KR102674769B1 - My data-based personal travel information linkage system and server - Google Patents

Abstract

My data-based personal travel information linking system and server collects personal travel information existing in various platforms and systems based on my data, allowing for more effective and convenient management of personal travel information and my data. In addition, through the embodiment, third-party businesses are allowed to access customer data, and information holding organizations can safely provide information to third parties through a standardized API. Additionally, in the embodiment, an optimal route for carbon reduction is created using my data based on personal travel information and provided through a mobile terminal, thereby reducing carbon emissions due to movement.

Description

My data-based personal travel information linkage system and server {MY DATA-BASED PERSONAL TRAVEL INFORMATION LINKAGE SYSTEM AND SERVER}

This disclosure relates to a personal travel information linkage system and server based on my data, and specifically relates to a system and method for collecting and processing personal travel information and linking it with my data.

Unless otherwise indicated herein, the material described in this section is not prior art to the claims of this application, and is not admitted to be prior art by inclusion in this section.

Personal travel information is mainly information related to the movement of individuals using transportation. Personal travel information is generated from various platforms and may include personal card company information, telecommunication company information, manufacturer information, insurance company information, public transportation information, and personal mobility information. In addition, communication big data that can estimate the user's location information based on signals periodically exchanged with cell phone users at each base station, transportation card data that can check public transportation movement history, and sharing economy such as taxi calls, proxy calls, bikes, and parking. Various data such as sharing economy platform data generated while using the platform are included in personal travel information. Because the amount and type of personal traffic information are vast, it is impossible for individuals to understand and manage all traffic information.

Meanwhile, My Data is data created or owned by an individual user, and My Data may mainly consist of various data that occurs in the individual's daily life. In addition, My Data allows individuals who own information to directly manage their own information as information subjects and directly control the provision of information when necessary, allowing all individuals who actively participate in services linked to various industries such as asset and credit management and personal health management. It means process. In other words, in the case of My Data, individuals directly manage personal information generated from various platforms in the form of data, and can provide or block personal information as needed when using third-party platforms. Technology using My Data supports the safe management of personal information through the concept of individuals controlling their My Data. Technology using My Data can build a big data ecosystem so that information providers can safely use personal information in various industries such as finance, medicine, transportation, and communications.

Previously, My Data was a service that was only available in limited areas such as finance and public sector. For example, communication data, vehicle driving information, transportation card usage information, credit card data, etc. are sensitive personal information and are strictly managed in accordance with the law, and there are many restrictions on providing and utilizing them outside of the collection agency. However, recent law amendments have laid the foundation for universal implementation in all areas according to the wishes of each citizen. Accordingly, there is a need for a system that can collect and link personal travel information generated from various platforms and systems into My Data.

1. Korean Patent Registration No. 10-2492835 (2023.01.20) 2. Korean Patent Publication No. 10-2023-0072257 (2023.05.24) 3. US Patent Registration No. 11803840 (2023.10.31) 4. US Patent Registration No. 11783015 (2023.10.10) 5. US Patent Registration No. 11762833 (2023.09.19) 6. US Patent Registration No. 11748512 (2023.09.05) 7. U.S. Patent Publication No. 20230262436 (2023.08.17)

The my data-based personal travel information linking system and server according to the embodiment collects and links personal travel information generated from various platforms and systems based on my data to manage personal travel information more conveniently and effectively.

In the embodiment, the server 100 links data items extracted from personal travel information with My Data, allowing various and massive data included in personal travel information to be used as My Data.

In the embodiment, in the case of My Data linked to personal traffic information, the server 100 has control over its own data and, if necessary, shares the data with other services or companies. Through this, users have transparency and control over their data, and users who are the owners of the data can use it to receive services that suit their purposes.

In addition, through examples, we build mobility big data that can analyze the passage of people, vehicles, and public transportation users, and by utilizing such mobile communication, public transportation card, and vehicle navigation data, individual travel routes can be determined. Of course, we build a personal trip chain DB that can identify the means and purpose of travel.

Additionally, the embodiment provides sustainable MaaS for converting individuals' use of private cars to public transportation in order to reduce greenhouse gas emissions in the transportation sector.

For example, the embodiment provides functions and services necessary to practice carbon neutrality, such as supporting driving on the optimal carbon reduction route through S-MaaS and providing benefits for using public transportation and zero-carbon vehicles.

Additionally, in the embodiment, data security is maintained by performing authentication of the information request terminal and transmitting personal travel information and my data according to the information request only to the information request terminal that has completed authentication.

Additionally, in the embodiment, data transmission efficiency is improved by using cursor-based paging technology and timestamps when transmitting large amounts of data.

However, the problems to be solved according to one embodiment are not limited to those mentioned above.

The MyData-based personal travel information linking server according to the embodiment includes a memory storing at least one command; and a processor, wherein at least one instruction is executed by the processor to collect personal traffic information including mobile raw log data, extract data corresponding to information items set from the personal traffic information, and convert it into big data, The data contained in the set information items is linked and processed into My Data, and a traffic chain is created according to the personal travel information and My Data analysis results. After completing authentication of the information request terminal, based on the request received from the generated information request terminal. and send my data.

My data-based personal travel information linking system and server as described above collects personal travel information existing on various platforms and systems based on my data, allowing for more effective and convenient management of personal travel information and my data. .

In addition, through the embodiment, third-party businesses are allowed to access customer data, and information holding organizations can safely provide information to third parties through a standardized API.

Additionally, in the embodiment, an optimal route for carbon reduction is created using my data based on personal travel information and provided through a mobile terminal, thereby reducing carbon emissions due to movement.

Additionally, data transmission efficiency and data security are improved through the embodiment.

The effects of the present invention are not limited to the effects described above, and should be understood to include all effects that can be inferred from the configuration of the invention described in the detailed description or claims of the present invention.

Figure 1 is a diagram showing a my data-based personal travel information linkage system according to an embodiment.
Figure 2 is a diagram for explaining the flow of personal traffic information collection and use according to an embodiment
Figure 3 is a block diagram of a personal travel information linking server according to an embodiment.
Figure 4 is a diagram showing the configuration of an instruction set stored in a memory according to an embodiment
Figure 5 is a diagram showing an example of personal traffic information collected in the embodiment
Figure 6 is a diagram showing the information included in the traffic chain and the types of traffic chains
Figure 7 is a diagram showing the map creation process in the embodiment
Figure 8 is a diagram showing the form of navigation data processed based on a link according to an embodiment
9 and 10 are diagrams showing data linkage items and data corresponding to each item according to an embodiment.

Hereinafter, embodiments disclosed in the present specification will be described in detail with reference to the attached drawings. However, identical or similar components will be assigned the same reference numbers regardless of reference numerals, and duplicate descriptions thereof will be omitted. The suffixes “module” and “part” for components used in the following description are given or used interchangeably only for the ease of preparing the specification, and do not have distinct meanings or roles in themselves. Additionally, in describing the embodiments disclosed in this specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed descriptions will be omitted. In addition, the attached drawings are only for easy understanding of the embodiments disclosed in this specification, and the technical idea disclosed in this specification is not limited by the attached drawings, and all changes included in the spirit and technical scope of the present invention are not limited. , should be understood to include equivalents or substitutes.

Terms containing ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

When a component is said to be "connected" or "connected" to another component, it is understood that it may be directly connected to or connected to the other component, but that other components may exist in between. It should be. On the other hand, when it is mentioned that a component is “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

In this application, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

In this specification, 'part' includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Additionally, one unit may be realized using two or more pieces of hardware, and two or more units may be realized using one piece of hardware.

In this specification, some of the operations or functions described as being performed by a terminal, apparatus, or device may instead be performed on a server connected to the terminal, apparatus, or device. Likewise, some of the operations or functions described as being performed by the server may also be performed in a terminal, apparatus, or device connected to the server.

Hereinafter, the present invention will be described in detail with reference to the attached drawings.

Figure 1 is a diagram showing a my data-based personal travel information linkage system according to an embodiment.

Referring to FIG. 1, a my data-based personal travel information linkage system according to an embodiment may be configured to include a server 100 and an information request terminal 200. In the embodiment, the server 100 collects personal traffic information including mobile raw log data, extracts data from the personal traffic information according to set information items, and converts the extracted data into big data. In an embodiment, mobile raw log data is data collected from an individual's mobile terminal, and includes, but is not limited to, start time of stay, end time of stay, base station, and time of stay. Afterwards, a travel chain is created according to the results of personal travel information analysis. In an embodiment, the travel chain may include an individual's routine travel route derived from personal travel information and a series of connected activities or events that occur during the movement process. The travel chain divides the entire journey from origin to destination into several stages. For example, a series of activities such as taking the subway from home, going to the station, and walking to the office can become a travel chain.

Additionally, the server 100 processes data extracted from personal travel information and links it with My Data. My Data is data created or owned by an individual. My Data includes all types of data collected, created, and stored with the user's consent. My Data may mainly include personal information, transaction records, consumption patterns, health information, etc. In the embodiment, the server 100 links data items extracted from personal travel information with My Data, allowing various and massive data included in personal travel information to be used as My Data.

In the embodiment, in the case of My Data linked to personal traffic information, the server 100 has control over its own data and, if necessary, shares the data with other services or companies. Through this, users have transparency and control over their data, and users who are the owners of the data can use it to receive services that suit their purposes.

In addition, after completing the authentication of the information request terminal 200, the server 100 transmits data based on the request of the information authentication terminal 200 among traffic chain information, personal traffic information, and my data to the information request terminal 200. . In an embodiment, the information request terminal 200 may include an individual's mobile terminal that generates personal travel information and terminals of various organizations that use personal travel information and my data.

Figure 2 is a diagram for explaining the flow of personal traffic information collection and use according to an embodiment.

In an embodiment, the my data-based personal travel information linkage system may link personal travel information with the S-MaaS (Smart Mobility as a Service) platform to integrate means of transportation and transportation services and provide transportation information to users. S-MaaS integrates individual means of transportation and allows users to conveniently use them by comprehensively providing smart mobility and services based on personal travel information and my data provided in the embodiment.

Referring to Figure 2, in the embodiment, the user is provided with his or her travel data request and request results through the S-MaaS application of his or her mobile terminal, and the S-Mass platform collects personal travel information from the individual's mobile terminal and Manage. In an embodiment, the S-MaaS platform may include the server 100 described in FIG. 1. In addition, the S-Maas platform transmits my data linked with personal travel information to the requested terminal and collects personal travel information from public transportation systems, telecommunication company systems, etc.

Figure 3 is a block diagram of a personal travel information linking server according to an embodiment.

In an embodiment, a personal traffic information link server (Server) is a computing system that provides services to other computers or devices in a computer network or stores and manages data. The server 200 accepts requests from other computers or devices called clients and provides responses or data to the requests. The configuration of the server 200 shown in FIG. 2 is only a simplified example.

The communication unit 110 can be configured regardless of the communication mode, such as wired or wireless, and can be configured with various communication networks such as a personal area network (PAN) and a wide area network (WAN). In addition, the communication unit 110 can operate based on the known World Wide Web (WWW) and uses wireless transmission technology used for short-distance communication, such as Infrared Data Association (IrDA) or Bluetooth. You can also use it. For example, the communication unit 110 may be responsible for transmitting and receiving data necessary to perform a technique according to an embodiment of the present disclosure.

Memory 120 may refer to any type of storage medium. For example, memory 120 may be a flash memory type, hard disk type, or multimedia card type. micro type), card type memory (e.g. SD or XD memory, etc.), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory) ), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk, and optical disk. This memory 120 may form the database shown in FIG. 1.

Memory 120 may store at least one instruction that can be executed by processor 130. Additionally, the memory 120 may store any type of information generated or determined by the processor 130 and any type of information received by the server 200. For example, the memory 120 stores RM data and RM protocols according to users, as will be described later. Additionally, the memory 120 stores various types of modules, instruction sets, or models.

The processor 130 may perform technical features according to embodiments of the present disclosure, which will be described later, by executing at least one instruction stored in the memory 120. In one embodiment, the processor 130 may be comprised of at least one core, including a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and tensor processing of a computer device. It may include a processor for data analysis and/or processing, such as a tensor processing unit (TPU).

Figure 4 is a diagram showing the configuration of an instruction set stored in a memory according to an embodiment.

Referring to FIG. 4, the command set according to the embodiment will include a collection unit 121, a big data generation unit 122, an authentication unit 123, a calculation unit 124, and an information transmission unit 125. You can. The term 'part' used in this specification should be construed to include software, hardware, or a combination thereof, depending on the context in which the term is used. For example, software may be machine language, firmware, embedded code, and application software. As another example, hardware may be a circuit, processor, computer, integrated circuit, integrated circuit core, sensor, Micro-Electro-Mechanical System (MEMS), passive device, or a combination thereof.

The collection unit 121 collects personal traffic information. In an embodiment, personal travel information is a series of data generated by an individual while moving, and may include vehicle navigation information, mobile communication data, public transportation card data, etc. Referring to FIG. 5 to explain personal travel information, personal travel information includes GPS data recording the movement of vehicles, DTG (Digital Tacho Graph) data, mobile data recording the movement of people, and public transportation data showing the movement of public transportation users. May contain card data.

In an embodiment, vehicle navigation data is vehicle movement trace information recorded every second through the vehicle's navigation terminal or mobile phone application. In the embodiment, the collection unit 121 accumulates navigation data based on links or GPS points depending on the collection method. Using navigation data, it is possible to estimate not only the movement trajectory of individual vehicles, but also the average speed and traffic volume of each road section, as well as the digital tacho graph (Digital Tacho Graph) for commercial vehicles such as taxis, buses, and cargo vehicles. Using DTG) information, detailed information for each vehicle type can also be collected.

The mobile communication data collected in the embodiment is sighting data accumulated as the mobile phone and a nearby base station (Base Transceiver Station Tower: BTS Tower) communicate at regular time intervals. Using this mobile communication data, it is possible to determine the movement trajectory and residence time of each individual by time zone, and construct a travel chain DB by gender and age, including detailed travel purposes.

The public transportation card information collected in the embodiment is boarding and alighting tag information recorded when a public transportation user uses public transportation with a prepaid or postpaid public transportation card. In the embodiment, by using various attribute information such as boarding and alighting tag information, history, stop, age, and gender, it is possible to identify various travel information ranging from individual public transportation use methods to transfers.

The big data generation unit 122 extracts errors and distorted data from personal traffic information, preprocesses the data, and generates a movement trajectory for each individual per base station through the processed data. In addition, personal travel information is converted into big data by classifying the route, residential area, and movement characteristics of potential residential area. For this purpose, the big data generation unit 122 receives personal traffic information including movement patterns, routes, residential areas, potential residential areas, etc. from the collection unit 121. Afterwards, errors or distorted data are identified and extracted from personal travel information. For example, it handles incorrect location information, missing data, and confused movement patterns. In the embodiment, when missing data is detected, the big data generator 122 corrects the missing data based on traffic patterns and public transportation performance data.

Afterwards, the big data generator 122 performs preprocessing on the extracted data. In embodiments, preprocessing includes cleaning and converting data into the required format. Additionally, data consistency is maintained and processed into an analyzable form. In the embodiment, the big data generator 122 generates a movement trajectory for each individual per base station based on the processed data. The movement trajectory represents the record of the individual moving from a specific base station to another base station. In addition, the big data generation unit 122 analyzes the generated movement trajectory and classifies movement characteristics such as route, residential area, and potential residential area. For example, the big data generator 122 can identify movement along a specific route, mainly visited areas, potential residential areas, etc. based on mobile raw log data. Afterwards, the big data generator 122 processes the personal traffic information into big data based on the classified movement characteristics. In embodiments, large data sets can be generated based on the match rate of the paths.

In the embodiment, the big data generator 122 generates a trip chain according to the results of personal travel information analysis. In an embodiment, a travel chain is information that connects a series of events or activities related to movement in chronological order. Referring to FIG. 6 illustrating the information included in the traffic chain and the types of traffic chains, in the embodiment, the traffic chain represents continuous traffic information and includes a settlement point for going to another point. Additionally, it may be defined differently depending on the classification of settlement and destination. In an embodiment, an individual's travel chain is used to analyze traffic volume and measure carbon emissions by transportation mode.

In the embodiment, the big data generator 122 generates traffic chain data in the form of traffic OD (Origin Destination). Passage OD largely includes purpose OD and means OD. The big data generation unit 122 uses mobile communication, public transportation cards, navigation data, Hi-Pass, land use information, etc. to build a personal travel chain database for each purpose and means that can identify the purpose, means, and movement route of travel. do.

For example, the big data generator 122 estimates the target OD using mobile communication data. Since mobile communication data continuously records everyone's movement and residence locations, detailed purpose OD is estimated by analyzing each individual's daily traffic pattern along with land use information. In the embodiment, the big data generator 122 first collects mobile data to build an OD based on communication (mobile) data. In an embodiment, mobile data is accumulated data of cell phone signals transmitted to a nearby base station. The form of mobile data includes CDR (Call Detailed Recorder), which is recorded when using a mobile phone, such as text messages, calls, and the Internet, and sighting data, which is recorded at regular time intervals even when a mobile phone call is not made. The data collected domestically is base station signal data (MPSD, Mobile Phone Signaling Data), which is a new type of data that is not currently used overseas in the transportation sector. Base station signal data is historical data transmitted and received between the terminal and the base station and is generated when the terminal is in the base station reception range while the power is on. When a terminal enters the base station's reception range, the receiving base station detects the signal from the terminal at regular time intervals and creates a history, and when it leaves the range, recording stops.

Since a base map must exist in order to analyze mobility, the big data generator 122 creates a map that is a spatial standard for monitoring and analysis. Hereinafter, referring to FIG. 7, the map creation process of the big data generator 122 in the embodiment will be described. First, the big data generator 122 sets the virtual cell radius of the main base station.

Afterwards, the big data generator 122 matches the base station reception range and the aggregate area. By overlapping the base station reception range and the aggregation zone, the range is adjusted so that the base station and the aggregation zone are at least 1:1 or N:1, and if the reception range of one base station spans multiple aggregation zones, they are merged into one aggregation zone. .

Afterwards, the big data generator 122 corrects the data by merging it with the nearby base map if it falls into the following two types. First, if the area is formed too small, the big data generator 122 corrects it by merging it with a nearby base map. For example, the big data generator 122 merges areas that are less than a certain percentage (e.g., 5%) in the cumulative distribution within a city or county. In addition, the big data generator 122 is located within the reception range of the same base station and is formed as a single base map polygon, but when the distance is distant and multiple base map polygons are formed, it is merged with a nearby map. This is corrected by excluding the one polygon with the largest area and merging the remaining polygons with adjacent polygons.

Afterwards, the big data generator 122 corrects some traffic polygons and matches the reception ranges of all base stations with the aggregate sphere. In the embodiment, the big data generator 122 merges the traffic polygon with the adjacent polygon belonging to the same administrative district when the traffic polygon is located on a river or when the actual base station location is closer to another traffic polygon than the matched traffic polygon.

In addition, the big data generation unit 122 estimates the traffic demand OD using public transportation data, and in addition, the travel OD by mode for private cars, taxis, buses, freight vehicles, etc. can be constructed using navigation and DTG data. ,

In the embodiment, the big data generator 122 processes navigation data collected every second into an aggregated form in links defined according to a specific purpose in order to build OD through navigation data. Figure 8 is a diagram showing the form of navigation data processed based on links. In order to use navigation data as a database in various forms depending on the purpose of use through the spatial and temporal movement information of individual vehicles, a series of processing procedures are required.

In the embodiment, the big data generator 122 first performs map matching with actual roads in the case of GPS data, and cleans related distorted data such as error data and travel routes. In the embodiment, when the primary data processing process of the navigation data is completed, the big data generator 122 builds a primary processing database in the most basic usable form based on the processed data. In an embodiment, the primary processing database of navigation data includes point/space traffic speed, movement route, and traffic volume for each link of navigation users.

Additionally, the big data generation unit 122 builds OD based on public transportation card data. Public transportation card data is information that is tagged when a user gets on or off public transportation such as a bus, subway, or taxi using a transportation card within a prepaid T-money card or a postpaid credit card. In the embodiment, the big data generator 122 processes integrated public transportation card data based on point and route information generation. Branch information corresponds to stops and entrances and exits for each station, and route information is route traffic information for each route. Public transportation card integrated data is often missing information on drop-off points due to the characteristics of different fare systems for each local government, and even though it is standardized, matching such as stop ID information is often missing. Therefore, the big data generation unit 122 performs a stop ID matching task prior to processing and preferentially builds a route map-based analysis map.

Additionally, in the embodiment, the big data generator 122 collects credit card information to analyze individual consumption patterns, and classifies users to perform traffic-related analysis through affiliated store information. The structure of credit card information can be divided into member information, affiliated store information, and transportation-related information. Through member information, you can find out age, gender, occupation, estimated income, credit rating, residence and work address, etc. Through affiliated store information, you can find out the affiliated store address, affiliated store industry information, etc., and transportation-related information includes Hi-Pass, toll usage information, public transportation usage information, and freight welfare card usage information.

Additionally, in the embodiment, the big data generator 122 may construct a traffic OD using high-pass data for traffic between highway toll gates for traffic between regions across the country.

The my data creation unit 123 creates personal my data using the constructed big data. In an embodiment, the my data generator 123 may extract data-linked items from big data constructed through the collection of personal travel information, and generate data for each extracted item as my data. Figures 9 and 10 are diagrams showing data linkage items and data corresponding to each item according to an embodiment. 9 and 10, in the embodiment, the my data generator 123 generates mobile personal travel data, public transportation card personal travel data, navigation personal travel data, shared mobility personal travel data, and automobile manufacturer personal travel data. Linked items can be extracted from etc.

After completing authentication of the personal travel information information request terminal, the information transmission unit 124 transmits travel chain information, personal travel information, and my data based on the request of the generated information request terminal. In the embodiment, the information request includes information provider data receiving the transmission request, information recipient data receiving personal traffic information, items of the personal traffic information, whether regular transmission is requested, purpose of transmission request, and personal behavior information retention period data. .

In the embodiment, the information transmission unit 124 provides mutual authentication (Mutual authentication) based on Transport Layer Security (TLS), a standard protocol that ensures end-to-end authentication, encryption, and integrity of transmitted data between the transport layer and the application layer. Authentication) and transmission section encryption, the information requesting terminal is authenticated.

To this end, the information transmission unit 124 first performs a TLS handshake. The TLS handshake process is a process of mutual authentication and key exchange between the client and server. In the embodiment, the information transmission unit 124 performs the role of a server, and the information request terminal is a client. Afterwards, the server is verified through mutual authentication. In the embodiment, the information transmission unit 124, which is a server, provides a server certificate to the information request terminal during the TLS handshake. This certificate contains the server's public key. Afterwards, the information requesting terminal, which is the client, provides the client certificate during the TLS handshake. This certificate contains the client's public key. The server and client exchange their public keys and create session keys for each other. This session key is a symmetric key that will be used for future communications. Thereafter, the information transmission unit 124 encrypts the transmission data using a symmetric key algorithm using the exchanged session key. This ensures the confidentiality of data. Additionally, the integrity of the data is verified using Hash-based Message Authentication Code (HMAC) or other integrity assurance mechanisms. Through this, all communications between the information request terminal and the information transmission unit are protected by TLS. The terminal verifies the server's certificate, and the server verifies the terminal's certificate and performs mutual authentication.

Thereafter, the information transmission unit 124 transmits personal travel information and my data to the authenticated terminal through the REST (Representational State Transfer) method, which transmits data using only GET and POST among HTTP methods.

REST (Representational State Transfer) is an architectural style for representing resources and transferring state. RESTful services use HTTP methods (GET, POST, PUT, DELETE, etc.) to perform operations on resources. In the embodiment, personal traffic information is transmitted to an authenticated terminal using the GET and POST methods.

First, the terminal that wishes to transmit personal traffic information and my data first performs authentication with the information transmission unit 124. Generally, a token-based authentication method can be used. Afterwards, request information using GET (GET Request for Information). For example, the terminal sends a request to the RESTful endpoint using the GET method to request personal travel information. Afterwards, the information transmission unit 124 processes the request for the authenticated terminal and responds with the corresponding personal traffic information. When the terminal wants to update personal travel information or add new information, it sends a request to the RESTful endpoint using the POST method. When a device transmits information using POST, the endpoint must be open only to authenticated users. In the embodiment, personal travel information and my data can be transmitted to an authenticated terminal using the GET and POST methods in a RESTful manner.

Additionally, in the case of an API that returns a list of information, the information transmission unit 124 transmits personal traffic information or my data through cursor-based pagination for partial range inquiry.

Cursor-Based Pagination is one of the ways to retrieve a result set from an API by dividing it into several parts. The cursor-based paging method is especially useful when retrieving parts of a large data set rather than retrieving the entire result at once. In order to query the partial range in the embodiment, the client, which is the information request terminal, transmits the first request to the API of the information transmission unit 124. This request usually includes a cursor value, along with parameters to retrieve part of the list. Afterwards, the information transmission unit 124 responds to the client with some data corresponding to the current page. The response includes the items on the current page and the next cursor value to bring up the next page. The client now sends the request back to the information transmission unit 124 using the new cursor value to retrieve the next page. In the embodiment, the process is repeated between the client and the information transmission unit 124 until all necessary data is retrieved. Embodiments use cursor-based paging so that the server does not have to send the entire data set at once. This allows you to handle large amounts of data more efficiently. The data transmission method according to the embodiment is particularly useful in situations where large-capacity databases or fast access are required.

In the embodiment, the information transmission unit 124 minimizes transmission by using the inquiry timestamp when there is no modification to the information provider's information when requesting regular transmission of the same information after the My Data service provider collects the information. . For example, the My Data service provider initially collects information and then transmits an initial request for regular updates to the information transmission unit 124. At this time, the request includes a timestamp for when the information was last received. The information transmission unit 124 checks whether there are any modifications that occurred after the corresponding timestamp for the My Data operator and responds with the modified data. In an embodiment, the information transmission unit 124 may check whether there are any modifications by using the maximum timestamp value among the modified data during the time when the information was most recently received. Thereafter, the information transmission unit 124 uses the latest timestamp value received in the previous response to check whether there are any modifications that have occurred since the most recent update in response to the regular request. At this time, if there are no modifications to the information provider's information, an empty response may be returned. In the embodiment, the timestamp allows only the latest data to be transmitted while minimizing information transmission. Additionally, if the information provider's information has not been modified, it can be maintained up-to-date without retransmitting unnecessary data.

The calculation unit 125 extracts the user's starting point and destination from the generated travel chain, creates a plurality of travel routes, calculates the carbon emissions of each generated travel route, and extracts the travel route with the minimum carbon emissions. and transmits it to individual mobile terminals. In the embodiment, the calculation unit 125 calculates carbon emissions by considering the driving distance, type of transportation, fuel efficiency, etc. for each created travel route. To this end, the calculation unit 125 identifies transportation means and fuel types, such as automobiles, bicycles, and public transportation. Afterwards, the travel distance from the starting point to the destination is measured through GPS and map API. Afterwards, considering the fuel efficiency of the means of transportation, the amount of fuel consumed according to the driving distance is calculated. In embodiments, fuel efficiency may include fuel efficiency of a vehicle, power consumption of an electric vehicle, etc. Afterwards, the calculation unit 125 calculates the carbon emissions. In the embodiment, the calculation unit 125 calculates the amount of carbon dioxide (CO2) actually emitted by applying the carbon emission coefficient of the used fuel. Since the carbon emissions per unit distance are different for each fuel, the calculation unit 125 calculates the carbon emissions for each travel route based on the carbon emissions per unit distance data for each fuel.

In the embodiment, carbon emissions can be calculated through Equation 1.

Equation 1

Carbon emissions = driving distance × (fuel consumed according to fuel efficiency) × (CO2 emission coefficient of fuel)

The my data-based personal travel information linking system and server according to the embodiment collects and links personal travel information generated from various platforms and systems based on my data to manage personal travel information more conveniently and effectively.

In the embodiment, the server 100 links data items extracted from personal travel information with My Data, allowing various and massive data included in personal travel information to be used as My Data.

In the embodiment, in the case of My Data linked to personal traffic information, the server 100 has control over its own data and, if necessary, shares the data with other services or companies. Through this, users have transparency and control over their data, and users who are the owners of the data can use it to receive services that suit their purposes.

In addition, through examples, we build mobility big data that can analyze the passage of people, vehicles, and public transportation users, and by utilizing such mobile communication, public transportation card, and vehicle navigation data, individual travel routes can be determined. Of course, we build a personal trip chain DB that can identify the means and purpose of travel.

Additionally, the embodiment provides sustainable MaaS for converting individuals' use of private cars to public transportation in order to reduce greenhouse gas emissions in the transportation sector.

For example, the embodiment provides functions and services necessary to practice carbon neutrality, such as supporting driving on the optimal carbon reduction route through S-MaaS and providing benefits for using public transportation and zero-carbon vehicles.

Additionally, in the embodiment, data security is maintained by performing authentication of the information request terminal and transmitting personal travel information and my data according to the information request only to the information request terminal that has completed authentication.

Additionally, in the embodiment, data transmission efficiency is improved by using cursor-based paging technology and timestamps when transmitting large amounts of data.

The disclosed content is merely an example and can be modified and implemented in various ways by those skilled in the art without departing from the gist of the claims, so the scope of protection of the disclosed content is limited to the above-mentioned specific scope. It is not limited to the examples.

Claims (21)

In the My Data-based personal travel information linkage server,
a memory storing at least one instruction; and
Contains a processor,
As the at least one instruction is executed by the processor,
Collect personal traffic information including mobile raw log data, extract data corresponding to information items set from the personal traffic information, turn it into big data, link the data included in the set information items, and process it into My Data.
Create a travel chain according to the personal travel information and my data analysis results,
After completing authentication of the information request terminal, my data is transmitted based on the request received from the generated information request terminal and
The personal traffic information link server; Is
To create a map used to build a mobile data-based origin-destination (OD), set the virtual cell radius covered by the main base station based on base station signal data (MPSD, Mobile Phone Signaling Data),
Match the virtual cell radius and the aggregation sphere including the reception range of the main base station, and
If the virtual cell radius is less than a certain size, the virtual cell is corrected by merging with a nearby map,
If a traffic polygon, which is a spatial unit included in the map, is located on a river or is closer to another traffic polygon than a traffic polygon matched by the base station location, the traffic polygon is merged with an adjacent polygon belonging to the same administrative district, personal traffic information Linked server.
The method of claim 1, further comprising: the personal traffic information linking server; Is
Error and distortion data are extracted and pre-processed from the collected personal travel information, the personal travel information is processed, and through the processed personal travel information, individual movement trajectories are generated per base station, and routes, residential areas and potential residents are generated. A personal travel information linkage server characterized by classifying regional movement characteristics and converting personal travel information into big data.
The method of claim 2, further comprising: the personal traffic information linking server; Is
A personal travel information linkage server that corrects the missing data based on traffic patterns and public transportation performance data when missing data occurs.


delete The method of claim 1, wherein the request received from the information request terminal is
Personal traffic, characterized in that it includes information provider data receiving a transmission request, information recipient data receiving personal traffic information, items of the personal traffic information, whether regular transmission is requested, purpose of transmission request, and personal behavior information retention period data. Information linkage server.
The method of claim 1, further comprising: the personal traffic information linking server; Is
Performs end-to-end primary authentication of the information requesting terminal between the transport layer and the application layer,
A personal traffic information linkage server characterized by final authentication of the information requesting terminal through mutual authentication and transmission section encryption based on TLS (Transport Layer Security), a standard protocol that guarantees integrity.
The method of claim 1, further comprising: the personal traffic information linking server; Is
Personal passage, which is characterized by transmitting personal passage information or processed my data included in the information request to an authenticated information request terminal through the REST (Representational State Transfer) method, which transmits data using GET and POST among HTTP methods. Information linkage server.
The method of claim 7, further comprising: the personal traffic information linking server; Is
In the case of an API that returns a list of information, a personal travel information linkage server characterized by transmitting personal travel information or processed my data through cursor-based paging for partial range inquiry.
The method of claim 7, further comprising: the personal traffic information linking server; Is
After collecting information, if regular transmission of the same information is requested from the information request terminal, the information provider's information is checked to see if there have been any modifications, and if there are no modifications, the information is transmitted using the information inquiry timestamp. A personal traffic information linkage server characterized by minimizing.
The method of claim 1, further comprising: the personal traffic information linking server; Is
Extract the user's origin and destination from the created travel chain, create multiple travel routes, calculate the carbon emissions of each created travel route, extract the travel route with the minimum carbon emissions, and transmit it to individual mobile terminals. A personal traffic information linkage server characterized in that.
In my data-based personal travel information linkage system,
Information request terminal requesting my data or personal travel information; and
Collect personal traffic information, extract data corresponding to the information items set from the personal traffic information, turn it into big data, link the data included in the set information items, and process it into My Data.
Create a travel chain according to the personal travel information and my data analysis results,
After completing authentication of the information request terminal, a personal traffic information linkage server that transmits my data based on the request received from the generated information request terminal; includes;
The personal traffic information link server; Is
To create a map used to build a mobile data-based origin-destination (OD), set the virtual cell radius covered by the main base station based on base station signal data (MPSD, Mobile Phone Signaling Data),
Match the virtual cell radius and the aggregation sphere including the reception range of the main base station, and
If the virtual cell radius is less than a certain size, the virtual cell is corrected by merging with a nearby map,
If a traffic polygon, which is a spatial unit included in the map, is located on a river or is closer to another traffic polygon than a traffic polygon matched by the base station location, the traffic polygon is merged with an adjacent polygon belonging to the same administrative district, personal traffic information Linkage system.
The method of claim 11, further comprising: the personal traffic information linking server; Is
Error and distortion data are extracted and pre-processed from the collected personal travel information, the personal travel information is processed, and through the processed personal travel information, individual movement trajectories are generated per base station, and routes, residential areas, and potential residents are generated. A personal travel information linkage system characterized by classifying regional movement characteristics and converting personal travel information into big data.
The method of claim 12, further comprising: the personal traffic information linking server; Is
A personal travel information linkage system characterized by correcting the missing data based on traffic patterns and public transportation performance data when missing data occurs.


delete The method of claim 11, wherein the request received from the information request terminal is
Personal traffic, characterized in that it includes information provider data receiving a transmission request, information recipient data receiving personal traffic information, items of the personal traffic information, whether regular transmission is requested, purpose of transmission request, and personal behavior information retention period data. Information linkage system.
The method of claim 11, further comprising: the personal traffic information linking server; Is
Performs end-to-end primary authentication of the information requesting terminal between the transport layer and the application layer,
A personal traffic information linkage system characterized by final authentication of the information requesting terminal through mutual authentication and transmission section encryption based on TLS (Transport Layer Security), a standard protocol that guarantees integrity.
The method of claim 11, further comprising: the personal traffic information linking server; Is
Personal traffic, characterized by transmitting personal traffic information or processed my data included in the information request to an authenticated information request terminal through the REST (Representational State Transfer) method, which transmits data using GET and POST among HTTP methods. Information linkage system.
The method of claim 17, further comprising: the personal traffic information linking server; Is
In the case of an API that returns a list of information, a personal travel information linkage system characterized by transmitting personal travel information or processed my data through cursor-based paging for partial range inquiry.
The method of claim 17, further comprising: the personal traffic information linking server; Is
After collecting information, if regular transmission of the same information is requested from the information request terminal, the information provider's information is checked to see if there have been any modifications, and if there are no modifications, the information is transmitted using the information inquiry timestamp. A personal traffic information linkage system characterized by minimizing.
The method of claim 11, further comprising: the personal traffic information linking server; Is
Extract the user's origin and destination from the created travel chain, create multiple travel routes, calculate the carbon emissions of each created travel route, extract the travel route with the minimum carbon emissions, and transmit it to individual mobile terminals. A personal traffic information linkage system characterized by:
In the my data-based personal travel information linking method,
(A) Collect personal traffic information including mobile raw log data from the server, extract data corresponding to the information items set from the personal traffic information, turn it into big data, and link the data included in the set information items into My Data. processing step;
(B) generating a travel chain in the server according to the personal travel information and my data analysis results; and
(C) After completing authentication of the information request terminal in the server, transmitting my data based on the request received from the generated information request terminal; includes
Step (B) above; Is
To create a map used to build a mobile data-based origin-destination (OD), set the virtual cell radius covered by the main base station based on base station signal data (MPSD, Mobile Phone Signaling Data),
Match the virtual cell radius and the aggregation sphere including the reception range of the main base station, and
If the virtual cell radius is less than a certain size, the virtual cell is corrected by merging with a nearby map,
If a traffic polygon, which is a spatial unit included in the map, is located on a river or is closer to another traffic polygon than a traffic polygon matched by the base station location, the traffic polygon is merged with an adjacent polygon belonging to the same administrative district, personal traffic information How to link.