KR20230141767A - Work management method, work management device and storage medium - Google Patents

Abstract

The work management method includes estimating the work type of the work based on operation information of the work device when the work is being performed in the work area within the first packaging. Additionally, the work management method includes outputting 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. Outputting an abnormal signal may include determining the scheduled work type based on the surrounding work type of the work performed on the surrounding pavement of the work area and the surrounding period indicating the time when the work of the surrounding work type was performed.

Description

Work management method, work management device and storage medium

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

Recently, research has been conducted on using information about agricultural work in the field to analyze cultivation management.

Patent Document 1 (Japanese Patent Application Publication No. 2019-020923) discloses a cultivation support device that notifies various agricultural operations suitable for cultivation at a time appropriate for the cultivation area according to the cultivation history. This cultivation support device determines the time to perform agricultural work by correcting the cultivation power, which is the standard for work required for cultivation, according to the area where the field is located.

Japanese Patent Publication No. 2019-020923

In the technology described in Patent Document 1, even if the worker performs incorrect work, it is judged that appropriate work has been performed and notification is given to perform work corresponding to the cultivation ability.

However, workers who perform agricultural work often have multiple fields, and may perform the work in the wrong order or number of times for each field. In this case, the operator may not notice that he or she has performed incorrect work, which may have a significant impact on the growth of the crop.

In view of the above situation, one purpose 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 purposes can be understood from the description and description of the embodiments below.

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

A storage medium according to an embodiment for achieving the above object stores a job management program. The work management program causes the computing device to estimate the work type of the work based on operation information of the work device when work is being performed in the work area within the first packaging. Additionally, the work management program causes the computing device to output 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.

According to the above aspect, the work management device can notify the worker to that effect when there is a possibility that the worker is performing work incorrectly.

1 is a schematic diagram of a job management system according to one embodiment.
FIG. 2 is a diagram showing the configuration of power generation data in one embodiment.
Fig. 3 is a diagram showing functional blocks executed by the job management system in one embodiment.
Fig. 4 is a flowchart showing processing by the job management system in one embodiment.
Fig. 5 is a flowchart showing processing for determining the type of scheduled work 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, as shown in FIG. 1 , the work management system 1000 includes a work management device 100 and a terminal 200 . The work management device 100 is connected to enable communication with the terminal 200 and the work vehicle 30 via the network 20, for example, the Internet.

The work management device 100 acquires operation information on the pavement from the work vehicle 30, and estimates information about the work, such as work period, work type, work area, etc., based on the acquired operation information. The work type indicates the type of work performed in the field, such as planting, planting, fertilizing, and planting. The work area represents the area where the work was performed, for example, the area within the packaging where the work was performed, or the area of the entire packaging where the work was performed. Additionally, the work management device 100 determines the type of work scheduled to be performed in the estimated work area based on work data related to work performed in the past or redevelopment capabilities. When the estimated work type is different from the determined scheduled work type, the work management device 100 informs the user, for example, through the terminal 200 that the type of work performed in the work area is likely to be incorrect. Notify workers, packaging owners, etc. In this way, the task management system 1000 can support the user in performing tasks with certainty. Additionally, when the user intends to perform a job that is different from the scheduled job type, the user registers the estimated job type as the correct job in the terminal 200. Accordingly, the work management system 1000 can detect changes in cultivation methods by recording changes in artificial work.

In addition, the operation information acquired from the work vehicle 30 includes information indicating the state of the work vehicle 30 when working on the pavement, for example, the speed and steering angle of the work vehicle 30. , engine speed, ON/OFF status of various clutches, position information of the work vehicle 30 at each time, information indicating the work period, etc. Work vehicle (30) When the vehicle towing the work machine is, for example, a tractor, the operation information includes PTO (power take-off) rotation speed when transmitting power to the work machine, hitch height indicating the attitude of the work machine, or Information such as lift arm angle may be included.

The configuration of the task management device 100 will be described. The job management device 100 includes an input/output device 110, an arithmetic device 120, a communication device 130, and a storage device 140. The task management device 100 is, for example, a computer. Information for the arithmetic unit 120 to execute processing is input to the input/output device 110. Additionally, 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, for example, a keyboard, mouse, microphone, display, speaker, touch panel, etc. The input/output device 110 may be omitted.

The communication device 130 is electrically connected to the network 20 and communicates with each device through the network 20. The communication device 130 transmits operation information acquired from the work vehicle 30 to the arithmetic device 120 . Additionally, the signal generated by the computing device 120 is transmitted to the terminal 200. The communication device 130 includes various interfaces, such as, for example, 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, reskilling data 310, and work management program 320. The storage device 140 is used as a non-transitory tangible storage medium to store the task management program 320. The job 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 paving work, for example, data calculated from operation information from the work vehicle 30 . For example, the work data 300 includes work period information indicating the work period, work area information indicating the work area, and work type information indicating the work type. Work period information, work area information, and work type information are registered in association with work data 300. The work period represents the time when the packaging work started and ended. The work area represents the area where packaging work was performed, such as location and shape. The work type indicates the type of work performed in the field, such as planting, planting, fertilizing, planting, etc.

Cultivation calendar data 310 indicates crops to be grown, cultivation calendar according to region, for example, calendar work type, which is the type of work performed for cultivation, and calendar period, which is the time when the work is performed. For example, the cultivation calendar data 310 represents the calendar period according to the crop and region to be cultivated, as shown in FIG. 2 . In the example shown in FIG. 2, when “soybeans” are cultivated in Hokkaido, “growing” is carried out in mid-May, and “row laying” and “fertilizing (fertilizing)” are carried out in late May. Additionally, it indicates that “sowing” is carried out in early June and “weeding” is carried out in mid-June.

The work data 300 and the repowering data 310 are read by the arithmetic device 120 shown in FIG. 1 and used for various data processing to detect abnormalities in work performed in packaging. The arithmetic unit 120 reads and executes the work management program 320 from the storage device 140 and detects abnormalities in work performed on packaging. For example, the computing unit 120 includes a central processing unit (CPU), etc.

The arithmetic unit 120 reads and executes the job management program 320, thereby realizing a data holding unit 150, a job estimation unit 160, and an abnormal job detection unit 170, as shown in FIG. 3. do. The data holding unit 150 maintains work data 300 and repowering 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 compares the estimated work type with the scheduled work type of work to be performed on the pavement and detects abnormalities in the performed work.

Next, the configuration 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, tablet, mobile phone, etc. Information for the arithmetic unit 220 to execute processing is input to the input/output device 210. Additionally, the input/output device 210 outputs the results of the processing performed by the arithmetic device 220. The input/output device 210 includes various input devices and output devices, and includes, for example, a keyboard, mouse, microphone, display, speaker, touch panel, etc.

The communication device 230 is electrically connected to the network 20 and communicates with each device through 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 . Additionally, the signal generated by the computing device 220 is transmitted to the task management device 100. The communication device 230 includes various interfaces, such as, for example, NIC (Network Interface Card) and USB (Universal Serial Bus).

The storage device 240 stores various data, such as a notification program 330, for notifying the user of job abnormalities detected by the job management device 100. The storage device 240 is used as a non-transitory tangible storage medium to store 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 that can be downloaded from a server. The notification program 330 may be provided by being recorded in the storage medium 1.

By reading and executing the notification program 330, the arithmetic unit 220 cooperates with the input/output device 210, as shown in FIG. 3, to notify the user of job abnormalities detected by the job management unit 100. The notification unit 250 is implemented. The notification unit 250 acquires information indicating a job abnormality detected by the job management device 100 and notifies the user of the job abnormality. The notification unit 250 displays the job type estimated by the job management device 100. The notification unit 250 updates information registered in the job data 300 according to the user's operation.

(Operation of task management device)

When the operation unit 120 of the work management device 100 receives operation information from the work vehicle 30, it reads and executes the work management program 320. By executing the job management program 320, the computing unit 120 executes the processing shown in FIG. 4.

In step S110, the work estimation unit 160 realized by the computing 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 time from the time the work vehicle 30 is started to the time the work vehicle 30 is stopped as the work period. In addition, the work estimation unit 160 is based on the start time and end time of the work of the work vehicle 30, for example, the time at which the work machine towed by the work vehicle 30 is driven and the time at which it is stopped. , you can estimate the work period. The work period may be estimated based on the time the work vehicle 30 enters the pavement and the time it leaves the pavement. Additionally, 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 in 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 indicating the position at each time moved during the work period. The acquired positional information is transmitted from the work vehicle 30 to the computing device 120 of the work management device 100. The work estimation unit 160 implemented by the computing device 120 estimates the work area based on the acquired position information. For example, the work area is displayed as an arbitrary closed shape, such as a polygon or rectangle, including the position shown in the acquired position information. For example, the work area is displayed as a figure surrounding all of the acquired location information. The work estimation unit 160 associates the estimated work area with the corresponding work period and registers it in the work data 300. Thereby, the work area is associated with the determined work period.

In step S120, the work type estimation unit 160 estimates the work type based on the operation information received from the work vehicle 30. For example, the job estimation unit 160 estimates the job type using a learned model obtained through machine learning. In this case, the learned model is trained to estimate the job type from operation information. Additionally, the work estimation unit 160 may estimate the work type based on the type of work vehicle 30 or work machine. In this case, the data holding unit 150 stores and maintains work corresponding data associating the type of work vehicle 30 or work machine with the work type in the storage device 140 . The job estimation unit 160 estimates the job type based on job corresponding data.

The work estimation unit 160 associates the estimated work type with the corresponding work period and registers it in the work data 300. Thereby, 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 the 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. determines. 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 job type estimated by the job 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 ends the processing. 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 processing 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 job is abnormal based on the abnormality signal. For example, the notification unit 250 displays a notification image notifying an abnormality in work 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 type. By viewing the notification image, the user can check the work period, work area, and work type, and check whether there was an error in the work performed on the packaging. The notification unit 250 may output a warning sound indicating an 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 an error in the work performed on the packaging.

When the estimated job type is incorrect, the user inputs a correction operation to correct the job type into 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 device 100 corrects the job type registered in the job data 300 based on the correction signal.

When the user performs the estimated job type with intent, he or she inputs a confirmation operation indicating that a normal job has been performed into the input/output device 210 of the terminal 200. The notification unit 250 generates a normal operation signal indicating that a normal operation has been performed, based on the input operation. The data holding unit 150 of the job management device 100 registers the normal job in the job data 300 based on the normal job signal. In this way, the data holding unit 150 records artificial changes in the type of work performed during cultivation. 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 erroneously performs the estimated job type, he/she inputs an erroneous operation indicating that the incorrect job was performed to the input/output device 210 of the terminal 200. The notification unit 250 generates an erroneous operation signal indicating that an incorrect operation has been performed, based on the input operation. The data holding unit 150 of the job management device 100 registers the erroneous job in the job data 300 based on the erroneous job signal. In this way, the data holding unit 150 records the job type of the erroneously performed job. The abnormal work detection unit 170 determines the scheduled work type without using the work type of the erroneously performed work. As a result, the abnormal work detection unit 170 can reduce the influence of erroneously performed work on the determination of the scheduled work type.

(How to estimate the type of scheduled work)

In step S130 shown in FIG. 4, the abnormal work detection unit 170 executes the process shown in FIG. 5 to determine the scheduled work type. In step S210, the abnormal operation detection unit 170 determines whether the work area is included in the area registered as packaging. In the work data 300, packaging on which the user has worked in the past is recorded. The abnormal work detection unit 170 extracts the packaging corresponding to the work area estimated by the work estimation unit 160 from the work data 300 . When the corresponding package is included in the work data 300, the abnormal work detection unit 170 determines that the estimated work area is registered as a package, and executes the process of step S230. When the corresponding package 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 package, and executes the process of step S220.

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

Additionally, the abnormal work detection unit 170 may determine the scheduled work type based on the order of the surrounding work types of the work performed on the pavement existing in the surroundings. For example, the abnormal work detection unit 170 extracts from the work data 300 the work types of the work performed so far in the estimated work area. By comparing the order of the job type of the extracted work with the order of the surrounding work types of the work performed on the surrounding pavement, the abnormal work detection unit 170 determines the scheduled work type of the work to be performed in the work area. do. For example, it is said that “competition” and “row-building” were being carried out one after another in the work area until now. In addition, in the surrounding pavement, when “starting,” “raising,” and “fertilizing” were being carried out one after another, the abnormal work detection unit 170 detects that the scheduled work type of the work to be performed in the work area is “ It is judged as “right or wrong.”

The abnormal work detection unit 170 may calculate the first accuracy of the scheduled work type based on the difference between the estimated work period and the surrounding work period representing the work period performed on the retrieved packaging. The first 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 area and during the estimated work period. The first accuracy of the scheduled work type may be calculated from the distribution of the surrounding work periods in which work of the corresponding work type was performed in each surrounding pavement. When the calculated first accuracy is greater than the predetermined threshold, the abnormal work detection unit 170 determines the corresponding scheduled work type as the work to be performed in the estimated work area. Additionally, the abnormal operation detection unit 170 may calculate the first accuracy using the order of the surrounding work types of the work performed on the packaging existing in the surroundings.

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

In step S240, the abnormal work detection unit 170 determines the scheduled work type based on the past work type indicating the work type of work performed in the past on the pavement corresponding to the work area. The abnormal operation detection unit 170 extracts from the operation data 300 the past operation type of the operation performed on the corresponding packaging and the past operation period indicating the operation period. The abnormal work detection unit 170 extracts the past work type of work performed on the corresponding packaging at a time corresponding to the estimated work period, for example, the same time one year ago, and divides the extracted past work type into the scheduled work type. It is judged as Additionally, the abnormal operation detection unit 170 may determine the scheduled operation type based on the order of past operation types of operations performed in the past on the corresponding packaging.

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 on the corresponding packaging. The second 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 area and during the estimated work period. The second accuracy of the scheduled work type may be calculated from the distribution of the past work period in which the work of the corresponding work type was performed in the corresponding packaging, for example, the work period of each year. When the calculated second accuracy is greater than the predetermined threshold, the abnormal work detection unit 170 determines the corresponding scheduled work type as the work to be performed in the estimated work area. Additionally, the abnormal operation detection unit 170 may calculate the second accuracy using the order of past operation types of operations performed in the past on the corresponding packaging.

When crops being grown in the corresponding field are registered, in step S250, the abnormal operation detection unit 170 determines the type of scheduled operation based on the cultivation history of the registered crops. The abnormal operation detection unit 170 extracts the cultivation history for crops grown in the corresponding field from the cultivation history data 310 stored in the storage device 140 shown in FIG. 1 . The abnormal work detection unit 170 determines the scheduled work type of the work to be performed in the estimated work area based on the estimated work period and the extracted redevelopment power. For example, the abnormal work detection unit 170 determines the calendar work type of the work to be performed in the calendar period corresponding to the estimated work period, for example, the calendar period closest to the estimated work period, from the extracted rescheduling power. Judgment is made according to the type of work scheduled. Additionally, the abnormal job detection unit 170 may determine the scheduled job type based on the order of the calendar job types of the jobs registered in the calendar.

For example, it is said that in the field corresponding to the cultivation data 310 shown in FIG. 2, “game” and “row planting” were carried out in May. In this case, the abnormal work detection unit 170 determines that the scheduled work type is “fertilization” based on the replanting 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 redevelopment ability and the work period performed on the corresponding packaging. 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 area and during the estimated work period. The third accuracy of the scheduled work type may be calculated by extracting the calendar period in which the work of the corresponding work type is performed from the cultivation calendar, and based on the difference between the extracted calendar period and the estimated work period. When the calculated third probability is greater than the predetermined threshold, the abnormal work detection unit 170 determines the corresponding scheduled work type as the work to be performed in the estimated work area. Additionally, the abnormal job detection unit 170 may calculate the third accuracy using the order of calendar job types of jobs registered in the rearrangement 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 processing from step S140 shown in FIG. 4. As a result, the impact on crops caused by workers performing incorrect work can be reduced.

For example, in the field corresponding to the cultivation data 310 shown in FIG. 2, when the worker mistakenly performed “fertilization” and “seeding” that should have been performed in late May, the abnormal operation detection unit 170 Notify workers that work that is different from the type of work scheduled has been performed. In this way, poor crop growth caused by forgetting to “fertilize” can be reduced. Additionally, the abnormal operation detection unit 170 notifies the operator that “seeding” that should have been carried out in early June has not been carried out, thereby reducing the occurrence of passing the sowing season. Similarly, the abnormal operation detection unit 170 reduces poor growth of crops due to “control” or “fertilization” not being carried out in August and September. In addition, even when excessive “pest control” or “fertilization” is performed, the abnormal operation detection unit 170 notifies the operator that abnormal work has been performed, thereby reducing excessive “pest control” or “fertilization”. .

In addition, as shown in FIG. 5, the abnormal work detection unit 170 determines a first scheduled work type determined based on work in the surrounding pavement, and a second scheduled work type determined based on past work in the same pavement. One of the type and the third scheduled work type determined based on cultivation ability is adopted as the scheduled work type. The abnormal operation detection unit 170 can detect erroneous operations by preferentially employing the third scheduled operation type, the second scheduled operation type, and the first scheduled operation type in that order, thereby preferentially using the operation type more suitable for cultivation. there is.

(variation example)

The configuration described in the embodiment is an example, and the configuration can be changed within the range that does not impair the function. The abnormal work detection unit 170 has shown an example of determining the type of scheduled work using any one of work on surrounding pavement, past work on the same pavement, and redevelopment history, but it is not limited to this. . The abnormal work detection unit 170 may determine the type of scheduled work using two or more of the work in the surrounding pavement, past work in the same pavement, and redevelopment history.

For example, in step S240 shown in FIG. 5 , the abnormal work detection unit 170 determines the type of scheduled work using work in the surrounding pavement and past work in the same pavement. In this case, the abnormal work detection unit 170 executes the process of step S220 and determines the first scheduled work type based on the work in the surrounding pavement. Additionally, the abnormal operation detection unit 170 executes the process of step S240 and determines the second scheduled operation type based on past operations on the same packaging. 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.

Furthermore, 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 on the surrounding pavement and the past work on the same pavement, and calculates the accuracy of the calculated work type. The type of scheduled work may be determined based on the diagram. For example, the abnormal operation detection unit 170 executes the process of step S220 and calculates the first accuracy of the scheduled operation type based on the operation in the surrounding pavement. Additionally, the abnormal operation detection unit 170 executes the process of step S240 and calculates the second accuracy of the scheduled operation type based on past operations on the same packaging. The abnormal operation detection unit 170 calculates the accuracy of the scheduled operation 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 first accuracy multiplied by the first coefficient and the second accuracy multiplied by the second coefficient. The abnormal work detection unit 170 determines the scheduled work type using the calculated accuracy.

Additionally, in step S250 shown in FIG. 5, the abnormal work detection unit 170 may determine the type of scheduled work based on past work and redevelopment history on the same pavement as the work on the surrounding pavement. In this case, the abnormal work detection unit 170 executes the process of step S220 and determines the first scheduled work type based on the work in the surrounding pavement. Additionally, the abnormal operation detection unit 170 executes the process of step S240 and determines the second scheduled operation type based on past operations on the same packaging. Then, the abnormal work detection unit 170 executes the process of step S250 and determines the third scheduled work type based on the redistribution ability. 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.

Furthermore, in step S240 shown in FIG. 5, the abnormal operation detection unit 170 calculates the accuracy of the scheduled work type based on the past work and redevelopment history on the same pavement as the work on the surrounding pavement, and , the type of scheduled work may be determined based on the calculated accuracy. For example, the abnormal operation detection unit 170 executes the process of step S220 and calculates the first accuracy of the scheduled operation type based on the operation in the surrounding pavement. Additionally, the abnormal operation detection unit 170 executes the process of step S240 and calculates the second accuracy of the scheduled operation type based on past operations on the same packaging. Additionally, the abnormal work detection unit 170 executes the process of step S250 and calculates the third probability of the scheduled work type based on the redistribution power. The abnormal operation detection unit 170 calculates the accuracy of the scheduled operation type based on the first, second, and third accuracies. The abnormal work detection unit 170 determines the scheduled work type using the calculated accuracy.

Additionally, 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 type of scheduled work based on a work plan registered in advance. For example, the data holding unit 150 maintains the work plan input by the user, for example, the work type and work period of work performed on packaging. In step S130 shown in FIG. 4, the abnormal work detection unit 170 determines the scheduled work type based on the work plan maintained by the data holding unit 150 and the work period estimated by the work estimation unit 160. Judge.

In step S110 shown in FIG. 4, the work period shows an example in which the work period is estimated as the period from when the work vehicle 30 starts work until it stops, but it is not limited to this. The work period may be an estimate of the period during which the work vehicle 30 is performing work, and may be a partial period during which the work vehicle 30 is performing work. For example, the work period may be the period from when the work vehicle 30 starts until a predetermined period of time has elapsed. In this case, the work management device 100 may execute the processing shown in FIG. 4 while the work vehicle 30 is performing work and notify the operator of work abnormalities.

The embodiments and modifications described above are examples, and the configurations described in each embodiment and modifications may be arbitrarily changed and/or combined arbitrarily as long as they do not impair the function. Additionally, some functions described in the embodiment and modified examples may be omitted if the necessary functions can be realized. For example, the work management device 100 may acquire operation information from any work device that performs work in packaging, 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 (12)

Estimating the work type of the work based on operation information of the work equipment when work is performed in the work area in the first packaging,
A work management method comprising outputting 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. According to claim 1,
Outputting the abnormal signal determines the scheduled work type based on the surrounding work type of the work performed on the surrounding pavement of the work area and the surrounding period indicating the time when the work of the surrounding work type was performed. Task management methods, including: According to claim 2,
To determine the type of scheduled work,
Based on the surrounding work type and the surrounding time, calculating a first probability that the scheduled work type is performed in the work area;
A work management method comprising determining the scheduled work type based on the calculated first probability. The method according to any one of claims 1 to 3,
A work management method wherein 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 on the first pavement including the work area. According to claim 4,
To determine the type of scheduled work,
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;
A work management method comprising determining the scheduled work type based on the calculated second probability. The method according to any one of claims 1 to 5,
Determining the scheduled work type is based on the crops being grown in the work area, the calendar work type of the work performed to grow the crops, and a cultivation calendar indicating the calendar time. A task management method that includes: According to claim 6,
To determine the type of scheduled work,
Based on the calendar task type and the calendar period, calculating a third probability that the scheduled task type has been performed in the work area;
A work management method comprising determining the scheduled work type based on the calculated third probability. According to claim 1,
Outputting the abnormal signal is,
determining a first scheduled work type based on the surrounding work type of work performed on the surrounding pavement existing in the periphery of the work area and the surrounding period indicating the time when the work of the surrounding work type was performed;
determining a second scheduled work type based on the past work type and past work period of past work performed on the first pavement including the work area;
determining a third scheduled work type based on crops being grown in the work area, calendar work types of work performed to grow the crops, and a cultivation calendar indicating a calendar period;
A work management method comprising determining the scheduled work type based on the first scheduled work type, the second scheduled work type, and the third scheduled work type. According to claim 8,
To determine the type of scheduled work,
A work management method comprising determining the third scheduled work type, the second scheduled work type, and the first scheduled work type preferentially as the scheduled work type in that order. According to claim 8,
To determine the type of scheduled work,
Based on the surrounding work type and the surrounding time, calculating a first probability that the scheduled work type is performed in the work area;
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;
Based on the calendar task type and the calendar period, calculating a third probability that the scheduled task type has been performed in the work area;
A work management method comprising determining the scheduled work type based on the first accuracy, the second accuracy, and the third accuracy. Estimating the work type of the work based on operation information of the work equipment when work is performed in the work area in the first packaging,
Storing a job management program that causes the computing device to output an abnormal signal indicating that the job being performed in the work area is abnormal when the job type is different from the scheduled work type of the work to be performed in the work area. Non-transitory memory medium. a work estimation unit that estimates the work type of the work based on operation information of the work equipment when the work is being performed in the work area within the first packaging;
A work management device comprising an abnormal work detection unit that outputs 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.

Images