Information processing method, information processing system, and program

Abstract

To acquire, as needed, information on the state of functions and components in a movable body.SOLUTION: An information processing method uses a model generated on the basis of the combination of movable body information that is information on a movable body and deterioration or abnormality degree information of first function and component in the movable body corresponding to the movable body information, and the method includes: acquiring movable body information of a first movable body at a first time point; on the basis of the movable body information of the first movable body at the first time point, inferring, by the model, a deterioration or abnormality degree state of the first function and component at the first time point in the first movable body; and outputting information on the deterioration or abnormality degree state at the first time point.SELECTED DRAWING: Figure 3

Description

[Technical field]

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

[0002] As part of vehicle management, maintaining each part of the vehicle at the appropriate time is important, for example, from the standpoint of operating the vehicle safely for a long period of time and enabling it to be sold at a high price after operation. Conventionally, vehicle maintenance was usually performed at regular intervals (e.g., every three months). However, when a vehicle is not used much or is used excessively, it may not be appropriate to perform efficient maintenance at intervals of every three months or the like. Also, from the viewpoint of a maintenance shop or the like that performs maintenance, if it is determined that no parts need to be replaced as a result of the maintenance, there is little profit in terms of business related to the man-hours of maintenance, and therefore this is not a very desirable form of checking.

[0003] For example, Patent Document 1 discloses a means for reading out driving data across multiple driving cycles from a vehicle equipped with a storage device that stores driving data indicating the fuel efficiency state of the vehicle in response to driving operations for each driving cycle of the vehicle, a means for creating a chart showing the fuel efficiency state for each driving operation for each driving cycle based on the read driving data, and a means for outputting the chart on a display device or to a printer as a comparison result for each driving cycle. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2010-223607 A Summary of the Invention

[0005] However, in the prior art of Patent Document 1, it only creates and outputs a chart representing the fuel consumption state for each driving operation, and it is impossible to grasp when maintenance should be performed corresponding to the actual driving content.

[0006] An object of the present invention is to enable the maintenance of functions and parts in a moving body as needed.

Means for Solving the Problems

[0007] According to one aspect of the present invention, an information processing method using a model generated based on a combination of moving body information, which is information related to a moving body, and the degree of deterioration information of a first function / part in the moving body corresponding to the moving body information includes acquiring the moving body information of a first moving body, inferring, based on the acquired moving body information of the first moving body, the degree of deterioration state of the first function / part in the first moving body by the model, and outputting information regarding the inferred degree of deterioration state.

Effects of the Invention

[0008] According to the present invention, it is possible to perform the maintenance of functions and parts in a moving body as needed.

Brief Description of the Drawings

[0009] [Figure 1] It is a flowchart of the principle of the learning process according to the embodiment. [Diagram 2] It is a flowchart of the principle of the inference process according to the embodiment. [Diagram 3] It is a system configuration diagram of a vehicle maintenance management system according to one aspect of the embodiment. [Figure 4] It is a block diagram showing the functional configuration of the moving body information acquisition device 10 in FIG. 3. [Diagram 5] It is a block diagram showing the functional configuration of the mobile terminal 20 in FIG. 3. [Figure 6]FIG. 4 is a block diagram showing a functional configuration of a server 30 in FIG. [Figure 7] 4 is a block diagram showing a functional configuration of the administrator terminal 40 of FIG. 3. [Figure 8] 4 is a flowchart of a vehicle maintenance management process in the present embodiment. [Figure 9] 13 is an example of vehicle management information displayed on the display unit 440 of the manager terminal 40, which is output by the vehicle maintenance process in this embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an example of an embodiment of the present invention will be described with reference to the drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and duplicate descriptions may be omitted. However, the components described in this embodiment are merely examples and are not intended to limit the scope of the present invention.

[0011] The following describes the processes related to learning and inference using moving body information used to realize the present invention.

[0012] <Principle> 1 and 2 are diagrams for explaining the principles of learning and inference using moving body information in this embodiment.

[0013] (1) During study FIG. 1 is a flowchart showing an example of a process flow during learning. First, the device that performs the learning process (server 30 in the embodiment described later) performs a learning data set generation process. The learning data set generation process is performed for functions / components that are targets for inferring the degree of deterioration or abnormality (hereinafter referred to as "degree of deterioration, etc.") in a moving object. The target functions / components may be one or multiple. In the sense of "multiple," the process may be performed for each of the multiple target functions / components, or may be performed for the purpose of obtaining an evaluation for the multiple target functions / components as a group.

[0014] In the learning data set generation process, the device performing the learning process performs the process of loop A (A1 to A7) on the moving object information of each processing target.

[0015] In the process of loop A, based on the mobile body information, input mobile body information data that will be explanatory variables in the learning process is generated (A3). Note that if the input mobile body information data is the acquired mobile body information itself (information in an unprocessed state as acquired), this process may be omitted and the mobile body information may be used as the input mobile body information data. The method for generating the input mobile object information data may be the same as that by the mobile object information processing process described below, for example. Also, various amounts for training corresponding to the input mobile object information data are acquired (A5). The various amounts for training are, for example, information regarding the maintenance timing of the target functions and parts, as described above. Then, the device performing the learning process moves the process to the next moving body information.

[0016] For example, when the processes of A3 and A5 have been performed for all pieces of mobile object information to be processed, the device performing the learning process ends the process of loop A (A7).

[0017] Thereafter, the device that performs the learning process performs the learning process and generates a trained model (trained model 324 in the embodiment described later) (A9). Specifically, based on the input moving object information data acquired in the processing of loop A and the teacher quantities generated in the processing of loop A, the trained model is generated, for example, by supervised learning.

[0018] In the flowchart shown in Fig. 1, input mobile body information data is generated for each mobile body information unit, and the corresponding teacher quantities are acquired, but the timing of generation and acquisition is not limited to this and may be performed at any timing. For example, input mobile body information data may be generated for all target mobile body information, or teacher quantities may be acquired after all input mobile body information data are generated or before generating the input mobile body information data.

[0019] (2) At the time of inference FIG. 2 is a flowchart showing an example of a process flow during inference. First, the device that performs the inference process determines whether the inference process is required (B1). The necessity of the inference process may be determined, for example, by whether a predetermined timing has occurred (for example, if the operation is such that the check is performed every mileage, whether the mileage has exceeded a predetermined distance, such as 5,000 km, since the previous inference process; if the operation is such that the check is performed weekly, whether a predetermined date and time has occurred, such as 9:00 a.m. every Monday, etc.), or whether a request for the inference process has been made through an external device (such as the administrator terminal 40 in the embodiment described later). The device (server) performing the inference process may be the same as the device performing the learning process (for example, the server 30 in the embodiment described later may perform both processes), or may be different. In other words, the device performing the inference process may be any device as long as it is possible to use the learning model generated by the device performing the learning process.

[0020] If it is determined that the inference process is not required (B1; N), the process of the flowchart in Fig. 2 is terminated. Alternatively, the process of step B1 may be performed again after a predetermined time has elapsed. If it is determined that inference processing is required (B1; Y), mobile body information required for the required inference processing is identified (B3). The necessary mobile body information may be extracted arbitrarily depending on the application, but for example, the mobile body information acquired from the start of acquiring mobile body information (in the embodiment described later, from the time the mobile body information acquisition device 10 is mounted on the mobile body) or from the time the most recent maintenance was performed until that time is identified as the target.

[0021] It should be noted that the time point based on which the mobile object information is to be used may be arbitrary. For example, the latest time point may be used as the reference, or any past time point may be used as the reference. In other words, the time point for inferring the degree of deterioration of functions and parts may be arbitrary, and for example, the information may be used to grasp the situation at the latest time point, or may be used to grasp the situation at a time point in the past.

[0022] Next, the device performing the inference process generates input mobile object information data based on the mobile object information as an input value corresponding to the trained model generated in A9 (B5). Specifically, for example, when position information and acceleration information are acquired in a time series manner as mobile object information for a target period, total mileage information is generated based on the position information, and driving quality information (e.g., driving score) is generated based on the acceleration information. Note that, when the mobile object information can be used as an input value as it is, the mobile object information may be used as input mobile object information data without any special processing.

[0023] Next, the device that performs the inference process performs the inference process (B7). Specifically, the trained model calculates various quantities based on the input mobile object information data. Then, the calculation results are regarded as various quantity inference results. Then, the device performing the inference processing ends the processing.

[0024] Although the processes A1 to A9 during learning and the processes B1 to B7 during inference are independent of each other, they may be performed in conjunction (for example, performing processes during inference based on acquired mobile body information while learning is performed using the mobile body information).

[0025] Also, for example, the trained model may be generated by machine learning, but is not limited to a machine learning model. For example, it may be a mathematical statistical model such as a linear or nonlinear regression model, or a connectionist model such as a deep neural network (DNN). That is, in the present invention, any model generated based on a set of mobile object information and various teacher quantities may be used.

[0026] (3) Data The data used in the learning process and the inference process will be described below. The input mobile object information data is at least a part of the acquired mobile object information corresponding to the data to be input to the trained model to be generated, and / or data obtained by processing the acquired mobile object information. The contents of the input mobile object information data are not limited to the following, but may be exemplified as follows: ·Location information -Mileage information - Travel time information Driving quality information Local information ·Speed ​​information Acceleration information ·Temperature information ·Humidity information Weather information Vehicle information

[0027] Since at least a part of the mobile body information (e.g., location information, driving quality information, geographical information, speed information, acceleration information, temperature information, weather information, etc.) is acquired in a time series, in the learning process or inference process, the mobile body information acquired after the mobile body information acquisition device 10 described later is mounted on the target mobile body (e.g., after the system starts acquiring the mobile body information of the target mobile body 1) may be input, or the mobile body information acquired from the time of the most recent maintenance may be input, or any value indicating the information as a whole during these periods (a statistical value such as a total value, an average value, a maximum value, a minimum value, a median value, or a value indicating a trend, etc., may be any value that can grasp the overall picture or characteristics of the target mobile body information to a certain degree). For example, with regard to the driving quality information, all driving quality information acquired during the target period may be input, or the driving quality information for the entire target period may be calculated and input.

[0028] The teacher quantities corresponding to the input mobile object information data indicate the degree of deterioration, etc., of the target functions and parts, and the contents thereof may be arbitrary. For example, the maintenance timing of the target functions and parts may be used. This "maintenance timing" refers to, by way of example and not by way of limitation, a state in which the degree of deterioration, etc., of the target functions and parts has reached a predetermined state (for example, the tire groove has become less than a predetermined depth, the brake pad has become less than a predetermined thickness, etc.) from the perspective of a person who performs mobile object maintenance at a maintenance shop, etc., such as a mobile object maintenance expert, or by OBD inspection, and measures such as replacement or repair are deemed necessary or recommended. Since the maintenance timing is usually identified at the time of checking each function and part of the mobile object at a repair shop, it is preferable to use information such as whether it was maintenance timing, etc., as the teacher quantities corresponding to the input mobile object information data.

[0029] Furthermore, it may be a numerical value or evaluation indicating the degree of deterioration of the target function or part, for example, the value of SOH (the ratio of the full charge capacity at the time of deterioration to the initial full charge capacity of 100%), the thickness of brake pads, the size of the tread of tires, etc.

[0030] In other words, as the mobile object is operated, these parts and functions deteriorate, and eventually repair or replacement becomes necessary, but it is usually difficult for a general driver or vehicle manager to determine whether any measures are required for the target functions and parts. However, it is possible to determine this from the perspective of a person who maintains the mobile object or from OBD information. In view of this, since the degree of deterioration of each function and part varies depending on, for example, the mileage and driving quality in response to the mobile object information, the grasped degree of deterioration is used as a teacher quantity in the learning process to generate a trained model, and the mobile object information is input into the generated trained model in the inference process, so that the corresponding degree of deterioration can be obtained.

[0031] In other words, by using information about a mobile object, such as its previous driving history, and the results of judgment by a person or other performing mobile object maintenance as a set of teaching quantities, it is possible to use such a model to infer whether a mobile object that has been driving in a similar manner requires measures to be taken with respect to specified functions and parts at the target time, without the involvement of a person or other performing mobile object maintenance.

[0032] Examples of parts and functions include, by way of example and not limitation, the following: ·tire ·engine Brake pads Brake drums ·SOH Air conditioner filters Wiper blades

[0033] Alternatively, the teacher quantities and output values ​​may be determined by the degree of deterioration, etc., obtained by combining the wear, consumption, and deterioration of the parts and functions belonging to each category (for example, but not limited to, the "engine" includes the "ignition system," "fuel system," "intake and exhaust system," and "lubrication system" for the "engine," the "charging system," "wiring and connection terminals," and "power control device" for the "battery," the "suspension," "tires and wheels," "brake system," and "steering system" for the "lubricants," the "engine oil," "transmission oil," "brake fluid," "power steering oil," and "cooling water" for the "lubricants," and the "safety equipment," "comfort equipment," "driver assist device," and "lighting device" for the "safety / comfort equipment"). For example, the teacher quantities and output values ​​may be determined when the deterioration level of a certain number (e.g., two) or more parts and functions in a certain category reaches a certain level.

[0034] In this way, when mobile object information is input, the model can output information regarding the degree of deterioration, etc., for each part and function of the mobile object, such as whether or not maintenance is due.

[0035] <First Example> Hereinafter, a first embodiment will be described in which the state of each function / part of the moving body 1 is periodically inferred, and when it is inferred that maintenance is required, a notification is sent to the manager terminal 40 or the like as appropriate.

[0036] <Functional configuration> FIG. 3 is a system configuration diagram of a vehicle maintenance management system according to an aspect of the present embodiment. In this system, a mobile body information acquisition device 10 mounted on a mobile body 1 such as a vehicle to be managed, a mobile terminal 20 held by a driver of the mobile body 1 for inputting and transmitting necessary information, a server 30, and an administrator terminal 40 operated by an administrator who manages the mobile body 1 are connected via a network NW. In the mobile body information acquisition device 10, mobile body information regarding the mobile body 1 is acquired and transmitted to the server 30 via the network NW, and the information input in the mobile terminal 20 is similarly transmitted to the server 30 via the network NW. In the server 30, various processes are executed based on the received and stored mobile body information, input information, etc., and the results are output to, for example, the administrator terminal 40.

[0037] Note that, in addition to being operated alone, the mobile body 1 may be operated in connection with a transportation assistance means 1a such as a chassis. In this case, the mobile body information acquisition device 10 may also be mounted on the transportation assistance means 1a, and acquisition of mobile body information regarding the transportation assistance means 1a and transmission to the server 30 may be performed. Further, when the mobile body 1 and the transportation assistance means 1a are connected, it may be possible to input information regarding the transportation assistance means 1a in the mobile terminal 20 held by the driver of the mobile body 1 and transmit it to the server 30. Thus, not only the mobile body 1 but also the functions / parts of the transportation assistance means 1a or the transportation assistance means 1a itself may be a management target such as inferring the degree of deterioration.

[0038] Here, the mobile body information is information related to the mobile body 1, and may be, but is not limited to, for example, position information, speed information, acceleration information, which is information related to the traveling of the mobile body 1, as well as information on each sensor, each actuator, etc. of the mobile body 1 (e.g., whether an abnormality has occurred, how much wear and tear there is, etc.) that can be obtained using the OBD (On-board diagnostics) method (hereinafter referred to as OBD information), information related to the situation in which the mobile body 1 is placed, such as temperature information, inclination angle information related to the inclination angle of the road it is traveling on, as well as input information input and obtained at the mobile terminal 20 described later, and information related to the specifications of the mobile body 1 itself (such as vehicle type information), and the like.

[0039] Furthermore, the mobile body information may include information obtained by processing based on various information (including the acquired mobile body information itself). For example, the mobile body information may include distance information calculated based on the position information included in the mobile body information. The distance information may be, for example, the distance since the mobile body information acquisition device 10 was mounted on the mobile body 1, or the distance since the most recent maintenance was performed, and the content of the distance information is not particularly limited and may be arbitrary. For example, the mobile body information may include driving quality information calculated based on acceleration information (or speed information, position information) included in the mobile body information. The driving quality information is information about the driving quality of the mobile body 1, and is information about the degree of influence on wear, consumption, deterioration, etc. of each part of the mobile body 1. For example, depending on the target function or part, such as tires, the content (for example, a numerical value; it can also be said to be a driving score) may be different depending on whether a large scalar value of acceleration is observed frequently or rarely. For example, the mobile body information may include driving time information obtained by summing up the driving time since the mobile body information was acquired or since maintenance was performed.

[0040] Furthermore, the OBD information may be acquired by a unique device for OBD (e.g., an inspection scan tool) separate from the mobile information acquisition device 10 and stored in the server 30 via a network, or information acquired using, for example, an inspection scan tool at a maintenance factory or the like at the timing of maintenance such as vehicle inspections, regular checks, and any repairs may be stored in the server 30. That is, for example, the OBD information may be transmitted in chronological order via the mobile information acquisition device 10 over the network NW to the server 30 and stored therein, or it may be temporarily stored in a server for a maintenance factory or the like that performs maintenance (hereinafter referred to as the "maintenance factory server"), and then retrieved from the maintenance factory server and stored in the server 30.

[0041] Furthermore, when at least location information is acquired as mobile body information in the mobile body information acquisition device 10 and transmitted to and stored in the server 30, such location information and information such as temperature, weather, inclination angle, etc. at the location corresponding to that time may be acquired from an external device (e.g., a server providing information regarding weather or a server providing information regarding geographical information) and stored in the server 30 as part of the mobile body information.

[0042] Moreover, the moving object information is not limited to being composed of one type of information, and may be composed of a plurality of types of information. For example, the moving object information may be composed of position information and acceleration information. Also, certain moving object information is collected at a predetermined timing (e.g., in time series) in the moving object information acquisition device 10, and similarly, the moving object information accumulated in the moving object information acquisition device 10 may be transmitted to the server 30 at a predetermined timing. For example, in a certain moving object information acquisition device 10, it is collected in units of seconds and transmitted to the server 30 in units of minutes. As another example, in another moving object information acquisition device 10, the moving object information is collected in units of 10 seconds and transmitted to the server 30 in units of 10 minutes. As yet another example, in a certain moving object information acquisition device 10, the moving object information is collected in units of 10 seconds and transmitted via a roadside unit when the moving object 1 passes near the roadside unit connected to the server 30 (e.g., a method according to ETC 2.0).

[0043] That is, the moving object information may be directly acquirable information about the moving object acquired by the moving object information acquisition device 10 or other means, or may be information indirectly acquired by processing the information acquired by the moving object information acquisition means 10 or other means, or may include a plurality of types of information. As long as it is information related to the moving object 1, its acquisition method, calculation method, and form may be arbitrary.

[0044] The moving object 1 is, for example, a passenger car or a truck vehicle, etc., but is not limited thereto and may be any one. For example, it may be a driverless vehicle. Also, it may be a gasoline vehicle, an electric vehicle, or a hybrid vehicle.

[0045] FIG. 4 is a block diagram showing the functional configuration of the moving object information acquisition device 10 of FIG. 3. The mobile object information acquisition device 10 in this embodiment is, for example, a device that collects mobile object information according to the ETC2.0 system and transmits it to the server 30. Another example is a device that can be inserted into a socket (for example, a cigarette lighter socket, an electricity supply socket, or a connection socket) of the mobile object 1 and fixed inside the mobile object 1 (referred to as a "cigarette lighter device" in this application). The electricity supply socket or the connection socket is, for example, a socket that supports USB (Universal Serial Bus). Of course, the mobile object information acquisition device 10 is not limited to these, and may be of any form or device, such as a device provided in the mobile object 1, such as a drive recorder, a car navigation device, or a digital tachograph, or even integrated with a mobile terminal 20 (described later) carried by the driver of the mobile object 1, as long as it can at least collect mobile object information of the mobile object 1 and transmit it to the server 30. The mobile object information acquisition device 10 is configured to include, for example, a processing unit 110, a storage unit 120, a communication unit 130, a mobile object information acquisition unit 170, and a clock unit 180.

[0046] As described above, the mobile object information acquisition device 10 collects mobile object information via the mobile object information acquisition unit 170 at predetermined intervals, and stores the information in the storage unit 120 in association with time information acquired by the clock unit 180. Then, the stored acquired mobile object information is transmitted at a predetermined timing to the server 30 connected to the network NW via the communication unit 130.

[0047] The processing unit 110 is configured by a processing operation device including, for example, a CPU (Central Processing Unit) and an MPU (Micro-Processing Unit). The processing unit 110 performs various processes on each piece of data, and also controls each functional unit such as the communication unit 130, the mobile object information acquisition unit 170, and the clock unit 180 by reading and executing a program stored in the storage unit 120.

[0048] The storage unit 120 includes, for example, a hard disk drive (HDD), a solid state drive (SSD), an electrically erasable programmable read-only memory (EEPROM), a read-only memory (ROM), a random access memory (RAM), and the like, and stores the control program processed by the processing unit 110, various data, for example, information acquired by each functional unit, and the like. Note that the storage unit 120 is not limited to being built into the mobile object information acquisition device 10, and may be an external storage device connected via a digital input / output port such as a universal serial bus (USB), or the like.

[0049] In this embodiment, the storage unit 120 stores, for example, a mobile object information acquisition and transmission processing program 121 and a mobile object information database 122 .

[0050] The mobile object information transmission processing program 121 is a program for realizing a mobile object information transmission processing for transmitting the mobile object information acquired via the mobile object information acquisition unit 170 to the server 30 at an appropriate timing.

[0051] The mobile object information database 122 is, for example, a database in which mobile object information acquired about the mobile object 1 is accumulated and stored. The mobile object information may be stored in the mobile object information database 122 in association with time information issued by a clock unit 180 described later. That is, the mobile object information is accumulated in the mobile object information database 122 in a manner that makes it possible to know when the mobile object information was acquired. For example, when the mobile object information acquisition device 10 acquires position information as the mobile object information, the coordinate information as the acquired position information may be stored in association with the time of acquisition.

[0052] The communication unit 130 is a module that can connect to a public network such as the Internet and communicate data with each device such as the server 30 connected to the network by using, for example, mobile communications such as LTE (Long Term Evolution), 3G, 4G, and 5G, or narrowband communications such as DSRC (Dedicated Short Range Communication). Alternatively, information may be exchanged by communications compatible with ETC2.0, which performs two-way communications using DSRC. The mobile object information stored in the mobile object information database 122 is transmitted to an external server 30 via the communication unit 130 .

[0053] For example, when the mobile object information includes position information, the mobile object information acquisition unit 170 acquires position information (for example, latitude and longitude information) of the mobile object information acquisition device 10 at a predetermined interval based on radio waves arriving from a GNSS satellite (for example, a GPS satellite). That is, the mobile object information acquisition unit 170 can acquire position information of the mobile object 1 equipped with the mobile object information acquisition device 10. In other words, by using the mobile object 1 equipped with the mobile object information acquisition device 10, the mobile object information acquisition unit 170 can substantially acquire position information of the mobile object 1. For example, when the mobile object information includes speed information, the mobile object information acquisition unit 170 acquires vehicle speed pulse information acquired by a vehicle speed pulse acquisition unit (not shown) mounted on the mobile object 1, and acquires the speed information of the mobile object 1 at a predetermined interval based on the vehicle speed pulse information. Alternatively, the speed information may be calculated based on position information acquired separately. For example, when the mobile object information includes acceleration information, the acceleration is acquired by a piezoelectric acceleration sensor. Alternatively, the acceleration of the vehicle may be calculated based on position information and speed information acquired separately.

[0054] Furthermore, the mobile object information acquisition unit 170 may be configured to include a temperature information acquisition unit (not shown). That is, the temperature may be measured in a time series manner and acquired as the mobile object information. Similarly, the mobile object information acquisition unit 170 may be configured to include any one of an atmospheric pressure information acquisition unit, an altitude information acquisition unit, a humidity information acquisition unit, and the like. That is, information related to some environment inside and outside the mobile object 1 may be acquired as the mobile object information.

[0055] Furthermore, the mobile object information acquisition unit 170 may be configured to include an image information acquisition unit (not shown), and images of the inside and outside of the mobile object 1 may be appropriately acquired by the image information acquisition unit, and such image information may be acquired as mobile object information. For example, image information of the road surface and image information of the weather may be acquired as mobile object information outside the mobile object 1, and image information of the driver may be acquired as mobile object information inside the mobile object 1, and the contents are not particularly limited.

[0056] The acquired mobile object information may be stored in the mobile object information database 122 of the storage unit 120 in association with information about the time (current time) at which the mobile object information was acquired, which is acquired by the clock unit 180 described later.

[0057] Here, when the location information is included in the mobile object information, an accuracy value (e.g., DOP value) indicating the accuracy of the location information may be acquired when acquiring the location information. In this case, the acquired location information and accuracy value may be associated with the current time and stored in the storage unit 120.

[0058] The method of acquiring the mobile object information is not limited to the above, and any method of acquiring the mobile object information may be applied. For example, when the mobile object 1 equipped with the mobile object information acquiring device 10 approaches, the mobile object information acquiring unit 170 may receive radio waves including the mobile object information emitted by a roadside device installed on the side of the road, thereby acquiring the mobile object information of the mobile object information acquiring device 10.

[0059] The clock unit 180 is a built-in clock of the mobile object information acquisition device 10, and outputs time information (timekeeping information). The clock unit 180 is configured to include, for example, a clock using a crystal oscillator. The clock unit 180 may be configured to include a clock that complies with the Network Identity and Time Zone (NITZ) standard or the like.

[0060] FIG. 5 is a block diagram showing a functional configuration of the mobile terminal 20 of FIG. The mobile terminal 20 in this embodiment is a device for transmitting input information, which is information input by the driver of the moving object 1, to the server 30. The mobile terminal 20 is configured to include, for example, a processing unit 210, a storage unit 220, a communication unit 230, a display unit 240, an operation unit 250, a sound output unit 260, and a clock unit 280. The mobile terminal 20 is realized by, for example, a smartphone.

[0061] The processing unit 210, memory unit 220, communication unit 230, and clock unit 280 have the same functional configurations as the processing unit 110, memory unit 120, communication unit 130, and clock unit 180 in the first information processing device 100, so their description is omitted here.

[0062] In this embodiment, the storage unit 220 stores, for example, an input information transmission processing program 221 and an input information database 222.

[0063] The input information transmission process program 221 is a program for realizing an input information transmission process for transmitting input information acquired via an operation unit 250 (to be described later) to the server 30.

[0064] The input information database 222 is a database in which input information acquired via the operation unit 250 is accumulated and stored. The input information is associated with time information issued by a clock unit 280 (described later) and stored in the input information database 222. That is, the input information is accumulated in the input information database 222 in a manner that makes it possible to know when the input information was acquired.

[0065] The display unit 240 is, for example, a display device configured to have an LCD or the like, and performs various displays based on a display signal output from the processing unit 210. The display unit 240 may be configured integrally with a touch panel to form the operation unit 250 as a touch screen.

[0066] The operation unit 250 is configured to have input devices such as operation buttons and operation switches for the user to perform various operation inputs to the mobile terminal 20. The operation unit 250 may also have a touch panel integrally configured with the display unit 240, and this touch panel may function as an input interface between the user and the mobile terminal 20. The operation unit 250 outputs an operation signal to the processing unit 210 in accordance with a user operation.

[0067] The operation unit 250 may be configured integrally with an image acquisition unit (not shown). For example, image information captured by the image acquisition unit may be acquired as input information. An example of the image information is an image of a warning light display in the instrument panel of the moving object 1. That is, by acquiring an image of a warning light display that notifies the user that an abnormality has occurred in some function or part of the moving object 1, the user can know that the function or part needs to be repaired or replaced.

[0068] The sound output unit 260 is a sound output device including a speaker and the like, and outputs various sounds based on the sound output signal output from the processing unit 210.

[0069] Fig. 6 is a block diagram showing the functional configuration of the server 30 in Fig. 3. The server 30 in this embodiment includes a processing unit 310, a storage unit 320, and a communication unit 330. The server 30 is connected to the mobile object information acquisition device 10, the mobile terminal 20, the administrator terminal 40, etc., via a network such as the Internet, receives mobile object information from the mobile object information acquisition device 10 and input information from the mobile terminal 20, and stores them in the storage unit 320. Also, the server 30 performs vehicle maintenance management processing based on the stored information.

[0070] The processing unit 310 is configured by a processing operation device including, for example, a CPU (Central Processing Unit) and an MPU (Micro-Processing Unit). The processing unit 310 performs various processes on each piece of data, and also reads out and executes programs stored in the storage unit 320.

[0071] The storage unit 320 includes, for example, a hard disk drive (HDD), a solid state drive (SSD), an electrically erasable programmable read-only memory (EEPROM), a read-only memory (ROM), a random access memory (RAM), etc., and stores the control program processed by the processing unit 210, various data, for example, an installed device table in which device identification information is registered, etc. Note that the storage unit 420 is not limited to being built into the server 400, and may be an external storage device connected via a digital input / output port such as a universal serial bus (USB), etc.

[0072] In this embodiment, the storage unit 320 stores, for example, a vehicle maintenance processing program 321, a database 322, a mobile object information processing program 323, and a trained model 324.

[0073] The vehicle maintenance processing program 321 is a program that is read by the processing unit 310 and executed as the vehicle maintenance processing described below.

[0074] Database 322 is a database for storing information about moving body 1, which accumulates not only the moving body information of moving body 1 transmitted from mobile body information acquisition device 10 and input information transmitted from mobile terminal 20, but also other moving body information calculated by appropriately processing the moving body information, etc.

[0075] The mobile object information processing program 323 is a program that is read by the processing unit 310 and executed as a mobile object information processing process for calculating other mobile object information by processing based on accumulated mobile object information (e.g., position information) and the like.

[0076] The trained model 324 corresponds in principle to the trained model obtained by the above-mentioned training process, and is a model for inputting mobile object information and outputting, as an inference result, information on the degree of deterioration of the target function / part, for example, information on the maintenance timing of the target function / part. The training process for generating the trained model 324 and the inference process are as described above.

[0077] The communication unit 330 is a module that can connect to a network such as the Internet using a wired or wireless communication interface, for example, mobile communications such as LTE (Long Term Evolution) or 3G, or narrowband communications such as DSRC (Dedicated Short Range Communication), and can communicate data with each device, such as the mobile information acquisition device 10, connected to the network.

[0078] Fig. 7 is a block diagram showing the functional configuration of the administrator terminal 40 in Fig. 3. The administrator terminal 40 in this embodiment may be, for example and without limitation, an electronic device such as a tablet or laptop PC, and is configured to include, for example, a processing unit 410, a storage unit 420, a communication unit 430, a display unit 440, an operation unit 450, and a sound output unit 460. The configurations of each of these functional units, namely, processing unit 410, memory unit 420, communication unit 430, display unit 440, operation unit 450, and sound output unit 460, may be substantially similar to those of processing unit 210, memory unit 220, communication unit 230, display unit 240, operation unit 250, and sound output unit 260 of mobile terminal 20, and therefore detailed explanations thereof will be omitted.

[0079] In this embodiment, the storage unit 420 stores, for example, a vehicle maintenance management information display processing program 421.

[0080] The vehicle maintenance management information display processing program 421 is read by the processing unit 410 and is intended to perform processing in cooperation with the vehicle maintenance management processing program 321 of the server 30, and is a program executed using output from the vehicle maintenance management processing described below.

[0081] FIG. 8 is a flowchart of a vehicle maintenance management process in this embodiment, in which the mobile object information acquisition device 10 acquires mobile object information, transmits the acquired mobile object information to the server 30, processes the acquired mobile object information in the server 30, and infers and notifies the status of specified functions and parts. The vehicle maintenance management processing is processing performed by a vehicle maintenance management processing program 321 stored in the storage unit 320 of the server 30.

[0082] First, in order to accumulate mobile object information on the mobile object 1, the mobile object information acquisition device 10 acquires the mobile object information (S1001) and transmits the acquired mobile object information to the server 30 (S1002). The mobile object information acquisition device 10 repeats these steps to acquire the mobile object information in chronological order and transmits it to the server 30. In the server 30, the mobile object information received from the mobile object information acquisition device 10 is stored in the database 322 of the storage unit 320 (S3001).

[0083] Although not shown in the flowchart of FIG. 8, the input information input and acquired from the mobile terminal 20 is also one type of mobile object information, and is transmitted to the server 30 and stored in the database 322 of the memory unit 320, similar to steps S1001 and S1002.

[0084] In addition, the mobile body information stored in the database 322 is processed by a mobile body information processing program 323 to generate separate mobile body information depending on the application, and the generated separate mobile body information is also stored in the database 322. Examples of separate mobile object information that may be generated include weather information generated based on location information, driving quality information generated based on acceleration information, and speed information and acceleration information generated based on location information, but the content is not particularly limited. Note that the processing of the mobile object information is not limited to being performed by the server 30, but may be performed by the mobile object information acquisition device 10 or by a device other than these.

[0085] The timing of the mobile body information processing may be performed each time the target mobile body information is accumulated in the server 30, or may be performed in accordance with the timing of determining whether the specified conditions are satisfied in step S3003 described below, or may be performed in accordance with the timing of performing the inference processing, and is not particularly limited.

[0086] In addition, when operating the mobile object 1, it is possible to perform maintenance in a maintenance factory or the like (S9001) during the operation, and to repair or replace all or part of the functions and parts of the mobile object 1 to recover from a broken or deteriorated state (hereinafter referred to as a "deteriorated state"). In consideration of the implementation of such maintenance, a device in the maintenance factory or the like (hereinafter referred to as a "maintenance factory device") may acquire the degree to which the deteriorated state of each function or part has been recovered (as a non-limiting example, a replacement may be regarded as 100% recovery, an overhaul may be regarded as 90% recovery, or any recovery standard may be set according to the nature of the treatment), based on a user input or OBD information, and a notification that maintenance has been performed on the function or part may be sent to the server 30 (S9002). As a non-limiting example, cases where a tire is replaced after a flat tire, as well as cases where parts are overhauled, polished, corrosion removed, gas is refilled, and the amount of fuel injected or pressure is adjusted, may be assumed. Upon receiving such notification, the server 30 stores information related to the maintenance, such as the timing when the maintenance was performed, the functions / parts that were maintained, and the degree to which the maintenance restored the functions / parts, in the storage unit 320 (S3002). In this manner, if maintenance was performed on all or some of the functions / parts after the mobile object information acquisition device 10 was mounted on the mobile object 1, the deterioration state, etc., of the functions / parts can be inferred, reflecting the contents of the maintenance performed.

[0087] Next, the server 30 judges whether or not a predetermined condition for performing the inference process is satisfied (S3003). When inferring the deterioration state of the functions and parts of the moving body 1, it is ideal to perform the inference continuously so as to grasp the timing of maintenance in near real time, but in consideration of the processing load and the load on the operation side that receives the notification, it is preferable to perform the inference process appropriately when necessary. Therefore, in this embodiment, the inference process is performed only when a predetermined condition for performing the inference process is satisfied.

[0088] Predetermined conditions include, by way of example and not limitation, the following: When an administrator (for example, from the administrator terminal 40) requests that inference be made - When a specified time arrives (for example, when inference processing is scheduled to be performed periodically, such as every Monday morning at 9:00) When the mobile information meets a certain condition (for example, inference is made every 5,000 km traveled) When a date and time arrives at which the deterioration or other condition of the target function or part is assumed to satisfy a specified condition based on the results of the previous inference process (for example, a specified state may simply be input into the inverse function of the generated model and the corresponding date and time may be output, or a function (for example, an approximation function) indicating the degree of deterioration or other conditions may be generated separately from the model based on the results of the previous inference process, and the date and time at which the value of such function will be a value corresponding to the specified state is calculated. In this case, the inference process may be performed exactly at the date and time at which the corresponding value is reached, or it may be performed at a nearby date and time, assuming that some degree of deviation will occur due to information about moving objects along the way)

[0089] If it is determined that the predetermined conditions are not satisfied (S3003; N), the process returns to step S3001 and continues to accumulate moving object information. On the other hand, if it is determined that the predetermined conditions are satisfied (S3003; Y), state inference processing is performed for the target functions and components (S3004). The state inference process is performed by the trained model obtained by the above-mentioned learning process outputting an inference result of the state of deterioration, etc., based on the accumulated mobile body information.

[0090] The process of determining whether or not a predetermined condition is satisfied may be performed collectively for all functions and parts that are the subject of state inference in the mobile object 1, or for each function and part, or for each category that includes multiple functions and parts (e.g., categories such as engine and suspension). In other words, when mobile object information is input to the model, the model may output a judgment result for one function and part, or for multiple functions and parts, or for one or multiple categories. Here, the judgment result for a category may be output directly as a result of the category as a whole, or judgment results for multiple functions and parts included in the category may be obtained first, and then the judgment result for the corresponding category may be output based on those judgment results. For example, when judging the engine category, the degree of deterioration, etc. for each of multiple functions and parts in the engine may be obtained, and then it may be judged whether or not maintenance is required for the engine as a whole based on the degree of deterioration, etc. for those multiple functions and parts. The method of determining whether or not maintenance is necessary for the entire category based on the degree of deterioration, etc. of multiple functions / parts may be arbitrary, and a determination may be made, for example, not only when the degree of deterioration, etc. of at least one of the multiple functions / parts satisfies the conditions corresponding to the need for maintenance, but also when the statistical value (e.g., average, weighted average, median, etc.) of the numerical value when the degree of deterioration, etc. of multiple functions / parts is expressed as a score is below (exceeds) a predetermined threshold, or using a separate model (learning model, etc.).

[0091] When performing inference processing for all functions / components or categories at once, inference processing may be performed for all functions / components or functions / components belonging to a category if the specified condition is satisfied, or inference processing may be performed only for functions / components corresponding to the satisfaction of the specified condition. In the latter case, processing returns to step S3001 for functions / components that do not correspond to the satisfaction of the specified condition. Furthermore, inference processing may be performed for the category itself. Also, when processing is performed for each function / component, each function / component performs the processing from step S3003 onwards independently. That is, the inference timing may be different for each function / part, all may be inferred at the same timing, or inference may be performed for each function / part or all functions / parts depending on the contents of the predetermined conditions. For example, for mobile unit 1, inference may be performed for all functions / parts once a month (e.g., at 9:00 a.m. on the first day of each month), while inference may be performed for the corresponding function / part when a predetermined condition for each function / part is satisfied (e.g., when the mileage for that function / part reaches 5,000 km since the most recent maintenance was performed for that function / part).

[0092] When the state inference result is output, it is determined whether the output state inference result satisfies a predetermined condition (S3005). The predetermined condition here includes, for example, whether or not it is determined that the state requires maintenance. For example, if the trained model is generated to output whether or not the state requires maintenance, the state requires maintenance is determined according to the output, and if the trained model is generated to output a numerical value indicating the degree of deterioration (for example, a numerical value indicating the degree of deterioration from 0 to 100 (100 being no deterioration)) or an evaluation (for example, an index indicating an evaluation from A to E), the state requires maintenance refers to a case where the output is less than or equal to a predetermined threshold (for example, if the output is a numerical value indicating the degree of deterioration, the threshold is 70, and if the output is an evaluation indicating the degree of deterioration, the threshold is D).

[0093] If it is determined that the state inference result does not satisfy the predetermined condition (S3005; N), the process returns to step S3001 and continues to accumulate the mobile object information. At this time, the state inference result or the fact that the predetermined condition is not satisfied may be notified. On the other hand, if it is determined that the state inference result satisfies the predetermined condition (S3005; Y), a notification is made based on the state inference result (S3006). The notification here may be, for example, outputting on the display unit 440 of the administrator terminal 40 that the function / component whose state inference result satisfies the predetermined condition is in a predetermined state, for example, that maintenance is required. In addition to this, the notification may be made by voice through the sound output unit 460, or may be output to the display unit 240 of the mobile terminal 20, and the method may be arbitrary.

[0094] Here, when performing the inference process on a function / component whose state can be defined by a numerical value, evaluation, etc., the branch process of step S3005 may not be performed and the state may be notified in step S3006. In other words, although measures such as maintenance are not yet necessary, it may be notified as to what state it is inferred to be at that point in time. Furthermore, when the state inference result indicates the degree of deterioration, etc., by a numerical value or the like, and whether or not it is time for maintenance is judged according to the content of the degree of deterioration, etc., if it is judged that it is not time for maintenance, the amount of time remaining until the maintenance timing may be estimated according to the difference between the degree of deterioration, etc. at that time and the degree of deterioration, etc. corresponding to the maintenance timing, and the estimation result may be output. In other words, it may be possible to indicate how much more (e.g., distance, time) is required to travel before the maintenance timing is reached. The total travel distance expected to reach the maintenance timing is referred to as the total travel distance at the expected maintenance timing.

[0095] 9 shows an example of vehicle management information displayed, for example, on the display unit 440 of the manager terminal 40 by the vehicle maintenance management information display process executed, for example, by the manager terminal 40 based on the vehicle maintenance management information display process program 421. As shown in FIG. The vehicle maintenance management information display process is a process that uses the state inference result and the like output by the server 30. The vehicle management information shown in Fig. 9 is generated, for example, in response to a generation request made through the operation unit 450 of the administrator terminal 40. Then, the generated vehicle management information is displayed, for example, on the display unit 440, and the contents are viewed by a user such as the administrator.

[0096] As shown in FIG. 9, the vehicle management information includes, for example, the following areas.

[0097] Area U11 is composed of information (e.g., name and affiliation) regarding the user (hereinafter referred to as the "target user") who is the driver of the mobile body 1 for which vehicle management information is being created, as well as information regarding the mobile body 1 including a mobile body ID.

[0098] Area U12 is other mobile object information (e.g., driving quality, total mileage) calculated based on mobile object information in a target period by the target user, and information (e.g., mileage at last maintenance, abnormality report) generated based on information transmitted from a maintenance factory device, a mobile terminal, etc. Here, the driving quality indicates, by way of example and not limitation, the quality of driving by the target user in the mobile object 1 from various viewpoints. Also, the abnormality report indicates, for example, whether or not a notification has been received from the input information transmitted from the mobile terminal 20 that some abnormality has occurred in the mobile object 1, and if so, what the content of the notification is.

[0099] The area U13 is an acceleration information map generated based on the acceleration information of the target user during a predetermined period. The acceleration information map is a map of the acquired acceleration information based on some element. For example, in this embodiment, a two-dimensional map based on the direction and magnitude is displayed. More specifically, the occurrence frequency of the acquired acceleration information is counted for each predetermined division, and the display based on the count value is performed for each division. Note that the display for each division in the acceleration map is not limited to the occurrence frequency, and may be based on, for example, the occurrence probability.

[0100] The area U14 shows the evaluation of each function / part for which state inference is performed in the mobile unit 1 and the total mileage at the time of the expected maintenance timing. In this embodiment, the corresponding functions / parts are summarized for each category (engine, battery, suspension, ..., safety / comfort equipment). For each function / part, the evaluation (corresponding to the degree of deterioration, etc., in this embodiment, A indicates the smallest degree of deterioration, and the degree of deterioration increases as B, C, ...) or the degree of deterioration, etc. (for example, for SOH, its value; the ratio of the full charge capacity at the time of deterioration when the initial full charge capacity is taken as 100%, for brake pads, their thickness, for tires, the size of the tread, etc.) calculated based on the mobile unit information, and the total mileage at the time when the need for the next maintenance corresponding to the evaluation is expected are shown.

[0101] For example, in the example shown in FIG. 9, for functions and parts with a rating of B, the total mileage at the time of the next expected maintenance is shown as 75,000-80,000 km, while for functions and parts with a rating of B-, it is shown as 60,000-65,000 km, and for functions and parts with a rating of A, it is shown as 95,000-100,000 km. As an exception, tires are shown with a rating of B but a total mileage at the time of the next expected maintenance as 85,000-90,000 km. This reflects, for example, the total mileage at the time of tire replacement (total mileage at the previous maintenance, which is 20,516 km) as a result of the tire being replaced after a failure (e.g., a puncture) caused by factors other than deterioration occurred in the tire.

[0102] The total mileage at the expected maintenance timing may be shown as a range, as in the example shown in Fig. 9, on the assumption that the contents of the mobile body information acquired in the future will vary compared to the past information, or may be shown as a single value calculated on the assumption that the mobile body information acquired in the future will be acquired in the same manner as the mobile body information acquired up to now, or may be calculated by any method. For example, based on the mobile body information of the mobile body 1 acquired up to that point, it may be calculated by a method such as extrapolation when the maintenance timing set for each function / part will be reached, or it may be calculated by using the trained model 324 to determine what kind of inference result will be obtained at the future maintenance timing (for example, after a mileage of 5,000 km). It may also be calculated based on the mobile body information of other mobile bodies than the mobile body 1.

[0103] The SOH of the battery is also shown as a degradation level of "87%". The SOH affects the residual value when the vehicle is sold, and by checking the SOH, it is possible to take measures according to the SOH, such as improving the driving quality of the moving body 1 to maintain a high residual value or deciding to sell the vehicle. Therefore, a predetermined point in time, for example 65%, may be set as the recommended timing for selling, and a notification to that effect may be given when the battery reaches 70%. A detailed explanation will be given later.

[0104] Information on the two functions / parts, "brake pads" and "brake drums", is displayed in a different format (white text on a black background) from the other functions / parts, and is also indicated as "maintenance recommended." This indicates that it has been inferred that the condition is such that maintenance is recommended, and in this embodiment, the trained model 324 performs inference based on the mobile object information, and outputs an inference result that these two functions / parts have reached a predetermined degree of deterioration and that it is time for maintenance, and this display notifies the user of this output content.

[0105] In addition, multiple levels of severity may be used for determining whether or not to perform maintenance. For example, if the level is equal to or lower than a first threshold, a notification may be issued stating that "maintenance is recommended," and if the level is equal to or lower than a second threshold that is lower than the first threshold, a notification may be issued stating that "maintenance is strongly recommended." In other words, even if a "maintenance recommended" notification is given, if maintenance is not performed, deterioration will progress further and the condition may become even more dangerous; therefore, in such cases, a "maintenance strongly recommended" notification is given to encourage the user to improve the dangerous condition as soon as possible.

[0106] Area U15 is information that maps the movement (driving route) of the mobile object 1 driven by the target user and the positions where a specific driving was observed on a map based on the position information included in the driving-related information by the target user during the target period. By providing such information, the administrator or the like can confirm how the target user operated the mobile object 1, in what location, and with what driving quality.

[0107] In this way, by acquiring mobile body information about the mobile body 1 and performing various processes including inference processing of maintenance timing based on the acquired mobile body information, information and services related to vehicle management can be provided to users such as vehicle managers, thereby enabling users to efficiently manage their vehicles.

[0108] <Specific examples and their effects> The following describes what effects can be expected by using what moving object information and teaching quantities.

[0109] (1) Location information When location information is included in mobile object information, the location information can indicate the types of roads and areas the object has been traveled over. For example, the following factors are thought to affect the degree of deterioration of the functions and parts of the mobile object: - Road conditions A bad road can have a negative effect on tires, etc., and in a snowy area, driving on a road where snow-melting agents have been spread can also have a negative effect on tires, etc. These may be used as regional information obtained by processing the position information. Weather in the area you are driving in High and low temperatures are thought to have the potential to accelerate the deterioration of functions and parts, and weather such as hail is thought to have a negative impact on the vehicle body, etc. These may be used as part of mobile object information, such as weather information obtained by processing location information.

[0110] In addition, the following elements, for example, can be used as mobile object information that can be obtained by processing location information. Distance information Distance information can be obtained by processing the position information acquired over time. Since distance information is information about the distance traveled by a moving object, it is possible to consider the impact on wear of the corresponding functions and parts such as tires. Road information By processing the location information acquired over time, it is possible to obtain road information, which is information about the roads that were traveled. Based on the road information, it is possible to understand what kind of roads were traveled on (for example, bad roads, roads with snow, roads muddy from rain, roads with snow-making agents, etc.), and the impact of such road conditions on the degree of deterioration of each function and part is reflected.

[0111] (2) Acceleration information When the mobile object information includes acceleration information, the type of driving performed by the driver can be indicated by the acceleration information. For example, the following elements are considered to affect the degree of deterioration of the functions and parts of the mobile object. -The magnitude and frequency of the acceleration that occurred It is considered that the greater the acceleration that occurs, the greater the burden on the functions and parts of the vehicle. Similarly, it is considered that the greater the number of times that a certain magnitude of acceleration occurs, the greater the burden on the functions and parts. In addition, driving quality information that can be obtained by processing acceleration information and integrating the magnitude and number of accelerations that occur may be used as part of the vehicle information. The acceleration information may be directly acquired or may be acquired by processing the position information. Any method may be used to acquire the acceleration information based on the position information, but for example, the method disclosed in International Publication WO2022 / 091650 may be applied.

[0112] (3) Speed ​​information When the moving body information includes speed information, the above (2) acceleration information is almost the same as the case, and therefore a description thereof will be omitted.

[0113] (4) Travel time information When the mobile object information includes travel time information, like the distance information in the location information (1) above, the travel time information is information about the time the mobile object has traveled, and therefore, the impact on wear, etc. of the corresponding functions and parts such as tires may be considered.

[0114] (5) Vehicle information When vehicle model information is included in the mobile unit information, the functions and parts used may differ depending on the vehicle model, and the degree of wear and tear may also differ accordingly. From this point of view, it is preferable to use information on functions and parts as the mobile unit information. However, since compatibility between functions and parts may also have an effect, it may also be meaningful to use vehicle model information that compiles a combination of multiple functions and parts into one. In addition, information such as vehicle type information (mobile body information regarding the mobile body 1, not information regarding driving) may be acquired, for example, as input information from a mobile terminal 20 or an administrator terminal 40, and the method of acquisition is not particularly limited.

[0115] <Modification> In the case of electric vehicles, since the residual value is set based on the SOH when they are sold, it is conceivable to take measures according to the state of the SOH in order to sell them for as high a price as possible. Therefore, a response may be made based on the value of SOH inferred by the trained model 324 based on the mobile object information.

[0116] For example, when the inferred SOH value falls below a predetermined threshold (e.g., 70% or less), it may be determined that it is time to sell, and a notification to that effect may be sent. Note that this threshold may be preset by the administrator or the like in the administrator terminal 40.

[0117] In addition, based on the SOH value inferred from the vehicle information, it may be evaluated whether the driver of the vehicle 1, which is an electric vehicle, is driving in a favorable manner in order to maintain a high residual value. For example, when the degree of decrease in the SOH value with respect to the travel distance or travel time is smaller than a predetermined threshold, it is determined that the driver is driving in a favorable manner. In addition, a driver who is determined to be driving satisfactorily may be given some kind of merit, such as a reward. That is, when a driver is determined to be driving satisfactorily, information regarding the reward for the driver of the moving body 1 may be generated, and an administrator or the like may give a reward to the driver in response to the generated information (by viewing, etc.).

[0118] In the above-mentioned embodiments, various programs and data relating to various processes are stored in the storage unit, and the processing unit reads and executes these programs to realize the processes in the above-mentioned embodiments. In this case, the storage unit of each device may have internal storage devices such as ROM, EEPROM, flash memory, hard disk, and RAM, as well as recording media (recording media, external storage devices, storage media) such as memory cards (SD cards), Compact Flash (registered trademark) cards, memory sticks, USB memories, CD-RWs (optical disks), and MOs (magneto-optical disks), and the above-mentioned various programs and data may be stored in these recording media.

[0119] Although the embodiment of the present invention has been described in detail above, the scope of the present invention is not limited to the above embodiment and modifications. Furthermore, the above embodiment and modifications can be improved or modified in various ways without departing from the spirit of the present invention. Furthermore, the above embodiment and modifications can be combined. [Explanation of symbols]

[0120] 1. Mobile 10 Mobile object information acquisition device 20 Mobile Devices 30 Servers 40 Administrator terminal

Claims

1. 1. An information processing method using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration level information of a first function / part in the mobile body corresponding to the mobile body information, comprising: Obtaining moving object information of a first moving object at a first time point; inferring a degree of deterioration or the like of the first function / part of the first moving body at the first time point using the model based on moving body information of the first moving body at the first time point; outputting information relating to the deterioration level at the first time point; An information processing method comprising:

2. The information processing method according to claim 1 further comprises: determining whether the deterioration level information at the first time point satisfies a predetermined condition; Including, outputting information regarding the degree of deterioration or the like at the first time point includes, when it is determined that the predetermined condition is satisfied, outputting information indicating that maintenance is required or recommended for the first function / part of the first moving object at the first time point; Information processing methods.

3. 2. The information processing method according to claim 1, The inference of the degree of deterioration or the like at the first time point is performed based on mobile body information related to a period from a time point of the most recent maintenance performed on the first function / part of the first mobile body to the first time point. Information processing methods.

4. 2. The information processing method according to claim 1, The means for acquiring the mobile object information of the first mobile object includes a device provided in the first mobile object. Information processing methods.

5. 5. The information processing method according to claim 4, acquiring location information of the first moving object by the device; acquiring at least one of travel distance information, acceleration information, speed information, travel time information, and driving quality information of the first moving body based on the acquired position information; The information processing method further comprises:

6. 5. An information processing method according to claim 1, further comprising: The mobile object information includes mileage information. Information processing methods.

7. 5. An information processing method according to claim 1, further comprising: The moving object information includes at least one of acceleration information and speed information. Information processing methods.

8. 5. An information processing method according to claim 1, further comprising: The mobile object information includes travel time information. Information processing methods.

9. 5. An information processing method according to claim 1, further comprising: The mobile object information includes vehicle type information. Information processing methods.

10. 5. An information processing method according to claim 1, further comprising: The mobile information includes location information. Information processing methods.

11. 5. An information processing method according to claim 1, further comprising: The mobile object information includes driving quality information. Information processing methods.

12. 2. The information processing method according to claim 1, the first function / part is a battery of the moving object 1, the deterioration degree information is a SOH of the battery, The information processing method includes: determining whether the deterioration level information at the first time point satisfies a predetermined condition; notifying information regarding a timing of selling the moving object at the first time point when it is determined that the predetermined condition is satisfied; An information processing method comprising:

13. 2. The information processing method according to claim 1, the first function / part is a battery of the moving object 1, the deterioration degree information is a SOH of the battery, The information processing method includes: determining whether the deterioration level information at the first time point satisfies a predetermined condition; generating information regarding the award of a reward to the driver of the moving object at the first time point when it is determined that the predetermined condition is satisfied; An information processing method comprising:

14. The information processing method according to claim 2 further comprises: inferring the next timing when maintenance is necessary or recommended for the first function / part of the first moving body at the first time point based on the moving body information of the first moving body, the deterioration degree information at the first time point, and the predetermined condition; An information processing method comprising:

15. 1. An information processing method using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration or the like degree information of each of a plurality of functions / components included in a first function / component group category in the mobile body corresponding to the mobile body information, the method comprising: Obtaining moving object information of a first moving object at a first time point; inferring a state of a degree of deterioration or the like at the first time point for each of the plurality of functions / components using the model based on mobile object information of a first mobile object at the first time point; determining whether the first function / component group category satisfies a predetermined condition based on the degree of deterioration or the like inferred for each of the plurality of functions / components; outputting a message indicating that maintenance is required or recommended for the first function / parts group category of the first moving object at the first time point when it is determined that the predetermined condition is satisfied; An information processing method comprising:

16. An information processing system using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration level information of a first function / part in the mobile body corresponding to the mobile body information, a moving object information acquisition unit that acquires moving object information of a first moving object at a first time point; an inference unit that infers a degree of deterioration or the like of the first function / part of the first moving body by the model based on moving body information of the first moving body at the first time point; an output unit that outputs information regarding the degree of deterioration or the like at the first time point; An information processing system comprising:

17. An information processing system using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration level information of each of a plurality of functions / components included in a first function / component group category in the mobile body corresponding to the mobile body information, the information processing system comprising: a moving object information acquisition unit that acquires moving object information of a first moving object at a first time point; an inference unit that infers a state of a degree of deterioration or the like at the first time point for each of the plurality of functions / components using the model based on mobile object information of a first mobile object at the first time point; a determination unit that determines whether the first function / component group category satisfies a predetermined condition based on the degree of deterioration or the like inferred for each of the plurality of functions / components; an output unit that outputs, when it is determined that the predetermined condition is satisfied, a message indicating that maintenance is required or recommended for the first function / parts group category in the first moving object at the first time point; An information processing system comprising:

18. An information processing system using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration level information of a first function / part in the mobile body corresponding to the mobile body information, Obtaining moving object information of a first moving object at a first time point; inferring a degree of deterioration or the like of the first function / part of the first moving object using the model based on moving object information of the first moving object at the first time point; outputting information relating to the deterioration level at the first time point; A program to execute.

19. An information processing system using a model generated based on a combination of mobile body information, which is information about a mobile body, and deterioration level information of each of a plurality of functions / components included in a first function / component group category in the mobile body corresponding to the mobile body information, Obtaining moving object information of a first moving object at a first time point; inferring a state of a degree of deterioration or the like at the first time point for each of the plurality of functions / components using the model based on mobile object information of a first mobile object at the first time point; determining whether the first function / component group category satisfies a predetermined condition based on the degree of deterioration or the like inferred for each of the plurality of functions / components; outputting a message indicating that maintenance is required or recommended for the first function / parts group category of the first moving object at the first time point when it is determined that the predetermined condition is satisfied; A program to execute.

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