WO2020090310A1 - Analysis system - Google Patents

Analysis system Download PDF

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Publication number
WO2020090310A1
WO2020090310A1 PCT/JP2019/038105 JP2019038105W WO2020090310A1 WO 2020090310 A1 WO2020090310 A1 WO 2020090310A1 JP 2019038105 W JP2019038105 W JP 2019038105W WO 2020090310 A1 WO2020090310 A1 WO 2020090310A1
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WO
WIPO (PCT)
Prior art keywords
data
analysis
passengers
route
processing unit
Prior art date
Application number
PCT/JP2019/038105
Other languages
French (fr)
Japanese (ja)
Inventor
綾乃 河江
Original Assignee
矢崎エナジーシステム株式会社
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
Application filed by 矢崎エナジーシステム株式会社 filed Critical 矢崎エナジーシステム株式会社
Priority to SG11202103186SA priority Critical patent/SG11202103186SA/en
Priority to CN201980064208.0A priority patent/CN112789670A/en
Publication of WO2020090310A1 publication Critical patent/WO2020090310A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06M—COUNTING MECHANISMS; COUNTING OF OBJECTS NOT OTHERWISE PROVIDED FOR
    • G06M7/00—Counting of objects carried by a conveyor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled

Definitions

  • the present invention relates to an analysis system.
  • Patent Document 1 discloses an information display system including a traffic information acquisition unit, an information output unit, and a display unit.
  • the traffic information acquisition unit acquires traffic information regarding traffic of a person.
  • the information output unit selectively outputs information based on the traffic information acquired by the traffic information acquisition unit.
  • the display unit displays the information selectively output by the information output unit in a place where a person corresponding to the passage information is passing.
  • This information display system for example, displays information according to the traffic volume of a person based on the traffic information acquired by the traffic information acquisition unit, thereby enabling charging according to the display effect of the information.
  • the system as described above uses, for example, a trade area survey, marketing, and advertisement to show an indicator of the flow of people at an arbitrary point or region, such as a traffic volume of a person or various indexes calculated based on the traffic volume.
  • the analysis system may, for example, analyze the tendency of the flow of a person on each route on which a moving body such as a bus moves. Even in such a case, the tendency of the flow of the person can be properly analyzed. Is desired.
  • the present invention has been made in view of the above circumstances, and an object of the present invention is to provide an analysis system capable of appropriately analyzing the tendency of a person's flow.
  • the analysis system is mounted on each of a plurality of moving bodies that move on a plurality of routes, and image data representing an image of the inside of the moving body and an inside of the moving body.
  • a plurality of data collection devices for collecting analysis data including position data representing the position where the image of the image is captured, and based on the analysis data collected by the plurality of data collection devices, each of the plurality of routes
  • a data analysis device for counting the number of passengers of the plurality of moving bodies for each route is provided.
  • the data analysis device may count the number of passengers on the basis of the number of persons included in the image represented by the image data.
  • the data analysis device may identify one of the plurality of routes from the analysis data collected by the plurality of data collection devices based on the position data included in the analysis data. The number of passengers on the moving body that has traveled on the route is extracted, and the number of passengers on the specific route on all the moving bodies that have traveled on the specific route is aggregated, and all the numbers on the specific route The total number of passengers in the moving body may be counted.
  • the data analysis device analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes based on the analysis data. You can
  • the mobile body is internally provided with an output device capable of outputting content
  • the data analysis device is based on the number of passengers on each line of the plurality of lines.
  • An index representing the number of passers-by who have passed the acceptable range in which the content output by the output device can be received may be calculated for each of a plurality of routes.
  • the analysis system is capable of collecting image data representing an image inside each moving body and analysis data including position data by a plurality of data collecting devices respectively mounted on the plurality of moving bodies. It can. Then, the data analysis device can count the number of passengers of the plurality of moving bodies for each of the plurality of routes based on the analysis data collected by the plurality of data collection devices. As a result, this analysis system has an effect of being able to appropriately analyze the tendency of the flow of a person.
  • FIG. 1 is a block diagram showing a schematic configuration of the analysis system according to the first embodiment.
  • FIG. 2 is a diagram illustrating an example of the number of passengers in one moving body that is an analysis target of the analysis system according to the first embodiment.
  • FIG. 3 is a schematic diagram illustrating an example of a route along which one mobile body, which is an analysis target of the analysis system according to the first embodiment, travels.
  • FIG. 4 is a schematic diagram illustrating an example of a plurality of routes on which a plurality of mobile bodies that are the analysis targets of the analysis system according to the first embodiment travel.
  • FIG. 5 is a diagram illustrating an example of the number of passengers for each of a plurality of moving bodies that are the analysis targets of the analysis system according to the first embodiment.
  • FIG. 1 is a block diagram showing a schematic configuration of the analysis system according to the first embodiment.
  • FIG. 2 is a diagram illustrating an example of the number of passengers in one moving body that is an analysis target of the analysis system according to the first embodiment.
  • FIG. 6 is a diagram illustrating an example of the number of passengers on each of a plurality of routes, which are the analysis targets of the analysis system according to the first embodiment.
  • FIG. 7 is a diagram illustrating an example of the number of passengers on each of a plurality of routes, which are the analysis targets of the analysis system according to the first embodiment.
  • FIG. 8 is a schematic diagram showing an example of analysis result data analyzed and processed by the analysis system according to the first embodiment.
  • FIG. 9 is a flowchart showing an example of processing in the analysis system according to the first embodiment.
  • the analysis system 1 of the present embodiment shown in FIG. 1 includes a recording device 10 as a plurality of data collection devices and an analysis device 20 as a data analysis device, and analyzes the analysis result data analyzed by the analysis device 20 as a client terminal.
  • This is a system provided to CL.
  • the analysis system 1 of the present embodiment utilizes the recording device 10 mounted on the moving body V and analyzes the tendency of the flow of a person based on image data collected by the recording device 10. Then, the analysis system 1 of the present embodiment combines the analysis data collected by the recording device 10 mounted on each of the plurality of moving bodies V moving on the plurality of routes, so that the number of persons can be properly calculated for each route. This is a configuration that can analyze the tendency of flow.
  • the configuration of the analysis system 1 will be described in detail with reference to the drawings.
  • the recording device 10 is mounted on the mobile body V and collects analysis data used for analysis by the analysis device 20.
  • the analysis data collected by the recording device 10 is data including image data and position data.
  • the image data is data representing an image inside the moving body V.
  • the position data is data representing the position where the image inside the moving body V is captured.
  • the recording device 10 collects image data and position data as analysis data.
  • the analysis data is used by the analysis device 20 to analyze the tendency of the flow of a person.
  • the moving body V on which the recording device 10 is mounted is typically an object configured to be movable on a plurality of predetermined routes.
  • the moving body V is typically a vehicle such as a private car, a rental car, a sharing car, a ride-sharing car, a bus, a taxi, a truck, a transport vehicle, or a work vehicle that travels on a road surface.
  • the moving body V is not limited to a vehicle, and may be a flying body such as a flying car or a drone that flies in the air.
  • the moving body V of the present embodiment will be described as an example of a route bus that repeatedly travels on a plurality of predetermined routes during a day.
  • a moving body V such as a route bus travels on a plurality of routes during one day while one moving body V travels on a plurality of routes in order to improve the efficiency of vehicle allocation.
  • the recording device 10 of the present embodiment is mounted on each of the plurality of moving bodies V moving on the plurality of routes in this manner. That is, the analysis system 1 of the present embodiment includes a plurality of recording devices 10 respectively mounted on a plurality of moving bodies V moving on a plurality of routes, and can collect analysis data from the plurality of recording devices 10. It is possible.
  • the recording device 10 includes an internal camera 11, a position information measuring device 12, a data input / output unit 13, and a control unit 14.
  • an in-vehicle device such as a so-called drive recorder mounted on the moving body V can be used, but the invention is not limited to this.
  • the internal camera 11 is an internal imaging device that captures an image of the inside of the moving body V, that is, the inside of the vehicle.
  • the internal camera 11 captures an image inside the moving body V and collects image data representing the image inside the moving body V.
  • the internal camera 11 typically captures a moving image inside the moving body V.
  • the internal camera 11 is installed in the moving body V so as to have an angle of view capable of imaging a person who is an analysis target by the analysis system 1, here, a passenger in the vehicle of the moving body V and the like.
  • a plurality of internal cameras 11 may be provided on a ceiling portion or the like inside the moving body V so that a person inside the moving body V can be imaged more preferably.
  • the internal camera 11 may be a monocular camera or a stereo camera.
  • the image captured by the internal camera 11 may be monochrome or color.
  • the control unit 14 is communicably connected to the internal camera 11 and can exchange various signals and data with each other.
  • the internal camera 11 outputs the collected image data to
  • the position information measuring device 12 is a positioning device that measures the current position of the mobile body V.
  • the position information measuring device 12 may be, for example, a GPS receiver that receives radio waves transmitted from a GPS (Global Positioning System) satellite.
  • the position information measuring device 12 receives radio waves transmitted from GPS satellites and acquires GPS information (latitude / longitude coordinates) as information indicating the current position of the mobile body V, whereby an image inside the mobile body V is captured. Collect location data that represents the location.
  • the position information measuring device 12 is communicably connected to the control unit 14 and outputs the collected position data to the control unit 14.
  • the data input / output unit 13 inputs / outputs various data between a device different from the recording device 10 and the recording device 10.
  • the data input / output unit 13 of the present embodiment can output analysis data to the analysis device 20, which is a device different from the recording device 10.
  • the data input / output unit 13 may be configured to input / output data to / from a device different from the recording device 10 by communication (whether wired or wireless) via a network, for example. Further, the data input / output unit 13 may be configured to input / output data to / from a device different from the recording device 10 via a recording medium having a slot portion and inserted into the slot portion, for example. Good.
  • the recording medium is, for example, a memory (removable medium) that can be attached to and detached from the recording device 10 via the slot portion.
  • the recording medium may be, for example, a memory card of various formats, for example, an SD card, but is not limited to this.
  • the control unit 14 centrally controls each unit of the recording device 10.
  • the control unit 14 executes various arithmetic processes for collecting analysis data.
  • the control unit 14 mainly includes a central processing unit such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and a well-known microcomputer including an interface. It is configured to include an electronic circuit.
  • the control unit 14 is communicably connected to the internal camera 11, the position information measuring device 12, the data input / output unit 13, and the like, and can exchange various signals and data with each other.
  • control unit 14 is configured to include a storage unit 14A and a processing unit 14B.
  • the storage unit 14A and the processing unit 14B can exchange various signals and data with each other.
  • the storage unit 14A stores conditions and information necessary for various processes in the processing unit 14B, various programs and applications executed by the control unit 14, control data, and the like.
  • the storage unit 14A can store the analysis data together with the collected time and the like. In other words, the analysis data also includes time data indicating the time when the data was collected and other data.
  • the storage unit 14A can also temporarily store various data generated in the process of processing by the processing unit 14B, for example. These data are read from the storage unit 14A by the processing unit 14B, the data input / output unit 13 and the like as needed.
  • the storage unit 14A can rewrite a relatively large-capacity storage device such as a hard disk, SSD (Solid State Drive), or optical disk, or data such as RAM, flash memory, NVSRAM (Non Volatile Static Random Access Memory). Any semiconductor memory may be used.
  • the processing unit 14B executes various programs stored in the storage unit 14A based on various input signals, etc., and outputs various output signals to each unit when the program operates to realize various functions. Execute the process.
  • the processing unit 14B controls the operations of the internal camera 11 and the position information measuring device 12, and executes a process of collecting analysis data including image data and position data. Further, the processing unit 14B executes a process related to data input / output via the data input / output unit 13.
  • the processing unit 14B executes, for example, a process of outputting the analysis data to the analysis device 20 via the data input / output unit 13.
  • the analysis device 20 analyzes the analysis data collected by the recording device 10 and provides the analysis result data representing the analysis result to the client terminal CL.
  • the analysis device 20 and the client terminal CL may form a so-called cloud service type device (cloud server) mounted on the network, or a so-called stand-alone type device separated from the network. Good.
  • the analysis device 20 of the present embodiment counts the number of passengers of the plurality of moving bodies V for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10.
  • the analysis device 20 of the present embodiment analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10. ..
  • the analysis device 20 of the present embodiment generates analysis result data based on the counting result of the number of passengers of the moving body V for each route, the analysis result of the attribute of the person who got on the moving body V, and the like, and the analysis result.
  • the data is provided to the client terminal CL.
  • the analysis device 20 executes various calculation processes for counting the number of passengers of a plurality of moving bodies V for each route based on the analysis data. Further, the analysis device 20 executes various arithmetic processes for analyzing the attributes of the person who has boarded the moving body V based on the analysis data.
  • the analysis device 20 is configured to include a central processing unit such as a CPU and a GPU, a ROM, a RAM, and an electronic circuit mainly including a well-known microcomputer including an interface.
  • the analysis device 20 can also be configured by installing an application that realizes various processes described below in a known computer system such as a PC or a workstation. Further, the analysis device 20 may be configured by combining a plurality of PCs so that they can communicate with each other.
  • the analysis device 20 includes a data input / output unit 21, a storage unit 22, and a processing unit 23.
  • the data input / output unit 21, the storage unit 22, and the processing unit 23 can exchange various signals and data with each other.
  • the data input / output unit 21 inputs / outputs various data between a device different from the analysis device 20 and the analysis device 20.
  • the data input / output unit 21 of the present embodiment can input analysis data from the recording device 10, which is a device different from the analysis device 20.
  • the data input / output unit 21 of the present embodiment can output the analysis result data to the client terminal CL, which is a device different from the analysis device 20.
  • the data input / output unit 21 inputs / outputs data to / from a device different from the analysis device 20, for example, by communication (whether wired or wireless) via a network. May be
  • the data input / output unit 21 is configured to input / output data to / from a device different from the analysis device 20 via, for example, a recording medium having a slot portion and inserted into the slot portion. Good.
  • the storage unit 22 stores conditions and information necessary for various processes in the processing unit 23, various programs and applications executed by the processing unit 23, control data, and the like.
  • the storage unit 22 can store the analysis data input by the data input / output unit 21.
  • the storage unit 22 can also temporarily store various data generated in the process of the processing by the processing unit 23, for example. These data are read from the storage unit 22 by the data input / output unit 21, the processing unit 23, and the like as needed.
  • the storage unit 22 may be, for example, a relatively large-capacity storage device such as a hard disk, SSD, or optical disk, or a rewritable semiconductor memory such as RAM, flash memory, or NVSRAM.
  • the storage unit 22 is functionally conceptually an analysis target database (hereinafter abbreviated as “analysis target DB”) 22A, an analysis reference database (hereinafter abbreviated as “analysis reference DB”). 22B and an analysis result database (hereinafter abbreviated as “analysis result DB”) 22C.
  • analysis target DB an analysis target database
  • analysis reference DB an analysis reference database
  • analysis result DB an analysis result database
  • the analysis target DB 22A is a part that accumulates analysis data (image data, position data, time data, etc.), which is analysis target data by the processing unit 23, and stores it as a database.
  • analysis data image data, position data, time data, etc.
  • the analysis data input from the recording device 10 to the data input / output unit 21 is stored in the analysis target DB 22A.
  • the analysis reference DB 22B is a part that accumulates the analysis reference data to be referred to when the processing unit 23 analyzes the analysis data, and stores it as a database.
  • the analysis reference data includes, for example, map reference data, attribute prediction reference data, and the like.
  • the map reference data is data representing a map to be referred to when the position of the moving body V, in other words, the position where the image inside the moving body V is captured, is specified based on the position data or the like.
  • the attribute prediction reference data is data that is referred to when estimating the attribute of a person included in the image represented by the image data. The attribute prediction reference data will be described in detail later.
  • the analysis reference data is referred to by the processing unit 23 when the analysis data is analyzed.
  • the analysis result DB 22C is a part for accumulating analysis result data representing the analysis result of the analysis data by the processing unit 23, converting it into a database, and storing it.
  • the analysis result data is, for example, data based on the counting result of the number of passengers of the moving body V for each route (passenger number data by route), the analysis result of the attribute of the person who got on the moving body V (person attribute data), and the like. is there.
  • the analysis result data is processed into a desired format by the processing unit 23, and is output and provided from the data input / output unit 21 to the client terminal CL.
  • various data stored in the analysis target DB 22A, the analysis reference DB 22B, and the analysis result DB 22C can be utilized as so-called big data (big data).
  • the processing unit 23 executes various programs stored in the storage unit 22 based on various input signals and the like, and executes various processes for analyzing the analysis data by operating the programs. In addition, the processing unit 23 executes processing for processing the analysis result data into a desired format. Further, the processing unit 23 executes a process related to data input / output via the data input / output unit 21. The processing unit 23 executes, for example, a process of outputting the analysis result data processed into a desired format to the client terminal CL via the data input / output unit 21.
  • the processing unit 23 functionally and conceptually includes a data preprocessing unit 23A, a data analysis processing unit 23B, and a data processing unit 23C.
  • the data preprocessing unit 23A is a unit that performs various preprocessing on the analysis data that is the analysis target data. As the preprocessing, the data preprocessing unit 23A executes, for example, processing for reading analysis data that is analysis target data from the analysis target DB 22A and cutting out a still image from the moving image represented by the image data included in the analysis data. .. In addition, the data preprocessing unit 23A includes, as preprocessing, for example, the still image cut out, the position represented by the position data included in the analysis data that is the analysis target data, and the analysis data that is the analysis target data. The process of associating with the time represented by the time data is executed.
  • the data analysis processing unit 23B is a unit that counts the number of passengers of a plurality of moving bodies V for each route of a plurality of routes based on the analysis data preprocessed by the data preprocessing unit 23A.
  • the data analysis processing unit 23B counts the number of passengers of each mobile object V to be analyzed, based on the image data included in the analysis data preprocessed by the data preprocessing unit 23A. ..
  • the data analysis processing unit 23B counts the number of passengers of each moving body V based on the number of persons included in the image represented by the image data.
  • the data analysis processing unit 23B executes a process of detecting and extracting a person from the still image cut out by the data preprocessing unit 23A based on the image data, using various known image processing techniques. Then, the data analysis processing unit 23B counts the number of detected and extracted persons, and calculates the counted number of persons as the number of passengers inside the moving body V.
  • the data preprocessing unit 23A may perform detection and extraction of a person included in the image represented by the image data on all the collected image data, or on the door of the route bus that constitutes the moving body V. It may be performed only for image data collected during a predetermined period including opening and closing. In this case, the data preprocessing unit 23A may specify the image data collected in the predetermined period based on the image itself represented by the image data, or when the recording device 10 collects the image data, The image data collected during the predetermined period may be specified in advance by various known methods using the opening and closing of the bus door as a trigger.
  • the data analysis processing unit 23B When the person is detected from the image represented by the image data, the data analysis processing unit 23B reads the position data and the time data associated with the image data in which the person is detected from the analysis target DB 22A. Then, the data analysis processing unit 23B collects the image data in which the person is detected, based on the read position data, time data, and map reference data (analysis reference data) stored in the analysis reference DB 22B. The position and time of the moving body V at the time of the occurrence are specified. Then, the data analysis processing unit 23B identifies the position and time of the moving body V when the image of the inside of the moving body V is captured, and arranges the positions in time series, and the moving body V of each time and position is determined. Identify the number of passengers inside.
  • the data analysis processing unit 23B based on the identified position and time of the moving body V, the line on which the moving body V, which is the target of counting the number of passengers, travels among a plurality of predetermined lines, Also, specify the time when the vehicle traveled on the route.
  • the data analysis processing unit 23B then counts the number of passengers, the moving body V, the route on which the moving body V travels, the time when the moving body travels on the line, and the moving body V on the specified line / time. Specify the number of passengers in and link them to each other.
  • the data analysis processing unit 23B generates, as the analysis result data obtained by analyzing the analysis data, the number-of-passengers-by-mobile-body data that includes the various information identified as described above.
  • the number of passengers for each moving body V is data regarding the number of passengers for each moving body V, and the moving body V for which the number of passengers has been counted, the number of passengers for the moving body V for each time / position, It is data representing the route on which the mobile body V traveled, the time when the mobile body V traveled, and the number of passengers of the mobile body V on the specified route / time. Then, the data analysis processing unit 23B accumulates the analysis result data including the generated passenger number data for each moving body in the analysis result DB 22C and stores it as a database.
  • FIG. 2 shows the number of passengers of each moving body V included in the number of passengers for each moving body generated by the data analysis processing unit 23B, and the moving body (route bus) V shown in FIG. 3 traveled.
  • the number of passengers of the moving body V on the route R1 is shown.
  • FIG. 2 shows the number of passengers of the moving body V per unit time that is arbitrarily set in advance.
  • FIG. 2 shows the number of passengers for one week (for seven days) with the unit time being 24 hours, that is, one day, and also shows the weekly average.
  • the unit time for indicating the number of passengers is not limited to one day, and may be set arbitrarily, for example, may be set to a shorter time or a longer time ( The same applies to the following description.).
  • the data analysis processing unit 23B can count the number of passengers per unit time set arbitrarily.
  • the data analysis processing unit 23B of the present embodiment performs the above-described processing of counting the number of passengers inside the moving body V for all moving bodies V traveling on a plurality of routes. Then, the data analysis processing unit 23B counts the number of passengers of the plurality of moving bodies V for each of the plurality of routes. That is, the data analysis processing unit 23B aggregates the number of passengers on all of the moving bodies V that have traveled on a specific route among the plurality of routes, and totals all the moving bodies V on the specific route. The number of passengers (total number of passengers) is counted.
  • the data analysis processing unit 23B of the present embodiment uses the analysis data collected by the plurality of recording devices 10 to determine a specific route among the plurality of routes.
  • the number of passengers of the moving body V that has moved is extracted.
  • the data analysis processing unit 23B extracts, from the above-mentioned data on the number of passengers on board for each moving body, the data on the number of passengers on board for each moving body V that has traveled on a specific route, and moves on the specific route.
  • the number of passengers may be extracted.
  • the data analysis processing unit 23B extracts the analysis data collected by the mobile body V that has moved the specific route from the analysis data collected by the plurality of recording devices 10, and moves the specific route.
  • the number of passengers of the moving body V may be extracted. Then, the data analysis processing unit 23B aggregates the number of passengers on the specific route of the number of passengers of all the moving bodies V that have traveled on the extracted specific route, and totals all the movable bodies V on the specific route. The number of passengers (total number of passengers) is counted.
  • the data analysis processing unit 23B firstly analyzes, from the analysis data collected by the plurality of recording devices 10, based on the position data included in the analysis data preprocessed by the data preprocessing unit 23A, The numbers of passengers of all the moving bodies V that have moved on a specific route are extracted.
  • the data analysis processing unit 23B as a specific route, the number of individual passengers of all the mobile bodies V that have traveled on the route R21, the number of individual passengers of all the mobile bodies V that have traveled on the route R22, and the route R23.
  • the individual numbers of passengers of all the moving bodies V that have moved are extracted. As illustrated in FIG.
  • the data analysis processing unit 23B determines that all the movements of the bus A, the bus B, the bus C, and the bus D are the number of passengers of the moving body V that has moved along the route R21. The number of individual passengers of the body V is extracted. Similarly, the data analysis processing unit 23B sets the individual passenger numbers of all the moving bodies V on the buses A, B, C, and D as the individual passenger numbers of the moving bodies V traveling on the route R22. Extract. Then, the data analysis processing unit 23B, as the number of individual passengers of the moving body V traveling on the route R23, excludes the bus B, and the individual riding of the three moving bodies V of the bus A, the bus C, and the bus D. Extract the number of people.
  • FIG. 5 shows an example of the number of individual passengers of the moving body V on each of the extracted routes R21, R22, and R23 for each moving body V and for each unit time.
  • the unit time is 3 hours, and the number of passengers on a day is shown. Each movement is every 3 hours for one business day from the operation start time of 6:00 to the operation end time of 18:00. The number of passengers for each body V is shown.
  • FIG. 5 also shows the total number of passengers of each moving body V that does not specify the routes R21, R22, and R23, and the total number of passengers of each time zone that does not specify the routes R21, R22, and R23. ..
  • the data analysis processing unit 23B aggregates and totals the number of passengers on each of the routes R21, R22, R23 of the number of passengers of all the moving bodies V that have moved on the extracted specific routes R21, R22, R23. Thereby, the data analysis processing unit 23B counts the total number of passengers (total number of passengers) of all the moving bodies V on each of the routes R21, R22, and R23.
  • FIG. 6 shows the total number of passengers of all the mobile bodies V on each of the routes R21, R22, and R23 when the unit time is one business day (one day) in the example shown in FIG.
  • the data analysis processing unit 23B determines that the number of passengers on the route R21 for one business day is "6: 00-9: 00" on the bus A and "9: 00-12: 00" on the bus B.
  • the number of passengers on the bus R, the number of passengers on the bus C from “15:00 to 18:00”, and the number of passengers on the bus D from “12:00 to 15:00” are aggregated and added to obtain 1 on the route R21.
  • the total number of passengers for business days can be counted (see “330” in FIG. 6).
  • the data analysis processing unit 23B determines, as the number of passengers on the route R22 for one business day, the number of passengers on the bus A at "9: 00-12: 00" and “12: 00-15: 00", and the bus B at the same time.
  • Bus C "6: 00-9: 00", "9:”
  • the total number of passengers for one business day on the relevant route R22 is calculated by aggregating and adding up the number of passengers on "00-12: 00" and the number of passengers on "15: 00-18: 00" on bus D (See “900” in FIG. 6).
  • the data analysis processing unit 23B determines that the number of passengers on the route R23 for one business day is "15: 00-18: 00" for the bus A and "12: 00-15: 00" for the bus C.
  • the total number of passengers on the bus R and the total number of passengers on the bus D at "6: 00-9: 00" and “9: 00-12: 00" are aggregated to add up for one business day on the route R23.
  • the number of people can be counted (see “225” in FIG. 6).
  • FIG. 6 also shows the total number of passengers on the plurality of routes R21, R22, and R23, which is the total number of passengers for one business day.
  • the data analysis processing unit 23B further combines a plurality of passengers on each of the routes R21, R22, R23 for one business day to determine the number of passengers on each of the routes R21, R22, R23. It is also possible to count. Similar to FIG. 2, FIG. 7 shows the number of passengers of all the mobile bodies V on each of the routes R21, R22, and R23 for one week (seven days worth), where the unit time is 24 hours, that is, one day. ing. Note that FIG. 7 also shows the weekly average number of passengers of all the mobile bodies V on each route R21, R22, R23, and the total number of passengers on each day of the week not specifying the routes R21, R22, R23. ..
  • the data analysis processing unit 23B generates, as the analysis result data obtained by analyzing the analysis data, the number-of-passengers-by-route data by route including the various information identified as described above.
  • the number of passengers by line is data on the number of passengers for each line, and is data indicating the line for which the number of passengers has been counted, the total number of passengers of all the mobile bodies V for each line, and the like. Then, the data analysis processing unit 23B accumulates the analysis result data including the generated passenger number data for each route in the analysis result DB 22C and stores it as a database.
  • the data analysis processing unit 23B of the present embodiment is also a unit that analyzes the attribute of a person included in the image represented by the image data, based on the analysis data preprocessed by the data preprocessing unit 23A.
  • the data analysis processing unit 23B analyzes the attributes of the person detected and extracted from the still image cut out by the data preprocessing unit 23A based on the image data.
  • the data analysis processing unit 23B typically analyzes the attribute of the person included in the image represented by the image data for each of the plurality of routes.
  • the data analysis processing unit 23B extracts, for example, from the analysis data collected by the plurality of recording devices 10, the analysis data collected by the mobile body V that has moved on a specific route based on the position data and the like. To do. Then, the data analysis processing unit 23B analyzes the attributes of the person included in the image represented by the image data, based on the extracted analysis data, to get on each moving body V for each route of the plurality of routes.
  • the data analysis processing unit 23B analyzes the routes R21, R22, and R23 collected by the mobile body V that has moved along each route.
  • the attribute of the person included in the image represented by the image data is analyzed based on the use data.
  • the data analysis processing unit 23B uses, for example, various known artificial intelligence (technical intelligence) techniques and deep learning (deep learning) techniques to identify the attribute of the person included in the image represented by the image data and the attribute. Is configured to be able to execute the process of analyzing the human flow of the identified person.
  • the data analysis processing unit 23B executes the process of detecting and extracting a person from the still image cut out by the data preprocessing unit 23A as described above. Then, the data analysis processing unit 23B of the present embodiment executes a process of extracting an image including the feature points of the detected and extracted person from the image represented by the image data.
  • the feature point of the person is a portion of the person included in the image that can specify the attribute of the person.
  • the characteristic point of the person is, for example, a face in which the person's facial expression appears, a limb in which a gesture / gesture appears, a position at which an accessory or the like tends to be worn, and the like.
  • the data analysis processing unit 23B extracts, for example, from a large number of images captured from different angles, an image showing a characteristic point of the person that can be used for identifying the attribute of the person.
  • the data analysis processing unit 23B executes a process of analyzing the attribute of the person included in the image based on the image including the feature points of the person extracted from the image data.
  • the data analysis processing unit 23B for example, based on the attribute prediction reference data (analysis reference data) stored in the analysis reference DB 22B and the feature points of the person included in the image extracted from the image data, Parse attributes.
  • the attribute prediction reference data reflects the results of learning the attributes of the person that can be estimated according to the feature points of the person included in the image by various methods using artificial intelligence technology and deep learning technology. Information.
  • the attribute prediction reference data was made into a database using various methods using artificial intelligence technology and deep learning technology in order to estimate the attribute of the person based on the feature points of the person included in the image.
  • This attribute prediction reference data can be updated sequentially.
  • the analysis result data person attribute data representing the analysis result by the data analysis processing unit 23B itself can be used as the data for learning.
  • the attribute of the person analyzed by the data analysis processing unit 23B typically, items that can be analyzed from the characteristic points of the appearance of the person, for example, sex, age, physique, social status, preference of the person, Or, it includes behavioral orientation.
  • the sex is an attribute indicating the sex of male and female.
  • Age is an attribute that represents the length of years from birth to the present (at that time).
  • the physique is an attribute that represents height, weight, various dimensions, and the like.
  • Social status is an attribute that represents occupation (self-employed, businessman, policeman, student, unemployed, part-time job), annual income, status, accompanying person, and the like.
  • the preference is an attribute that represents the tendency of clothes, personal belongings, and fashion (casual orientation, elegant orientation, brand orientation, luxury orientation, fast fashion orientation), hobbies (sports / subculture / outdoor / beauty, etc.), and the like.
  • the action-oriented attribute is an attribute that represents the mood, interest and interest (what you want to do, where you want to go), etc. at that time. That is, here, the data analysis processing unit 23B estimates gender, age, physique, social status, preference, action orientation, etc. as the attributes of the person.
  • the data analysis processing unit 23B refers to the attribute prediction reference data and extracts an attribute (gender, age, physique, social status, preference, or action-oriented) corresponding to the feature point of the person included in the image, It is estimated that the extracted attributes are the attributes of the person reflected in the image.
  • the data analysis processing unit 23B refers to the attribute prediction reference data according to, for example, a facial expression that is a feature point of a person included in an image, gestures / gestures of limbs, attached accessories or clothes, and the like. Attributes such as sex, age, physique, social status, preference, and behavior orientation of the person are estimated by matching the attributes that match the feature points.
  • the data analysis processing unit 23B executes processing for analyzing the position of the person whose attribute is specified as described above, based on the position data associated with the image data in which the attribute of the person is specified. ..
  • the data analysis processing unit 23B reads, for example, the position data associated with the image data in which the attribute of the person is specified from the analysis target DB 22A. Then, the data analysis processing unit 23B analyzes the position and the like of the person whose attribute is specified, based on the map reference data (analysis reference data) stored in the analysis reference DB 22B and the read position data. For example, the data analysis processing unit 23B refers to the map reference data and specifies the position where the image is captured based on the position data. Then, the data analysis processing unit 23B specifies the position of the person whose attribute is specified, based on the position represented by the position data.
  • the data analysis processing unit 23B includes, as analysis result data obtained by analyzing the analysis data, person attribute data representing the attributes of the person analyzed as described above, and attribute-based position data representing the position of the person whose attribute is specified. To generate. Then, the data analysis processing unit 23B accumulates the generated person attribute data and the analysis result data including the attribute-based position data in the analysis result DB 22C and stores it as a database.
  • the moving body V in which the recording device 10 of the present embodiment is mounted has the output device OD installed therein.
  • the output device OD is a device capable of outputting content, and is provided inside each of the plurality of moving bodies V.
  • the output device OD may be a so-called cloud service type device that is mounted on the network and provides various contents via the network, or a so-called stand-alone type device separated from the network. May be.
  • the output device OD is configured to include a display capable of displaying an image corresponding to the content, a speaker capable of outputting sound / voice corresponding to the content, and the like.
  • contents output by the output device OD for example, in addition to contents such as advertisements and coupons, various guide information such as regional information, route information to a predetermined facility, evacuation route / safety support information at the time of disaster, etc. is configured. It may include content.
  • the content data output by the output device OD can be sequentially updated via a network, a recording medium, or the like.
  • the data analysis processing unit 23B of the present embodiment may also be configured to be capable of executing, as the analysis result data, a process of generating commercial use data based on the number of passengers for each moving body, the number of passengers for each route, and the like. Good. Specifically, the data analysis processing unit 23 of the present embodiment calculates an index representing the number of passers-by who have passed the content acceptable range from the output device OD provided inside each moving body V.
  • the content acceptable range of the output device OD is a spatial range in which a person can receive the content output by the output device OD, and a visible range in which a person can visually recognize an image displayed by the output device OD, the output device OD. It is determined according to the audible range in which the person can hear the sound / voice output by.
  • the data analysis processing unit 23 calculates, for example, an index representing the number of passers-by who have passed the acceptable range for each route based on the number-of-passengers data for each route showing the number of passengers for each route.
  • the data analysis processing unit 23 based on the number of passengers for each moving body V, which indicates the number of passengers for each moving body V, is an index indicating the number of passers who have passed the acceptable range for each moving body V. May be calculated.
  • the data analysis processing unit 23 generates the commercial use data representing the index, accumulates the analysis result data including the generated commercial use data in the analysis result DB 22C, and stores it as a database.
  • the number of passers who have passed the content acceptable range of the output device OD can be regarded as the number of persons who have received the content of the output device OD. Then, when the output device OD is installed inside the moving body V, the acceptable range can be typically regarded as the entire inside of the moving body V. Therefore, the number of passers who have passed the content acceptable range of the output device OD inside the moving body V can be considered to be substantially the same as the number of passengers of the moving body V.
  • the data analysis processing unit 23B of the present embodiment sets the number of passengers of the moving body V as the number of passers in the content acceptable range. That is, here, the data analysis processing unit 23B sets the number of passengers for each mobile body V represented by the number of passengers for each mobile body as the number of passers in the content acceptable range for each mobile body V. Similarly, the data analysis processing unit 23B sets the number of passengers for each route represented by the number of passengers for each route as the number of passers in the content acceptable range for each route.
  • the data analysis processing unit 23B may use the number of passers who have passed the acceptable range of the content itself as an index indicating the number of passers, or calculate the index indicating the number of passers based on the number of passers. You may. Examples of the index representing the number of passers calculated by the data analysis processing unit 23B include “DEC: Daily Effective Circulation” and “GRP: Gross Rating Point”. “DEC” and “GRP” are both indicators of advertising effectiveness. “DEC” is typically the number of people who pass through the acceptable range (visible range) of the target advertisement per day.
  • the "DEC” may be the number of passers-by who is a person who satisfies a predetermined age limit, such as 18 years old or older, or may be the number of passers-by who is not subject to any age limit. .. “GRP” is typically the proportion of the daily number of people who pass the above-mentioned acceptable range in the target population within the area that can be reached for the target advertisement in one day. “GRP” can be represented by [DEC / target population in target area]. The “target population in the target area” is the population that satisfies the age restriction in the target area when the age limit is set for the target of “DEC”.
  • the data analysis processing unit 23B calculates “DEC” and “GRP” for each moving body V as an index representing the number of passing people based on the number of passing people in the content acceptable range for each moving body V. be able to. For example, the number of passengers in a day for each moving object V described in FIG. 2 and the average value thereof, the total number of passengers in each moving object V described in FIG. 5, and the like are “DEC” for each moving object V. Equivalent to.
  • the data analysis processing unit 23B calculates "DEC” and "GRP" for each route as an index indicating the number of passers based on the number of passers in the content acceptable range for each route. You can For example, the number of passengers on each day and the average value thereof for each route described in FIGS. 6 and 7 described above correspond to “DEC” for each route.
  • the data analysis processing unit 23B generates and generates commercial use data representing “DEC” and “GRP” for each moving body V and each route as an index representing the number of passers who have passed the acceptable range.
  • the analysis result data including the above-mentioned commercial use data can be accumulated in the analysis result DB 22C and stored as a database.
  • the data processing unit 23C is a unit that executes a process of processing the analysis result data analyzed by the data analysis processing unit 23B into a desired format.
  • the data processing unit 23C processes the number of passengers for each moving body, the data for the number of passengers for each route, the attribute data for each person, the flow data for each attribute, and the commercial use data, which are included in the analysis result data, into a desired format. For example, as illustrated in FIG.
  • the data processing unit 23C displays the analysis result data including the number of passengers by moving body, the number of passengers by route, the person attribute data, the person flow data by attribute, and the commercial use data when , Which route and how many people had attributes, "DEC", "GRP” for each mobile unit V, "DEC” for each route, “GRP”, etc. Process into a diagram. Then, the processing unit 23 executes a process of outputting the analysis result data processed into a desired format by the data processing unit 23C to the client terminal CL via the data input / output unit 21.
  • the client terminal CL makes it possible to use the analysis result data provided from the analysis device 20 for various purposes such as commercial area surveys, marketing, advertisements, judgment materials when determining advertising fees, disaster prevention and city planning, etc. Is.
  • the client terminal CL is composed of, for example, a notebook PC, a desktop PC, a tablet PC, a smartphone, a mobile terminal, or the like.
  • the plurality of recording devices 10 respectively mounted on the plurality of moving bodies V collect analysis data including image data and position data as the moving bodies V move (step S1).
  • the recording device 10 outputs the collected analysis data via the data input / output unit 13 and inputs it to the analysis device 20 via the data input / output unit 21 of the analysis device 20 (step S2).
  • the analysis data input to the analysis device 20 is stored in the analysis target DB 22A.
  • the data preprocessing unit 23A of the analysis device 20 performs various preprocessing as described above on the analysis data stored in the analysis target DB 22A (step S3).
  • the data analysis processing unit 23B of the analysis device 20 performs analysis based on the analysis data that has been preprocessed by the data preprocessing unit 23A, and as analysis result data, the number of passengers for each moving body, and for each route Passenger number data, person attribute data, attribute-based flow data, commercial use data, etc. are generated (step S4).
  • the data analysis processing unit 23B accumulates the generated analysis result data such as the number of passengers in each moving body data, the number of passengers in each route, the person attribute data, the attribute-based pedestrian flow data, and the commercial use data in the analysis result DB 22C and creates a database. And store it (step S5).
  • the data processing unit 23C of the analysis device 20 responds to a request from the client terminal CL or the like, and stores the analysis result data (the number of passengers for each moving body, the number of passengers for each route) stored in the analysis result DB 22C.
  • Person attribute data, attribute-based person flow data, commercial use data, etc. are processed into a desired format as illustrated in FIG. 8 (step S6).
  • the processing unit 23 of the analysis device 20 outputs and provides the analysis result data processed in the desired format by the data processing unit 23C to the client terminal CL via the data input / output unit 21 (step S7), A series of processing ends.
  • the analysis system 1 described above collects the image data representing the image inside each moving body V and the analysis data including the position data by the plurality of recording devices 10 respectively mounted on the plurality of moving bodies V. can do. Then, the analysis device 20 can count the number of passengers of the plurality of moving bodies V for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10. That is, in this analysis system, for example, in order to improve the efficiency of vehicle allocation, one moving body V travels on a plurality of routes in one day, and the plurality of moving bodies V travels on a plurality of routes.
  • the analysis system 1 can appropriately analyze the flow tendency of the person for each of the plurality of routes on which the plurality of moving bodies V move. Then, the analysis system 1 can analyze the tendency of the flow of people for each route analyzed as described above in various applications such as commercial area surveys, marketing, advertisements, judgment materials when deciding advertisement fees, disaster prevention and city planning, etc. It can be utilized.
  • the analysis system 1 described above counts the number of passengers of the moving body V based on the number of persons included in the image represented by the image data. As a result, the analysis system 1 can reduce the workload of counting and significantly improve the frequency of counting itself, as compared with the case where the number of passengers in the moving body V is counted manually, for example. You can As a result, the analysis system 1 can analyze the flow tendency of a person with higher accuracy.
  • the analysis system 1 described above extracts the number of passengers of the mobile body V that has moved on a specific route from the analysis data collected by the plurality of recording devices 10, and moves on the specific route.
  • the number of passengers on the specific route for each of all the moving bodies V is aggregated, and the total number of passengers of all the moving bodies V on the specific route is counted. Therefore, the analysis system 1 can properly count the total number of passengers of all the moving bodies on each of the plurality of routes based on the analysis data collected by the plurality of recording devices 10.
  • the analysis system 1 described above further analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes by the analysis device 20 based on the analysis data.
  • this analysis system in addition to the number of passengers of the moving body V, the person who got on the moving body V as a tendency of the flow of the person for each of the plurality of routes on which the plurality of moving bodies V move
  • the attributes of can also be analyzed.
  • the analysis system 1 can, for example, grasp not only the number of passengers on each route operated by the plurality of moving bodies V, but also the attribute tendency of the passenger on each route, and conversely, It is possible to easily specify a route or the like having many passengers having a desired attribute tendency.
  • the analysis system 1 can more appropriately utilize the tendency of the flow of the person for each route in various applications as described above.
  • the analysis system 1 based on the number of passengers of each of a plurality of routes by the analysis device 20, the content of the output device OD mounted on the moving body V of each route is displayed. An index representing the number of people who have passed the acceptable range is calculated.
  • the analysis system 1 suitably uses the index for each route, for example, as a determination material when determining the usage fee (advertising fee, etc.) of the content output from the output device OD for each route.
  • the analysis system 1 can suitably utilize the occupant's attribute tendency for each route, for example, as a determination material when determining the content to be output from the output device OD of the mobile unit V for each route.
  • the moving object V described above has been described as having the output device OD mounted therein, but is not limited to this.
  • the analysis device 20 has been described as calculating an index representing the number of passers-by who have passed the content acceptable range of the output device OD for each of a plurality of routes, but the present invention is not limited to this.
  • the analysis device 20 described above is described as analyzing the attributes of a person included in the image represented by the image data for each route of a plurality of routes, but the present invention is not limited to this.
  • the control unit 14 and the analysis device 20 described above may be configured such that each unit is configured separately and each unit is connected so as to be capable of exchanging various electrical signals with each other, and some functions are It may be realized by another control device.
  • the programs, applications, various data, and the like described above may be appropriately updated, or may be stored in a server connected to the analysis system 1 via an arbitrary network.
  • all or part of the programs, applications, various data, and the like described above can be downloaded as necessary.
  • all or an arbitrary part thereof may be realized by, for example, a CPU or the like and a program interpreted and executed by the CPU or the like. Also, it may be realized as hardware such as a wired logic.
  • the analysis system 1 performs primary image analysis such as clipping of an outer peripheral image including a person on each recording device 10 side, and according to the data based on the analysis data transmitted from each recording device 10 to the analysis device 20.
  • the analysis device 20 may perform secondary image analysis such as counting the number of passengers and analyzing the attributes of people. Further, for example, the analysis system 1 counts the number of individual passengers for each moving body V on the side of each recording device 10 to generate the number of passengers for each moving body, and the analysis transmitted from each recording device 10 to the analyzing device 20.
  • the number of passengers of the plurality of moving bodies V may be counted for each route on the analysis device 20 side to generate the passenger number data for each route.
  • Analysis system 10 Recording device (data collection device) 11 Internal Camera 12 Position Information Measuring Device 13, 21 Data Input / Output Unit 14 Control Unit 14A, 22 Storage Unit 14B, 23 Processing Unit 20 Analysis Device (Data Analysis Device) 22A Analysis target DB 22B Analysis reference DB 22C analysis result DB 23A Data pre-processing unit 23B Data analysis processing unit 23C Data processing processing unit CL Client terminal OD Output device R1, R21, R22, R23 Route V Mobile

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Abstract

An analysis system (1) is provided with: a plurality of data collection devices (10) that are mounted on a plurality of mobile bodies (V) moving on a plurality of routes and that collect analysis data including image data indicating inner images of the mobile bodies (V) and position data indicating positions at which the inner images of the mobile bodies (V) had been captured; and a data analysis device (20) that counts the number of passengers on the mobile bodies (V) for each of the routes on the basis of the analysis data collected by the data collection devices (10). As a result, the analysis system (1) provides an advantageous effect of being able to appropriately analyze the trend in human movement.

Description

解析システムAnalysis system
　本発明は、解析システムに関する。 The present invention relates to an analysis system.
　従来の解析システムとして、例えば、特許文献１には、通行情報取得ユニットと、情報出力ユニットと、表示ユニットとを備えた情報表示システムが開示されている。通行情報取得ユニットは、人の通行に関する通行情報を取得する。情報出力ユニットは、通行情報取得ユニットによって取得された通行情報に基づいて情報を選択的に出力する。表示ユニットは、情報出力ユニットが選択的に出力した情報を、通行情報に対応した人が通行している場所に表示する。この情報表示システムは、例えば、通行情報取得ユニットで取得された通行情報に基づいて人の通行量に応じて情報を表示させることで、当該情報の表示効果に応じた課金を可能としている。 As a conventional analysis system, for example, Patent Document 1 discloses an information display system including a traffic information acquisition unit, an information output unit, and a display unit. The traffic information acquisition unit acquires traffic information regarding traffic of a person. The information output unit selectively outputs information based on the traffic information acquired by the traffic information acquisition unit. The display unit displays the information selectively output by the information output unit in a place where a person corresponding to the passage information is passing. This information display system, for example, displays information according to the traffic volume of a person based on the traffic information acquired by the traffic information acquisition unit, thereby enabling charging according to the display effect of the information.
特開２００３－３０２９２３号公報JP, 2003-302923, A
　ところで、上述のようなシステムは、例えば、人物の通行量や当該通行量を基に算出した各種指標等、任意の地点や地域における人の流動の傾向を表す指標を、商圏調査、マーケティング、広告、広告料を決める際の判断材料、防災・都市計画等の様々な用途で活用する場合がある。そして、解析システムは、例えば、バス等の移動体が移動する各路線における人物の流動の傾向を解析する場合があるが、このような場合であっても適正に人物の流動の傾向が解析できることが望まれている。 By the way, the system as described above uses, for example, a trade area survey, marketing, and advertisement to show an indicator of the flow of people at an arbitrary point or region, such as a traffic volume of a person or various indexes calculated based on the traffic volume. , It may be used for various purposes such as judgment materials when deciding advertising fees and disaster prevention and city planning. The analysis system may, for example, analyze the tendency of the flow of a person on each route on which a moving body such as a bus moves. Even in such a case, the tendency of the flow of the person can be properly analyzed. Is desired.
　本発明は、上記の事情に鑑みてなされたものであって、人物の流動の傾向を適正に解析することができる解析システムを提供することを目的とする。 The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an analysis system capable of appropriately analyzing the tendency of a person's flow.
　上記目的を達成するために、本発明に係る解析システムは、複数の路線を移動する複数の移動体にそれぞれ搭載され、当該移動体の内部の画像を表す画像データ、及び、当該移動体の内部の画像が撮像された位置を表す位置データを含む解析用データを収集する複数のデータ収集装置と、前記複数のデータ収集装置によって収集された前記解析用データに基づいて、前記複数の路線の各路線ごとに、前記複数の移動体の乗車人数を計数するデータ解析装置とを備えることを特徴とする。 In order to achieve the above-mentioned object, the analysis system according to the present invention is mounted on each of a plurality of moving bodies that move on a plurality of routes, and image data representing an image of the inside of the moving body and an inside of the moving body. A plurality of data collection devices for collecting analysis data including position data representing the position where the image of the image is captured, and based on the analysis data collected by the plurality of data collection devices, each of the plurality of routes A data analysis device for counting the number of passengers of the plurality of moving bodies for each route is provided.
　また、上記解析システムでは、前記データ解析装置は、前記画像データが表す画像に含まれる人物の数に基づいて、前記乗車人数を計数するものとすることができる。 In the above analysis system, the data analysis device may count the number of passengers on the basis of the number of persons included in the image represented by the image data.
　また、上記解析システムでは、前記データ解析装置は、前記解析用データに含まれる前記位置データに基づいて、前記複数のデータ収集装置によって収集された前記解析用データから、前記複数の路線のうち特定の路線を移動した前記移動体の前記乗車人数を抽出し、当該特定の路線を移動した全ての前記移動体の当該特定の路線での前記乗車人数を集約し、当該特定の路線における全ての前記移動体の合計の前記乗車人数を計数するものとすることができる。 In the analysis system, the data analysis device may identify one of the plurality of routes from the analysis data collected by the plurality of data collection devices based on the position data included in the analysis data. The number of passengers on the moving body that has traveled on the route is extracted, and the number of passengers on the specific route on all the moving bodies that have traveled on the specific route is aggregated, and all the numbers on the specific route The total number of passengers in the moving body may be counted.
　また、上記解析システムでは、前記データ解析装置は、前記解析用データに基づいて、前記複数の路線の各路線ごとに、前記画像データが表す画像に含まれる人物の属性を解析するものとすることができる。 Further, in the above-mentioned analysis system, the data analysis device analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes based on the analysis data. You can
　また、上記解析システムでは、前記移動体は、内部に、コンテンツを出力可能である出力装置が搭載され、前記データ解析装置は、前記複数の路線の各路線ごとの前記乗車人数に基づいて、前記複数の路線の各路線ごとに、前記出力装置が出力する前記コンテンツを受容可能な受容可能範囲を通過した通過者人数を表す指標を算出するものとすることができる。 Further, in the analysis system, the mobile body is internally provided with an output device capable of outputting content, and the data analysis device is based on the number of passengers on each line of the plurality of lines. An index representing the number of passers-by who have passed the acceptable range in which the content output by the output device can be received may be calculated for each of a plurality of routes.
　本発明に係る解析システムは、複数の移動体にそれぞれ搭載された複数のデータ収集装置によって、各移動体の内部の画像を表す画像データ、及び、位置データを含む解析用データを収集することができる。そして、データ解析装置は、複数のデータ収集装置によって収集された当該解析用データに基づいて、複数の路線の各路線ごとに、複数の移動体の乗車人数を計数することができる。この結果、この解析システムは、人物の流動の傾向を適正に解析することができる、という効果を奏する。 The analysis system according to the present invention is capable of collecting image data representing an image inside each moving body and analysis data including position data by a plurality of data collecting devices respectively mounted on the plurality of moving bodies. it can. Then, the data analysis device can count the number of passengers of the plurality of moving bodies for each of the plurality of routes based on the analysis data collected by the plurality of data collection devices. As a result, this analysis system has an effect of being able to appropriately analyze the tendency of the flow of a person.
図１は、実施形態１に係る解析システムの概略構成を表すブロック図である。FIG. 1 is a block diagram showing a schematic configuration of the analysis system according to the first embodiment. 図２は、実施形態１に係る解析システムの解析対象である１台の移動体の乗車人数の一例を表す図である。FIG. 2 is a diagram illustrating an example of the number of passengers in one moving body that is an analysis target of the analysis system according to the first embodiment. 図３は、実施形態１に係る解析システムの解析対象である１台の移動体が走行する路線の一例を表す模式図である。FIG. 3 is a schematic diagram illustrating an example of a route along which one mobile body, which is an analysis target of the analysis system according to the first embodiment, travels. 図４は、実施形態１に係る解析システムの解析対象である複数の移動体が走行する複数の路線の一例を表す模式図である。FIG. 4 is a schematic diagram illustrating an example of a plurality of routes on which a plurality of mobile bodies that are the analysis targets of the analysis system according to the first embodiment travel. 図５は、実施形態１に係る解析システムの解析対象である複数の移動体ごとの乗車人数の一例を表す図である。FIG. 5 is a diagram illustrating an example of the number of passengers for each of a plurality of moving bodies that are the analysis targets of the analysis system according to the first embodiment. 図６は、実施形態１に係る解析システムの解析対象である複数の路線ごとの乗車人数の一例を表す図である。FIG. 6 is a diagram illustrating an example of the number of passengers on each of a plurality of routes, which are the analysis targets of the analysis system according to the first embodiment. 図７は、実施形態１に係る解析システムの解析対象である複数の路線ごとの乗車人数の一例を表す図である。FIG. 7 is a diagram illustrating an example of the number of passengers on each of a plurality of routes, which are the analysis targets of the analysis system according to the first embodiment. 図８は、実施形態１に係る解析システムにおいて解析され加工された解析結果データの一例を表す模式図である。FIG. 8 is a schematic diagram showing an example of analysis result data analyzed and processed by the analysis system according to the first embodiment. 図９は、実施形態１に係る解析システムにおける処理の一例を表すフローチャート図である。FIG. 9 is a flowchart showing an example of processing in the analysis system according to the first embodiment.
　以下に、本発明に係る実施形態を図面に基づいて詳細に説明する。なお、この実施形態によりこの発明が限定されるものではない。また、下記実施形態における構成要素には、当業者が置換可能かつ容易なもの、あるいは実質的に同一のものが含まれる。 Embodiments according to the present invention will be described below in detail with reference to the drawings. The present invention is not limited to this embodiment. In addition, constituent elements in the following embodiments include elements that can be easily replaced by those skilled in the art, or substantially the same elements.
［実施形態１］
　図１に示す本実施形態の解析システム１は、複数のデータ収集装置としての記録装置１０と、データ解析装置としての解析装置２０とを備え、解析装置２０によって解析された解析結果データをクライアント端末ＣＬに提供するシステムである。本実施形態の解析システム１は、移動体Ｖに搭載された記録装置１０を活用し、当該記録装置１０によって収集される画像データ等に基づいて人物の流動の傾向を解析するものである。そして、本実施形態の解析システム１は、複数の路線を移動する複数の移動体Ｖにそれぞれ搭載された記録装置１０によって収集された解析用データを組み合わせることで、各路線ごとに適正に人物の流動の傾向を解析することができる構成を実現したものである。以下、各図を参照して解析システム１の構成について詳細に説明する。 [Embodiment 1]
The analysis system 1 of the present embodiment shown in FIG. 1 includes a recording device 10 as a plurality of data collection devices and an analysis device 20 as a data analysis device, and analyzes the analysis result data analyzed by the analysis device 20 as a client terminal. This is a system provided to CL. The analysis system 1 of the present embodiment utilizes the recording device 10 mounted on the moving body V and analyzes the tendency of the flow of a person based on image data collected by the recording device 10. Then, the analysis system 1 of the present embodiment combines the analysis data collected by the recording device 10 mounted on each of the plurality of moving bodies V moving on the plurality of routes, so that the number of persons can be properly calculated for each route. This is a configuration that can analyze the tendency of flow. Hereinafter, the configuration of the analysis system 1 will be described in detail with reference to the drawings.
　記録装置１０は、移動体Ｖに搭載され、解析装置２０による解析に用いる解析用データを収集するものである。記録装置１０によって収集される解析用データは、画像データ、及び、位置データを含むデータである。画像データは、移動体Ｖの内部の画像を表すデータである。位置データは、当該移動体Ｖの内部の画像が撮像された位置を表すデータである。記録装置１０は、解析用データとして、画像データ、及び、位置データを収集する。解析用データは、解析装置２０による人物の流動の傾向の解析に用いられる。 The recording device 10 is mounted on the mobile body V and collects analysis data used for analysis by the analysis device 20. The analysis data collected by the recording device 10 is data including image data and position data. The image data is data representing an image inside the moving body V. The position data is data representing the position where the image inside the moving body V is captured. The recording device 10 collects image data and position data as analysis data. The analysis data is used by the analysis device 20 to analyze the tendency of the flow of a person.
　ここで、記録装置１０が搭載される移動体Ｖは、典型的には、予め定められた複数の路線を移動可能に構成された物体である。移動体Ｖは、典型的には、自家用車、レンタカー、シェアリングカー、ライドシェアカー、バス、タクシー、トラック、輸送車、作業車等の路面を走行する車両である。また、移動体Ｖは、車両に限らず、例えば、フライングカーやドローン等、空中を飛行する飛行体であってもよい。本実施形態の移動体Ｖは、一例として、一日の間に予め定められた複数の路線を繰り返し走行する路線バスであるものとして説明する。路線バス等の移動体Ｖは、例えば、配車の効率化等のために、１台の移動体Ｖが一日の間に複数の路線を走行しつつ、複数の移動体Ｖが複数の路線に渡って使い分けられて運行する場合がある。本実施形態の記録装置１０は、このように複数の路線を移動する当該複数の移動体Ｖにそれぞれ搭載される。つまり、本実施形態の解析システム１は、複数の路線を移動する複数の移動体Ｖにそれぞれ搭載された複数の記録装置１０を備え、当該複数の記録装置１０から解析用データを収集することが可能である。 Here, the moving body V on which the recording device 10 is mounted is typically an object configured to be movable on a plurality of predetermined routes. The moving body V is typically a vehicle such as a private car, a rental car, a sharing car, a ride-sharing car, a bus, a taxi, a truck, a transport vehicle, or a work vehicle that travels on a road surface. The moving body V is not limited to a vehicle, and may be a flying body such as a flying car or a drone that flies in the air. The moving body V of the present embodiment will be described as an example of a route bus that repeatedly travels on a plurality of predetermined routes during a day. For example, a moving body V such as a route bus travels on a plurality of routes during one day while one moving body V travels on a plurality of routes in order to improve the efficiency of vehicle allocation. There are cases in which they are operated separately depending on their use. The recording device 10 of the present embodiment is mounted on each of the plurality of moving bodies V moving on the plurality of routes in this manner. That is, the analysis system 1 of the present embodiment includes a plurality of recording devices 10 respectively mounted on a plurality of moving bodies V moving on a plurality of routes, and can collect analysis data from the plurality of recording devices 10. It is possible.
　具体的には、記録装置１０は、内部カメラ１１と、位置情報測定器１２と、データ入出力部１３と、制御部１４とを備える。記録装置１０は、例えば、移動体Ｖに搭載されるいわゆるドライブレコーダ等の車載機器を用いることができるがこれに限らない。 Specifically, the recording device 10 includes an internal camera 11, a position information measuring device 12, a data input / output unit 13, and a control unit 14. As the recording device 10, for example, an in-vehicle device such as a so-called drive recorder mounted on the moving body V can be used, but the invention is not limited to this.
　内部カメラ１１は、移動体Ｖの内部、すなわち、車内の画像を撮像する内部撮像装置である。内部カメラ１１は、当該移動体Ｖの内部の画像を撮像し、当該移動体Ｖの内部の画像を表す画像データを収集する。内部カメラ１１は、典型的には、移動体Ｖの内部の動画像を撮像する。内部カメラ１１は、解析システム１による解析対象である人物、ここでは、移動体Ｖの車内の乗客等を撮像可能な画角となるように移動体Ｖに設置される。内部カメラ１１は、移動体Ｖの内部の人物をより好適に撮像可能なように、移動体Ｖの内部の天井部等に複数設けられてもよい。内部カメラ１１は、単眼カメラであってもよいし、ステレオカメラであってもよい。また、内部カメラ１１が撮像する画像は、モノクロであってもよいしカラーであってもよい。制御部１４は、この内部カメラ１１と通信可能に接続され、相互に各種信号、データを授受可能である。内部カメラ１１は、収集した画像データを制御部１４に出力する。 The internal camera 11 is an internal imaging device that captures an image of the inside of the moving body V, that is, the inside of the vehicle. The internal camera 11 captures an image inside the moving body V and collects image data representing the image inside the moving body V. The internal camera 11 typically captures a moving image inside the moving body V. The internal camera 11 is installed in the moving body V so as to have an angle of view capable of imaging a person who is an analysis target by the analysis system 1, here, a passenger in the vehicle of the moving body V and the like. A plurality of internal cameras 11 may be provided on a ceiling portion or the like inside the moving body V so that a person inside the moving body V can be imaged more preferably. The internal camera 11 may be a monocular camera or a stereo camera. The image captured by the internal camera 11 may be monochrome or color. The control unit 14 is communicably connected to the internal camera 11 and can exchange various signals and data with each other. The internal camera 11 outputs the collected image data to the control unit 14.
　位置情報測定器１２は、移動体Ｖの現在位置を測定する測位器である。位置情報測定器１２は、例えば、ＧＰＳ（Ｇｌｏｂａｌ　Ｐｏｓｉｔｉｏｎｉｎｇ　Ｓｙｓｔｅｍ）衛星から送信される電波を受信するＧＰＳ受信器等を用いることができる。位置情報測定器１２は、ＧＰＳ衛星から送信される電波を受信し移動体Ｖの現在位置を表す情報としてＧＰＳ情報（緯度経度座標）を取得することで、移動体Ｖの内部の画像が撮像された位置を表す位置データを収集する。位置情報測定器１２は、制御部１４と通信可能に接続されており、収集した位置データを制御部１４に出力する。 The position information measuring device 12 is a positioning device that measures the current position of the mobile body V. The position information measuring device 12 may be, for example, a GPS receiver that receives radio waves transmitted from a GPS (Global Positioning System) satellite. The position information measuring device 12 receives radio waves transmitted from GPS satellites and acquires GPS information (latitude / longitude coordinates) as information indicating the current position of the mobile body V, whereby an image inside the mobile body V is captured. Collect location data that represents the location. The position information measuring device 12 is communicably connected to the control unit 14 and outputs the collected position data to the control unit 14.
　データ入出力部１３は、記録装置１０とは異なる機器と当該記録装置１０との間で各種データを入出力するものである。本実施形態のデータ入出力部１３は、記録装置１０とは異なる機器である解析装置２０に対して、解析用データを出力可能である。データ入出力部１３は、例えば、ネットワークを介した通信（有線、無線を問わない）によって、記録装置１０とは異なる機器との間でデータを入出力する構成であってもよい。また、データ入出力部１３は、例えば、スロット部を有し当該スロット部に差し込まれた記録媒体を介して、記録装置１０とは異なる機器との間でデータを入出力する構成であってもよい。ここで、記録媒体は、例えば、スロット部を介して記録装置１０に脱着可能なメモリ（リムーバブルメディア）である。記録媒体は、例えば、様々な形式のメモリカード、例えばＳＤカードなどを用いることができるがこれに限らない。 The data input / output unit 13 inputs / outputs various data between a device different from the recording device 10 and the recording device 10. The data input / output unit 13 of the present embodiment can output analysis data to the analysis device 20, which is a device different from the recording device 10. The data input / output unit 13 may be configured to input / output data to / from a device different from the recording device 10 by communication (whether wired or wireless) via a network, for example. Further, the data input / output unit 13 may be configured to input / output data to / from a device different from the recording device 10 via a recording medium having a slot portion and inserted into the slot portion, for example. Good. Here, the recording medium is, for example, a memory (removable medium) that can be attached to and detached from the recording device 10 via the slot portion. The recording medium may be, for example, a memory card of various formats, for example, an SD card, but is not limited to this.
　制御部１４は、記録装置１０の各部を統括的に制御するものである。制御部１４は、解析用データを収集するための種々の演算処理を実行する。制御部１４は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＧＰＵ（Ｇｒａｐｈｉｃｓ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）等の中央演算処理装置、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）、及び、インターフェースを含む周知のマイクロコンピュータを主体とする電子回路を含んで構成される。制御部１４は、内部カメラ１１、位置情報測定器１２、データ入出力部１３等の各部と通信可能に接続され、各部との間で相互に各種信号、データを授受可能である。 The control unit 14 centrally controls each unit of the recording device 10. The control unit 14 executes various arithmetic processes for collecting analysis data. The control unit 14 mainly includes a central processing unit such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and a well-known microcomputer including an interface. It is configured to include an electronic circuit. The control unit 14 is communicably connected to the internal camera 11, the position information measuring device 12, the data input / output unit 13, and the like, and can exchange various signals and data with each other.
　より具体的には、制御部１４は、記憶部１４Ａ、及び、処理部１４Ｂを含んで構成される。記憶部１４Ａ、及び、処理部１４Ｂは、各部との間で相互に各種信号、データを授受可能である。記憶部１４Ａは、処理部１４Ｂでの各種処理に必要な条件や情報、制御部１４で実行する各種プログラムやアプリケーション、制御データ等が格納されている。記憶部１４Ａは、解析用データを、収集した時刻等と共に記憶することができる。言い換えれば、解析用データは、当該データを収集した時刻を表す時刻データやその他のデータも含む。記憶部１４Ａは、例えば、処理部１４Ｂによる処理の過程で生成される各種データを一時的に記憶することもできる。記憶部１４Ａは、処理部１４Ｂ、データ入出力部１３等によってこれらのデータが必要に応じて読み出される。記憶部１４Ａは、例えば、ハードディスク、ＳＳＤ（Ｓｏｌｉｄ　Ｓｔａｔｅ　Ｄｒｉｖｅ）、光ディスクなどの比較的に大容量の記憶装置、あるいは、ＲＡＭ、フラッシュメモリ、ＮＶＳＲＡＭ（Ｎｏｎ　Ｖｏｌａｔｉｌｅ　Ｓｔａｔｉｃ　Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）などのデータを書き換え可能な半導体メモリであってもよい。処理部１４Ｂは、各種入力信号等に基づいて、記憶部１４Ａに記憶されている各種プログラムを実行し、当該プログラムが動作することにより各部に出力信号を出力し各種機能を実現するための種々の処理を実行する。処理部１４Ｂは、内部カメラ１１、位置情報測定器１２の動作を制御し、画像データ、位置データを含む解析用データを収集する処理を実行する。また、処理部１４Ｂは、データ入出力部１３を介したデータの入出力に関わる処理を実行する。処理部１４Ｂは、例えば、解析用データを、データ入出力部１３を介して解析装置２０に出力する処理を実行する。 More specifically, the control unit 14 is configured to include a storage unit 14A and a processing unit 14B. The storage unit 14A and the processing unit 14B can exchange various signals and data with each other. The storage unit 14A stores conditions and information necessary for various processes in the processing unit 14B, various programs and applications executed by the control unit 14, control data, and the like. The storage unit 14A can store the analysis data together with the collected time and the like. In other words, the analysis data also includes time data indicating the time when the data was collected and other data. The storage unit 14A can also temporarily store various data generated in the process of processing by the processing unit 14B, for example. These data are read from the storage unit 14A by the processing unit 14B, the data input / output unit 13 and the like as needed. The storage unit 14A can rewrite a relatively large-capacity storage device such as a hard disk, SSD (Solid State Drive), or optical disk, or data such as RAM, flash memory, NVSRAM (Non Volatile Static Random Access Memory). Any semiconductor memory may be used. The processing unit 14B executes various programs stored in the storage unit 14A based on various input signals, etc., and outputs various output signals to each unit when the program operates to realize various functions. Execute the process. The processing unit 14B controls the operations of the internal camera 11 and the position information measuring device 12, and executes a process of collecting analysis data including image data and position data. Further, the processing unit 14B executes a process related to data input / output via the data input / output unit 13. The processing unit 14B executes, for example, a process of outputting the analysis data to the analysis device 20 via the data input / output unit 13.
　解析装置２０は、記録装置１０によって収集された解析用データを解析し、解析結果を表す解析結果データをクライアント端末ＣＬに提供するものである。解析装置２０、及び、クライアント端末ＣＬは、ネットワーク上に実装されるいわゆるクラウドサービス型の装置（クラウドサーバ）を構成してもよいし、ネットワークから切り離されたいわゆるスタンドアローン型の装置を構成してもよい。本実施形態の解析装置２０は、複数の記録装置１０によって収集された解析用データに基づいて、複数の路線の各路線ごとに、複数の移動体Ｖの乗車人数を計数する。さらに、本実施形態の解析装置２０は、複数の記録装置１０によって収集された解析用データに基づいて、複数の路線の各路線ごとに、画像データが表す画像に含まれる人物の属性を解析する。そして、本実施形態の解析装置２０は、各路線ごとの移動体Ｖの乗車人数の計数結果や移動体Ｖに乗車した人物の属性の解析結果等に基づく解析結果データを生成し、当該解析結果データをクライアント端末ＣＬに提供する。 The analysis device 20 analyzes the analysis data collected by the recording device 10 and provides the analysis result data representing the analysis result to the client terminal CL. The analysis device 20 and the client terminal CL may form a so-called cloud service type device (cloud server) mounted on the network, or a so-called stand-alone type device separated from the network. Good. The analysis device 20 of the present embodiment counts the number of passengers of the plurality of moving bodies V for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10. Furthermore, the analysis device 20 of the present embodiment analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10. .. Then, the analysis device 20 of the present embodiment generates analysis result data based on the counting result of the number of passengers of the moving body V for each route, the analysis result of the attribute of the person who got on the moving body V, and the like, and the analysis result. The data is provided to the client terminal CL.
　解析装置２０は、解析用データに基づいて、各路線ごとに、複数の移動体Ｖの乗車人数を計数するための種々の演算処理を実行する。また、解析装置２０は、解析用データに基づいて、移動体Ｖに乗車した人物の属性を解析するための種々の演算処理を実行する。解析装置２０は、ＣＰＵ、ＧＰＵ等の中央演算処理装置、ＲＯＭ、ＲＡＭ、及び、インターフェースを含む周知のマイクロコンピュータを主体とする電子回路を含んで構成される。解析装置２０は、既知のＰＣやワークステーションなどのコンピュータシステムに下記で説明する種々の処理を実現させるアプリケーションをインストールすることで構成することもできる。また、解析装置２０は、複数のＰＣを相互通信可能に組み合わせることで構成されてもよい。 The analysis device 20 executes various calculation processes for counting the number of passengers of a plurality of moving bodies V for each route based on the analysis data. Further, the analysis device 20 executes various arithmetic processes for analyzing the attributes of the person who has boarded the moving body V based on the analysis data. The analysis device 20 is configured to include a central processing unit such as a CPU and a GPU, a ROM, a RAM, and an electronic circuit mainly including a well-known microcomputer including an interface. The analysis device 20 can also be configured by installing an application that realizes various processes described below in a known computer system such as a PC or a workstation. Further, the analysis device 20 may be configured by combining a plurality of PCs so that they can communicate with each other.
　具体的には、解析装置２０は、データ入出力部２１と、記憶部２２と、処理部２３とを備える。データ入出力部２１、記憶部２２、及び、処理部２３は、各部との間で相互に各種信号、データを授受可能である。 Specifically, the analysis device 20 includes a data input / output unit 21, a storage unit 22, and a processing unit 23. The data input / output unit 21, the storage unit 22, and the processing unit 23 can exchange various signals and data with each other.
　データ入出力部２１は、解析装置２０とは異なる機器と当該解析装置２０との間で各種データを入出力するものである。本実施形態のデータ入出力部２１は、解析装置２０とは異なる機器である記録装置１０から解析用データを入力可能である。さらに、本実施形態のデータ入出力部２１は、解析装置２０とは異なる機器であるクライアント端末ＣＬに対して解析結果データを出力可能である。データ入出力部２１は、データ入出力部１３と同様に、例えば、ネットワークを介した通信（有線、無線を問わない）によって、解析装置２０とは異なる機器との間でデータを入出力する構成であってもよい。同様に、データ入出力部２１は、例えば、スロット部を有し当該スロット部に差し込まれた記録媒体を介して、解析装置２０とは異なる機器との間でデータを入出力する構成であってもよい。 The data input / output unit 21 inputs / outputs various data between a device different from the analysis device 20 and the analysis device 20. The data input / output unit 21 of the present embodiment can input analysis data from the recording device 10, which is a device different from the analysis device 20. Furthermore, the data input / output unit 21 of the present embodiment can output the analysis result data to the client terminal CL, which is a device different from the analysis device 20. Similar to the data input / output unit 13, the data input / output unit 21 inputs / outputs data to / from a device different from the analysis device 20, for example, by communication (whether wired or wireless) via a network. May be Similarly, the data input / output unit 21 is configured to input / output data to / from a device different from the analysis device 20 via, for example, a recording medium having a slot portion and inserted into the slot portion. Good.
　記憶部２２は、処理部２３での各種処理に必要な条件や情報、処理部２３で実行する各種プログラムやアプリケーション、制御データ等が格納されている。記憶部２２は、データ入出力部２１によって入力された解析用データを記憶することができる。記憶部２２は、例えば、処理部２３による処理の過程で生成される各種データを一時的に記憶することもできる。記憶部２２は、データ入出力部２１、処理部２３等によってこれらのデータが必要に応じて読み出される。記憶部２２は、例えば、ハードディスク、ＳＳＤ、光ディスクなどの比較的に大容量の記憶装置、あるいは、ＲＡＭ、フラッシュメモリ、ＮＶＳＲＡＭなどのデータを書き換え可能な半導体メモリであってもよい。 The storage unit 22 stores conditions and information necessary for various processes in the processing unit 23, various programs and applications executed by the processing unit 23, control data, and the like. The storage unit 22 can store the analysis data input by the data input / output unit 21. The storage unit 22 can also temporarily store various data generated in the process of the processing by the processing unit 23, for example. These data are read from the storage unit 22 by the data input / output unit 21, the processing unit 23, and the like as needed. The storage unit 22 may be, for example, a relatively large-capacity storage device such as a hard disk, SSD, or optical disk, or a rewritable semiconductor memory such as RAM, flash memory, or NVSRAM.
　より具体的には、記憶部２２は、機能概念的に、解析対象データベース（以下、「解析対象ＤＢ」と略記する。）２２Ａ、解析参照データベース（以下、「解析参照ＤＢ」と略記する。）２２Ｂ、及び、解析結果データベース（以下、「解析結果ＤＢ」と略記する。）２２Ｃを含んで構成される。 More specifically, the storage unit 22 is functionally conceptually an analysis target database (hereinafter abbreviated as “analysis target DB”) 22A, an analysis reference database (hereinafter abbreviated as “analysis reference DB”). 22B and an analysis result database (hereinafter abbreviated as “analysis result DB”) 22C.
　解析対象ＤＢ２２Ａは、処理部２３による解析対象データである解析用データ（画像データ、位置データ、時刻データ等）を蓄積しデータベース化して記憶する部分である。記録装置１０からデータ入出力部２１に入力された解析用データは、この解析対象ＤＢ２２Ａに記憶される。 The analysis target DB 22A is a part that accumulates analysis data (image data, position data, time data, etc.), which is analysis target data by the processing unit 23, and stores it as a database. The analysis data input from the recording device 10 to the data input / output unit 21 is stored in the analysis target DB 22A.
　解析参照ＤＢ２２Ｂは、処理部２３による解析用データの解析の際に参照する解析参照データを蓄積しデータベース化して記憶する部分である。解析参照データは、例えば、地図参照データ、属性予測参照データ等を含む。地図参照データは、位置データ等に基づいて移動体Ｖの位置、言い換えれば、移動体Ｖの内部の画像が撮像された位置を特定する際に参照する地図を表すデータである。属性予測参照データは、画像データが表す画像に含まれる人物の属性の推定の際等に参照するデータである。属性予測参照データについては、後で詳細に説明する。解析参照データは、処理部２３によって解析用データの解析の際に参照される。 The analysis reference DB 22B is a part that accumulates the analysis reference data to be referred to when the processing unit 23 analyzes the analysis data, and stores it as a database. The analysis reference data includes, for example, map reference data, attribute prediction reference data, and the like. The map reference data is data representing a map to be referred to when the position of the moving body V, in other words, the position where the image inside the moving body V is captured, is specified based on the position data or the like. The attribute prediction reference data is data that is referred to when estimating the attribute of a person included in the image represented by the image data. The attribute prediction reference data will be described in detail later. The analysis reference data is referred to by the processing unit 23 when the analysis data is analyzed.
　解析結果ＤＢ２２Ｃは、処理部２３による解析用データの解析結果を表す解析結果データを蓄積しデータベース化して記憶する部分である。解析結果データは、例えば、各路線ごとの移動体Ｖの乗車人数の計数結果（路線別乗車人数データ）や移動体Ｖに乗車した人物の属性の解析結果（人物属性データ）等に基づくデータである。解析結果データは、処理部２３によって所望の形式に加工されて、データ入出力部２１からクライアント端末ＣＬに出力、提供される。 The analysis result DB 22C is a part for accumulating analysis result data representing the analysis result of the analysis data by the processing unit 23, converting it into a database, and storing it. The analysis result data is, for example, data based on the counting result of the number of passengers of the moving body V for each route (passenger number data by route), the analysis result of the attribute of the person who got on the moving body V (person attribute data), and the like. is there. The analysis result data is processed into a desired format by the processing unit 23, and is output and provided from the data input / output unit 21 to the client terminal CL.
　なお、解析対象ＤＢ２２Ａ、解析参照ＤＢ２２Ｂ、解析結果ＤＢ２２Ｃに記憶される各種データは、いわゆるビッグデータ（ｂｉｇ　ｄａｔａ）として活用することができる。 Incidentally, various data stored in the analysis target DB 22A, the analysis reference DB 22B, and the analysis result DB 22C can be utilized as so-called big data (big data).
　処理部２３は、各種入力信号等に基づいて、記憶部２２に記憶されている各種プログラムを実行し、当該プログラムが動作することにより解析用データを解析するための種々の処理を実行する。また、処理部２３は、解析結果データを所望の形式に加工する処理を実行する。また、処理部２３は、データ入出力部２１を介したデータの入出力に関わる処理を実行する。処理部２３は、例えば、所望の形式に加工された解析結果データを、データ入出力部２１を介してクライアント端末ＣＬに出力する処理を実行する。 The processing unit 23 executes various programs stored in the storage unit 22 based on various input signals and the like, and executes various processes for analyzing the analysis data by operating the programs. In addition, the processing unit 23 executes processing for processing the analysis result data into a desired format. Further, the processing unit 23 executes a process related to data input / output via the data input / output unit 21. The processing unit 23 executes, for example, a process of outputting the analysis result data processed into a desired format to the client terminal CL via the data input / output unit 21.
　より具体的には、処理部２３は、機能概念的に、データ前処理部２３Ａ、データ解析処理部２３Ｂ、及び、データ加工処理部２３Ｃを含んで構成される。 More specifically, the processing unit 23 functionally and conceptually includes a data preprocessing unit 23A, a data analysis processing unit 23B, and a data processing unit 23C.
　データ前処理部２３Ａは、解析対象データである解析用データに対して種々の前処理を施す部分である。データ前処理部２３Ａは、前処理として、例えば、解析対象ＤＢ２２Ａから解析対象データとなる解析用データを読み出し、当該解析用データに含まれる画像データが表す動画像から静止画像を切り出す処理を実行する。また、データ前処理部２３Ａは、前処理として、例えば、切り出した当該静止画像と、解析対象データとなる解析用データに含まれる位置データが表す位置と、解析対象データとなる解析用データに含まれる時刻データが表す時刻とを紐付する処理を実行する。 The data preprocessing unit 23A is a unit that performs various preprocessing on the analysis data that is the analysis target data. As the preprocessing, the data preprocessing unit 23A executes, for example, processing for reading analysis data that is analysis target data from the analysis target DB 22A and cutting out a still image from the moving image represented by the image data included in the analysis data. .. In addition, the data preprocessing unit 23A includes, as preprocessing, for example, the still image cut out, the position represented by the position data included in the analysis data that is the analysis target data, and the analysis data that is the analysis target data. The process of associating with the time represented by the time data is executed.
　データ解析処理部２３Ｂは、データ前処理部２３Ａによって前処理が施された解析用データに基づいて、複数の路線の各路線ごとに、複数の移動体Ｖの乗車人数を計数する部分である。 The data analysis processing unit 23B is a unit that counts the number of passengers of a plurality of moving bodies V for each route of a plurality of routes based on the analysis data preprocessed by the data preprocessing unit 23A.
　典型的には、データ解析処理部２３Ｂは、データ前処理部２３Ａによって前処理が施された解析用データに含まれる画像データに基づいて、解析対象となる各移動体Ｖの乗車人数を計数する。ここでは、データ解析処理部２３Ｂは、当該画像データが表す画像に含まれる人物の数に基づいて、各移動体Ｖの乗車人数を計数する。データ解析処理部２３Ｂは、種々の公知の画像処理技術を用いて、画像データに基づいてデータ前処理部２３Ａによって切り出された静止画像から人物を検出し抽出する処理を実行する。そして、データ解析処理部２３Ｂは、検出、抽出した人物の数を計数し、当該計数した人物の数を移動体Ｖの内部の乗車人数として算出する。 Typically, the data analysis processing unit 23B counts the number of passengers of each mobile object V to be analyzed, based on the image data included in the analysis data preprocessed by the data preprocessing unit 23A. .. Here, the data analysis processing unit 23B counts the number of passengers of each moving body V based on the number of persons included in the image represented by the image data. The data analysis processing unit 23B executes a process of detecting and extracting a person from the still image cut out by the data preprocessing unit 23A based on the image data, using various known image processing techniques. Then, the data analysis processing unit 23B counts the number of detected and extracted persons, and calculates the counted number of persons as the number of passengers inside the moving body V.
　なお、データ前処理部２３Ａは、画像データが表す画像に含まれる人物の検出、抽出を、収集した全ての画像データに対して行ってもよいし、移動体Ｖを構成する路線バスの扉の開閉時を含む所定期間に収集された画像データに対してのみ行ってもよい。この場合、データ前処理部２３Ａは、当該画像データが表す画像自体に基づいて、当該所定期間に収集された画像データを特定してもよいし、記録装置１０によって画像データを収集する際、路線バスの扉の開閉がなされたことをトリガとして、種々の公知の手法により、当該所定期間に収集された画像データを予め特定しておいてもよい。 Note that the data preprocessing unit 23A may perform detection and extraction of a person included in the image represented by the image data on all the collected image data, or on the door of the route bus that constitutes the moving body V. It may be performed only for image data collected during a predetermined period including opening and closing. In this case, the data preprocessing unit 23A may specify the image data collected in the predetermined period based on the image itself represented by the image data, or when the recording device 10 collects the image data, The image data collected during the predetermined period may be specified in advance by various known methods using the opening and closing of the bus door as a trigger.
　データ解析処理部２３Ｂは、画像データが表す画像から人物を検出した場合、解析対象ＤＢ２２Ａから、当該人物が検出された画像データに紐付された位置データ、時刻データを読み出す。そして、データ解析処理部２３Ｂは、読み出した位置データ、時刻データと、解析参照ＤＢ２２Ｂに記憶されている地図参照データ（解析参照データ）とに基づいて、当該人物が検出された画像データが収集された際の当該移動体Ｖの位置、時刻を特定する。そして、データ解析処理部２３Ｂは、移動体Ｖの内部の画像が撮像された際の当該移動体Ｖの位置、時刻を特定しこれを時系列で並べ、時刻ごと、位置ごとの移動体Ｖの内部の乗車人数を特定する。 When the person is detected from the image represented by the image data, the data analysis processing unit 23B reads the position data and the time data associated with the image data in which the person is detected from the analysis target DB 22A. Then, the data analysis processing unit 23B collects the image data in which the person is detected, based on the read position data, time data, and map reference data (analysis reference data) stored in the analysis reference DB 22B. The position and time of the moving body V at the time of the occurrence are specified. Then, the data analysis processing unit 23B identifies the position and time of the moving body V when the image of the inside of the moving body V is captured, and arranges the positions in time series, and the moving body V of each time and position is determined. Identify the number of passengers inside.
　そして、データ解析処理部２３Ｂは、特定した当該移動体Ｖの位置、時刻に基づいて、予め定められた複数の路線のうち、乗車人数の計数対象となった当該移動体Ｖが走行した路線、及び、当該路線を走行した時刻を特定する。そして、データ解析処理部２３Ｂは、乗車人数の計数対象となった当該移動体Ｖ、当該移動体Ｖが走行した路線、当該路線を走行した時刻、及び、特定した路線／時刻における当該移動体Ｖの乗客人数を特定し、相互に紐付する。 Then, the data analysis processing unit 23B, based on the identified position and time of the moving body V, the line on which the moving body V, which is the target of counting the number of passengers, travels among a plurality of predetermined lines, Also, specify the time when the vehicle traveled on the route. The data analysis processing unit 23B then counts the number of passengers, the moving body V, the route on which the moving body V travels, the time when the moving body travels on the line, and the moving body V on the specified line / time. Specify the number of passengers in and link them to each other.
　データ解析処理部２３Ｂは、解析用データを解析した解析結果データとして、上述のようにして特定した種々の情報を含む移動体別乗車人数データを生成する。移動体別乗車人数データは、各移動体Ｖごとの個別の乗車人数に関するデータであり、乗車人数の計数対象となった当該移動体Ｖ、時刻ごと／位置ごとの当該移動体Ｖの乗車人数、当該移動体Ｖが走行した路線、当該路線を走行した時刻、及び、特定した路線／時刻における当該移動体Ｖの乗客人数等を表すデータである。そして、データ解析処理部２３Ｂは、生成した移動体別乗車人数データを含む解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させる。 The data analysis processing unit 23B generates, as the analysis result data obtained by analyzing the analysis data, the number-of-passengers-by-mobile-body data that includes the various information identified as described above. The number of passengers for each moving body V is data regarding the number of passengers for each moving body V, and the moving body V for which the number of passengers has been counted, the number of passengers for the moving body V for each time / position, It is data representing the route on which the mobile body V traveled, the time when the mobile body V traveled, and the number of passengers of the mobile body V on the specified route / time. Then, the data analysis processing unit 23B accumulates the analysis result data including the generated passenger number data for each moving body in the analysis result DB 22C and stores it as a database.
　図２は、一例として、データ解析処理部２３Ｂによって生成された移動体別乗車人数データに含まれる移動体Ｖ個別の乗車人数であって、図３に示す移動体（路線バス）Ｖが走行した路線Ｒ１における当該移動体Ｖの乗車人数を表している。図２は、予め任意に設定される単位時間当たりの当該移動体Ｖの乗車人数を表している。ここでは、図２は、単位時間を２４時間、すなわち、１日単位とし、１週間（７日分）分の乗車人数を示し、あわせて週間平均も示している。なお、乗車人数を表す際の単位時間は、１日単位に限らず、任意に設定されればよく、例えば、より短い時間に設定されてもよいし、より長い時間に設定されてもよい（以下の説明でも同様である。）。データ解析処理部２３Ｂは、任意に設定された当該単位時間当たりの乗車人数を計数することができる。 As an example, FIG. 2 shows the number of passengers of each moving body V included in the number of passengers for each moving body generated by the data analysis processing unit 23B, and the moving body (route bus) V shown in FIG. 3 traveled. The number of passengers of the moving body V on the route R1 is shown. FIG. 2 shows the number of passengers of the moving body V per unit time that is arbitrarily set in advance. Here, FIG. 2 shows the number of passengers for one week (for seven days) with the unit time being 24 hours, that is, one day, and also shows the weekly average. The unit time for indicating the number of passengers is not limited to one day, and may be set arbitrarily, for example, may be set to a shorter time or a longer time ( The same applies to the following description.). The data analysis processing unit 23B can count the number of passengers per unit time set arbitrarily.
　本実施形態のデータ解析処理部２３Ｂは、上記のような移動体Ｖの内部の乗車人数を計数する処理を、複数の路線を走行する全ての移動体Ｖごとに行う。そして、データ解析処理部２３Ｂは、複数の路線の各路線ごとに、複数の移動体Ｖの乗車人数を計数する。すなわち、データ解析処理部２３Ｂは、複数の路線のうち特定の路線を移動した全ての移動体Ｖの当該特定の路線での乗車人数を集約し、当該特定の路線における全ての移動体Ｖの合計の乗車人数（延べの乗車人数）を計数する。 The data analysis processing unit 23B of the present embodiment performs the above-described processing of counting the number of passengers inside the moving body V for all moving bodies V traveling on a plurality of routes. Then, the data analysis processing unit 23B counts the number of passengers of the plurality of moving bodies V for each of the plurality of routes. That is, the data analysis processing unit 23B aggregates the number of passengers on all of the moving bodies V that have traveled on a specific route among the plurality of routes, and totals all the moving bodies V on the specific route. The number of passengers (total number of passengers) is counted.
　より詳細には、本実施形態のデータ解析処理部２３Ｂは、解析用データに含まれる位置データに基づいて、複数の記録装置１０によって収集された解析用データから、複数の路線のうち特定の路線を移動した移動体Ｖの乗車人数を抽出する。この場合、データ解析処理部２３Ｂは、上述した移動体別乗車人数データから、特定の路線を移動した移動体Ｖの移動体別乗車人数データを抽出し、当該特定の路線を移動した移動体Ｖの乗車人数を抽出してもよい。また、データ解析処理部２３Ｂは、複数の記録装置１０によって収集された解析用データから、特定の路線を移動した移動体Ｖで収集された解析用データを抽出し、当該特定の路線を移動した移動体Ｖの乗車人数を抽出してもよい。そして、データ解析処理部２３Ｂは、抽出した特定の路線を移動した全ての移動体Ｖの乗車人数の当該特定の路線での乗車人数を集約し、当該特定の路線における全ての移動体Ｖの合計の乗車人数（延べの乗車人数）を計数する。 More specifically, the data analysis processing unit 23B of the present embodiment, based on the position data included in the analysis data, uses the analysis data collected by the plurality of recording devices 10 to determine a specific route among the plurality of routes. The number of passengers of the moving body V that has moved is extracted. In this case, the data analysis processing unit 23B extracts, from the above-mentioned data on the number of passengers on board for each moving body, the data on the number of passengers on board for each moving body V that has traveled on a specific route, and moves on the specific route. The number of passengers may be extracted. In addition, the data analysis processing unit 23B extracts the analysis data collected by the mobile body V that has moved the specific route from the analysis data collected by the plurality of recording devices 10, and moves the specific route. The number of passengers of the moving body V may be extracted. Then, the data analysis processing unit 23B aggregates the number of passengers on the specific route of the number of passengers of all the moving bodies V that have traveled on the extracted specific route, and totals all the movable bodies V on the specific route. The number of passengers (total number of passengers) is counted.
　以下、図４、図５、図６、図７を参照して、データ解析処理部２３Ｂによる特定の路線における複数の移動体Ｖの乗車人数の計数の具体例について説明する。以下で説明する例は、バスＡ、バスＢ、バスＣ、及び、バスＤの合計４台の移動体Ｖによって、図４に例示する路線Ｒ２１、路線Ｒ２２、及び、路線Ｒ２３の合計３路線を運行する場合を説明する。この例では、図５に示すように、バスＡ、バスＣ、及び、バスＤは、路線Ｒ２１、路線Ｒ２２、及び、路線Ｒ２３の合計３路線全てを走行し、バスＢは、３路線のうち路線Ｒ２１、及び、路線Ｒ２２の２路線のみを走行するものとして説明する。 Hereinafter, with reference to FIGS. 4, 5, 6, and 7, a specific example of counting the number of passengers of a plurality of moving bodies V on a specific route by the data analysis processing unit 23B will be described. In the example described below, a total of three routes of route R21, route R22, and route R23 illustrated in FIG. 4 are used by a total of four moving bodies V of bus A, bus B, bus C, and bus D. The case of operation will be described. In this example, as shown in FIG. 5, bus A, bus C, and bus D travel on all three routes of route R21, route R22, and route R23, and bus B out of the three routes. The description will be given assuming that the vehicle travels only on two routes, the route R21 and the route R22.
　この場合、データ解析処理部２３Ｂは、まず、データ前処理部２３Ａによって前処理が施された解析用データに含まれる位置データに基づいて、複数の記録装置１０によって収集された解析用データから、特定の路線を移動した全ての移動体Ｖの乗車人数を抽出する。この例では、データ解析処理部２３Ｂは、特定の路線として、路線Ｒ２１を移動した全ての移動体Ｖの個別の乗車人数、路線Ｒ２２を移動した全ての移動体Ｖの個別の乗車人数、路線Ｒ２３を移動した全ての移動体Ｖの個別の乗車人数をそれぞれ抽出する。図５に例示するように、ここでは、データ解析処理部２３Ｂは、路線Ｒ２１を移動した移動体Ｖの個別の乗車人数として、バスＡ、バスＢ、バスＣ、及び、バスＤの全ての移動体Ｖの個別の乗車人数を抽出する。同様に、データ解析処理部２３Ｂは、路線Ｒ２２を移動した移動体Ｖの個別の乗車人数として、バスＡ、バスＢ、バスＣ、及び、バスＤの全ての移動体Ｖの個別の乗車人数を抽出する。そして、データ解析処理部２３Ｂは、路線Ｒ２３を移動した移動体Ｖの個別の乗車人数として、バスＢを除く、バスＡ、バスＣ、及び、バスＤの３台の移動体Ｖの個別の乗車人数を抽出する。 In this case, the data analysis processing unit 23B firstly analyzes, from the analysis data collected by the plurality of recording devices 10, based on the position data included in the analysis data preprocessed by the data preprocessing unit 23A, The numbers of passengers of all the moving bodies V that have moved on a specific route are extracted. In this example, the data analysis processing unit 23B, as a specific route, the number of individual passengers of all the mobile bodies V that have traveled on the route R21, the number of individual passengers of all the mobile bodies V that have traveled on the route R22, and the route R23. The individual numbers of passengers of all the moving bodies V that have moved are extracted. As illustrated in FIG. 5, here, the data analysis processing unit 23B determines that all the movements of the bus A, the bus B, the bus C, and the bus D are the number of passengers of the moving body V that has moved along the route R21. The number of individual passengers of the body V is extracted. Similarly, the data analysis processing unit 23B sets the individual passenger numbers of all the moving bodies V on the buses A, B, C, and D as the individual passenger numbers of the moving bodies V traveling on the route R22. Extract. Then, the data analysis processing unit 23B, as the number of individual passengers of the moving body V traveling on the route R23, excludes the bus B, and the individual riding of the three moving bodies V of the bus A, the bus C, and the bus D. Extract the number of people.
　図５は、抽出した各路線Ｒ２１、Ｒ２２、Ｒ２３における移動体Ｖの個別の乗車人数の一例を、移動体Ｖごと、単位時間ごとに表したものである。ここでは、図５は、単位時間を３時間とし、１日の乗車人数を示し、運行開始時刻の６：００から運行終了時刻の１８：００までの１営業日分の３時間ごとの各移動体Ｖごとの乗車人数を示している。なお、図５は、あわせて路線Ｒ２１、Ｒ２２、Ｒ２３を特定しない各移動体Ｖの合計の乗車人数、及び、路線Ｒ２１、Ｒ２２、Ｒ２３を特定しない各時間帯の合計の乗車人数も示している。 FIG. 5 shows an example of the number of individual passengers of the moving body V on each of the extracted routes R21, R22, and R23 for each moving body V and for each unit time. Here, in FIG. 5, the unit time is 3 hours, and the number of passengers on a day is shown. Each movement is every 3 hours for one business day from the operation start time of 6:00 to the operation end time of 18:00. The number of passengers for each body V is shown. Note that FIG. 5 also shows the total number of passengers of each moving body V that does not specify the routes R21, R22, and R23, and the total number of passengers of each time zone that does not specify the routes R21, R22, and R23. ..
　そして、データ解析処理部２３Ｂは、抽出した特定の路線Ｒ２１、Ｒ２２、Ｒ２３を移動した全ての移動体Ｖの乗車人数の当該各路線Ｒ２１、Ｒ２２、Ｒ２３での乗車人数をそれぞれ集約、合算する。これにより、データ解析処理部２３Ｂは、各路線Ｒ２１、Ｒ２２、Ｒ２３における全ての移動体Ｖの合計の乗車人数（延べの乗車人数）をそれぞれ計数する。図６は、図５で示す例において、単位時間を１営業日（１日）とした場合の各路線Ｒ２１、Ｒ２２、Ｒ２３における全ての移動体Ｖの合計の乗車人数を示している。この場合、データ解析処理部２３Ｂは、路線Ｒ２１の１営業日分の乗車人数として、バスＡの「６：００－９：００」の乗車人数、バスＢの「９：００－１２：００」の乗車人数、バスＣの「１５：００－１８：００」の乗車人数、及び、バスＤの「１２：００－１５：００」の乗車人数を集約、合算することで、当該路線Ｒ２１における１営業日分の延べの乗車人数を計数することができる（図６の「３３０」参照）。同様に、データ解析処理部２３Ｂは、路線Ｒ２２の１営業日分の乗車人数として、バスＡの「９：００－１２：００」、「１２：００－１５：００」の乗車人数、バスＢの「６：００－９：００」、「１２：００－１５：００」、「１５：００－１８：００」の乗車人数、バスＣの「６：００－９：００」、「９：００－１２：００」の乗車人数、及び、バスＤの「１５：００－１８：００」の乗車人数を集約、合算することで、当該路線Ｒ２２における１営業日分の延べの乗車人数を計数することができる（図６の「９００」参照）。さらに、データ解析処理部２３Ｂは、路線Ｒ２３の１営業日分の乗車人数として、バスＡの「１５：００－１８：００」の乗車人数、バスＣの「１２：００－１５：００」の乗車人数、及び、バスＤの「６：００－９：００」、「９：００－１２：００」の乗車人数を集約、合算することで、当該路線Ｒ２３における１営業日分の延べの乗車人数を計数することができる（図６の「２２５」参照）。なお、図６は、複数の路線Ｒ２１、Ｒ２２、Ｒ２３における１営業日分の延べの乗車人数を合算した合計の乗車人数も示している。 Then, the data analysis processing unit 23B aggregates and totals the number of passengers on each of the routes R21, R22, R23 of the number of passengers of all the moving bodies V that have moved on the extracted specific routes R21, R22, R23. Thereby, the data analysis processing unit 23B counts the total number of passengers (total number of passengers) of all the moving bodies V on each of the routes R21, R22, and R23. FIG. 6 shows the total number of passengers of all the mobile bodies V on each of the routes R21, R22, and R23 when the unit time is one business day (one day) in the example shown in FIG. In this case, the data analysis processing unit 23B determines that the number of passengers on the route R21 for one business day is "6: 00-9: 00" on the bus A and "9: 00-12: 00" on the bus B. The number of passengers on the bus R, the number of passengers on the bus C from “15:00 to 18:00”, and the number of passengers on the bus D from “12:00 to 15:00” are aggregated and added to obtain 1 on the route R21. The total number of passengers for business days can be counted (see “330” in FIG. 6). Similarly, the data analysis processing unit 23B determines, as the number of passengers on the route R22 for one business day, the number of passengers on the bus A at "9: 00-12: 00" and "12: 00-15: 00", and the bus B at the same time. "6: 00-9: 00", "12: 00-15: 00", "15: 00-18: 00" passengers, Bus C "6: 00-9: 00", "9:" The total number of passengers for one business day on the relevant route R22 is calculated by aggregating and adding up the number of passengers on "00-12: 00" and the number of passengers on "15: 00-18: 00" on bus D (See “900” in FIG. 6). Further, the data analysis processing unit 23B determines that the number of passengers on the route R23 for one business day is "15: 00-18: 00" for the bus A and "12: 00-15: 00" for the bus C. The total number of passengers on the bus R and the total number of passengers on the bus D at "6: 00-9: 00" and "9: 00-12: 00" are aggregated to add up for one business day on the route R23. The number of people can be counted (see “225” in FIG. 6). In addition, FIG. 6 also shows the total number of passengers on the plurality of routes R21, R22, and R23, which is the total number of passengers for one business day.
　また、データ解析処理部２３Ｂは、さらに、図７に示すように、１営業日分の各路線Ｒ２１、Ｒ２２、Ｒ２３の乗車人数を複数組み合わせて、各路線Ｒ２１、Ｒ２２、Ｒ２３ごとの乗車人数を計数するようにすることもできる。図７は、図２と同様に、単位時間を２４時間、すなわち、１日単位とし、１週間（７日分）分の各路線Ｒ２１、Ｒ２２、Ｒ２３における全ての移動体Ｖの乗車人数を示している。なお、図７は、あわせて各路線Ｒ２１、Ｒ２２、Ｒ２３における全ての移動体Ｖの乗車人数の週間平均、及び、路線Ｒ２１、Ｒ２２、Ｒ２３を特定しない各曜日の合計の乗車人数も示している。 Further, as shown in FIG. 7, the data analysis processing unit 23B further combines a plurality of passengers on each of the routes R21, R22, R23 for one business day to determine the number of passengers on each of the routes R21, R22, R23. It is also possible to count. Similar to FIG. 2, FIG. 7 shows the number of passengers of all the mobile bodies V on each of the routes R21, R22, and R23 for one week (seven days worth), where the unit time is 24 hours, that is, one day. ing. Note that FIG. 7 also shows the weekly average number of passengers of all the mobile bodies V on each route R21, R22, R23, and the total number of passengers on each day of the week not specifying the routes R21, R22, R23. ..
　データ解析処理部２３Ｂは、解析用データを解析した解析結果データとして、上述のようにして特定した種々の情報を含む路線別乗車人数データを生成する。路線別乗車人数データは、各路線ごとの乗車人数に関するデータであり、乗車人数の計数対象となった路線、当該路線ごとの全ての移動体Ｖの延べの乗車人数等を表すデータである。そして、データ解析処理部２３Ｂは、生成した路線別乗車人数データを含む解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させる。 The data analysis processing unit 23B generates, as the analysis result data obtained by analyzing the analysis data, the number-of-passengers-by-route data by route including the various information identified as described above. The number of passengers by line is data on the number of passengers for each line, and is data indicating the line for which the number of passengers has been counted, the total number of passengers of all the mobile bodies V for each line, and the like. Then, the data analysis processing unit 23B accumulates the analysis result data including the generated passenger number data for each route in the analysis result DB 22C and stores it as a database.
　また、本実施形態のデータ解析処理部２３Ｂは、データ前処理部２３Ａによって前処理が施された解析用データに基づいて、画像データが表す画像に含まれる人物の属性を解析する部分でもある。 The data analysis processing unit 23B of the present embodiment is also a unit that analyzes the attribute of a person included in the image represented by the image data, based on the analysis data preprocessed by the data preprocessing unit 23A.
　データ解析処理部２３Ｂは、画像データに基づいてデータ前処理部２３Ａによって切り出された静止画像から検出、抽出された人物の属性を解析する。データ解析処理部２３Ｂは、典型的には、上記の複数の路線の各路線ごとに、画像データが表す画像に含まれる人物の属性を解析する。この場合、データ解析処理部２３Ｂは、例えば、複数の記録装置１０によって収集された解析用データから、位置データ等に基づいて特定の路線を移動した移動体Ｖで収集された解析用データを抽出する。そして、データ解析処理部２３Ｂは、抽出した解析用データに基づいて、画像データが表す画像に含まれる人物の属性を解析することで、複数の路線の各路線ごとに、各移動体Ｖに乗車した人物の属性を解析する。図４、図５、図６、図７で説明した例で言えば、データ解析処理部２３Ｂは、路線Ｒ２１、路線Ｒ２２、路線Ｒ２３ごとに、各路線を移動した移動体Ｖで収集された解析用データに基づいて、画像データが表す画像に含まれる人物の属性を解析する。ここでは、データ解析処理部２３Ｂは、例えば、種々の公知の人工知能（Ａｒｔｉｆｉｃｉａｌ　Ｉｎｔｅｌｌｉｇｅｎｃｅ）技術や深層学習（Ｄｅｅｐ　Ｌｅａｒｎｉｎｇ）技術を用いて画像データが表す画像に含まれる人物の属性、及び、当該属性が特定された人物の人流を解析する処理を実行可能に構成される。 The data analysis processing unit 23B analyzes the attributes of the person detected and extracted from the still image cut out by the data preprocessing unit 23A based on the image data. The data analysis processing unit 23B typically analyzes the attribute of the person included in the image represented by the image data for each of the plurality of routes. In this case, the data analysis processing unit 23B extracts, for example, from the analysis data collected by the plurality of recording devices 10, the analysis data collected by the mobile body V that has moved on a specific route based on the position data and the like. To do. Then, the data analysis processing unit 23B analyzes the attributes of the person included in the image represented by the image data, based on the extracted analysis data, to get on each moving body V for each route of the plurality of routes. Analyzes the attribute of the person who did. In the examples described with reference to FIGS. 4, 5, 6, and 7, the data analysis processing unit 23B analyzes the routes R21, R22, and R23 collected by the mobile body V that has moved along each route. The attribute of the person included in the image represented by the image data is analyzed based on the use data. Here, the data analysis processing unit 23B uses, for example, various known artificial intelligence (technical intelligence) techniques and deep learning (deep learning) techniques to identify the attribute of the person included in the image represented by the image data and the attribute. Is configured to be able to execute the process of analyzing the human flow of the identified person.
　具体的には、データ解析処理部２３Ｂは、上述のように、データ前処理部２３Ａによって切り出された静止画像から人物を検出し抽出する処理を実行する。そして、本実施形態のデータ解析処理部２３Ｂは、画像データが表す画像から当該検出、抽出された人物の特徴点を含む画像を抽出する処理を実行する。ここで、当該人物の特徴点とは、画像に含まれる人物において当該人物の属性を特定可能な部位である。当該人物の特徴点とは、例えば、当該人物の表情が現われる顔、しぐさ・ジェスチャが現れる手足、アクセサリ等が装着されやすい傾向にある位置等の部位である。データ解析処理部２３Ｂは、例えば、異なる角度から撮像された多数の画像から、人物の属性特定に用いることができる当該人物の特徴点が写った画像を抽出する。 Specifically, the data analysis processing unit 23B executes the process of detecting and extracting a person from the still image cut out by the data preprocessing unit 23A as described above. Then, the data analysis processing unit 23B of the present embodiment executes a process of extracting an image including the feature points of the detected and extracted person from the image represented by the image data. Here, the feature point of the person is a portion of the person included in the image that can specify the attribute of the person. The characteristic point of the person is, for example, a face in which the person's facial expression appears, a limb in which a gesture / gesture appears, a position at which an accessory or the like tends to be worn, and the like. The data analysis processing unit 23B extracts, for example, from a large number of images captured from different angles, an image showing a characteristic point of the person that can be used for identifying the attribute of the person.
　そして、データ解析処理部２３Ｂは、画像データから抽出した人物の特徴点を含む画像に基づいて、当該画像に含まれる人物の属性を解析する処理を実行する。データ解析処理部２３Ｂは、例えば、解析参照ＤＢ２２Ｂに記憶されている属性予測参照データ（解析参照データ）と、画像データから抽出された画像に含まれる人物の特徴点とに基づいて、当該人物の属性を解析する。ここで、属性予測参照データは、人工知能技術や深層学習技術を用いた様々な手法によって、画像に含まれる人物の特徴点等に応じて推定可能な当該人物の属性を学習した結果が反映される情報である。言い換えれば、属性予測参照データは、画像に含まれる人物の特徴点等に基づいて人物の属性を推定するために、人工知能技術や深層学習技術を用いた様々な手法を用いてデータベース化されたデータである。この属性予測参照データは、逐次更新可能である。属性予測参照データは、例えば、データ解析処理部２３Ｂによる解析結果を表す解析結果データ（人物属性データ）自体を学習のためのデータとすることもできる。 Then, the data analysis processing unit 23B executes a process of analyzing the attribute of the person included in the image based on the image including the feature points of the person extracted from the image data. The data analysis processing unit 23B, for example, based on the attribute prediction reference data (analysis reference data) stored in the analysis reference DB 22B and the feature points of the person included in the image extracted from the image data, Parse attributes. Here, the attribute prediction reference data reflects the results of learning the attributes of the person that can be estimated according to the feature points of the person included in the image by various methods using artificial intelligence technology and deep learning technology. Information. In other words, the attribute prediction reference data was made into a database using various methods using artificial intelligence technology and deep learning technology in order to estimate the attribute of the person based on the feature points of the person included in the image. The data. This attribute prediction reference data can be updated sequentially. As the attribute prediction reference data, for example, the analysis result data (person attribute data) representing the analysis result by the data analysis processing unit 23B itself can be used as the data for learning.
　データ解析処理部２３Ｂによって解析される人物の属性としては、典型的には、当該人物の外観の特徴点から解析可能な事項、例えば、当該人物の性別、年齢、体格、社会的地位、嗜好、又は、行動志向等を含む。ここで、性別とは、男性、女性の別を表す属性である。年齢とは、生まれてから現在（その時）までの年月の長さを表す属性である。体格とは、身長、体重、各種寸法等を表す属性である。社会的地位とは、職業（自営業、ビジネスマン、警官、学生、無職、アルバイト）、年収、身分、同行者等を表す属性である。嗜好とは、服装・所持品・ファッションの傾向（カジュアル志向、エレガント志向、ブランド志向、高級志向、ファストファッション志向）、趣味（スポーツ／サブカルチャー／アウトドア／美容等）等を表す属性である。行動志向とは、その時点での気分、興味関心（やりたいこと、行きたいところ）等を表す属性である。つまりここでは、データ解析処理部２３Ｂは、人物の属性として、性別、年齢、体格、社会的地位、嗜好、行動志向等を推定する。 As the attribute of the person analyzed by the data analysis processing unit 23B, typically, items that can be analyzed from the characteristic points of the appearance of the person, for example, sex, age, physique, social status, preference of the person, Or, it includes behavioral orientation. Here, the sex is an attribute indicating the sex of male and female. Age is an attribute that represents the length of years from birth to the present (at that time). The physique is an attribute that represents height, weight, various dimensions, and the like. Social status is an attribute that represents occupation (self-employed, businessman, policeman, student, unemployed, part-time job), annual income, status, accompanying person, and the like. The preference is an attribute that represents the tendency of clothes, personal belongings, and fashion (casual orientation, elegant orientation, brand orientation, luxury orientation, fast fashion orientation), hobbies (sports / subculture / outdoor / beauty, etc.), and the like. The action-oriented attribute is an attribute that represents the mood, interest and interest (what you want to do, where you want to go), etc. at that time. That is, here, the data analysis processing unit 23B estimates gender, age, physique, social status, preference, action orientation, etc. as the attributes of the person.
　データ解析処理部２３Ｂは、属性予測参照データを参照して、画像に含まれる人物の特徴点に対応する属性（性別、年齢、体格、社会的地位、嗜好、又は、行動志向）を抽出し、抽出した属性を当該画像に映り込んだ人物の属性であるものと推定する。データ解析処理部２３Ｂは、例えば、画像に含まれる人物の特徴点である顔の表情、手足のしぐさ・ジェスチャ、装着されているアクセサリや洋服等に応じて、属性予測参照データを参照し、当該特徴点にあう属性をマッチングし、当該人物の性別、年齢、体格、社会的地位、嗜好、行動志向等の属性を推定する。 The data analysis processing unit 23B refers to the attribute prediction reference data and extracts an attribute (gender, age, physique, social status, preference, or action-oriented) corresponding to the feature point of the person included in the image, It is estimated that the extracted attributes are the attributes of the person reflected in the image. The data analysis processing unit 23B refers to the attribute prediction reference data according to, for example, a facial expression that is a feature point of a person included in an image, gestures / gestures of limbs, attached accessories or clothes, and the like. Attributes such as sex, age, physique, social status, preference, and behavior orientation of the person are estimated by matching the attributes that match the feature points.
　そしてさらに、データ解析処理部２３Ｂは、人物の属性が特定された画像データに紐付された位置データに基づいて、上記のようにして属性が特定された人物の位置等を解析する処理を実行する。データ解析処理部２３Ｂは、例えば、解析対象ＤＢ２２Ａから、人物の属性が特定された画像データに紐付された位置データを読み出す。そして、データ解析処理部２３Ｂは、解析参照ＤＢ２２Ｂに記憶されている地図参照データ（解析参照データ）と、読み出した位置データとに基づいて、当該属性が特定された人物の位置等を解析する。例えば、データ解析処理部２３Ｂは、地図参照データを参照して、当該位置データに基づいて当該画像が撮像された位置を特定する。そして、データ解析処理部２３Ｂは、当該位置データが表す位置に基づいて、属性が特定された人物の位置を特定する。 Further, the data analysis processing unit 23B executes processing for analyzing the position of the person whose attribute is specified as described above, based on the position data associated with the image data in which the attribute of the person is specified. .. The data analysis processing unit 23B reads, for example, the position data associated with the image data in which the attribute of the person is specified from the analysis target DB 22A. Then, the data analysis processing unit 23B analyzes the position and the like of the person whose attribute is specified, based on the map reference data (analysis reference data) stored in the analysis reference DB 22B and the read position data. For example, the data analysis processing unit 23B refers to the map reference data and specifies the position where the image is captured based on the position data. Then, the data analysis processing unit 23B specifies the position of the person whose attribute is specified, based on the position represented by the position data.
　データ解析処理部２３Ｂは、解析用データを解析した解析結果データとして、上記のように解析した人物の属性を表す人物属性データ、及び、属性が特定された人物の位置を表す属性別位置データを生成する。そして、データ解析処理部２３Ｂは、生成した人物属性データ、及び、属性別位置データを含む解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させる。 The data analysis processing unit 23B includes, as analysis result data obtained by analyzing the analysis data, person attribute data representing the attributes of the person analyzed as described above, and attribute-based position data representing the position of the person whose attribute is specified. To generate. Then, the data analysis processing unit 23B accumulates the generated person attribute data and the analysis result data including the attribute-based position data in the analysis result DB 22C and stores it as a database.
　なお、本実施形態の記録装置１０が搭載された移動体Ｖは、内部に出力装置ＯＤを搭載している。出力装置ＯＤは、コンテンツを出力可能な装置であり、複数の移動体Ｖの内部にそれぞれ設けられる。出力装置ＯＤは、ネットワーク上に実装され、様々なコンテンツがネットワークを介して提供されるいわゆるクラウドサービス型の装置を構成してもよいし、ネットワークから切り離されたいわゆるスタンドアローン型の装置を構成してもよい。出力装置ＯＤは、コンテンツに応じた画像を表示可能であるディスプレイ、コンテンツに応じた音・音声を出力可能であるスピーカ等を含んで構成される。出力装置ＯＤが出力するコンテンツとしては、例えば、広告やクーポン等のコンテンツの他、地域情報や所定の施設への道順情報、災害時の避難経路／安全サポート情報等、様々な案内情報を構成するコンテンツを含んでいてもよい。出力装置ＯＤが出力するコンテンツのデータは、ネットワークや記録媒体等を介して逐次更新可能である。 Note that the moving body V in which the recording device 10 of the present embodiment is mounted has the output device OD installed therein. The output device OD is a device capable of outputting content, and is provided inside each of the plurality of moving bodies V. The output device OD may be a so-called cloud service type device that is mounted on the network and provides various contents via the network, or a so-called stand-alone type device separated from the network. May be. The output device OD is configured to include a display capable of displaying an image corresponding to the content, a speaker capable of outputting sound / voice corresponding to the content, and the like. As the contents output by the output device OD, for example, in addition to contents such as advertisements and coupons, various guide information such as regional information, route information to a predetermined facility, evacuation route / safety support information at the time of disaster, etc. is configured. It may include content. The content data output by the output device OD can be sequentially updated via a network, a recording medium, or the like.
　そして、本実施形態のデータ解析処理部２３Ｂは、さらに、解析結果データとして、移動体別乗車人数データ、路線別乗車人数データ等に基づく商用利用データを生成する処理も実行可能に構成されてもよい。具体的には、本実施形態のデータ解析処理部２３は、各移動体Ｖの内部に設けられた出力装置ＯＤからのコンテンツの受容可能範囲を通過した通過者人数を表す指標を算出する。ここで、出力装置ＯＤのコンテンツの受容可能範囲とは、出力装置ＯＤが出力するコンテンツを人物が受容できる空間範囲であり、出力装置ＯＤが表示する画像を人物が視認できる可視範囲、出力装置ＯＤが出力する音・音声を人物が聴き取りできる可聴範囲等に応じて定まる。 Further, the data analysis processing unit 23B of the present embodiment may also be configured to be capable of executing, as the analysis result data, a process of generating commercial use data based on the number of passengers for each moving body, the number of passengers for each route, and the like. Good. Specifically, the data analysis processing unit 23 of the present embodiment calculates an index representing the number of passers-by who have passed the content acceptable range from the output device OD provided inside each moving body V. Here, the content acceptable range of the output device OD is a spatial range in which a person can receive the content output by the output device OD, and a visible range in which a person can visually recognize an image displayed by the output device OD, the output device OD. It is determined according to the audible range in which the person can hear the sound / voice output by.
　データ解析処理部２３は、例えば、各路線ごとの乗車人数を表す路線別乗車人数データに基づいて、各路線ごとに、上記受容可能範囲を通過した通過者人数を表す指標を算出する。あわせて、データ解析処理部２３は、各移動体Ｖごとの乗車人数を表す移動体別乗車人数データに基づいて、各移動体Ｖごとに、上記受容可能範囲を通過した通過者人数を表す指標を算出するようにしてもよい。そして、データ解析処理部２３は、当該指標を表す商用利用データを生成し、生成した商用利用データを含む解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させる。 The data analysis processing unit 23 calculates, for example, an index representing the number of passers-by who have passed the acceptable range for each route based on the number-of-passengers data for each route showing the number of passengers for each route. In addition, the data analysis processing unit 23, based on the number of passengers for each moving body V, which indicates the number of passengers for each moving body V, is an index indicating the number of passers who have passed the acceptable range for each moving body V. May be calculated. Then, the data analysis processing unit 23 generates the commercial use data representing the index, accumulates the analysis result data including the generated commercial use data in the analysis result DB 22C, and stores it as a database.
　ここで、上述の出力装置ＯＤのコンテンツの受容可能範囲を通過した通過者人数は、当該出力装置ＯＤのコンテンツを受容した人数であるものとみなすることができる。そして、当該受容可能範囲は、出力装置ＯＤが移動体Ｖの内部に設置された場合においては、典型的には、移動体Ｖの内部全体とみなすることができる。このため、移動体Ｖの内部の出力装置ＯＤのコンテンツの受容可能範囲を通過した通過者人数は、当該移動体Ｖの乗車人数と略同数であるものとみなすることができる。 Here, the number of passers who have passed the content acceptable range of the output device OD can be regarded as the number of persons who have received the content of the output device OD. Then, when the output device OD is installed inside the moving body V, the acceptable range can be typically regarded as the entire inside of the moving body V. Therefore, the number of passers who have passed the content acceptable range of the output device OD inside the moving body V can be considered to be substantially the same as the number of passengers of the moving body V.
　上記を踏まえて、本実施形態のデータ解析処理部２３Ｂは、移動体Ｖの乗車人数を、コンテンツの受容可能範囲の通過者人数とする。すなわちここでは、データ解析処理部２３Ｂは、移動体別乗車人数データが表す各移動体Ｖごとの乗客人数を、各移動体Ｖごとのコンテンツの受容可能範囲の通過者人数とする。同様に、データ解析処理部２３Ｂは、路線別乗車人数データが表す各路線ごとの乗客人数を、各路線ごとのコンテンツの受容可能範囲の通過者人数とする。 Based on the above, the data analysis processing unit 23B of the present embodiment sets the number of passengers of the moving body V as the number of passers in the content acceptable range. That is, here, the data analysis processing unit 23B sets the number of passengers for each mobile body V represented by the number of passengers for each mobile body as the number of passers in the content acceptable range for each mobile body V. Similarly, the data analysis processing unit 23B sets the number of passengers for each route represented by the number of passengers for each route as the number of passers in the content acceptable range for each route.
　そして、データ解析処理部２３Ｂは、コンテンツの受容可能範囲を通過した通過者人数そのものを当該通過者人数を表す指標としてもよいし、当該通過者人数に基づいて当該通過者人数を表す指標を算出してもよい。データ解析処理部２３Ｂが算出する通過者人数を表す指標としては、例えば、「ＤＥＣ：Ｄａｉｌｙ　Ｅｆｆｅｃｔｉｖｅ　Ｃｉｒｃｕｌａｔｉｏｎ」や「ＧＲＰ：Ｇｒｏｓｓ　Ｒａｔｉｎｇ　Ｐｏｉｎｔ」等が挙げられる。「ＤＥＣ」、「ＧＲＰ」は、共に広告の効果を表す指標である。「ＤＥＣ」は、典型的には、対象の広告の受容可能範囲（可視範囲）を通過する１日の通過者人数である。「ＤＥＣ」は、例えば、満１８歳以上等、所定の年齢制限を満たす人を対象とした通過者人数としてもよいし、年齢制限を設けず全ての人を対象とした通過者人数としてもよい。「ＧＲＰ」は、典型的には、対象の広告に対して１日に到達可能なエリア内の対象人口における上記受容可能範囲を通過する１日の通過者人数の割合である。「ＧＲＰ」は、［ＤＥＣ／対象エリア内の対象人口］で表すことができる。「対象エリア内の対象人口」は、「ＤＥＣ」の対象に年齢制限を設けた場合には対象エリア内の当該年齢制限を満たす人口となる。 Then, the data analysis processing unit 23B may use the number of passers who have passed the acceptable range of the content itself as an index indicating the number of passers, or calculate the index indicating the number of passers based on the number of passers. You may. Examples of the index representing the number of passers calculated by the data analysis processing unit 23B include “DEC: Daily Effective Circulation” and “GRP: Gross Rating Point”. “DEC” and “GRP” are both indicators of advertising effectiveness. “DEC” is typically the number of people who pass through the acceptable range (visible range) of the target advertisement per day. The "DEC" may be the number of passers-by who is a person who satisfies a predetermined age limit, such as 18 years old or older, or may be the number of passers-by who is not subject to any age limit. .. “GRP” is typically the proportion of the daily number of people who pass the above-mentioned acceptable range in the target population within the area that can be reached for the target advertisement in one day. “GRP” can be represented by [DEC / target population in target area]. The “target population in the target area” is the population that satisfies the age restriction in the target area when the age limit is set for the target of “DEC”.
　データ解析処理部２３Ｂは、各移動体Ｖごとのコンテンツの受容可能範囲の通過者人数に基づいて、通過者人数を表す指標として、各移動体Ｖごとの「ＤＥＣ」、「ＧＲＰ」を算出することができる。例えば、上述の図２で説明した各移動体Ｖごとの１日の乗車人数やその平均値、図５で説明した各移動体Ｖの合計の乗車人数等が各移動体Ｖごとの「ＤＥＣ」に相当する。 The data analysis processing unit 23B calculates “DEC” and “GRP” for each moving body V as an index representing the number of passing people based on the number of passing people in the content acceptable range for each moving body V. be able to. For example, the number of passengers in a day for each moving object V described in FIG. 2 and the average value thereof, the total number of passengers in each moving object V described in FIG. 5, and the like are “DEC” for each moving object V. Equivalent to.
　同様に、データ解析処理部２３Ｂは、各路線ごとのコンテンツの受容可能範囲の通過者人数に基づいて、通過者人数を表す指標として、各路線ごとの「ＤＥＣ」、「ＧＲＰ」を算出することができる。例えば、上述の図６、図７で説明した各路線ごとの１日の乗車人数やその平均値が各路線ごとの「ＤＥＣ」に相当する。 Similarly, the data analysis processing unit 23B calculates "DEC" and "GRP" for each route as an index indicating the number of passers based on the number of passers in the content acceptable range for each route. You can For example, the number of passengers on each day and the average value thereof for each route described in FIGS. 6 and 7 described above correspond to “DEC” for each route.
　そして、データ解析処理部２３Ｂは、受容可能範囲を通過した通過者人数を表す指標として、各移動体Ｖごと、各路線ごとの「ＤＥＣ」、「ＧＲＰ」を表す商用利用データを生成し、生成した商用利用データを含む解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させることができる。 Then, the data analysis processing unit 23B generates and generates commercial use data representing “DEC” and “GRP” for each moving body V and each route as an index representing the number of passers who have passed the acceptable range. The analysis result data including the above-mentioned commercial use data can be accumulated in the analysis result DB 22C and stored as a database.
　データ加工処理部２３Ｃは、データ解析処理部２３Ｂによって解析された解析結果データを所望の形式に加工する処理を実行する部分である。データ加工処理部２３Ｃは、解析結果データに含まれる移動体別乗車人数データ、路線別乗車人数データ、人物属性データ、属性別人流データ、商用利用データ等を所望の形式に加工する。データ加工処理部２３Ｃは、例えば、図８に例示するように、移動体別乗車人数データ、路線別乗車人数データ、人物属性データ、属性別人流データ、商用利用データを含む解析結果データを、いつ、どの路線のどこに、どんな属性の人が何人いたか、移動体Ｖごとの「ＤＥＣ」、「ＧＲＰ」、路線ごとの「ＤＥＣ」、「ＧＲＰ」等を地図上にプロットしたものや各種グラフ、ダイヤグラム等に加工する。そして、処理部２３は、データ加工処理部２３Ｃによって所望の形式に加工された解析結果データを、データ入出力部２１を介してクライアント端末ＣＬに出力する処理を実行する。クライアント端末ＣＬは、解析装置２０から提供された解析結果データを、例えば、商圏調査、マーケティング、広告、広告料を決める際の判断材料、防災・都市計画等の各種用途にて利用可能とする端末である。クライアント端末ＣＬは、例えば、ノート型ＰＣ、デスクトップ型ＰＣ、タブレット型ＰＣ、スマートフォン、携帯端末等によって構成される。 The data processing unit 23C is a unit that executes a process of processing the analysis result data analyzed by the data analysis processing unit 23B into a desired format. The data processing unit 23C processes the number of passengers for each moving body, the data for the number of passengers for each route, the attribute data for each person, the flow data for each attribute, and the commercial use data, which are included in the analysis result data, into a desired format. For example, as illustrated in FIG. 8, the data processing unit 23C displays the analysis result data including the number of passengers by moving body, the number of passengers by route, the person attribute data, the person flow data by attribute, and the commercial use data when , Which route and how many people had attributes, "DEC", "GRP" for each mobile unit V, "DEC" for each route, "GRP", etc. Process into a diagram. Then, the processing unit 23 executes a process of outputting the analysis result data processed into a desired format by the data processing unit 23C to the client terminal CL via the data input / output unit 21. The client terminal CL makes it possible to use the analysis result data provided from the analysis device 20 for various purposes such as commercial area surveys, marketing, advertisements, judgment materials when determining advertising fees, disaster prevention and city planning, etc. Is. The client terminal CL is composed of, for example, a notebook PC, a desktop PC, a tablet PC, a smartphone, a mobile terminal, or the like.
　次に、図９のフローチャート図を参照し解析システム１における処理の一例を説明する。 Next, an example of processing in the analysis system 1 will be described with reference to the flowchart of FIG.
　まず、複数の移動体Ｖにそれぞれ搭載された複数の記録装置１０は、移動体Ｖの移動に伴って画像データ、位置データを含む解析用データを収集する（ステップＳ１）。 First, the plurality of recording devices 10 respectively mounted on the plurality of moving bodies V collect analysis data including image data and position data as the moving bodies V move (step S1).
　次に、記録装置１０は、収集した解析用データを、データ入出力部１３を介して出力し、解析装置２０のデータ入出力部２１を介して解析装置２０に入力する（ステップＳ２）。解析装置２０に入力された解析用データは、解析対象ＤＢ２２Ａに記憶される。 Next, the recording device 10 outputs the collected analysis data via the data input / output unit 13 and inputs it to the analysis device 20 via the data input / output unit 21 of the analysis device 20 (step S2). The analysis data input to the analysis device 20 is stored in the analysis target DB 22A.
　次に、解析装置２０のデータ前処理部２３Ａは、解析対象ＤＢ２２Ａに記憶されている解析用データに対して、上述したような種々の前処理を施す（ステップＳ３）。 Next, the data preprocessing unit 23A of the analysis device 20 performs various preprocessing as described above on the analysis data stored in the analysis target DB 22A (step S3).
　次に、解析装置２０のデータ解析処理部２３Ｂは、データ前処理部２３Ａによって前処理が施された解析用データに基づいて解析を行い、解析結果データとして、移動体別乗車人数データ、路線別乗車人数データ、人物属性データ、属性別人流データ、商用利用データ等を生成する（ステップＳ４）。 Next, the data analysis processing unit 23B of the analysis device 20 performs analysis based on the analysis data that has been preprocessed by the data preprocessing unit 23A, and as analysis result data, the number of passengers for each moving body, and for each route Passenger number data, person attribute data, attribute-based flow data, commercial use data, etc. are generated (step S4).
　そして、データ解析処理部２３Ｂは、生成した移動体別乗車人数データ、路線別乗車人数データ、人物属性データ、属性別人流データ、商用利用データ等の解析結果データを解析結果ＤＢ２２Ｃに蓄積しデータベース化して記憶させる（ステップＳ５）。 Then, the data analysis processing unit 23B accumulates the generated analysis result data such as the number of passengers in each moving body data, the number of passengers in each route, the person attribute data, the attribute-based pedestrian flow data, and the commercial use data in the analysis result DB 22C and creates a database. And store it (step S5).
　次に、解析装置２０のデータ加工処理部２３Ｃは、クライアント端末ＣＬ等からの要求に応じて、解析結果ＤＢ２２Ｃに記憶されている解析結果データ（移動体別乗車人数データ、路線別乗車人数データ、人物属性データ、属性別人流データ、商用利用データ等）を、図８に例示したような所望の形式に加工する（ステップＳ６）。 Next, the data processing unit 23C of the analysis device 20 responds to a request from the client terminal CL or the like, and stores the analysis result data (the number of passengers for each moving body, the number of passengers for each route) stored in the analysis result DB 22C. Person attribute data, attribute-based person flow data, commercial use data, etc.) are processed into a desired format as illustrated in FIG. 8 (step S6).
　そして、解析装置２０の処理部２３は、データ加工処理部２３Ｃによって所望の形式に加工された解析結果データを、データ入出力部２１を介してクライアント端末ＣＬに出力、提供し（ステップＳ７）、一連の処理を終了する。 Then, the processing unit 23 of the analysis device 20 outputs and provides the analysis result data processed in the desired format by the data processing unit 23C to the client terminal CL via the data input / output unit 21 (step S7), A series of processing ends.
　以上で説明した解析システム１は、複数の移動体Ｖにそれぞれ搭載された複数の記録装置１０によって、各移動体Ｖの内部の画像を表す画像データ、及び、位置データを含む解析用データを収集することができる。そして、解析装置２０は、複数の記録装置１０によって収集された当該解析用データに基づいて、複数の路線の各路線ごとに、複数の移動体Ｖの乗車人数を計数することができる。すなわち、この解析システムは、例えば、配車の効率化等のために、１台の移動体Ｖが一日の間に複数の路線を走行しつつ、複数の移動体Ｖが複数の路線に渡って使い分けられて運行するような場合であっても、各移動体Ｖごとの乗車人数だけでなく、例えば、各路線に紐付いた各路線ごとの延べの乗車人数を適正に計数することができる。この結果、この解析システム１は、複数の移動体Ｖが移動する複数の路線の各路線ごとに適正に人物の流動の傾向を解析することができる。そして、解析システム１は、上記のように解析した各路線ごとの人物の流動の傾向を、商圏調査、マーケティング、広告、広告料を決める際の判断材料、防災・都市計画等の様々な用途で活用させることができる。 The analysis system 1 described above collects the image data representing the image inside each moving body V and the analysis data including the position data by the plurality of recording devices 10 respectively mounted on the plurality of moving bodies V. can do. Then, the analysis device 20 can count the number of passengers of the plurality of moving bodies V for each route of the plurality of routes based on the analysis data collected by the plurality of recording devices 10. That is, in this analysis system, for example, in order to improve the efficiency of vehicle allocation, one moving body V travels on a plurality of routes in one day, and the plurality of moving bodies V travels on a plurality of routes. Even when the vehicles are used separately, it is possible to properly count not only the number of passengers for each moving body V, but also the total number of passengers for each route associated with each route, for example. As a result, the analysis system 1 can appropriately analyze the flow tendency of the person for each of the plurality of routes on which the plurality of moving bodies V move. Then, the analysis system 1 can analyze the tendency of the flow of people for each route analyzed as described above in various applications such as commercial area surveys, marketing, advertisements, judgment materials when deciding advertisement fees, disaster prevention and city planning, etc. It can be utilized.
　ここでは、以上で説明した解析システム１は、画像データが表す画像に含まれる人物の数に基づいて移動体Ｖの乗車人数を計数する。これにより、解析システム１は、例えば、目視等により人手で移動体Ｖの乗車人数を計数するような場合と比較して、計数の作業負荷を低減し、計数自体の頻度を大幅に向上することができる。この結果、解析システム１は、より精度よく人物の流動の傾向を解析することができる。 Here, the analysis system 1 described above counts the number of passengers of the moving body V based on the number of persons included in the image represented by the image data. As a result, the analysis system 1 can reduce the workload of counting and significantly improve the frequency of counting itself, as compared with the case where the number of passengers in the moving body V is counted manually, for example. You can As a result, the analysis system 1 can analyze the flow tendency of a person with higher accuracy.
　より詳細には、以上で説明した解析システム１は、複数の記録装置１０によって収集された解析用データから特定の路線を移動した移動体Ｖの乗車人数を抽出し、当該特定の路線を移動した全ての移動体Ｖごとの当該特定の路線での乗車人数を集約し当該特定の路線における全ての移動体Ｖの合計の乗車人数を計数する。したがって、解析システム１は、複数の記録装置１０によって収集された解析用データに基づいて、複数の路線の各路線ごとにおける全ての移動体の合計の乗車人数を適正に計数することができる。 More specifically, the analysis system 1 described above extracts the number of passengers of the mobile body V that has moved on a specific route from the analysis data collected by the plurality of recording devices 10, and moves on the specific route. The number of passengers on the specific route for each of all the moving bodies V is aggregated, and the total number of passengers of all the moving bodies V on the specific route is counted. Therefore, the analysis system 1 can properly count the total number of passengers of all the moving bodies on each of the plurality of routes based on the analysis data collected by the plurality of recording devices 10.
　また、以上で説明した解析システム１は、さらに、解析装置２０によって解析用データに基づいて、複数の路線の各路線ごとに、画像データが表す画像に含まれる人物の属性を解析する。この結果、この解析システム１は、複数の移動体Ｖが移動する複数の路線の各路線ごとに、人物の流動の傾向として、移動体Ｖの乗車人数に加えて、移動体Ｖに乗車した人物の属性も解析することができる。これにより、この解析システム１は、例えば、複数の移動体Ｖによって運行される各路線ごとの乗車人数だけでなく、当該各路線ごとの乗車者の属性傾向を把握させることができ、逆に、所望の属性傾向の乗車者が多い路線等を容易に特定することができる。この結果、解析システム１は、各路線ごとの人物の流動の傾向を、上記のような様々な用途でより好適に活用させることができる。 Further, the analysis system 1 described above further analyzes the attribute of the person included in the image represented by the image data for each route of the plurality of routes by the analysis device 20 based on the analysis data. As a result, in this analysis system 1, in addition to the number of passengers of the moving body V, the person who got on the moving body V as a tendency of the flow of the person for each of the plurality of routes on which the plurality of moving bodies V move The attributes of can also be analyzed. As a result, the analysis system 1 can, for example, grasp not only the number of passengers on each route operated by the plurality of moving bodies V, but also the attribute tendency of the passenger on each route, and conversely, It is possible to easily specify a route or the like having many passengers having a desired attribute tendency. As a result, the analysis system 1 can more appropriately utilize the tendency of the flow of the person for each route in various applications as described above.
　一例として、以上で説明した解析システム１は、解析装置２０によって、複数の路線の各路線ごとの乗車人数に基づいて、当該各路線ごとに、移動体Ｖに搭載された出力装置ＯＤのコンテンツの受容可能範囲を通過した通過者人数を表す指標を算出する。この結果、解析システム１は、各路線ごとの当該指標を、例えば、各路線ごとに、出力装置ＯＤから出力するコンテンツの利用料（広告料等）を決める際の判断材料として好適に活用させることができる。また、解析システム１は、各路線ごとの乗車者の属性傾向を、例えば、各路線ごとに移動体Ｖの出力装置ＯＤから出力するコンテンツを決める際の判断材料として好適に活用させることができる。 As an example, in the analysis system 1 described above, based on the number of passengers of each of a plurality of routes by the analysis device 20, the content of the output device OD mounted on the moving body V of each route is displayed. An index representing the number of people who have passed the acceptable range is calculated. As a result, the analysis system 1 suitably uses the index for each route, for example, as a determination material when determining the usage fee (advertising fee, etc.) of the content output from the output device OD for each route. You can Further, the analysis system 1 can suitably utilize the occupant's attribute tendency for each route, for example, as a determination material when determining the content to be output from the output device OD of the mobile unit V for each route.
　なお、上述した本発明の実施形態に係る解析システムは、上述した実施形態に限定されず、請求の範囲に記載された範囲で種々の変更が可能である。 The above-described analysis system according to the embodiment of the present invention is not limited to the above-described embodiment, and various modifications can be made within the scope of the claims.
　以上で説明した移動体Ｖは、内部に出力装置ＯＤを搭載しているものとして説明したがこれに限らない。解析装置２０は、複数の路線の各路線ごとに、出力装置ＯＤのコンテンツの受容可能範囲を通過した通過者人数を表す指標を算出するものとして説明したがこれに限らない。 The moving object V described above has been described as having the output device OD mounted therein, but is not limited to this. The analysis device 20 has been described as calculating an index representing the number of passers-by who have passed the content acceptable range of the output device OD for each of a plurality of routes, but the present invention is not limited to this.
　また、以上で説明した解析装置２０は、複数の路線の各路線ごとに、画像データが表す画像に含まれる人物の属性を解析するものとして説明したがこれに限らない。 Further, the analysis device 20 described above is described as analyzing the attributes of a person included in the image represented by the image data for each route of a plurality of routes, but the present invention is not limited to this.
　以上で説明した制御部１４、解析装置２０は、各部が別体に構成され、当該各部が各種の電気信号を相互に授受可能に接続されることで構成されてもよく、一部の機能が他の制御装置によって実現されてもよい。また、以上で説明したプログラム、アプリケーション、各種データ等は、適宜、更新されてもよいし、解析システム１に対して任意のネットワークを介して接続されたサーバに記憶されていてもよい。以上で説明したプログラム、アプリケーション、各種データ等は、例えば、必要に応じてその全部又は一部をダウンロードすることも可能である。また、例えば、制御部１４、解析装置２０が備える処理機能については、その全部又は任意の一部を、例えば、ＣＰＵ等及び当該ＣＰＵ等にて解釈実行されるプログラムにて実現してもよく、また、ワイヤードロジック等によるハードウェアとして実現してもよい。 The control unit 14 and the analysis device 20 described above may be configured such that each unit is configured separately and each unit is connected so as to be capable of exchanging various electrical signals with each other, and some functions are It may be realized by another control device. In addition, the programs, applications, various data, and the like described above may be appropriately updated, or may be stored in a server connected to the analysis system 1 via an arbitrary network. For example, all or part of the programs, applications, various data, and the like described above can be downloaded as necessary. Further, for example, as for the processing functions of the control unit 14 and the analysis device 20, all or an arbitrary part thereof may be realized by, for example, a CPU or the like and a program interpreted and executed by the CPU or the like. Also, it may be realized as hardware such as a wired logic.
　例えば、解析システム１は、解析装置２０のデータ前処理部２３Ａ、データ解析処理部２３Ｂの一部の機能が各記録装置１０側に設けられていてもよい。例えば、解析システム１は、各記録装置１０側で人物を含む外周画像の切り取り等の１次画像解析を行い、各記録装置１０から解析装置２０に送信された解析用データに基づくデータに応じて、解析装置２０側で、乗車人数の計数、人物属性の解析等の２次画像解析を行うようにしてもよい。また例えば、解析システム１は、各記録装置１０側で各移動体Ｖごとの個別の乗車人数を計数し移動体別乗車人数データを生成し、各記録装置１０から解析装置２０に送信された解析用データに基づくデータに応じて、解析装置２０側で、各路線ごとに複数の移動体Ｖの乗車人数を計数し路線別乗車人数データを生成してもよい。 For example, in the analysis system 1, some functions of the data preprocessing unit 23A and the data analysis processing unit 23B of the analysis device 20 may be provided on each recording device 10 side. For example, the analysis system 1 performs primary image analysis such as clipping of an outer peripheral image including a person on each recording device 10 side, and according to the data based on the analysis data transmitted from each recording device 10 to the analysis device 20. The analysis device 20 may perform secondary image analysis such as counting the number of passengers and analyzing the attributes of people. Further, for example, the analysis system 1 counts the number of individual passengers for each moving body V on the side of each recording device 10 to generate the number of passengers for each moving body, and the analysis transmitted from each recording device 10 to the analyzing device 20. Depending on the data based on the use data, the number of passengers of the plurality of moving bodies V may be counted for each route on the analysis device 20 side to generate the passenger number data for each route.
１　解析システム
１０　記録装置（データ収集装置）
１１　内部カメラ
１２　位置情報測定器
１３、２１　データ入出力部
１４　制御部
１４Ａ、２２　記憶部
１４Ｂ、２３　処理部
２０　解析装置（データ解析装置）
２２Ａ　解析対象ＤＢ
２２Ｂ　解析参照ＤＢ
２２Ｃ　解析結果ＤＢ
２３Ａ　データ前処理部
２３Ｂ　データ解析処理部
２３Ｃ　データ加工処理部
ＣＬ　クライアント端末
ＯＤ　出力装置
Ｒ１、Ｒ２１、Ｒ２２、Ｒ２３　路線
Ｖ　移動体 1 Analysis system 10 Recording device (data collection device)
11 Internal Camera 12 Position Information Measuring Device 13, 21 Data Input / Output Unit 14 Control Unit 14A, 22 Storage Unit 14B, 23 Processing Unit 20 Analysis Device (Data Analysis Device)
22A Analysis target DB
22B Analysis reference DB
22C analysis result DB
23A Data pre-processing unit 23B Data analysis processing unit 23C Data processing processing unit CL Client terminal OD Output device R1, R21, R22, R23 Route V Mobile

Claims (5)

  1. 　複数の路線を移動する複数の移動体にそれぞれ搭載され、当該移動体の内部の画像を表す画像データ、及び、当該移動体の内部の画像が撮像された位置を表す位置データを含む解析用データを収集する複数のデータ収集装置と、
    　前記複数のデータ収集装置によって収集された前記解析用データに基づいて、前記複数の路線の各路線ごとに、前記複数の移動体の乗車人数を計数するデータ解析装置とを備えることを特徴とする、
    　解析システム。     Analysis data including image data representing an image inside the moving body and position data representing a position where the image inside the moving body is captured, which is mounted on each of the moving bodies moving on the plurality of routes. A plurality of data collection devices for collecting
    A data analysis device that counts the number of passengers of the plurality of moving bodies for each of the plurality of routes based on the analysis data collected by the plurality of data collection devices. ,
    Analysis system.
  2. 　前記データ解析装置は、前記画像データが表す画像に含まれる人物の数に基づいて、前記乗車人数を計数する、
    　請求項１に記載の解析システム。     The data analysis device counts the number of passengers on the basis of the number of persons included in the image represented by the image data.
    The analysis system according to claim 1.
  3. 　前記データ解析装置は、前記解析用データに含まれる前記位置データに基づいて、前記複数のデータ収集装置によって収集された前記解析用データから、前記複数の路線のうち特定の路線を移動した前記移動体の前記乗車人数を抽出し、当該特定の路線を移動した全ての前記移動体の当該特定の路線での前記乗車人数を集約し、当該特定の路線における全ての前記移動体の合計の前記乗車人数を計数する、
    　請求項１又は請求項２に記載の解析システム。     The data analysis device, based on the position data included in the analysis data, from the analysis data collected by the plurality of data collection devices, the movement of moving a specific route among the plurality of routes. The number of passengers on the body is extracted, and the number of passengers on the specific route of all the moving bodies that have traveled on the specific route are aggregated, and the total ride of all the moving bodies on the specific route Counting the number of people,
    The analysis system according to claim 1 or 2.
  4. 　前記データ解析装置は、前記解析用データに基づいて、前記複数の路線の各路線ごとに、前記画像データが表す画像に含まれる人物の属性を解析する、
    　請求項１乃至請求項３のいずれか１項に記載の解析システム。     The data analysis device, based on the analysis data, for each route of the plurality of routes, analyzes the attribute of the person included in the image represented by the image data,
    The analysis system according to any one of claims 1 to 3.
  5. 　前記移動体は、内部に、コンテンツを出力可能である出力装置が搭載され、
    　前記データ解析装置は、前記複数の路線の各路線ごとの前記乗車人数に基づいて、前記複数の路線の各路線ごとに、前記出力装置が出力する前記コンテンツを受容可能な受容可能範囲を通過した通過者人数を表す指標を算出する、
    　請求項１乃至請求項４のいずれか１項に記載の解析システム。     The moving body is internally provided with an output device capable of outputting contents,
    The data analysis device has passed an acceptable range in which the content output by the output device can be received, for each route of the plurality of routes, based on the number of passengers on each route of the plurality of routes. Calculate an index that represents the number of passersby,
    The analysis system according to any one of claims 1 to 4.
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