JP2017027414A - Server device, life log system and caution information output method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technology which alleviates an influence of an accident by a simple method.SOLUTION: A safe driving support device 100 receives life log data from a life log sensor 300 of a portable telephone terminal 200, receives operational behavior data from a telematics device 400 of a mobile body 400M, and receives accident data from an insurance server 500. By using the life log data, the operational behavior data and the accident data, the safe driving support device specifies the degree of risk in the case of a living body drives a vehicle, and provides caution information for avoiding an accident to the portable telephone terminal 200 and the telematics device 400.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a server device, a life log system, and an attention information output method.

  Patent Document 1 discloses that “equipped with a body data collecting unit that is mounted on a vehicle and collects body data of the vehicle occupant, and based on the body data collected by the body data collection unit, A health management support system including a vehicle-mounted device for diagnosing a condition, the computer including a computer device that is external to the vehicle and that executes an application relating to health management using physical data of a user, the vehicle-mounted device including the computer Communication means capable of exchanging data with the device; estimation means for estimating the state of the occupant based on physical data collected by the physical data collection means; and the estimation means estimated by the estimation means Depending on the state of the occupant, at least a question about the state is output as a voice and an answer is received from the occupant for that question. And interactive means for collecting at least data relating to the state of the occupant, and based on the body data collected by the physical data collection means and the data concerning the state of the occupant collected by the interactive means, A health management support system characterized by diagnosing the health condition of an occupant and sharing at least physical data collected by the physical data collecting means with the computer device via the communication means " ing.

JP 2012-24482 A

  In the above technique, health data during driving of the driver is acquired, the health state of the driver is estimated, and the degree of danger is detected. However, health data acquired in a state other than driving is not taken into consideration, and it has not always been highly effective in mitigating the effects of accidents.

  An object of the present invention is to provide a technique for mitigating the influence of an accident by a simpler method.

  The present application includes a plurality of means for solving at least a part of the above-described problems. Examples of such means are as follows. In order to solve the above-described problem, the server device according to the present invention includes a life log data processing unit that receives biological state information that is information indicating the state of a living body, and the living body drives a vehicle using the biological state information. And a caution information providing unit for specifying the risk level and providing caution information.

  In the server device, the information indicating the state of the living body may be information related to sleep of the living body.

  Further, in the server device, the caution information providing unit specifies the risk level using the biological state information and the biological state information of the parties to the traffic accident on the day before the occurrence of the traffic accident. It may be a thing.

  Further, in the server device, the caution information providing unit has caused the traffic accident in a predetermined period before the occurrence of the traffic accident and the biological state information of the party of the traffic accident on the day before the occurrence of the traffic accident. The degree of risk may be specified using driving behavior information indicating the behavior of the vehicle and the biological state information.

  The server device includes an insurance premium calculation unit that discounts the automobile insurance premium according to a combination of the predetermined classification using the biological state information, the type of driving license, and the age group. It may be.

  The life log system according to the present invention is a life log system including a server device and a client device, wherein the server device receives life state data that is information indicating a state of a living body. And a caution information providing unit that specifies a degree of danger when the living body drives a vehicle using the biological state information and provides caution information, and the client device sets the biological state information to a predetermined value. An operation information management unit that acquires from the external device and transmits to the server device, and a caution information output control unit that displays the danger level and the caution information provided from the server device Good.

  The communication information output method according to the present invention is a caution information output method for executing a procedure of outputting caution information using a computer, and the control means provided in the computer is information indicating a state of a living body. A life log data processing step for receiving biological state information; and a caution information providing step for specifying a degree of danger when the biological body drives a vehicle using the biological state information and providing caution information. There may be.

  According to the present invention, it is possible to provide a technique for mitigating the influence of an accident by a simpler method.

  Problems, configurations, and effects other than those described above will become apparent from the following description of embodiments.

It is a figure which shows the outline | summary of a structure of the life log insurance system which concerns on embodiment. It is a block diagram of the life log insurance system which concerns on embodiment. It is a figure which shows the data structure stored in a customer master memory | storage part. It is a figure which shows the data structure stored in a life log memory | storage part. It is a figure which shows the data structure stored in a driving behavior data storage part. It is a figure which shows the data structure stored in an accident data storage part. It is a figure which shows the data structure stored in an analysis result log | history memory | storage part. It is a figure which shows the hardware structural example of a safe driving assistance apparatus. It is a figure which shows the hardware structural example of a mobile telephone terminal. It is a figure which shows the flow of attention information specific processing. It is a figure which shows the flow of a driving | operation prediction process. It is a figure which shows the example of a classification tree. It is a figure which shows the example of a caution information display screen (the 1). It is a figure which shows the example of a caution information display screen (the 2). It is a figure which shows the example of a caution information display screen (the 3). It is a figure which shows the example of a caution information display screen (the 4). It is a figure which shows the flow of a risk group classification | category process. It is a figure which shows the example of the classification tree of a risk group. It is a figure which shows the flow of a renewal premium calculation process. It is a figure which shows the example of a renewal premium calculation screen.

  Hereinafter, an embodiment using a life log insurance system 1 to which an embodiment according to the present invention is applied will be described with reference to the drawings.

  FIG. 1 is a diagram illustrating a configuration example of a life log insurance system 1 to which an embodiment of the present invention is applied. A user provides life log information at an arbitrary timing using the life log insurance system 1 and obtains a discount calculation of attention information or insurance premiums. In the life log insurance system 1 assumed in the present embodiment, the safe driving support device 100 provided in the data center 100D, the mobile phone terminal 200, the telematics device 400 provided in the moving body 400M, and the insurance server device 500 are provided. And are included. Although the life log sensor 300 is communicably connected to the mobile phone terminal 200, the life log sensor 300 can also be communicably connected to the telematics device 400. The safe driving support device 100 can communicate with each of the mobile phone terminal 200, the telematics device 400, and the insurance server device 500 via the network 50.

  However, the present invention is not limited to this, and the safe driving support device 100, the mobile phone terminal 200, and the telematics device 400 are not connected to each other by the network 50 so as to be communicable with each other, but are realized by the same device. May be. Further, the exchange of data among the mobile phone terminal 200, the telematics device 400, and the safe driving support device 100 may be performed via a nonvolatile storage medium.

  Here, the safe driving support device 100 is, for example, a so-called server device. However, the present invention is not limited to this, and the safe driving support apparatus 100 may be various information processing apparatuses such as a personal computer, a smartphone, a workstation, a PDA (Personal Data Assistant), and a tablet device.

  The mobile phone terminal 200 is, for example, a so-called mobile phone or a wireless communication device. However, the present invention is not limited to this, and the mobile phone terminal 200 includes various information processing devices such as a personal computer, a smartphone, a workstation, a PDA, a tablet device, a GPS (Global Positioning System) / GLONASS (Global Navigation System System) logger device, and a smart watch. It may be.

  In this system, the user basically inputs and outputs to the telematics device 400. In addition, when the telematics device 400 and the safe driving support device 100 communicate with each other via the network 50, a predetermined protocol (for example, a mobile phone, Bluetooth (registered trademark), wireless LAN, NFC (Near Field communication) is used. , RFID (Radio Frequency Identifier), etc.) are communicably connected to each other via a wireless communication path.

  The telematics device 400 receives satellite radio waves (for example, radio waves such as GPS or GLONASS) at a predetermined timing, and measures the distance between the telematics device 400 and the satellites and the rate of change of distance for three or more satellites. Thus, the current location, traveling speed, traveling direction, and time of the telematics device 400 are specified, and the position and the like are recorded in the storage unit in association with the specified date.

  The network 50 is a communication network such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, and a mobile phone network. It may be a VPN (Virtual Private Network) on a wireless communication network such as a mobile phone communication network.

  FIG. 2 is a block diagram of the life log insurance system 1 according to the embodiment.

  The safe driving support device 100 includes a control unit 110, a storage unit 120, and a communication unit 130. The control unit 110 includes a life log data processing unit 111, a driving behavior data processing unit 112, an accident data processing unit 113, a data correlation analysis unit 114, a caution information providing unit 115, and a driving diagnosis information providing unit 116. And an insurance premium discount calculation unit 117. The storage unit 120 includes a customer master storage unit 121, a life log storage unit 122, a driving behavior data storage unit 123, an accident data storage unit 124, and an analysis result history storage unit 125.

  When the life log data is received, the life log data processing unit 111 performs name identification for each customer, and stores and manages information indicating a biological state for each customer in time series.

  When the driving behavior data processing unit 112 receives data indicating the behavior of the vehicle accompanying driving of the vehicle, the driving behavior data processing unit 112 integrates the data for each combination of the telematics device 400 and the customer, and indicates the behavior of the vehicle for each combination of the telematics device 400 and the customer. Store and manage information in time series.

  The accident data processing unit 113 integrates data for each combination of the insurance non-life insurance company for which the insurance money was paid and the customer when the data indicating the accident details of the vehicle is received, and the non-life insurance company that provided the insurance money for the accident. Information indicating the accident contents for each combination of customers is stored and managed in time series. In this context, insurance premium refers to the amount of money paid by an insurance policyholder to an insurance company in order to take out insurance such as non-life insurance, and insurance money refers to damage caused by accidents by an insurance company such as non-life insurance. The amount of money paid to the insured for the main purpose of compensation.

  The data correlation analysis unit 114 analyzes the correlation among life log data, driving behavior data, and accident data. In addition, the data correlation analysis unit 114 uses the correlation having a certain level or more obtained by the correlation analysis, and an accident related to the current value of the life log data and a life log necessary for avoiding the accident. Identify improvements in the data as caution information.

  Upon receiving the attention information from the data correlation analysis unit 114, the attention information providing unit 115 transmits the attention target life log data to the telematics device 400 that has transmitted the attention information.

  When the driving diagnosis information providing unit 116 receives the caution information and the life log data from the data correlation analysis unit 114, the driving diagnosis information providing unit 116 generates output information according to a format of a life log diagnosis document, which will be described later, and transmits the life log data to be cautioned To the telematics device 400.

  The premium discount calculation unit 117 uses life log data and driving behavior data to classify the risk level of the user into a predetermined group, and further increase or decrease the premium depending on the license type and age group Identify rates.

  The storage unit 120 includes a customer master storage unit 121, a life log storage unit 122, a driving behavior data storage unit 123, an accident data storage unit 124, and an analysis result history storage unit 125.

  FIG. 3 is a diagram illustrating a data structure stored in the customer master storage unit 121. In the customer master storage unit 121, a customer identifier 121A, a name 121B, a gender 121C, a date of birth 121D, a sensor identifier 121E, a telematics identifier 121F, and a subscription insurance 121G are stored in association with each other. ing.

  The customer identifier 121A is information for identifying a customer who is a user of the life log insurance system 1. The name 121B is information for specifying the name of the customer specified by the customer identifier 121A. The sex 121C is information for specifying the sex of the customer specified by the customer identifier 121A. The date of birth 121D is information for specifying the date of birth of the customer specified by the customer identifier 121A. The sensor identifier 121E is information for specifying the life log sensor 300 used by the customer specified by the customer identifier 121A. The telematics identifier 121F is information for specifying the telematics device 400 used by the customer specified by the customer identifier 121A. The non-life insurance 121G is information for specifying non-life insurance to which the customer specified by the customer identifier 121A is subscribed, such as an insurance contract number.

  FIG. 4 is a diagram illustrating a data structure stored in the life log storage unit 122. The life log storage unit 122 includes a sensor identifier 122A, a name 122B, a date 122C, a body temperature 122D, a heart rate 122E, an acceleration 122F, an exercise intensity 122G, a bedtime 122H, a wake-up time 122J, and a step count. 122K is stored in association with each other.

  The sensor identifier 122A is information for specifying the life log sensor 300. The name 122B is information for specifying the name of the user of the sensor specified by the sensor identifier 122A. The date and time 122C is information for specifying the date and time measured by the sensor specified by the sensor identifier 122A. The body temperature 122D is information for specifying the body temperature measured by the sensor specified by the sensor identifier 122A. The heart rate 122E is information for specifying the heart rate measured by the sensor specified by the sensor identifier 122A. The acceleration 122F is information for specifying the acceleration measured by the sensor specified by the sensor identifier 122A. The exercise intensity 122G is information for specifying the exercise intensity measured by the sensor specified by the sensor identifier 122A. The bedtime 122H is information for specifying the bedtime measured by the sensor specified by the sensor identifier 122A. The wake-up time 122J is information for specifying the wake-up time measured by the sensor specified by the sensor identifier 122A. The step count 122K is information for specifying the step count measured by the sensor specified by the sensor identifier 122A.

  The life log storage unit 122 only needs to store information measured by the life log sensor 300, and is not necessarily limited to the measurement items described above.

  FIG. 5 is a diagram illustrating a data structure stored in the driving behavior data storage unit 123. The driving behavior data storage unit 123 includes a telematics identifier 123A, a customer identifier 123B, a departure date and time 123C, a stop date and time 123D, a position 123E, an altitude 123F, an acceleration 123G, a speed 123H, and an accelerator opening 123J. The continuous operation time 123K is stored in association with each other.

  The telematics identifier 123A is information that identifies the telematics device 400 used by the customer. The customer identifier 123 </ b> B is information that identifies a customer who is a user of the life log insurance system 1. The departure date and time 123C is information for specifying the date and time when the driving of the vehicle is started. The stop date and time 123D is information for specifying the date and time when the driving of the vehicle is finished. The position 123E is information for specifying the position where the driving behavior is measured. The altitude 123F is information for specifying the altitude at the position where the driving behavior is measured. The acceleration 123G, the speed 123H, and the accelerator opening 123J are information for specifying the acceleration, the speed, and the accelerator opening measured as the driving behavior, respectively. Note that the driving behavior is not limited to acceleration, speed, and accelerator opening, and may include various measurable items such as steering angle, centrifugal force, and front / rear weight ratio. The continuous driving time 123K is information for specifying the time during which driving is continued without taking a break.

  FIG. 6 is a diagram illustrating a data structure stored in the accident data storage unit 124. The accident data storage unit 124 stores a non-life insurance company 124A, a customer identifier 124B, a name 124C, an accident date 124D, an accident content 124E, a negligence 124F, and a payment insurance 124G in association with each other. ing.

  The non-life insurance company 124A is information for specifying the non-life insurance company of the insurance applied in the event of an accident. The customer identifier 124B is information for identifying a customer who is a user of the life log insurance system 1. The name 124C is information for specifying the name of the customer specified by the customer identifier 124B. The accident date 124D is information for specifying the date and time when the accident occurred. The accident content 124E is information for specifying the content of the accident. The negligence degree 124 </ b> F is information that specifies the percentage of negligence that the customer specified by the customer identifier 124 </ b> B bears regarding the accident. Insurance payment 124G is information for specifying the amount of insurance money paid by non-life insurance company 124A.

  FIG. 7 is a diagram illustrating a data structure stored in the analysis result history storage unit 125. The analysis result history storage unit 125 stores a customer identifier 125A, a name 125B, an analysis date and time 125C, a health condition 125D, a driving suitability 125E, and caution information 125F in association with each other.

  The customer identifier 125 </ b> A is information for identifying a customer who is a user of the life log insurance system 1. The name 125B is information for specifying the name of the customer specified by the customer identifier 125A. The analysis date and time 125C is information for specifying the date and time of analysis. The health state 125D is information for specifying the health state. The driving suitability 125E is predetermined index information that specifies the degree to which the customer specified by the customer identifier 125A can drive safely when driving. The attention information 125F is information that specifies attention information for the customer specified by the customer identifier 125A.

  The communication unit 130 communicates with other devices such as the telematics device 400 via the network 50.

  The mobile phone terminal 200 can perform voice communication with other mobile phone terminals via a voice line. The mobile phone terminal 200 includes a control unit 210, a display unit 220, and a communication unit 230. The control unit 210 can connect to the life log sensor 300 and receive life log information. The control unit 210 also uploads life log data to the safe driving support apparatus 100 or a predetermined server apparatus on the Internet, generates screen information, acquires a website provided by the Web server by browser application software, and the like. The communication is controlled via the communication unit 230.

  The display unit 220 outputs display information. The communication unit 230 communicates with other devices connected to the network 50.

  The life log sensor 300 is a sensor device that acquires biological information. The life log sensor 300 has a function of measuring and calculating body temperature, heart rate, acceleration, exercise intensity, bedtime, wake-up time, and number of steps as biological information. Note that the calculated biological information is not limited to these, and may be, for example, meal time, weight, position, and the like. Further, the life log sensor 300 sends the measured or calculated biological information to other devices connected by wire or wireless.

  The telematics device 400 is a so-called car navigation device or in-vehicle device. The telematics device 400 has functions such as so-called route guidance for guiding a route to a set destination, and reporting the occurrence and position of an accident by a predetermined reporting means when an accident occurs.

  The telematics device 400 includes a control unit 410, a display unit 420, and a communication unit 430. The control unit 410 includes at least a driving information management unit 411 and a caution information output control unit 412.

  The driving information management unit 411 manages driving information. Specifically, the driving information management unit 411 acquires and records the driving behavior of the vehicle on which the telematics device 400 is mounted, and transmits the acquired driving behavior information to a predetermined other device via the communication unit 430. Send. For example, the driving information management unit 411 acquires information on each item included in the driving behavior data storage unit 123 from a unique sensor or a sensor attached to the vehicle, and transmits the information to the safe driving support device 100.

  The caution information output control unit 412 controls the output of caution information. The caution information is information including a message about a point to be paid attention to the driver of the vehicle on which the telematics device 400 is mounted.

  The display unit 420 outputs display information. The communication unit 430 communicates with other devices connected to the network 50.

  The insurance server device 500 is a server device provided by an insurance company. The insurance server device 500 includes at least a control unit 510, a storage unit 520, and a communication unit 530. The control unit 510 generates screen information for performing various applications and procedures such as provision of an estimate of non-life insurance subscription, provision of an update estimate, contract change, cancellation, and payment.

  The storage unit 520 stores various types of information. The communication unit 530 communicates with other devices connected to the network 50.

  FIG. 8 is a diagram illustrating a hardware configuration example of the safe driving support apparatus 100. The safe driving support device 100 includes at least an arithmetic device 102, an external storage device 103, a main storage device 104, an output device 105, a communication device 106, and a bus 107 that connects the devices. In addition, the safe driving support device 100 includes an input device 101.

  The arithmetic device 102 is an arithmetic device such as a CPU (Central Processing Unit).

  The external storage device 103 is a non-volatile storage device such as a so-called hard disk (Hard Disk Drive), SSD (Solid State Drive) or flash memory capable of storing digital information.

  The main storage device 104 is a memory device such as a RAM (Random Access Memory).

  The output device 105 is a display device such as a liquid crystal display or an organic EL (Electro Luminescence) display.

  The communication device 106 is a device such as a network card that establishes a communication path with other devices such as the telematics device 400 via the network 50 and transmits and receives information.

  The input device 101 is various input devices such as a keyboard, a mouse, and a touch panel.

  The input device 101, the arithmetic device 102, the external storage device 103, the main storage device 104, the output device 105, and the communication device 106 are connected to each other by a connecting conductor such as a bus 107.

  The life log data processing unit 111, the driving behavior data processing unit 112, the accident data processing unit 113, the data correlation analysis unit 114, the caution information providing unit 115, and the driving diagnosis information providing unit of the safe driving support device 100 described above. 116 and the insurance premium discount calculation unit 117 are realized by a program that causes the computing device 102 to perform processing. The program is stored in the main storage device 104, the external storage device 103, or a ROM device (not shown), loaded onto the main storage device 104 for execution, and executed by the arithmetic device 102.

  Further, the storage unit 120 of the safe driving support device 100 is realized by the main storage device 104 and the external storage device 103. Further, the communication unit 130 of the safe driving support device 100 is realized by the communication device 106. The above is the hardware configuration example of the safe driving support apparatus 100. The insurance server device 500 also has a configuration substantially similar to the hardware configuration example shown in FIG.

  FIG. 9 is a diagram illustrating a hardware configuration example of the mobile phone terminal 200. The mobile phone terminal 200 includes an arithmetic device 201, a main storage device 202, an external storage device 203, a satellite radio wave reception device 204, a communication device 205, an input / output device 206, and a bus 207 that connects the devices. At least.

  The arithmetic device 201 is an arithmetic device such as a CPU, for example.

  The main storage device 202 is a memory device such as a RAM, for example.

  The external storage device 203 is a non-volatile storage device such as a so-called hard disk, SSD, or flash memory that can store digital information.

  The satellite radio wave reception device 204 receives radio waves from a satellite by GPS or GLONASS or both, and specifies the position of the mobile phone terminal 200 by coordinates.

  The communication device 205 is a device such as a network module that establishes a communication path with other devices such as the safe driving support device 100 via the network 50 and transmits and receives information.

  The input / output device 206 includes, for example, a display device such as a liquid crystal display or an organic EL display, and various input devices such as a touch panel attached to or incorporated in the display device and receiving a touched position as an input. And a device responsible for output processing.

  The arithmetic device 201, the main storage device 202, the external storage device 203, the satellite radio wave reception device 204, the communication device 205, and the input / output device 206 are connected to each other by a connecting conductor such as a bus 207.

  The control unit 210 of the mobile phone terminal 200 described above is realized by a program that causes the arithmetic device 201 to perform processing. This program is stored in the main storage device 202, the external storage device 203, or a ROM device (not shown), loaded onto the main storage device 202 for execution, and executed by the arithmetic unit 201.

  The display unit 220 of the mobile phone terminal 200 is realized by the input / output device 206. The communication unit 230 of the mobile phone terminal 200 is realized by the communication device 205. The above is the hardware configuration example of the mobile phone terminal 200. The telematics device 400 also has a configuration that is substantially the same as the hardware configuration example shown in FIG. Further, the life log sensor 300 has substantially the same configuration as the hardware configuration example shown in FIG. 9, but includes various body temperature measurement temperature sensors, heart rate measurement pulse sensors, acceleration measurement acceleration sensors, and the like. The difference is that a plurality of various sensors are provided.

  The configurations of the safe driving support device 100, the mobile phone terminal 200, the life log sensor 300, the telematics device 400, and the insurance server device 500 can be classified into more components according to the processing content. Moreover, it can also classify | categorize so that one component may perform more processes.

  Each control unit may be constructed by hardware (ASIC, GPU, etc.). Further, the processing of each control unit may be executed by one hardware, or may be executed by a plurality of hardware.

  [Description of Operation] Next, the operation of the life log insurance system 1 in this embodiment will be described.

  FIG. 10 is a diagram illustrating a flow of the attention information specifying process. In the attention information specifying process, the safe driving support device 100 receives life log data from the mobile phone terminal 200 and receives driving behavior data from the telematics device 400. And the safe driving assistance apparatus 100 receives accident data from the insurance server apparatus 500. Then, using the driving behavior data and the accident data, the correlation between the accident occurrence content and the driving behavior is analyzed, and the safe driving support device 100 determines the correlation between the correlation obtained by the analysis and the life log data. Detect associations. When the association is detected, the safe driving support apparatus 100 identifies items on the life log data that break the association and the amount to be changed, and determines the caution information.

  First, when receiving the life log data from the life log sensor 300, the mobile phone terminal 200 transmits the life log data to the safe driving support device 100 (step S101). Specifically, when the control unit 210 receives the life log data transmitted from the life log sensor 300, the control unit 210 transmits the life log data to the safe driving support apparatus 100 via the communication unit 230.

  Upon receiving the life log data, the safe driving support device 100 stores the life log data (step S102). Specifically, upon receiving life log data from the mobile phone terminal 200, the life log data processing unit 111 stores the life log data in the life log storage unit 122.

  When measuring the driving behavior data, the telematics device 400 transmits the driving behavior data to the safe driving support device 100 (step S103). Specifically, when the driving information management unit 411 measures the driving behavior of the vehicle via various sensors, the driving behavior data is transmitted to the safe driving support device 100 via the communication unit 230.

  Upon receiving the driving behavior data, the safe driving support device 100 stores the driving behavior data (step S104). Specifically, when the driving behavior data processing unit 112 receives the driving behavior data from the telematics device 400, the driving behavior data processing unit 112 stores the driving behavior data in the driving behavior data storage unit 123.

  The insurance server device 500 transmits accident data to the safe driving support device 100 (step S105). Specifically, control unit 510 transmits accident data stored in storage unit 520 to safe driving support apparatus 100 via communication unit 530.

  Upon receiving the accident data, the safe driving support device 100 stores the accident data (step S106). Specifically, upon receiving accident data from the insurance server device 500, the accident data processing unit 113 stores the accident data in the accident data storage unit 124.

  Then, the safe driving support device 100 analyzes the correlation and determines the caution information (step S107). Specifically, the data correlation analysis unit 114 uses the life log data, the driving behavior data, and the accident data to determine the life log data and the occurrence of the accident and the occurrence of the accident based on the date and time of each data and the common party relationship. Analyze the correlation of the driving behavior that causes it. In addition, the data correlation analysis unit 114 uses the correlation having a certain level or more obtained by the correlation analysis, and an accident related to the current value of the life log data and a life log necessary for avoiding the accident. Identify improvements in the data as caution information. In the processing, when there is an item deviating from the normal value of the user who provided life log data described later, the correlation related to the item is used. In the present embodiment, the caution information is the content that informs the user of excess or deficiency of data items that have a strong causal relationship with the occurrence of the accident among the life log data common to the driving behavior that tends to cause the accident. That is, for example, assuming that a short sleep time has a strong causal relationship with the occurrence of an accident, the data correlation analysis unit 114 determines that the sleep time is insufficient when the sleep time of the received life log data is shorter than normal. A message prompting to supplement is specified as caution information.

  Then, the attention information providing unit 115 transmits the attention information to the mobile phone terminal 200 and the telematics device 400 (step S108). Then, the caution information providing unit 115 records information such as caution information as a history in the analysis result history storage unit 125.

  Then, the display unit 220 of the mobile phone terminal 200 configures and outputs screen information to be displayed for the transmitted caution information (step S109).

  Further, the caution information output control unit 412 of the telematics device 400 instructs the display unit 420 to configure and output screen information to be displayed for the transmitted caution information (step S110).

  The above is the flow of the attention information specifying process. According to the caution information specifying process, caution points assumed from the life log data can be presented before the start of driving or shortly after the start of driving. Therefore, it is possible to recognize at a time close to the driving start time what the driver should pay attention to when driving, and to be aware of safe driving.

  FIG. 11 is a diagram illustrating a flow of the operation prediction process. The driving prediction process is started after the correlation analysis is completed in step S107 of the attention information specifying process. The biological state information of the parties to the traffic accident on the day before the occurrence of the traffic accident, driving behavior information indicating the behavior of the vehicle that caused the traffic accident in a predetermined period before the occurrence of the traffic accident, the biological state information, Use to identify the risk

  First, the data correlation analysis unit 114 reads the classification tree from the storage unit 120 (not shown) (step S201). The classification tree has, for example, a three-layer hierarchical structure as shown in FIG. 12, and is tree-structured data having a branch for each item of biometric information included in the life log data. The classification tree is specified and configured based on a correlation derived using life log data, driving behavior data, and accident data.

  Then, the data correlation analysis unit 114 performs determination of the first layer of the classification tree and reading of the determination contents of the second layer (step S202). Specifically, the data correlation analysis unit 114 performs the determination by reading the determination items of the first layer and the determination criteria and matching them with the life log data. And the item relevant to the result of determination among the items of the second layer to be read next is specified and read.

  Then, the data correlation analysis unit 114 performs determination of the second layer of the classification tree and reading of the determination contents of the third layer (step S203). Specifically, the data correlation analysis unit 114 performs the determination by matching the determination items of the second layer, the determination criteria, and the life log data. And the item relevant to the result of determination among the items of the third layer to be read out next is specified and read out.

  Then, the data correlation analysis unit 114 determines the third layer of the classification tree and specifies the risk level (step S204). Specifically, the data correlation analysis unit 114 performs the determination by matching the determination items of the third layer, the determination criteria, and the life log data. Then, the degree of risk previously associated with the determination result is specified.

  Then, the data correlation analysis unit 114 specifies characteristic items and attention information according to the degree of risk (step S205). Specifically, the data correlation analysis unit 114 characterizes each item of the acquired life log data when there is an item that deviates from the normal value of the user who provided the life log data. Assuming that the item is an item, the attention information corresponding to the risk level is specified.

  The above is the driving prediction process. According to the driving prediction process, life log data can be analyzed according to a predetermined classification tree, and the driving risk level and the caution information can be specified.

  FIG. 12 is a diagram illustrating an example of a classification tree. The classification tree is divided into a first layer 610, a second layer 620, and a third layer 630, and each layer includes one or more items related to biological information of life log data. The item is provided with a threshold for classification, and each region has a structure associated with a further lower-level item with the threshold as a boundary.

  For example, the first layer 610 includes an item of sleep time 611, and when it is 6 hours or more, the first layer 610 is associated with the wake-up time 621 included in the second layer 620. If it is less than 6 hours, it is associated with the bedtime 622 included in the second layer 620.

  The item of the rising time 621 of the second layer 620 is associated with the body temperature 631 included in the third layer 630 when it is before 6:00. If it is after 6 o'clock, it is associated with the exercise intensity 632 included in the third layer 630.

  The item of the bedtime 622 of the second layer 620 is associated with the heart rate 633 included in the third layer 630 if it is before 12:00. If it is after 12:00, it is associated with the number of walks 634 included in the third layer 630.

  For example, although the classification tree is configured in this way, the above example is an example for explanation, and it goes without saying that the embodiment according to the present invention is not limited to this. The classification tree may have a multilayer structure other than the three-layer structure. In any case, the classification tree only needs to be configured according to the probability that an accident will occur based on correlated biological information.

  FIG. 13 is a diagram illustrating an example of a caution information display screen (part 1). The attention information display screen 240 includes a plurality of message display areas. The first message display area 241 is an area for displaying a main message, and is arranged at a conspicuous position on the layout of the attention information display screen 240. For example, the first message display area 241 is arranged at the top of the screen, and a message such as “Last night sleep was shallower than usual. The degree of driving risk is ☆☆☆ (three stars)” is displayed. Is done.

  The attention information display screen 240 includes a second message display area 241A and a third message display area 241B. In the second message display area 241A, supplementary / detailed information of the first message display area 241 is displayed. For example, specific information supplementing the degree of driving risk such as “the number of lateral blurring tends to double as compared with sufficient sleep” is displayed.

  The third message display area 241B displays related information of the first message display area 241, mainly information for canceling the attention state. For example, specific information for reducing the degree of driving risk such as “If a break is taken for 15 minutes, the degree of danger is reduced to ☆ (one star)” is displayed.

  FIG. 14 is a diagram illustrating an example of the caution information display screen (No. 2). The attention information display screen 250 includes a plurality of message display areas. The first message display area 251 is an area for displaying a main message, and is arranged at a prominent position on the layout of the attention information display screen 250. For example, the first message display area 251 is arranged at the top of the screen, and a message such as “It is less than one hour since getting up. The driving risk is ☆☆☆☆ (four stars)” is displayed. .

  Further, the caution information display screen 250 includes a second message display area 251A. In the second message display area 251A, supplementary / detailed information of the first message display area 251 is displayed. For example, specific information supplementing the degree of driving risk such as “Be careful with the distance between cars until 8:00, please drive carefully” is displayed.

  FIG. 15 is a diagram illustrating an example of the caution information display screen (No. 3). The attention information display screen 260 includes a life log medical certificate display area 261. In the life log medical certificate display area 261, life log data and messages such as a user's bedtime, wake-up time, sleep time, body temperature, heart rate, number of walks, exercise intensity, and the like are displayed. The message is a text message for eliminating an abnormality according to the degree of abnormality if there is an abnormality in the physical state using the life log data. For example, the message is “There is no problem in driving, but please drive carefully”.

  FIG. 16 is a diagram illustrating an example of a caution information display screen (No. 4). The caution information display screen 260 ′ is basically the same screen as the caution information display screen 260, and is an example in the case where the display contents of the life log medical certificate display area 261 and the displayed message are different. In the caution information display screen 260 ′, the life log medical certificate display area 261 ′ includes life log data such as a user's bedtime, wake-up time, sleep time, body temperature, heart rate, number of walks, exercise intensity, and message. Is displayed. The message is a text message for eliminating an abnormality according to the degree of abnormality if there is an abnormality in the physical state using the life log data. For example, the message is “Please take regular breaks and try to drive safely”.

  The above is an example of the screen that outputs the degree of danger and the caution information specified by the driving prediction process.

  FIG. 17 is a diagram illustrating a flow of risk group classification processing. The risk group classification process is started when, for example, the insurance server device 500 calculates the renewal premium when updating an existing car insurance contract or when determining the disclaimer of an existing car insurance contract. .

  First, the insurance premium discount calculation unit 117 reads the classification tree from the storage unit 120 (not shown) (step S301). As shown in FIG. 18, the classification tree has, for example, a four-layer hierarchical structure, and is a tree-structured data having a branch for each item of biometric information included in life log data or items included in driving behavior data. is there. The classification tree is specified and configured based on a correlation derived using life log data, driving behavior data, and accident data.

  Then, the insurance premium discount calculation unit 117 performs determination of the first layer of the classification tree and reading of the determination contents of the second layer (step S302). Specifically, the insurance premium discount calculation unit 117 performs the determination by reading the determination items of the first layer and the determination criteria and matching them with the life log data or the driving behavior data. And the item relevant to the result of determination among the items of the second layer to be read next is specified and read.

  Then, the insurance premium discount calculation unit 117 performs determination of the second layer of the classification tree and reading of the determination contents of the third layer (step S303). Specifically, the insurance premium discount calculation unit 117 performs the determination by matching the determination items of the second layer, the determination criteria, and life log data or driving behavior data. And the item relevant to the result of determination among the items of the third layer to be read out next is specified and read out.

  Then, the insurance premium discount calculation unit 117 reads the third layer determination and the fourth layer determination contents of the classification tree (step S304). Specifically, the insurance premium discount calculation unit 117 performs the determination by matching the determination items of the third layer, the determination criteria, and life log data or driving behavior data. And the item relevant to the result of determination among the items of the fourth layer to be read next is specified and read.

  Then, the insurance premium discount calculation unit 117 determines the fourth layer of the classification tree and determines the risk group (step S305). Specifically, the insurance premium discount calculation unit 117 performs the determination by matching the determination items of the fourth layer, the determination criteria, and life log data or driving behavior data. And the risk group relevant to the result of determination is determined.

  The above is the risk group classification process. According to the risk group classification processing, life log data or driving behavior data can be analyzed according to a predetermined classification tree, and a risk group corresponding to the degree of driving risk can be specified.

  FIG. 18 is a diagram illustrating an example of a risk group classification tree. The classification tree is divided into a first layer 710, a second layer 720, a third layer 730, and a fourth layer 740. Each layer includes items or operations related to biological information of one or more life log data. Contains behavior data items. The item is provided with a threshold for classification, and each region has a structure associated with a further lower-level item with the threshold as a boundary.

  For example, the first layer 710 includes an item of horizontal blur 711, and if it is less than a predetermined value, the first layer 710 is associated with the sleep time 721 included in the second layer 720. Further, when it is equal to or greater than the predetermined value, it is associated with the sudden braking 722 included in the second layer 720.

  The item of the sleep time 721 of the second layer 720 is associated with the wake-up time 731 included in the third layer 730 when it is 6 hours or longer. Further, when it is less than 6 hours, it is associated with the unconscious deceleration 732 included in the third layer 730.

  When the item of the sudden braking 722 of the second layer 720 is less than the predetermined value, the item is associated with the sudden acceleration 733 included in the third layer 730. Further, if it is equal to or greater than the predetermined value, it is associated with the bedtime 734 included in the third layer 730.

  The item of the rising time 731 of the third layer 730 is associated with the body temperature 741 included in the fourth layer 740 when it is before 6:00. In addition, when it is after 6 o'clock, it is associated with the accelerator opening 742 included in the fourth layer 740.

  The item of the unconscious deceleration 732 of the third layer 730 is associated with the continuous operation time 743 included in the fourth layer 740 when it is less than a predetermined value. Further, when the number is equal to or greater than a predetermined value, the number of walks 744 included in the fourth layer 740 is associated.

  The item of the rapid acceleration 733 of the third layer 730 is associated with the brake frequency 745 included in the fourth layer 740 when it is less than the predetermined value. Further, if it is greater than or equal to a predetermined value, it is associated with the exercise intensity 746 included in the fourth layer 740.

  The item of the bedtime 734 of the third layer 730 is associated with the heart rate 747 included in the fourth layer 740 if it is before 12:00. If it is after 12:00, it is associated with the sharp handle 748 included in the fourth layer 740.

  For example, although the classification tree is configured in this way, the above example is an example for explanation, and it goes without saying that the embodiment according to the present invention is not limited to this. The classification tree may have a multilayer structure other than the four-layer structure. In any case, the classification tree only needs to be configured according to the probability that an accident will occur based on biometric information or driving behavior data having correlation.

  FIG. 19 is a diagram illustrating a flow of the updated insurance premium calculation process. The renewal premium calculation process is a process for calculating the renewed premium when the insurance is renewed. The renewal insurance premium calculation process is started in a process for performing a renewal procedure of insurance executed in the insurance server device 500.

  First, the control unit 510 of the insurance server device 500 calculates an updated insurance premium (step S401). This process may be a process for calculating a renewed premium, and may be a calculation of an insurance premium for any insurance product. Preferably, it may be a calculation of a renewal premium for automobile insurance. desirable. Then, control unit 510 transmits an increase / decrease rate specification request to safe driving support device 100. This increase / decrease rate specifying request includes at least information for specifying a person who intends to renew the automobile insurance contract.

  Then, the insurance premium discount calculation unit 117 of the safe driving support device 100 includes a risk group of information for identifying a person who intends to renew the automobile insurance contract included in the increase / decrease rate specification request, a license type, and an age group. A corresponding increase / decrease rate is specified (step S402). For specifying the increase / decrease rate, a method of deriving a discount rate according to a predetermined combination of three-dimensional parameters is conceivable. However, the present invention is not limited to this. For example, a value obtained by indexing with a predetermined weight is used. The increase / decrease rate may be calculated. Then, the insurance premium discount calculation unit 117 transmits the specified increase / decrease rate to the insurance server device 500.

  The control unit 510 of the insurance server device 500 applies the increase / decrease rate to the updated insurance premium (step S403). Specifically, control unit 510 calculates an amount obtained by applying the increase / decrease rate specified in step S402 to the updated insurance premium specified in step S401, and determines it as the updated insurance premium.

  The above is the renewal premium calculation processing. According to the renewal premium calculation process, it is possible to easily calculate a renewal premium with a discount according to the risk group, license type, and age group. In particular, the risk group based on life log data of other living activities that are not in the state of driving a vehicle is included in the rate of increase / decrease, making it possible to analyze the risk trend more accurately, making it more detailed and appropriate. This can be reflected in the setting of insurance premiums.

  FIG. 20 is a diagram illustrating an example of a renewal insurance premium calculation screen. The renewal premium calculation screen 270 is an example of an output screen in the renewal premium calculation process described above. The updated premium calculation screen 270 includes a discount display area 272 for displaying a discount calculation in addition to the premium display area 271 indicating the updated premium. In the discount display area 272, for example, “The trial calculation result of the discount rate by providing life log information is 30% discount. (The insurance premium after renewal when discount is applied is YYY yen (annual amount).)” A message indicating the discount rate based on the biometric information is displayed.

  The life log insurance system 1 to which the embodiment according to the present invention is applied has been described above. According to the embodiment, the user can mitigate the influence of the accident by a simpler method. Specifically, for example, the user can perceive the degree of driving risk even before the start of driving based on a life log related to daily activities including other than driving.

  The present invention is not limited to the above embodiment. The above embodiment can be variously modified within the scope of the technical idea of the present invention. For example, in the above-described embodiment, the mobile phone terminal 200 and the life log sensor 300 exchange biological information and the like by wireless communication or the like, but are not limited thereto. For example, it may be wired communication, or may be exchanged via a storage medium or another device such as a personal computer or a tablet. The communication is not limited to direct communication, and may be exchanged by communication such as e-mail, chat, homepage, web log, SNS (Social Network Service).

  In addition, for example, the life log sensor 300 is assumed to be a terminal mainly sending sensor information to other devices in the above embodiment, but is not limited thereto. For example, the data may be transmitted to the safe driving support apparatus 100 by connecting to the Internet alone. By doing in this way, the latest biometric information can be transmitted to the safe driving support apparatus 100 with higher convenience.

  Further, the technical elements of the above-described embodiments may be applied independently, or may be applied by being divided into a plurality of parts such as program parts and hardware parts.

  In the above, this invention was demonstrated centering on embodiment.

DESCRIPTION OF SYMBOLS 1 ... Life log insurance system, 50 ... Network, 100 ... Safe driving assistance apparatus, 110 ... Control part, 111 ... Life log data processing part, 112 ... Driving behavior data processing part 113 ... Accident data processing unit, 114 ... Data correlation analysis unit, 115 ... Caution information providing unit, 116 ... Driving diagnosis information providing unit, 117 ... Insurance discount discount calculating unit, 120 ..Storage unit 121 ... Customer master storage unit 122 ... Life log storage unit 123 ... Driving behavior data storage unit 124 ... Accident data storage unit 125 ... Analysis result history storage unit , 130 ... communication unit, 200 ... mobile phone terminal, 210 ... control unit, 220 ... display unit, 230 ... communication unit, 300 ... life log sensor, 310 ... control Part, 320 Storage unit 330 ... communication unit 400 ... telematics device 410 ... control unit 411 ... driving information management unit 412 ... attention information output control unit 420 ... display unit 430: Communication unit, 500 ... Insurance server device, 510 ... Control unit, 520 ... Storage unit, 530 ... Communication unit

Claims (7)

A life log data processing unit that receives biological state information that is information indicating the state of the biological body;
A caution information providing unit that specifies the degree of danger when the living body drives a vehicle using the biological state information, and provides caution information;
A server apparatus comprising: The server device according to claim 1,
The information indicating the state of the living body is information related to sleep of the living body.
A server device characterized by that. The server device according to claim 1,
The caution information providing unit specifies the degree of risk using the biological state information and the biological state information of the parties to the traffic accident on the day before the occurrence of the traffic accident.
A server device characterized by that. The server device according to claim 1,
The caution information providing unit includes the biological state information of the parties to the traffic accident on the day before the occurrence of the traffic accident, and driving behavior information indicating the behavior of the vehicle that caused the traffic accident in a predetermined period before the occurrence of the traffic accident. The risk level is identified using the biological state information.
A server device characterized by that. The server device according to claim 1,
An insurance premium calculation unit that discounts automobile insurance premiums according to a combination of the predetermined classification using the biological state information, the type of driving license, and the age group,
A server apparatus comprising: A life log system including a server device and a client device,
The server device is
A life log data processing unit that receives biological state information that is information indicating the state of the biological body;
A caution information providing unit that specifies the degree of danger when the living body drives a vehicle using the biological state information, and provides caution information;
With
The client device is
An operation information management unit that acquires the biological state information from a predetermined external device and transmits the information to the server device;
A warning information output control unit that displays the degree of danger and the warning information provided from the server device,
Life log system characterized by that. A caution information output method for executing a procedure for outputting caution information using a computer,
The control means provided in the computer includes:
A life log data processing step for receiving biological state information which is information indicating the state of the biological body;
A caution information providing step for identifying a risk level when the living body drives a vehicle using the biological state information and providing caution information;
The notice information output method characterized by performing.

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