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 at least one of an item and a load of a job being performed by a user; and a detection unit that detects, via a sensor provided to the user or around the user, an abnormal situation of the user on the basis of a determination criterion corresponding to the at least one identified by the identification 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 perform work with fewer people. On the other hand, when there are fewer people, even if an abnormal situation such as a worker falls (tripping over something, falling due to poor physical condition, etc.) occurs, the possibility that other workers will not notice it increases. In particular, if a worker is injured and unable to move or loses consciousness due to a fall, there is a possibility of falling 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 are sometimes different from abnormal situations that are difficult to occur. 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 problems, and an object of the present invention is to contribute to improving 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 comprises: a determination unit, which determines at least one of the items and loads of the work being performed by the user; and a detection unit, which detects the abnormal situation of the user according to a judgment criterion corresponding to the at least one determined by the determination unit via a sensor equipped on the user or around the user.

[0012] Effects of the Invention

[0013] According to the present invention, it is possible to help improve the accuracy of abnormal situation detection. 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 refers to a fall. A drop refers to falling from a height. An impact refers to applying an acceleration above a certain value. Lying motionless refers to not moving in a fallen state. Fatigue refers to accumulated fatigue. A high heart rate refers to 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 random access memory (RAM) used for temporarily storing information, developing programs, 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 various abnormal situations such as falling, 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, a posture of lying on a table, a steering wheel, etc., a posture of being hung by a seat belt, etc.) so that 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. 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 obtained 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 refers to the scale of 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 the four values ​​of "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 second 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 work item of the work 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 make a correction. If the value of the index used for judging the abnormality is greater than the corrected reference value, it is detected as an abnormality. 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 an 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 this embodiment, the detection sensitivity is predetermined in such a way that the detection sensitivity for an abnormal situation predetermined as an abnormal situation assumed to be erroneously detected in an operation is set 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., 5 m) from the ground), work that involves lifting and lowering using step stools, etc. (harvesting, 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 (hammer operations), it is assumed that they are false detections of falls, and the sensitivity of fall detection is set to less than "weak".

[0046] In addition, when a situation that may be confused with an abnormal situation is likely to occur during operation, it is assumed that it is a false detection of an abnormal situation. Therefore, in this embodiment, the sensitivity of detection is predetermined in such a way that the sensitivity of detection of such an abnormal situation is set to be below a predetermined threshold value (for example, "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, or when the vehicle is started or stopped. This acceleration may be confused with the impact applied to the user. Therefore, it is assumed that the impact is detected by mistake. Therefore, in this embodiment, for operations such as operations using a hammer, farm tools, and operations moving in a vehicle that may cause a situation in which the user is subjected to an acceleration exceeding a certain level, the sensitivity of the 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, hammer work, harvesting work, and weeding work.

[0048] In addition, in the present embodiment, the sensitivity of detection is predetermined by setting the sensitivity of detection for abnormal situations that are predetermined as abnormal situations that are assumed to cause serious damage to the user during operation to a predetermined threshold value (for example, "weak", "standard", etc.) or more. Falling tends to cause serious damage to the user, so it is desirable to prevent undetected conditions 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 so as 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 orthogonal axes, 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 such as an environmental sensor (a sensor that detects wet bulb temperature, black globe temperature, dry bulb temperature, etc.) provided in the environment where the user operates, and a beacon that sends a signal indicating the position information. In the following, the signal indicating the position information sent by the beacon is set as a beacon signal. The processor 201 obtains the wet bulb temperature, black bulb temperature, and dry bulb temperature of the environment in which the user performs work 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 the user to input information, 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 (such as 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. In the following, the processing described mainly with the determination unit 601, the detection unit 602, and the output control unit 603 as the main body is actually the processing mainly performed by the processor 101.

[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 , the server device 10 performs a detection process of an abnormality of a user having the terminal device 20. When the processor 101 receives a start instruction of the detection process of an abnormality of a 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, it 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 inclination 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 the sensor 204 detects a signal exceeding the specified threshold, it 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 operation being performed by the user having the terminal device 20. In the present embodiment, the determination unit 601 determines the work item of the operation 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 abnormality from the reference value table 301. Then, the detection unit 602 obtains the value of the determined index. More specifically, the detection unit 602 is as follows.

[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 index value 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 an indicator value. In addition, the detection unit 602 requests the terminal device 20 to obtain 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 obtains 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 proceeds to step S104 .

[0071] In step S104, the detection unit 602 obtains the reference value corresponding to the selected abnormal situation from the reference value table 301. In addition, when the selected abnormal situation 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 situation determined in step S101. In addition, when the selected abnormal situation 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 according to 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, and information urging the user to respond to the occurrence of the abnormal situation.

[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 neglect to 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 under a criterion corresponding to the work items of the work being performed 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 abnormal situations that are predetermined as abnormal situations that may cause serious damage to the user in the work items being worked on by the user. Thus, the server device 10 can reduce the number of undetected abnormal situations.

[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 based on 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 will be described.

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

[0093] The workload is a scale indicating that a larger workload is associated with a larger workload, 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, the sensitivity of detection is determined to be equal to or less than a threshold value for a predetermined abnormal situation as an abnormal situation in which the workload value is assumed to be erroneously detected.

[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 relative to the value of the workload.

[0098] In addition, for the values ​​of the workload of the level below 25 and the level greater than 25 and below 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 cause of the increase in heart rate, so regardless of such a situation, the increased heart rate 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, it can also be set so that the greater the workload, the greater the sensitivity of the high heart rate detection.

[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 sensitivity of detection according to the value of the workload. The detection unit 602 may also, when the value of the workload is above a predetermined threshold for a period of time exceeding a predetermined threshold, set the risk of a work-related accident to be higher due to a decrease in the physical strength and judgment of the operator, and increase the sensitivity of detection to above the predetermined threshold for abnormal conditions other than "fatigue" and "high heart rate" (for example, falling, dropping, impact, lying still, etc.). For example, the detection unit 602 may also increase the sensitivity of detection to the standard for a situation where the sensitivity of detection in falling, dropping, impact, 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 S200 and S201 is replaced by the processing of steps S100 and S101.

[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 for 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 a certain interval (e.g., 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, 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 falsely detected, with respect to the workload of the work being performed by the user. Thus, the server device 10 can reduce false detection of the abnormal situation.

[0108] In addition, the server device 10 sets the detection sensitivity to a predetermined value or more for an abnormality that is predetermined as an abnormality that causes serious damage to the workload of the user's ongoing work. Thus, the server device 10 can reduce undetected abnormalities.

[0109] (Third Embodiment)

[0110] In the present embodiment, the server device 10 detects abnormality based on a determination 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 the determination criteria 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 the sensitivity for detecting a fall, a drop, an impact, and lying still. In addition, the sensitivity table 1002 is a table showing the correspondence between work load and the sensitivity for detecting fatigue and a 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 S300 and S301 is included instead of the processing of steps S100 and S101.

[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 this embodiment, the server device 10 can contribute to improving the accuracy of abnormality detection by detecting abnormalities based on the judgment 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.) being used by the user tilts to a certain degree or more and may fall. In the present embodiment, the moving body that can be used by the user 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 includes an index and a reference value about the abnormal situation of the vehicle body overturning. The index for detecting the inclination of the moving body is the inclination of the moving body detected by the inclination 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 carts, 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 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 assumed to cause erroneous detection during operation becomes 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 cycling, it is not assumed that the user has fallen or tripped. Therefore, when the user's means of movement is other than walking or cycling, 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 cycling is determined to be less than a predetermined value ("weak" in this embodiment). Fig.13 In the example, for passenger carts, cars, motorcycles, trucks, forklifts, tractors, and torpedo vehicles, false detections of falls and drops are not assumed, and the sensitivity of fall and drop detection is set to "weak" or below.

[0132] In addition, when a situation that may be confused with an abnormal situation is likely to occur during operation, it is assumed that the abnormal situation is 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 detected by mistake. Therefore, in this embodiment, for means of movement other than walking, the sensitivity of the impact detection is set to be below a predetermined threshold. Fig.13 In the example, for bicycles, passenger carts, cars, 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 detection sensitivity is predetermined in such a way that the detection sensitivity for abnormal situations that are predetermined as abnormal situations that are assumed to cause serious damage to the user during operation is above 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 performs an undesired action and causes an accident, causing 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 cart, 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 replaced by 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 is equipped with 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 equipped on 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 equipped with 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] In step S103 of the present embodiment, when the user's means of movement is a predetermined mobile body, 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 to the 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 means of movement is a predetermined moving body, the detection unit 602 detects an abnormality based on a signal detected by a sensor provided to the moving body. In the present embodiment, the detection unit 602 acquires 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 acquired value.

[0147] In step S103, when the user's means of movement is a predetermined moving body, the detection unit 602 obtains the abnormality 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 in a 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 on the steering wheel, etc.) without moving. Then, the detection unit 602 detects lying still using the value of the obtained 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 (e.g., 3 seconds, 5 seconds, etc.), the detection unit 602 outputs information indicating a warning for dangerous driving to a predetermined output destination (e.g., 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 is using 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 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 abnormal situations that are predetermined for the user's means of movement as abnormal situations that may cause serious damage to the user. Thus, the server device 10 can reduce undetected abnormal situations.

[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, 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 (e.g., 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 the abnormal situation: fatigue. However, other indicators may be used as indicators for detecting the abnormal situation: fatigue. For example, the stress value of the user may be used as an indicator for detecting the abnormal situation: fatigue. Here, the stress value refers to an indicator value that is higher as it is estimated that the user feels stressed. It is known that the more stressed the user feels, the more activated the sympathetic nerves become.

[0159] Therefore, for example, the detection unit 602 may also estimate the degree of activation 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 heartbeat changes. The power spectrum density includes a high-frequency variation component (HF component) and a low-frequency component (LF component). The detection unit 602 respectively calculates the value of the sum of the intensities of the LF component area (0.05 Hz to 0.15 Hz) and the HF component area (0.15 Hz to 0.40 Hz), and uses it as the value of the LF component and the value of the HF component. Then, the detection unit 602 can calculate (the value of the LF component) / (the value of the HF component) as the pressure value.

[0160] In a relaxed state, i.e., when the parasympathetic nerves are activated, 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, i.e., when the sympathetic nerves are activated, 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 heartbeat sensor for detecting the heartbeat 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 detection of an abnormal situation that is predetermined for any one of the work items, work load, and user's means of movement of the user, and is assumed to be a false detection, to below a predetermined threshold. However, the server device 10 may also set the sensitivity of detection of an abnormal situation that is predetermined for any one of the work items, work load, and user's means of movement of the user, and is assumed to be a false detection, as follows. That is, the server device 10 may also make the sensitivity of detection of the abnormal situation lower than the situation where the abnormal situation is not assumed to be a false detection. For example, the server device 10 may also make the sensitivity of detection of a false detection of a work item assumed to be a fall: a fall in a clerical work lower than the sensitivity of detection of a false detection of a work item not assumed to be a fall: a fall in an aerial work.

[0163] In addition, in each of the above-mentioned embodiments, the output control unit 603 outputs warning information for the 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 output warning information 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 below 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 below 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 below the threshold. In addition, the output control unit 603 may also accept a response indicating that the warning has been confirmed 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 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 any one of the means of movement of the user. However, the server device 10 may detect the abnormality of the user based on a judgment criterion corresponding to both at least one of the work item and the work load of the work being performed by the user and the means of movement of the user.

[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 bicycle, and may update the sensitivity of a predetermined abnormal situation (e.g., stumbling, falling, etc.) to below a predetermined threshold when the determined means of movement is a vehicle or a work vehicle. In addition, the detection unit 602 may determine the user's means of movement according to a predetermined period, and update the sensitivity of detection of abnormal situations according to 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 around 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 correspondence information of the work item. For example, when the work item of the work performed by the user is determined according to 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 input of the work item from the user via the UI unit 206 (touch input, voice input, gesture input, etc.), 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 space, etc.) attached to a 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 the operation via the communication I / F 207, the processor 201 may transmit information of the tool attached with the short-distance communication device that communicated to the server device 10. The determination unit 601 may also determine the operation item of the operation performed by the user based on the information of the tool. For example, the determination unit 601 may also determine the operation item of the operation 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 job being performed by the user. Here, it is assumed that the correspondence information between the work item and the work load of the job within a certain period is pre-stored in the auxiliary storage device 103. The determination unit 601 may also determine the work load of the job being performed by the user by multiplying the work load within a certain period corresponding to the work item determined based on the correspondence information by the period during which the user continues the job.

[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 pre-stored 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 above a predetermined value, the determination unit 601 may correct the workload by multiplying the workload by a predetermined coefficient greater than 1. In addition, if the temperature is below a predetermined value, the determination unit 601 may correct the workload 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, the mobile body is provided with a communication device that transmits a beacon signal, and the determination unit 601 determines the mobile body provided with 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 a 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 belts, steering wheels, 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 determine the user's means of movement 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 obtained speed is above a predetermined threshold (for example, 30 km / h, etc.), determine the user's means of movement as a predetermined moving body (for example, a car, a motorcycle).

[0190] Furthermore, the above 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 one part being software and one part being hardware. Moreover, the invention is also established even if it is a recording medium of a program for a 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] Description of Reference Numerals

[0192] 1…Detection system, 10…Server device, 20…Terminal device, 30…Network, 101…Processor, 102…Main storage device, 103…Auxiliary storage device, 104…Communication 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: The information processing device comprises: a determination unit that determines at least one of a project and a load of a job being performed by a user; as well as A detection unit detects an abnormality of the user according to a determination criterion corresponding to the at least one determined by the determination unit via a sensor provided at the user or around the user.

2. The information processing device according to claim 1, characterized in that The detection unit detects the abnormality according to a criterion in which a sensitivity for detecting the abnormality that is predetermined for the at least one identified by the identification unit and is assumed to be erroneously detected is set to be less than a threshold value.

3. The information processing device according to claim 1, characterized in that The detection unit detects the abnormality according to a criterion that sets a sensitivity for detecting the abnormality predetermined for the at least one determined by the determination unit and assumed to be erroneously detected to be lower than that for detecting the abnormality not assumed to be erroneously detected.

4. The information processing device according to claim 1, characterized in that The detection unit detects the abnormality according to a criterion in which a sensitivity for detecting the abnormality that is predetermined for the at least one determined by the determination unit and is assumed to cause serious damage to the user is set to be greater than a threshold.

5. The information processing device according to claim 1, characterized in that The determination unit determines the at least one based on a location of the user.

6. The information processing device according to claim 1, characterized in that The identification unit acquires a predetermined type of information, and identifies the at least one based on the acquired information and correspondence information between the predetermined type of information and an item or load of work.

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: A determining step of determining at least one of a project and a load of a job being performed by a user; and The detection step detects an abnormality of the user according to a judgment criterion corresponding to the at least one determined in the determination step via a sensor provided at the user or around the user.

10. A program, characterized in that The program is used to make the computer execute the following steps: A determining step of determining at least one of a project and a load of a job being performed by a user; as well as The detection step detects an abnormality of the user according to a judgment criterion corresponding to the at least one determined in the determination step via a sensor provided at the user or around the user.

Images