JP7122493B2 - Vital data abstraction device, vital data utilization system, vital data abstraction program, vital data abstraction method, and vital data utilization method - Google Patents

Description

The present disclosure relates to a vital data utilization system that utilizes vital data.

Conventionally, there is a technology that provides a common infrastructure that allows privacy-related vital data to be used by multiple services. In the prior art, confirmation is requested from the user of the service, and the vital data of the user is used when consent to the confirmation is obtained.
(For example, Patent Document 1).

JP 2006-048404 A

In the case of the conventional technology, when using the vital data of the user who uses the service, it is necessary to obtain the consent of the user, and there is a problem that utilization of the vital data is limited.

An object of the present disclosure is to provide a device and system that protects the privacy of vital data and promotes the utilization of vital data.

The vital data abstraction device according to the present disclosure is
a first abstraction unit that acquires the vital data from a vital sensor that detects the vital data, abstracts the vital data, and transmits first abstracted data representing the abstracted vital data to a vital data utilization device; ,
Using the vital data as a response to transmission of the first abstract data, a request signal requesting second abstract data having a lower degree of abstraction than the first abstract data for the vital data detected by the vital sensor. a second abstraction unit that receives from the device and transmits the second abstracted data requested by the request signal to the vital data utilization device;
Prepare.

According to the present disclosure, it is possible to provide a device that protects the privacy of vital data and promotes utilization of vital data.

1 is a diagram of the first embodiment, showing a configuration of a vital data utilization system 100; FIG. FIG. 2 is a diagram of the first embodiment, showing a hardware configuration of a vital data management device 10; FIG. FIG. 2 is a diagram of the first embodiment, showing a hardware configuration of a work risk evaluation device 20; FIG. 4 is a diagram of the first embodiment and is a flow chart for explaining an outline of the operation of the work risk evaluation device 20. FIG. FIG. 10 is a diagram of the first embodiment, and is a flow chart of an overview of the operation of the first abstraction unit 11 of the vital data management device 10; FIG. 10 is a diagram of the first embodiment and is a flow chart of an outline of the operation of the second abstraction unit 12 of the vital data management device 10; The operation sequence of the vital data utilization system 100 in the diagram of the first embodiment. Fig. 10 is a diagram of the first embodiment, showing reference information 13a registered in a reference vital data DB 13; FIG. 4 is a diagram of the first embodiment and shows the relationship between a graph 51, vital data 41a, and first abstracted data 11a; Fig. 4 is a diagram of the first embodiment, showing work content information 24a and past case information 25a; Fig. 10 is a diagram of the first embodiment, showing past case vital data information 26a; FIG. 2 is a diagram of the first embodiment, showing a configuration in which functions of the vital data management device 10 are realized by hardware;

Embodiments will be described below with reference to the drawings. In each figure, the same reference numerals are given to the same or corresponding parts. In the description of the embodiments, the description of the same or corresponding parts will be omitted or simplified as appropriate.

Embodiment 1.
A vital data management device 10 according to the first embodiment will be described with reference to FIGS. 1 to 12. FIG.

*** Configuration description ***
FIG. 1 shows the configuration of a vital data utilization system 100. As shown in FIG. A vital data utilization system 100 includes a vital data management device 10 and a work risk evaluation device 20 . The vital data management device 10 is an implementation example of the vital data abstraction device 910 . Also, the work risk evaluation device 20 is an implementation example of the vital data utilization device 920 . FIG. 1 shows functional configurations of the vital data management device 10 and the work risk evaluation device 20 . The vital data management device 10 includes a first abstraction unit 11, a second abstraction unit 12, a reference vital data DB 13, and a consent data DB 14. The first abstraction unit 11 acquires vital data 41 a from the wearable sensor 41 worn by the worker 40 . Functions of the vital data management device 10 will be described later in the description of the operation. The work risk evaluation device 20 includes a first evaluation unit 21, a second evaluation unit 22, a trigger acquisition unit 23, a work content DB 24, a past case DB 25, and a past case vital data DB 26. The database is written as DB. Functions of the work risk evaluation device 20 will be described later in the description of the operation.

FIG. 2 shows the hardware configuration of the vital data management device 10. As shown in FIG. The hardware configuration of the vital data management device 10 will be described with reference to FIG.

The vital data management device 10 is a computer. The vital data management device 10 has a processor 110 . The vital data management device 10 includes other hardware such as a main memory device 120 , an auxiliary memory device 130 , an input IF 140 , an output IF 150 and a communication IF 160 in addition to the processor 110 . Processor 110 is connected to other hardware via signal line 170 and controls the other hardware.

The vital data management device 10 includes a first abstraction unit 11 and a second abstraction unit 12 as functional elements. Functions of the first abstraction unit 11 and the second abstraction unit 12 are implemented by the vital data abstraction program 101 .

Processor 110 is a device that executes vital data abstraction program 101 . The vital data abstraction program 101 is a program that implements the functions of the first abstraction unit 11 and the second abstraction unit 12 . The processor 110 is an IC (Integrated Circuit) that performs arithmetic processing. Specific examples of the processor 110 are a CPU (Central Processing Unit), a DSP (Digital Signal Processor), and a GPU (Graphics Processing Unit).

The main memory device 120 is a storage device. Specific examples of the main memory device 120 are SRAM (Static Random Access Memory) and DRAM (Dynamic Random Access Memory). The main memory device 120 holds the computation results of the processor 110 .

The auxiliary storage device 130 is a storage device that stores data in a non-volatile manner. A specific example of the auxiliary storage device 130 is an HDD (Hard Disk Drive). The auxiliary storage device 130 is a portable recording medium such as an SD (registered trademark) (Secure Digital) memory card, a NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, and a DVD (Digital Versatile Disk). There may be.
The auxiliary storage device 130 stores the vital data abstraction program 101, the reference vital data DB 13, and the consent data DB 14. The reference vital data DB 13 and consent data DB 14 are programs.

The input IF 140 is a port through which data is input from each device. The output IF 150 is a port to which various devices are connected and data is output from the processor 110 to the various devices. A warning device 30 is connected to the output IF 150 . Communication IF 160 is a communication port for the processor to communicate with other devices.

The processor 110 loads the vital data abstraction program 101 from the auxiliary storage device 130 to the main storage device 120, reads the vital data abstraction program 101 from the main storage device 120, and executes it. The vital data management device 10 may include multiple processors that substitute for the processor 110 . These multiple processors share execution of the vital data abstraction program 101 . Each processor, like the processor 110, is a device that executes the vital data abstraction program 101. FIG.

The vital data abstraction program 101 converts each process, each procedure, or each process by replacing the "part" of the first abstraction unit 11 and the second abstraction unit 12 with "processing," "procedure," or "step." It is a program to be executed by

The vital data abstraction program 101 may be stored in a computer-readable recording medium and provided, or may be provided as a program product.

FIG. 3 shows the hardware configuration of the work risk evaluation device 20. As shown in FIG. The hardware configuration of the work risk evaluation device 20 will be described with reference to FIG.

The work risk evaluation device 20 is a computer similar to the vital data management device 10 . The hardware of the work risk evaluation device 20 is the same as that of the vital data management device 10 . A is added to the code of the hardware of the work risk evaluation device 20 like 110A. Regarding the work risk evaluation device 20, the differences from the vital data management device 10 will be explained.

The vital data management device 10 includes a first evaluation section 21, a second evaluation section 22, and a trigger acquisition section 23 as functional elements. Functions of the first evaluation unit 21 , the second evaluation unit 22 and the trigger acquisition unit 23 are implemented by the vital data utilization program 201 .

Processor 110A executes vital data utilization program 201 . The vital data utilization program 201 is a program that implements the functions of the first evaluation unit 21 , the second evaluation unit 22 and the trigger acquisition unit 23 .

The auxiliary storage device 130A stores a vital data utilization program 201, a work content DB 24, a past case DB 25, and a past case vital data DB 26. FIG. The work content DB 24, the past case DB 25, and the past case vital data DB 26 are programs.

The vital data utilization program 201 includes each process, each procedure, or each process obtained by replacing the "sections" of the first evaluation unit 21, the second evaluation unit 22, and the trigger acquisition unit 23 with "processing," "procedure," or "step." is a program that causes a computer to execute

The vital data utilization program 201 may be stored in a computer-readable recording medium and provided, or may be provided as a program product.

***Description of operation***
FIG. 4 is a flowchart for explaining an outline of the operation of the work risk evaluation device 20. As shown in FIG. An outline of the operation of the work risk evaluation device 20 will be described with reference to FIG.

<Step S10>
In step S10, the trigger acquisition unit 23 receives an instruction signal for instructing the start of work as a trigger for starting work.

<Step S11>
In step S<b>11 , the first evaluation unit 21 receives the first abstracted data 11 a and the category name from the vital data management device 10 . The first abstract data 11a and category names will be described later.

<Step S12>
In step S12, the first evaluation unit 21 refers to the work content DB 24 and the past case DB 25 to calculate a first risk value indicating the risk represented by the first abstract data 11a.
Details of the work content DB 24 and the past case DB 25 will be described later.

<Step S13>
In step S13, the first evaluation unit 21 compares the first risk value with the first threshold. If the first risk value is less than or equal to the first threshold, the process of the first evaluation unit 21 proceeds to step S18 and ends. When proceeding to step S18, no warning is generated. If the first risk value is greater than the first threshold, the process of the first evaluation unit 21 proceeds to step S14.

<Step S14>
In step S<b>14 , the first evaluation unit 21 transmits the request signal 21 a to the vital data management device 10 . After the first evaluation section 21 has been sent, the process moves to the second evaluation section 22 .

<Step S15>
In step S15, the second evaluation unit 22 determines whether or not the second abstract data 12b has been acquired. If the second abstract data 12b cannot be acquired, the process of the second evaluation unit 22 proceeds to step S19, and the process ends. In step S19, when the second evaluation unit 22 can acquire the second abstracted data 12b for outputting the warning signal 22a to the warning device 30, the processing of the second evaluation unit 22 proceeds to step S16.

<Step S16>
In step S<b>16 , the second evaluation unit 22 performs detailed evaluation of the work risk of the worker 40 .
As a detailed evaluation, the second evaluation unit 22 compares the second abstract data 12b of the worker 40 acquired from the vital data management device 10 with the vital data of past cases registered in the past case vital data DB 26. . The second evaluation unit 22 calculates a second risk value as a result of this comparison, and compares the second risk value with the second threshold.

<Step S17>
In step S17, the second evaluation unit 22 compares the second risk value with the second threshold. If the second risk value is less than or equal to the second threshold, the process of the first evaluation unit 21 proceeds to step S18 and ends. If the second risk value is greater than the second threshold, the process of the second evaluation unit 22 proceeds to step S19.
The above is the outline of the operation of the work risk evaluation device 20 .

FIG. 5 is a flow chart of an outline of the operation of the first abstraction unit 11 of the vital data management device 10. As shown in FIG. An overview of the operation of the first abstraction unit 11 will be described with reference to FIG.

<Step S21>
In step S<b>21 , the first abstraction unit 11 acquires vital data 41 a from the wearable sensor 41 . The wearable sensor 41, which is the vital sensor 941, is worn by the worker 40 during work.

<Step S22>
In step S22, the first abstraction unit 11 attempts to extract vital data similar to the vital data 41a from each category registered in the reference vital data DB 13. FIG.

<Step S23>
In step S23, the first abstraction unit 11 determines whether the reference vital data DB 13 has a category associated with vital data similar to the vital data 41a. If there is no category associated with vital data similar to the vital data 41a, the process of the first abstraction unit 11 proceeds to step S24, and the process ends. If there is a category associated with vital data similar to the vital data 41a, the process of the first abstraction unit 11 proceeds to step S25.

<Step S24>
In step S24, the first abstraction unit 11 determines that the worker 40 of the vital data 41a is in the normal state.

<Step S25>
In step S25, the first abstraction unit 11 extracts from the reference vital data DB 13 the category name of the category associated with vital data similar to the vital data 41a. Also, the first abstraction unit 11 abstracts the vital data 41a to generate the first abstracted data 11a. Details of step S25 will be described in the sequence of FIG.

<Step S26>
In step S<b>26 , the first abstraction unit 11 transmits the category name and the first abstraction data 11 a to the work risk evaluation device 20 . The outline of the operation of the first abstraction unit 11 has been described above.

FIG. 6 is a flow chart of an outline of the operation of the second abstraction unit 12 of the vital data management device 10. As shown in FIG. An outline of the operation of the second abstraction unit 12 will be described with reference to FIG.

<Step S31>
In step S<b>31 , the second abstraction unit 12 receives a request signal 21 a requesting the second abstracted data 12 b from the work risk evaluation device 20 .

<Step S32>
In step S32, the second abstraction unit 12 checks the consent data DB 14 to confirm whether or not the worker 40 has consented. If there is no consent from the worker 40, the process of the second abstraction unit 12 proceeds to step S36, and the process ends. If the worker 40 agrees, the process of the second abstraction unit 12 proceeds to step S34.

<Step S34>
In step S34, the second abstraction unit 12 generates the second abstracted data 12b from the vital data 41a.

<Step S35>
In step S<b>35 , the second abstraction unit 12 transmits the second abstracted data 12 b to the work risk evaluation device 20 . The above is the outline of the operation of the second abstraction unit 12 .

FIG. 7 is an operation sequence of the vital data utilization system 100. As shown in FIG. The operation of vital data utilization system 100 will be described in detail with reference to FIG. In the following description of the operation, the operating procedure of the vital data management device 10, which is an implementation example of the vital data abstraction device 910, corresponds to the vital data abstraction method. A program that realizes the operation of the vital data management device 10 as an implementation example of the vital data abstraction device 910 corresponds to the vital data abstraction program 101 . The operation procedure of the work risk evaluation device 20, which is an example of implementation of the vital data utilization device 920, corresponds to the vital data utilization method. A program that realizes the operation of the work risk evaluation device 20, which is an implementation example of the vital data utilization device 920, corresponds to a vital data utilization program.

<Step S101>
In step S<b>101 , the first abstraction unit 11 of the vital data management device 10 acquires the vital data 41 a from the wearable sensor 41 worn by the worker 40 . Step S101 is the same as step S21.

<Step S102>
In step S22, the first abstraction unit 11 abstracts the vital data 41a. Step S102 corresponds to steps S22, S23, S25, and S26. The first abstraction unit 11 acquires the vital data 41a from the vital sensor 941 that detects the vital data 41a, abstracts the vital data 41a, and transmits first abstracted data 11a representing the abstracted vital data 41a. A specific description will be given below.

The first abstraction unit 11 attempts to extract vital data similar to the vital data 41 a from among the categories registered in the reference vital data DB 13 .
FIG. 8 shows reference information 13a registered in the reference vital data DB 13. As shown in FIG. As shown in FIG. 8, the reference information 13a has each category. Vital data, which is raw data, is associated with each category. The raw data is vital data detected by the wearable sensor 41 and not abstracted. In FIG. 8, the category “sleepiness” is associated with the vital data indicated by the graph 51, and the category “poor physical condition” is associated with the vital data indicated by the graph 52. In FIG. Graphs 51 and 52 have time on the horizontal axis and vital values such as pulsation on the vertical axis. In the graph 51, the vital value slightly oscillates around the level LV1. In graph 52, the vital value fluctuates greatly around level LV2.

The first abstraction unit 11 determines whether the reference information 13a has a category associated with vital data similar to the vital data 41a. In this example, the vital data 41 a acquired from the wearable sensor 41 is assumed to be similar to the graph 51 . That is, the first abstraction unit 11
A category associated with vital data similar to the vital data 41a is determined to be "sleepy". In this case, the first abstraction unit 11 extracts "sleepiness" as the category name from the reference information 13a.

Also, the first abstraction unit 11 generates the first abstraction data 11a as follows.
FIG. 9 shows the relationship between the graph 51, the vital data 41a, and the first abstract data 11a. In the graph of the first abstract data 11a, the horizontal axis represents time and the vertical axis represents vital values. FIG. 9 shows that the first abstraction unit 11 has generated the first abstracted data 11a from the graph 51 and the vital data 41a, which is raw data. The first abstraction unit 11 generates first abstracted data 11a as follows. The first abstraction unit 11 compares the graph 51 with the graph of the first abstracted data 11a. In the graph of the first abstract data 11a, the first abstraction unit 11 converts the vital values equal to or higher than LV1 to LV1, and converts the values lower than LV1 to zero. Through this conversion, the first abstraction unit 11 abstracts the vital data 41a into a step function shown in FIG.

The first abstraction unit 11 transmits the category name “sleepiness” and the first abstraction data 11 a in the form of a step function to the work risk evaluation device 20 .

<Step S103>
In step S<b>103 , the first evaluation unit 21 receives the category name “sleepiness” and the first abstract data 11 a from the vital data management device 10 . Step S103 corresponds to steps S11, S12, S13 and S14. The first evaluation unit 21 receives the first abstract data 11a, and based on the first abstract data 11a and first comparison data, which is vital data that can be compared with the first abstract data 11a, performs Evaluate whether the abstract data 11a represents a risk. This evaluation corresponds to the calculation of the first risk value. Also, the first comparison data is, for example, first abstract data XX in a corresponding record described later. The first abstract data XX, which is the first comparison data, is abstracted from vital data detected by a vital sensor worn by a worker different from the worker 40 wearing the vital sensor 941 . When the first evaluation unit 21 evaluates that the first abstract data 11a represents a risk, that is, determines that the first risk value is greater than the first threshold, A request signal 21a requesting the second abstracted data 12b of a lower degree for the vital data 41a detected by the vital sensor 941 is transmitted to the vital data management device 10, which is an implementation example of the vital data abstraction device 910. FIG.

A method of calculating the first risk value is described below.
The first evaluation unit 21 has a work content DB 24 in which the work content of the worker 40 wearing the vital sensor 941 is registered, and the work content of each of the plurality of workers corresponds to the first comparison data. Using the attached past case DB 25, it is evaluated whether or not the first abstract data 11a represents a risk. Evaluating the risk representation means calculating a first risk value and determining the magnitude of the first risk value and the first threshold. The same applies to detailed evaluation by the second evaluation unit 22, which will be described later.
FIG. 10 shows work content information 24 a registered in the work content DB 24 and past case information 25 a registered in the past case DB 25 .

<Work content information 24a>
The work content information 24a is one record including work targets and work procedures as items. In the example of FIG. 10, [work object, work procedure]=[work on elevator car, (A1, B, 1, C1)] and [work object, work procedure]=[work inside hoistway, (A2 , B2, C2)]. The first evaluation unit 21 knows which record of the work content information 24a the worker 40 is working on. In this example, the first evaluation unit 21 knows that the worker 40 is working on the first record shown in FIG.

<Past example information 25a>
The past case information 25a is a record in which the record items of the work content information 24a are further associated with the status and category items of the worker who performed the work of the record. The content of the "worker's state" is the first abstraction data. Although the work targets and procedures in FIG. 10 are the same as those in the first record, they may differ. In FIG. 10, "first abstract data XX (graph)" is written in the "worker state" cell. This indicates that the graph of the first abstract data like the step function shown in FIG. 9 is actually associated.

The work content DB 24 is information specifying the work content of the worker 40 who is working, and the past case DB 25 is information which specifies past cases corresponding to the work content of the worker 40 who is working.

<Extract corresponding records>
Extraction of corresponding records is explained below. Since the first evaluation unit 21 knows that the work content of the worker 40 who is working corresponds to the first record, the first evaluation unit 21 uses the information of the first record from the past case information 25a as a search key to search the past case information 25a. , and extracts records identical or similar to [work target, work procedure] of the first record from the past case information 25a as corresponding records. For example, points are given to work targets and work procedures in the work content information 24a and the past case information 25a. The first evaluation unit 21 can extract corresponding records from the past case information 25a based on the scores.

<Calculation of first risk value>
The first risk value is a value calculated by the first evaluation unit 21 based on the first abstract data 11a.
The calculation of the first risk value is as follows. The first evaluation unit 21 recognizes (1) the first record, (2) the first abstract data 11a received from the vital data management device 10 and the category name=“sleepiness” as current information. . These pieces of information (1) and (2) are called current information. The first evaluation unit 21 recognizes corresponding records. Corresponding records are past cases. The corresponding record in FIG. 10 is called past information. The first evaluation unit 21 calculates the degree of similarity between current information and past information as follows. First, the first evaluation unit 21 calculates the degree of similarity between [work target, work procedure] of the first record and [work target, work procedure] of the corresponding record. The first evaluation unit 21 can calculate the degree of similarity based on the scores described above. Next, the first evaluation unit 21 compares the “first abstracted data 11a and category name=“sleepiness”” received from the vital data management device 10 and the corresponding record ““first abstracted data XX” and category = Calculate the degree of similarity with "drowsy". For example, points are assigned to categories. The first evaluation unit 21 calculates the similarity of categories based on the scores. As for the similarity of the first abstract data, which is graph information, the first evaluation unit 21 calculates the similarity by pattern matching, for example. The first evaluation unit 21 calculates a first risk value from each calculated similarity. The higher the degree of similarity, the more dangerous the current state of worker 40 is. When the first evaluation unit 21 evaluates that the first abstract data 11a represents a risk, the first evaluation unit 21 determines a risk level, and applies the determined risk level to the vital data management device 10, which is an implementation example of the vital data abstraction device 910. Send to A first evaluator 21 calculates a risk level from the first risk value. The risk level indicates the work risk of the worker 40 . The higher the risk level value, the higher the work risk of the worker 40 . In addition, the 1st evaluation part 21 may use the 1st risk value itself as a risk level.

The first evaluation unit 21 compares the first risk value with the already set first threshold. When the first risk value is greater than the first threshold, the first evaluation unit 21 transmits a request signal 21a to the vital data management device 10. FIG. The request signal 21a contains the risk level. The above is the processing of step S103.

<Step S104>
In step S104, the second abstraction unit 12 receives the request signal 21a. Step S104 corresponds to steps S31, S32, S33, S34 and S35. Upon receiving the request signal 21 a , the second abstraction unit 12 transmits the second abstracted data 12 b to the work risk evaluation device 20 that is an implementation example of the vital data utilization device 920 . A specific description will be given below.

<Step S32>
The second abstraction unit 12 confirms whether or not there is consent from the worker 40 by confirming the consent data DB 14 . The second abstraction unit 12 recognizes who the worker 40 is. The consent of the worker 40 is the consent of the worker 40 that the raw vital data 41a of the worker 40 detected by the wearable sensor 41 may be provided to a third party. If there is consent, the second abstraction unit 12 determines the degree of abstraction of the second abstraction data 12b according to the risk level when receiving the risk level. The second abstraction unit 12 abstracts the vital data 41a according to the determined degree of abstraction to generate the second abstracted data 12b. Generation of the second abstract data 12b is as follows. The second abstraction unit 12 has a switch 12a as shown in FIG. The selector switch 12a has terminals T0 to T3. The second abstraction unit 12 determines the degree of abstraction according to the risk level. In this example, the second evaluation unit 22 determines that “risk level=abstraction degree”. One of the connection between the terminal T0 and the terminal T1, the connection between the terminal T0 and the terminal T2, and the connection between the terminal T0 and the terminal T3 is executed. Here, it is assumed that the risk level received by the second abstraction unit 12 is one of three levels of low, medium, and high. Therefore, there are three levels of abstraction: low, medium, and high. Low, medium, and high risk levels correspond to high, medium, and low levels of abstraction. Here terminal T1 corresponds to the high of abstraction, terminal T2 to the middle of abstraction, and terminal T3 to the low of abstraction. When the received risk level is low, the second abstraction unit 12 connects terminal T0 with terminal T1. In this case, the generated second abstract data 12b has the highest degree of abstraction. However, the second abstracted data 12b has a lower degree of abstraction than the first abstracted data 11a. When the received risk level is medium, the second abstraction unit 12 connects the terminal T0 with the terminal T2. In this case, the degree of abstraction of the generated second abstract data 12b is lower than that of the terminal T1. When the received risk level is high, the second abstraction unit 12 connects terminal T0 with terminal T3. In this case, the second abstraction unit 12 transmits raw data, which is the non-abstracted vital data 41a detected by the vital sensor 941, to the work risk assessment device 20 as the second abstracted data 12b.

The second abstraction unit 12 transmits the generated second abstracted data 12 b to the work risk evaluation device 20 .

<Step S105>
In step S105, the second evaluation unit 22 receives the second abstracted data 12b. Step S105 corresponds to steps S15, S16, S17, and S19. When the second evaluation unit 22 receives the second abstracted data 12b, the second abstracted data 12b and the second abstracted data 12b It evaluates whether the second abstract data 12b represents a risk based on the second comparison data, which is comparable vital data, and outputs the evaluation result. This evaluation corresponds to the calculation of the second risk value. Output of the evaluation result corresponds to output of a warning signal 22a, which will be described later. Also, the second comparison data is, for example, the second abstract data VV in the corresponding record of the past case vital data information 26a to be described later.

When the second abstract data 12b can be acquired, the second evaluation unit 22 performs detailed evaluation of the work risk of the worker 40. FIG. As a detailed evaluation, the second evaluation unit 22 compares the received second abstract data 12b with past case vital data information registered in the past case vital data DB 26 . The past case vital data information 26a registered in the past case vital data DB 26 is the same as the past case information 25a of FIG.
FIG. 11 shows the past case vital data information 26a. In contrast to the past case information 25a, the past case vital data information 26a has the second abstract data VV and the second abstract data WW as the "state of the worker". This difference is enclosed in a dashed box. The second abstract data of the past case vital data information 26a has a data format that can be compared with the second abstract data 12b. For example, if the second abstract data 12b is raw data, the second abstract data of the past case vital data information 26a is raw data. The second evaluation unit 22 calculates the second risk value in the same manner as when calculating the first risk value. In the calculation of the second risk value, the past case information 25a at the time of the first risk value is replaced with the past case vital data information 26a. As shown in FIG. 11, the second evaluation unit 22 extracts the record of "elevator car work" as a corresponding record, and calculates the second risk.

The second evaluation unit 22 compares the calculated second risk value with the second threshold. If the second risk value is greater than the second threshold, the second evaluation unit 22 outputs a warning signal 22 a to the warning device 30 .

<Step S106>
In step S106, the warning device 30 issues a warning according to the warning signal 22a. The warning device 30 is, for example, a display device, and displays a warning on the screen.

*** Effect of Embodiment 1 ***
According to the vital data utilization system 100 of Embodiment 1, it is possible to provide a device that protects the privacy of vital data and promotes utilization of the vital data.
In addition, in the vital data utilization system 100 , the vital data management device 10 includes a first abstraction section 11 and a second abstraction section 12 . The work risk evaluation device 20 also includes a first evaluation section 21 and a second evaluation section 22 . Therefore, according to the vital data utilization system 100, it is possible to suppress the expansion of utilization of vital data from the viewpoint of privacy, and to issue an appropriate warning to the operator.

<Supplementary hardware configuration>
In the vital data management device 10 of FIG. 10, the functions of the vital data management device 10 are implemented by software, but the functions of the vital data management device 10 may be implemented by hardware. FIG. 12 shows a configuration in which the functions of the vital data management device 10 are realized by hardware. The electronic circuit 90 in FIG. 12 is a dedicated electronic circuit that implements the functions of the first abstraction section 11 and the second abstraction section 12 of the vital data management device 10 . Electronic circuit 90 is connected to signal line 91 . Electronic circuit 90 is specifically a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, GA, ASIC, or FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array. The functions of the constituent elements of the vital data management device 10 may be implemented by one electronic circuit, or may be implemented by being distributed among a plurality of electronic circuits. Also, some functions of the components of the vital data management device 10 may be implemented by electronic circuits, and the remaining functions may be implemented by software.

Each of processor 110 and electronic circuitry 90 is also referred to as processing circuitry. In the vital data management device 10, the functions of the first abstraction unit 11, the second abstraction unit 12, the reference vital data DB 13, and the consent data DB 14 may be realized by processing circuitry.

In the work risk evaluation device 20 of FIG. 3, the functions of the work risk evaluation device 20 are realized by software. The functions of the work risk evaluation device 20 may be realized by the electronic circuit of FIG. 12, like the vital data management device 10. FIG. Since the work risk evaluation device 20 is the same as the vital data management device 10, the description thereof is omitted.

Note that the wearable sensor 41 and the vital data management device 10 shown in FIG. 1 may be realized as one wearable device.

10 vital data management device 11 first abstraction unit 11a first abstraction data 12 second abstraction unit 12a switch 12b second abstraction data 13 reference vital data DB 13a reference information 14 consent Data DB, 20 work risk evaluation device, 21 first evaluation unit, 21a request signal, 22 second evaluation unit, 22a warning signal, 23 trigger acquisition unit, 24 work content DB, 24a work content information, 25 past case DB, 25a Past case information 26 Past case vital data DB 30 Warning device 40 Worker 41 Wearable sensor 41a Vital data 100 Vital data utilization system 910 Vital data abstraction device 920 Vital data utilization device 941 Vital sensor.

Claims (14)

obtaining the vital data from a vital sensor that detects the vital data, abstracting the vital data, obtaining first abstract data indicating the abstracted vital data, and determining a risk level of the first abstract data a first abstraction unit that transmits to the data utilization device ;
When the risk level of the first abstract data is received from the vital data utilization device, abstraction of second abstract data having a lower degree of abstraction than the first abstract data according to the risk level is performed. a second abstraction unit that determines a degree and transmits second abstracted data generated according to the determined degree to the vital data utilization device;
a vital data abstraction device. The risk level is
The vital data utilization device receives the first abstract data, and based on the first abstract data and first comparison data, which is vital data comparable to the first abstract data, performs the first 2. The vital data abstraction apparatus according to claim 1, wherein the risk level is determined when evaluating whether or not one abstract data represents a risk, and evaluating that the first abstract data represents a risk. The vital sensor is
is worn by the worker,
The first comparison data is
3. The vital data abstracting device according to claim 2 , wherein the vital data is abstracted from vital data detected by a vital sensor worn by a worker different from the worker wearing the vital sensor. The risk level is
The vital data utilization device stores a work content database in which the work content of the worker wearing the vital sensor is registered, and the work content of each worker of a plurality of workers and the first comparison data. 4. The vital data abstraction device according to claim 3 , wherein the vital data abstraction apparatus is a risk level determined when evaluating whether or not the first abstraction data represents a risk using a past case database associated therewith. The second abstraction unit includes:
5. The vital data abstraction device according to any one of claims 1 to 4 , wherein raw data detected by said vital sensor and being non-abstraction vital data is transmitted as said second abstract data . The vital data abstraction device comprises:
5. The vital data abstraction device according to any one of claims 1 to 4 , which is a wearable device. A vital data abstraction apparatus comprising a first abstraction unit that acquires the vital data from a vital sensor that detects the vital data, abstracts the vital data, and transmits first abstract data representing the abstracted vital data. When,
receiving the first abstract data, and determining the risk based on the first abstract data and first comparison data that is vital data that can be compared with the first abstract data; a first evaluation unit that evaluates whether the first abstract data represents a risk, determines a risk level when evaluating that the first abstract data represents a risk, and transmits the determined risk level to the vital data abstraction device. a data utilization device;
with
The vital data abstraction device further comprises:
When the risk level is received, determining the degree of abstraction of second abstraction data having a lower degree of abstraction than the first abstraction data according to the risk level, and generating according to the determined degree and a second abstraction unit that transmits the second abstracted data to the vital data utilization device. The vital sensor is
is worn by the worker,
The first comparison data is
8. The vital data utilization system according to claim 7 , wherein the vital data is abstracted from vital data detected by a vital sensor worn by a worker different from the worker wearing the vital sensor. The first evaluation unit
A work content database in which the work content of the worker wearing the vital sensor is registered, and a past case database in which the work content of each worker of a plurality of workers is associated with the first comparison data. 9. The vital data utilization system according to claim 8 , wherein whether or not said first abstract data represents a risk is evaluated using and. The second abstraction unit includes:
10. The vital data utilization system according to any one of claims 7 to 9 , wherein raw data, which is non-abstracted vital data detected by said vital sensor, is transmitted as said second abstract data. The vital data abstraction device comprises:
10. The vital data utilization system according to any one of claims 7 to 9 , which is a wearable device. to the computer,
obtaining the vital data from a vital sensor that detects the vital data, abstracting the vital data, obtaining first abstract data indicating the abstracted vital data, and determining a risk level of the first abstract data a first abstraction process for transmission to the data utilization device;
When the risk level of the first abstract data is received from the vital data utilization device, abstraction of second abstract data having a lower degree of abstraction than the first abstract data according to the risk level is performed. a second abstraction process of determining a degree and transmitting second abstracted data generated according to the determined degree to the vital data utilization device;
A vital data abstraction program that runs the computer
obtaining the vital data from a vital sensor that detects the vital data, abstracting the vital data, obtaining first abstract data indicating the abstracted vital data, and determining a risk level of the first abstract data Send to the data utilization device,
the computer
When the risk level of the first abstract data is received from the vital data utilization device, abstraction of second abstract data having a lower degree of abstraction than the first abstract data according to the risk level is performed. A vital data abstraction method of determining a degree and transmitting second abstracted data generated according to the determined degree to the vital data utilization device. A vital data abstraction device
acquiring the vital data from a vital sensor that detects the vital data, abstracting the vital data, and transmitting first abstract data representing the abstracted vital data;
The vital data utilization device
receiving the first abstract data, and determining the risk based on the first abstract data and first comparison data that is vital data that can be compared with the first abstract data; determining whether the first abstract data represents a risk, determining a risk level when evaluating that the first abstract data represents a risk, transmitting the determined risk level to the vital data abstraction device;
The vital data abstraction device comprises:
When the risk level is received, determining the degree of abstraction of second abstraction data having a lower degree of abstraction than the first abstraction data according to the risk level, and generating according to the determined degree and transmitting the second abstract data to the vital data utilization device.

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