CN116802670A

CN116802670A - Job management method, job management apparatus, and storage medium

Info

Publication number: CN116802670A
Application number: CN202280013011.6A
Authority: CN
Inventors: 宫内俊辅; 吉峰拓海; 近藤拓也
Original assignee: Yanmar Holdings Co Ltd
Current assignee: Yanmar Holdings Co Ltd
Priority date: 2021-02-10
Filing date: 2022-01-19
Publication date: 2023-09-22
Also published as: WO2022172707A1; JP7503009B2; KR20230141767A; JP2022122565A

Abstract

The job management method includes the steps of: the job type of the job is estimated based on the operation information of the working device when the job is performed in the job area in the 1 st field. In addition, the job management method includes the steps of: when the job type is different from a predetermined job type of a job to be performed in the job area, an abnormality signal indicating abnormality of the job performed in the job area is output. The step of outputting the abnormality signal may include the steps of: the predetermined job type is determined based on the surrounding job type of the job performed in the surrounding field of the job area and the surrounding time period indicating the time period of the job of the surrounding job type.

Description

Job management method, job management apparatus, and storage medium

Technical Field

The application relates to a job management method, a job management apparatus, and a storage medium.

Background

In recent years, a technique of using information related to agricultural operations in a field in analysis of cultivation management has been studied.

Patent document 1 (japanese patent application laid-open publication No. 2019-020923) discloses a cultivation aid device for notifying various kinds of agricultural operations suitable for cultivation at a time suitable for a cultivation area in accordance with a cultivation history. The cultivation aid device corrects a cultivation history which is a basis of a work required for cultivation according to a region where a field is located, thereby determining a timing of performing agricultural work.

Prior art literature

Patent literature

Patent document 1: japanese patent application laid-open No. 2019-020923

Disclosure of Invention

In the technique described in patent document 1, even if an operator performs an erroneous operation, it is determined that an appropriate operation is performed, and the operator is notified of the operation corresponding to the cultivation history.

However, many workers who perform agricultural work have a plurality of fields, and sometimes erroneously execute the order and number of works for each field. In this case, the operator may have a significant influence on the cultivation of the crop without noticing the wrong work.

In view of the above-described situation, an object of the present disclosure is to provide a job management apparatus that reduces the influence caused by an erroneous job by determining whether or not an operator has performed an appropriate job. Other objects will be understood from the following description and description of the embodiments.

The job management method according to one embodiment for achieving the above object includes the steps of: the job type of the job is estimated based on the operation information of the working device when the job is performed in the job area in the 1 st field. In addition, the job management method includes the steps of: when the job type is different from a predetermined job type of a job to be performed in the job area, an abnormality signal indicating abnormality of the job performed in the job area is output.

The job management apparatus according to one embodiment for achieving the above object includes a job estimating section and an abnormal job monitoring section. The job estimation unit estimates the job type of the job based on the operation information of the working device when the job is performed in the job area in the 1 st field. When the job type is different from a predetermined job type of a job to be performed in the job area, the abnormal job monitoring part outputs an abnormal signal indicating that the job performed in the job area is abnormal.

The storage medium according to one embodiment for achieving the above object stores a job management program. The job management program causes the arithmetic device to execute: the job type of the job is estimated based on the operation information of the working device when the job is performed in the job area in the 1 st field. The job management program causes the arithmetic device to execute: when the job type is different from a predetermined job type of a job to be performed in the job area, an abnormality signal indicating abnormality of the job performed in the job area is output.

According to the above aspect, the job management apparatus can notify the worker of the possibility of an erroneous job.

Drawings

Fig. 1 is a schematic diagram of a job management system according to an embodiment.

Fig. 2 is a diagram showing a structure of cultivation history data according to an embodiment.

Fig. 3 is a diagram showing functional blocks executed by the job management system according to the embodiment.

Fig. 4 is a flowchart showing a process of the job management system according to an embodiment.

Fig. 5 is a flowchart showing a process of determining a predetermined job type in one embodiment.

Detailed Description

(embodiment 1)

A job management system 1000 according to the present embodiment of the present application will be described with reference to the drawings. In the present embodiment, as shown in fig. 1, a job management system 1000 includes a job management apparatus 100 and a terminal 200. Work management device 100 is communicably connected to terminal 200 and work vehicle 30 via network 20, for example, the internet.

The work management device 100 acquires operation information in the field from the work vehicle 30, and estimates information related to the work, such as a work period, a work category, a work area, and the like, based on the acquired operation information. The job type indicates the type of job to be performed on the field, for example, cultivated land, soil preparation, fertilization, planting, and the like. The work area represents an area where work is performed, for example, an area where work is performed in a field, and an area of a whole field where work is performed. The job management apparatus 100 determines a predetermined job type to be performed in the estimated job area based on the job data and the cultivation history related to the job performed in the past. When the estimated job type is different from the determined predetermined job type, the job management apparatus 100 notifies the user, for example, an operator, a field owner, or the like, of the type of the job performed in the job area via the terminal 200, and there is a possibility that an error may occur. In this way, the job management system 1000 can assist the user in reliably performing the job. When the user intentionally performs a job different from the predetermined job type, the estimated job type is registered in the terminal 200 as a correct job. Thus, the work management system 1000 can record a change in an artificial work and monitor a change in the cultivation method.

The operation information acquired from work vehicle 30 includes information indicating the state of work vehicle 30 when the work is performed in the field, and includes, for example, the speed of work vehicle 30, the steering angle, the engine speed, the ON/OFF states of the various clutches, position information at each time of work vehicle 30, information indicating the period of the work, and the like. When work vehicle 30 is a vehicle that pulls a work machine, such as a tractor, the operation information may include information such as a PTO (power take-off) rotation speed at the time of transmitting power to the work machine, a suspension height indicating the posture of the work machine, and a boom angle.

The configuration of the job management apparatus 100 will be described. The job management apparatus 100 includes an input/output device 110, a computing device 120, a communication device 130, and a storage device 140. The job management apparatus 100 is, for example, a computer. Information for the arithmetic device 120 to execute processing is input to the input-output device 110. The input/output device 110 outputs the result of the processing performed by the arithmetic device 120. The input/output device 110 includes various input devices and output devices including, for example, a keyboard, a mouse, a microphone, a display, a speaker, a touch panel, and the like. The 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. Communication device 130 transmits the operation information acquired from work vehicle 30 to computing device 120. The signal generated by the arithmetic device 120 is transmitted 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 job type, for example, job data 300, cultivation history data 310, and job management program 320. The storage device 140 serves as a non-temporary storage medium (non-transitory tangible storage medium) that stores the job management program 320. The job management program 320 may be provided as a computer program product (computer program product) recorded in the computer-readable storage medium 1, or may be provided as a computer program product that can be downloaded from a server.

The job data 300 includes data related to the job of the field, for example, data calculated from the operation information from the work vehicle 30. For example, the job data 300 includes job period information indicating a job period, job area information indicating a job area, and job category information indicating a job category. The job period information, job area information, and job category information are registered in the job data 300 in association with each other. The job period indicates a time when the job in the field is started and a time when the job is ended. The work area represents an area where work in the field is performed, for example, a position and a shape. The job type indicates the type of job to be performed on the field, for example, cultivated land, soil preparation, fertilization, planting, and the like.

The cultivation history data 310 indicates cultivation histories corresponding to the cultivated crop and the region, for example, a history job type which is a job type of a job to be performed for cultivation, and a history time which is a time when the job is performed. For example, as shown in fig. 2, the cultivation history data 310 indicates history times corresponding to the cultivated crops and regions. In the example shown in fig. 2, it is shown that: when "soybean" is cultivated in Hokkaido, "cultivated land" is performed in the middle of 5 months, and "ridging" and "fertilization (base fertilizer)" are performed in the next ten days. In addition, it indicates that: the seeds were sown in the last ten days of 6 months, and the weeds were removed in the middle ten days.

The job data 300 and the cultivation history data 310 are read by the arithmetic device 120 shown in fig. 1, and are used for various data processing for monitoring abnormality of a job performed in a field. The arithmetic device 120 reads and executes the job management program 320 from the storage device 140, and detects an abnormality of a job performed in the field. For example, the arithmetic device 120 includes a central processing unit (CPU: central Processing Unit) and the like.

The arithmetic device 120 reads and executes the job management program 320 to realize the data holding unit 150, the job estimating unit 160, and the abnormal job monitoring unit 170 as shown in fig. 3. The data holding unit 150 holds the job data 300 and the cultivation history data 310. The work estimating unit 160 estimates a work category based on the operation information obtained from the work vehicle 30 and registers the estimated work category in the work data 300. The abnormal job monitoring part 170 compares the predetermined job type of the job to be performed in the field with the estimated job type to monitor the abnormality of the performed job.

Next, the structure of the terminal 200 will be described. As shown in fig. 1, the terminal 200 includes an input/output device 210, an arithmetic device 220, a communication device 230, and a storage device 240. The terminal 200 includes, for example, a computer, a tablet computer, a mobile phone, and the like. Information for the arithmetic device 220 to execute processing is input to the input-output device 210. The input/output device 210 outputs the result of the processing performed by the arithmetic device 220. The input/output device 210 includes various input devices and output devices including, for example, a keyboard, a mouse, a microphone, a display, a speaker, a touch panel, and the like.

The communication device 230 is electrically connected to the network 20, and communicates with each device via the network 20. The communication device 230 transmits information included in the job data 300 acquired from the job management device 100 to the arithmetic device 220. The signal generated by the arithmetic unit 220 is transmitted to the job management apparatus 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 the abnormality of the job monitored by the job management device 100, for example, the notification program 330. The storage device 240 serves as a non-temporary storage medium (non-transitory tangible storage medium) that stores the notification program 330. The notification program 330 may be provided as a computer program product (computer program product) recorded in the computer-readable recording medium 2, or may be provided as a computer program product that can be downloaded from a server. The notification program 330 may be provided by being recorded in the storage medium 1.

The arithmetic device 220 reads and executes the notification program 330 to realize a notification unit 250 for notifying the user of the abnormality of the job monitored by the job management device 100 in cooperation with the input/output device 210 as shown in fig. 3. The notification unit 250 acquires information indicating an abnormality of the job monitored by the job management apparatus 100, and notifies the user of the abnormality of the job. The notification unit 250 displays the job type estimated by the job management apparatus 100. The notification unit 250 updates information registered in the job data 300 by a user operation.

(operation of work management device)

When operation information is received from work vehicle 30, operation device 120 of work management device 100 reads and executes work management program 320. The arithmetic device 120 executes the processing shown in fig. 4 by executing the job management program 320.

In step S110, the work estimating unit 160 implemented by the computing device 120 estimates the work period and the work area based on the operation information received from the work vehicle 30. For example, work estimating unit 160 estimates a period from the time when work vehicle 30 starts to the time when work vehicle 30 stops as a work period. Further, the work estimating unit 160 may estimate the work period based on the time when the work of the work vehicle 30 is started and ended, for example, the time when the work machine towed by the work vehicle 30 is driven and stopped. The working period may be estimated based on the time when working vehicle 30 enters the field and the time when it exits from the field. The operation period may be estimated based on the time when the engine of work vehicle 30 starts and the time when work vehicle 30 stops, for example, the time when the engine stops. The job estimation unit 160 registers the estimated job period in the job data 300.

The work estimating unit 160 estimates a work area based on the estimated position information of the work vehicle 30 during the work. Specifically, work vehicle 30 includes a positioning device, for example, a GNSS (Global Navigation Satellite System) receiver, and acquires position information indicating the position at each time point of movement during the work. The acquired position information is transmitted from work vehicle 30 to computing device 120 of work management device 100. The 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 an arbitrary closed figure including a position represented by the acquired position information, such as a polygon, a rectangle, or the like. For example, the work area is represented graphically by surrounding all the position information to be acquired. The job estimation unit 160 registers the estimated job area in the job data 300 in association with the corresponding job period. Thus, the job area is associated with the determined job period.

In step S120, the job estimating unit 160 estimates the job type based on the operation information received from the work vehicle 30. For example, the job estimating unit 160 estimates the job type using a learning-completed model obtained by machine learning. In this case, the learning model is learned so that the job type is estimated from the operation information. Further, the work estimating unit 160 may estimate the work category based on the model of the work vehicle 30 or the work machine. In this case, the data holding unit 150 stores and holds job-related data that associates the model of the work vehicle 30 or the work machine with the job type in the storage device 140. The job estimation unit 160 estimates the job type based on the job correspondence data.

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

In step S130, the abnormal job monitoring part 170 determines a predetermined job type of a job to be performed in the estimated job period and in the estimated job area based on the job period and the job area estimated by the job estimating part 160. The abnormal job monitoring part 170 may determine 1 or more predetermined job categories. The method of determining the predetermined job type by the abnormal job monitoring part 170 will be described later.

In step S140, the abnormal job monitoring part 170 determines whether or not the job type estimated by the job estimating part 160 is included in the determined predetermined job type. When the predetermined job category includes a job category, the abnormal job monitoring portion 170 determines that the job performed by the work vehicle 30 is normal and ends the process. When the predetermined job category does not include a job category, the abnormal job monitoring part 170 determines that there is a possibility that the job performed by the work vehicle 30 is abnormal, and executes the process of step S150.

In step S150, abnormal work monitoring unit 170 generates and outputs an abnormality signal indicating an abnormality of the work performed by work vehicle 30. The notifying unit 250 of the terminal 200 notifies the user of the abnormality of the job based on the abnormality signal. For example, the notification unit 250 displays a notification image for notifying an abnormality of a job on the input/output device 210 of the terminal 200 shown in fig. 1. The notification image indicates the estimated work period, work area, and work category. The user can check the operation period, the operation area, and the operation type by observing the notification image, and can check whether or not the operation performed on the field is erroneous. The notification unit 250 may output a warning voice notifying an abnormality from the input/output device 210 of the terminal 200. The user can confirm the possibility of a job error performed in the field based on the warning voice.

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

When the user intentionally estimates the job type, the user inputs a confirmation operation indicating that the normal job is performed to the input/output device 210 of the terminal 200. The notification unit 250 generates a normal job signal indicating that a normal job is performed based on the input operation. The data holding unit 150 of the job management apparatus 100 registers the case of a normal job in the job data 300 based on the normal job signal. In this way, the data holding unit 150 records an artificial change for the type of work performed during cultivation. The work management system 1000 records the change in the cultivation method in the work data 300, and can monitor the change in the cultivation method.

When the user erroneously estimates the type of job, the user inputs an erroneous job operation indicating that the erroneous job is performed to the input/output device 210 of the terminal 200. The notification unit 250 generates an error job signal indicating that an error job is performed based on the input operation. The data holding unit 150 of the job management apparatus 100 registers the case of the wrong job in the job data 300 based on the wrong job signal. In this way, the data holding unit 150 records the job type of the erroneously performed job. The abnormal job monitoring part 170 determines a predetermined job type without using the job type of the erroneously performed job. Thus, the abnormal job monitoring part 170 can reduce the influence of the erroneously performed job on the determination of the predetermined job type.

(method of estimating a predetermined job class)

In step S130 shown in fig. 4, the abnormal job monitoring part 170 performs the processing shown in fig. 5 to determine a predetermined job type. In step S210, the abnormal work monitoring part 170 determines whether or not the work area is included in the area registered as the field. Fields in which the user performed a job in the past are recorded in the job data 300. The abnormal work monitoring unit 170 extracts a field corresponding to the work area estimated by the work estimating unit 160 from the work data 300. When the corresponding field is included in the job data 300, the abnormal job monitoring part 170 determines that the estimated job area is registered as a field and executes the process of step S230. When the corresponding field is not included in the job data 300, the abnormal job monitoring part 170 determines that the estimated job area is not registered as a field and executes the process of step S220.

In step S220, the abnormal job monitoring part 170 determines a predetermined job type based on the surrounding job type indicating the job type of the job performed in the surrounding field existing around the estimated job area. The abnormal work monitoring unit 170 searches the work data 300 for a field existing around the estimated work area. For example, the abnormal work monitoring part 170 searches the work data 300 for a field existing within 10km with respect to the estimated work area. The abnormal job monitoring part 170 extracts a peripheral job category of a job performed on the retrieved field at a peripheral time indicating a time corresponding to the estimated job period, and determines the extracted peripheral job category as a predetermined job category. For example, the abnormal job monitoring part 170 determines the surrounding job type performed in the retrieved field at a time closest to the estimated job period as the predetermined job type.

The abnormal job monitoring part 170 may determine the predetermined job type based on the order of the peripheral job types of the jobs performed in the peripheral field. For example, the abnormal job monitoring part 170 extracts the job type of the job performed in the estimated job area so far from the job data 300. The abnormal job monitoring part 170 compares the order of job categories of the extracted jobs with the order of surrounding job categories of jobs performed in the surrounding field to determine a predetermined job category of a job to be performed in the job area. For example, it is assumed that "tillage" and "ridging" have been performed in this order in the work area so far. When "cultivated land", "ridging" and "fertilizer application" are performed in this order on the surrounding field, the abnormal work monitoring part 170 determines that the predetermined work type of the work to be performed in the work area is "fertilizer application".

The abnormal job monitoring part 170 may calculate the 1 st accuracy of the predetermined job category based on the difference between the estimated job period and the surrounding job period indicating the job period performed in the retrieved field. The 1 st accuracy of the predetermined job category indicates a possibility, for example, probability of performing a job of the predetermined job category in the estimated job area and during the estimated job. The 1 st accuracy of the predetermined job category may be calculated from a distribution during surrounding jobs in which jobs of the corresponding job category are performed in each surrounding field. When the calculated 1 st accuracy is greater than the predetermined threshold, the abnormal job monitoring part 170 determines that the corresponding predetermined job type is a job to be performed in the estimated job area. Further, the abnormal job monitoring part 170 may calculate the 1 st accuracy using the order of the surrounding job categories of the jobs performed in the surrounding field.

When the estimated work area is registered as a field, in step S230, the abnormal work monitoring part 170 determines whether or not the crop cultivated in the corresponding field is registered. Crops cultivated in the registered fields are registered in the job data 300. The abnormal work monitoring part 170 searches the work data 300 for the crop cultivated in the field corresponding to the estimated work area. When the cultivated crop is registered in the job data 300, the abnormal job monitoring part 170 performs the process of step S250. When the cultivated crop is not registered in the job data 300, the abnormal job monitoring part 170 performs the process of step S240.

In step S240, the abnormal job monitoring part 170 determines a predetermined job category based on a past job category indicating a job category of a job performed in the past in the field corresponding to the job area. The abnormal job monitoring part 170 extracts, from the job data 300, the past job type of the job performed on the corresponding field and the past job period indicating the job period thereof. The abnormal job monitoring part 170 extracts a past job category of a job performed in a corresponding field at a time corresponding to the estimated job period, for example, at the same time as 1 year or more, and determines the extracted past job category as a predetermined job category. The abnormal job monitoring part 170 may determine the predetermined job type based on the order of the past job types of the jobs performed in the corresponding field in the past.

The abnormal job monitoring part 170 may calculate the 2 nd accuracy of the predetermined job category based on the difference between the estimated job period and the past job period performed in the corresponding field in the past. The 2 nd accuracy of the predetermined job category indicates a possibility, e.g., probability, of performing a job of the predetermined job category in the estimated job area and during the estimated job. The 2 nd accuracy of the predetermined job category may be calculated from a distribution during past jobs, for example, during jobs of each year, in which the jobs of the corresponding job category are performed in the corresponding field. When the calculated 2 nd accuracy is greater than the predetermined threshold, the abnormal job monitoring part 170 determines that the corresponding predetermined job type is a job to be performed in the estimated job area. Further, the abnormal job monitoring part 170 may calculate the 2 nd accuracy using the order of the past job categories of the jobs performed in the corresponding fields in the past.

When the crop cultivated in the corresponding field has been registered, the abnormal operation monitor 170 determines a predetermined operation type based on the cultivation history of the registered crop in step S250. The abnormal operation monitoring unit 170 extracts a cultivation history related to the crop cultivated in the corresponding field from the cultivation history data 310 stored in the storage device 140 shown in fig. 1. The abnormal job monitoring part 170 determines a predetermined job type corresponding to the job performed in the estimated job area based on the estimated job period and the extracted cultivation history. For example, the abnormal job monitoring part 170 determines, based on the extracted cultivation history, a history job type of a job to be performed at a history time corresponding to the estimated job period, for example, a history time closest to the estimated job period, as a predetermined job type. The abnormal job monitoring part 170 may determine the predetermined job type based on the order of the history job types of the jobs registered in the cultivation history.

For example, it is assumed that "cultivated land" and "ridging" are performed in 5 months on a field corresponding to the cultivation history data 310 shown in fig. 2. In this case, the abnormal job monitoring part 170 determines that the predetermined job category is "fertilizer application" based on the cultivation history data 310 in step S250.

The abnormal job monitoring part 170 may calculate the 3 rd accuracy of the predetermined job category based on the difference between the cultivation history and the job period performed in the corresponding field. The 3 rd accuracy of the predetermined job category indicates a possibility, e.g., probability, of performing a job of the predetermined job category in the estimated job area and during the estimated job. The history time of the operation of the corresponding operation category is extracted from the cultivation history, and the 3 rd accuracy of the predetermined operation category is calculated based on the difference between the extracted history time and the estimated operation period. When the calculated 3 rd accuracy is greater than the predetermined threshold value, the abnormal job monitoring part 170 determines that the corresponding predetermined job type is a job to be performed in the estimated job area. The abnormal job monitoring part 170 may calculate the 3 rd accuracy using the order of the history job types of the jobs registered in the cultivation history.

As described above, the abnormal job monitoring part 170 determines the predetermined job type. The abnormal job monitoring part 170 performs the processing of step S140 and subsequent steps shown in fig. 4 using the determined predetermined job type. This reduces the influence on the crop caused by the operator performing the wrong operation.

For example, when the operator makes a mistake about "fertilizer application" to be performed in the late 5 months and performs "sowing" on the field corresponding to the cultivation history data 310 shown in fig. 2, the abnormal work monitoring part 170 notifies the operator that a work different from the predetermined work type is performed. Thus, the occurrence of crop growth failure due to forgetting to apply fertilizer can be reduced. The abnormal operation monitoring unit 170 can reduce the missing of the sowing time by notifying the operator that the sowing to be performed in the last ten days of 6 months has not been performed. Similarly, the abnormal operation monitoring unit 170 can reduce crop dysplasia caused by "control" or "fertilization" not performed for 8 months or 9 months. In addition, even when the "control" or "fertilizer application" is excessively performed, the abnormal operation monitoring unit 170 notifies the operator that the abnormal operation is performed, and thus, the "control" or "fertilizer application" can be reduced from being excessively performed.

As shown in fig. 5, the abnormal job monitoring part 170 uses, as the predetermined job category, any one of the 1 st predetermined job category determined based on the jobs in the surrounding field, the 2 nd predetermined job category determined based on the past jobs in the same field, and the 3 rd predetermined job category determined based on the cultivation history. The abnormal job monitoring part 170 preferentially uses the 3 rd predetermined job category, the 2 nd predetermined job category, and the 1 st predetermined job category in this order, so that the erroneous job can be monitored by preferentially using the job category more suitable for cultivation.

(modification)

The configuration described in the embodiment is an example, and the configuration may be changed within a range that does not interfere with the function. The following examples are shown: the abnormal job monitoring part 170 determines a predetermined job type using any one of a job in the surrounding field, a past job in the same field, and a cultivation history, but is not limited thereto. The abnormal job monitoring part 170 may determine a predetermined job type using 2 or more of the jobs in the surrounding field, the past jobs in the same field, and the cultivation history.

For example, in step S240 shown in fig. 5, the abnormal job monitoring part 170 determines a predetermined job type using a job in the surrounding field and a past job in the same field. In this case, the abnormal job monitoring part 170 executes the process of step S220, and determines the 1 st predetermined job type based on the jobs in the surrounding field. The abnormal job monitoring part 170 executes the process of step S240, and determines the 2 nd predetermined job type based on the past job in the same field. The abnormal job monitoring part 170 determines a predetermined job category including the 1 st predetermined job category and the 2 nd predetermined job category as a job category of a job performed in the job area.

In addition, in step S240 shown in fig. 5, the abnormal job monitoring part 170 may calculate the accuracy of the predetermined job category based on the jobs in the surrounding field and the past jobs in the same field, and determine the predetermined job category based on the calculated accuracy. For example, the abnormal job monitoring part 170 performs the process of step S220 to calculate the 1 st accuracy of the predetermined job category based on the jobs in the surrounding field. Further, the abnormal job monitoring part 170 performs the process of step S240 to calculate the 2 nd accuracy of the predetermined job category based on the past jobs in the same field. The abnormal job monitoring part 170 calculates the accuracy of the predetermined job category based on the 1 st accuracy and the 2 nd accuracy. For example, the abnormal job monitoring part 170 calculates the accuracy of the predetermined job category by adding the value obtained by multiplying the 1 st accuracy by the 1 st coefficient and the value obtained by multiplying the 2 nd accuracy by the 2 nd coefficient. The abnormal job monitoring part 170 determines a predetermined job category using the calculated accuracy.

In step S250 shown in fig. 5, the abnormal job monitoring part 170 may determine a predetermined job type based on the jobs in the surrounding field, the past jobs in the same field, and the cultivation history. In this case, the abnormal job monitoring part 170 executes the process of step S220, and determines the 1 st predetermined job type based on the jobs in the surrounding field. The abnormal job monitoring part 170 executes the process of step S240, and determines the 2 nd predetermined job type based on the past job in the same field. The abnormal job monitoring part 170 executes the processing of step S250, and determines the 3 rd predetermined job type based on the cultivation history. The abnormal job monitoring part 170 determines a predetermined job category including the 1 st predetermined job category, the 2 nd predetermined job category, and the 3 rd predetermined job category as a job category of a job performed in the job area.

In step S240 shown in fig. 5, the abnormal job monitoring part 170 may calculate the accuracy of the predetermined job type based on the jobs in the surrounding field, the past jobs in the same field, and the cultivation history, and determine the predetermined job type based on the calculated accuracy. For example, the abnormal job monitoring part 170 performs the process of step S220 to calculate the 1 st accuracy of the predetermined job category based on the jobs in the surrounding field. Further, the abnormal job monitoring part 170 performs the process of step S240 to calculate the 2 nd accuracy of the predetermined job category based on the past jobs in the same field. The abnormal job monitoring part 170 performs the process of step S250, and calculates the 3 rd accuracy of the predetermined job type based on the cultivation history. The abnormal job monitoring part 170 calculates the accuracy of the predetermined job category based on the 1 st accuracy, the 2 nd accuracy, and the 3 rd accuracy. The abnormal job monitoring part 170 determines a predetermined job category using the calculated accuracy.

Further, the abnormal job monitoring part 170 may determine the predetermined job type by any method as long as it can determine the predetermined job type of the job to be performed in the job area. For example, the abnormal job monitoring part 170 may determine a predetermined job category based on a job plan registered in advance. For example, the data holding unit 150 holds a job plan input by a user, for example, a job type and a job time of a job performed in a field. In step S130 shown in fig. 4, the abnormal job monitoring part 170 determines a predetermined job type based on the job plan held by the data holding part 150 and the job period estimated by the job estimating part 160.

The following examples are shown: in step S110 shown in fig. 4, the work period is estimated as a period from when the work vehicle 30 starts to work to when it stops, but is not limited thereto. The work period may be a part of the work period during which work vehicle 30 performs the work, as long as the work period can be estimated. For example, the work period may be a period from when the work vehicle 30 is started up until a predetermined period elapses. In this case, the job management apparatus 100 may execute the processing shown in fig. 4 and notify the worker of an abnormality of the job while the work vehicle 30 is performing the job.

The above-described embodiments and modifications are examples, and the configurations described in the embodiments and modifications may be arbitrarily changed or/and arbitrarily combined within a range that does not interfere with the functions. In addition, if the necessary functions can be realized, some of the functions described in the embodiments and modifications may be omitted. For example, the job management apparatus 100 may acquire operation information from any job apparatus that performs a job in a field, such as an unmanned aerial vehicle.

The present application claims priority based on japanese patent application No. 2021-019890 filed on 10, 2, 2021, and the entire disclosure of which is incorporated herein.

Claims

1. A job management method is characterized in that,

the job management method includes the steps of:

estimating a job type of a job based on operation information of a job device when the job is performed in a job area in a 1 st field; and

when the job type is different from a predetermined job type of a job to be performed in the job area, an abnormality signal indicating abnormality of the job performed in the job area is output.

2. The job management method as set forth in claim 1, wherein,

the step of outputting the abnormality signal includes the steps of:

the predetermined job category is determined based on a surrounding job category of a job performed in a surrounding field of the job area and a surrounding time period indicating a time period of performing the job of the surrounding job category.

3. The job management method as set forth in claim 2, wherein,

the step of determining the predetermined job category includes the steps of:

calculating a 1 st accuracy of performing a job of the predetermined job category in the job area based on the surrounding job category and the surrounding time period; and

the predetermined job category is determined based on the calculated 1 st accuracy.

4. The job management method according to any one of claims 1 to 3, wherein,

the step of outputting the abnormality signal includes the steps of:

the predetermined job category is determined based on a past job category of a past job performed in the 1 st field including the job area and a past job period.

5. The job management method as set forth in claim 4, wherein,

the step of determining the predetermined job category includes the steps of:

calculating a 2 nd accuracy of a job of the predetermined job category in the job area based on the past job category and the past job period; and

the predetermined job category is determined based on the calculated 2 nd accuracy.

6. The job management method according to any one of claims 1 to 5, wherein,

the step of determining the predetermined job category includes the steps of:

the predetermined job type is determined based on the crop cultivated in the work area and a cultivation history indicating a history job type and a history time of a job performed for cultivating the crop.

7. The job management method as set forth in claim 6, wherein,

the step of determining the predetermined job category includes the steps of:

calculating a 3 rd accuracy of performing the job of the predetermined job category in the job area based on the history job category and the history time; and

the predetermined job category is determined based on the calculated 3 rd accuracy.

8. The job management method as set forth in claim 1, wherein,

the step of outputting the abnormality signal includes the steps of:

determining a 1 st predetermined job category based on a peripheral job category of a job performed in a peripheral field existing around the job area and a peripheral time period indicating a time period of performing the job of the peripheral job category;

determining a 2 nd predetermined job category based on a past job category of a past job performed in the 1 st field including the job area and a past job period;

determining a 3 rd predetermined job type based on the crop cultivated in the work area and a cultivation history indicating a history job type and a history time of a job performed for cultivating the crop; and

the predetermined job category is determined based on the 1 st predetermined job category, the 2 nd predetermined job category, and the 3 rd predetermined job category.

9. The job management method as set forth in claim 8, wherein,

the step of determining the predetermined job category includes the steps of:

the predetermined job category is preferentially determined in the order of the 3 rd predetermined job category, the 2 nd predetermined job category, and the 1 st predetermined job category.

10. The job management method as set forth in claim 8, wherein,

the step of determining the predetermined job category includes the steps of:

calculating a 1 st accuracy of performing a job of the predetermined job category in the job area based on the surrounding job category and the surrounding time period;

calculating a 2 nd accuracy of a job of the predetermined job category in the job area based on the past job category and the past job period;

the predetermined job category is determined based on the 1 st accuracy, the 2 nd accuracy, and the 3 rd accuracy.

11. A non-transitory storage medium, characterized in that,

the non-transitory storage medium stores a job management program that causes an arithmetic device to execute:

12. A job management apparatus, characterized in that,

the job management device includes:

a job estimation unit that estimates a job type of a job based on operation information of a job device when the job is performed in a job area in a 1 st field; and;

an abnormal job monitoring part which outputs an abnormal signal indicating that the job performed in the job area is abnormal when the job type is different from a predetermined job type of the job to be performed in the job area.