Estimation system, estimation method, and estimation program

Abstract

An estimation system (100) comprises: a position detection unit for detecting the position of a user; a work estimation unit for estimating candidates for a work performed by the user on the basis of the position of the user; a displayed work setting unit for displaying the work candidates estimated by the work estimation unit on a screen of a wearable device used by the user; a vital data acquisition unit that identifies the work selected by the 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 unit that estimates the user's stress 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 the storage unit in association with each other.

Description

Estimation system, estimation method, and estimation program

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

[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).

[0003] JP 2016-181160 A

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

[0005] However, there is a problem in that the process of the user manually inputting the tasks that the user will perform from among a large number of 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.

[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 the position of a user, 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 the user's input operation from the candidate tasks displayed on the screen of the terminal device as the task to be performed by the user, and acquires information on the identified task in association with the user's vital data, and a second estimation unit that 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 memory unit.

[0008] According to the present invention, it is possible to easily identify the work performed by the user and associate it with the stress estimation result.

[0009] FIG. 1 is a diagram illustrating the configuration of an estimation system according to an embodiment. FIG. 2 is a diagram illustrating the configuration of a wearable device shown in FIG. 1. FIG. 3 is a diagram illustrating the configuration of a server device shown in FIG. 1. FIG. 4 is a diagram illustrating an example of the data configuration of the process chart data shown in FIG. 3. FIG. 5 is a diagram illustrating an example of the data configuration of the schedule data group shown in FIG. 3. FIG. 6 is a diagram illustrating an example of a work menu displayed on the screen of a wearable device. FIG. 7 is a diagram illustrating an example of a work menu displayed on the screen of a wearable device. FIG. 8 is a diagram illustrating an example of a work menu displayed on the screen of a wearable device. FIG. 9 is a sequence diagram illustrating the processing steps of a communication method according to an embodiment. FIG. 10 is a diagram illustrating an example of a computer on which each device of the estimation system is realized by executing a program.

[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 designated by the same reference numerals.

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

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

[0013] As shown in FIG. 1, the estimation system 100 according to the 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 the user. The wearable device 30 is, for example, a wristwatch-type device, but is not limited to this. The wearable device 30 displays a list of candidate tasks estimated by the server device 10 on, for example, a touch panel screen. When a task is selected by the user's input operation, the wearable device 30 measures the user's vital data and transmits the measured time-series vital data to the server device 10 via the communication terminal 20 in association with the task selected by the user's input operation. The vital data includes, for example, heart rate, body temperature, blood flow, and 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 smartphone, and has a communication function, a location detection function (for example, a GPS (Global Positioning System) function), a photo taking function, a text input function, etc. The communication terminal 20 connects to the server device 10 and the wearable device 30 via a vital data acquisition application, associates the time-series vital data measured by the wearable device 30 with an operation selected by a user's input operation, and transmits the associated data to the server device 10.

[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 the screen, or the list may be displayed on an operation panel of the device on which the user is working or on a display near the device.

[0018] [Wearable Device] 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 types of information and receives various types of 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 an operation 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 when various programs are run.

[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 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 candidate tasks for the user on the screen of the wearable device 30 in accordance with 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 candidate tasks and a task menu that displays the candidate tasks in a selectable list. The menu display control unit 352 identifies the task selected by the user's input operation from the candidate tasks 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 user issues an instruction to start acquiring vital data through an input operation, the vital data acquisition unit 353 starts the process of acquiring vital data of the user by the sensor 32. For example, when the user issues an instruction to end acquiring vital data through an input operation, 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 identified by menu display control unit 352 and the user's vital data in association with each other, and stores the information in storage unit 34 as vital data 342. Vital data 342 stored in storage 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 illustrating 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 the other devices and the control unit 13 (described later) via telecommunication 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, and 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 transmitted from the wearable device 30 in which the user's work is associated with vital data; 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 and 12:00."

[0037] 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 includes items such as schedule, time, location, and notes. For example, for the user corresponding to the schedule data in FIG. 5, a "meeting" is scheduled in "conference room 2" from "10:00-12:00." The schedule data group 123 is obtained, for example, from schedules registered in the terminal devices used by each user for business purposes, reservation data from 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 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 operation estimation unit 132 (first estimation unit), a display operation 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] In addition, the location data acquisition unit 131 may detect the user's location based on images captured by imaging devices installed in various locations, the operation status of the device that is the target of work, or records of entry and exit from a building or room.

[0042] For example, the location data acquisition unit 131 analyzes images captured by imaging devices installed at various locations, and determines the location and time of the image capture of the user, thereby acquiring the user's location 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 the registered user is located near the device during the registration period.

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

[0045] The task estimation unit 132 estimates candidate tasks to be performed by the user based on the user's location. The task estimation unit 132 references the process chart data 122 or the schedule data group 123 stored in the storage unit 12, and estimates candidate tasks for the user based on the user's location and the user's task 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 candidate estimated by the task estimation unit 132 as tasks to be displayed on 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 that displays a list of the set tasks, and transmits it to the wearable device 30.

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

[0049] The stress estimation unit 135 estimates the user's stress based on the user's vital data. The stress estimation unit 135 then associates the stress estimation result with the task 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, which is a machine learning model configured using a neural network or the like. The stress estimation unit 135 estimates the user's stress using an existing method for estimating the user's stress using the user's vital data.

[0050] When another device requests the output of stress estimation data, the stress data output control unit 136 transmits and outputs the stress estimation data of the requested user. At this time, the stress data output control unit 136 associates the stress estimation result with information on the corresponding task as stress estimation data and transmits it. In other words, the task that the user was actually performing when the stress was occurring is also transmitted to the requesting device, so the user of the requesting device can recognize the degree of stress that the user was experiencing during each task.

[0051] [Example of Task Estimation] Next, a description will be given of task estimation by the task estimation unit 132 and an example of a task menu displayed on the screen of the wearable device 30. Figures 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 in which user U1 is located in area C1 of factory C. In this case, the work estimation unit 132 estimates three work tasks as candidate work tasks to be performed by user U1: "process 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 showing three tasks, "1. Process A1," "2. Inspection," and "3. Data entry," on the screen of the wearable device 30 used by the user, as shown in Figure 6.

[0054] User U1 selects a task to be performed from the tasks displayed in task menu M1, and selects the start button to start the task. This causes the wearable device 30 to start acquiring vital data. Then, when user U1 has finished the task, user U1 selects the end button in task menu M1. This causes the wearable device 30 to stop acquiring vital data. The vital data acquired during this time is transmitted to server device 10 in association with information about the task selected by user U1.

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

[0056] For example, if 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 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 references the schedule data group 123 for user U3, it compares the schedule data group 123 with the location of user U3. In this case, the user's schedule indicates that a "meeting" is scheduled for after 10:00. Therefore, the task estimation unit 132 further estimates the content of the "meeting" and estimates three tasks for user U3: "checking presentation materials," "practicing the presentation," and "checking the proposal." Each of these tasks is estimated based on user U3's previous schedule, business records, etc.

[0058] For example, when the user's location is 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 crops, and the shipping records of the tomatoes by the user. Each of these tasks may also be estimated by analyzing captured images of the user's current state.

[0059] Then, the display work setting unit 133 displays a work menu M3 showing four works, "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 Figure 8.

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

[0061] [Communication Processing] FIG. 9 is a sequence diagram showing the 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 to thereby detect 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). In this case, 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 candidate tasks of the user estimated by the task estimation unit 132 as display tasks to be displayed in the task menu of the wearable device 30 used by the user (step S5).The server device 10 then 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 the user's vital data using the sensor 32 (step S10).

[0067] When the user operates the wearable device 30 to instruct the user 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 about the task selected by the user and transmits the associated data 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 work information (step S15).

[0069] Effect of the embodiment As described above, the estimation system 100 according to the embodiment estimates candidate tasks to be performed by the user based on the detected user position 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 a large number of tasks. 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. The estimation system 100 can then 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 can use the stress estimation results to clearly determine which tasks the user feels most stressed about, and can appropriately apply the stress estimation results 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 functional components 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 (Central Processing Unit), 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 using a known method. In addition, the processing procedures, control procedures, specific names, and information including various data and parameters described above and illustrated can be changed as appropriate unless otherwise specified.

[0075] 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. These components are connected by a bus 1080.

[0076] The memory 1010 includes a read-only memory (ROM) 1011 and a random access memory (RAM) 1012. The ROM 1011 stores a boot program such as a basic input / output system (BIOS). 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 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 in 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 in the estimation system 100 is stored in the hard disk drive 1090. Note that 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 them.

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

[0080] Although the present invention has been described above as an embodiment, the present invention is not limited to the descriptions and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention.

[0081] 10 Server device 11, 31 Communication unit 12, 34 Storage unit 13, 35 Control unit 20 Communication terminal 30 Wearable device 32 Sensor 33 Input / output unit 100 Estimation system 121 User data 122 Work schedule data 123 Schedule data group 124 Vital data group 125 Stress estimation data 126 Environmental data 131 Position data acquisition unit 132 Work estimation unit 133 Display work setting unit 134 Vital data acquisition unit 135 Stress estimation unit 136 Stress data output control unit 341 Position data 342 Vital data 351 Position detection unit 352 Menu display control unit 353 Vital data acquisition unit 1351 Estimation model

Claims

1. An estimation system comprising: 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.

2. The estimation system described in claim 1, characterized in that the memory unit stores the user's work schedule or the user's schedule, and the first estimation unit estimates candidate tasks for the user based on the user's location and the user's work schedule or the user's schedule.

3. The estimation system according to claim 1, characterized in that it comprises: a terminal device used by the user having the display control unit, the acquisition unit, and a transmission unit for transmitting the work information and the user's vital data; and a server device having the first estimation unit, a communication unit for receiving the work information and the user's vital data, the first estimation unit, and the memory unit.

4. The estimation system described in claim 1, characterized in that the location detection unit detects the user's location 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, characterized in that the display control unit displays a list of the task candidates in a number corresponding to the size of the screen of the terminal device.

6. An estimation method executed by an estimation system, comprising: a location process for detecting a user's location; a first estimation process for estimating candidate tasks to be performed by the user based on the user's location; a control process for displaying the candidate tasks estimated in the first estimation process on a screen of a terminal device used by the user; an acquisition process for identifying 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 acquiring information on the identified task in association with vital data of the user; and a second estimation process for estimating the user's stress based on the user's vital data, and storing the stress estimation result in association with the task selected by the input operation of the user in a memory unit.

7. An estimation program for causing a computer to execute the following steps: a location step for detecting a user's location; a first estimation step for estimating candidate tasks to be performed by the user based on the user's location; a control step for displaying the candidate tasks estimated in the first estimation step on a screen of a terminal device used by the user; an acquisition step for identifying a task selected by an input operation of the user from the candidate tasks displayed on the screen of the terminal device as the task to be performed by the user, and acquiring information on the identified task in association with vital data of the user; and a second estimation step for estimating the user's stress based on the vital data of the user, and storing the stress estimation result in association with the task selected by the input operation of the user in a memory unit.

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