Estimation system, estimation method, and estimation program

Abstract

To easily identify a work performed by a user and associate the work with a stress estimation result.SOLUTION: An estimation system comprises: a position detection section for detecting a position of a user; a work estimation section for estimating candidates for a work performed by the user on the basis of the position of the user; a displayed work setting section for displaying the work candidates estimated by the work estimation section on a screen of a wearable device used by the user; a vital data acquisition section that identifies the work selected by input operation by the user among the work candidates displayed on the screen of the wearable device as the work performed by the user, and acquires information of the identified work and vital data of the user in association with each other; and a stress estimation section that estimates stress of the user on the basis of the vital data of the user, and stores a stress estimation result and the work selected by the input operation by the user in a storage section in association with each other.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an estimation system, an estimation method, and an estimation program. [Background technology]

[0002] A technology has been proposed in which a user wears a wearable device, collects the user's vital data (biological information (e.g., skin potential and heart rate)), and estimates the user's psychological burden (stress). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-181160 A Summary of the Invention [Problem to be solved by the invention]

[0004] For example, the stress estimation results may be used to determine which tasks cause the most stress, and the direction of work or guidance may be changed accordingly. For this reason, there has been a demand to clarify the relationship between the specific tasks and the degree of stress.

[0005] However, there is a problem in that the process of a user manually inputting from scratch the tasks that the user will perform from among the many tasks and linking them to vital data is extremely cumbersome.

[0006] The present invention has been made in consideration of the above, and aims to provide an estimation system, an estimation method, and an estimation program that can easily identify tasks performed by a user and associate them with stress estimation results. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the object, the estimation system of the present invention is characterized by having a position detection unit that detects a user's position, a first estimation unit that estimates candidate tasks to be performed by the user based on the user's position, a display control unit that displays the candidate tasks estimated by the first estimation unit on a screen of a terminal device used by the user, an acquisition unit that identifies a task selected by an input operation of the user from the candidate tasks displayed on the screen of the terminal device as a task to be performed by the user and acquires information on the identified task in association with vital data of the user, and a second estimation unit that estimates stress of the user based on the vital data of the user, and stores the stress estimation result in association with the task selected by the input operation of the user in a memory unit. Effect of the Invention

[0008] According to the present invention, an operation performed by a user can be easily identified and associated with a stress estimation result. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating a configuration of an estimation system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating the configuration of the wearable device shown in FIG. [Diagram 3] FIG. 3 is a diagram illustrating the configuration of the server device shown in FIG. [Figure 4] FIG. 4 is a diagram showing an example of a data configuration of the process chart data shown in FIG. [Diagram 5] FIG. 5 is a diagram showing an example of a data configuration of the schedule data shown in FIG. [Figure 6] FIG. 6 is a diagram showing an example of a task menu displayed on the screen of a wearable device. [Figure 7] FIG. 7 is a diagram showing an example of a task menu displayed on the screen of a wearable device. [Figure 8]FIG. 8 is a diagram showing an example of a task menu displayed on the screen of the wearable device. [Figure 9] FIG. 9 is a sequence diagram showing a processing procedure of the communication method according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of a computer that implements each device of the estimation system by executing a program. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. In addition, in the description of the drawings, the same parts are indicated by the same reference numerals.

[0011] [Embodiment Mode] In the embodiment, candidate tasks to be performed by the user are estimated using at least the user's position, and the estimated candidate tasks are displayed on the screen of the terminal device used by the user. In the embodiment, the user is allowed to select the task to be actually performed from the candidate tasks, thereby easily identifying the user's task. In the embodiment, the stress estimation result estimated based on the user's vital data is stored in association with information on the identified user's task.

[0012] [Estimation system] First, an estimation system according to an embodiment will be described. Fig. 1 is a diagram illustrating a configuration of the estimation system according to an embodiment.

[0013] As shown in FIG. 1, an estimation system 100 according to an embodiment includes a server device 10 that controls and manages the processing of the estimation system 100, a communication terminal 20 carried by a user, and a wearable device 30 worn by the user.

[0014] The server device 10 controls and manages the processing of the estimation system 100. The server device 10 estimates candidate tasks to be performed by the user based on the user's location, and displays a list of the estimated candidate tasks on the screen of the terminal device used by the user. The server device 10 also estimates the user's stress based on the user's vital data, and stores the stress estimation result in a memory unit in association with the task selected by the user's input operation.

[0015] The wearable device 30 is a device worn by a user. The wearable device 30 is, for example, a wristwatch-type device, but is not limited to a wristwatch-type device. The wearable device 30 displays a list of work candidates estimated by the server device 10 on, for example, a touch panel screen. When a work is selected by a user's input operation, the wearable device 30 measures the user's vital data, associates the measured time-series vital data with the work selected by the user's input operation, and transmits the data to the server device 10 via the communication terminal 20. The vital data is, for example, a heart rate, a body temperature, a blood flow, and a respiratory rate.

[0016] The communication terminal 20 is a communication terminal carried by a user. The communication terminal 20 is, for example, a smart device such as a tablet or a smartphone, and has a communication function, a position detection function (for example, a GPS function), a photography function, a text input function, etc. The communication terminal 20 connects to the server device 10 and the wearable device 30 via an application for acquiring vital data, and transmits to the server device 10 the time-series vital data measured by the wearable device 30 in association with an operation selected by a user's input operation.

[0017] In the following description, an embodiment will be described taking as an example a case where a list of candidate tasks is displayed on the screen of the wearable device 30. However, this is not limited to this, and for example, the communication terminal 20 may display the list of candidate tasks on a screen, or may display the list on an operation panel of the device on which the user is working or on a display near the device.

[0018] [Wearable devices] Next, a description will be given of the wearable device 30. Fig. 2 is a diagram illustrating the configuration of the wearable device 30 shown in Fig. 1.

[0019] As shown in FIG. 2, the wearable device 30 includes a communication unit 31, a sensor 32, an input / output unit 33, a storage unit 34, and a control unit 35.

[0020] The communication unit 31 wirelessly communicates with other devices. The communication unit 31 is a communication interface that transmits and receives various information to and from other devices connected via Bluetooth (registered trademark), a network, or the like.

[0021] The sensor 32 detects vital data of the user wearing the wearable device 30. The sensor 32 detects, for example, the user's heart rate, body temperature, blood flow, and respiratory rate.

[0022] The input / output unit 33 outputs various information and receives various information input by a user's input operation. The input / output unit 33 includes, for example, a touch panel, a speaker, a microphone, etc. The input / output unit 33 outputs a task selection menu, an operation screen for vital data measurement operation, etc., and audio.

[0023] The storage unit 34 is a rewritable semiconductor memory such as a random access memory (RAM), a flash memory, or a non-volatile static random access memory (NVSRAM). The storage unit 34 stores various programs executed by the wearable device 30. Furthermore, the storage unit 34 stores various information used in the execution of the programs.

[0024] The storage unit 34 stores, for example, position data 341 of the wearable device 30 and vital data 342 measured by the sensor 32. The vital data 342 is time-series vital data, and is stored in association with information about the user's work.

[0025] The control unit 35 controls the entire wearable device 30. The control unit 35 is, for example, an electronic circuit such as a central processing unit (CPU) or a micro processing unit (MPU), or an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The control unit 35 also has an internal memory for storing programs that define various processing procedures and control data, and executes each process using the internal memory. The control unit 35 also functions as various processing units by the operation of various programs.

[0026] The control unit 35 includes a position detection unit 351, a menu display control unit 352 (display control unit), and a vital data acquisition unit 353 (acquisition unit).

[0027] The position detection unit 351 detects the position of the user. The position detection unit 351 detects the position of the user by detecting the position of the wearable device 30. For example, the position detection unit 351 detects the position of the wearable device 30 using a GPS (Global Positioning System) function. The position detection unit 351 may also detect the position of the wearable device 30 based on the communication status with other devices, access points, etc., via various wireless communication functions such as Bluetooth (registered trademark). The user's position data detected by the position detection unit 351 is transmitted to the server device 10.

[0028] The menu display control unit 352 displays a task menu showing a list of task candidates for the user on the screen of the wearable device 30 in accordance with the menu display instruction information from the server device 10. The menu display instruction information is control information that instructs the display of one or more task candidates and a task menu that lists the task candidates in a selectable manner. The menu display control unit 352 identifies the task selected by the user's input operation from among the task candidates displayed in the task menu as the task to be performed by the user.

[0029] The vital data acquisition unit 353 controls the process of acquiring time-series vital data of the user by the sensor 32. For example, when the start of acquisition of vital data is instructed by an input operation by the user, the vital data acquisition unit 353 starts the process of acquiring vital data of the user by the sensor 32. For example, when the end of acquisition of vital data is instructed by an input operation by the user, the vital data acquisition unit 353 ends the process of acquiring vital data of the user by the sensor 32.

[0030] Vital data acquisition unit 353 acquires information about the task specified by menu display control unit 352 and vital data of the user in association with each other, and stores the information in memory unit 34 as vital data 342. Vital data 342 stored in memory unit 34 is transmitted to server device 10 via an application for acquiring vital data in communication terminal 20.

[0031] [Server device] Next, a description will be given of the server device 10. Fig. 3 is a diagram for explaining the configuration of the server device 10 shown in Fig. 1.

[0032] As shown in FIG. 3, the server device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0033] The communication unit 11 is a communication interface for transmitting and receiving various information to and from other devices connected via a network, etc. The communication unit 11 is realized by a NIC (Network Interface Card) or the like, and performs communication between other devices and a control unit 13 (described later) via electric communication lines such as a LAN (Local Area Network) or the Internet.

[0034] The memory unit 12 is realized by semiconductor memory elements such as RAM (Random Access Memory) and flash memory, and stores processing programs that operate the server device 10, data used during execution of the processing programs, and the like.

[0035] The memory unit 12 stores user data 121 including each user's identification information, attribute information, attendance information, etc., schedule data 122 including each user's work schedule, a schedule data group 123 for each user, a vital data group 124 in which the user's work is associated with vital data transmitted from the wearable device 30, stress estimation data 125 for each user estimated by a stress estimation unit 135 (described later), and environmental data 126 such as weather information that may be referenced in the estimation process in the stress estimation unit 135.

[0036] Fig. 4 is a diagram showing an example of the data configuration of the process chart data 122 shown in Fig. 3. As shown in Fig. 4, the process chart data 122 has items such as process, person in charge, work time, and identification information of the device on which the work is to be performed. For example, it is determined that process "A1" is to be performed by person in charge "U1" operating device "E1" between "10:00-12:00".

[0037] Fig. 5 is a diagram showing an example of the data configuration of the schedule data group 123 shown in Fig. 3. As shown in Fig. 5, the schedule data group 123 is created for each user, and has items such as plan, time, place, and remarks. For example, for the user corresponding to the schedule data in Fig. 5, a "conference" is scheduled in "conference room 2" from "10:00-12:00". The schedule data group 123 is obtained, for example, from schedules registered in terminal devices used by each user for business, reservation data of a conference room reservation system, etc.

[0038] The control unit 13 controls the entire server device 10. The control unit 13 is, for example, an electronic circuit such as a CPU (Central Processing Unit) or an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 13 also has an internal memory for storing programs that define various processing procedures and control data, and executes each process using the internal memory. The control unit 13 also functions as various processing units by running various programs.

[0039] The control unit 13 has a position data acquisition unit 131, an activity estimation unit 132 (first estimation unit), a display activity setting unit 133 (display control unit), a vital data acquisition unit 134 (acquisition unit), a stress estimation unit 135 (second estimation unit) having an estimation model 1351, and a stress data output control unit 136.

[0040] The position data acquisition unit 131 acquires position data of the user. For example, the position data acquisition unit 131 acquires the position of the wearable device 30 detected by the wearable device 30 carried by the user as the user's position.

[0041] Furthermore, the position data acquisition unit 131 may detect the position of the user based on images captured by imaging devices provided at various locations, the operating status of the device that is the target of the work, or records of entering and leaving a building or room.

[0042] For example, the position data acquisition unit 131 analyzes images captured by imaging devices installed at various locations, and determines when and where the user was imaged by the imaging device, thereby acquiring the user's position data in association with time.

[0043] In addition, for a device that registers user information for starting and ending operation of the device, the location data acquisition unit 131 uses the user information and registration period registered in the device to detect that a registered user is located near the device during the registration period.

[0044] In addition, the location data acquisition unit 131 acquires the user's location data as a building or room entry / exit record, for example, from a system that registers entry / exit by holding an employee ID card over a reader, using a record from a system that unlocks a building or room. In addition, the location data acquisition unit 131 can also acquire the user's location data based on, for example, the usage status of a ticket gate system.

[0045] The task estimation unit 132 estimates task candidates to be performed by the user based on the user's location. The task estimation unit 132 refers to the process chart data 122 or the schedule data group 123 stored in the storage unit 12, and estimates task candidates for the user based on the user's location and the user's task process chart or user's schedule.

[0046] The activity estimation unit 132 estimates the number of activity candidates according to the size of the screen of the wearable device 30. For example, when a list of activity candidates is displayed on the wearable device 30, the activity estimation unit 132 estimates the number of activity candidates to be, for example, four or less.

[0047] The display task setting unit 133 sets the user's task candidates estimated by the task estimation unit 132 as tasks to be displayed in a task selection menu (task menu) of the wearable device 30 used by the user. Then, the display task setting unit 133 creates menu display instruction information for displaying a list of the set tasks, and transmits it to the wearable device 30.

[0048] The vital data acquisition unit 134 acquires vital data of the user from the wearable device 30 via the communication terminal 20. At this time, the vital data acquisition unit 134 acquires information on the work performed by the user in association with the vital data of the user. The work performed by the user is, for example, a work selected by the user's input operation from among work candidates displayed in a work menu of the wearable device 30, and identified as the work to be performed by the user.

[0049] The stress estimation unit 135 estimates the user's stress based on the user's vital data. Then, the stress estimation unit 135 associates the stress estimation result with an operation selected by the user's input operation, and stores the result as stress estimation data 125 in the storage unit 12. The stress estimation unit 135 estimates the user's stress using, for example, an estimation model 1351 that is a machine learning model configured by a neural network or the like. The stress estimation unit 135 estimates the user's stress using an existing method of estimating the user's stress using the user's vital data.

[0050] When the stress data output control unit 136 is requested by another device to output stress estimation data, it transmits and outputs the stress estimation data of the requested user. At this time, the stress data output control unit 136 transmits the stress estimation result in association with the corresponding work information as the stress estimation data. In other words, the work that the user was actually performing when this stress was being exerted is also transmitted to the requesting device, so that the user of the requesting device can recognize the degree of stress that the user was exerting during which work.

[0051] [Work Estimation Example] Next, a description will be given of an example of task estimation by the task estimator 132 and a task menu displayed on the screen of the wearable device 30. Figs. 6 to 8 are diagrams showing an example of a task menu displayed on the screen of the wearable device 30.

[0052] For example, a case will be described where the location of user U1 is area C1 of factory C. In this case, the task estimation unit 132 estimates three tasks as candidate tasks to be performed by user U1: "step A1" of operating device E1 located in area C1, "inspection" of the device located in area C1, and "data input" into the device located in area C1.

[0053] Then, the display work setting unit 133 displays a work menu M1 indicating three works, "1. Process A1," "2. Inspection," and "3. Data entry," on the screen of the wearable device 30 used by the user, as shown in FIG. 6.

[0054] User U1 selects a task that user U1 will perform from among the tasks displayed in task menu M1, and selects the start button when the task begins. This causes wearable device 30 to start acquiring vital data. Then, user U1 selects the end button in task menu M1 when the task is completed. This causes wearable device 30 to end acquiring vital data. The vital data acquired during this time is transmitted to server device 10 in a state associated with information about the task selected by user U1.

[0055] Furthermore, the work estimation unit 132 further refers to the process chart data 122 and collates the contents of the process chart data 122 with the location of the user U1. In this case, the first line of the process chart data 122 describes the process "A1" as the process for which the user U1 is responsible, the work time, and the device "E1" located in the area C1 that is the target of the work. Therefore, the work estimation unit 132 estimates the work of operating the device E1 located in the area C1 to perform "process A1" as a candidate work to be performed by the user U1. The display work setting unit 133 displays a work menu showing "process A1" on the screen of the wearable device 30 used by the user.

[0056] Furthermore, for example, when the user U3 is located in the second conference room, the task estimation unit 132 estimates three tasks, "meeting," "creating materials," and "answering phone calls," as candidate tasks that the user U3 will perform after 10:00 a.m. Then, the display task setting unit 133 displays a task menu M2 indicating the three tasks, "1. Meeting," "2. Creating materials," and "3. Answering phone calls," on the screen of the wearable device 30 used by the user, as shown in FIG.

[0057] Furthermore, when the task estimation unit 132 refers to the schedule data group 123 of user U3, it compares the schedule data group 123 with the location of user U3. In this case, the user's schedule states that a "meeting" is scheduled after 10:00. Therefore, the task estimation unit 132 further estimates the content of the "meeting" and estimates three tasks of user U3, namely, "checking presentation materials," "practicing presentation," and "checking proposal." Each of these tasks is estimated based on the schedule of user U3 to date, business records, etc.

[0058] For example, when the user's location is in a tomato field, the task estimation unit 132 estimates that the candidate task to be performed by the user is one of the farm tasks in the tomato field. For example, the task estimation unit 132 estimates four tasks among the farm tasks in the tomato field: "planting seedlings," "spreading fertilizer," "weeding," and "harvesting." Each of these tasks is estimated based on the date and time when the user's location is detected, purchase records of seedlings, etc., the growth status of the agricultural crops, shipment records of tomatoes by the user, etc. Each of these tasks may also be estimated by analyzing a captured image capturing the current state of the user.

[0059] Then, the display work setting unit 133 displays a work menu M3 indicating four tasks, "1. Planting seedlings," "2. Spreading fertilizer," "3. Weeding," and "4. Harvesting," on the screen of the wearable device 30 used by the user, as shown in FIG. 8.

[0060] Furthermore, the work estimation unit 132 may, for example, refer to the usage status of the ticket gate system, and when the user passes through the ticket gate of a certain station, compare the railway line map data with the movement history based on the GPS function or the like, and estimate that the user is "traveling by train". At this time, the work estimation unit 132 may refer to the congestion status published by each railway company, and associate the congestion degree of the railway used by the user with the work of the user who is "traveling by train". Furthermore, when the user is at home, the work estimation unit 132 may refer to the user's scheduler or the like, and estimate the housework work the user is performing at home.

[0061] [Communication processing] FIG. 9 is a sequence diagram showing a processing procedure of the communication method according to the embodiment.

[0062] As shown in FIG. 9, the wearable device 30 detects the position of the wearable device 30, thereby detecting the position of the user (step S1), and transmits the detected position to the server device 10 (step S2).

[0063] The server device 10 reads out the process chart data 122 or the schedule data group 123 (step S3). The server device 10 estimates candidate tasks to be performed by the user based on the user's location (step S4). At this time, the server device 10 may estimate candidate tasks to be performed by the user using the process chart data 122 or the schedule data group 123 read out in step S3 in addition to the user's location.

[0064] The server device 10 sets the user's task candidates estimated by the task estimation unit 132 as display tasks to be displayed in a task menu of the wearable device 30 used by the user (step S5). Then, the server device 10 transmits menu display instruction information for displaying a list of the set tasks to the wearable device 30 (step S6).

[0065] In accordance with the menu display instruction information, the wearable device 30 displays on the screen a task menu showing a list of task candidates for the task to be performed by the user (step S7).

[0066] When the user operates the wearable device 30 to select an operation to be performed by the user (step S8) and instructs the user to start the operation (step S9), the wearable device 30 detects vital data of the user by the sensor 32 (step S10).

[0067] When the user instructs the wearable device 30 to end the task (step S11), the wearable device 30 ends the detection of vital data. The wearable device 30 associates the detected vital data with information on the task selected by the user and transmits them to the server device 10 via the communication terminal 20 (steps S12 and S13).

[0068] The server device 10 estimates the user's stress based on the user's vital data transmitted from the wearable device 30 (step S14), and stores the stress estimation result in the memory unit 12 in association with the user's task information (step S15).

[0069] [Effects of the embodiment] In this way, the estimation system 100 according to the embodiment estimates candidate tasks to be performed by the user based on the detected position of the user, and displays the estimated candidate tasks on the screen of the wearable device 30 used by the user. The estimation system 100 identifies a task selected by the user's input operation from among the candidate tasks displayed on the screen of the wearable device 30 as the task to be performed by the user, and acquires information on the identified task in association with the user's vital data. The estimation system 100 then estimates the user's stress based on the user's vital data, and stores the stress estimation result in association with the task selected by the user's input operation in a storage unit.

[0070] Therefore, the estimation system 100 does not require the user to manually input the task to be performed from among many tasks, and the user only needs to select the task displayed in the task menu. Therefore, the estimation system 100 can easily identify the task to be performed by the user. Then, the estimation system 100 can associate the task to be performed by the user with the stress estimation result.

[0071] Therefore, according to the embodiment, the user or the user's instructor, etc. can use the stress estimation result to clearly determine which tasks the user feels most stressed about, and can appropriately apply the stress estimation result when making decisions such as changing the direction of work or instruction.

[0072] [System configuration of the embodiment] The components of each device in the estimation system 100 are conceptual and functional, and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of the functions of each device in the estimation system 100 is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed or integrated in any unit depending on various loads, usage conditions, etc.

[0073] Furthermore, all or any part of the processes performed in each device of the estimation system 100 may be realized by a CPU, a GPU (Graphics Processing Unit), and a program analyzed and executed by the CPU and the GPU. Furthermore, each process performed in each device of the estimation system 100 may be realized as hardware using wired logic.

[0074] Furthermore, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually. Alternatively, all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the process procedures, control procedures, specific names, and information including various data and parameters described above and shown in the drawings can be changed as appropriate unless otherwise specified.

[0075] [program] 10 is a diagram showing an example of a computer in which each device of the estimation system 100 is realized by executing a program. The computer 1000 has, for example, a memory 1010 and a CPU 1020. The computer 1000 also has a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. Each of these units is connected by a bus 1080.

[0076] The memory 1010 includes a ROM 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1090. The disk drive interface 1040 is connected to a disk drive 1100. A removable storage medium such as a magnetic disk or an optical disk is inserted into the disk drive 1100. The serial port interface 1050 is connected to a mouse 1110 and a keyboard 1120, for example. The video adapter 1060 is connected to a display 1130, for example.

[0077] The hard disk drive 1090 stores, for example, an OS (Operating System) 1091, an application program 1092, a program module 1093, and program data 1094. That is, a program that defines each process of each device of the estimation system 100 is implemented as a program module 1093 in which code executable by the computer 1000 is written. The program module 1093 is stored, for example, in the hard disk drive 1090. For example, a program module 1093 for executing the same process as the functional configuration of each device of the estimation system 100 is stored in the hard disk drive 1090. The hard disk drive 1090 may be replaced with an SSD (Solid State Drive).

[0078] Furthermore, setting data used in the processing of the above-described embodiment is stored as program data 1094, for example, in memory 1010 or hard disk drive 1090. Then, CPU 1020 reads out program module 1093 or program data 1094 stored in memory 1010 or hard disk drive 1090 into RAM 1012 as necessary, and executes the program.

[0079] Note that the program module 1093 and the program data 1094 are not limited to being stored in the hard disk drive 1090, but may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1100 or the like. Alternatively, the program module 1093 and the program data 1094 may be stored in another computer connected via a network (such as a local area network (LAN) or wide area network (WAN)). The program module 1093 and the program data 1094 may then be read by the CPU 1020 from the other computer via the network interface 1070.

[0080] Although the embodiment of the invention made by the present inventor has been described above, the present invention is not limited by the description and drawings that form a part of the disclosure of the present invention according to the present embodiment. In other words, other embodiments, examples, operation techniques, etc. made by those skilled in the art based on the present embodiment are all included in the scope of the present invention. [Explanation of symbols]

[0081] 10. Server device 11,31 Communications Department 12,34 Storage part 13,35 Control section 20 Communication terminals 30 Wearable Devices 32 Sensors 33 Input / output section 100 Estimation System 121 User Data 122 Schedule data 123 Schedule Data Group 124 Vital Data Group 125 Stress Estimation Data 126 Environmental Data 131 Location data acquisition unit 132 Work Estimation Department 133 Display operation setting section 134 Vital Data Acquisition Unit 135 Stress Estimation Department 136 Stress data output control section 341 Location Data 342 Vital Data 351 Position detection unit 352 Menu display control unit 353 Vital Data Acquisition Department 1351 Estimation Model

Claims

1. A position detection unit that detects the position of a user; A first estimation unit that estimates a candidate task to be performed by the user based on a position of the user; a display control unit that displays the task candidates estimated by the first estimation unit on a screen of a terminal device used by the user; an acquisition unit that identifies an operation selected by an input operation of the user from among operation candidates displayed on a screen of the terminal device as an operation to be performed by the user, and acquires information on the identified operation and vital data of the user in association with each other; a second estimation unit that estimates a stress of the user based on the vital data of the user, and stores the stress estimation result in a storage unit in association with an operation selected by the user; An estimation system comprising:

2. The storage unit stores a schedule of the user or a schedule of the user, The estimation system according to claim 1 , wherein the first estimation unit estimates candidate tasks for the user based on a location of the user and a task schedule or a schedule of the user.

3. The estimation system comprises: a terminal device used by the user, the terminal device having the display control unit, the acquisition unit, and a transmission unit that transmits information about the work and vital data of the user; a server device including the first estimation unit, a communication unit that receives information about the work and vital data of the user, the first estimation unit, and the storage unit; The estimation system according to claim 1, further comprising:

4. The estimation system according to claim 1, characterized in that the position detection unit detects the user's position based on the communication status between the terminal device and other communication devices, images captured by an imaging device, the operation status of the device that is the target of work, or records of entry and exit from a building or room.

5. The estimation system according to claim 1 , wherein the display control unit displays a list of the task candidates, the number of which corresponds to a size of a screen of the terminal device.

6. An estimation method executed by an estimation system, comprising: a location step of detecting a location of a user; A first estimation step of estimating a candidate task to be performed by the user based on a position of the user; a control step of displaying the task candidates estimated in the first estimation step on a screen of a terminal device used by the user; an acquisition step of identifying an operation selected by an input operation of the user from among the operation candidates displayed on the screen of the terminal device as an operation to be performed by the user, and acquiring information on the identified operation and vital data of the user in association with each other; a second estimation step of estimating the stress of the user based on the vital data of the user, and storing the stress estimation result in a storage unit in association with an operation selected by the user through an input operation; The estimation method according to claim 1, further comprising:

7. a location step of detecting a location of a user; A first estimation step of estimating a candidate task to be performed by the user based on a position of the user; a control step of displaying the task candidates estimated in the first estimation step on a screen of a terminal device used by the user; an acquisition step of identifying an operation selected by an input operation of the user from among operation candidates displayed on a screen of the terminal device as an operation to be performed by the user, and acquiring information on the identified operation and vital data of the user in association with each other; a second estimation step of estimating a stress of the user based on the vital data of the user, and storing the stress estimation result and an operation selected by an input operation of the user in a storage unit in association with each other; An estimation program for causing a computer to execute the above.

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