JP2019149147A - Data registration system - Google Patents

Abstract

To provide a data registration system that can efficiently register effective data related to vehicles and the like.SOLUTION: A data registration system 1 includes an integration processing server 3 and an integrated database server 4. The integration processing server 3 creates a data mart associating FCD, weather data, vehicle state data, fuel consumption data, navigation data, vehicle ID, and user ID with each other (STEP 22-26), compresses the data mart by Lzo algorithm, and encrypts the compressed data mart to create an encrypted data mart (STEP 27-28). The integrated database server 4 stores the encrypted data mart in a storage area (STEP 80-90).SELECTED DRAWING: Figure 3

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, what was described in patent document 1 is known as a management system of vehicle operation data. This management system includes an in-vehicle device and an operation management device, and the in-vehicle device detects the travel speed, travel distance, acceleration, geographical position, driving operation, and fuel injection amount from various devices and various sensors of the vehicle. Etc. are acquired as operation data.

  In this in-vehicle device, after the start of operation data acquisition, the operation data and identification information for identifying the driver are associated (associated) and stored, and associated when there is a closing operation by the driver. The operation data and identification information are transmitted to the operation management device.

JP 2017-27545 A

  In recent years, in various fields, it has been desired that data is sequentially registered and converted into big data, which is analyzed and used. This is also true for data related to vehicles and the like. On the other hand, the management system of Patent Document 1 has a problem in that highly effective data cannot be efficiently registered because it is not premised on making the data big data and utilizing it.

  SUMMARY An advantage of some aspects of the invention is that it provides 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 movement state data representing a time-series movement state of a mobile station (navigation device, portable information terminal), and a vehicle 14 that moves simultaneously with the mobile station. A plurality of types of data including consumption ratio data representing the energy consumption ratio of the vehicle, 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 exists, Data receiving means (data processing server 2) in which vehicle specifying data (vehicle ID, user ID) for specifying at least one of the owners of the vehicle 14 is input via the network 10, movement state data, and consumption Data that creates a data group (data mart) that links ratio data, navigation data, weather data, and vehicle specific data Compressing the creation means (integrated processing server 3, STEP22-26) and data group (data mart) with a predetermined compression algorithm (Lzo algorithm), and creating registration data using the compressed data group (data mart) Registration data creation means (integrated processing server 3, STEP 27 to 28) and data storage means (integrated database server 4, STEP 80 to 90) for storing registration 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 identification data are linked to each other is created. In this case, the movement state data indicates the time-series movement state of the mobile station, the consumption ratio data indicates the energy consumption ratio of the vehicle moving simultaneously with the mobile station, the navigation data indicates the navigation calculation result and setting state of the vehicle, and the weather data. Represents the weather in the area where the vehicle exists, and the vehicle identification data is for identifying the vehicle and / or the user of the vehicle. It becomes highly effective when analyzing data related to the big data. Furthermore, while compressing the data group by a predetermined compression algorithm, using the compressed data group, registration data is created and the registration data is stored in the storage area, so the size of the registration data can be reduced, Thereby, the number of stored registration data can be relatively increased with respect to the storage area having the same capacity. As described above, it is possible to efficiently register highly effective data (in addition, “navigation data representing the vehicle navigation calculation result and setting state” in this specification refers to the calculation result of the navigation device mounted on the vehicle. In addition to the data indicating the setting state, the route calculation or the position calculation is performed based on the data received from the navigation device of the vehicle in the server or the portable information terminal, and the data when the calculation result is transmitted to the navigation device is used. Including).

  In the present invention, the data group creation means includes a first data group (FCD-provisional data mart of fuel consumption) in which vehicle identification data (vehicle ID, user ID), movement state data, and consumption rate data are linked to each other, A second data group (FCD-Navi provisional data mart) associated with specific data (vehicle ID, user ID), movement state data, and navigation data, and movement state data and weather data associated with each other. It is preferable to create three data groups (FCD-temporary data mart of weather) and create a data group (data mart) using the first to third data groups.

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

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

  According to this data registration system, the vehicle status data representing at least one of the manufacturing status and repair status of the vehicle in addition to the vehicle identification data, the movement status data, the consumption rate data, the navigation data, and the weather data is further included as a data group. Since the data group is created by linking each other, the effectiveness of the data group when the data is converted into big data and analyzed can be further enhanced.

  In the present invention, the data group creation means includes a first data group (FCD-provisional data mart of fuel consumption) in which vehicle identification data (vehicle ID, user ID), movement state data, and consumption rate data are linked to each other, A second data group (FCD-Navi provisional data mart) associated with specific data (vehicle ID, user ID), movement state data, and navigation data, and movement state data and weather data associated with each other. 3 data group (FCD-temporary data mart of weather), fourth data group (FCD-provisional data of vehicle situation) in which vehicle identification data (vehicle ID, user ID), movement state data, and vehicle situation data are linked to each other It is preferable to create a data group (data mart) 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 associated with each other, the second data group in which the movement state data and the weather data are associated with each other, the movement state data and the navigation data. Since the third data group linked to each other and the fourth data group linked to each other of the movement state data and the vehicle status data are created, the data group is created using the first to fourth data groups. Compared with the case where a data group is created at a time, the load at the time of creating the data group can be reduced.

  In the present invention, the movement state data and the navigation data are provided with the vehicle position at the time of sampling as data, and the data group creation means, when creating the second data group, at the time of sampling in the movement state data and the navigation data When the vehicle positions do not coincide with each other, it is preferable to associate the data of the movement state data and the navigation data that have the closest vehicle positions at the time of sampling (STEPs 40 and 41).

  According to this data registration system, when the second data group is created, if the vehicle positions at the time of sampling in the movement state data and the navigation data do not coincide with each other, the sampling state of the movement state data and the navigation data Since the data with the closest vehicle position are linked to each other, the second data group is created while linking the data that are estimated to be highly relevant due to the closest vehicle position at the time of sampling. Can do. Thereby, the creation accuracy of 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 creation means creates the second data group, When there are a plurality of pieces of data in which the vehicle positions at the time of sampling in the navigation data coincide with each other, it is preferable to link the data with the closest time stamp at the time of sampling among the plurality of data (STEP 40, 42, 44). .

  According to this data registration system, when the second data group is created, 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 coincide with each other, Since the data with the closest time stamps are linked to each other, the second data group is created while linking the data that are estimated to be highly relevant because the time stamps at the time of sampling are the closest. And the production accuracy can be improved.

  Preferably, the registration data creating means creates registration data by encrypting the compressed data group with a predetermined encryption algorithm (STEP 28).

  According to this data registration system, the registration data is created by encrypting the 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 a tied data creation process. It is a flowchart which shows a data integration process. It is a flowchart which shows the provisional data mart creation process of FCD-navi. It is a flowchart which shows an encryption data mart creation process. It is a flowchart which shows a data storage process.

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

  Each of the 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 input / output data in the memory.

  The data processing server 2 executes an association data creation process, which will be described later, and stores a large amount of user information data in a storage area. This user information data is obtained by associating personal information of a user of a vehicle, a user registration date, a user ID, and a vehicle ID with each other, and the above-mentioned data via an input interface (not shown) by a server administrator. Are created using these. In the present embodiment, the data processing server 2 corresponds to data receiving means, and the user ID and vehicle ID correspond to vehicle specifying data.

  The data processing server 2 includes, via a network 10, a weather server 11, a number of factories 12 (only one shown), a number of dealers 13 (only one shown), and a number of vehicles 14 (only one shown). 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 the internal combustion engine.

  Specifically, weather data is input from the weather server 11 to the data processing server 2. This weather data is obtained by associating the mesh code of the country in which the vehicle is used, the weather, and the time stamp when the weather is measured.

  In addition, manufacturing data is input from the factory 12 to the data processing server 2. This manufacturing time data is obtained by associating a vehicle ID, a time stamp at the time of manufacturing the vehicle, a manufacturing factory name, a manufacturing lot number of the vehicle, and the like.

  Further, dealer data is input from the dealer 13 to the data processing server 2. This dealer data is obtained by associating a vehicle ID, a time stamp at the time of maintenance or repair of the vehicle, a dealer name, and details of maintenance or repair of the vehicle. In the following description, manufacturing data and dealer data are collectively referred to as “vehicle status 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 at a predetermined control period from when the ignition switch of the vehicle 14 is turned on until it is turned off, and the sampling results are input to the data processing server 2. Is done. In this case, the data sampled at the timing when the ignition switch is turned off is input from the navigation device to the data processing server 2 at the timing when the next ignition switch is turned on.

  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. Is called "FCD". The fuel consumption data is obtained by associating the fuel consumption of the vehicle 14, the time stamp when the fuel consumption is sampled, and the user ID.

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

  In the following description, when weather data, vehicle status data, movement state 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 tied data by a tied data creation process described later, and outputs it to the integrated processing server 3.

  The integrated processing server 3 creates a data mart from the data integration processing described later using the association data input from the data processing server 2 and encrypts the data mart to create an encrypted data mart. The consolidated data mart is output to the integrated database server 4. In the present embodiment, the integrated processing server 3 corresponds to the data group creation unit and the registration data creation unit, and the data mart and the encrypted data mart correspond to the data group and the registration data, respectively.

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

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

  As shown in the figure, first, various data input to the data processing server 2 are read (FIG. 2 / STEP 1). Next, a time stamp at the time of reading (hereinafter referred to as a “time stamp at the time of reading”) is associated with the various types of read data (FIG. 2 / STEP 2).

  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 / STEP 3).

  When this determination is affirmative (FIG. 2 / STEP3... YES), that is, when the data associated with the read time stamp is data (FCD, fuel consumption data or navigation data) provided with the user ID, 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 / STEP 4).

  Next, the pegging data (that is, FCD, fuel consumption data or navigation data) subjected to pegging as described above is output to the integrated processing server 3 (FIG. 2 / STEP 5). Thereafter, this process is terminated.

  On the other hand, when the above-described determination is negative (FIG. 2 / STEP3... NO), that is, when the data associated with the read time stamp is data that does not have a user ID (vehicle status data or weather data), 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 / STEP 6).

  When this determination is affirmative (FIG. 3 / STEP 6... YES), that is, when the data associated with the reading time stamp is the vehicle status data provided with the vehicle ID, the user information The user ID corresponding to the vehicle ID of the data is linked (FIG. 2 / STEP7).

  Next, the linking data that is the vehicle status data subjected to the above linking process is output to the integrated processing server 3 (FIG. 2 / STEP 5). Thereafter, this process is terminated.

  On the other hand, when the above-mentioned determination is negative (FIG. 2 / STEP6... NO), that is, when the data associated with the reading time stamp is weather data that does not include the user ID and the vehicle ID, only the reading time stamp. Is output as it is to the integrated processing server 3 (STEP 5 in FIG. 2). Thereafter, this process is terminated.

  Next, the data integration process will be described with reference to FIG. This process is to create an encrypted data mart using the association data input from the data processing server 2 and to output the created encrypted data mart to the integrated database server 4. This is executed at the predetermined control period ΔT described above.

  As shown in the figure, first, the association data input from the data processing server 2 is stored in the storage area (FIG. 3 / STEP 20).

  Next, it is determined whether it is the creation timing of the encrypted data mart (FIG. 3 / STEP 21). This creation timing is set to a predetermined timing (for example, 24:00) in one day.

  When this determination is negative (FIG. 3 / STEP 21... NO), this processing is terminated as it is.

  On the other hand, when this determination is affirmative (FIG. 3 / STEP 21... YES), an FCD-fuel consumption provisional data mart is created (FIG. 3 / STEP 22). This FCD-fuel economy provisional data mart (first data group) searches the FCD and fuel economy data for the last 30 days stored in the storage area using the user ID and vehicle ID as keys, and associates them with each other. Thus, a user ID, a vehicle ID, an FCD, fuel consumption data, a time stamp at the time of sampling of the fuel consumption data, and a time stamp at the time of reading of the fuel consumption data are created as a data group (map).

  Next, a provisional data mart for FCD-Navi is created (FIG. 3 / STEP 23). The creation of the provisional data mart (second data group) of the FCD-navigation is specifically 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 the latitude / longitude of the FCD and navigation data, that is, whether or not the vehicle position is completely matched. Is determined (FIG. 4 / STEP 40).

  When this determination is negative (FIG. 4 / STEP 40... NO), that is, when the latitude and longitude of the FCD and navigation data do not completely match, the data having the closest latitude and longitude of the FCD and navigation data are linked. (FIG. 4 / STEP 41).

  On the other hand, when this determination is affirmative (FIG. 4 / STEP 40... YES), it is determined whether or not there is only one piece of data in which the latitude and longitude coincide completely (FIG. 4 / STEP 42).

  If this determination is affirmative (FIG. 4 / STEP 42... YES), the FCD and the navigation data are linked to each other (FIG. 4 / STEP 43).

  On the other hand, when the above determination is negative (FIG. 4 / STEP 42... NO) and there are a plurality of data whose latitude / longitude coincide completely, the data at which the navigation data sampling time stamp is the closest to the FCD sampling time stamp. They are linked to each other (FIG. 4 / STEP 44).

  Following the above linking process, it is determined whether or not all data has been linked (FIG. 4 / STEP 45). When this determination is negative (FIG. 4 / STEP 45... NO), the above processing is executed again.

  On the other hand, when this determination is affirmative (FIG. 4 / STEP 45... YES), that is, when the association between the FCD and the navigation data for the last 30 days is completed, this processing is terminated. As described above, the provisional data mart of FCD-Navi is data in which the user ID, vehicle ID, FCD, navigation data, navigation data sampling time stamp, and navigation data reading time stamp are associated with each other. Created as a group (map).

  Returning to FIG. 3, after the FCD-Navi provisional data mart is created as described above, the FCD-weather provisional data mart is created (FIG. 3 / STEP 24). More specifically, mesh codes are linked to these FCDs based on the latitude and longitude data of FCDs for the last 30 days stored in the storage area. Next, the FCD and the weather data are compared to search for a matching mesh code, and match each other with each other. As described above, the provisional data mart (third data group) of FCD-weather reads 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 the time stamp is linked to each other.

  Next, a provisional data mart of FCD-vehicle status is created (FIG. 3 / STEP 25). This FCD-vehicle status provisional data mart (fourth data group) searches the last 30 days of FCD and vehicle status data stored in the storage area using the user ID and vehicle ID as keys, and links them together. As a data group (map) in which the user ID, the vehicle ID, the FCD, the vehicle situation data, the vehicle situation data sampling time stamp, and the vehicle situation data reading time stamp are associated with each other. Created.

  Next, a data mart is created (FIG. 3 / STEP 26). Specifically, by associating the four provisional data marts created as described above with the user ID and the vehicle ID as keys, the data mart can have the user ID, the vehicle ID, the FCD, the navigation, Data, weather data, vehicle status data, sampling time stamp, and reading time stamp are created as a data group (map) associated with each other.

  Next, the data mart is compressed into data in the Lzo format using the Lzo algorithm (FIG. 3 / STEP 27). Thereafter, an encrypted data mart creation process is executed (FIG. 3 / STEP 28). Specifically, the encrypted data mart creation processing is executed as shown in FIG.

  As shown in the figure, first, the encryption condition flag F_ENC is read (FIG. 5 / STEP 50). The encryption condition flag F_ENC is set to any one of “1” to “5” by the administrator of the integrated processing server 3 according to the use purpose (analysis purpose) of the data mart as described below.

(A) The encryption condition flag F_ENC is set to “1” when there is no problem in data analysis even when the vehicle ID changes at a certain position, for example, when it is desired to analyze the traffic volume / congestion level of a specific intersection. The
(B) The encryption condition flag F_ENC is set to “2” when there is no problem in data analysis even if the vehicle ID changes in a certain amount of time, for example, when it is desired to analyze a tourist area or a trade area of a store.
(C) When it is desired to analyze the movement preference of the user, 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 / STEP 51). When this determination is affirmative (FIG. 5 / STEP 51... YES), the encryption key is set to a combination of a part of the mesh code and the fixed key (FIG. 5 / STEP 52). This fixed key is preset.

  On the other hand, when the above determination is negative (FIG. 5 / STEP 51... NO), that is, when F_ENC ≠ 1, it is determined whether or not the encryption condition flag F_ENC is “2” (FIG. 5 / STEP 53). . If this determination is affirmative (FIG. 5 / STEP 53... YES), the encryption key is set to a combination of a part of the navigation data sampling time stamp and the fixed key (FIG. 5 / STEP 54).

  On the other hand, when the above determination is negative (FIG. 5 / STEP 53... NO), that is, when F_ENC ≠ 1, 2, it is determined whether or not the encryption condition flag F_ENC is “3” (FIG. 5 / (STEP 55). When this determination is affirmative (FIG. 5 / STEP 55... YES), the encryption key is set to a combination of a part of the user ID and the fixed key (FIG. 5 / STEP 56).

  On the other hand, when the above determination is negative (FIG. 5 / STEP 55... 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 / (STEP 57). When this determination is affirmative (FIG. 5 / STEP 57... YES), the encryption key is set to a combination of a part of the vehicle ID and the fixed key (FIG. 5 / STEP 58).

  On the other hand, when the above determination is negative (FIG. 5 / STEP 57... NO), that is, when F_ENC = 5, the encryption key is set as a fixed key (FIG. 5 / STEP 59).

  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 the predetermined encryption algorithm (for example, SHA-256) using the encryption key. The ID is encrypted (FIG. 5 / STEP 60).

  Next, an encrypted data mart is created by associating the vehicle type data and the encryption condition flag with the data mart obtained by encrypting the vehicle ID and the user ID (FIG. 5 / STEP 61). This vehicle type data corresponds to a part of the vehicle ID. Thereafter, this process is terminated.

  Returning to FIG. 3, after the encrypted data mart creation processing is executed as described above, the encrypted data mart is output to the integrated database server 4 (FIG. 3 / STEP 29). Thereafter, this process is terminated.

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

  As shown in the figure, first, the encrypted data mart is read (FIG. 6 / STEP 80). Next, the vehicle type is determined based on the vehicle type data included in the encrypted data mart (FIG. 6 / STEP 81). Hereinafter, this determined vehicle type is referred to as a “determined 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 / STEP 82).

  When this determination is affirmative (FIG. 6 / STEP 82... YES), the encrypted data mart is stored as registration data in the first area for the determination vehicle type (FIG. 6 / STEP 83). Thereafter, this process is terminated.

  On the other hand, when the above determination is negative (FIG. 6 / STEP 82... NO), that is, when F_ENC ≠ 1, it is determined whether or not the encryption condition flag F_ENC is “2” (FIG. 6 / STEP 84).

  When this determination is affirmative (FIG. 6 / STEP 84... YES), the encrypted data mart is stored as registration data in the second area for the determination vehicle type (FIG. 6 / STEP 85). Thereafter, this process is terminated.

  On the other hand, when the above determination is negative (FIG. 6 / STEP 84... NO), that is, when F_ENC ≠ 1, 2, it is determined whether or not the encryption condition flag F_ENC is “3” (FIG. 6 / STEP 86). ).

  If this determination is affirmative (FIG. 6 / STEP 86... YES), the encrypted data mart is stored as registration data in the third area for the determination vehicle type (FIG. 6 / STEP 87). Thereafter, this process is terminated.

  On the other hand, when the above determination is negative (FIG. 6 / STEP 86... 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 / STEP 88). ).

  When this determination is affirmative (FIG. 6 / STEP 88... YES), the encrypted data mart is stored as registration data in the fourth area for the determination vehicle type (FIG. 6 / STEP 89). Thereafter, this process is terminated.

  On the other hand, when this determination is negative (FIG. 6 / STEP 88... NO), that is, when F_ENC = 5, the encrypted data mart is stored as registration data in the fifth area for the determination vehicle type (FIG. 6 / STEP 90). . Thereafter, this process is terminated.

  As described above, according to the data registration system 1 of the present embodiment, the FCD, weather data, vehicle status data, fuel consumption data, and navigation data input via the network 10 are associated with the vehicle ID and the user ID. As the attached data group, a data mart is created and compressed. Further, only the vehicle ID and user ID of the compressed data mart are encrypted by an encryption algorithm using an encryption key to create an encrypted data mart, which is stored as registration data in a storage area in the integrated database server 4 Is done.

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

  Also, FCD-Provisional data mart of fuel consumption, FCD-Navi provisional data mart, FCD-weather provisional data mart, and FCD-vehicle situation provisional data mart shall be created, and these provisional data marts should be linked together. Thus, since the data mart is created, the load at the time of creating the data mart can be reduced as compared with the case where the data mart is created at once.

  In addition to this, when the latitude and longitude of the FCD and the navigation data, that is, the vehicle positions at the time of sampling do not match each other in the FCD-navigation provisional data mart creation process shown in FIG.・ Since the data with the closest longitude are linked to each other, the temporary data mart of FCD-Navi is linked while linking the data that are 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 a plurality of data in which the latitude / longitude of the FCD and the navigation data completely match, the data with the closest time stamp at the time of sampling among the plurality of data are linked to each other. Is the closest, it is possible to create a provisional data mart for FCD-navigation while linking data that are estimated to be highly related to each other. As described above, the creation accuracy of the provisional data mart for FCD-Navi can be improved.

  Further, since the data mart is encrypted after being compressed, the size of the encrypted data mart can be reduced. Accordingly, the number of registered data 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, an FCD-fuel provisional data mart, an FCD-navigation provisional data mart, an FCD-weather provisional data mart, and an FCD-vehicle situation provisional data mart are created. This is an example of creating a data mart as a data group by linking them together, but linking the FCD-Fuel consumption provisional data mart, the FCD-Navi provisional data mart, and the FCD-weather provisional data mart together By doing so, you may comprise so that the data mart as a data group may be produced.

  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 in STEPs 22 to 24 and 26 described above.

  The embodiment is an example in which a navigation device is used as a mobile station. However, the mobile station of the present invention is not limited to this, and any mobile station that moves simultaneously with the vehicle may be used. For example, a mobile information terminal such as a smartphone may be used as the mobile station.

  In that case, the portable information terminal performs data communication with the ECU and navigation device of the vehicle, and is configured so that the vehicle ID and / or user ID data is received on the portable information terminal side, As the movement state data, the position (latitude, longitude) of the portable information terminal, the data associated with the time stamp at the time of sampling of the position, the user ID, and the like are either from the portable information terminal, the ECU of the vehicle, or the navigation device. What is necessary is just to comprise so that it may input into the data processing server 2. FIG.

  Further, when the portable information terminal is used as a mobile station, the user is not limited to the time 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 a future route calculation or the like may be input as navigation data from the portable information terminal to the data processing server 2 and the movement state data may be input from the portable information terminal to the data processing server 2. Furthermore, in such a configuration, for example, a data mart may be created using data that does not change when the ignition switch of the vehicle is off (that is, fuel consumption data, etc.) as a constant value or empty data.

  Furthermore, although embodiment is an example using vehicle ID and user ID as vehicle specific data, the vehicle specific data of this invention are for not only this but for specifying at least one of a vehicle and the user of a vehicle. If it is. For example, a vehicle ID or a user ID may be used as the vehicle specifying data. In that case, for example, in the linked data creation process of FIG. 2 of the embodiment, only one of the vehicle ID and the user ID is linked to data other than the weather data, and in STEPs 22 to 26 of FIG. A 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 using an internal combustion engine as a power source. However, the data registration system of the present invention is not limited to this and uses a power source other than the internal combustion engine. It can also be applied to vehicles. For example, the present invention can be applied to a fuel cell vehicle or an electric vehicle.

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

  Further, the embodiment is an example using the Lzo algorithm as a compression algorithm when compressing the data mart. However, the compression algorithm when compressing the data mart is not limited to this, and any 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, STEP 25 and 26 may be omitted, and the data mart may be created by associating the weather data and the vehicle situation data with the two provisional data marts created in STEP 22 and 23.

  The embodiment is an example in which an encrypted data mart is created by encrypting the compressed data mart, and this encrypted data mart is stored in the integrated database server 4 as registered data. May be stored in the integrated database server 4 without encryption.

  Furthermore, 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 representing a time-series movement state of the mobile station, consumption ratio data representing an energy consumption ratio of a vehicle moving simultaneously with the mobile station, navigation data representing a navigation calculation result and a setting state of the vehicle, A plurality of types of data including weather data representing the weather in the area where the mobile station is present, 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;
Data group creation means for creating a data group in which the movement state data, the consumption ratio data, the navigation data, the weather data, and the vehicle identification data are linked to each other;
The data group is compressed by a predetermined compression algorithm, and using the compressed data group, registration data creating means for creating registration data,
Data storage means for storing the registration data in a storage area;
A data registration system comprising:   The data group creation means associates the vehicle identification data, the movement state data, and the consumption rate data with each other, the vehicle identification data, the movement state data, and the navigation data with each other. Creating 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, and using the first to third data groups, creating the data group The data registration system according to claim 1. The plurality of types of data further includes vehicle status data representing at least one of a manufacturing status and a repair status of the vehicle,
In addition to the movement state data, the consumption ratio data, the navigation data, the weather data, and the vehicle identification data, the data group creation means further associates the vehicle status data with each other, thereby The data registration system according to claim 1, wherein the data registration system is created.   The data group creation means associates the vehicle identification data, the movement state data, and the consumption rate data with each other, the vehicle identification data, the movement state data, and the navigation data with each other. A second data group that is attached, a third data group that associates the movement state data and the weather data with each other, and a fourth data that associates the vehicle specifying data, the movement state data, and the vehicle state data with 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,
The data group creating means creates the second data group, and when the vehicle position at the time of sampling in the movement state data and the navigation data does not coincide with each other, the movement state data and the navigation data 5. The data registration system according to claim 2, wherein 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,
The data group creation means, when creating the second data group, when there are a plurality of data in which the vehicle position at the time of sampling in the movement state data and the navigation data coincides with each other, 6. The data registration system according to claim 2, wherein data having the closest time stamps at the time of sampling are linked to each other.   7. The data registration system according to claim 1, wherein the registration data creation unit creates the registration data by encrypting the compressed data group with a predetermined encryption algorithm. .