Information processing device, information processing method, and program

Abstract

The purpose of the present invention is to contribute to improving the accuracy of detecting an abnormal situation. The present invention is provided with: a specifying unit that specifies a moving means of a user; and a detection unit that detects, via a sensor provided in the user or in the vicinity of the user, an abnormality of the user on the basis of a determination criterion corresponding to the movement means specified by the specifying unit.

Description

Technical Field

[0001] The present invention relates to an information processing device, an information processing method, and a program. Background Art

[0002] In recent years, automation and labor-saving have been developed in factories, agricultural work sites, etc., making it possible to operate with fewer people. On the other hand, if there are fewer people, even if an abnormal situation such as a worker falls (falls due to tripping or poor physical condition) or falls, it is more likely that other workers will not notice it. In particular, if a worker is injured by a fall and cannot move his body or loses consciousness, he may fall into a serious situation.

[0003] In order to avoid falling into such a serious situation, a technology for detecting abnormal situations such as falls using sensors has been proposed. Patent document 1 discloses a technology for installing an acceleration sensor at a desired position of a person and detecting a fall when the acceleration obtained from the sensor exceeds a preset reference acceleration.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Publication No. 2004-252618 Summary of the invention

[0007] Problems to be solved by the invention

[0008] It is desirable to improve the accuracy of detecting abnormal situations. Therefore, in order to detect abnormal situations without omission, it is considered to increase the sensitivity of the sensor, but if the sensitivity is increased excessively, over-detection will occur. In addition, depending on the user's situation, abnormal situations that are easy to occur and those that are difficult to occur are sometimes different. For example, in the case where the user is working in a flat low position, it is almost impossible for the user to fall. Therefore, when the fall detection is performed under the condition that the user is unlikely to fall, the possibility of false detection increases. In the prior art, under such conditions, there is a limit to the accuracy of detecting abnormal situations.

[0009] The present invention has been made in view of such a problem, and an object of the present invention is to contribute to improvement in the accuracy of abnormality detection.

[0010] Means for solving problems

[0011] In order to achieve the above-mentioned purpose, the information processing device of the present invention has: a determination unit, which determines the user's means of movement; and a detection unit, which detects abnormal conditions of the user through sensors provided to the user or the user's surroundings with a judgment criterion corresponding to the means of movement determined by the determination unit.

[0012] Effects of the Invention

[0013] According to the present invention, it is possible to contribute to improving the accuracy of detecting abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a diagram showing an example of a system configuration of a detection system.

[0015] Figure 2 This is a diagram showing an example of the hardware configuration of a server device.

[0016] Figure 3 This is a diagram showing an example of a reference value table.

[0017] Figure 4 This is a diagram showing an example of a sensitivity table.

[0018] Figure 5 This is a diagram showing an example of the hardware configuration of a terminal device.

[0019] Figure 6 This is a diagram showing an example of the functional structure of a server device.

[0020] Figure 7 This is a flowchart showing an example of the detection process.

[0021] Figure 8 This is a diagram showing an example of a sensitivity table.

[0022] Fig. 9 This is a flowchart showing an example of the detection process.

[0023] Fig.10 This is a diagram showing an example of a sensitivity table.

[0024] Fig.11 This is a flowchart showing an example of the detection process.

[0025] Fig.12 This is a diagram showing an example of a reference value table.

[0026] Fig.13 This is a diagram showing an example of a sensitivity table.

[0027] Fig.14 This is a flowchart showing an example of the detection process. DETAILED DESCRIPTION

[0028] (First Embodiment)

[0029] Figure 1 1 is a diagram showing an example of a system configuration of a detection system 1 according to the present embodiment. The detection system 1 is a system for detecting abnormal conditions of users, and includes a server device 10 and terminal devices 20 respectively provided to one or more users who perform agricultural operations on a farm, operations in a factory, etc. The server device 10 and the terminal device 20 are respectively connected via a network 30.

[0030] The server device 10 is an information processing device such as a server computer or a general-purpose computer that detects abnormal conditions of the user based on signals obtained via various sensors. In the present embodiment, the server device 10 detects a fall, a drop, an impact, lying motionless, fatigue, and a high heart rate as abnormal conditions. A fall means falling down. A drop means falling from a height. An impact means applying an acceleration above a certain value. Lying motionless means not moving in a fallen state. Fatigue means accumulated fatigue. A high heart rate means a heart rate higher than normal.

[0031] The terminal device 20 is an information processing device such as a smartphone or a smart watch that includes a sensor and transmits a signal acquired via the sensor to the server device 10 .

[0032] Figure 2 This is a diagram showing an example of the hardware configuration of the server device 10 .

[0033] The server device 10 includes a processor 101 , a main storage device 102 , an auxiliary storage device 103 , and a communication interface (I / F) 104 .

[0034] The processor 101 is a control device for controlling the server device 10. The main storage device 102 is a storage device such as a RAM (Random Access Memory) used for temporary storage of information, program development, etc. The auxiliary storage device 103 is a storage device for storing Figure 3 The reference value table 301 described later in Figure 4 The communication I / F 104 is an interface for communicating with an external device such as the terminal device 20 via the network 30 .

[0035] use Figure 3 The reference value table 301 will be described.

[0036] The reference value table 301 shows the correspondence between abnormal situations and indicators and reference values ​​used for judging abnormal situations. The reference value is a value indicating what value the corresponding indicator must have to be in order to be judged as an abnormal situation. In this embodiment, the server device 10 detects an abnormal situation when the value of the indicator corresponding to the abnormal situation becomes greater than the reference value.

[0037] The reference value table 301 includes items of “abnormal situation” indicating an abnormal situation, an index for determining a corresponding abnormal situation, “index” indicating a reference value, and “reference value”.

[0038] In this embodiment, the reference value table 301 includes indicators and reference values ​​corresponding to the abnormal conditions of stumbling, falling, impact, lying still, fatigue, and high heart rate.

[0039] In the present embodiment, the index for detecting a fall is the change value of the acceleration applied to the user in the vertical direction and the horizontal direction during a given period (e.g., 1 second, 2 seconds, etc.). In addition, the index for detecting a fall is the change value of the acceleration applied to the user in the vertical direction during a given period. In addition, the index for detecting an impact is the scalar value of the synthetic vector of the acceleration of the three axes that can be detected by the acceleration sensor possessed by the user during a given period. In addition, the index used in the detection of lying still is the period after the user takes a given posture (a posture of falling down, a posture of lying on a table / handle, etc., a posture of hanging on a seat belt, etc.) and the inclination of the terminal device 20 becomes a value within a given range, and the user's movement stops. In the present embodiment, the given range is a range predetermined as a range of inclination that the terminal device 20 can take when the user lies horizontally. However, the range can also be adjusted to an arbitrary range according to a designation from the user, etc. In addition, the index for detecting fatigue is the duration of the operation. In addition, in the present embodiment, a plurality of reference values ​​for fatigue detection are determined based on the value (WBGT value) of the heat index (WBGT: Wet Bulb Globe Temperature). The index for detecting a high heart rate is the user's heart rate. In addition, each index is acquired by the terminal device 20 and sent to the server device 10. This process will be described later.

[0040] use Figure 4 The sensitivity table 401 will be described.

[0041] The sensitivity table 401 indicates the correspondence between the items of the operation performed by the user (hereinafter referred to as the operation items) and the sensitivity of the detection of each abnormal situation. Here, the sensitivity of the detection is a scale indicating the ease of detecting the abnormal situation of the detection object, and the higher it is, the easier it is to detect. In the present embodiment, the sensitivity of the detection takes any one of the multiple values ​​after classification (in the present embodiment, the order from high to low is "standard", "slightly weak", "weak", and "off"). Regarding the level of sensitivity, among "standard", "slightly weak", "weak", and "off", the highest sensitivity is "standard", the second highest is "slightly weak", the third highest is "weak", and the lowest is "off". In addition, the sensitivity "off" means that no detection is performed.

[0042] In the present embodiment, the server device 10 detects an abnormality of a user having a terminal device 20 with a sensitivity corresponding to the operation item of the operation being performed by the user stored in the sensitivity table 401. When the server device 10 detects an abnormality, when the sensitivity of the detection is either "slightly weak" or "weak", the value of the reference value used for judging the abnormality is multiplied by a coefficient corresponding to the sensitivity of the detection to perform correction. If the value of the index used for judging the abnormality is greater than the corrected reference value, the abnormality is detected. The coefficient is a value greater than 1, and the smaller the corresponding sensitivity, the larger the value. For example, a coefficient of 1.2 is set for "slightly weak", and a coefficient of 1.5 is set for "weak". Thus, when a value (sensor value) of an index that is judged as an abnormality in the sensitivity "standard" of the detection is detected, it does not exceed the reference value in "weak", so it will not be judged as an abnormality, and it can prevent excessive judgment as abnormality. In the present embodiment, a low sensitivity of detection means that the reference value is high, and a high sensitivity of detection means that the reference value is low.

[0043] In this way, the server device 10 detects the abnormality of the user with a judgment standard corresponding to the operation item of the operation being performed by the user. Here, the judgment standard is a standard indicating how to detect the abnormality, and in this embodiment, it is a standard indicating which indicator value exceeds which reference value to be an abnormality.

[0044] In the present embodiment, the detection sensitivity is predetermined so that the detection sensitivity for an abnormal situation predetermined as an abnormal situation assumed to be erroneously detected during operation is set to be below a predetermined threshold value (for example, "slightly weak", "weak", etc.).

[0045] For example, for work items other than work that may cause a fall, such as work at high altitude (work at a height above a predetermined height (e.g., 5m, etc.) from the ground), work that involves lifting and lowering using step stools, etc. (harvesting work, agricultural work such as weeding, etc.), and work on mountain slopes (agricultural work, etc.), there is almost no possibility that the user will fall. Therefore, for such work items, if a fall is detected, it is assumed to be a false detection. Therefore, in the present embodiment, the sensitivity of detection of a fall for such work items is determined to be below a predetermined value ("weak" in the present embodiment). Figure 4 In the example, regarding operations in places where toxic gases may be produced (operations in toxic gas zones), clerical operations, crane operating operations, mobile operations in vehicles, and operations using hammers (hammering operations), the sensitivity of fall detection is set to less than "weak" as a false detection of an assumed fall.

[0046] In addition, in the case where an event that may be confused with an abnormal situation is likely to occur during operation, it is assumed that an abnormal situation may be misdetected. Therefore, in this embodiment, the sensitivity of detection is predetermined by setting the sensitivity of detection of such an abnormal situation to below a predetermined threshold value (e.g., "slightly weak", "weak", etc.).

[0047] In operations such as operations using a hammer, operations using farm tools, and operations moving in a vehicle, acceleration is applied to the user when the hammer / farm tool is used, the vehicle is started / stopped, etc. This acceleration may be confused with the impact applied to the user. Therefore, it is assumed that the impact is erroneously detected. Therefore, in this embodiment, for operations such as operations using a hammer / farm tool, and operations moving in a vehicle that may cause a situation in which a certain acceleration or more is applied to the user, the sensitivity of impact detection is set to be below a predetermined threshold. Figure 4 In the example of FIG. 1 , the sensitivity of detecting the impact is set to “weak” or less for moving work in a vehicle, hammering work, harvesting work, and weeding work.

[0048] In addition, in the present embodiment, the detection sensitivity is predetermined so that the detection sensitivity of the abnormal situation that is predetermined as an abnormal situation that is assumed to cause serious damage to the user during operation is greater than a predetermined threshold value (for example, "weak", "standard", etc.). There is a tendency for a fall to cause serious damage to the user, so it is desirable to prevent undetected falls as much as possible. Figure 4 In the example, for work items where there is a possibility of falling, such as high-altitude work, work involving lifting using step stools, etc., and work on mountain slopes, the detection sensitivity is determined to be above "standard".

[0049] When receiving an instruction to change the detection sensitivity of each abnormal situation for each operation item based on the user's operation on the input device of the server device 10, the processor 101 updates the sensitivity table 401 to change the detection sensitivity of each abnormal situation for each operation item. In addition, the processor 101 may also receive an instruction to change the content of the sensitivity table 401 from the terminal device 20.

[0050] By using the sensitivity table 401 updated in this way, the server device 10 can detect abnormalities under the judgment criteria assumed by the user.

[0051] Figure 5 It is a diagram showing an example of the hardware configuration of each terminal device 20.

[0052] The terminal device 20 includes a processor 201 , a main storage device 202 , an auxiliary storage device 203 , a sensor 204 , a short-range wireless communication I / F 205 , a UI unit 206 , and a communication I / F 207 .

[0053] The processor 201 is a control device for controlling the terminal device 20. The main storage device 202 is a storage device such as RAM for temporary storage of information, expansion of programs, etc. The auxiliary storage device 203 is a storage device such as HDD, SSD, etc. that stores various information and various programs. The sensor 204 is a sensor that detects predetermined information. In this embodiment, the sensor 204 includes an acceleration sensor that detects acceleration in three mutually perpendicular axial directions, a tilt sensor that detects the tilt of the terminal device 20, a camera, a heart rate sensor that detects the heart rate of the user, a position sensor that receives GNSS signals and detects the position, and an altimeter. The short-range wireless communication I / F 205 is an interface for short-range wireless communication with environmental sensors (sensors that detect wet bulb temperature, black bulb temperature, dry bulb temperature, etc.) in the environment where the user is working, beacons that send signals indicating position information, etc. In the following, the signal indicating the position information sent by the beacon is referred to as a beacon signal. The processor 201 obtains the wet bulb temperature, black bulb temperature, and dry bulb temperature in the environment where the user is working from the environmental sensor via the short-range wireless communication I / F 205. The UI unit 206 includes an input unit such as a touch panel, hard buttons, and a microphone for inputting information from the user, and an output unit such as a monitor and a speaker for presenting information to the user. The communication I / F 207 is an interface for communicating with an external device such as the server device 10 via the network 30 .

[0054] In addition, in this embodiment, the terminal device 20 has a heart rate sensor to detect the user's heart rate, but as another example, the terminal device 20 may also obtain the user's heart rate by other methods. For example, the processor 201 of the terminal device 20 may also obtain the user's heart rate detected by an external device (e.g., a smart watch, etc.) having a heart rate sensor from the external device via the short-range wireless communication I / F 205.

[0055] use Figure 6 , the functional structure of the server device 10 is explained.

[0056] The processor 101 of the server device 10 executes a program stored in the auxiliary storage device 103 or the like, thereby functioning as the determination unit 601, the detection unit 602, and the output control unit 603. The processing described below with the determination unit 601, the detection unit 602, and the output control unit 603 as the main body is actually the processing with the processor 101 as the main body.

[0057] The determination unit 601 determines the work item of the work being performed by the user having the terminal device 20. The detection unit 602 detects the abnormality of the user through at least one of the sensor 204 of the terminal device 20 and an external sensor (environmental sensor, etc.) using a judgment standard corresponding to the work item determined by the determination unit 601. The output control unit 603 outputs warning information for the abnormality detected by the detection unit 602.

[0058] use Figure 7 , describing the abnormality detection process of the user having the terminal device 20 executed by the server device 10. When the processor 101 receives the start instruction of the abnormality detection process of the user from the terminal device 20, the processor 101 starts Figure 7Processing. When the processor 201 of the terminal device 20 receives an instruction to start the detection process of an abnormal situation from the user via the UI unit 206, the processor 201 sends the instruction to start the detection process of the abnormal situation to the server device 10. In addition, when the processor 201 sends the instruction to start the detection process of the abnormal situation, it periodically detects the acceleration applied to the terminal device 20 (user), the tilt of the terminal device 20, and the heart rate of the user via the sensor 204, and sends the detected information to the server device 10. However, the processor 201 can also instruct the sensor 204 to send the value of the detected signal only when it exceeds a specified threshold. In this case, when a signal exceeding the specified threshold is detected, the sensor 204 sends the detected signal to the processor 201. In addition, when the processor 201 sends the instruction to start the detection process of the abnormal situation, it periodically obtains the detected signal from the environmental sensor and beacon in the environment where the user is working via the short-range wireless communication I / F 205. Then, the processor 201 periodically sends the signal obtained from the environmental sensor and beacon to the server device 10.

[0059] In step S100, the determination unit 601 determines the work item of the work being performed by the user having the terminal device 20. In the present embodiment, the determination unit 601 determines the work item of the work being performed by the user based on the location of the terminal device 20 (the location of the user). More specifically, the determination unit 601 inquires the terminal device 20 about the location of the terminal device 20. Based on the inquiry, the processor 201 of the terminal device 20 determines the location (latitude, longitude, altitude) of the terminal device 20 via the location sensor and the altimeter included in the sensor 204. However, the processor 201 may also determine the location of the terminal device 20 by other methods. For example, when there is a device that sends a beacon signal indicating the location of the terminal device 20 around the terminal device 20, the processor 201 may also receive the beacon signal and determine the location based on the received beacon signal. The processor 201 sends the determined location to the server device 10. The identification unit 601 obtains the work item corresponding to the position transmitted from the terminal device 20 based on the correspondence information between the position and the work item pre-stored in the auxiliary storage device 103, and identifies the obtained work item as the work item of the user's work.

[0060] After completing the process of step S100, the determination unit 601 proceeds to step S101. The process of step S100 is an example of a determination step.

[0061] In step S101, the detection unit 602 determines the sensitivity of detection of each abnormality for the work item determined in step S100 based on the sensitivity table 401 stored in the auxiliary storage device 103. After completing the process of step S101, the determination unit 601 advances the process to step S102.

[0062] In step S102, the detection unit 602 selects one of the multiple abnormal conditions (fall, fall, impact, lying still, fatigue, high heart rate) of the detection object. Hereinafter, the abnormal condition selected in the previous step S102 is referred to as the selected abnormal condition. After the determination unit 601 completes the processing of step S102, the processing proceeds to step S103. In addition, when the sensitivity of the detection of the selected abnormal condition determined by the detection unit 602 in step S101 is "off", after the processing of step S102 is completed, the processing proceeds to step S107.

[0063] In step S103, the detection unit 602 determines the index corresponding to the selected abnormal situation from the reference value table 301. Then, the detection unit 602 obtains the value of the determined index. More specifically, the detection unit 602 performs the following processing.

[0064] When the abnormal situation is selected as a fall, the detection unit 602 obtains the change value of the acceleration applied to the terminal device 20 in the vertical and horizontal directions within a predetermined period as the value of the indicator based on the information of the acceleration applied to the terminal device 20 received from the terminal device 20.

[0065] When the abnormal situation is selected as falling, the detection unit 602 obtains the conversion value of the acceleration in the vertical direction applied to the terminal device 20 within a predetermined period as the value of the index based on the information of the acceleration applied to the terminal device 20 received from the terminal device 20.

[0066] When the abnormality is selected as impact, the detection unit 602 obtains the scalar value of the composite vector of the three-axis acceleration applied to the terminal device 20 as the index value based on the information of the acceleration applied to the terminal device 20 received from the terminal device 20.

[0067] When the abnormal condition is selected as lying still, the detection unit 602 obtains the following value based on the information of the inclination of the terminal device 20 and the acceleration applied to the terminal device 20 received from the terminal device 20. That is, the detection unit 602 obtains the value of the index during the period when the inclination of the terminal device 20 is within a predetermined range corresponding to the work item being worked on by the user and the acceleration applied to the terminal device 20 is 0.

[0068] When fatigue is selected as the abnormal condition, the detection unit 602 obtains the duration of the operation of the user having the terminal device 20 (the elapsed period from the start of the abnormal condition detection process) as the value of the index. In addition, the detection unit 602 requests the terminal device 20 for the wet bulb temperature, black bulb temperature, and dry bulb temperature of the environment in which the user performs the operation. In response to the request, the processor 201 obtains the wet bulb temperature, black bulb temperature, and dry bulb temperature from the environmental sensor via the short-range wireless communication I / F 205, and transmits them to the server device 10. The detection unit 602 obtains the WBGT value based on the received wet bulb temperature, black bulb temperature, and dry bulb temperature.

[0069] When the abnormality is selected as a high heart rate, the detection unit 602 acquires the user's heart rate received from the terminal device 20 as an index value.

[0070] After completing the process of step S103 , the determination unit 601 advances the process to step S104 .

[0071] In step S104, the detection unit 602 obtains the reference value corresponding to the selected abnormal condition from the reference value table 301. In addition, when the selected abnormal condition is fatigue, the detection unit 602 obtains the reference value corresponding to the WBGT value determined in step S103 from the reference value table 301. The detection unit 602 corrects the value of the obtained reference value according to the sensitivity of the detection of the selected abnormal condition determined in step S101. In addition, when the selected abnormal condition is a fall, the detection unit 602 corrects the two reference values ​​respectively.

[0072] More specifically, when the sensitivity of the abnormal situation is selected as "standard", the detection unit 602 does not correct the reference value. In addition, when the sensitivity of the abnormal situation is selected as "slightly weak", the detection unit 602 corrects the reference value by multiplying it by a predetermined coefficient greater than 1. In addition, when the sensitivity of the abnormal situation is selected as "weak", the detection unit 602 corrects the reference value by multiplying it by a predetermined coefficient greater than the coefficient corresponding to "slightly weak". In addition, the coefficients corresponding to the sensitivity "slightly weak" and "weak" can be different values ​​according to the abnormal situation of the detection object, or can be the same value. After the processing of step S104 is completed, the determination unit 601 causes the processing to enter step S105.

[0073] In step S105 , the detection unit 602 determines whether the value of the index acquired in the previous step S103 is equal to or greater than the reference value corrected based on the sensitivity in the previous step S104 .

[0074] In addition, when the abnormal situation is selected as a fall, when the values ​​of two indicators (the change value of the acceleration in the vertical direction and the change value of the acceleration in the horizontal direction) are both above the corresponding reference values, the detection unit 602 determines that the value of the indicator is above the reference value.

[0075] When the detection unit 602 determines that the value of the index is greater than the reference value, it detects a selection abnormality and causes the process to proceed to step S106. When the detection unit 602 determines that the value of the index is less than the reference value, it determines that no selection abnormality has occurred and causes the process to proceed to step S107. The process of step S105 is an example of a detection step.

[0076] In step S106, the output control unit 603 outputs information indicating a warning for the occurrence of the selected abnormal situation to a predetermined output destination. In this embodiment, the output control unit 603 sends information indicating a warning for the selected abnormal situation to an information processing device possessed by an administrator who manages the user, and displays the information on a display unit of the information processing device. The information indicating a warning for the abnormal situation is, for example, information indicating that an abnormal situation has occurred, information urging the user to respond to the occurrence of the abnormal situation, and the like.

[0077] In addition, in this embodiment, when the operation item determined in step S100 is "harvesting operation", the output control unit 603 sends an alarm message indicating the possibility of falling to the terminal device 20, and displays the alarm of falling on the UI unit 206 to prompt the user. This is because when the harvested objects are at a high place, the user may pay attention to the feet.

[0078] After completing the process of step S106 , the output control unit 603 advances the process to step S107 .

[0079] In step S107, the detection unit 602 determines whether all of the multiple abnormal situations of the detection object are selected as the selected abnormal situation in step S102. If the detection unit 602 determines that all of the multiple abnormal situations of the detection object are selected as the selected abnormal situation in step S102, the processing proceeds to step S108. If the detection unit 602 determines that there is an abnormal situation that is not selected as the selected abnormal situation in step S102 among the multiple abnormal situations of the detection object, the processing proceeds to step S102.

[0080] In step S108, the detection unit 602 determines whether an instruction to end the abnormality detection process has been received from the terminal device 20. If the detection unit 602 determines that an instruction to end the abnormality detection process has been received from the terminal device 20, the detection unit 602 completes the abnormality detection process. Figure 7In addition, when the detection unit 602 determines that the instruction to end the abnormality detection process has not been received from the terminal device 20, it clears the history records selected as the selected abnormality for the multiple abnormalities to be detected, and advances the process to step S100.

[0081] As described above, according to the configuration of the present embodiment, the server device 10 can contribute to improving the accuracy of abnormality detection by detecting abnormalities based on the judgment criteria according to the work items being worked on by the user.

[0082] In the present embodiment, the server device 10 sets the detection sensitivity to a predetermined value or less for abnormal situations that are predetermined as abnormal situations that are assumed to be erroneously detected for the work items being performed by the user. Thus, the server device 10 can reduce erroneous detection of the abnormal situations.

[0083] In addition, the server device 10 sets the detection sensitivity to a predetermined value or more for an abnormality predetermined as an abnormality that causes serious damage to the user in the work item being worked on by the user. Thus, the server device 10 can reduce the number of undetected abnormalities.

[0084] (Second Embodiment)

[0085] In the present embodiment, the server device 10 detects abnormality based on a judgment criterion corresponding to the load of the work being performed by the user (hereinafter referred to as work load), not the work item being performed by the user.

[0086] Hereinafter, the detection system 1 of the present embodiment will be described with respect to points different from the first embodiment.

[0087] The system configuration of the detection system 1 of this embodiment is the same as that of the first embodiment. In addition, the hardware configuration of the server device 10 and the terminal device 20 of this embodiment is the same as that of the first embodiment.

[0088] The functional configuration of the server device 10 according to the present embodiment will be described.

[0089] The processor 101 of this embodiment functions as a determination unit 601 , a detection unit 602 , and an output control unit 603 similarly to the first embodiment.

[0090] The determination unit 601 of this embodiment determines the workload of the operation being performed by the user having the terminal device 20. In addition, the detection unit 602 detects the abnormality of the user through at least one of the sensor 204 of the terminal device 20 and an external sensor (environmental sensor, etc.) using a judgment criterion corresponding to the workload determined by the determination unit 601. The output control unit 603 is the same as that of the first embodiment.

[0091] In this embodiment, the server device 10 uses a sensitivity table 801 instead of the sensitivity table 401. The sensitivity table 801 is pre-stored in the auxiliary storage device 103. Figure 8 , the sensitivity table 801 of this embodiment is described.

[0092] The sensitivity table 801 of this embodiment shows the correspondence between the workload and the detection sensitivity of each abnormality.

[0093] The work load is a measure indicating that the greater the load during work, and in the present embodiment, takes a value of 0 to 100.

[0094] In the present embodiment, the value of the workload is classified into four levels: a level of 25 or less, a level of more than 25 and less than 50, a level of more than 50 and less than 75, and a level of more than 75 and less than 100.

[0095] In the present embodiment, regarding the abnormal situation in which the workload value is assumed to be erroneously detected, the detection sensitivity is determined to be equal to or less than a threshold value for a predetermined abnormal situation.

[0096] The sensitivity of fatigue detection is determined to be “slightly weak” or less for work load values ​​of level 25 or less and level greater than 25 and less than 50. This is because it is believed that the smaller the work load, the less fatigue is accumulated.

[0097] In addition, in the present embodiment, the sensitivity of detection is determined to be equal to or greater than a threshold value for an abnormal situation that is predetermined as an abnormal situation in which damage to the user becomes serious with respect to the value of the workload.

[0098] In addition, for the values ​​of the workload of the level below 25 and the level above 50, the sensitivity of the high heart rate detection is set to be above "standard". This is because the smaller the workload, the smaller the factor of the heart rate increase, so the reason why the heart rate increases despite such a situation is that it is likely to be caused by a cardiac abnormality. However, in order to avoid the danger of a high heart rate when the workload is heavy, the sensitivity of the high heart rate detection can also be set to be greater as the workload is greater.

[0099] Thus, the detection unit 602 can change the sensitivity of detecting "fatigue" and "high heart rate" according to the value of the workload. In this embodiment, the detection unit 602 increases the sensitivity of detecting "fatigue" and "high heart rate" as the value of the workload increases.

[0100] In addition, for abnormal conditions other than "fatigue" and "high heart rate", the detection unit 602 may also change the detection sensitivity according to the value of the workload. The detection unit 602 may also increase the detection sensitivity to above the predetermined threshold for abnormal conditions other than "fatigue" and "high heart rate" (for example, falls, drops, impacts, lying still, etc.) when the value of the workload is above the predetermined threshold for a period of time above the predetermined threshold, as the risk of industrial accidents increases due to the reduction of the operator's physical strength and judgment. For example, the detection unit 602 may also increase the detection sensitivity to the standard for the case where the detection sensitivity of falls, drops, impacts, and lying still is less than the standard.

[0101] use Fig. 9 The detection process of abnormality in this embodiment is described below. Fig. 9 in the process of Figure 7 The different points of processing are explained below.

[0102] Fig. 9 Processing and Figure 7 Compared with the processing of , it is different in that the processing of steps S100 and S101 is replaced by the processing of steps S200 and S201.

[0103] In step S200, the determination unit 601 determines the workload of the operation being performed by the user based on the user's heart rate in the previous predetermined period obtained from the terminal device 20. In addition, when the predetermined period includes a rest period of the user, the determination unit 601 determines the workload based on the user's heart rate in the period after the rest period. In the present embodiment, the determination unit 601 calculates the average heart rate of the user in each certain interval (for example, an interval of a predetermined number of seconds, etc.) within the predetermined period (or the period after the rest period). Then, the determination unit 601 determines whether the average heart rate is above a predetermined threshold for each interval. The determination unit 601 determines the workload by multiplying the number of intervals in which the average heart rate is above a predetermined threshold by a predetermined coefficient.

[0104] After completing the process of step S200 , the determination unit 601 proceeds to step S201 .

[0105] In step S201 , the detection unit 602 determines the sensitivity of detecting each abnormality corresponding to the workload determined in step S200 , based on the sensitivity table 801 indicating the correspondence between the workload and the sensitivity of detecting the abnormality.

[0106] As described above, according to the configuration of the present embodiment, the server device 10 can contribute to improving the accuracy of abnormality detection by detecting abnormalities based on a criterion that corresponds to the workload of the job being performed by the user.

[0107] In addition, in the present embodiment, regarding the workload of the user's ongoing work, the server device 10 sets the detection sensitivity to a predetermined value or less as an abnormality predetermined as an abnormality assumed to be erroneously detected. Thus, the server device 10 can reduce erroneous detection of the abnormality.

[0108] In addition, regarding an abnormal situation that is predetermined as an abnormal situation that causes serious damage to the user with respect to the workload of the work being performed by the user, the server device 10 sets the detection sensitivity to a predetermined value or more. Thus, the server device 10 can reduce the number of undetected abnormal situations.

[0109] (Third Embodiment)

[0110] In the present embodiment, the server device 10 detects an abnormality based on a judgment criterion according to the work item of the work being performed by the user and the work load of the work being performed by the user.

[0111] Hereinafter, the detection system 1 of the present embodiment will be described with respect to points different from the first embodiment.

[0112] The system configuration of the detection system 1 of this embodiment is the same as that of the first embodiment. In addition, the hardware configuration of the server device 10 and the terminal device 20 of this embodiment is the same as that of the first embodiment.

[0113] The functional configuration of the server device 10 according to the present embodiment will be described.

[0114] The processor 101 of this embodiment functions as a determination unit 601 , a detection unit 602 , and an output control unit 603 similarly to the first embodiment.

[0115] The determination unit 601 of this embodiment determines the work item and work load of the work being performed by the user having the terminal device 20. In addition, the detection unit 602 detects abnormality of the user based on a judgment standard corresponding to the work item and work load determined by the determination unit 601. The output control unit 603 is the same as that of the first embodiment.

[0116] In this embodiment, the server device 10 uses sensitivity tables 1001 and 1002 instead of the sensitivity table 401. The sensitivity tables 1001 and 1002 are stored in advance in the auxiliary storage device 103. Fig.10 The sensitivity tables 1001 and 1002 according to this embodiment will be described.

[0117] The sensitivity table 1001 of this embodiment is a table showing the correspondence between work items and detection sensitivities of falling, dropping, impact, and lying still. In addition, the sensitivity table 1002 is a table showing the correspondence between work load and detection sensitivities of fatigue and high heart rate.

[0118] use Fig.11 , the detection and processing of abnormal situations in this embodiment are described. Fig.11 In the process of Figure 7 The different points of processing are explained below.

[0119] Fig.11 Processing and Figure 7 Compared with the processing of , it is different in that the processing of steps S100 and S101 is replaced by the processing of steps S300 and S301.

[0120] In step S300, the identification unit 601 identifies the work item of the work performed by the user in the same process as that of the first embodiment. In addition, the identification unit 601 identifies the work load of the work performed by the user in the same process as that of the second embodiment.

[0121] In step S301 , the detection unit 602 determines the sensitivity of detecting each abnormality corresponding to the work item and the work load determined in step S100 , based on the sensitivity tables 1001 and 1002 .

[0122] As described above, according to the configuration of the present embodiment, the server device 10 can contribute to improving the accuracy of abnormality detection by detecting abnormalities based on the criteria corresponding to the work items and work load of the work being performed by the user.

[0123] (Fourth Embodiment)

[0124] In the present embodiment, the server device 10 detects abnormality based on a judgment criterion according to the user's means of movement.

[0125] Hereinafter, the detection system 1 of the present embodiment will be described with respect to points different from the first embodiment.

[0126] The system structure of the detection system 1 of the present embodiment is the same as that of the first embodiment. In addition, the hardware structure of the server device 10 and the terminal device 20 of the present embodiment is the same as that of the first embodiment. In the present embodiment, the abnormal conditions of the detection object include not only falling, falling, impact, lying still, fatigue, and high heart rate, but also the tilt of the moving body. The tilt of the moving body is an abnormal condition in which the moving body (bicycle, car, forklift, heavy machinery, etc.) used by the user tilts to a certain degree or more and may fall. In the present embodiment, the moving body that the user can use is equipped with a tilt sensor, an acceleration sensor, and an internal camera.

[0127] In this embodiment, the server device 10 uses a reference value table 1201 instead of the reference value table 301. The reference value table 1201 is pre-stored in the auxiliary storage device 103. Fig.12 The reference value table 1201 of this embodiment will be described.

[0128] exist Fig.12 In the example, the reference value table 1201 has Figure 3 In addition to the various information in the example, the information of the index and the reference value about the abnormal situation of the vehicle body falling is also included. The index for detecting the tilt of the moving body is the tilt of the moving body detected by the tilt sensor provided in the moving body.

[0129] In addition, in this embodiment, the server device 10 uses a sensitivity table 1301 instead of the sensitivity table 401. The sensitivity table 1301 is pre-stored in the auxiliary storage device 103. Fig.13 The sensitivity table 1301 of this embodiment is described. The sensitivity table 1301 of this embodiment shows the correspondence between the means of movement that the user can take and the sensitivity of detection of each abnormal situation. In this embodiment, the means of movement that the user can take are walking, bicycles, passenger cars, cars, motorcycles, trucks, forklifts, tractors, and torpedo vehicles, but as other examples, some of them may not be included, and other means of movement such as forklifts may also be included.

[0130] In the present embodiment, the detection sensitivity is predetermined so that the detection sensitivity for an abnormal situation predetermined as an abnormal situation in which erroneous detection is assumed to occur during operation is below a predetermined threshold value (for example, "slightly weak", "weak", etc.).

[0131] For example, when the user's means of movement is other than walking or riding a bicycle, it is not assumed that the user has fallen or tripped. Therefore, when the user's means of movement is other than walking or riding a bicycle, if a fall or trip is detected, it is assumed to be a false detection. Therefore, in this embodiment, the sensitivity of the detection of a fall or trip for means of movement other than walking or riding a bicycle is determined to be less than a predetermined value ("weak" in this embodiment). Fig.13 In the example, for passenger cars, automobiles, motorcycles, trucks, forklifts, tractors, and torpedo vehicles, as false detections of falls and drops are not anticipated, the sensitivity of fall and drop detection is set to "weak" or less.

[0132] In addition, in the case where an event that may be confused with an abnormal situation is likely to occur during operation, it is assumed that an abnormal situation may be misdetected. Therefore, in this embodiment, the sensitivity of detection is predetermined by setting the sensitivity of detection of such an abnormal situation to below a predetermined threshold value (e.g., "slightly weak", "weak", etc.).

[0133] When riding on some moving objects, acceleration is applied to the user when starting or stopping. This acceleration may be confused with the impact applied to the user. Therefore, it is assumed that the impact is erroneously detected. Therefore, in this embodiment, for means of movement other than walking, the sensitivity of impact detection is set to be below a predetermined threshold. Fig.13 In the example, for bicycles, passenger cars, automobiles, motorcycles, trucks, forklifts, tractors, and torpedo vehicles, the impact detection sensitivity is determined to be "slightly weak" or less.

[0134] In addition, in the present embodiment, the sensitivity of detection is predetermined in such a way that the sensitivity of detection of abnormal situations that are predetermined as abnormal situations that are assumed to cause serious damage to the user during operation is greater than a predetermined threshold. When a user is riding in a moving object such as a car, if the user lies in a horizontal position and does not move, it is assumed that the moving object will perform an undesirable movement and cause an accident, which will cause serious damage to the user. Therefore, when a user is riding in such a moving object, it is desirable to prevent the user from lying in a horizontal position without detection. Fig.13 In the example of FIG. 1 , for a passenger car, a car, a motorcycle, a truck, an excavator, a tractor, and a torpedo vehicle, the sensitivity of the recumbent detection is determined to be above “standard”.

[0135] The functional configuration of the server device 10 according to the present embodiment will be described.

[0136] The processor 101 of this embodiment functions as a determination unit 601 , a detection unit 602 , and an output control unit 603 similarly to the first embodiment.

[0137] The determination unit 601 of this embodiment determines the means of movement of the user having the terminal device 20. In addition, the detection unit 602 detects abnormality of the user via at least one of the sensor 204 and an external sensor using a judgment criterion corresponding to the workload determined by the determination unit 601. The output control unit 603 is the same as that of the first embodiment.

[0138] use Fig.14 , the detection and processing of abnormal situations in this embodiment are described. Fig.14 In the process of Figure 7 The different points of processing are explained below.

[0139] Fig.14 Processing and Figure 7 Compared with the processing of , it is different in that the processing of steps S400 and S401 is included instead of the processing of steps S100 and S101.

[0140] In step S400, the determination unit 601 determines the user's means of movement. In this embodiment, when the terminal device 20 of the user communicates with the communication device of the mobile body (two-way communication or one-way communication), the determination unit 601 determines the mobile body as the user's means of movement. More specifically, the determination unit 601 is as follows.

[0141] In this embodiment, each of the mobile bodies that the user can ride on has a communication device that emits a predetermined beacon signal that can be received near the mobile body. When the processor 201 of the terminal device 20 receives a beacon signal from the communication device of the mobile body via the short-range wireless communication I / F 205, it sends the received beacon signal to the server device 10. When receiving the beacon signal, the determination unit 601 determines the mobile body that has the communication device that sent the beacon signal based on the received beacon signal, and determines the determined mobile body as the user's means of movement. In addition, when no beacon signal is received, the determination unit 601 determines walking as the user's means of movement.

[0142] Furthermore, when determining a predetermined moving object as the user's means of movement, the determination unit 601 periodically obtains information on the inclination and acceleration detected by the inclination sensor and acceleration sensor of the determined moving object and an image captured by a camera inside the moving object.

[0143] After completing the process of step S400 , the determination unit 601 advances the process to step S401 .

[0144] In step S401 , the detection unit 602 determines the sensitivity of detection of each abnormality corresponding to the moving means determined in the previous step S400 , based on the sensitivity table 1301 .

[0145] Furthermore, in step S103 of the present embodiment, the detection unit 602 obtains the value of the abnormality: shock index (the scalar value of the composite vector of the acceleration of three axes detectable by the acceleration sensor) based on the value of the acceleration detected by the acceleration sensor provided by the mobile body when the user's means of movement is a predetermined mobile body. However, even when the user's means of movement is a predetermined mobile body, the detection unit 602 may obtain the value of the abnormality: shock index based on the value of the acceleration detected by the acceleration sensor of the terminal device 20.

[0146] In addition, in the present embodiment, when the user's moving means is a predetermined moving body, the detection unit 602 detects an abnormality based on a signal detected by a sensor provided on the moving body. In the present embodiment, the detection unit 602 obtains a value of an indicator of abnormality: moving body tilt based on a value of tilt detected by the tilt sensor in step S103, and detects the moving body tilt based on the obtained value.

[0147] In addition, in step S103, when the user's means of movement is a predetermined moving body, the detection unit 602 obtains the abnormal situation as follows: the value of the index of lying still. The detection unit 602 obtains the following value based on the images continuously captured by the internal camera of the moving body along the time series. That is, the detection unit 602 obtains the period during which the user maintains a posture different from the predetermined driving posture (a posture of holding the steering wheel and looking forward) (for example, a posture of taking the hands off the steering wheel, a posture of lying prone on the steering wheel, etc.). Then, the detection unit 602 detects lying still using the value of the acquired period.

[0148] Furthermore, in step S106 of the present embodiment, when the moving means is a predetermined moving body and the selected abnormal situation is an impact, the output control unit 603 outputs information indicating a warning for emergency braking as a warning for the impact.

[0149] In addition, in the present embodiment, the detection unit 602 detects the user's dangerous driving based on the image of the internal camera of the mobile body. When the user continues a posture different from the predetermined driving posture for a predetermined period (for example, 3 seconds, 5 seconds, etc.), the detection unit 602 outputs information indicating a warning for dangerous driving to a predetermined output destination (for example, the terminal device 20, the display unit of the mobile body, the server device 10, the information processing device of the administrator, etc.). In addition, the detection unit 602 stores the image of the state of dangerous driving in the auxiliary storage device 103. Thus, the server device 10 can contribute to the analysis of the situation during dangerous driving.

[0150] As described above, according to the structure of this embodiment, the server device 10 can detect abnormal situations corresponding to the situation where the user uses different means of transportation by detecting abnormal situations under the judgment criteria corresponding to the user's means of transportation, which can help improve the accuracy of abnormal situations.

[0151] In addition, in the present embodiment, the server device 10 sets the detection sensitivity to a predetermined value or less for abnormal situations that are predetermined for the user's means of movement as abnormal situations that are assumed to be erroneously detected. Thus, the server device 10 can reduce erroneous detection of the abnormal situations.

[0152] In addition, the server device 10 sets the detection sensitivity to a predetermined value or more for an abnormality that is predetermined for the user's means of movement as an abnormality that causes serious damage to the user. Thus, the server device 10 can reduce undetected abnormalities.

[0153] In addition, in this embodiment, when the moving means is a predetermined moving body, the detection unit 602 obtains the value of the recumbent index based on the image captured by the internal camera of the moving body. The period during which the user does not move can be obtained more accurately through the image. As a result, the detection unit 602 can detect the user's recumbent state with higher accuracy.

[0154] (Note)

[0155] In each of the above-mentioned embodiments, the server device 10 detects falls, falls, impacts, lying still, fatigue, and high heart rate as abnormal conditions. However, the server device 10 may not detect at least a part of these abnormal conditions, and may also detect other abnormal conditions (gas leakage, excessive decrease in heart rate, high pressure (stress), etc.). For example, the sensor 204 may also have a gas sensor for detecting gas. In this case, the processor 201 of the terminal device 20 detects the concentration of the gas. Moreover, the processor 101 may also obtain the concentration of the gas from the terminal device 20 via the gas sensor, and detect gas leakage when the obtained concentration is above the reference value. In addition, for example, the processor 201 of the terminal device 20 may also obtain the concentration of the gas detected by an external device (for example, a gas detector, etc.) having a gas sensor from the external device via the short-range wireless communication I / F 205, and send the obtained gas concentration to the server device 10.

[0156] In addition, for example, the processor 101 may detect high stress when the user's heart rate is above a reference value.

[0157] In addition, in each of the above-mentioned embodiments, as an indicator used for detecting abnormal situations, the server device 10 uses an indicator whose larger value indicates a greater degree of abnormal situation. However, as an indicator for detecting abnormal situations, the server device 10 may also use an indicator whose smaller value indicates a greater degree of abnormal situation (for example, the inverse of the indicator in each of the above-mentioned embodiments, the heart rate when detecting abnormal situations such as cardiopulmonary arrest where the heart rate is excessively reduced, etc.). In this case, in step S104, the detection unit 602 may correct the reference value according to the sensitivity so that the smaller the sensitivity, the smaller the reference value. Then, the detection unit 602 may detect the abnormal situation when the value of the indicator is below the reference value in step S105. Thus, the server device 10 can detect abnormal situations corresponding to the sensitivity even when using an indicator whose smaller value indicates a greater degree of abnormal situation.

[0158] In addition, in each of the above-mentioned embodiments, the duration of the operation of the user having the terminal device 20 is used as an indicator for detecting abnormal conditions: fatigue. However, other indicators may be used as indicators for detecting abnormal conditions: fatigue. For example, the stress value of the user may be used as an indicator for detecting abnormal conditions: fatigue. Here, the stress value refers to an indicator value that is higher when it is estimated that the user feels stressed. It is known that the more stressed the user feels, the more active the sympathetic nerves are.

[0159] Therefore, for example, the detection unit 602 may also estimate the activity level of the sympathetic nerves based on the heart rate detected by the heart rate sensor included in the sensor 204 in step S103, and obtain it as a pressure value. Specifically, the detection unit 602 first measures the power spectrum density in order to extract the periodic structure from the time series data of the heart rate variation. The power spectrum density includes a high-frequency variation component (HF component) and a low-frequency component (LF component). The detection unit 602 obtains the total value of the intensity of the LF component area (0.05 Hz to 0.15 Hz) and the HF component area (0.15 Hz to 0.40 Hz), respectively, as the value of the LF component and the value of the HF component. Then, the detection unit 602 can obtain (the value of the LF component) / (the value of the HF component) as the pressure value.

[0160] In a relaxed state, that is, when the parasympathetic nerves are active, the HF component reflecting the respiratory fluctuation and the LF component reflecting the blood pressure fluctuation appear. On the other hand, in a stressed state, that is, when the sympathetic nerves are active, the LF component appears, while the HF component decreases. Therefore, the greater the stress, the greater the pressure value.

[0161] In addition, in each of the above-mentioned embodiments, the sensor 204 includes an acceleration sensor for detecting acceleration in three-axis directions, a tilt sensor for detecting the tilt of the terminal device 20, a camera, a heart rate sensor for detecting the heart rate of the user, a position sensor for receiving GNSS signals and detecting the position, and an altimeter. However, the sensor 204 may not have at least some of them. For example, the sensor 204 may not have an altimeter. In this case, the processor 101 may also obtain the altitude information from the altimeter provided in the environment where the user performs the operation.

[0162] In addition, in each of the above-mentioned embodiments, the server device 10 sets the sensitivity of detecting an abnormal situation that is predetermined for any one of the work items, work load, and user's means of movement of the user, that is, an abnormal situation that is assumed to be misdetected, to below a predetermined threshold. However, the server device 10 may also detect an abnormal situation that is predetermined for any one of the work items, work load, and user's means of movement of the user, that is, an abnormal situation that is assumed to be misdetected, as follows. That is, the server device 10 may also make the sensitivity of detecting the abnormal situation smaller than the case where the abnormal situation is not assumed to be misdetected. For example, the server device 10 may also make the sensitivity of detecting a fall in a work item that is assumed to be misdetected: a fall in a clerical work lower than the sensitivity of detecting a fall in a work item that is not assumed to be misdetected: a fall in an aerial work.

[0163] In addition, in each of the above-mentioned embodiments, the output control unit 603 outputs information of a warning for a detected abnormal situation. The output control unit 603 may also switch the display mode of the warning information according to the severity of the detected abnormal situation. For example, the output control unit 603 may also obtain the difference obtained by subtracting the reference value from the value of the index corresponding to the abnormal situation as a scale indicating the severity of the abnormal situation, and switch the display mode of the warning information according to the obtained scale. For example, the output control unit 603 may also switch the content of the warning information to be output according to whether the obtained scale is above the threshold. For example, if the obtained scale is above the threshold, the output control unit 603 may also output information indicating that it is a more serious situation than the situation less than the threshold. In addition, the output control unit 603 may also display the warning information in a different color from the situation where the scale is less than the threshold when the obtained scale is above the threshold. In addition, the output control unit 603 may also output a different sound as the warning information when the obtained scale is above the threshold and the scale is less than the threshold. In addition, the output control unit 603 may also receive a response indicating confirmation of the warning from the output destination of the information indicating the warning. In addition, the output control unit 603 may also notify the predetermined output destination (police, fire department, etc.) of the information indicating the warning of the abnormal situation when no response is received within a predetermined period from the output of the information indicating the warning. Thus, the server device 10 can improve the safety of users.

[0164] In addition, in each of the above-mentioned embodiments, the output control unit 603 outputs information indicating a warning for an abnormal situation to an information processing device possessed by the administrator. However, the output control unit 603 may also output information indicating a warning for an abnormal situation to other output destinations. For example, the output control unit 603 may also output the information to the terminal devices 20 of other users that exist within a predetermined range centered on the user in which the abnormal situation occurred. In addition, the output control unit 603 may also output the information to the terminal device 20 possessed by the user in which the abnormal situation occurred. For example, the output control unit 603 may also send information indicating a warning for the occurrence of a selected abnormal situation (for example, information indicating a recommended rest when the abnormal situation is fatigue, etc.) to the user's terminal device 20, and cause the UI unit 206 to display the information.

[0165] In addition, the output control unit 603 may also change the output destination of the information indicating the warning according to the type of abnormality detected by the detection unit 602. The output control unit 603 may also output the warning information to the user's terminal device 20 when the abnormality detected by the detection unit 602 is fatigue, and output the warning information to the terminal devices 20 of other users around the user, the information processing device of the administrator, etc. when the abnormality detected by the detection unit 602 is falling. In this way, the server device 10 can present a warning of the abnormality to the object corresponding to the occurrence of each abnormality.

[0166] In addition, in each of the above-mentioned embodiments, the output control unit 603 outputs information indicating a warning for an abnormal situation by causing the display unit to display information indicating a warning for an abnormal situation. However, the output control unit 603 may also output information indicating a warning for an abnormal situation in other ways. For example, the output control unit 603 may also output information indicating a warning for an abnormal situation by sound via a speaker. In addition, the output control unit 603 may output information indicating a warning for an abnormal situation by vibrating a vibrator or the like, or may output information indicating a warning for an abnormal situation by causing a lamp such as a rotating lamp to emit light.

[0167] In addition, in each of the above-mentioned embodiments, the server device 10 detects the abnormality of the user based on a judgment criterion corresponding to at least one of the work item and the work load of the work being performed by the user and the user's means of movement. However, the server device 10 may detect the abnormality of the user based on a judgment criterion corresponding to at least one of the work item and the work load of the work being performed by the user and the user's means of movement.

[0168] For example, the detection unit 602 may be as follows. That is, the detection unit 602 calculates the sensitivity of detection of each abnormal situation in the same manner as in the third embodiment, and determines the user's means of movement in the same manner as in the fourth embodiment. Furthermore, the detection unit 602 may not update the sensitivity of detection of each abnormal situation when the determined means of movement is walking or a bicycle, and may update the sensitivity of a predetermined abnormal situation (e.g., a fall, etc.) to below a predetermined threshold when the determined means of movement is a vehicle or a work vehicle. Furthermore, the detection unit 602 may determine the user's means of movement at predetermined intervals, and update the sensitivity of detection of abnormal situations based on the determined means of movement.

[0169] In addition, for example, the detection unit 602 may be as follows. The detection unit 602 obtains the sensitivity of detection of each abnormal situation in the same manner as in the fourth embodiment. In addition, the detection unit 602 obtains the workload of the operation being performed by the user in the same manner as in the second embodiment. If the obtained workload is above a predetermined threshold, the detection unit 602 may also increase the sensitivity of detection of each obtained abnormal situation.

[0170] In the first and third embodiments described above, the identification unit 601 identifies the work item based on the user's position. However, the identification unit 601 may identify the work item being performed by the user having the terminal device 20 by other methods.

[0171] For example, the determination unit 601 obtains an image of the surroundings of the terminal device 20 (for example, an image of the user, an image of the user's surroundings, etc.) captured by the camera of the terminal device 20. The determination unit 601 obtains the image of the surroundings of the terminal device 20 by requesting the terminal device 20 for the image of the surroundings of the terminal device 20. The processor 201 of the terminal device 20 captures the image of the surroundings of the terminal device 20 via the camera of the sensor 204 in accordance with the request, and sends the captured image to the server device 10. However, the determination unit 601 may also obtain an image of the surroundings of the terminal device 20 captured by a camera different from the camera of the terminal device 20. For example, the determination unit 601 may also obtain an image captured by other cameras (helmet-mounted cameras, body cameras, etc.) possessed by the user possessing the terminal device 20, an image captured by a fixed camera possessed by the user, etc.

[0172] The determination unit 601 may also determine the work item based on the acquired image. For example, when the determination unit 601 recognizes a tool (agricultural implement, tool, equipment, vehicle, etc.) used in the work of a specific work item from the image, the work item of the work using the recognized tool may be determined as the work item of the work performed by the user.

[0173] In addition, for example, the determination unit 601 may also obtain information of a type different from the user's position (e.g., information of the time period during processing, etc.), and determine the work item of the user's work based on the information of the type and the corresponding information of the work item. For example, when the work item of the work performed by the user is determined based on the time period (e.g., summer: weeding work, autumn: harvesting work, etc.), the determination unit 601 may also determine the work item corresponding to the time period during processing.

[0174] In addition, for example, when the schedule of the job is determined for each user, the determination unit 601 may be as follows: That is, the determination unit 601 may obtain the identification information of the user from the terminal device 20, determine the schedule of the user of the obtained identification information, and determine the job item of the job performed by the user at the processing time point.

[0175] In addition, for example, the determination unit 601 may inquire the terminal device 20 about the work item of the job performed by the user. In response to the inquiry, the processor 201 inquires about the work item from the user via the UI unit 206. If the processor 201 receives an input of the work item (touch input, voice input, gesture input, etc.) from the user via the UI unit 206, the processor 201 transmits the input work item to the server device 10. The determination unit 601 may also determine the work item received from the terminal device 20 as the work item of the job performed by the user.

[0176] In addition, for example, when the processor 201 of the terminal device 20 reads code information (two-dimensional code, barcode, chameleon code, color bit, etc.) attached to the tool used in the work via the camera of the sensor 204, the processor 201 of the terminal device 20 may send the read code information to the server device 10. The determination unit 601 may also determine the work item of the work performed by the user based on the code information. For example, the determination unit 601 may also determine the work item of the work using the tool corresponding to the code.

[0177] In addition, for example, when the processor 201 of the terminal device 20 communicates with a short-distance communication device (RFID chip, NFC card, etc.) attached to a tool used in a task via the communication I / F 207, the processor 201 may transmit information about the tool attached with the short-distance communication device that communicated to the server device 10. The determination unit 601 may also determine the task item of the task performed by the user based on the information about the tool. For example, the determination unit 601 may also determine the task item of the task using the tool.

[0178] In the second and third embodiments described above, the determination unit 601 determines the workload of the user's work based on the user's heart rate. However, the determination unit 601 may determine the workload of the user's work in other ways.

[0179] For example, the determination unit 601 determines the work item of the work being performed by the user. Here, it is assumed that the correspondence information between the work item and the work load during a certain period of the work is pre-stored in the auxiliary storage device 103. The determination unit 601 may also determine the work load of the work being performed by the user by multiplying the work load during a certain period corresponding to the work item determined based on the correspondence information by the period during which the user continues the work.

[0180] In addition, for example, correspondence information between predetermined types of information (e.g., the location, time, user identification information, etc. of the job) and the workload is stored in advance in the auxiliary storage device 103. In this case, the determination unit 601 may obtain the predetermined types of information from the terminal device 20, and obtain the workload corresponding to the obtained information from the correspondence information as the workload of the job being performed by the user.

[0181] In addition, for example, the user's schedule is determined in advance, and the workload in each job is also determined in advance. In this case, the determination unit 601 may determine the workload of the job that the user is performing based on this information.

[0182] In addition, the determination unit 601 may also correct the workload based on weather information (temperature, humidity, illumination, WBGT value, UV index, wind speed, etc.), environmental information (gas concentration, radioactivity, photochemical oxidant concentration, etc.), etc. For example, if the WBGT value is greater than a predetermined value, the determination unit 601 may perform correction by multiplying the workload by a predetermined coefficient greater than 1. In addition, if the temperature is less than a predetermined value, the determination unit 601 may also perform correction by multiplying the workload by a predetermined coefficient less than 1.

[0183] In addition, for example, the determination unit 601 may receive a designation of a value of a workload of a job being performed by a user. For example, the determination unit 601 may receive a value of a workload inputted by a user in the terminal device 20 from the terminal device 20 .

[0184] In the fourth embodiment described above, the mobile body has a communication device that transmits a beacon signal, and the determination unit 601 determines the mobile body having the communication device that transmits the beacon signal as the user's means of movement when the terminal device 20 receives the beacon signal. However, the determination unit 601 may determine the user's means of movement in other ways.

[0185] For example, each mobile body may also have a communication device different from the communication device that sends the beacon signal. For example, each mobile body may also have a communication device such as an RFID tag or an NFC card. In this case, when the processor 201 of the terminal device 20 receives predetermined information from these communication devices via the communication I / F 207, it sends the received information to the server device 10. When receiving the information, the determination unit 601 may also determine the mobile body that has the communication device that sent the information based on the received information, and determine the determined mobile body as the user's means of movement.

[0186] In addition, for example, when the processor 201 of the terminal device 20 reads code information (two-dimensional code, barcode, chameleon code, color space, etc.) attached to the moving object via the camera of the sensor 204, the processor 201 of the terminal device 20 may send the read code information to the server device 10. The determination unit 601 may also determine the moving object to which the code is attached based on the code information, and determine the determined moving object as the user's means of movement.

[0187] In addition, for example, the determination unit 601 may determine the user's means of movement based on an image of the surroundings of the terminal device 20 captured by a camera of the terminal device 20, a camera possessed by the user, an external fixed camera, an internal camera of the moving object, etc. The determination unit 601 may also determine the moving object as the user's means of movement when at least a part of the moving object (e.g., the exterior, internal equipment (seat, steering wheel, etc.)) is recognized from the image of the surroundings of the terminal device 20.

[0188] In addition, for example, the determination unit 601 may determine the user's means of movement based on the sounds around the terminal device 20. For example, when the determination unit 601 recognizes a predetermined sound (engine sound, etc.) generated when the moving body moves based on the ambient sound around the terminal device 20 recorded by the microphone of the terminal device 20, the moving body may be determined as the user's means of movement.

[0189] In addition, for example, the determination unit 601 may specify the user's means of transportation based on the user's speed. For example, the determination unit 601 may also determine the speed of the terminal device 20 based on the time series change of the position information of the terminal device 20, and when the determined speed is above a predetermined threshold (for example, 30 km / h, etc.), determine the user's means of transportation as a predetermined moving body (for example, a car, a motorcycle).

[0190] Furthermore, the above-mentioned devices, programs, and methods may be implemented as separate devices or by using shared components in multiple devices, including various methods. In addition, it may be appropriately changed to be partly software and partly hardware. Furthermore, the invention also exists as a recording medium of the program of the control device. Of course, the recording medium of the program may be a magnetic recording medium or a semiconductor memory, and any recording medium developed in the future may be considered in exactly the same way.

[0191] Explanation of symbols

[0192] 1…detection system, 10…server device, 20…terminal device, 30…network, 101…processor, 102…main storage device, 103…auxiliary storage device, 104communication I / F, 201…processor, 202…main storage device, 203…auxiliary storage device, 204…sensor, 205…short-range wireless communication I / F, 206…UI unit, 207…communication I / F, 301…reference value table, 401…sensitivity table, 801…sensitivity table, 1001…sensitivity table, 1002…sensitivity table, 1201…reference value table, 1301…sensitivity table.

Claims

1. An information processing device, characterized in that: have: a determination unit that determines a user's means of movement; and A detection unit detects an abnormality of the user via a sensor provided at the user or around the user, using a determination criterion according to the moving means determined by the determination unit.

2. The information processing device according to claim 1, characterized in that The detection unit detects the abnormality based on the determination criterion that sets the sensitivity for detecting the abnormality predetermined for the moving means, that is, the abnormality in which erroneous detection is assumed to occur, to a threshold value or less.

3. The information processing device according to claim 1, characterized in that The detection unit detects the abnormal situation using the determination criterion that the sensitivity of detecting the abnormal situation predetermined by the moving means determined by the determination unit, that is, the abnormal situation where erroneous detection is assumed to occur, is lower than that of detecting a situation where erroneous detection is not assumed to occur.

4. The information processing device according to claim 1, characterized in that The detection unit detects the abnormal situation using the judgment standard that sets the sensitivity for detecting the abnormal situation predetermined for the moving means determined by the determination unit, that is, the abnormal situation that is expected to cause serious harm to the user, to be greater than a threshold value.

5. The information processing device according to claim 1, characterized in that The specifying unit specifies the moving object as the moving means when communication is performed between the device of the user and the device of the moving object.

6. The information processing device according to claim 1, characterized in that When the moving means determined by the determination unit is a predetermined moving body, the detection unit detects the abnormality via a sensor included in the moving body.

7. The information processing device according to any one of claims 1 to 6, characterized in that: The information processing device further includes an output control unit that outputs information of a warning regarding the abnormality detected by the detection unit to a predetermined output destination.

8. The information processing device according to claim 7, characterized in that: The output control unit outputs the warning information to the output destination according to the type of the abnormal situation detected by the detection unit.

9. An information processing method executed by an information processing device, characterized in that: The information processing method comprises the following steps: a step of determining the user's means of movement; and A step of detecting an abnormality of the user via a sensor provided at the user or around the user, using a determination criterion corresponding to the moving means determined in the determining step.

10. A program, characterized in that Used to make the computer perform the following steps: a step of determining the user's means of movement; and A step of detecting an abnormality of the user via a sensor provided at the user or around the user, using a determination criterion corresponding to the moving means determined in the determining step.

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