WO2024101293A1 - Appareil de gestion de données, système de gestion de données et procédé de gestion de données - Google Patents

Appareil de gestion de données, système de gestion de données et procédé de gestion de données Download PDF

Info

Publication number
WO2024101293A1
WO2024101293A1 PCT/JP2023/039822 JP2023039822W WO2024101293A1 WO 2024101293 A1 WO2024101293 A1 WO 2024101293A1 JP 2023039822 W JP2023039822 W JP 2023039822W WO 2024101293 A1 WO2024101293 A1 WO 2024101293A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
information
data management
management device
status
Prior art date
Application number
PCT/JP2023/039822
Other languages
English (en)
Japanese (ja)
Inventor
光司 天野
佑介 中西
潤 小池
Original Assignee
株式会社日立製作所
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from JP2022180566A external-priority patent/JP2024070142A/ja
Priority claimed from JP2022180580A external-priority patent/JP2024070147A/ja
Application filed by 株式会社日立製作所 filed Critical 株式会社日立製作所
Publication of WO2024101293A1 publication Critical patent/WO2024101293A1/fr

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/60—Testing or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry

Definitions

  • the present invention relates to a data management device, a data management system, and a data management method.
  • Patent Document 1 JP 2011-31711 A
  • Patent Document 1 JP 2011-31711 A
  • the system includes a control processing device having a storage device that stores geospatial information within a line section, a train having an on-board observation device and a real-time train position and speed measurement device, ground observation devices within the line section, a control center, and an external organization that provides weather information and earthquake information, and by combining ground observation data from the ground observation devices, on-board observation data from the on-board observation devices, vehicle position and speed information from the real-time train position and speed measurement device, the geospatial information, weather information and earthquake information from the external organization, and observation data obtained from other trains and transmitted from the control center, highly accurate disaster predictions are performed on the train.”
  • position information when collecting vehicle position information, it is possible to use distance traveled information from speed pulses, position information from the Global Positioning System (GPS), and position information based on door-opening events. Since these types of position information vary in format and reliability, an important issue was how to handle it simply despite the differences in format, etc. Furthermore, position information is used for a variety of purposes and applications, such as operation control, troubleshooting, and analysis, and the requirements for the amount of data and reliability vary depending on the purpose and application.
  • GPS Global Positioning System
  • the present invention aims to achieve efficient use of diverse information.
  • one of the representative data management devices and data management systems of the present invention comprises a calculation device and a memory device, the memory device stores status information indicating a status related to an object of analysis, and the calculation device accepts a data provision request that partially specifies a structure that contributes to identifying the status information, searches for and provides status information that matches the partial specification from status information of different formats, accepts edits to the provided status information, and generates standardized data processing for the object of analysis based on the data provision request and the content of the edits.
  • one representative data management method of the present invention is characterized in that it includes the steps of a data management device storing status information indicating a status related to an analysis target, accepting a data provision request that partially specifies a structure that contributes to identifying the status information, searching for status information that matches the partial specification from status information of different formats, providing the results of the search, accepting edits to the provided status information, and generating standardized data processing for the analysis target based on the data provision request and the content of the edits.
  • the present invention makes it possible to realize efficient use of a wide variety of information. Problems, configurations, and advantages other than those described above will become clear from the description of the embodiments below.
  • FIG. 1 is an explanatory diagram of a configuration of a railway operation data management system according to a first embodiment.
  • FIG. 13 is an explanatory diagram of input of a data provision request.
  • An explanatory diagram of data editing (part 1).
  • An explanatory diagram of data editing (part 2).
  • An explanatory diagram of editing data (part 3).
  • An explanatory diagram of data editing (part 4).
  • An explanatory diagram of data editing part 5).
  • An explanatory diagram of editing data part 6
  • An explanatory diagram of editing data part 7).
  • 13 is a specific example of a data request packet.
  • An example of a dimensional integration table. 13 is a flowchart for generating a data search edit query in conjunction with an edit screen.
  • FIG. 13 is a diagram illustrating node error.
  • FIG. 11 is an explanatory diagram of the configuration of a railway operation data management system according to a second embodiment.
  • FIG. 11 is an explanatory diagram of control generation according to the second embodiment. 13 is a flowchart of control triggered by event information from a train.
  • FIG. 11 is an explanatory diagram (part 1) of know-how data generation according to the second embodiment.
  • FIG. 13 is an explanatory diagram (part 2) of know-how data generation according to the second embodiment.
  • a specific example of a screen showing a train in operation (part 1).
  • Example 1 a railway operation data management system that analyzes various data related to railway operation
  • Example 2 an example in which the railway operation data management system uses the analysis results to perform driving assistance or automatic driving of railway vehicles will be described.
  • components having substantially the same functions or configurations are denoted by the same reference numerals and redundant explanations will be omitted.
  • FIG. 1 is an explanatory diagram of the configuration of a railway operation data management system.
  • the railway operation data management system includes a user terminal 1 and a server system 2 serving as a data management device.
  • the user terminal 1 is a computer equipped with an internal CPU (Central Processing Unit) 1-3 and a main memory device 1-4, and is connected to peripheral devices such as a display device 1-1 and a disk 1-2 serving as an auxiliary memory device.
  • the user terminal 1 accepts an operation by the user 9 and transmits a data provision request to the server system 2. Then, the user terminal 1 receives a data response from the server system 2 and causes the display device 1-1 to display the data.
  • CPU Central Processing Unit
  • the server system 2 includes one or more servers 3 and one or more storages 5 .
  • the storage 5 is a storage device that stores status information indicating the status of the railway operation.
  • the storage 5 can also store a search log.
  • the configuration of the server 3 will be described below by taking as an example a server 3-a which is one of the one or more servers 3.
  • the server 3 has a CPU 3-1 which is a computing device, a memory 3-2 which is a main storage device, a network interface card (NIC) 3-3, a disk controller 3-4, and a disk 3-5 which is an auxiliary storage device.
  • NIC network interface card
  • the CPU 3-1 loads programs and data into the memory 3-2 and executes the programs in sequence to realize various functions.
  • the memory 3-2 stores data related to an OS (Operating System) 3-11, a use case threshold table 3-12, a state management function 3-13, a dimension integration table 3-14, a reliability analysis function 3-15, a railway topology management table 3-21, timetable information 3-22, an event management dictionary 3-23, a search target and a valid width for a width candidate dictionary 3-24, and an extracted know-how data after overlay 3-25.
  • OS Operating System
  • the OS 3-11 is a group of programs responsible for controlling the basic operations of the server 3.
  • the use case threshold table 3-12 is a table that associates the data threshold required for each use case.
  • the state management function 3-13 is a function for finding an error that occurs in the state information by comparing a plurality of state information acquired in different formats for the same state.
  • the dimension integration table 3-14 is a table that associates the hierarchical data acquisition purpose, a data table of status information corresponding to the search results, and occurrence errors of the status information.
  • the reliability analysis function 3-15 is a function for analyzing the reliability of a plurality of pieces of status information acquired in different formats regarding the same status. For example, in the case where the position information of a railway vehicle is obtained by acquiring the opening and closing of the doors of the railway vehicle, the travel distance information based on the speed pulse, and the GPS position information, the reliability analysis function 3-15 increases the reliability of the position information based on the event of door opening when the event occurs, decreases the reliability of the travel distance information when the traveling speed is below a predetermined level, and changes the reliability of the GPS position information according to the map information.Then, the reliability corresponding to each piece of position information is integrated to obtain the reliability of the final position information. If the data provision request specifies a tolerance, the reliability analysis function 3-15 further provides the result of comparison between the occurring error and the tolerance together with the status information of the search results.
  • the railway topology management table 3-21 is a table for managing the network topology that indicates the network configuration of a railway.
  • the timetable information 3-22 is data showing the operation status of trains.
  • the event management dictionary 3-23 is data that associates the event to be analyzed with the status information at the time the event occurred.
  • the appropriate range 3-24 for the search target and width candidate dictionary is determined as the appropriate range when searching for data using know-how data 3-25 and using a specified range of the search results. This appropriate range is determined from the editing history of the data included in the search log.
  • the extracted know-how data 3-25 after overlay is generated from the search log as know-how for data acquisition and editing.
  • the search log includes the specified search conditions, search results, the time required for the search, and the editing performed on the search results.
  • the railway operation data management system generates a query from the search log that can be used for searches and editing at other times.
  • This query is standardized data processing for the analysis target. By using this query, searches and editing performed by an expert in the past can be utilized for searches and editing at any time in the future.
  • FIG. 2 is an explanatory diagram of inputting a data provision request.
  • the display device 1-1 of the user terminal 1 displays the input area for the data provision request shown in FIG. 2 on the screen 1-1-1.
  • the input area has a data type, target data identifier, error value, search condition content, and search condition specification box.
  • the data type is the type of data used to search for information for data editing.
  • the data types correspond to the railway topology management table 3-21, timetable information 3-22, matter management dictionary 3-23, search target and valid width for the width candidate dictionary 3-24, and extracted know-how data after overlay 3-25 shown in Figure 1.
  • the target data identifier indicates how the target data is identified. For example, in railway topology management tables and timetable information, the storage location of the target data is indicated by its position in the hierarchical structure, such as "column/nested data/structure identifier/target identifier.” In event information, an identifier that is assigned in advance to the type of event is used. In a reasonable range, it can be identified by time or kilometre distance. The know-how data after overlay is generated from past search logs, and has not yet been generated in the state shown in Figure 2.
  • the error value indicates the range between the maximum and minimum values permitted for that item.
  • the error value is shown as "none.”
  • the error value is shown as "severe disruption.”
  • the error value is shown as "60 minutes.”
  • the error value is shown as "0.2 m.”
  • search condition content specific search conditions for the value of that data type can be entered.
  • search condition specification box it is possible to specify whether or not to use that data type as a search condition. Note that the data types shown in Figure 2 are merely examples, and more can be added as appropriate. For this reason, a button for adding conditions is also provided in the input area.
  • FIGs 3 to 10 are explanatory diagrams of editing data provided in response to a data request.
  • display device 1-1 displays two different types of data related to distance and position as a result of a data request.
  • One type of data is distance traveled information from the speed pulse, known as kilometers.
  • kilometers When the train's speed is below 3 km/m, it is difficult to obtain accurate speed pulses based on the rotation of the wheels, so the reliability of kilometers is low, but when the speed exceeds 3 km/m, it shows high reliability.
  • the other type of data is the event when a train opens its doors at a station, known as a door-opening event.
  • Door-opening events occur only when the train's position is precisely aligned with the platform, and are therefore more reliable than kilometres.
  • door-opening events occur precisely on the station platform, they cannot provide position information while the train is traveling between stations.
  • the screen 1-1-1 of the display device 1-1 displays a data editing layer addition area 1-1-1a and a cursor 1-1-1b.
  • the screen 1-1-1 also displays the following editing screen buttons: a layer deletion button 1-1-1c, a scale adjustment button 1-1-1d, a layer alignment button 1-1-1e, a cutting plane condition setting button 1-1-1f, and a horizontal axis selection button 1-1-1g.
  • the data editing layer addition area 1-1-1a in Figure 3 shows the data type, target data identifier, error value, data and reliability, and usability determination for the kilometer distance data and door-opening event data.
  • the usability determination is a checkbox that selects whether or not to use the data. When a checkbox is turned on using the cursor, a layer is assigned to the corresponding data, making it possible to overlay the data.
  • Figure 3 shows the state in which layer 1 is assigned to the kilometer distance and layer 2 is assigned to the door-opening event.
  • the layer alignment button 1-1-1e is operated, and time is specified on the horizontal axis of layer 1.
  • the following information is displayed as properties. - The layer “Layer 1" that is selected and slid along the time axis - Difference between edit screen time scale and data time: -300msec - Error range for each layer's time is +-10 sec
  • the layer alignment button 1-1-1e is operated, and kilometers are specified on the horizontal axis of layer 1.
  • the following information is displayed as properties. - The layer “Layer 1" that is selected and slid along the time axis ⁇ The difference between the kilometer scale on the editing screen and the data is "-30m” - The error range of each layer is 100m.
  • the cut plane condition setting button 1-1-1f is operated, and the cursor 1-1-1b is used to select the reliability of layer 1.
  • the following information is displayed as properties. - The layer “Layer 1" that is selected and slid along the time axis ⁇ Intercepts to be removed based on reliability: "Less than 80%" It should be noted that a cut plane condition save button 1-1-1h is also displayed here, but details of this button will be described later. Furthermore, regarding the intercepts to be removed based on the data values, no input is accepted at the stage of FIG.
  • the cutting plane condition setting button 1-1-1f is operated, and the cursor 1-1-1b is used to select data on layer 1.
  • the following information is displayed as properties: - The layer “Layer 1" that is selected and slid along the time axis - Intercept to be removed based on data value "less than 30” ⁇ The intercept to be removed based on the horizontal axis value "above XXX"
  • the scale adjustment button 1-1-1d is operated, and the cursor 1-1-1b is used to change the scale of the data in layer 2.
  • the following information is displayed as properties: - Layer 2 is selected and slid along the time axis - Ratio to horizontal axis scale: -8% In this state, when the cutting plane condition save button 1-1-1h is operated, the state changes to that shown in FIG.
  • screen 1-1-1 displays the data of layers 1 and 2 after the cutting surface condition settings and scale adjustment have been applied. As properties, it displays various conditions, an input form for know-how names, and a button 1-1-1j for automatically converting data search and editing queries from editing conditions.
  • the various conditions include conditions for the period, conditions for the cut surface for each layer, and valid width. These are displayed based on the editing operations performed up to that point. These conditions can also be added, deleted, or modified as appropriate. In this way, by adding, deleting, or modifying conditions based on the actual search and editing content, a query can be generated that performs formalized data processing that can be applied to subsequent analyses. By using this query, it is possible to easily execute data processing similar to that performed by an expert, and in a sense, the expert's know-how is converted into a query.
  • the know-how name is the name given to the formulated data processing. This name may be given arbitrarily, or may be generated based on the contents of the data processing. After entering the various conditions and the know-how name, operating the Data Search Edit Query Automatic Conversion from Editing Conditions button 1-1-1j causes the server 3 to automatically generate a query.
  • the server 3 stores the generated query as the extracted overlaid know-how data 3-25, and displays it as a candidate during subsequent analysis.
  • this query is selected, the server 3 generates a data provision request similar to the data provision request packet, and performs editing on the corresponding data.
  • FIG. 11 shows a specific example of a data request packet.
  • FIG. 11 shows an example of packet 1-1-2a that specifies an event interval and a multidimensional tolerance range, and packet 1-1-2b that specifies a time interval and a multidimensional tolerance range.
  • These packets include elements for sending information to the server 3 that narrows down the data, such as the purpose of data analysis, multidimensional tolerance, and intervals based on time or events.
  • the data analysis purpose is "Past history analysis/Stop time/Stop time analysis/Operation efficiency.”
  • the multidimensional tolerance is specified as "*/Kilometers", value: "0", unit "m”. In this way, by using the wildcard "*" to ignore part of the data, it is possible to search for data in "Kilometers” with the unit "m” from a database stored in any data format. Note that kilometers indicates the travel distance calculated based on the speed pulse.
  • packet 1-1-2a specifies the events from “Control event/door open” to "Control event/door close”
  • packet 1-1-2b specifies the time from "2021-01-01T00:00:00" to "2021-01-01T00:01:00”. In this way, you can specify any format for the search range period to perform a search.
  • Figure 12 is a specific example of a dimension integration table.
  • the dimension integration table 3-14 is a management table that contains data acquisition objectives (user input values) hierarchically organized into at least one level, data templates on the server 3 side and their learning status, data tables, target data identifiers, and generated error values for comparison with allowable errors, and is used for analysis objectives and automatic learning of target data, etc.
  • FIG. 13 is a flowchart for generating a data search and editing query linked to the editing screen.
  • the server 3 narrows down the type and range of data making use of the characteristics of railways (step S100). For this narrowing down, identifiers indicating the storage location of the data or the structure of the data itself can be used.
  • narrowing down the type and range of data making use of the characteristics of railways involves identifying data based on railway topology and timetable information. Another characteristic of railways is that they use a wide variety of information that differs in format and reliability but can be superimposed. By appropriately selecting, editing, and superimposing such information, the desired data can be obtained.
  • Step S100 includes a step of accepting a data provision request that partially specifies a structure that contributes to identifying the status information, a step of searching for status information that matches the partial specification from status information of different formats, and a step of providing the results of the search.
  • step S101 the server 3 extracts and connects valuable data by editing the reliability and values on the editing screen (step S101).
  • this step S101 includes a step of accepting edits to the provided status information.
  • step S102 is a step for generating standardized data processing for the analysis target based on the data provision request and the editing contents.
  • Figure 14 is an explanatory diagram of railway topology. As shown in Figure 14, stations, tracks, signaling equipment, and so on on a line can be managed as nodes and links in the topology. Information such as distances on the line can be managed by assigning various coordinate systems to the nodes of the topology.
  • Figure 15 is an explanatory diagram of node errors. Nodes in railway topology may form a hierarchy.
  • Platform Edge the boundary between the track number and the railway line
  • Platform, Operational Point (station), and Railway Line form a hierarchy.
  • server 3 uses information with different reliability levels in combination, making it possible to effectively utilize information with low reliability.
  • FIG. 16 is an explanatory diagram of the configuration of a railway operation data management system in the second embodiment.
  • information indicating the running state of railway vehicles is provided to a server system 2 in real time.
  • the server 3 further includes a know-how search function 3-26 for each event reception and a prefetch condition table 3-27.
  • the know-how search function for each received event 3-26 is a function that searches the extracted and overlaid know-how data 3-25 for queries to be executed for real-time events related to railway vehicles.
  • the prefetch condition table 3-27 is a table that shows the conditions for extracting necessary information from multiple types of data in accordance with the timing of railway vehicle control, and for issuing control commands or transmitting information required for control to the vehicle.
  • FIG. 17 is an explanatory diagram of vehicle control in Example 2.
  • FIG. 18 shows a case where a control event in layer 2 is executed based on data in layer 1.
  • the current cursor indicates the current time in each layer, and a control event in layer 2 is executed based on the position of the current cursor in the data in layer 1. This time, an example is given of issuing a control command, but similar explanatory diagrams and flow charts would be used even in the case where the control itself is performed on the vehicle side and only information required for control is transmitted.
  • FIG. 18 is a flow chart of control triggered by event information from a train.
  • the server 3 receives an event from the train (step S200).
  • the know-how search function 3-26 for each event reception of the server 3 searches for a know-how template that corresponds to the received event (step S201). Through this search, the know-how search function 3-26 for each event reception checks whether a template is already in operation.
  • step S202 If the search result shows that the corresponding template is not active (step S202; No), the event reception know-how search function 3-26 launches the know-how template and makes it active (step S203).
  • step S202 If the template is active (step S202; Yes), or after the template is activated in step S203, the server 3 plots the current information in the active know-how template, judges whether the status is good or bad, and issues a control command (step S204).
  • FIGS. 19 and 20 are explanatory diagrams of know-how generation in the second embodiment.
  • FIG. 19 shows a case where data of layer 1 is acquired and a control event of layer 2 is executed.
  • the acquisition of data of layer 1, editing of the acquired data, and execution of a control event of layer 2 are registered as know-how data in the extracted overlaid know-how data 3-25.
  • a certain amount of time is required from the acquisition of data of layer 1 to the execution of a control event of layer 2. Therefore, a prefetch trigger that ensures sufficient time for the know-how data to be read in is selected, and the prefetch trigger and know-how data are associated and registered in the prefetch condition table 3-27.
  • FIG. 19 shows a state where data of layer 3 is selected as a prefetch trigger.
  • the screen 1-1-1 for registering know-how data is provided with a layer of the data to be used, an area for inputting logical calculation operations, and an input form for inputting the command to be executed when the logical calculation is established.
  • 21 to 23 are specific examples of screens when a train is in operation.
  • screen 1-1-1 displays a detailed analysis of know-how data. In this detailed analysis, the value at that time point is determined for each data used in the know-how data and displayed. The result of the determination is, for example, "within the acceptable range,”"delayed,””missing," etc.
  • the screen 1-1-1 displays the transition status of events. By using this transition status of events, it is possible to confirm what events may transition from the current status. In addition, it is possible to accumulate data that contributes to control improvement by comparing the state transitions registered in the know-how data with the event statistical information from the current train.
  • screen 1-1-1 shows the status of the control flow. This status of the control flow can visualize the progress of the control of the railway vehicle. It is also possible to display the distribution of transition probabilities at the branching of the control.
  • a railway operation data management system including a server 3 as a data management device comprises a CPU 3-1 as a calculation device and a storage 5 as a memory device, the memory device stores status information indicating a status related to the subject of analysis, the calculation device accepts a data provision request that partially specifies a structure that contributes to identifying the status information, searches for and provides status information that matches the partial specification from status information of different formats, accepts edits to the provided status information, and generates standardized data processing for the subject of analysis based on the data provision request and the content of the edits. Therefore, the data management device and the data management system can realize efficient use of various information.
  • the analysis target is railway operations
  • the computing device generates standardized data processing based on the data provision request, the content of the editing, and the network configuration of the railway. This makes it possible to take advantage of the unique characteristics of railways and realize efficient use of diverse information regarding railway operations.
  • the editing is, for example, superimposition of a plurality of pieces of status information.
  • the editing is, for example, editing in which the state information is extracted based on a value or a reliability. In this way, by standardizing the editing process of extracting and superimposing multiple pieces of status information based on their values and reliability, it becomes possible to widely utilize the know-how of experts.
  • the status information includes information indicating a running state of the railway vehicle
  • the standardized data processing is processing for associating control of the running of the railway vehicle with standardized data.
  • the arithmetic device uses the standardized data processing to obtain necessary information in advance according to the running state of the railway vehicle. Therefore, by issuing control commands or transmitting information required for control to the vehicle according to the timing of control, information corresponding to the running state of the railway vehicle can be used for driving assistance or autonomous driving.
  • it is possible to obtain autonomous driving assistance information by linking know-how information that obtains the information necessary for control decisions with real-time events that are received as precursors so that the information can be pre-fetched in advance at a reasonable time interval.
  • the system has a know-how set of query conversion rules based on multi-hierarchical information (static and dynamic event information) and pre-fetch condition information, and can provide autonomous driving assistance information triggered by real-time received events.
  • the present invention is not limited to the above-mentioned embodiment, but includes various modified examples.
  • the above-mentioned embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to having all of the configurations described.
  • know-how data which is a collection of search and editing queries
  • know-how data may be registered and generated when actual operations are performed, or it may be possible to accumulate search and editing logs and generate the data at any time later.
  • the normal embodiment has been described using railway operations as an example, but the present invention can be applied to any system that analyzes a variety of data.
  • 1 User terminal, 1-1: Display device, 1-1-1: Screen, 1-1-2: Packet, 1-2: Disk, 1-4: Main storage device, 2: Server system, 3: Server, 3-1: CPU, 3-2: Memory, 3-4: Disk controller, 3-5: Disk, 3-12: Threshold table for use cases, 3-13: State management function, 3-14: Dimension integration table, 3-15: Reliability analysis function, 3-21: Railway topology management table, 3-22: Timetable information, 3-23: Event management dictionary, 3-24: Validity range, 3-25: Know-how data, 3-26: Know-how search function for each event reception, 3-27: Prefetch condition table, 5: Storage, 9: User

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • Mechanical Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Train Traffic Observation, Control, And Security (AREA)

Abstract

La présente divulgation concerne un appareil de gestion de données qui comprend un dispositif de calcul et un dispositif de stockage. Le dispositif de stockage stocke des informations d'état indiquant un état associé à un sujet d'analyse. Le dispositif de calcul reçoit une demande de fourniture de données spécifiant partiellement une structure qui contribue à l'identification des informations d'état, recherche des informations d'état correspondant à la spécification partielle à partir d'informations d'état dans différents formats et fournit les informations d'état recherchées, reçoit une édition sur les informations d'état fournies et génère, sur la base de la demande de fourniture de données et du contenu de l'édition, un traitement de données stylisé pour le sujet d'analyse. Par conséquent, il est possible de réaliser une utilisation efficace d'un grand choix d'informations.
PCT/JP2023/039822 2022-11-10 2023-11-06 Appareil de gestion de données, système de gestion de données et procédé de gestion de données WO2024101293A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
JP2022180566A JP2024070142A (ja) 2022-11-10 2022-11-10 データ管理装置、データ管理システム及びデータ管理方法
JP2022-180580 2022-11-10
JP2022180580A JP2024070147A (ja) 2022-11-10 2022-11-10 データ管理装置、データ管理システム及びデータ管理方法
JP2022-180566 2022-11-10

Publications (1)

Publication Number Publication Date
WO2024101293A1 true WO2024101293A1 (fr) 2024-05-16

Family

ID=91032360

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2023/039822 WO2024101293A1 (fr) 2022-11-10 2023-11-06 Appareil de gestion de données, système de gestion de données et procédé de gestion de données

Country Status (1)

Country Link
WO (1) WO2024101293A1 (fr)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH10329717A (ja) * 1997-05-30 1998-12-15 Toshiba Corp 列車運行管理システム
US20060248045A1 (en) * 2003-07-22 2006-11-02 Kinor Technologies Inc. Information access using ontologies
CN101026627A (zh) * 2007-03-15 2007-08-29 上海交通大学 基于规则和可信度的多源数据融合系统
JP2018090139A (ja) * 2016-12-06 2018-06-14 東日本旅客鉄道株式会社 車両運用業務支援システム
WO2018206610A1 (fr) * 2017-05-08 2018-11-15 Apollo Rail Ltd Système décentralisé de commande de train basé sur des communications

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH10329717A (ja) * 1997-05-30 1998-12-15 Toshiba Corp 列車運行管理システム
US20060248045A1 (en) * 2003-07-22 2006-11-02 Kinor Technologies Inc. Information access using ontologies
CN101026627A (zh) * 2007-03-15 2007-08-29 上海交通大学 基于规则和可信度的多源数据融合系统
JP2018090139A (ja) * 2016-12-06 2018-06-14 東日本旅客鉄道株式会社 車両運用業務支援システム
WO2018206610A1 (fr) * 2017-05-08 2018-11-15 Apollo Rail Ltd Système décentralisé de commande de train basé sur des communications

Similar Documents

Publication Publication Date Title
Ghofrani et al. Recent applications of big data analytics in railway transportation systems: A survey
Lu et al. Case-based reasoning for automated safety risk analysis on subway operation: Case representation and retrieval
CN110775109B (zh) 一种基于调度指挥系统的高速铁路列车到站时间预测方法
CN105844435A (zh) 一种基于fmeca的地铁车辆故障信息管理系统
US20170236234A1 (en) Risk management method and system for a land transporation system
Bach et al. A case-based reasoning approach for providing machine diagnosis from service reports
CN104240017A (zh) 一种城市轨道交通线网联网管理的方法
CN114048882B (zh) 铁路故障处理运维决策建议方法
EP3086268A1 (fr) Appareil pour assister la planification de ressources opérationnelle et méthode pour assister la planification de ressources
CN108228378A (zh) 列车组故障预测的数据处理方法及装置
Xu et al. A traffic hotline discovery method over cloud of things using big taxi GPS data
CN117041269A (zh) 一种用于同步子数据库数据的实时双向同步系统
Zhao et al. Applying Hybrid Decision‐Making Method Based on Fuzzy AHP‐WOWA Operator for Emergency Alternative Evaluation of Unattended Train Operation Metro System
WO2024101293A1 (fr) Appareil de gestion de données, système de gestion de données et procédé de gestion de données
Andrzejczak et al. Computerization of operation process in municipal transport
CN112232553B (zh) 一种基于贝叶斯网络的高铁列车晚点影响因素诊断方法
US10402755B2 (en) Transportation service information providing apparatus, and transportation service information providing method
JP2024070147A (ja) データ管理装置、データ管理システム及びデータ管理方法
JP2024070142A (ja) データ管理装置、データ管理システム及びデータ管理方法
CN112732787A (zh) 面向动车组重要部件的设备画像与个性化运维服务方法
Yan et al. Evaluating railway operation safety situation in China based on an improved TOPSIS method: A regional perspective
Lin et al. Intuitionistic mechanism for weak components identification method of complex electromechanical system
JP2017154536A (ja) 乗務員運用管理システムおよび乗務員運用管理方法
CN112801537B (zh) 一种发电企业非停事故分析方法、系统、介质及设备
CN114398475A (zh) 数据处理方法、装置、电子设备以及存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23888641

Country of ref document: EP

Kind code of ref document: A1