JP7013712B2 - Data processing device and data processing method - Google Patents

Description

Disclosures herein relate to data processing techniques for transferring or preserving data samples.

Conventionally, for example, Patent Document 1 discloses a core network device used in a mobile communication system as a kind of device for transferring data and the like. This core network device sends a usage promotion message to the mobile terminal to encourage the use of communication when the resource utilization rate of the own device decreases. As a result, it is possible to dynamically encourage the user to use it and increase the usage rate, and the utilization rate on the resource side can be optimized.

Japanese Patent No. 5692384

However, in the technique disclosed in Patent Document 1, although the utilization rate on the resource side can be optimized, the value of the transferred data is not defined at all. Therefore, when data processing resources are limited, data priorities are not properly defined, and even high-value data that can be used for various purposes can be transferred or stored. It could have been expected that it would come off.

The present disclosure has been made in view of the above problems, the purpose of which is to provide data processing technology that can efficiently utilize data processing resources while maximizing the value of data. There is something in it.

In order to achieve the above object, the first aspect disclosed is a data processing device for transferring or preserving a data sample, which is a data type of the data sample and one or more attribute types related to a usage pattern of the data sample. A table management unit (23) that manages a data value table containing information that can define a value index of a data sample based on the usage attribute information defined as a pair of and value, and the usage that belongs to a specific data type. It is equipped with a priority setting unit (25) that defines the value index of the data sample to which the attribute information is associated based on the data value table and sets the priority of transfer or maintenance of the data sample using the value index . The attribute type is a data processing device that includes identification information of a user who uses a data sample or a classification of the user .
The second aspect disclosed is a data processing device that transfers or maintains a data sample, and is a pair of a data type of the data sample and one or more attribute types and values related to a usage pattern of the data sample. Based on the usage attribute information defined in, the table management unit (23) that manages the data value table containing information that can define the value index of the data sample is linked to the usage attribute information that belongs to a specific data type. The priority setting unit is provided with a priority setting unit (25) that defines the value index of the obtained data sample based on the data value table and sets the priority of transfer or maintenance of the data sample using the value index. , It is a data processing device that changes the value index defined for each usage attribute information according to the number of users matching each usage attribute information.
Further, the third aspect disclosed is a data processing device for transferring or preserving a data sample, which is a pair of a data type of the data sample and one or more attribute types and values related to a usage pattern of the data sample. Based on the usage attribute information defined in, the table management unit (23) that manages the data value table containing information that can define the value index of the data sample is linked to the usage attribute information that belongs to a specific data type. The data value table is provided with a priority setting unit (25) that defines the value index of the obtained data sample based on the data value table and sets the priority of transfer or maintenance of the data sample using the value index. The value index in one usage attribute information includes a data value map that can be defined in association with the state information indicating the state of the data processing device, and the priority setting unit uses the state information when the data sample is acquired as the data value. By applying it to a map, it is a data processing device that derives a value index of a data sample.
The fourth aspect disclosed is a data processing device that transfers or maintains a data sample, and is a pair of a data type of the data sample and one or more attribute types and values related to a usage pattern of the data sample. Based on the usage attribute information defined in, the table management unit (23) that manages the data value table containing information that can define the value index of the data sample is linked to the usage attribute information that belongs to a specific data type. The priority setting unit (25) that defines the value index of the obtained data sample based on the data value table and sets the priority of transfer or maintenance of the data sample using the value index, and the occurrence of an event that affects the value index. It is a data processing device including an event information acquisition unit (22) for acquiring information.
The fifth aspect disclosed is a mobile terminal (100) capable of communicating with the server (10b), which is a data processing device for transferring or maintaining a data sample, and the data type of the data sample and the data sample. A table management unit that manages a data value table that includes information that can define a value index of a data sample based on the usage attribute information defined by pairing one or more attribute types and values related to the usage pattern of. 23) and the value index of the data sample that belongs to a specific data type and is associated with the usage attribute information is defined based on the data value table, and the priority is set to set the transfer or maintenance priority of the data sample using the value index. The table management unit includes a degree setting unit (25) and a transmission unit (30) that transmits at least one of the movement history of the mobile terminal and the predicted movement route of the mobile terminal to the server, and the table management unit is a movement transmitted from the transmission unit. It is a data processing device that acquires a data value table that can define a value index of a data sample acquired by a history or a predicted movement route from a server that stores a large number of data value tables so that it can be distributed.
The sixth aspect disclosed is a data processing device that transfers or maintains a data sample, and is a pair of a data type of the data sample and one or more attribute types and values related to a usage pattern of the data sample. Based on the usage attribute information defined in, the table management unit (23) that manages the data value table containing information that can define the value index of the data sample is linked to the usage attribute information that belongs to a specific data type. The table management unit includes a priority setting unit (25) that defines the value index of the obtained data sample based on the data value table and sets the priority of transfer or maintenance of the data sample using the value index. The communication resource map associated with the information about the communication resource used for transferring the data sample and the status information indicating the status of the data processing device is held, and the priority setting unit is the communication resource used for transferring the data sample to be transferred. Is a data processing device that selects based on the communication resource map.

The seventh aspect disclosed is a data processing method for transferring or preserving a data sample, in which the data type of the data sample and the usage pattern of the data sample are determined by the processing of at least one processing unit (20). Refer to the data value table containing the information that can define the value index of the data sample based on the usage attribute information defined by the pair of one or more attribute types and values (S103), and set the attribute type. , The value index of the data sample that includes the identification information of the user who uses the data sample, or the classification of the user, belongs to a specific data type, and is associated with the usage attribute information, is defined based on the data value table ( S104), the data processing method is set to prioritize the transfer or preservation of the data sample using the defined value index (S105).
The eighth aspect disclosed is a data processing method for transferring or preserving a data sample, in which the data type of the data sample and the usage pattern of the data sample are determined by the processing of at least one processing unit (20). Refer to the data value table containing information that can define the value index of the data sample based on the usage attribute information defined by the pair of one or more attribute types and values (S103), and specify the specific data type. The value index of the data sample belonging to and associated with the usage attribute information is defined based on the data value table (S104), and the priority of transfer or maintenance of the data sample is set using the defined value index (S105). ), It is a data processing method that changes the value index defined for each usage attribute information according to the number of users that match the individual usage attribute information.
Further, the disclosed ninth aspect is a data processing method used in a data processing apparatus for transferring or preserving a data sample, wherein the data type of the data sample and the data type of the data sample are determined by processing by at least one processing unit (20). Refer to the data value table including the information that can define the value index of the data sample based on the usage attribute information defined by the pair of one or more attribute types and values related to the usage pattern of the data sample (S103). ), Define the value index of the data sample belonging to a specific data type and associated with the usage attribute information based on the data value table (S104), and prioritize the transfer or maintenance of the data sample using the defined value index. The degree was set (S105), and the data value table included a data value map in which the value index in one usage attribute information could be defined in association with the state information indicating the state of the data processing device, and a data sample was acquired. It is a data processing method that derives the value index of the data sample by applying the current state information to the data value map.
Further, the tenth aspect disclosed is a data processing method for transferring or preserving a data sample, in which the data type of the data sample and the usage pattern of the data sample are determined by the processing of at least one processing unit (20). Refer to the data value table containing information that can define the value index of the data sample based on the usage attribute information defined by the pair of one or more attribute types and values (S103), and affect the value index. The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104), and the data is used by using the defined value index. It is a data processing method that sets the priority of sample transfer or maintenance (S105).
Further, the eleventh aspect disclosed is a data processing method used in a mobile terminal (100) capable of communicating with a server (10b) to transfer or maintain a data sample, and is a data processing method, in which at least one processing unit (20) is used. ), The value index of the data sample can be defined based on the data type of the data sample and the usage attribute information defined by the pair of one or more attribute types and values related to the usage pattern of the data sample. The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104) by referring to the data value table containing various information (S104), and the defined value index. (S105), the transfer or maintenance priority of the data sample is set by using, and at least one of the movement history of the mobile terminal and the predicted movement route of the mobile terminal is transmitted to the server, and the movement history or predicted movement transmitted to the server. It is a data processing method that acquires a data value table that can define a value index of a data sample acquired by a route from a server that stores a large number of data value tables so that it can be distributed.
Further, the twelfth aspect disclosed is a data processing method used in a data processing apparatus for transferring or preserving a data sample, and the data type of the data sample is determined by processing by at least one processing unit (20). Refer to the data value table, which contains information that can define the value index of the data sample based on the usage attribute information defined by the pair of one or more attribute types and values related to the usage pattern of the data sample (. S103), the value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104), and the defined value index is used to transfer or maintain the data sample. The priority is set (S105), and the communication resource map associated with the information about the communication resource used for transferring the data sample and the status information indicating the status of the data processing device is held, and the data sample to be transferred is transferred. It is a data processing method that selects the communication resource to be used based on the communication resource map.

According to these aspects, the data sample to be transferred or maintained has a value index according to the usage pattern defined in the usage attribute information based on the data value table. Then, using the defined value index, the priority of transfer or preservation of the data sample is set. As described above, if the value index of each data sample can be defined in consideration of the usage pattern of the data, for example, the priority of transferring or preserving the data sample in response to the change of the usage pattern can be flexibly set. Can be changed. Therefore, data processing resources are efficiently available while maximizing the value of the data.

The reference numbers in parentheses are merely examples of the correspondence with the specific configuration in the examples described later, and do not limit the technical scope at all.

It is a block diagram which shows the whole image of the system related to data processing including a mobile terminal. It is a flowchart which shows the detail of the priority setting process performed in the control circuit of a mobile terminal. It is a figure which visualized the data value map in Street View use. It is a figure which shows the value correction map in the pedestrian recognition use. It is a figure which shows the transition of the value index of the data sample in 1st Example. It is a figure which visualized the data value map in SLAM use. It is a figure which shows the value correction map in SLAM use. It is a figure which shows the transition of the value index of the data sample in the 2nd Example. It is a figure which shows the delay correction map used for the definition of the value index of a data sample in a remote monitoring application. It is a figure which shows the transition of the value index of the data sample in the 3rd Example. It is a figure which shows the transition of the value index of a data sample. It is a figure which shows the transition of the value index of a data sample. It is a figure which shows the transition of the value index of a data sample. It is a figure which shows the value correction map which corrects the decrease of the value index due to the transfer of a data sample. It is a figure which shows the transition of the value index of the data sample in the 4th Example. It is a figure for demonstrating the information which the mobile terminal of 5th Embodiment acquires from a server. It is a figure which visualized the data value map in Street View use. It is a figure which shows the value correction map in the pedestrian recognition use. It is a figure which shows the transition of the value index of the data sample in the 6th Example. It is a figure which visualized the communication resource map of LTE. It is a figure which visualized the communication resource map of WiFi. It is a figure which shows the bandwidth of each communication resource in a movement path, and the communication cost per bit. It is a figure which shows the correlation between the position of a mobile terminal, and the value of each data sample. It is a figure which shows the detail of the transfer schedule 1 established in the 7th Example. It is a figure which shows the detail of the transfer schedule 2 which is established in the 7th Example. It is a figure which shows the detail of the transfer schedule 3 formulated in the 7th Example. It is a figure which shows the detail of the transfer schedule 4 established in the 7th Example. It is a figure which shows the transition of the value index of the data sample in the 8th Example. It is a figure which shows the transition of the value index of the data sample in the 9th Example.

Hereinafter, a plurality of embodiments of the present disclosure will be described with reference to the drawings. By assigning the same reference numerals to the corresponding components in each embodiment, duplicate description may be omitted. When only a part of the configuration is described in each embodiment, the configuration of the other embodiment described above can be applied to the other parts of the configuration. Further, not only the combination of the configurations specified in the description of each embodiment but also the configurations of a plurality of examples can be partially combined even if the combination is not specified. Further, a combination of configurations described in a plurality of examples and modifications is also disclosed by the following description.

(First Example)
The mobile terminal 100 according to the first embodiment of the present disclosure shown in FIG. 1 is mounted on the vehicle Ac and can move together with the vehicle Ac. The mobile terminal 100 functions as a data processing device that transfers or maintains various data samples acquired by the vehicle Ac. The mobile terminal 100 can communicate with at least one server 10 installed in a data center or the like through the base station 12 and the Internet 11.

The server 10 is a computing device installed outside the vehicle Ac. The server 10 is provided with a large-capacity storage device such as a hard disk drive. The server 10 is connected to the Internet 11, receives information such as a data sample from each mobile terminal 100 mounted on a large number of vehicle Acs, and stores the received information in a storage device. In addition, the server 10 transmits information such as a data value table, which will be described later, to the requesting mobile terminal 100 in response to a request for information provision from each mobile terminal 100.

The mobile terminal 100 is electrically connected to the front camera 40 and the storage unit 50 mounted on the vehicle Ac. The mobile terminal 100 is composed of a communication unit 30, a locator 36, a control circuit 20, and the like.

The front camera 40 is an image pickup device that captures a front region of the vehicle Ac. The front camera 40 generates an image of the front region by taking an image of the front region (hereinafter, “front image”) at a predetermined cycle. The front camera 40 detects the occurrence information of a specific event. The event occurrence information is, for example, information that a detection target such as a pedestrian exists. In another example, it is information that the detected object is closest to the object. The image data of the front image generated by the front camera 40 corresponds to a data sample.

The storage unit 50 has a storage medium such as a flash memory or a hard disk drive. In the storage unit 50, in addition to a data sample such as a front image, a data value table or the like, which will be described later, is stored. The information stored in the storage unit 50 can be read by the mobile terminal 100. The storage unit 50 may be in the form of being built in the mobile terminal 100, or may be in the form of a memory card or the like that can be removed from the mobile terminal 100.

The communication unit 30 has a plurality of antennas 31 and 32 for wireless communication. The antenna 31 performs mobile communication with the base station 12. The antenna 32 transmits / receives information by wireless communication with, for example, an access point of a wireless LAN. The communication unit 30 can communicate with the server 10 via the base station 12 and the Internet 11 under the control of the control circuit 20. The communication unit 30 can transfer the data sample generated by the front camera 40 and the untransmitted data sample stored in the storage unit 50 to the server 10. The communication unit 30 can receive the data value table and the like stored in the server 10 from the server 10.

The locator 36 receives positioning signals transmitted from a plurality of positioning satellites and, for example, by combining with the measurement results of the inertial sensor, positions the current position of the mobile terminal 100. The locator 36 measures the traveling direction of the vehicle Ac by combining the positioning signal and the measurement result of the electronic compass. The locator 36 provides position information including information on the traveling direction to the control circuit 20 together with map information around the corresponding vehicle Ac.

The control circuit 20 includes at least one processor, a RAM, a rewritable non-volatile storage medium, an input / output interface for inputting / outputting information, a bus connecting these, and the like. The control circuit 20 has a clock function and can acquire the current time information. The storage medium is, for example, a flash memory or the like, and stores a data processing program for transferring or preserving a data sample. The control circuit 20 has functional blocks such as a communication control unit 21, a data acquisition unit 22, a table management unit 23, a map update unit 24, and a priority setting unit 25 by executing a data processing program by a processor.

The communication control unit 21 controls the transfer of the data sample from the communication unit 30 to the server 10. The communication control unit 21 requests the server 10 to provide information such as a necessary data value table, and acquires the information provided by the server 10. The communication control unit 21 acquires information indicating the reception status of each of the antennas 31 and 32 (hereinafter, “communication status information”), and switches the communication resource used for data transfer among the available communication resources.

The data acquisition unit 22 acquires data samples such as a front image, event occurrence information such as pedestrian detection, and state information of the mobile terminal 100. The state information includes time information, current position information acquired from the locator 36, information indicating the traveling direction, information indicating the reliability of these (peripheral recognition state information), and movement indicating the curvature of the road on which the vehicle is traveling. Contains information. In addition, the status information includes communication status information of each communication resource acquired from the communication unit 30, position information indicating the detection range SA (see FIG. 3) of the front camera 40, and the like. The data acquisition unit 22 can also acquire information from an in-vehicle network mounted on the vehicle Ac, for example, a communication bus such as CAN (registered trademark). Further, the data acquisition unit 22 can also acquire information on the speed information of the vehicle Ac acquired from the vehicle-mounted network and information on the degree of abnormality of the vehicle Ac such as the operation of sudden braking as state information (see Modification 2).

The table management unit 23 manages and refers to the data value table stored in the storage unit 50. The table management unit 23 can read the data value table necessary for calculating the value index of the acquired data sample from the storage unit 50. The data value table is associated with the data type of the data sample, the information that can define the value index, and the usage attribute information.

The data type is information indicating the contents of individual data such as a front image. Information that can define a value index includes a data value map, a value correction map, a data transfer value map, a communication resource map, and the like, which will be described later.

The usage attribute information is defined by a pair of one or more attribute types and values related to the usage mode. The attribute types include usage, user identification information for using data, user classification, number of users, and the like. The purpose of use, which is one of the attribute types, is information indicating the purpose of use of the data sample. Specific examples of values that are paired with applications include street view, pedestrian recognition, SLAM (Simultaneous Localization and Mapping), and training data for detection algorithms.

The paired values of the user identification information include information indicating individual users who use the data sample, specifically, "trader A", "trader B", "individual C", "individual D", and so on.・ Etc. can enter. The paired values of the user category include information indicating the type and position of the user who uses the data sample, specifically, "business operator", "individual", "platinum member", "gold member", and " "Paid users", "free users", etc. can enter. The value paired with the number of users may include numerical values such as "1", "2", etc. indicating the number of users to be used. In the first embodiment, only "use" is set as the attribute type of the usage attribute information.

The map update unit 24 updates the information such as the data value map included in the data value table to the latest contents. The map update unit 24 causes the server 10 to transmit a data value map update request at a predetermined timing. Based on the request of the map update unit 24, the communication control unit 21 communicates with the server 10. The map update unit 24 rewrites the contents of the data value table with the latest information provided from the server 10 in response to the request.

The priority setting unit 25 sets specific usage attribute information and transfer or maintenance priority for each data sample that belongs to a specific data type and is associated with the usage attribute information described above. When one data sample has a plurality of usage attribute information (for example, usage), the priority setting unit 25 defines a value index for each usage attribute information (usage) based on the corresponding data value table. The priority setting unit 25 prioritizes the data sample by using a plurality of value indexes defined for each usage attribute information (use) and specifically based on the sum of the plurality of value indexes defined for each use. Determine the degree. Each value index thus defined is a scalar quantity that can convert the value of a data sample into a monetary value.

For example, when a data value map corresponding to an application is prepared, the priority setting unit 25 derives a value index of the data sample by applying the state information at the time of acquiring the data sample to the data value map. The priority setting unit 25 can derive a value index of a data sample based on the latest data value map updated by the map update unit 24.

The priority setting unit 25 transfers the data sample to the server 10 or the like and stores the data sample in the storage unit 50 based on the set priority. More specifically, among the plurality of data samples to be transferred to the server 10, the higher priority data sample set by the priority setting unit 25 is transferred first. Further, among the plurality of data samples to be preserved in the storage unit 50, the data sample having the lower priority is deleted from the storage unit 50 first.

The details of the data processing method executed by the above control circuit 20 will be described with reference to FIG. 1 with reference to FIG. The priority setting process shown in FIG. 2 is started by the control circuit 20 when, for example, the vehicle Ac becomes operable and the power supply to the mobile terminal 100 is started. The control circuit 20 is repeatedly executed by the control circuit 20 until the power supply to the mobile terminal 100 is terminated. The priority setting process may be switched between an on state and an off state by the user of the vehicle Ac.

In S101, a data sample is acquired and the process proceeds to S102. In S101, individual data samples may be sequentially acquired, or a plurality of data samples may be collectively acquired at a predetermined cycle. In S102, the usage attribute information (use, user classification, number of users, etc.) of the data sample acquired in S101 is set, and the process proceeds to S103. The usage attribute information of the data sample may be the usage input by the user of the mobile terminal 100, or the usage set by a specific management organization. The content of the usage attribute information associated with the data sample may be changed sequentially. For example, the number of uses may be one or multiple. Further, a period may be provided in which one usage attribute information is not set.

In S103, the data value table in which the value index in the usage attribute information (use) set in S102 can be defined is referred from the storage unit 50, and the process proceeds to S104. In S104, a value index is defined based on a data value table for a data sample belonging to a specific data type (for example, a front image or the like). If a plurality of uses are set in S102, a value index for each use is defined, and the process proceeds to S105.

In S105, the priority of the data sample is set from the sum of the value indexes for each use defined in S104, and the process returns to S101. Based on the priority set in S105, a process of transferring the data sample, a process of preserving the data sample, and the like are performed.

Next, the details of the processing of the data sample by the mobile terminal 100 will be described by exemplifying a specific scene. The scenes described with reference to FIGS. 3 to 5 are scenes in which the priority of transfer to the server 10 and maintenance to the storage unit 50 is determined for the front image that can be used in Street View and pedestrian recognition. ..

The data value map shown in FIG. 3 is information that can define a value index of a data sample for Street View use. The data value map is information included in the data value table and is stored in the storage unit 50. The data value map is referred to by the table management unit 23 in the above priority setting process (see FIG. 2S103).

In the data value map for Street View use, the position information and the time information, which are the state information of the mobile terminal 100, are associated with the value index. The value index is derived by applying the position information when the data sample is acquired to the corresponding data value map of the time information (see FIG. 2S104). In the data value map, a value index is set for each rectangular area defined in a grid pattern. When the data value map is visualized, the shades of each area indicate the level of the value index.

The value index of each region in the data value map is set based on, for example, the density of the data sample in a specific time zone transferred to the server 10 and the distribution of the content of the information extracted from the data sample. Specifically, the smaller the number of samples (collection amount) stored in the server 10 in a specific time zone, the higher the value index is derived. In addition, for the collected data sample, the value index is derived higher in the region where information such as brightness is widely dispersed (larger variance). The dark dot region in FIG. 3 is a region where the data sample is insufficient or a region where the data sample is widely dispersed.

By applying the location information to the above data value map, the value index for street view use defined by the mobile terminal 100 that has moved along the movement route TP changes as shown in the solid line Vi1 in FIG. The position information applied to the data value map may be the position information of the mobile terminal 100, or may be the position information that specifies the detection range SA of the front camera 40. When the position information of the detection range SA is used, the highest value index among the value indexes associated with the plurality of regions included in the detection range SA is associated with the data sample. The data value map is set for each time zone and is sequentially updated with the contents corresponding to the current time.

In addition, as another example, when the value index of the data sample is defined as the training data use for training the detection algorithm, the peripheral cognitive state information indicating the reliability of the position information is used to determine the value index for the training data use. Used as. The above data value map highly defines the value index of the front image, which is a data sample, when the positioning accuracy is lowered due to, for example, the shadow of a building. By matching with the map information using the front image, it is possible to estimate the substantially correct position of the mobile terminal 100. Therefore, it is useful as data for evaluating whether or not the accuracy of the position information is ensured in an environment where it is difficult to receive satellite signals.

The value correction map shown in FIG. 4 is information that can define a value index of a data sample for pedestrian recognition use. For pedestrian recognition applications, the front image of the front camera 40 is uploaded to the server 10 for machine learning. The value index for pedestrian recognition applications does not change depending on the absolute position of the mobile terminal 100, and the difference in state with respect to the time of pedestrian detection, which is the time when a specific event occurs, specifically, the time difference or It fluctuates depending on the distance traveled (difference in position) or both. In other words, the data value map for pedestrian recognition use has a predetermined value α regardless of the position of the mobile terminal 100. The "state difference" of the mobile terminal 100 used to set the attenuation factor in the value correction map is not limited to the time difference and the position difference as described above. The difference in the index indicating the state of the mobile terminal 100 may be appropriately used in the value correction map as the "difference in state".

Specifically, in the value correction map for pedestrian recognition applications, the closest point to the detected specific target such as a pedestrian is set as the reference point (see FIG. 4 “0”), and it is used by pedestrians. The distance from the closest closest point and the rate of increase / decrease in the value index (hereinafter referred to as “value maintenance rate”) are associated with each other. The value maintenance rate is a value obtained by subtracting the attenuation rate of the value index from "1". The value retention rate gradually increases as it approaches the closest point, and shows "1" at the closest point (damping factor = 0). This shows that the front image shows the pedestrian at the highest resolution, which increases the value of the data sample. Then, it gradually decreases as the closest point passes, and the value retention rate becomes "0" at a distance of a certain distance or more from the closest point. In other words, the attenuation factor is "0" when the state (position) information at the time of data sample acquisition is the same as the state (position) information at the time of event detection, and when there is a difference of a certain amount or more in the state information, it becomes. It becomes "1".

The event to be detected is not limited to the closest approach to the detected target as described above, and an event that can be detected by the event detection unit may be used as appropriate. Further, the correspondence between the value maintenance rate and the difference in the state is not limited to the continuous correspondence as described above. For example, the detection of a pedestrian is set as a detection target event, and the value maintenance rate is set to "1" when one or more pedestrians are detected and "0" when no one is detected. It may be a discontinuous correspondence setting.

The value maintenance rate is calculated by applying the position information of the closest point and the position information at the time of data sample acquisition to the above value correction map. The value index of the data sample can be defined by multiplying the value retention rate, which is the reference result of the value correction map, by the preset predetermined value α. As a result, the value index for pedestrian recognition use defined by the mobile terminal 100 that has moved along the movement route TP changes as shown in the solid line Vi2 in FIG.

The priority of the data sample is based on the sum (dashed line TA) of the value index for street view use (solid line Vi1) based on the data value map and the value index for pedestrian recognition use (solid line Vi2) based on the value correction map. Set. As a result, the priority of the data samples acquired at the points A to E increases in the order of C> A> B> D> E. As described above, in the state where communication with the server 10 is possible, the data sample is transferred to the server 10 in the order of C, A, B, D, and E. If the storage capacity of the storage unit is insufficient outside the communication range, the data samples are discarded in the order of E, D, B, A, and C.

According to the first embodiment described so far, in the data sample to be transferred or maintained, a value index corresponding to the usage pattern defined in the usage attribute information is defined based on the data value table. Then, using the defined value index, the priority of transfer or preservation of the data sample is set. As described above, if the value index of each data sample can be defined in consideration of the usage pattern of the data, for example, the priority of transferring or preserving the data sample in response to the change of the usage pattern can be flexibly set. Can be changed.

More specifically, the data sample of the first embodiment has a plurality of uses, which is one of the attribute types. In such a case, a value index for each use is defined based on the data value table. Data sample transfer or conservation priorities are then set using a plurality of defined value indicators. As described above, if the value index of each data sample can be defined for each application, the priority of transferring or preserving the data sample can be flexibly changed in response to the addition or reduction of applications.

Further, in the data sample in the first embodiment, a value index corresponding to the state information indicating the state of the mobile terminal 100 is defined based on the data value map. Then, using the defined value index, the priority of transfer or preservation of the data sample is set. As described above, if the value index of each data sample can be defined in consideration of the state of the mobile terminal 100, the priority for transferring or preserving the data sample in response to the change in the state of the mobile terminal 100 is , Can be changed flexibly.

Therefore, data processing resources such as communication resources and storage media can be efficiently used so that the value of data is maximized.

In addition, the priority in the first embodiment is set based on the sum of the value indexes defined for each usage attribute information, specifically for each use. Therefore, the priority of the data sample, which has many uses, is surely set high. Therefore, the value of each data sample can be flexibly defined with respect to changes in the content of usage attribute information, such as changes in usage, while ensuring fairness between different uses.

Further, if a data value map as in the first embodiment is used, a value index corresponding to the state of the mobile terminal 100 at the time of acquiring the data sample is derived. Based on the above, the priority setting unit 25 can appropriately define a value index for applications that changes according to the state of the mobile terminal 100.

If the position information and the time information are used as the state information indicating the state of the mobile terminal 100, the priority setting unit 25 can correctly evaluate the priority of the data sample whose value changes depending on the acquisition position and the acquisition time. Further, if peripheral recognition information is used as the state information of the data value map, the priority of the data sample can be appropriately evaluated even when the value changes due to the fluctuation of the positioning accuracy.

Further, in the first embodiment, the map update unit 24 sequentially updates, so that the priority setting unit 25 can derive the value index of the data sample based on the latest data value map. According to the above, even if the value index is used such that the value index changes from moment to moment depending on, for example, the sufficiency of the collected amount of the data sample, the priority setting unit 25 can appropriately and appropriately.

In addition, in the first embodiment, by updating the data value map, the value index of the region where the density of the data sample acquired by the server 10 is insufficient is adjusted to be high. By updating the value index in this way, data samples in the missing area will be preferentially collected in the server 10.

Further, according to the update of the data value map in the first embodiment, the value index is adjusted to be high in the region where the content of the acquired data sample is widely dispersed. By updating the value index in this way, it becomes possible to efficiently collect data samples in areas that require more information than usual to ensure accuracy.

Further, the priority setting unit 25 of the first embodiment can define a value index by using a value correction map even for an application in which the value increases or decreases in relation to the occurrence of an event. In addition, the mobile terminal 100 can acquire information on the occurrence of an event such as pedestrian detection. Therefore, the priority setting unit 25 can appropriately evaluate the value index of the data sample related to the event.

Further, the value correction map of the first embodiment defines the value index most tacky when the occurrence of the event is detected, and defines the low value index for the data sample as the distance from the state at the time of the event occurrence increases. By adopting such a definition method, it is possible to provide appropriate value to the data sample in response to an event in which the value gradually decreases from the time of occurrence. Further, the event includes detection and loss of a detection object other than a pedestrian (for example, a white line, a road sign, etc.), passage of a maximum point and a minimum point of detection reliability, and the like. By detecting such events, the value index of the data sample can be correctly defined in a specific case (use) in which the value (value index) is affected by these events.

Further, the value index defined in the first embodiment is a scalar quantity that can convert the value of the data sample into a monetary value. Therefore, it is easy to objectively compare the value index of the data sample with, for example, the cost of using communication resources. Based on the above, it is possible to objectively evaluate whether or not sufficient profit can be obtained by transferring the data sample to the server 10.

In the first embodiment, the control circuit 20 corresponds to the "processing unit", the data acquisition unit 22 corresponds to the "event information acquisition unit", the communication unit 30 corresponds to the "transmission unit", and the storage unit 50. Corresponds to the "event detection unit", and the mobile terminal 100 corresponds to the "data processing device".

(Second Example)
In the second embodiment shown in FIGS. 6 to 8, SLAM use is added to the street view use and pedestrian recognition use of the first embodiment as the use of the data sample. In SLAM, the error of the position information due to the locator 36 (see FIG. 1) or the like is corrected by matching the detection timing of the right / left turn and the curve running with the intersection and the curve section on the map data. As described above, in SLAM, traveling with curvature is required to ensure the accuracy of map matching. Therefore, in SLAM applications, a higher value index is set for a data sample acquired with a curve having a larger curvature.

The value correction map shown in FIG. 7 is information that can define a value index of a data sample for SLAM applications. As described above, the value index for SLAM applications does not fluctuate depending on the absolute position of the mobile terminal 100, but fluctuates depending on the curvature of the curve. Therefore, in the value correction map for SLAM use, the curvature information of the curve at the time of data sample acquisition is used as the state information of the mobile terminal 100. The curve curvature information can be calculated from, for example, vehicle speed information and lateral acceleration information acquired from an in-vehicle network, steering angle information, and the like.

In the value correction map, the curvature information of the curve is associated with the relative value of the data sample. The relative value is generally set to "1" when traveling in a curve section larger than a specific curvature. The relative value decreases to a value less than "1" as the curvature of the curve decreases. For example, when the vehicle Ac turns right (see Cu1), the relative value is set to "1". On the other hand, when traveling on a gentle curve section (see Cu2), the relative value is set to about "0.4". By applying the curvature information of the curve detected by the vehicle Ac to the value correction map as described above, the value index for SLAM use is defined. As an example, the value index for SLAM applications defined by the mobile terminal 100 that moves along the movement path TP changes as shown in the solid line Vi3 in FIG.

The priority of the data sample is based on the sum of the sum of each value index for street view use and pedestrian recognition use (solid line Vi12) and the value index for SLAM use (solid line Vi3) based on the value correction map (dashed line TV2). Is set. As a result, the priority of the data samples acquired at the points A to E increases in the order of C> A> E> B> D, unlike the first embodiment.

Here, the information that can define the value index of the data sample for SLAM use may be a data value map as shown in FIG. 6 instead of the value correction map as described above. In the data value map for SLAM use, the value index is associated with the location information. In FIG. 6, the darker the dot, the higher the value index is set. That is, among the many areas of the data value map, the value index is set high especially in the area corresponding to the intersection, the curve section, or the like. By using such a data value map, it is possible to define a value index for SLAM use based on the position information even in a form in which the curvature information of the curve cannot be acquired.

In the second embodiment described so far, the same effect as that of the first embodiment is obtained, and the priority of the data sample is set corresponding to the plurality of uses set in the data sample. Therefore, data processing resources such as communication resources and storage media can be efficiently used while maximizing the value of data.

In addition, in the second embodiment, a value index for SLAM applications that fluctuates according to the curvature of the curve is defined by using a value correction map associated with the curvature information of the curve and the relative value. According to such a method, the value index of the data sample is properly evaluated even in the application where the value of the data sample increases or decreases in relation to the traveling state of the vehicle Ac.

(Third Example)
In the third embodiment shown in FIGS. 9 to 13, as the use of the data sample, in addition to the street view use, the pedestrian recognition use, and the SLAM use up to the second embodiment, the remote monitoring use in the area where automatic driving is difficult is used. Has been added.

Real-time performance is required for the front image acquired for remote monitoring applications. Therefore, for example, if the elapsed time from the time of data acquisition becomes long due to the transfer delay, the value of the data sample in the remote monitoring application rapidly decreases (see the solid line in FIG. 9). On the other hand, in street view applications, pedestrian recognition applications, and SLAM applications, real-time performance is not required as compared with remote monitoring applications. Therefore, the value of the data sample is maintained even after a lapse of time from the time when the data sample was acquired (see the broken line in FIG. 9).

The value index of the data sample for remote monitoring use is a value obtained by multiplying the reference sample value RV (see FIG. 10 and the like) by the value maintenance rate corresponding to the elapsed time from the time of data acquisition. The delay correction map shown in FIG. 9 is information that can define a value index of a data sample in a remote monitoring application, and is information that derives a value maintenance rate. In the delay correction map, the elapsed time after the acquisition of the data sample is associated with the value maintenance rate of the data sample. Specifically, in the delay correction map, the value retention rate at the time of data sample acquisition is "1 (attenuation rate = 0)", and the value retention rate becomes "0 (attenuation rate = 1)" after a certain period of time has passed since the acquisition. ) ”.

FIG. 10 shows a sample value RV for remote monitoring applications defined by a mobile terminal 100 (see FIG. 1) that has moved along a mobile route TP (see FIG. 6 and the like), and each value index other than remote monitoring applications. The transition of the total of (solid line Vi13) is shown. The sample value RV is set to a high value in areas where automatic driving is difficult. The value index for remote monitoring applications is the sample value RV multiplied by the value maintenance rate based on the value correction map.

As shown in FIG. 11, when a transfer delay occurs in the data sample, the value index (solid line Vi4) for remote monitoring applications becomes a low value with respect to the sample value RV. The priority setting unit 25 (see FIG. 1) is the sum of the value index (solid line Vi4) corrected by the value correction map for remote monitoring use and the total value index (solid line Vi13) for non-remote monitoring use. The priority of each data sample is set based on the broken line TV3).

Further, as described above, the value index for remote monitoring applications depends on the elapsed time after data sample acquisition. Therefore, as the moving speed of the vehicle Ac (see FIG. 1) becomes slower, the value of the data sample is lost at a short distance from the acquisition point of the data sample.

More specifically, FIGS. 11 and 12 show a value index after the lapse of time T1 from the time of data sample acquisition. The moving speed (= 0.5 Va) of the vehicle Ac in FIG. 12 is half of the moving speed (= Va) of the vehicle Ac in FIG. As is clear from the transition of the two solid lines Vi4, the slower the moving speed, the shorter the attenuation occurs.

Further, FIG. 13 shows a value index for remote monitoring applications at time T2 (> T1) after passing through an area where autonomous driving is difficult. Since a certain amount of time has passed since the acquisition of the data sample, the value index for remote control applications is practically 0. Therefore, the value index of the data sample is the same as the total value (solid line Vi13) of each value index other than the remote control application. In other words, value indicators for remote monitoring applications make little contribution to determining the priority of data samples.

The third embodiment described so far has the same effect as that of the first embodiment, and the data processing resources are efficiently used while maximizing the value of the data. In addition, in the third embodiment, remote monitoring that attenuates due to transfer delay is performed by setting the increase / decrease rate (attenuation rate) of the value index from the delay correction map that associates the elapsed time after data sample acquisition with the value retention rate. The value index of the application is properly defined.

(Fourth Example)
In the fourth embodiment shown in FIGS. 14 and 15, the street view use and the pedestrian recognition use are set as the use of the data sample as in the first embodiment. In addition, in the fourth embodiment, the value index of each application is corrected based on the past transfer record of the data sample.

More specifically, for example, in Street View applications, not all of the front images taken at predetermined image acquisition intervals are required, and it is sufficient if the front images are acquired at intervals required for each application. Therefore, when one front image is transferred to the server 10, the value of the front images acquired before and after that is reduced. The value correction map shown in FIG. 14 is information that corrects the decrease in the value index due to the event, with the acquisition and transfer of the data sample as an event.

Specifically, in the value correction map, the acquisition position of the transferred data sample is set as the reference point, and the moving distance from the reference point and the attenuation rate of the value index are associated with each other. The attenuation factors β and γ for each application decrease as the distance traveled from the reference point increases. In addition, the attenuation factors β and γ for each application change with respect to the moving distance.

A first desired acquisition cycle fd and a second desired acquisition cycle fe are set in the attenuation rate β for Street View use. In the section from the reference point to the first desired acquisition cycle fd, the decrease in the attenuation rate per unit movement distance is set to be larger than in the section from the first desired acquisition cycle fd to the second desired acquisition cycle fe. There is. The attenuation factor β becomes “0” in the second desired acquisition cycle fe.

The attenuation factor γ for pedestrian recognition applications linearly decreases up to the desired acquisition cycle fc. The desired acquisition cycle fc for pedestrian recognition use is closer to the reference point than the first desired acquisition cycle fd for Street View use. In addition, the desired acquisition cycle fc for pedestrian recognition applications is shorter than the image acquisition interval. As described above, the value index for pedestrian recognition use has a narrower range affected by the data transfer event than the value index for street view use.

When the data sample is transferred, the priority setting unit 25 (see FIG. 1) applies the moving distance from the acquired position of the transferred data sample to the value correction map, and the attenuation factors β and γ for each application. Is calculated. By multiplying these attenuation factors β and γ by the transitions (Vi1, Vi2) of the value index of each application before correction shown in FIG. 15, the value index of each data sample after transfer is defined.

More specifically, the mobile terminal 100 transfers the data sample f1 having the highest sum (TV1) of the two value indexes from the large number of acquired data samples. As described above, in the transition of the value index for Street View use (Vi1), the attenuation factor β based on the value correction map is multiplied in the range before and after the acquisition point of the data sample f1 as a reference. The value index for Street View applications decreases in the range from the acquisition point of the data sample f1 to the second desired acquisition cycle fe (see the second row from the top of FIG. 15). The range in which the value index for pedestrian recognition is set is separated from the acquisition point of the data sample f1 by the desired acquisition cycle fc or more. Therefore, the transfer of the data sample f1 does not affect the value index for pedestrian recognition applications.

When the value index for Street View use is corrected by the transfer of the data sample f1, the mobile terminal 100 transfers the data sample f2 having the highest sum of the corrected value indexes (TV1). As described above, the attenuation factor β is multiplied in the range before and after the acquisition point of the data sample f2 in the transition of the value index for Street View use (Vi1). In addition, in the transition of the value index for pedestrian recognition use (Vi2), the attenuation factor γ is multiplied in the range before and after the acquisition point of the data sample f2 as a reference. As a result, the value index for pedestrian recognition applications decreases in the range from the acquisition point of the data sample f2 to the desired acquisition cycle fc (see the third row from the top of FIG. 15).

When the value index for each application is corrected by the transfer of the data sample f2, the mobile terminal 100 transfers the data sample f3 having the highest sum of the corrected value indexes (TV1). As described above, the attenuation factors β and γ are multiplied in the range before and after the acquisition point of the data sample f3 in the transition of each value index. As a result, the data sample f4 becomes the data sample to be transferred next (see the lower part of FIG. 15). As described above, even the data sample f4 whose value has been reduced by the transfer of the data sample f1 may be transferred after the transfer of another data sample is completed.

In the fourth embodiment described so far, the same effect as that of the first embodiment is obtained, and the data processing resources are efficiently used while maximizing the value of the data. In addition, in the fourth embodiment, the calculation of an appropriate value index is realized by using the value correction map even for the application whose value is affected by the transfer of the data sample. Further, by adjusting the length of the desired acquisition cycle of the value correction map for each application, the temporal or spatial range affected by the data sample transfer can be appropriately set for each application.

(Fifth Example)
In the fifth embodiment shown in FIG. 16, similarly to the second embodiment, the street view use, the pedestrian recognition use, and the SLAM use are set as the use of the data sample. In addition, in the fifth embodiment, the mobile terminal 100 can communicate with the management server 10b, and acquires the minimum information necessary for defining the value index for each application from the management server 10b. The management server 10b stores a large number of data value tables so that they can be distributed. In the fifth embodiment, the server 10 (see FIG. 1) to which the data sample is transferred is referred to as the user server 10a in order to distinguish it from the management server 10b.

The mobile terminal 100 can transmit the state change history or the state change prediction of the vehicle Ac to the management server 10b. Specifically, the mobile terminal 100 transmits a travel route TP that has traveled or is scheduled to travel to the management server 10b. The movement route TP may be the movement history of the mobile terminal 100, or may be the predicted movement route of the mobile terminal 100.

When the management server 10b receives the mobile route TP from the mobile terminal 100, the management server 10b transmits to the mobile terminal 100 information that can define a value index for each use for the data sample acquired or scheduled to be acquired on the mobile terminal TP. do. Specifically, the management server 10b cuts out a range related to the movement route TP from the data value map and transmits it to the mobile terminal 100. The management server 10b can cut out a range related to the movement route TP from each data value map for Street View use and SLAM use and provide it to the mobile terminal 100.

The table management unit 23 (see FIG. 1) of the mobile terminal 100 acquires information such as a data value table in which a value index of each data sample can be defined from the management server 10b. The priority setting unit 25 (see FIG. 1) sets the sum (TV2) and the priority of the value indexes of a large number of data samples that have not been transmitted, based on each data value map received from the management server 10b. The method of setting the priority is substantially the same as the method described in the second embodiment. Then, the data sample selected at the top is transferred to the user server 10a in order.

The fifth embodiment described so far has the same effect as that of the first embodiment. In addition, in the fifth embodiment, the data value map around the mobile route TP is cut out by the management server 10b and provided to the mobile terminal 100. According to such a method, the mobile terminal 100 does not have to have an unnecessary data value map. Therefore, the storage capacity of the storage unit 50 (see FIG. 1) can be saved. Further, the data value map transmitted to the mobile terminal 100 is limited to the vicinity of the mobile route TP. Therefore, it is possible to save the downlink band.

In the above fifth embodiment, the actual or predicted movement route TP was transmitted to the management server 10b, but the mobile terminal 100 replaces the movement route TP with the current position information of the vehicle Ac to the management server 10b. You may send it. Based on the received location information, the management server 10b cuts out a specific range based on the current position of the mobile terminal 100 from the data value map for each application, and transmits the data to the mobile terminal 100. As a result, the table management unit 23 can acquire a data value table in which the value index of the data sample acquired in a specific range can be defined. In the above modification, since the information transmitted from the mobile terminal 100 to the management server 10b is limited to the location information, the uplink band can be saved.

Further, the value correction map for pedestrian recognition may be information provided from the management server 10b, similarly to the data value map. When the mobile terminal 100 detects an event, the mobile terminal 100 requests the management server 10b to provide a value correction map related to the detected event. In such a modification, the mobile terminal 100 acquires only the value correction map of only the events that can be detected by the vehicle Ac. Therefore, it is possible to save the downlink bandwidth and the capacity of the storage unit 50.

(Sixth Example)
In the sixth embodiment shown in FIGS. 17 to 19, the street view use and the pedestrian recognition use are set as the use of the data sample as in the first embodiment. In addition, the mobile terminal 100 of the sixth embodiment acquires information about the event detected in another vehicle Ba, and determines the priority of each data sample by combining the acquired information with the data value correction map. do. In the sixth embodiment, the vehicle Ac is referred to as "own vehicle Ac" in order to distinguish it from other vehicle Ba. Further, the mobile terminal mounted on the vehicle Ac is described as "own terminal 100", and the mobile terminal mounted on another vehicle Ba is described as "other terminal T".

Similar to the own terminal 100, the other terminal T acquires event occurrence information such as pedestrian detection based on the detection information of an autonomous sensor such as a front camera mounted on another vehicle Ba. The other terminal T transfers the acquired occurrence information to the server 10 (see FIG. 1) together with the position information and the time information indicating the occurrence location and occurrence time of the event.

The own terminal 100 shown in FIGS. 1 and 17 can acquire event occurrence information acquired by the other terminal T by communicating with the server 10 by the communication unit 30 and the communication control unit 21. As a result, the data acquisition unit 22 has the pedestrian detection occurrence information acquired by the own terminal 100 (hereinafter, "own terminal information") and the pedestrian detection occurrence information acquired by the other terminal T (hereinafter, "own terminal information"). Other terminal information ") can be acquired together.

The priority setting unit 25 corrects the value index of the data sample by using the own terminal information and the other terminal information. The priority setting unit 25 compares the own terminal information with the other terminal information, and extracts the difference in the detection result of the event occurring between the own terminal information and the other terminal information. The priority setting unit 25 defines a value index of a data sample related to a specific event higher when there is a difference in the detection result than when there is no difference.

Here, "there is a difference" is a case where a target is detected only in one of the terminals, for example, in a region that is simultaneously within the field of view of the cameras of both the own terminal and the other terminal. Or, it is impossible if the detection results of both terminals are true, such as the estimated position of the target detected at the same time on each terminal is different by more than the positioning error, or the number and type of targets are different. It is a state to be judged.

The reason for defining the value of the data sample when there is a "difference" as described above is that it can be used for human eyes, judgment of detection failure by a high-performance server, and alarm notification by uploading to the server. .. Another reason is that it is expected to be higher than when there is no difference in contribution to improvement of detection performance by machine learning.

Specifically, the priority setting unit 25, in addition to the value correction map described in the second embodiment (hereinafter, “first correction map” see FIG. 4), own terminal information and other terminal information shown in FIG. A value correction map based on comparison with (hereinafter referred to as "second correction map") is used to define the value index. The priority setting unit 25 multiplies the data value map for pedestrian recognition use showing a predetermined value α by both the first correction map and the second correction map to obtain a value index of the data sample for pedestrian recognition use. Derived.

In the second correction map, as in the first correction map, the distance from the closest point closest to the pedestrian and the value maintenance rate of the value index are associated with each other. In the second correction map, the correlation line δ that defines the value maintenance rate when the own terminal 100 and the other terminal T can detect the same target, and the value when the same target cannot be detected. A correlation line ε that defines the maintenance rate is set. The value maintenance rate based on the correlation line δ is a value around “1”. The value maintenance rate based on the correlation line ε shows “2” at the closest point, gradually decreases as the distance from the closest point increases, and becomes “0” at a distance of a certain distance or more from the closest point. By applying the second correction map as described above, the difference between the event detection results of the other terminal T and the own terminal 100 is included in the parameters that change the value index of each data sample.

FIG. 19 shows the transition of the value index of the data sample defined by the own terminal 100 that has moved along the movement path TP (see FIG. 17). It is assumed that another vehicle Ba has detected a pedestrian at a specific point P shown in FIGS. 17 and 19. When the same pedestrian as the other vehicle Ba can be detected in the own vehicle Ac, the transition of the value index in the pedestrian recognition application (solid line Vi22) is almost the same as that in the second embodiment (see FIG. 5 solid line Vi2). Will be.

On the other hand, when the own vehicle Ac cannot detect the same pedestrian as the other vehicle Ba, the value index for pedestrian recognition use detects the same pedestrian at the point P where the pedestrian is detected. The value is set to about twice that of the case where it was completed (solid line Vi6). In this case, the priority setting unit 25
(See FIG. 1) is the priority of each data sample based on the sum (dashed line TV6) of the value index when the same pedestrian cannot be detected and the value index (solid line Vi1) for Street View use. Is defined.

The sixth embodiment described so far has the same effect as that of the first embodiment. In addition, in the sixth embodiment, the other terminal information acquired by the other terminal T can be acquired, and the change in the value of the data sample due to the influence of the other terminal information is corrected. As described above, the priority setting unit 25 can correctly define the value index of the data sample even if the value index is used in which the value fluctuates when the event detection discrepancy occurs.

(Seventh Example)
In the seventh embodiment shown in FIGS. 20 to 27, the mobile terminal 100 holds a communication resource map relating to communication resources. In the mobile terminal 100, the transfer schedule of the data sample according to the status of the communication resource is generated by using the communication resource map. In the communication resource map, information about the communication resource used for transferring the data sample and the state information (for example, position information) indicating the state of the mobile terminal 100 are associated with each other.

The priority setting unit 25 (see FIG. 1) can select the communication resource used for the transfer of the data sample to be transferred based on the communication resource map. In addition, the priority setting unit 25 compares the value index per data amount (for example, bits) with the usage cost of the communication resource per data amount for the communication resources that can be used for the transfer of the data sample. Then, the priority setting unit 25 selects a data sample whose difference or ratio between the value index per data amount and the usage cost is equal to or greater than the threshold value as the transfer target to be transferred using the communication resource.

The communication unit 30 (see FIG. 1) is, for example, wireless communication using a line of a Long Term Evolution (LTE) cellular system (hereinafter, simply referred to as “LTE”) and wireless communication according to a WiFi (registered trademark) standard (hereinafter, simply referred to as “LTE”). , Simply described as "WiFi") is possible. The storage unit 50 (see FIG. 1) of the mobile terminal 100 stores a plurality of communication resource maps generated for each of these communication resources. The information related to the communication resource includes information indicating the availability of the communication resource, information regarding the usable capacity of the communication resource, information indicating the communication band when the resource is used, information indicating the communication delay when the resource is used, and the information concerned. Information indicating communication loss when using resources is included. In particular, the information regarding the communication resource for LTE includes information indicating the number of terminals using the specific base station.

In the communication resource map shown in FIG. 20, information indicating the width of the LTE band that can be used for transferring the data sample is associated with the position information of the mobile terminal 100. In the LTE communication resource map, the width of the usable band is defined for each rectangular area defined in a grid pattern. When the communication resource map is visualized, the shades of dots in each area indicate the bandwidth. The darker the dot area, the wider the LTE band is secured. It should be noted that the dot shading in each region may indicate information on the other communication resources described above, such as the length of delay and the susceptibility to loss.

In the communication resource map shown in FIG. 21, information indicating the bandwidth of the WiFi that can be used for transferring the data sample and the range and out of range is associated with the position information of the mobile terminal 100. The WiFi resource map may be information that simply indicates the area within which WiFi can communicate.

In addition, the information about the communication resource includes the information about the usage cost of the communication resource. The information on the usage cost includes contract information with the provider of the communication resource, information indicating the resource utilization efficiency, and the like. Information on usage costs is provided, for example, as a usage cost map. As an example, when the mobile terminal 100 moves along the movement path TP shown in FIGS. 20 and 21, the bandwidth and cost per bit of each communication resource are shown in FIG. 22 based on the communication resource map and the usage cost map. It changes like this.

The communication cost (broken line) per bit of LTE is based on the transfer unit price extracted based on the contract information, and is constant regardless of the position of the mobile terminal 100 as an example. On the other hand, the communication cost (solid line) per bit of WiFi is calculated lower as the broadband has a larger transfer amount per hour, assuming that the maintenance cost per hour of WiFi is constant.

The details of the plurality of transfer schedules generated by using the above communication resource map and usage cost map will be described below with reference to FIG. The mobile terminal 100 is moving on the movement path TP, and acquires a fixed point monitoring request at a point R that is scheduled to pass in the future. The mobile terminal 100 acquires the user's biosensor information, vehicle control information such as vehicle speed, and a front image as a data sample. As shown in FIG. 23, the value of each data sample gradually decreases as the distance from each acquisition site SPA to SPb from which each data sample was acquired increases. FIG. 23 shows each transition of the value Va of the biosensor information, the value Vb of the vehicle control information, and the value Vc of the front image which is a fixed point monitoring image. In the following description, the data amount of each data sample will be described as the same.

<Transfer schedule 1>
In the transfer schedule 1 shown in FIG. 24, each data sample of the biological signal (see region a in FIG. 24) and the vehicle control information (see region b in FIG. 24) is transferred using the LTE line. On the other hand, the data sample of the front image (see FIG. 24 area c) as the fixed point monitoring image is transferred by WiFi. In the transfer schedule 1, data samples with the highest value at the present time are transferred in order. Specifically, among the biological sensor information and the vehicle control information, the biological signal information is first transferred.

The priority setting unit 25 estimates the average transfer band based on the communication resource map, and calculates the transfer time required for the transfer of each data sample. The priority setting unit 25 can determine whether or not to transfer each data sample by comparing the value of each data sample at the end of the transfer with the cost of using the communication resource.

According to the above comparison process, the value at the end of the transfer of the biosensor information is estimated to be higher than the LTE usage cost. Similarly, the value at the end of transfer of the front image is estimated to be higher than the usage cost of WiFi. Therefore, each data sample of the biosensor information and the front image is transferred to the server 10. On the other hand, the value at the end of transfer of the vehicle control information is estimated to be lower than the LTE usage cost. Therefore, the priority setting unit 25 can stop the transfer of the vehicle control information which is a negative profit.

<Transfer schedule 2>
In the transfer schedule 2 shown in FIG. 25, as in the transfer schedule 1, each data sample of the biological signal (see region a in FIG. 25) and the vehicle control information (see region b in FIG. 25) is transferred using the LTE line. To. Then, the data sample of the front image (see region c in FIG. 25) is transferred by WiFi. In the transfer schedule 2, the vehicle control information is transferred before the biosensor signal. Biosensor information is less likely to lose value than vehicle control information. The priority setting unit 25 increases the total transfer value by first transferring the data sample having a low value at the present time.

<Transfer schedule 3>
In the transfer schedule 3 shown in FIG. 26, the transfer of the data sample that can be transmitted is waited for in consideration of the communication resources that will be available in the future and the data value that will be generated. Specifically, vehicle control information (see region b in FIG. 26) in which the sample value is significantly reduced is transmitted immediately by LTE. On the other hand, biosensor information whose sample value is unlikely to decrease is not transferred until WiFi becomes available. The biosensor information (see region a in FIG. 26) is transferred by WiFi after the front image with high sample value (see region c in FIG. 26) has been transferred. As a result, it is possible to minimize the cost of using communication resources required for data transfer.

<Transfer schedule 4>
In the transfer schedule 4 shown in FIG. 27, similarly to the transfer schedule 3, the transfer of the data sample that can be transmitted is waited until the WiFi can be used. As a result, the transfer order of each data sample becomes the same as the transfer schedule 3 (see FIG. 26). On the other hand, in the transfer schedule 4, each data sample of the biosensor information (see FIG. 27 region a) and the front image (see FIG. 27 region c) is both LTE and WiF so that the value of the data sample is maximized. It is transferred using the communication resources of. Assuming that the communication load is evenly distributed to each communication resource, the communication cost required for transfer is the average of LTE and WiFi.

In the seventh embodiment described so far, as shown in the transfer schedules 1 to 4, it is possible to stratify the data sample to be transferred according to the current state and status prediction of each communication resource. In addition, in the seventh embodiment, both the cost rate of the communication resource or the usage cost of the communication resource such as the contract content and the value of the data sample are reflected in the priority of transferring the data sample. Therefore, it is possible to select only the data samples that are definitely considered to be useful as the transfer target. As described above, the mobile terminal 100 can select and transfer only the data sample that generates a certain amount of profit or more by the transfer.

In addition, in the seventh embodiment, the communication resources and the transfer order are used so that the difference (or ratio) between the total value index and the usage cost at the time of completion of the transfer is maximized for the combination of the data samples selected as the transfer target. Is decided. As described above, it is possible to optimize the profit to be maximized by using the profit generated by the transfer as an objective function.

Further, in the seventh embodiment, the position at the future time can be estimated from the movement plan of the mobile terminal 100. Then, comprehensively considering the usage cost of each communication resource that can be used at each point on the predicted movement route TP and the value of the data sample newly acquired before reaching each point, etc. A transfer schedule can be developed. According to the above processing, it is possible to further increase the profit generated by the transfer.

Here, in the seventh embodiment, the threshold value for selecting the data sample to be transferred is always set to a positive value so that the transfer benefits. However, for example, it is difficult to estimate the value of data used for machine learning with high accuracy at the time of collection. Therefore, in order to reduce the risk of failing to collect high-value data due to value fluctuations after collection, the threshold value for selecting the data sample to be transferred may be set to zero or a negative value. With such a setting, it is possible to collect a data sample in which the value index per amount of data is lower than the usage cost, in other words, a data sample having a loss below a certain level.

(Eighth Example)
In the usage attribute information of the eighth embodiment, attribute types other than "use" and their values are defined. Specifically, "user identification information" is set as the attribute type in the usage attribute information of the eighth embodiment. Detailed usage attribute information includes {(user identification information = user 1), (use = street view): attribute A} and {(user identification information = user 2), (use = street view): attribute B}. Become.

Here, even if the usage of the front image, which is a data sample, is the same, the value of the data sample to the user (trader) increases or decreases depending on whether the data is insufficient or sufficient. As shown in FIG. 28, the transition of the value index corresponding to the attribute A (solid line Vp1) and the transition of the value index corresponding to the attribute B (solid line Vp2) are different. Each value index is calculated based on each data value map defined for each user.

The priority of the data sample is set based on the sum of the value index corresponding to the attribute A and the value index corresponding to the attribute B (dashed line TV8). As a result, the priority of the data sample acquired at the points A to E increases in the order of D> A> E> C> B. As described above, the data sample is transferred to the server 10 in the order of D, A, E, C, and B in a communicable state. If the storage capacity of the storage unit is insufficient outside the communication range, the data sample is discarded in the order of B, C, E, A, and D.

The eighth embodiment described so far has the same effect as that of the first embodiment. In addition, in the eighth embodiment, different value distributions can be applied to each user even for the same application. As a result, the priority can be determined based on the sum of the values for all the users who can use the data sample.

(Ninth Example)
In the usage attribute information of the ninth embodiment, "number of users" is set as the attribute type. Detailed usage attribute information is {(use = street view), (number of users = 2): attribute C} and {(use = SLAM), (number of users = 1): attribute D}. In this case, as a value index that reflects the number of users who use the same usage attribute (use), an effective value index obtained by correcting the value index for one user according to the number of users is calculated.

As shown in FIG. 29, the priority setting unit 25 (see FIG. 1) sets the number of users in the value index (solid line Vp1) for one user calculated based on the data value map as the value index corresponding to the attribute C. Multiply to calculate the effective value index (solid line Vdp1). In the ninth embodiment, the value obtained by doubling the value index for one user is the effective value index.

The priority of the data sample is set based on the sum (dashed line TV9) of the effective value index corresponding to the attribute C reflecting the number of users and the value index (solid line Vp3) corresponding to the attribute D for one user. .. As a result, the priority of the data sample acquired at the points A to E increases in the order of A> E> B> C> D. As described above, the data sample is transferred to the server 10 (see FIG. 1) in the order of A, E, B, C, and D in a communicable state. If the storage capacity of the storage unit is insufficient outside the communication range, the data sample is discarded in the order of D, C, B, E, and A.

The ninth embodiment described so far has the same effect as that of the eighth embodiment. In addition, in the ninth embodiment, the number of users who use the data sample in the same usage pattern is reflected in the value index. According to such a method, the mobile terminal 100 can appropriately evaluate the value index of the data sample that increases or decreases according to the number of users.

The calculation method for obtaining the effective value index based on the number of users is not limited to the method of multiplying the value index for one user by the number of users. For example, the value index for one user may be multiplied by the value of the square root of the number of users. Alternatively, the effective value index is calculated by defining a table that associates the number of users with a constant that gradually increases according to the number of users, and multiplying the value index for one user by a constant based on the table. May be good.

(Other Examples)
Although a plurality of examples have been described above, the present disclosure is not construed as being limited to the above-mentioned examples, and may be applied to various examples and combinations without departing from the gist of the present disclosure. can.

In the above embodiment, the priority of transfer and maintenance of the data sample is set based on the sum of the value indexes defined for each usage attribute information such as usage, but each value index for each usage attribute information is input. It may be defined by a function with a value. Further, the "event detection unit" that detects the occurrence of an event in the vehicle is not limited to the front camera, and may be various autonomous sensors mounted on the vehicle.

In the first modification of the above embodiment, the state information of the mobile terminal includes the state information of wireless communication. Based on the wireless communication status information, the value index of the front image as a data sample is calculated higher as the communication status with the base station deteriorates. The front image is used for analysis of obstacles such as buildings that are deteriorating communication conditions. As described above, by using the wireless communication status information, the priority setting unit can perform a legitimate value evaluation even for the usage attribute information such as the usage whose value changes depending on the wireless communication status.

In the second modification of the above embodiment, the state information of the mobile terminal includes information on the degree of abnormality in vehicle behavior. Specifically, the value of the front image as a data sample when sudden steering and sudden braking as abnormal behavior are performed based on vehicle speed information, front / rear / left / right acceleration information, or steering and brake pedal operation information. The index is calculated high. The front image is used for the analysis of the hiyari hat point. As described above, by using the information regarding the degree of abnormality, the priority setting unit can perform a legitimate value evaluation even for the usage attribute information such as the usage whose value changes depending on the degree of abnormality in the behavior.

In the modified example 3 of the above embodiment, as in the modified example 2, specific actions such as sudden steering wheel and sudden braking are acquired by the mobile terminal as event occurrence information. As described above, even if the information related to the degree of abnormality is acquired as the event occurrence information, the value index of the data sample before and after the event occurrence can be enhanced.

In the fourth modification of the above embodiment, the event occurrence information includes the detection of data having a certain degree of similarity to the specific reference data. Specifically, a reference point is set in which the value index is locally corrected to be high by detecting the passage of a specific point by the position fingerprint or the detection of a specific person. Based on the above, it is possible to give a legitimate value to the data sample corresponding to the usage attribute information such as the usage whose value is affected by the detection of similar data of the specific data.

In the fifth modification of the seventh embodiment, the contract information with the telecommunications carrier is referred to as the information regarding the telecommunications resource. As a result, the transfer schedule of the data sample can be changed to a mode suitable for the contents of the contract, for example, only high-value data in a pay-as-you-go contract and the transfer amount approaches the upper limit in a fixed-rate contract with an upper limit.

Further, in another modification 6 of the seventh embodiment, the information regarding the communication resource includes information regarding the usable capacity of the communication resource and information regarding the communication delay when the communication resource is used. From the above, the transfer completion time is predicted in consideration of the influence of congestion on the communication resource and the influence of the delay on the low communication load. As a result, the value at the time of transfer completion can be estimated in consideration of the delay dependence of the value.

Further, if the information on the communication resource includes the information on the communication loss at the time of using the resource, it is possible to consider the probability distribution of delay and cost increase due to retransmission. In addition, by including the number of terminals using the LTE specific base station in the information regarding the communication resource, it is possible to consider the fluctuation probability due to factors outside the resource map of the usable capacity.

As described above, in the modification 6, for the combination of data samples selected as the transfer target, the transfer value and resource utilization cost calculated from the communication capacity, communication delay, communication loss, and delay dependency, and their probability distributions are obtained. In view of this, the usage mode of the communication resource is determined.

In the above embodiment, the mobile terminal mounted on the vehicle functions as a data processing device. However, the data processing method according to the present disclosure may be realized by software and hardware different from the above, or a combination thereof. For example, the data processing program for transferring or maintaining the data sample may be executed by a processing unit other than the on-board mobile terminal, for example, a processing unit of a server provided on the network. The server can calculate the value index and priority for each usage attribute information such as the purpose of the data sample based on the information acquired from the vehicle. Further, as the storage unit of the mobile terminal and the storage device of the server, a non-transitory tangible storage medium such as a flash memory or a hard disk drive can be adopted.

10b management server (server), 20 control circuit (processing unit), 22 data acquisition unit (event information acquisition unit), 23 table management unit, 24 map update unit, 25 priority setting unit, 30 communication unit (transmission unit), 40 Front camera (event detection unit), 100 Mobile terminal, own terminal (data processing device), T Other terminal (other mobile terminal)

Claims (28)

A data processing device that transfers or preserves data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. It is equipped with a priority setting unit (25) to be used.
The attribute type is a data processing device including identification information of a user who uses the data sample or a classification of the user . The data processing device according to claim 1, wherein the priority setting unit changes the value index defined for each usage attribute information according to the number of users matching the usage attribute information. A data processing device that transfers or preserves data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. It is equipped with a priority setting unit (25) to be used.
The priority setting unit is a data processing device that changes the value index defined for each usage attribute information according to the number of users matching each usage attribute information . The data value table includes a data value map that can be defined by associating the value index in one usage attribute information with the state information indicating the state of the data processing device.
The priority setting unit according to any one of claims 1 to 3 for deriving the value index of the data sample by applying the state information when the data sample is acquired to the data value map. The data processing device described. A data processing device that transfers or preserves data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. It is equipped with a priority setting unit (25) to be used.
The data value table includes a data value map that can be defined by associating the value index in one usage attribute information with the state information indicating the state of the data processing device.
The priority setting unit is a data processing device that derives the value index of the data sample by applying the state information when the data sample is acquired to the data value map . A map update unit (24) for updating the data value map is further provided.
The data processing device according to claim 4 or 5 , wherein the priority setting unit derives the value index of the data sample based on the latest data value map updated by the map update unit. The data processing apparatus according to claim 6 , wherein the data value map is set to derive a higher value index as information in a region where the amount of collected data sample corresponding to a specific state is smaller. The data processing device according to claim 6 or 7 , wherein the data value map is set to derive a higher value index as information in a region where the content of the data sample corresponding to a specific state is more dispersed. The data processing apparatus according to any one of claims 1 to 8 , further comprising an event information acquisition unit (22) for acquiring event occurrence information that affects the value index. A data processing device that transfers or preserves data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. Priority setting unit (25) and
The event information acquisition unit (22) for acquiring event occurrence information that affects the value index, and
A data processing device. In the data value table, in a specific case where the value index is affected by the event, the difference between the states at the time of the event occurrence and the state at the time of acquisition of the occurrence information is associated with the increase / decrease rate of the value index. Includes more value correction maps,
The data processing device according to claim 9 or 10 , wherein the priority setting unit defines the value index of the data sample by multiplying the increase / decrease rate based on the value correction map. A data processing device that is a mobile terminal (100) that can be moved together with an event detection unit (40) that detects the generated information.
The event information acquisition unit further acquires the other terminal information which is the occurrence information acquired by the other mobile terminal (T) together with the own terminal information which is the occurrence information detected by the event detection unit. ,
The data processing device according to claim 11 , wherein the priority setting unit defines the value index by using the other terminal information together with the value correction map. When the priority setting unit has a difference between the own terminal information and the other terminal information regarding the event included in at least one of the own terminal information and the other terminal information, there is no difference. The data processing apparatus according to claim 12 , which defines the value index of the data sample related to the event higher than that of the event. A data processing device that is a mobile terminal (100) capable of communicating with a server (10b) that stores a large number of the data value tables so that it can be distributed.
Further, a transmission unit (30) for transmitting at least one of the movement history of the mobile terminal and the predicted movement route of the mobile terminal to the server is provided.
The table management unit acquires the data value table from the server, which can define the value index of the data sample acquired by the movement history or the predicted movement route transmitted from the transmission unit. The data processing apparatus according to any one of 13 . A mobile terminal (100) capable of communicating with a server (10b), a data processing device for transferring or preserving data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. Priority setting unit (25) and
A transmission unit (30) for transmitting at least one of the movement history of the mobile terminal and the predicted movement route of the mobile terminal to the server is provided .
The table management unit distributes the data value table that can define the value index of the data sample acquired by the movement history or the predicted movement route transmitted from the transmission unit, and a large number of the data value tables. A data processing device that can be acquired from the server that has been stored . The table management unit holds a communication resource map associated with information on communication resources used for transferring the data sample and status information indicating the status of the data processing device.
The data processing device according to any one of claims 1 to 15 , wherein the priority setting unit selects a communication resource used for transferring the data sample to be transferred based on the communication resource map. A data processing device that transfers or preserves data samples.
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Table management unit (23) that manages the data value table including
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table, and the transfer or maintenance priority of the data sample is set using the value index. It is equipped with a priority setting unit (25) to be used.
The table management unit holds a communication resource map associated with information on communication resources used for transferring the data sample and status information indicating the status of the data processing device.
The priority setting unit is a data processing device that selects a communication resource used for transferring the data sample to be transferred based on the communication resource map . The data processing apparatus according to any one of claims 1 to 17 , wherein the attribute type includes the use of the data sample. The data processing device according to any one of claims 1 to 18 , wherein the priority setting unit determines the priority of the data sample based on the sum of a plurality of the value indexes defined for each usage attribute information. .. The data processing apparatus according to any one of claims 1 to 19 , wherein the value index defined by the priority setting unit is a scalar amount that can convert the value of the data sample into a monetary value. A data processing device that is a mobile terminal (100) capable of communicating with a server (10b) that stores a large number of the data value tables so that it can be distributed.
Further, a transmission unit (30) for transmitting position information indicating the current position of the mobile terminal to the server is provided.
Any one of claims 1 to 20 in which the table management unit acquires the data value table from the server, which can define the value index of the data sample acquired in a specific range based on the current position. The data processing apparatus according to paragraph 1. The priority setting unit is
For the communication resources that can be used for the transfer of the data sample, the value index per data amount and the usage cost of the communication resource per data amount are compared.
The item according to any one of claims 1 to 21 , wherein the data sample whose difference or ratio between the value index and the usage cost per data amount is equal to or more than a threshold value is selected as a transfer target to be transferred using the communication resource. The data processing device described. A data processing method that transfers or preserves data samples.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
The attribute type includes identification information of a user who uses the data sample, or a classification of the user.
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
A data processing method for setting a priority for transfer or preservation of the data sample using the defined value index (S105). A data processing method that transfers or preserves data samples.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
Using the defined value index, the transfer or maintenance priority of the data sample is set (S105).
A data processing method for changing the value index defined for each usage attribute information according to the number of users matching the individual usage attribute information . A data processing method used in data processing equipment that transfers or preserves data samples.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
Using the defined value index, the transfer or maintenance priority of the data sample is set (S105).
The data value table includes a data value map that can be defined by associating the value index in one usage attribute information with the state information indicating the state of the data processing device.
A data processing method for deriving the value index of the data sample by applying the state information when the data sample is acquired to the data value map . A data processing method that transfers or preserves data samples.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
Obtain information on the occurrence of events that affect the value index,
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
A data processing method for setting a priority for transfer or preservation of the data sample using the defined value index (S105). A data processing method used in a mobile terminal (100) capable of communicating with a server (10b) to transfer or preserve a data sample.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
Using the defined value index, the transfer or maintenance priority of the data sample is set (S105).
At least one of the movement history of the mobile terminal and the predicted movement route of the mobile terminal is transmitted to the server.
The data value table that can define the value index of the data sample acquired by the movement history or the predicted movement route transmitted to the server is acquired from the server that stores a large number of the data value tables so that they can be distributed. Data processing method . A data processing method used in data processing equipment that transfers or preserves data samples.
By the processing of at least one processing unit (20)
Information that can define a value index of the data sample based on the data type of the data sample and the usage attribute information defined by a pair of one or more attribute types and values related to the usage pattern of the data sample. Refer to the data value table including (S103),
The value index of the data sample belonging to a specific data type and associated with the usage attribute information is defined based on the data value table (S104).
Using the defined value index, the transfer or maintenance priority of the data sample is set (S105).
Holds a communication resource map associated with information about the communication resource used for transferring the data sample and state information indicating the state of the data processing device.
A data processing method for selecting a communication resource to be used for transferring the data sample to be transferred based on the communication resource map .

Images