection unit 170 determines the peripheral work type performed in the searched field at the time closest to the estimated work period as the scheduled work type.

In addition, the abnormal work detection unit 170 may determine the scheduled work type based on the order of the peripheral work types of the work performed in the surrounding fields. For example, the abnormal work detection unit 170 extracts from the work data 300 the work type of the work that has been performed so far in the estimated work area. The abnormal work detection unit 170 compares the order of the work types of the extracted work with the order of the peripheral work types of the work performed in the surrounding fields, and detects the scheduled work to be performed in the work area. Determine the type. For example, it is assumed that until now, “plowing” and “raising ridges” have been performed in order in the work area. In addition, when “plowing”, “rowing”, and “fertilizing” are performed in order in a field existing in the vicinity, the abnormal work detection unit 170 detects the scheduled work to be performed in the work area. It is determined that the type is "fertilization".

The abnormal work detection unit 170 may calculate the first probability of the scheduled work type based on the difference between the estimated work period and the peripheral work period representing the work period performed in the searched field. The first probability of the scheduled work type represents the possibility, for example, probability, that the work of the scheduled work type will be performed in the estimated work period in the estimated work area. The first probability of the scheduled work type may be calculated from the distribution of surrounding work periods during which the work of the corresponding work type was performed in each surrounding field. When the calculated first probability is greater than a predetermined threshold, the abnormal work detection unit 170 determines that the corresponding scheduled work type is work to be performed in the estimated work area. Also, the abnormal work detection unit 170 may calculate the first accuracy using the order of the peripheral work types of the work performed in the surrounding farm fields.

When the estimated work area is registered as a field, in step S230, the abnormal work detection unit 170 determines whether crops cultivated in the corresponding field are registered. The work data 300 registers crops grown in the registered fields. The abnormal work detection unit 170 searches the work data 300 for crops cultivated in the field corresponding to the estimated work area. When the cultivated crop is registered in the work data 300, the abnormal work detection unit 170 executes the process of step S250. When the cultivated crop is not registered in the work data 300, the abnormal work detection unit 170 executes the process of step S240.

In step S240, the abnormal work detection unit 170 determines the scheduled work type based on the past work type representing the work type of work performed in the past in the field corresponding to the work area. The abnormal work detection unit 170 extracts from the work data 300 the past work type of the work performed in the corresponding field and the past work period representing the work period. The abnormal work detection unit 170 extracts the past work type of the work performed in the corresponding field at the time corresponding to the estimated work period, for example, at the same time one year ago, and determines the extracted past work type. Determined as work type. Further, the abnormal work detection unit 170 may determine the scheduled work type based on the order of the past work types of the work performed in the corresponding field in the past.

The abnormal work detection unit 170 may calculate the second accuracy of the scheduled work type based on the difference between the estimated work period and the past work period performed in the corresponding field. The second probability of the scheduled work type represents the possibility, for example, the probability, that the work of the scheduled work type will be performed in the estimated work period in the estimated work area. The second accuracy of the scheduled work type may be calculated from the past work periods in which the work of the corresponding work type was performed in the corresponding field, for example, the distribution of the work periods of each year. When the calculated second accuracy is greater than a predetermined threshold, the abnormal work detection unit 170 determines that the corresponding scheduled work type is work to be performed in the estimated work area. Further, the abnormal work detection unit 170 may calculate the second accuracy using the order of the past work types of the past work performed in the corresponding field.

When the crops cultivated in the corresponding field are registered, in step S250, the abnormal work detection unit 170 determines the scheduled work type based on the registered cultivation calendar of the crops. The abnormal work detection unit 170 extracts the cultivation calendar related to the crops cultivated in the corresponding field from the cultivation calendar data 310 stored in the storage device 140 shown in FIG. The abnormal work detection unit 170 determines the scheduled work type of work to be performed in the estimated work area based on the estimated work period and the extracted cultivation calendar. For example, from the extracted cultivation calendar, the abnormal work detection unit 170 determines the calendar work type of the work to be performed at the calendar time corresponding to the estimated work period, for example, at the calendar time closest to the estimated work period. Judged as a type. Further, the abnormal work detection unit 170 may determine the scheduled work type based on the order of the calendar work types of the work registered in the cultivation calendar.

For example, in the field corresponding to the cultivation calendar data 310 shown in FIG. In this case, the abnormal work detection unit 170 determines that the scheduled work type is "fertilization" based on the cultivation calendar data 310 in step S250.

The abnormal work detection unit 170 may calculate the third accuracy of the scheduled work type based on the difference between the cultivation calendar and the work period performed in the corresponding field. The third certainty of the scheduled work type represents the possibility, for example, the probability, that the work of the scheduled work type will be performed in the estimated work period in the estimated work area. The third accuracy of the scheduled work type may be calculated based on the difference between the extracted calendar time and the estimated work period, by extracting the calendar time for performing the work of the corresponding work type from the cultivation calendar. When the calculated third accuracy is greater than a predetermined threshold, the abnormal work detection unit 170 determines that the corresponding scheduled work type is work to be performed in the estimated work area. Moreover, the abnormal work detection unit 170 may calculate the third accuracy using the order of the calendar work type of the work registered in the cultivation calendar.

As described above, the abnormal work detection unit 170 determines the scheduled work type. Using the determined scheduled work type, the abnormal work detection unit 170 executes the processes after step S140 shown in FIG. As a result, it is possible to reduce the influence on the crop caused by the wrong work performed by the operator.

For example, in the field corresponding to the cultivation calendar data 310 shown in FIG. 2, when the worker performs "fertilization" that should be performed in late May and "seeding" by mistake, the abnormal work detection unit 170 detects that the type of work is different from the scheduled work type. Notify the worker that the work has been done. As a result, poor growth of crops caused by forgetting to "fertilize" can be reduced. In addition, the abnormal work detection unit 170 reduces the possibility that the sowing time has passed by notifying the operator that the "seeding" that should be performed in early June has not been performed. Similarly, the abnormal work detection unit 170 reduces poor growth of crops due to lack of "control" and "fertilization" in August and September. In addition, even when excessive “control” or “fertilization” is performed, the abnormal work detection unit 170 notifies the worker that abnormal work has been performed. ”.

In addition, as shown in FIG. 5, the abnormal work detection unit 170 detects a first scheduled work type determined based on work in a neighboring field and a second scheduled work type determined based on past work in the same field. and the third scheduled work type determined based on the cultivation calendar is employed as the scheduled work type. By preferentially adopting the third scheduled work type, the second scheduled work type, and the first scheduled work type in this order, the abnormal work detection unit 170 preferentially uses the work type that is more suitable for cultivation. work can be detected.

(Modification)
The configuration described in the embodiment is an example, and the configuration can be changed within a range that does not hinder the functions. Although the abnormal work detection unit 170 determines the scheduled work type using any one of the work in the neighboring field, the past work in the same field, and the cultivation calendar, the abnormal work detection unit 170 is not limited to this. The abnormal work detection unit 170 may determine the scheduled work type using two or more of the work in the neighboring field, the past work in the same field, and the cultivation calendar.

For example, in step S240 shown in FIG. 5, the abnormal work detection unit 170 determines the scheduled work type using the work in the surrounding field and the past work in the same field. In this case, the abnormal work detection unit 170 executes the process of step S220 to determine the first scheduled work type based on the work in the surrounding field. Further, the abnormal work detection unit 170 executes the process of step S240 to determine the second scheduled work type based on past work in the same field. The abnormal work detection unit 170 determines the scheduled work type including the first scheduled work type and the second scheduled work type as the work type of the work performed in the work area.

Further, in step S240 shown in FIG. 5, the abnormal work detection unit 170 calculates the accuracy of the scheduled work type based on the work in the neighboring field and the past work in the same field, and based on the calculated accuracy, the scheduled work type may be determined. For example, the abnormal work detection unit 170 executes the process of step S220 to calculate the first probability of the scheduled work type based on the work in the surrounding field. In addition, the abnormal work detection unit 170 executes the process of step S240 to calculate the second accuracy of the scheduled work type based on past work in the same field. The abnormal work detection unit 170 calculates the accuracy of the scheduled work type based on the first accuracy and the second accuracy. For example, the abnormal work detection unit 170 calculates the accuracy of the scheduled work type by adding the value obtained by multiplying the first accuracy by the first coefficient and the value obtained by multiplying the second accuracy by the second coefficient. The abnormal work detection unit 170 determines the scheduled work type using the calculated accuracy.

In addition, in step S250 shown in FIG. 5, the abnormal work detection unit 170 may determine the scheduled work type based on the work in the neighboring field, the past work in the same field, and the cultivation calendar. In this case, the abnormal work detection unit 170 executes the process of step S220 to determine the first scheduled work type based on the work in the surrounding field. Further, the abnormal work detection unit 170 executes the process of step S240 to determine the second scheduled work type based on past work in the same field. Furthermore, the abnormal work detection unit 170 executes the process of step S250 to determine the third scheduled work type based on the cultivation calendar. The abnormal work detection unit 170 determines the scheduled work type including the first scheduled work type, the second scheduled work type, and the third scheduled work type as the work type of the work performed in the work area.

Further, in step S240 shown in FIG. 5, the abnormal work detection unit 170 calculates the accuracy of the scheduled work type based on the work in the neighboring field, the past work in the same field, and the cultivation calendar, and the calculated accuracy Based on this, the scheduled work type may be determined. For example, the abnormal work detection unit 170 executes the process of step S220 to calculate the first probability of the scheduled work type based on the work in the surrounding field. In addition, the abnormal work detection unit 170 executes the process of step S240 to calculate the second accuracy of the scheduled work type based on past work in the same field. Furthermore, the abnormal work detection unit 170 executes the process of step S250 to calculate the third probability of the scheduled work type based on the cultivation calendar. The abnormal work detection unit 170 calculates the accuracy of the scheduled work type based on the first accuracy, the second accuracy, and the third accuracy. The abnormal work detection unit 170 determines the scheduled work type using the calculated accuracy.

In addition, the abnormal work detection unit 170 may determine the scheduled work type by any method as long as it can determine the scheduled work type of the work to be performed in the work area. For example, the abnormal work detection unit 170 may determine the scheduled work type based on a pre-registered work plan. For example, the data holding unit 150 holds a work plan input by a user, for example, a work type and a work period of work to be performed in a field. The abnormal work detection unit 170 determines the scheduled work type based on the work plan held by the data holding unit 150 and the work period estimated by the work estimation unit 160 in step S130 shown in FIG.

In step S110 shown in FIG. 4, an example is shown in which the work period is estimated as the period from when the work vehicle 30 starts working until it stops, but it is not limited to this. The work period may be the period during which the work vehicle 30 is performing work, and may be a part of the period during which the work vehicle 30 is performing work. For example, the work period may be a period from when the work vehicle 30 is activated until a predetermined period of time elapses. In this case, the work management device 100 may perform the process shown in FIG. 4 while the work vehicle 30 is working to notify the worker of the abnormality in the work.

The embodiments and modifications described above are examples, and the configurations described in the embodiments and modifications may be arbitrarily changed and/or combined as long as the functions are not hindered. may Furthermore, some of the functions described in the embodiment and modifications may be omitted as long as the required functions can be realized. For example, the work management device 100 may acquire operation information from any work device that performs work in a field, such as a drone.

This application claims priority based on Japanese Patent Application No. 2021-019890 filed on February 10, 2021, and the entire disclosure thereof is incorporated herein.

Claims

estimating the work type of the work based on the operation information of the work device when the work is performed in the work area in the first field;
outputting an abnormality signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area;
work management methods, including;
Outputting the abnormal signal determines the scheduled work type based on the surrounding work type of the work performed in the surrounding field of the work area and the surrounding time representing the time when the work of the surrounding work type is performed. 2. The work management method of claim 1, comprising determining.
Determining the scheduled work type includes:
calculating a first probability that the scheduled work type was performed in the work area based on the peripheral work type and the peripheral time;
Determining the scheduled work type based on the calculated first probability;
The work management method according to claim 2, comprising:
2. The step of outputting the abnormal signal includes determining the scheduled work type based on a past work type and a past work period of past work performed in the first field including the work area. 4. The work management method according to any one of 3.
Determining the scheduled work type includes:
calculating a second probability that the scheduled work type was performed in the work area based on the past work type and the past work period;
Determining the scheduled work type based on the calculated second accuracy;
The work management method according to claim 4, comprising:
Determining the scheduled work type is performed based on the crops cultivated in the work area and a cultivation calendar representing the calendar work type and calendar time of the work performed for cultivating the crops. The work management method according to any one of claims 1 to 5, comprising determining a type.
Determining the scheduled work type includes:
calculating a third probability that the scheduled work type was performed in the work area based on the calendar work type and the calendar time;
Determining the scheduled work type based on the calculated third probability;
The work management method according to claim 6, comprising:
Outputting the abnormal signal includes:
Determining a first scheduled work type based on a surrounding work type of work performed in a surrounding field existing around the work area and a surrounding time representing a time when the work of the surrounding work type was performed. ,
Determining a second scheduled work type based on a past work type and a past work period of past work performed in the first field including the work area;
Determining a third scheduled work type based on a crop cultivated in the work area and a cultivation calendar representing a calendar work type and a calendar time of work to be performed for cultivating the crop;
determining the scheduled work type based on the first scheduled work type, the second scheduled work type, and the third scheduled work type;
The work management method according to claim 1, comprising:
Determining the scheduled work type includes:
9. The work management method according to claim 8, further comprising determining the scheduled work type preferentially in the order of the third scheduled work type, the second scheduled work type, and the first scheduled work type.
Determining the scheduled work type includes:
calculating a first probability that the scheduled work type was performed in the work area based on the peripheral work type and the peripheral time;
calculating a second probability that the scheduled work type was performed in the work area based on the past work type and the past work period;
calculating a third probability that the scheduled work type was performed in the work area based on the calendar work type and the calendar time;
determining the scheduled work type based on the first accuracy, the second accuracy, and the third accuracy;
The work management method according to claim 8, comprising:
estimating the work type of the work based on the operation information of the work device when the work is performed in the work area in the first field;
outputting an abnormality signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area;
A non-temporary storage medium that stores a work management program that causes the arithmetic device to execute
a work estimating unit for estimating a work type of the work based on operation information of the work device during work in the work area in the first field;
an abnormal work detection unit that outputs an abnormal signal indicating that the work being performed in the work area is abnormal when the work type is different from the scheduled work type of the work to be performed in the work area;
A work management device with