JP7042734B2 - Data registration system - Google Patents

Description

The present invention relates to a data registration system for registering data related to a vehicle or the like input via a network.

Conventionally, a system described in Patent Document 1 is known as a vehicle operation data management system. This management system is equipped with an in-vehicle device and an operation management device, and the in-vehicle device can be used from various devices and sensors of the vehicle to travel speed, mileage, acceleration, geographical position, driving operation, and fuel injection amount of the vehicle. Etc. are acquired as operation data.

In this in-vehicle device, after the start of acquisition of the operation data, the operation data and the identification information for identifying the driver are associated (associated) and stored, and when the driver makes an end-of-work operation, the association is performed. The operation data and identification information are transmitted to the operation management device.

Japanese Unexamined Patent Publication No. 2017-27545

In recent years, in various fields, it has been desired to sequentially register data, convert it into big data, analyze it, and utilize it, and this point is the same for data related to vehicles and the like. On the other hand, in the case of the management system of Patent Document 1, there is a problem that highly effective data cannot be efficiently registered because it is not premised that the data is converted into big data and utilized.

The present invention has been made to solve the above problems, and an object of the present invention is to provide a data registration system capable of efficiently registering highly effective data related to a vehicle or the like.

In order to achieve the above object, the data registration system 1 according to the present invention includes mobile state data representing a time-series mobile state of a mobile station (navigation device, mobile information terminal) and a vehicle 14 that moves at the same time as the mobile station. A plurality of types of data including consumption ratio data representing the energy consumption ratio of the vehicle 14, navigation data representing the navigation calculation result and setting state of the vehicle 14, weather data representing the weather in the area where the mobile station existed, and the vehicle 14 and Data receiving means (data processing server 2) in which vehicle identification data (vehicle ID, user ID) for identifying at least one of the owners of the vehicle 14 is input via the network 10, movement state data, and consumption. Data group creation means (integrated processing server 3, STEP 22 to 26) and data group (data mart) that create a data group (data mart) in which ratio data, navigation data, weather data, and vehicle specific data are linked to each other. ) Is compressed by a predetermined compression algorithm (Lzo algorithm), and registration data creation means (integrated processing server 3, STEP 27 to 28) for creating registration data using the compressed data group (data mart) and registration data. It is characterized by comprising a data storage means (integrated database server 4, STEP 80 to 90) for storing the data in a storage area.

According to this data registration system, a data group in which movement state data, consumption ratio data, navigation data, weather data, and vehicle specific data are linked to each other is created. In this case, the movement state data is the time-series movement state of the mobile station, the consumption ratio data is the energy consumption ratio of the vehicle moving at the same time as the mobile station, and the navigation data is the navigation calculation result and setting state of the vehicle, and the weather data. Represents the weather in the area where the vehicle existed, and the vehicle identification data is for identifying the vehicle and / or the user of the vehicle. Therefore, the data group in which these data are linked to each other is a vehicle or the like. It will be highly effective when converting data related to the above into big data and analyzing it. Further, the data group is compressed by a predetermined compression algorithm, and the registered data is created using the compressed data group, and the registered data is stored in the storage area, so that the size of the registered data can be reduced. As a result, the number of registered data stored can be relatively increased with respect to the storage area having the same capacity. As described above, highly effective data can be efficiently registered (note that the "navigation data representing the vehicle navigation calculation result and setting state" in the present specification is the calculation result of the navigation device mounted on the vehicle. And not limited to the data representing the setting state, the data when route calculation, position calculation, etc. are performed based on the data received from the navigation device of the vehicle on the server or mobile information terminal, and the calculation result is transmitted to the navigation device. include).

In the present invention, the data group creating means includes a first data group (FCD-provisional data mart for fuel efficiency) in which vehicle specific data (vehicle ID, user ID), movement state data, and consumption ratio data are linked to each other, and a vehicle. The second data group (FCD-navigation provisional data mart) in which specific data (vehicle ID, user ID), movement state data, and navigation data are linked to each other, and the second data group in which movement state data and weather data are linked to each other. It is preferable to create 3 data groups (FCD-provisional weather data mart) and create a data group (data mart) using the 1st to 3rd data groups.

According to this data registration system, the first data group in which the movement state data and the consumption ratio data are linked to each other, the second data group in which the movement state data and the weather data are linked to each other, the movement state data and the navigation data are combined. Since the data group is created by creating the third data group linked to each other and using the first to third data groups, the load at the time of creating the data group is compared with the case where the data group is created at once. Can be reduced.

In the present invention, the plurality of types of data further include vehicle status data representing at least one of the manufacturing status and the repair status of the vehicle 14, and the data group creating means includes movement state data, consumption ratio data, navigation data, weather data, and the like. It is preferable to create a data group by further associating vehicle status data with each other in addition to vehicle specific data.

According to this data registration system, as a data group, in addition to vehicle identification data, movement state data, consumption ratio data, navigation data, and weather data, vehicle status data representing at least one of vehicle manufacturing status and repair status is further added. Since the data group is created by associating with each other, the effectiveness of the data group when converting the data into big data and analyzing it can be further enhanced.

In the present invention, the data group creating means includes a first data group (FCD-provisional data mart for fuel efficiency) in which vehicle specific data (vehicle ID, user ID), movement state data, and consumption ratio data are linked to each other, and a vehicle. The second data group (FCD-navigation provisional data mart) in which specific data (vehicle ID, user ID), movement state data, and navigation data are linked to each other, and the second data group in which movement state data and weather data are linked to each other. The third data group (FCD-provisional data of the weather), the fourth data group (FCD-provisional data of the vehicle condition) in which the vehicle specific data (vehicle ID, user ID), the movement state data, and the vehicle condition data are linked to each other. It is preferable to create a data group (data mart) by creating a mart) and using the first to fourth data groups.

According to this data registration system, the first data group in which the movement state data and the consumption ratio data are linked to each other, the second data group in which the movement state data and the weather data are linked to each other, the movement state data and the navigation data are combined. Since the third data group linked to each other and the fourth data group linked to the moving state data and the vehicle status data are created, and the data group is created using the first to fourth data groups, the data group is created. Compared to the case where the data group is created all at once, the load when creating the data group can be reduced.

In the present invention, the moving state data and the navigation data include the vehicle position at the time of sampling as data, and the data group creating means when creating the second data group at the time of sampling in the moving state data and the navigation data. When the vehicle positions do not match each other, it is preferable to link the data of the movement state data and the navigation data having the closest vehicle position at the time of sampling to each other (STEP 40, 41).

According to this data registration system, when the second data group is created, when the vehicle positions at the time of sampling in the movement state data and the navigation data do not match each other, the time of sampling of the movement state data and the navigation data is used. Since the data with the closest vehicle positions are linked to each other, create the second data group while linking the data that are presumed to be highly relevant because the vehicle positions at the time of sampling are the closest. Can be done. Thereby, the accuracy of creating the second data group can be improved.

In the present invention, the moving state data and the navigation data include the time stamp at the time of sampling and the vehicle position at the time of sampling as data, and the data group creating means has the moving state data and the moving state data when creating the second data group. When there are a plurality of data in which the vehicle positions at the time of sampling match each other in the navigation data, it is preferable to link the data having the closest time stamp at the time of sampling among the plurality of data to each other (STEP 40, 42, 44). ..

According to this data registration system, when creating a second data group, when there are a plurality of data in which the vehicle positions at the time of sampling in the movement state data and the navigation data match each other, the time of sampling among the plurality of data is used. Since the data with the closest time stamps are associated with each other, create the second data group while associating the data that are presumed to be highly related because the time stamps at the time of sampling are the closest. And the creation accuracy can be improved.

The registered data creating means preferably creates registered data (STEP 28) by encrypting the compressed data group with a predetermined encryption algorithm.

According to this data registration system, registration data is created by encrypting a compressed data group with a predetermined encryption algorithm, so that the security of the registration data can be improved.

It is a figure which shows typically the structure of the data registration system which concerns on one Embodiment of this invention. It is a flowchart which shows the association data creation process. It is a flowchart which shows the data integration process. It is a flowchart which shows the provisional data mart creation process of FCD-navigation. It is a flowchart which shows the encrypted data mart creation process. It is a flowchart which shows the data storage process.

Hereinafter, the data registration system according to the embodiment of the present invention will be described with reference to the drawings. As shown in FIG. 1, the data registration system 1 of the present embodiment includes a data processing server 2, an integrated processing server 3, and an integrated database server 4.

Each of the above servers 2 to 4 includes a processor, a memory, an I / O interface, and the like, and is configured to be able to execute various arithmetic processes based on the arithmetic program and the input / output data in the memory.

The data processing server 2 executes the association data creation process described later, and stores a large amount of user information data in the storage area. This user information data is the personal information of the user of the vehicle, the user registration date, the user ID, and the vehicle ID linked to each other, and is described above by the server administrator via an input interface (not shown). Is created using these when is entered. In the present embodiment, the data processing server 2 corresponds to the data receiving means, and the user ID and the vehicle ID correspond to the vehicle specific data.

The data processing server 2 includes a weather server 11, a large number of factories 12 (only one is shown), a large number of dealers 13 (only one is shown), and a large number of vehicles 14 (only one is shown) via the network 10. A navigation device (not shown) is connected, and the following various data are input from these elements. In the following description, it is assumed that the vehicle 14 is powered by an internal combustion engine.

Specifically, the weather data is input from the weather server 11 to the data processing server 2. This weather data links the mesh code of the country of use of the vehicle with the weather and the time stamp at the time of measuring the weather.

Further, the manufacturing data is input from the factory 12 to the data processing server 2. This manufacturing data is associated with the vehicle ID, the time stamp at the time of manufacturing the vehicle, the name of the manufacturing factory, the manufacturing lot number of the vehicle, and the like.

Further, the dealer data is input from the dealer 13 to the data processing server 2. This dealer data is associated with the vehicle ID, the time stamp at the time of maintenance or repair of the vehicle, the dealer name, the maintenance content or the repair content of the vehicle, and the like. In the following description, the manufacturing data and the dealer data are collectively referred to as "vehicle condition data".

Further, the movement state data, the fuel consumption data, and the navigation data are input to the data processing server 2 from the navigation device (mobile station) of the vehicle 14. These movement state data, fuel consumption data, and navigation data are sampled in a predetermined control cycle from the time when the ignition switch of the vehicle 14 is turned on to the time when the ignition switch is turned off, and the sampling result is input to the data processing server 2. Will be done. In that case, the data sampled at the timing when the ignition switch is turned off is input to the data processing server 2 from the navigation device at the timing when the ignition switch is turned on next time.

The movement state data is obtained by associating the position of the vehicle 14, which is the position (longitude, latitude) of the navigation device, the time stamp at the time of sampling of the position, and the user ID with each other. Is called "FCD". Further, the fuel consumption data is a combination of the fuel consumption of the vehicle 14, the time stamp at the time of sampling the fuel consumption, and the user ID.

Further, the navigation data includes the departure point in the navigation device of the vehicle 14, the setting state of the destination, the calculation result of the latitude / longitude of the current location, the calculation result of the route from the departure point to the destination, and the time at the time of sampling these data. The stamp and the user ID are associated with each other.

In the following explanation, when weather data, vehicle condition data, movement condition data, fuel consumption data, and navigation data are input, the time stamps included in these data are collectively referred to as "sampling time stamp". ..

The data processing server 2 creates the linked data by the linked data creation process described later, and outputs it to the integrated processing server 3.

In the integrated processing server 3, a data mart is created by the data integration processing described later using the linked data input from the data processing server 2, and the data mart is encrypted to create an encrypted data mart, and this encryption is also performed. Output the data mart to the integrated database server 4. In the present embodiment, the integrated processing server 3 corresponds to the data group creating means and the registered data creating means, and the data mart and the encrypted data mart correspond to the data group and the registered data, respectively.

The integrated database server 4 stores the encrypted data mart input from the integrated processing server 3 in the storage area as described later.

Next, the above-mentioned association data creation process will be described with reference to FIG. In this processing, associating data is created using various data (that is, movement state data, fuel consumption data, navigation data, vehicle condition data, and weather data) input to the data processing server 2, and the integrated processing server 3 is used for this processing. It is output to the data processing server 2, and is executed in a predetermined control cycle ΔT (for example, 5 min).

As shown in the figure, first, various data input to the data processing server 2 are read (FIG. 2 / STEP1). Next, the time stamp at the time of reading (hereinafter referred to as "time stamp at the time of reading") is associated with the various data read (FIG. 2 / STEP2).

Next, it is determined whether or not the user ID in the data associated with the read time stamp matches the user ID of the user information data stored in the data processing server 2 (FIG. 2 / STEP3).

When this determination is affirmative (FIG. 2 / STEP3 ... YES), that is, when the data associated with the read time stamp is data having a user ID (FCD, fuel consumption data, or navigation data), the read time. The vehicle ID corresponding to the user ID of the user information data is associated with the data associated with the stamp (FIG. 2 / STEP4).

Next, the associating data (that is, FCD, fuel consumption data, or navigation data) that has been associated as described above is output to the integrated processing server 3 (FIG. 2 / STEP5). After that, this process ends.

On the other hand, when the above-mentioned determination is negative (FIG. 2 / STEP3 ... NO), that is, when the data associated with the read time stamp is data without a user ID (vehicle status data or weather data), the data is read. It is determined whether or not the vehicle ID in the data associated with the time stamp matches the vehicle ID of the user information data stored in the data processing server 2 (FIG. 2 / STEP6).

When this determination is affirmative (FIG. 3 / STEP6 ... YES), that is, when the data associated with the read time stamp is the vehicle status data having the vehicle ID, the user information is obtained with respect to this vehicle status data. The user ID corresponding to the vehicle ID of the data is associated (FIG. 2 / STEP7).

Next, the linking data, which is the vehicle status data obtained by performing the above linking process, is output to the integrated processing server 3 (FIG. 2 / STEP 5). After that, this process ends.

On the other hand, when the above-mentioned determination is negative (FIG. 2 / STEP6 ... NO), that is, when the data associated with the read time stamp is weather data that does not have the user ID and the vehicle ID, only the read time stamp is used. The linked data, which is the weather data associated with the above, is output to the integrated processing server 3 as it is (FIG. 2 / STEP5). After that, this process ends.

Next, the data integration process will be described with reference to FIG. In this process, an encrypted data mart is created using the associated data input from the data processing server 2, and the created encrypted data mart is output to the integrated database server 4, which is the integrated processing server 3. , Is executed in the predetermined control cycle ΔT described above.

As shown in the figure, first, the associated data input from the data processing server 2 is stored in the storage area (FIG. 3 / STEP20).

Next, it is determined whether or not it is the creation timing of the encrypted data mart (FIG. 3 / STEP21). This creation timing is set to a predetermined timing of the day (for example, 24:00).

When this determination is negative (FIG. 3 / STEP21 ... NO), the present process is terminated as it is.

On the other hand, when this determination is affirmative (FIG. 3 / STEP21 ... YES), a provisional data mart of FCD-fuel consumption is created (FIG. 3 / STEP22). This FCD-provisional fuel consumption data mart (first data group) searches for FCD and fuel consumption data for the last 30 days stored in the storage area using the user ID and vehicle ID as keys, and links them to each other. Is created as a data group (map) in which the user ID, the vehicle ID, the FCD, the fuel consumption data, the time stamp at the time of sampling the fuel consumption data, and the time stamp at the time of reading the fuel consumption data are linked to each other.

Next, a provisional data mart for FCD-navigation is created (Fig. 3 / STEP23). Specifically, the creation of the provisional data mart (second data group) of the FCD-navigation is executed as shown in FIG.

As shown in the figure, first, using the user ID and vehicle ID as keys, the FCD and navigation data for the last 30 days are compared, and whether or not the latitude / longitude of the FCD and the navigation data, that is, the vehicle position, completely match. (Fig. 4 / STEP40).

When this judgment is negative (Fig. 4 / STEP40 ... NO), that is, when the latitude / longitude of the FCD and the navigation data do not completely match, the data having the closest latitude / longitude of the FCD and the navigation data are linked to each other. (Fig. 4 / STEP41).

On the other hand, when this determination is affirmative (FIG. 4 / STEP40 ... YES), it is determined whether or not there is one data in which the latitude and longitude completely match (FIG. 4 / STEP42).

When this determination is affirmative (FIG. 4 / STEP42 ... YES), the FCD and the navigation data are associated with each other (FIG. 4 / STEP43).

On the other hand, when the above judgment is negative (Fig. 4 / STEP42 ... NO) and there are multiple data whose latitude and longitude are exactly the same, the data at the time of sampling of the navigation data and the data at the time of sampling of the FCD are the closest. Link each other (Fig. 4 / STEP44).

Following the above linking process, it is determined whether or not the linking of all the data is completed (FIG. 4 / STEP45). When this determination is negative (FIG. 4 / STEP45 ... NO), the above processing is executed again.

On the other hand, when this determination is affirmative (FIG. 4 / STEP45 ... YES), that is, when the association between the FCD and the navigation data for the last 30 days is completed, this process ends. Based on the above, the FCD-Navi provisional data mart is data in which the user ID, vehicle ID, FCD, navigation data, navigation data sampling time stamp, and navigation data reading time stamp are linked to each other. Created as a group (map).

Returning to FIG. 3, after creating the provisional data mart of FCD-navigation as described above, the provisional data mart of FCD-weather is created (FIG. 3 / STEP24). Specifically, the mesh code is associated with these FCDs based on the latitude / longitude data of the FCDs stored in the storage area for the last 30 days. Next, the FCD and the weather data are compared, the mesh codes matching each other are searched, and the matching mesh codes are linked to each other. Based on the above, the FCD-weather provisional data mart (third data group) can read the user ID, vehicle ID, mesh code, FCD, weather data, weather data sampling time stamp, and weather data. It is created as a data group (map) in which hour time stamps are linked to each other.

Next, a provisional data mart of FCD-vehicle status is created (Fig. 3 / STEP25). This FCD-provisional data mart of vehicle status (fourth data group) searches for FCD and vehicle status data for the last 30 days stored in the storage area using the user ID and vehicle ID as keys, and links them to each other. By doing so, as a data group (map) in which the user ID, the vehicle ID, the FCD, the vehicle status data, the sampling time stamp of the vehicle status data, and the reading time stamp of the vehicle status data are linked to each other. Will be created.

Next, a data mart is created (Fig. 3 / STEP26). Specifically, by using the user ID and the vehicle ID as keys and associating the four provisional data marts created as described above with each other, the data mart can be a user ID, a vehicle ID, an FCD, and a navigation system. It is created as a data group (map) in which data, weather data, vehicle condition data, sampling time stamp, and reading time stamp are linked to each other.

The data mart is then compressed into Lzo format data using the Lzo algorithm (FIG. 3 / STEP27). After that, the encrypted data mart creation process is executed (FIG. 3 / STEP28). Specifically, this encrypted data mart creation process is executed as shown in FIG.

As shown in the figure, first, the encryption condition flag F_ENC is read (FIG. 5 / STEP50). The encryption condition flag F_ENC is set by the administrator of the integrated processing server 3 to any of "1" to "5" according to the purpose of use (analysis purpose) of the data mart as described below.

(A) When there is no problem in data analysis even if the vehicle ID changes at a certain position, for example, when it is desired to analyze the traffic volume / congestion at a specific intersection, the encryption condition flag F_ENC is set to "1". To.
(B) When there is no problem in data analysis even if the vehicle ID changes in a certain period of time, for example, when it is desired to analyze the trade area of a tourist spot or a store, the encryption condition flag F_ENC is set to "2".
(C) When it is desired to analyze the user's movement preference, the encryption condition flag F_ENC is set to "3".
(D) When it is desired to analyze the usage method in the market for each vehicle type, the encryption condition flag F_ENC is set to "4".
(E) For purposes other than the above (a) to (d), the encryption condition flag F_ENC is set to "5".

Next, it is determined whether or not the read encryption condition flag F_ENC is "1" (FIG. 5 / STEP51). When this determination is affirmative (FIG. 5 / STEP51 ... YES), the encryption key is set to be a combination of a part of the mesh code and the fixed key (FIG. 5 / STEP52). This fixed key is preset.

On the other hand, when the above-mentioned determination is negative (FIG. 5 / STEP51 ... NO), that is, when F_ENC ≠ 1, it is determined whether or not the encryption condition flag F_ENC is "2" (FIG. 5 / STEP53). .. When this determination is affirmative (FIG. 5 / STEP53 ... YES), the encryption key is set to be a combination of a part of the sampling time stamp of the navigation data and the fixed key (FIG. 5 / STEP54).

On the other hand, when the above-mentioned determination is negative (FIG. 5 / STEP53 ... NO), that is, when F_ENC ≠ 1 and 2, it is determined whether or not the encryption condition flag F_ENC is "3" (FIG. 5 /. STEP55). When this determination is affirmative (FIG. 5 / STEP55 ... YES), the encryption key is set to be a combination of a part of the user ID and the fixed key (FIG. 5 / STEP56).

On the other hand, when the above-mentioned determination is negative (FIG. 5 / STEP55 ... NO), that is, when F_ENC ≠ 1 to 3, it is determined whether or not the encryption condition flag F_ENC is "4" (FIG. 5 /. STEP57). When this determination is affirmative (FIG. 5 / STEP57 ... YES), the encryption key is set to be a combination of a part of the vehicle ID and the fixed key (FIG. 5 / STEP58).

On the other hand, when the above-mentioned determination is negative (FIG. 5 / STEP57 ... NO), that is, when F_ENC = 5, the encryption key is set as the fixed key (FIG. 5 / STEP59).

As described above, after setting the encryption key according to the value of the encryption condition flag F_ENC, the vehicle ID and the user in the data mart are used by a predetermined encryption algorithm (for example, SHA-256) using the encryption key. The ID is encrypted (Fig. 5 / STEP60).

Next, an encrypted data mart is created by associating the vehicle type data and the encryption condition flag with the data mart in which the vehicle ID and the user ID are encrypted (FIG. 5 / STEP61). This vehicle type data corresponds to a part of the vehicle ID. After that, this process ends.

Returning to FIG. 3, after executing the encrypted data mart creation process as described above, the encrypted data mart is output to the integrated database server 4 (FIG. 3 / STEP29). After that, this process ends.

Next, the data storage process will be described with reference to FIG. This process stores the encrypted data mart input from the integrated processing server 3 in the storage area in the integrated database server 4, and is executed every time the encrypted data mart is input.

As shown in the figure, first, the encrypted data mart is read (FIG. 6 / STEP80). Next, the vehicle type is determined based on the vehicle type data included in the encrypted data mart (FIG. 6 / STEP81). Hereinafter, the determined vehicle type is referred to as a "judgment vehicle type".

Next, it is determined whether or not the encryption condition flag F_ENC included in the encrypted data mart is "1" (FIG. 6 / STEP82).

When this determination is affirmative (FIG. 6 / STEP82 ... YES), the encrypted data mart is stored as registered data in the first area for the determination vehicle model (FIG. 6 / STEP83). After that, this process ends.

On the other hand, when the above-mentioned determination is negative (FIG. 6 / STEP82 ... NO), that is, when F_ENC ≠ 1, it is determined whether or not the encryption condition flag F_ENC is "2" (FIG. 6 / STEP84).

When this determination is affirmative (FIG. 6 / STEP84 ... YES), the encrypted data mart is stored as registered data in the second area for the determination vehicle model (FIG. 6 / STEP85). After that, this process ends.

On the other hand, when the above-mentioned determination is negative (FIG. 6 / STEP84 ... NO), that is, when F_ENC ≠ 1 and 2, it is determined whether or not the encryption condition flag F_ENC is "3" (FIG. 6 / STEP86). ).

When this determination is affirmative (FIG. 6 / STEP86 ... YES), the encrypted data mart is stored as registered data in the third area for the determination vehicle model (FIG. 6 / STEP87). After that, this process ends.

On the other hand, when the above-mentioned determination is negative (FIG. 6 / STEP86 ... NO), that is, when F_ENC ≠ 1 to 3, it is determined whether or not the encryption condition flag F_ENC is "4" (FIG. 6 / STEP88). ).

When this determination is affirmative (FIG. 6 / STEP88 ... YES), the encrypted data mart is stored as registered data in the fourth area for the determination vehicle model (FIG. 6 / STEP89). After that, this process ends.

On the other hand, when this determination is negative (FIG. 6 / STEP88 ... NO), that is, when F_ENC = 5, the encrypted data mart is stored as registered data in the fifth area for the determination vehicle model (FIG. 6 / STEP90). .. After that, this process ends.

As described above, according to the data registration system 1 of the present embodiment, the FCD, the weather data, the vehicle condition data, the fuel consumption data and the navigation data, which are input via the network 10, and the vehicle ID and the user ID are linked to each other. A data mart is created as the attached data group, and this is compressed. Further, an encrypted data mart is created by encrypting only the vehicle ID and the user ID of the compressed data mart by the encryption algorithm using the encryption key, and this is stored in the storage area in the integrated database server 4 as registered data. Will be done.

In this case, the FCD, the weather data, the vehicle condition data, the fuel consumption data, and the navigation data are highly effective when the data related to the vehicle is converted into big data and analyzed. Therefore, such highly effective data. Can be registered efficiently while increasing its confidentiality.

In addition, create a provisional data mart for FCD-fuel consumption, a provisional data mart for FCD-navigation, a provisional data mart for FCD-weather, and a provisional data mart for FCD-vehicle conditions, and link these provisional data marts together. As a result, the data mart is created, so that the load at the time of creating the data mart can be reduced as compared with the case where the data mart is created all at once.

In addition to this, in the process of creating the provisional data mart of FCD-navigation shown in FIG. 4, when the latitude / longitude of the FCD and the navigation data, that is, the vehicle positions at the time of sampling do not completely match each other, the latitude of the FCD and the navigation data. -Since the data with the closest longitude are linked to each other, the provisional data mart of FCD-Navi is linked while linking the data estimated to be highly relevant because the vehicle position at the time of sampling is the closest. Can be created.

On the other hand, when there are multiple data in which the latitude and longitude of the FCD and the navigation data are exactly the same, the data with the closest sampling time stamp among the multiple data are linked to each other, so the sampling time stamp. By the fact that is the closest, it is possible to create a provisional data mart for FCD-Navi while associating data that are presumed to be highly relevant. As a result, the accuracy of creating the provisional data mart of the FCD-navigation can be improved.

Also, since the data mart is compressed and then encrypted, the size of the encrypted data mart can be reduced. As a result, the number of registered data stored can be relatively increased with respect to the storage area having the same capacity while improving the security of the registered data.

In the embodiment, FCD-provisional fuel consumption data mart, FCD-navigation provisional data mart, FCD-weather provisional data mart, and FCD-vehicle condition provisional data mart are created, and these four provisional data marts are created. This is an example of creating a data mart as a data group by linking them together, but FCD-provisional fuel consumption data mart, FCD-navigation provisional data mart, and FCD-weather provisional data mart are linked together. By doing so, it may be configured to create a data mart as a data group.

In that case, STEP 25 in FIG. 3 of the embodiment may be omitted, and a data mart as a data group may be created by the same method as STEP 22 to 24, 26 described above.

Further, the embodiment is an example in which a navigation device is used as the mobile station, but the mobile station of the present invention is not limited to this, and may be any one that moves at the same time as the vehicle. For example, a mobile information terminal such as a smartphone may be used as the mobile station.

In that case, the mobile information terminal is configured to perform data communication with the vehicle's ECU and navigation device, and receive the vehicle ID and / or user ID data on the mobile information terminal side. As the movement state data, the data associated with the position (latitude, longitude) of the mobile information terminal, the time stamp at the time of sampling of the position, the user ID, etc. can be obtained from any of the mobile information terminal, the vehicle ECU, and the navigation device. It may be configured to be input to the data processing server 2.

Further, when the mobile information terminal is used as a mobile station, the user can use the mobile information terminal not only during the period from when the ignition switch of the vehicle is turned on to when the ignition switch of the vehicle is turned off but also after the ignition switch of the vehicle is turned off. The result of performing future route calculation or the like may be input to the data processing server 2 from the mobile information terminal as navigation data, and the movement state data may be input to the data processing server 2 from the mobile information terminal. Further, in such a configuration, for example, data that does not change while the ignition switch of the vehicle is off (that is, fuel consumption data, etc.) may be used as constant value or empty data to create a data mart.

Further, the embodiment is an example in which the vehicle ID and the user ID are used as the vehicle identification data, but the vehicle identification data of the present invention is not limited to this, and is for specifying at least one of the vehicle and the user of the vehicle. It should be. For example, the vehicle ID or the user ID may be used as the vehicle specific data. In that case, for example, in the associative data creation process of FIG. 2, only one of the vehicle ID and the user ID is associated with the data other than the weather data, and in STEP 22 to 26 of FIG. The data mart may be created using only one of the vehicle ID and the user ID as a key.

On the other hand, the embodiment is an example in which the data registration system of the present invention is applied to a vehicle powered by an internal combustion engine, but the data registration system of the present invention is not limited to this and uses a power source other than the internal combustion engine as a power source. It can also be applied to vehicles. For example, it can be applied to fuel cell vehicles and electric vehicles.

Further, the embodiment is an example in which fuel consumption is used as the consumption ratio data, but the consumption ratio data of the present invention is not limited to this, and may be any data representing the energy consumption ratio of the vehicle. For example, in the case of a fuel cell vehicle, the hydrogen consumption ratio corresponds to the consumption ratio data, and in the case of an electric vehicle, the electric power consumption ratio corresponds to the consumption ratio data.

Further, the embodiment is an example in which the Lzo algorithm is used as the compression algorithm when compressing the data mart, but the compression algorithm when compressing the data mart is not limited to this, as long as the data can be compressed. good. For example, Gzip or the like may be used as a compression algorithm when creating a data mart.

On the other hand, in the embodiment, the data mart is created by the method shown in FIG. 3, but the data mart creation method is not limited to this. For example, in the method of FIG. 3, a data mart may be created by omitting STEP 25 and 26 and associating the weather data and the vehicle condition data with the two provisional data marts created in STEP 22 and 23.

Further, the embodiment is an example in which an encrypted data mart is created by encrypting the compressed data mart and the encrypted data mart is stored in the integrated database server 4 as registered data. May be configured to be stored in the integrated database server 4 as it is without being encrypted.

Further, although the embodiment is an example in which the data registration system is configured by three servers, the data registration system may be configured by two or less or four or more servers.

1 Data registration system 2 Data processing server (data receiving means)
3 Integrated processing server (data group creation means, registration data creation means)
4 Integrated database server (data storage means)
10 network 14 vehicle

Claims (7)

Movement state data showing the time-series movement state of the mobile station, consumption ratio data showing the energy consumption ratio of the vehicle moving at the same time as the mobile station, navigation data showing the navigation calculation result and the setting state of the vehicle, and navigation data. A plurality of types of data including weather data representing the weather in the area where the mobile station is located and vehicle identification data for identifying at least one of the vehicle and the owner of the vehicle are input via a network. Data receiving means and
A data group creating means for creating a data group in which the moving state data, the consumption ratio data, the navigation data, the weather data, and the vehicle specific data are linked to each other.
A registration data creation means that compresses the data group by a predetermined compression algorithm and creates registration data using the compressed data group, and
A data storage means for storing the registered data in the storage area,
A data registration system characterized by being equipped with. The data group creating means links the first data group in which the vehicle identification data, the movement state data, and the consumption ratio data are linked to each other, and the vehicle identification data, the movement state data, and the navigation data to each other. The attached second data group and the third data group in which the movement state data and the weather data are linked to each other are created, and the data group is created using the first to third data groups. The data registration system according to claim 1. The plurality of types of data further include vehicle status data representing at least one of the manufacturing status and the repair status of the vehicle.
The data group creating means obtains the data group by further associating the vehicle status data with each other in addition to the movement state data, the consumption ratio data, the navigation data, the weather data, and the vehicle specific data. The data registration system according to claim 1, wherein the data is created. The data group creating means links the first data group in which the vehicle identification data, the movement state data, and the consumption ratio data are linked to each other, and the vehicle identification data, the movement state data, and the navigation data to each other. The attached second data group, the third data group in which the moving state data and the weather data are linked to each other, and the fourth data group in which the vehicle specific data, the moving state data, and the vehicle status data are linked to each other. The data registration system according to claim 3, wherein a data group is created, and the data group is created using the first to fourth data groups. The movement state data and the navigation data include the vehicle position at the time of sampling as data.
When the data group creating means creates the second data group and the vehicle positions at the time of sampling in the moving state data and the navigation data do not match each other, the moving state data and the navigation data The data registration system according to claim 2 or 4, wherein the data having the closest vehicle positions at the time of sampling are linked to each other. The movement state data and the navigation data include a time stamp at the time of sampling and a vehicle position at the time of sampling as data.
In the case of creating the second data group, when the data group creating means has a plurality of data in which the vehicle positions at the time of sampling in the moving state data and the navigation data match each other, among the plurality of data. The data registration system according to any one of claims 2, 4 and 5, wherein the data having the closest time stamps at the time of sampling are associated with each other. The data registration system according to any one of claims 1 to 6, wherein the registered data creating means creates the registered data by encrypting the compressed data group with a predetermined encryption algorithm. ..

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