JPWO2014038014A1 - Face-to-face data generation apparatus and face-to-face data generation method - Google Patents

Abstract

A face-to-face data generation apparatus that includes a processor and a storage unit and generates data related to physical face-to-face contact between persons, and the physical quantity detected by a first sensor of a sensor terminal attached to each of a plurality of persons A communication unit that receives sensing data to be received and a second sensor that is disposed at a predetermined position and that measures the position of the person, and that determines the position of the person based on the received data. A first measurement unit, a second measurement unit arranged at a predetermined position and communicating with the sensor terminal to identify the position of the sensor terminal, and the position of the person identified by the first measurement unit A face data generation unit that combines the position of the sensor terminal specified by the second measurement unit and generates the face data of the person based on the physical quantity of the sensing data.

Description

  The present invention quantifies communication in business according to the activity situation using person-to-person data acquired by a wearable sensor terminal and person activity data acquired by a distance sensor installed indoors. The present invention relates to a computer system for visualizing data. In particular, the present invention relates to a business system that grasps the situation of persons facing each other in business and extracts the relationship between the persons.

  For companies, people are important capital, and the state of the company changes greatly depending on the behavior of people. Communication is one of the actions necessary for the smooth execution of business. Communication is very important in various situations, such as checking the purpose and direction of a team, sharing situational awareness and problem awareness, exchanging know-how and knowledge, and getting ideas for work and problem solving. Indicates role. By grasping communication objectively and knowing the actual state of communication, it becomes possible to know the characteristics and problems of the organization, and to improve the efficiency and efficiency of business, and to revitalize the organization.

  One way to know the actual state of communication in business is a network correlation diagram that presents the relationship between people visually and clearly. In the network correlation diagram, a person is regarded as one node, and nodes in which some kind of interaction (correlation) occurs are connected by a line according to the strength of the interaction.

  2. Description of the Related Art Conventionally, a technique for generating a network diagram between members of an organization from an email, an electronic document filing system, and a telephone communication record log is known as a method for generating a correlation diagram of people in business (for example, patent literature) 1, Patent Document 2).

  This makes it possible to know the online communication status inside and outside the company, but not the face-to-face physical meeting. As a technique for acquiring a person's physical meeting in business, a technique for calculating a value indicating a relationship between wearers from data acquired by a sensor terminal worn by the person is known (for example, Patent Document 3).

  On the other hand, it has become easy to use due to the recent price reduction of distance sensors, and the development of services using the three-dimensional shape and movement of the object obtained from the data acquired by the sensors is progressing. For example, a usage method such as operating a PC or a television by a gesture or changing an image displayed in accordance with a body movement has been proposed.

JP2007-249307 JP 2009-59075 A JP2008-210363

  In the above conventional example, it is possible to know the communication status between persons wearing the sensors. However, we were unable to know the status of communication with visitors from outside the company, who are difficult to put on sensors.

  As one of the information necessary for smooth execution of business and improvement of business efficiency, physical face-to-face situation including internal and external business is quantitatively analyzed not only in time but also in quality (activity). It is effective to grasp. From the conventional example and the combination of the conventional examples, there is a problem that the face-to-face situation between persons inside and outside the company cannot be grasped.

  The present invention is a face-to-face data generation apparatus that includes a processor and a storage unit and generates data related to physical face-to-face contact between persons, and is detected by a first sensor of a sensor terminal attached to each of a plurality of persons. A communication unit that receives sensing data indicating the measured physical quantity and a second sensor that is arranged at a predetermined position and measures the position of the person, and the position of the person based on the received data A first measurement unit that identifies the first measurement unit, a second measurement unit that is disposed at a predetermined position and communicates with the sensor terminal to identify the position of the sensor terminal, and the first measurement unit identifies the position A face data generation unit that combines the position of the person and the position of the sensor terminal specified by the second measurement unit, and generates the face data of the person based on the physical quantity of the sensing data; That.

  According to the present invention, by analyzing the sensing data of the sensor terminal, not only can the status of communication between persons wearing the sensor terminal be understood, but also the status of communication with a person not wearing the sensor terminal can be grasped. It is also possible.

It is a block diagram which shows the Example of this invention and shows the structure and utilization state of a business facing data generation system. It is a block diagram which shows the Example of this invention and shows an example of a structure of a client. It is a block diagram which shows the Example of this invention and shows an example of a structure of an application server. It is a block diagram which shows the Example of this invention and shows an example of a structure of a data processing server. It is a block diagram which shows the Example of this invention and shows an example of a structure of measurement PC. It is a block diagram which shows the Example of this invention and shows an example of a structure of a sensor network server. It is a block diagram which shows the Example of this invention and shows an example of a structure of a base station. It is the first half part of the block diagram which shows the Example of this invention and shows an example of a structure of a terminal. It is a second half part of the block diagram which shows the Example of this invention and shows an example of a structure of a terminal. It is a sequence diagram which shows the Example of this invention, measures the data of the distance sensor which records the activity of the meeting with the outsider, and shows an example of a process until meeting secondary meeting data generation with a data processing server. It is a sequence diagram which shows an Example of this invention and shows an example of a process until sensing data is stored in a sensor network server. It is a sequence diagram which shows the Example of this invention and shows an example of the basic content production | generation process performed with an application server. FIG. 10 is an example of the first half of a sequence diagram illustrating an example of processing for displaying a screen on a client according to an embodiment of this invention. It is a second half part of a sequence diagram showing an example of the present invention and showing an example of processing for displaying a screen on a client. It is the first half of the flowchart which shows the Example of this invention and shows an example of the seating chart production | generation process at the time of the meeting performed by measurement PC. It is a second half part of the flowchart which shows the Example of this invention and shows an example of the seating chart production | generation process at the time of the meeting performed by measurement PC. It is a figure which shows the Example of this invention and shows an example of meeting basic data. It is a conceptual diagram of the process which shows the Example of this invention and extracts a person area | region from sensing data. It is a conceptual diagram of the process which shows the Example of this invention and calculates a person area center from sensing data. It is a conceptual diagram of the process which shows the Example of this invention and calculates a person area center from sensing data. It is a conceptual diagram of the process which shows the Example of this invention and calculates a person area center from sensing data. It is a conceptual diagram of the process which shows the Example of this invention and produces | generates a seating chart from the person area center. It is an example of the figure which shows the Example of this invention and shows the coordinate of the person area center calculated based on sensing data. It is an example of the seat plan sketch calculated based on sensing data, showing an example of the present invention. It is a top view which shows the Example of this invention and shows an example of the viewing angle (measurement range) of a sensor wearer detector. It is a figure which shows the Example of this invention and shows an example of the basic information measured with the sensor wearer detector. It is a figure which shows the Example of this invention and shows an example of the detection ID data table of a sensor wearer detector. It is a figure which shows the Example of this invention and shows an example of the detection ID data table of another sensor wearer detector. It is an example of the figure which shows the Example of this invention and shows the detection ID reception frequency of a sensor wearer detector. It is an image which shows the Example of this invention and has superposed the arrangement | positioning and viewing angle of a sensor wearer detector, and a seating plan sketch. It is a figure which shows the Example of this invention and shows an example of a user list. It is an image which shows the Example of this invention and shows an example of the screen which inputs data into a seating plan. It is an image which shows the Example of this invention and shows an example of the screen which inputs data into a seating plan. It is an image which shows the Example of this invention and shows an example of the screen which inputs data into a seating plan. It is an image which shows the Example of this invention, shows the Example of this invention, and shows an example of the screen which inputs data into a seating plan. It is a figure which shows the Example of this invention and shows an example of the seating table of a conference participant. It is a flowchart which shows the Example of this invention and shows an example of the conference activity amount calculation process performed with a data processing server. It is a figure which shows the Example of this invention and shows an example of the sensing data measured with the distance sensor. It is a figure which shows the Example of this invention and shows an example of the human head three-dimensional coordinate value for every time in a meeting. It is an example of the figure which shows the Example of this invention and shows the person head movement amount for every time in a meeting. It is an example of the figure which shows the Example of this invention and shows the person head movement amount for every time in a meeting. It is the figure which showed the Example of this invention and matched the person's vertebral number with the table | surface which shows the human head movement amount for every time in a meeting. It is the figure which showed the Example of this invention and matched the person area | region and the seating chart person number. It is the figure which shows the Example of this invention and matched the person's name and head movement amount for every time in a meeting. It is a flowchart which shows the Example of this invention and shows an example of the production | generation process of the meeting facing secondary data performed with a data processing server. It is a figure which shows the Example of this invention and shows an example of the meeting activity table | surface which shows the activity for every time and the person in a meeting. It is a figure which shows the Example of this invention and shows the other form of the meeting activity table | surface which shows the activity for every person for every time in a meeting. It is a figure which shows the Example of this invention and shows an example of the count of the meeting activity table of the state which considered the activity level of the other party. It is a figure which shows the Example of this invention and shows an example of the conference activity matrix which is conference activity secondary data. It is a figure which shows the Example of this invention and shows the other example of the conference activity matrix which is conference activity secondary data. It is a flowchart which shows the Example of this invention and shows an example of the business meeting activity matrix production | generation process performed with an application server. It is a figure which shows the Example of this invention and shows the example which calculates a meeting activity correction value. It is a figure which shows the Example of this invention and shows the example of the interactive meeting activity matrix based on the data acquired with the sensor terminal. It is a figure which shows the Example of this invention and shows the example of the one-way facing activity matrix based on the data acquired with the sensor terminal. It is a figure which shows the Example of this invention and shows an example of a sensing database. It is a figure which shows the Example of this invention and shows an example of a sensing database. It is an example of the figure which shows the Example of this invention and shows a sensing database. It is an example of the business meeting activity matrix which showed the Example of this invention and was produced | generated based on the sensor terminal secondary data and the conference activity secondary data. It is an example of the business meeting activity matrix which showed the Example of this invention and was produced | generated based on the sensor terminal secondary data and the conference activity secondary data. It is a figure which shows the Example of this invention and shows an example of the basic policy of the display between nodes at the time of network figure production | generation. It is a figure which shows the Example of this invention and shows the example whose bidirectional | two-way activity of persons A and B is 100% by the display between nodes at the time of network diagram generation. It is a figure which shows the Example of this invention and shows the example which only the activity level of the person A is 100% by the display between nodes at the time of network diagram generation. It is a figure which shows the Example of this invention and shows the example which only the activity level of the person B is 100% by the display between nodes at the time of network diagram generation. It is an example of the in-house network diagram which showed the Example of this invention and was produced | generated from the face-to-face activity matrix. It is an example of the in-house activity network diagram which showed the Example of this invention and was produced | generated from the face-to-face activity matrix. It is an example of the in-house activity network diagram which showed the Example of this invention and was produced | generated from the face-to-face activity matrix. It is an example of the business network diagram which showed the Example of this invention and was produced | generated from the business meeting activity matrix. It is an example of the business activity network diagram which showed the Example of this invention and was produced | generated from the business meeting activity matrix. It is an example of the business activity network diagram which showed the Example of this invention and was produced | generated from the business meeting activity matrix. It is a flowchart which shows the Example of this invention and shows a browser determination process. FIG. 2 is an example of a diagram illustrating an embodiment of the present invention, illustrating an embodiment of the present invention, and illustrating an access control rule; It is an example of the figure which shows the Example which shows the Example of this invention and displays on a client.

  Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings.

  The present invention is a business face-to-face data generation system that generates face-to-face data indicating that a person has faced the person in the work, and using a plurality of sensing data, the face-to-face situation with not only inside the company but also outside the person, A business face-to-face activity matrix and visualization data are generated together with the amount of activity at the time of face-to-face. Hereinafter, description will be made with reference to the drawings. Note that the business facing data generation system is a computer system including a sensor, a computer, and a network.

  First, a first embodiment of the present invention will be described with reference to the drawings. In the first embodiment, face-to-face data between internal employees (employees) and face-to-face data with outsiders are combined. Then, face-to-face data between persons including inside and outside the business is generated. In generating the face-to-face data, the communication amount (face-to-face time) is calculated from the face-to-face data of the outside person and the in-house (or outside) person in the same unit system as the face-to-face data between the persons in the company. Further, the first embodiment is characterized in that the amount of activity of the person at the time of meeting is also calculated.

  In the first embodiment, in the generation of in-house face-to-face data, a method for generating face-to-face data between employees based on information obtained from sensor terminals worn by employees is disclosed. Good. This makes it possible to generate face-to-face data based on the substance when face-to-face employees in the company.

  Further, in the first embodiment, a method of using a distance sensor installed in the conference room is disclosed in generating the meeting data with an outsider, but other methods such as image recognition may be used.

<Figure 1: Overall processing flow>
FIG. 1 shows an outline of a business meeting data generation system according to the first embodiment. In the first embodiment, a sensor terminal (TR, TR2 to 8: hereinafter referred to as TR when not identifying an individual) is worn by an employee (person in the company) who is a user (US). Sensing data related to each employee's behavior and interaction (interaction) between employees is acquired by the terminal (TR). As for the interaction, when the users (US) face each other, the face-to-face state is detected by transmitting and receiving infrared rays between the sensor terminals (TR). The sensor terminal (TR) detects infrared rays from other sensor terminals that face each other as one of the physical quantities. Sensing data acquired by each terminal (TR) is transmitted to a base station (GW) connected wirelessly or by wire.

  The base station (GW) stores the sensing data transferred via the network (NW) in the sensor network server (SS). The sensor network server (SS) performs preprocessing of the stored sensing data periodically (such as a predetermined cycle) to generate secondary data, and stores it as secondary data.

  On the other hand, in the conference room used by the employee (US) and the company visitor (VT, VT2-3: hereinafter, all shown as VT when not identifying the individual) for a meeting or the like, the distance sensor (RS) The state of the meeting is measured by shape data and transmitted to the measurement PC (MP). The distance sensor (RS) is installed at a predetermined position in the conference room, and generates shape data by measuring the distance while scanning the conference room using a well-known technique such as wireless, sound wave, and light.

  In addition, the sensor terminal wearer detector (ISD) arranged at a predetermined position in the conference room detects the terminal ID of the person wearing the sensor terminal (TR), that is, the employee (US), and measuring PC To (MP). The sensor terminal wearer detector (ISD) is installed at a predetermined position in the conference room, and communicates with the sensor terminal (TR) using a known technology such as radio, sound wave, light, etc., and the sensor terminal (TR). And the terminal ID set in the sensor terminal (TR). Details of the sensor terminal wearer detector (ISD) will be described later.

  The measurement PC (MP) generates a seating chart based on the actual arrangement of persons (employees and visitors) and furniture in the conference room from the shape data acquired by the distance sensor (RS). Then, the measurement PC (MP) wears the sensor terminal (TR) from the terminal ID detected by the sensor terminal wearer detector (ISD) and the position and direction of the sensor terminal wearer detector (ISD). Identify the seats of employees who are working.

  Next, the measurement PC (MP) specifies the seat position of the visitor (VT) from the generated seat chart and the seat of the employee (US). The measurement PC (MP) uses the input device to input visitor information for the specified seat position, thereby generating a seating table in which the names of the participants in the conference and the seat positions are associated with each other.

  The seating chart data generated by the measurement PC (MP) and the sensing data acquired by the distance sensor (RS) are transmitted to the data processing server (DS).

  In the data processing server (DS), the activity level of the conference participants is calculated based on the sensing data including the generated seating chart data and the shape data acquired by the distance sensor (RS). Conference activity secondary data (conference data) is generated after calculating the activity of the conference for the combination.

  In the present embodiment, the activity is used as a value for estimating the number of speeches at the meeting from the body movements of the participants obtained from the amount of activity. That is, when there is much movement of the participant's body, it is estimated that there are many remarks at the conference, and in this case, it is determined that the activity is high. That is, when an active discussion is performed, gestures when speaking are increased, and operations such as whispering when listening to opinions are also increased. Such a situation where there is an active exchange of opinions is assumed to be highly active.

  On the contrary, when the participant's body movement is small, it is estimated that there are few statements at the conference, and in this case, it is determined that the activity is low. That is, in a situation where the user simply listens to an announcement from another person, the activity such as whispering decreases when listening to an opinion, and the activity is low in a situation where there is almost no exchange of opinions.

  As described above, in the present invention, the activity level of the meeting (or conversation) is estimated from the activity amount of the person who is facing.

  When generating content (mostly images, but other data such as video, text data, audio data, etc.) to be displayed for the user (US) who is an employee can be generated by the client (CL). The application server (AS) periodically acquires conference data and business data from the data processing server (DS), and acquires secondary data from the sensor network server (SS). Then, the application server (AS) performs processing that combines the business data and the secondary data to generate content.

  The client (CL) has a viewer detector (CLBD) and a display (CSOD), and the viewer detector (CLBD) receives infrared information including the terminal ID transmitted from the terminal (TR). It is detected that the user (US) is browsing the display. As a method for detecting a viewer, in addition to the infrared sensor, a face recognition using a wireless transceiver, RFID, or camera may be used. When a viewer is detected, the client (CL) sends a list of viewers to the application server (AS), and the application server (AS) transmits the received content for the viewer to the client (CL). . The client (CL) displays the received content on the screen (OD) of the display (CLOD).

  The NTP server (TS) transmits a reference time in order to synchronize the time of a computer, a sensor terminal (TR), and a base station (GW) connected to the network (NW).

<Block diagram of each server and device>
FIG. 2A and FIG. 2B to FIG. 5A and FIG. 5B are block diagrams illustrating the configuration of a computer for realizing the business face-to-face data generation system according to the embodiment of this invention. For convenience of illustration, the components shown in FIGS. 2A to 5A and 5B are divided. However, as shown in FIG. 1, the respective constituent elements operate in cooperation with each other. Each function in the figure is realized by hardware or software, or a combination of hardware and software, and each functional block is not necessarily accompanied by a hardware entity. Hereinafter, each component will be described as having a control unit, a storage unit, and a transmission / reception unit, as shown in FIGS. 2A and 2B to FIGS. 5A and 5B.

  Each control unit is configured by a central processing unit (CPU, not shown) that is a processing unit such as a normal computer, and the storage unit is configured by a memory device such as a semiconductor storage device or a magnetic storage device. The transmission / reception unit includes a network interface such as wired or wireless. In addition, a clock or the like is provided as necessary.

  2A, 2B to 5A, and 5B are different types of arrows for time synchronization, associate, storage of acquired sensing data, analysis of sensing data, firmware update, and control signal, respectively. Each represents a data or signal flow. Hereinafter, description will be made with reference to FIGS. 2A and 2B to FIGS. 5A and 5B individually.

<Client (CL), Application server (AS)>
2A and 2B are block diagrams showing examples of the client (CL) and the application server (AS).

<Client (CL)>
In FIG. 2A, the client (CL) inputs and outputs data as a contact (interface) with the user (US). The client (CL) includes an input / output unit (CLIO), a transmission / reception unit (CLSR), a storage unit (CLME), a control unit (CLCO), and a viewer detector (CLVD).

  The input / output unit (CLIO) is a part serving as an interface with the user (US). The input / output unit (CLIO) includes a display (CLOD), a touch panel (CLIT), a keyboard (CLIK), a mouse (CLIM), and the like. Other input / output devices can be connected to an external input / output (CLIU) as required.

  The display (CLOD) is an image display device such as a CRT (Cathode-Ray Tube) or a liquid crystal display. The display (CLOD) may include a speaker, a printer, and the like. When the touch panel (CLIT) is used to support input by the user (US), the touch panel (CLIT) is installed so as to overlap the screen (OD) of the display (CLOD), and the output and input are on the same screen. It can also be displayed as it does.

  The transmission / reception unit (CLSR) transmits / receives data and commands to / from the application server (AS) and other devices connected to the network (NW). Specifically, the transmission / reception unit (CLSR) transmits a content request to the application server (AS) and receives the content corresponding to the request from the application server (AS).

  The storage unit (CLME) is configured by an external recording device such as a hard disk, a memory, or an SD (registered trademark) memory card. The storage unit (CLME) stores a detector ID (CLVDID) which is an ID of a viewer detector (CLVD) and a terminal ID list (CLID) indicating a list of valid terminal IDs, and is detected. Stores a client log (CLCB) for accumulating a log of a viewer and a record of detection time and other events occurring in the client.

  The viewer detector (CLVD) is a terminal built in or externally connected to the client (CL), has a sensor such as an infrared transmitter / receiver (CLVDIR) or a human sensor (CLVDHI), and displays the client (CL) display ( This is for detecting a viewer who is browsing (CLOD). When the browser detector (CLVD) is externally connected to the client (CL), it is connected via an interface such as a USB. When a viewer is detected by infrared rays, detection is performed by receiving a terminal ID periodically transmitted from an infrared transmission / reception unit (AB) provided in a sensor terminal (TR) worn by a user (US).

  The control unit (CLCO) includes a CPU (not shown), controls communication, inputs related to content selection from the user (US), and input / output control (CLCIO) for outputting content to the user (US). Control of the viewer detector (CLCBD), browser determination (CLCVD) for appropriately determining the viewer from the detected data, content list request (CLCLR) and content request (CLCLR) to the application server (AS) CLCCR) is executed.

  The detector control (CLCBD) controls the operation of the viewer detector (CLVD). A detector ID (CLVDID) is given and transmitted from the viewer detector (CLVD), or the received information is noise. In this case, it is confirmed that the data is valid by referring to the terminal ID list (CLID), and infrared transmission / reception timing in the viewer detector (CLVD) is controlled. In the browser determination (CLCVD), users who are considered to be browsing at the present time are sequentially identified based on the detection data obtained from the viewer detector (CLVD).

  In the content list request (CLCLR), a list of terminal IDs of the current viewer is sent to the application server (AS), and the content list having the browsing permission in the member configuration of the viewer, the name of the viewer, the application server ( AS). In this regard, the content list (ASCL) and the access control rule (ASAC) may be held in the client (CL), and a content list having browsing permission may be generated in the client (CL). However, by generating a content list (ASCLM) that is permitted to be viewed on the application server (AS) side and searching for the name from the terminal ID, the name of the user as personal information is changed to the client (CL). This eliminates the need to hold the data and increases security.

  The input / output control (CLCIO) generates and controls a screen image to be output to the display (CLOD), and also accepts input from a touch panel (CLIT), a mouse (CLIM), and the like. The output screen is sequentially changed according to the input, that is, the user's operation. The input / output control (CLCIO) reflects the content list received from the application server (AS) and the name of the user, and displays a content switching button (OD_C) and a viewer selection button (OD_A) on the screen. The content switching button (OD_C) and the viewer selection button (OD_A) will be described later with reference to FIG. These buttons are for the user to select content that the user wants to browse, and only buttons related to content that has browsing permission in the member configuration of the viewer at the time of selection are displayed. By this mechanism, since the viewer cannot access content that does not have permission to browse, browsing restrictions can be realized.

  The input / output control (CLCIO) waits for input from the touch panel (CLIT) or mouse (CLIM) by a user operation, and when there is an input operation, requests for content corresponding to the input operation are sent to the application server (AS). Send and receive content information (CLCCR). The content information is mainly an image and is received together with a highlighted coordinate list (ASEM) corresponding to the terminal ID. When there is no designation by the user operation, the latest date data (content) is requested. The input / output control (CLCIO) displays a content image on a display, and an overlay (CLCEM) displays symbols such as a rectangle and a circle for emphasizing coordinates corresponding to the current viewer. . In addition, highlighting (CLCEM) displays a content image by moving or enlarging the image so that a portion including the current viewer comes to the center of the screen. With this function, it is possible to first focus attention on information having a high priority for the viewer.

<Application server (AS)>
In FIG. 2B, the application server (AS) receives conference data from the data processing server (DS) and receives secondary data of sensing data from the sensor network server (SS). The application server (AS) processes the received secondary data of the conference data and sensing data, and provides content information to be presented to the user (US) through the client (CL) or a personal client (CP) not shown. Generate. The content information is mostly an image, but may be other data such as a moving image, text data, audio data, or a combination of these data.

  The application server (AS) includes a transmission / reception unit (ASSR), a storage unit (ASME), and a control unit (ASCO). The transmission / reception unit (ASSR) transmits and receives data to and from the sensor network server (SS), data processing server (DS), NTP (Network Time Protocol) server (TS), and client (CL) through the network (NW). Control reception.

  The storage unit (ASME) is configured by an external recording device such as a hard disk, a memory, or an SD memory card. The storage unit (ASME) stores the generated content information, a program for generating content, and other data related to content generation. Specifically, the storage unit (ASME) includes a user attribute list (ASUL), an external meeting person list (ASPL), a content list (ASCL), a client log (ASCB), an access control rule (ASAC), a business meeting activity matrix. (ASGM), basic content file (ASBF), highlighted coordinate list (ASEM), sensor terminal information reading program (ASSR), conference activity secondary data reading program (ASKR), basic content generation program (ASCBC4), business face-to-face activities A matrix generation program (ASCMC) and a meeting facing secondary data correction program (ASCCC) are stored.

  The user attribute list (ASUL) can refer to the relationship between the ID of the sensor terminal (TR) and the name, terminal ID, affiliation, mail address, attribute, etc. of the user (US) wearing the sensor terminal (TR). It is a comparison table.

  The external meeting person list (ASPL) is a comparison table that can refer to the name, company name, affiliation, position, etc. of the outside meeting person (visitor). A company visitor is extracted from the basic conference data stored in the data processing server (DS), and the application server (AS) combines the extraction results to generate an external meeting list (ASPL).

  The content list (ASCL) is a list describing a list of contents that can be presented by the client (CL). When a content list request (CLCLR) is received from the client (CL) together with the terminal ID of the viewer, the content list (ASCL) and the access control rule (ASAC) are inquired together, and in the content list generation (ASCLM) A list that can be browsed by the current viewer is extracted and transmitted to the client (CL).

  The access control rule (ASAC) defines a condition for enabling browsing for each content. It is mainly defined by the terminal ID or attribute. For example, the terminal ID is logical so that it can be viewed when a user belonging to a specific organization or a user with a specific position or higher is included in the viewer. It is defined by the OR of the expression. Further, the logical expression AND may be defined so that browsing is possible only when all the specific members are detected by the browser detector (CLVD). Alternatively, it may be specified that browsing is not possible when a specific member is present.

  The business face-to-face activity matrix (ASGM) uses organization members (employees) and face-to-face counterparts (visitors) outside the organization as elements of the vertical axis (column direction) and horizontal axis (row direction), and the application server (AS ) Is obtained by digitizing the information related to meeting in each combination (time corresponding to the activity at the time of meeting) and inputting the numerical value to the corresponding cell on the business meeting activity matrix (ASGM). This numerical value is generated by secondary data of sensing data, that is, internal meeting data, and secondary data relating to the meeting at the time of meeting obtained by processing and analyzing the distance sensor data, that is, external meeting data.

  The basic content file (ASBF) contains content information (as a result of basic content generation (ASCBC)) (many are images, but may be other data such as moving images, text data, audio data). An image based on sensor data relating to a specific period or a specific member may be accommodated, or a text content or coordinate value of the text is stored as text data, and a basic content file when called from a client (CL) May be combined and rearranged to generate an image. A program that changes the shape of an image in real time according to a user operation, such as a servlet, may be used. All contents are provided with tags such as date, terminal ID or organization ID, and content type, and are specified as one by a request from the client (CL).

  The secondary data reading program (ASSR) is a program for reading secondary data of sensing data received from the sensor network server (SS). A file format such as a face-to-face activity matrix (ASMM) which is secondary data is held, and data of a specified date, time and target user is read in accordance with the file format. The face-to-face activity matrix (ASMM) will be described later with reference to FIGS. 33A and 33B.

  The conference activity data reading program (ASKR) is a program for reading the conference basic data received from the data processing server (DS) and the secondary data of the conference activity obtained by processing and analyzing the data of the distance sensor (RS). is there. The conference activity secondary data will be described with reference to FIGS. 30A and 30B described later.

  The external meeting person list update program (ASLU) extracts information, name, company name, affiliation and position, etc. related to external meeting persons from the data read by the meeting information reading program (ASGR), and puts it in the list as necessary. Append.

  The basic content generation program (ASBP) is various programs for generating basic content. At the time of basic content generation (ASCBC), this is started by timer start (ASTK), manual start by an administrator, or a request by a client (CL), and a basic content file is output.

  The business face-to-face activity matrix generation program (ASMCC) is a part of the basic content generation program (ASBP), and is a program for generating a business face-to-face activity matrix (ASGM), which is a base for content generation for visualizing business face-to-face. is there. In the business face-to-face activity matrix (ASGM), activities of a communication amount corresponding to the activities at the time of face-to-face are recorded in an N × N matrix.

  The control unit (ASCO) includes a CPU (not shown), and executes data transmission / reception control and data processing. Specifically, a CPU (not shown) executes a program stored in a storage unit (ASME), thereby generating a content list (ASCLM), content selection / drawing control (ASCCS), timer activation (ASTK), basic Processing such as content generation (ASCBC) and highlight coordinate list generation (ASCEM) is executed. Also, the clock (ASCK) held inside holds the standard time of the site (where the system is installed) by periodically connecting to an external NTP server (TS).

  When the content list generation (ASCLM) receives a content list request (CLCLR) together with the viewer's terminal ID from the client (CL), the content list generation (ASCL) and the access control rule (ASAC) are inquired together. This is a process of performing processing from extracting a list of contents that are permitted to be browsed by the viewer of the current client (CL) and transmitting it to the client (CL). The same applies when a content list request (CPCLR) is received from a personal client (CP) (not shown).

  The content selection / drawing control (ASCCS) is specified in response to a selection operation by a user (US) browsing the display (CLOD) of the client (CL) or a request automatically issued from the client (CL). The content is extracted from the basic content file (ASBF), and if necessary, the corresponding highlight coordinate list (ASEM) is combined and transmitted to the client (CL). In the case of content that moves interactively according to the operation of the user (US), such as a servlet, rendering is controlled by content selection / drawing control (ASCCS). Also, a process of generating a single image by combining basic content files in accordance with the member configuration of the user (US) who is browsing is performed.

  The timer activation (ASTK) starts the basic content generation (ASCBC) process when the clock (ASCK) reaches a predetermined time.

  The basic content generation (ASCBC) reads the basic content generation program (ASBP), conference information acquired from the data processing server (DS), and sensing data acquired from the sensor network server (SS) or secondary data of the sensing data, To output a basic content file (ASBF). Specifically, a basic content file (ASBF) such as a screen of the network diagram (FIG. 9) is output.

  In this way, by separating the client (CL) in FIG. 2A and the application server (AS) in FIG. 2B, it is not necessary to store personal information or confidential information in the client (CL). Can be placed outside the security area.

  However, the client (CL) and the application server (AS) may be integrated, and the content file and the user attribute list may be held in the client (CL).

  The CPU operates as a functional unit that realizes a predetermined function by operating according to a program of each functional unit. For example, the CPU functions as a basic content generation unit by operating according to the basic content generation program. The same applies to other programs. Furthermore, the CPU also operates as a functional unit that realizes each of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  Information such as programs and tables for realizing each function of the control unit (ASCL) is a storage device, a nonvolatile semiconductor memory, a hard disk drive, a storage device such as an SSD (Solid State Drive), or an IC card, an SD card, a DVD Etc., and can be stored in a computer readable non-transitory data storage medium.

<FIGS. 3A and 3B: Data Processing Server (DS), Measurement PC (MP)>
FIG. 3A shows a block diagram of the data processing server (DS), and FIG. 3B is a block diagram showing a configuration of the measurement PC (MP).

<Data processing server (DS)>
In FIG. 3A, the data processing server (DS) receives the data of the distance sensor (RS) measured by the measurement PC (MP) and the seating chart data of the conference participant generated by the measurement PC (MP). Based on the received data, secondary data on the amount of conference activity and the activity state at the time of the conference is generated. Further, based on a request from the application server (AS), basic conference information and secondary conference activity data are transmitted.

  The data processing server (DS) includes a transmission / reception unit (GSSR), a control unit (DSCO), and a storage unit (DSME).

  The transmission / reception unit (GSSR) controls data transmission / reception with the application server (AS) and the measurement PC (MP).

  The storage unit (GSME) is configured by a data storage device such as a hard disk, and stores at least a conference basic information database (DSDM), a conference activity secondary database (DSKM), a seating chart (DSLT), and a sensing database (DSSD). . Further, the storage unit (DSME) stores a program executed by a CPU (not shown) of the control unit (DSCO).

  The conference basic information database (DSDM) stores basic information about the conference transmitted from the measurement PC (MP), the date and place, and the participants.

  The sensing database (DSSD) is transmitted from the measurement PC (MP), and the sensing information of the distance sensor (RS) controlled via the measurement PC (MP), specifically, the sensing time and the sensing time A pair of point cloud data representing the surface shape of the object is recorded in time series.

  The seating table (DSLT) stores the seat arrangement at the time of the conference generated by the measurement PC (MP) transmitted from the measurement PC (MP). The seating chart (DSLT) is data that specifies who is sitting at which position in the meeting, and further, the activity status of the participant by associating the name with the amount of activity. Used for output.

  The conference activity secondary database (DSKM) is information generated by the data processing server (DS). The conference activity secondary database (DSKM) is based on the amount of activity of each participant at the time of the conference and the amount of activity of each participant in the combination of all conference participants generated based on the amount of activity of each participant. Stores data representing meeting time.

  Data reception (DSRV) receives data from the measurement PC (MP).

  The conference activity amount calculation (DSAC) calculates the activity amount of each participant for each hour based on the sensing data (DSSD) and the seating chart (DSLR). Details of the process of calculating the amount of activity will be described with reference to FIG.

  In meeting face-to-face secondary data generation (DSMM), the time corresponding to each other's activity amount is calculated and stored in a matrix format in all combinations of the conference participants based on the activity of each participant's time amount. Details of the meeting-facing secondary data generation will be described with reference to FIG.

  The conference information search (DSDS) is performed according to a request from the application server (AS), specifically, conference information on a specified date, specifically, conference basic information in the conference basic information database (DSDM), or conference activity secondary database ( DSKM) conference activity secondary data is retrieved and transmitted to the application server (AS) via the transceiver.

  The CPU of the data processing server (DS) is similar to the CPU of the application server (AS), and the CPU operates as a function unit that realizes a predetermined function by operating according to the program of each function unit. For example, the CPU functions as a conference activity amount calculator by operating according to the conference activity amount calculation program. The same applies to other programs. Furthermore, the CPU also operates as a functional unit that realizes each of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  Information such as programs and tables for realizing each function of the control unit (DSCO) is a storage device, a nonvolatile semiconductor memory, a hard disk drive, a storage device such as an SSD (Solid State Drive), or an IC card, an SD card, a DVD Etc., and can be stored in a computer readable non-transitory data storage medium.

<Measurement PC (MP)>
In FIG. 3B, the measurement PC (MP) controls the distance sensor (RS) and the sensor terminal wearer detector (ISD) to receive measurement data, and based on the received data, , Generate meeting basic information that stores the meeting date and time, place, participants, etc., and send sensing data, seating charts, and meeting basic data measured by the distance sensor (RS) via the transmission / reception unit to the data processing server ( DS). The measurement PC (MP) includes a transmission / reception unit (MPSR), a control unit (MPCO), and a storage unit (MPME).

  The transceiver unit (MPSR) controls data transmission / reception with the data processing server (DS), distance sensor (RS), and sensor terminal wearer detector (ISD).

  The storage unit (MPME) is configured by a data storage device such as a hard disk, and stores at least a conference basic information database (MPDM), a seating chart (MPLT), a sensing database (MPSD), and a detection ID database (MPDT). Further, the storage unit (MPME) stores a program executed by a CPU (not shown) of the control unit (MPCO).

  The meeting basic information (MPDM) stores the date and place of the meeting, the location, participants, and the like. In the seating chart data (MPLT), names and affiliations of participants in the conference, seat coordinate values at the time of the conference, and the like are stored.

  In the sensing database (MPSD), information measured by the distance sensor (RS), specifically, the time of sensing and point cloud data representing the surface shape of the object at the sensing time are paired in time series. Records are stored. As a result, it is possible to leave a log of the movements of the participants in the room in the conference.

  In the detection ID database (MPDT), the terminal IDs of the sensor terminals (TR) detected by the sensor terminal wearer detector (ISD) are stored in time series. It is used to estimate the position of the sensor terminal wearer from the position and orientation of the sensor terminal wearer detector (ISD) and the detected terminal ID.

  The control unit (MPCO) includes data transmission (MPSDD), conference basic information generation (MPDM), seating chart generation (MPSC), distance sensor control (MPRS), and detector control (MPISD).

  In the detector control (MPISD), a measurement request can be issued to the wearer detector (ISD), or the measured data can be received and stored in the detection ID database (MPDT).

  In the distance sensor control (MPRS), a measurement request can be issued to the distance sensor (RS), or the measured data can be received and stored in the sensing database (MPSD).

  In the seating chart generation (MPSC), a seating chart based on the sensing data is generated, and the seating position of the sensor terminal wearer is specified based on the detection ID database (MPDT). In addition, display the seat layout on the display (MPOD) of the input / output unit (MPIO), or enter information of visitors from outside the company using the mouse (MPIM) or keyboard (MOIK) with reference to the seat layout Can do.

  In the basic conference information generation (MPDM), the date and time of the conference, the place, and the data of the participants are generated.

  In data transmission, conference basic information (MPDM), seating chart data (MPLT), and sensing data (MPSD) are transmitted to the data processing server (DS).

  The CPU (not shown) of the measurement PC (MP) is similar to the CPU of the application server (AS), and the CPU operates as a functional unit that realizes a predetermined function by operating according to the program of each functional unit. For example, the CPU functions as a distance sensor control unit by operating according to the distance sensor control program. The same applies to other programs. Furthermore, the CPU also operates as a functional unit that realizes each of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  Information such as programs and tables for realizing each function of the control unit (MPCO) is a storage device, a nonvolatile semiconductor memory, a hard disk drive, a storage device such as an SSD (Solid State Drive), an IC card, an SD card, a DVD Etc., and can be stored in a computer readable non-transitory data storage medium.

<Sensor network server (SS) base station (GW)>
4A and 4B are block diagrams illustrating configuration examples of the sensor network server (SS) and the base station (GW).

<Sensor network server (SS)>
In FIG. 4A, the sensor network server (SS) manages data collected from all sensor terminals (TR). Specifically, the sensor network server (SS) stores the sensing data sent via the base station (GW) in the sensing database (SSDB). The sensor network server (SS) transmits sensing data or secondary data based on a request from the application server (AS) or the client (CL). Furthermore, the sensor network server (SS) manages information on the base station (GW) and the sensor terminals (TR) under the control of the base station (GW) as needed.

  The sensor network server (SS) includes a transmission / reception unit (SSSR), a storage unit (SSME), and a control unit (SSCO).

  The transmission / reception unit (SSSR) controls data transmission and reception with the base station (GW) and the application server (AS).

  The storage unit (SSME) is configured by a data storage device such as a hard disk, and stores at least a sensing database (SSDB), a secondary database (SSDT), and data format information (SSMF). Furthermore, the storage unit (SSME) stores a program executed by a CPU (not shown) of the control unit (SSCO).

  The sensing database (SSDB) is a base station (GW) through which sensing data acquired by each sensor terminal (TR), information on the sensor terminal (TR), and sensing data transmitted from each sensor terminal (TR) has passed. It is a database for recording such information. A column is generated for each data element such as acceleration, and the data is managed. A table may be generated for each data element. In either case, all data is managed in association with terminal information (TRMT) (FIG. 4), which is the ID of the sensor terminal (TR) that acquired the data, and information regarding the sensed time.

  The secondary database (SSDT) is a database that stores the result of sensing data processing (SSCDT) on data in the sensing database (SSDB). The secondary data stored in the secondary database (SSDT) is data that can specify the physical face-to-face state between users (US), that is, employees in the company, standardized by predetermined preprocessing. . In this secondary data, noise is removed from the sensing data, and a format suitable for generating basic content, for example, the total face-to-face time between any two users (US) per day is expressed in a matrix format. Stored in things, etc.

  Data format information (SSMF) includes a data format for communication, a method of separating sensing data tagged with a base station (GW) and recording it in a database, and secondary data subjected to sensing data processing (SSCDT). Information indicating a method of recording in the next database (SSDT) and a method of responding to the request for data are recorded. The sensor network server (SS) refers to this data format information (SSMF) after data reception or before data transmission, and performs data format conversion and data distribution.

  The control unit (SSCO) includes a CPU (not shown) and controls transmission / reception of sensing data and recording / retrieving to / from a database. Specifically, the CPU executes a program stored in the storage unit (SSME) to execute processing such as sensing data storage (SSCDB), sensing data processing (SSCDT), and secondary data search (SSCTS). .

  Sensing data storage (SSCDB) is processing for receiving sensing data sent from a base station (GW) and storing it in a sensing database (SSDB). Additional information such as time information, terminal ID, and time via the base station is combined and stored in the database as one record.

  The clock (SSCK) maintains a standard time by periodically connecting to the external NTP server (TS). When the clock (SSCK) satisfies a predetermined time or a specific condition, the sensing data processing (SSCDT) is activated (SSTK).

  Sensing data processing (SSCDT) pre-processes sensing data from the sensing database (SSDB), that is, data acquired by the sensor terminal (TR) by the method specified by the data format information (SSMF), and generates secondary data To do.

  The generated secondary data is stored in a secondary database (SSDT). By starting sensing data processing (SSCDT) at regular intervals and processing newly added sensing data, the secondary database (SSDT) is always kept updated.

  In the secondary data search (SSCTS), when a request is received from the application server (AS), secondary data corresponding to the request is extracted from the secondary database (SSDT) and transmitted to the request source. In this process, secondary data is searched based on tag information such as date and terminal ID given to the secondary data.

  The CPU of the sensor network server (SS) is similar to the CPU of the application server (AS), and the CPU operates as a functional unit that realizes a predetermined function by operating according to the program of each functional unit. For example, the CPU functions as a sensing data processing unit by operating according to a sensing data processing program. The same applies to other programs. Furthermore, the CPU also operates as a functional unit that realizes each of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  Information such as a program and a table for realizing each function of the control unit (SSCO) is a storage device, a nonvolatile semiconductor memory, a hard disk drive, a storage device such as an SSD (Solid State Drive), an IC card, an SD card, a DVD Etc., and can be stored in a computer readable non-transitory data storage medium.

<Base station (GW)>
In FIG. 4B, the base station (GW) has a role of mediating between the sensor terminal (TR) and the sensor network server (SS). When the sensor terminal (TR) and the base station (GW) are wirelessly connected, a plurality of base stations (GWs) are provided so as to cover areas such as living rooms and workplaces in consideration of the wireless reachable distance. Be placed. In the case of wired connection, an upper limit of the number of sensor terminals (TR) to be managed is set in accordance with the processing capability of the base station (GW).

  The base station (GW) includes a transmission / reception unit (GWSR), a storage unit (GWME), and a control unit (GWCO).

  The transmission / reception unit (GWSR) receives data from the sensor terminal (TR) wirelessly or by wire, and performs wired or wireless transmission to the sensor network server (SS). When wireless is used for transmission / reception, the transmission / reception unit (GWSR) includes an antenna for performing wireless communication.

  The storage unit (GWME) is configured by an external recording device (not shown) such as a hard disk, a memory, or an SD memory card. The storage unit (GWME) stores data format information (GWMF), base station information (GWMG), and the like. The data format information (GWMF) includes information indicating a data format for communication and information necessary for tagging the sensing data. The base station information (GWMG) includes information such as the address of the base station (GW) itself.

  The storage unit (GWME) may further store a program executed by a CPU (not shown) of the control unit (GWCO).

  The control unit (GWCO) includes a CPU (not shown). When the CPU executes a program stored in the storage unit (GWME), the timing at which sensing data is received from the sensor terminal (TR), the processing of the sensing data, to the sensor terminal (TR) or the sensor network server (SS) The transmission / reception timing and the time synchronization timing are managed. Specifically, processes such as sensing data reception control (GWCSR), sensing data transmission (GWCSS), and time synchronization (GWCS) are executed.

  The clock (GWCK) holds time information. The time information is updated at regular intervals. That is, the time information of the clock (GWCK) is corrected by the time information acquired from the NTP server (TS) at regular intervals.

  Time synchronization (GWCS) transmits time information to a subordinate sensor terminal (TR) at a fixed interval or triggered by the sensor terminal (TR) being connected to a base station (GW). Thereby, the time of the clock (GWCK) of the plurality of sensor terminals (TR) and the base station (GW) is synchronized.

  The sensing data reception control (GWCSR) receives a packet of sensing data (SENSD) sent from the sensor terminal (TR). In the sensing data reception control (GWCSR), it is possible to read the header of the data packet, determine the type of data, and perform congestion control so that data is not concentrated and transmitted simultaneously from many sensor terminals (TR). .

  In the sensing data transmission (GWCSS), the ID of the base station through which the data has passed and the time data through which the data has passed are assigned, and the sensing data is transmitted to the sensor network server (SS).

<Sensor terminal (TR)>
5A and 5B show the configuration of a sensor terminal (TR) which is an embodiment of the sensor node. In this embodiment, as shown in FIG. 1, the sensor terminal (TR) has a name tag type shape and is assumed to hang from a person's neck, but this is an example, and other shapes are also possible. Good.

  In many cases, a plurality of sensor terminals (TR) exist in the system described in the present embodiment, and a person belonging to an organization (in this embodiment, a user (US) who is an in-house employee) Is equivalent to this). The sensor terminal (TR) includes various infrared transmission / reception units (AB) for detecting the face-to-face situation between humans (users (US)), a triaxial acceleration sensor (AC) for detecting a wearer's movement, and the like. Mount the sensor. The mounted sensor is an example, and other sensors may be used to detect the face-to-face situation and movement between wearers.

  In this embodiment, four sets of infrared transmission / reception units (AB) are provided. The infrared transmission / reception unit (AB) continues to periodically transmit terminal information (TRMT), which is unique identification information of the sensor terminal (TR), in the front direction of the sensor terminal (TR). When a person wearing another sensor terminal (TR) is positioned substantially in front (for example, front or diagonally front), the sensor terminal (TR) and the other sensor terminal (TR) have their respective terminal information (TRMT). Communicate with each other via infrared. By acquiring this terminal information (TRMT), it is possible to record who and who are facing each other.

  In addition, the viewer detector (CLVD) provided in the client (CL) receives this terminal information (TRMT), which user (US) is browsing the display (CLOD) of the client (CL). Can be detected. Conversely, the user (US) stayed at the installation location of the client (CL) when the sensor terminal (TR) received the detector ID (CLVDID) transmitted from the viewer detector (CLVD). Can be recorded.

  Sensing data (SENSD) detected by the various sensors described above is stored in the storage unit (STRG) by the sensing data storage control unit (SDCNT). The sensing data (SENSD) is processed into a transmission packet by the communication control unit (TRCC) and transmitted to the base station (GW) by the transmission / reception unit (TRSR).

  The triaxial acceleration sensor (AC) detects the acceleration of the node, that is, the movement of the sensor terminal (TR). That is, from the acceleration data obtained from the triaxial acceleration sensor (AC), it is possible to analyze the intensity of movement of a person wearing the sensor terminal (TR) and behavior such as walking. Further, by comparing the acceleration values detected by the plurality of sensor terminals (TR) in, for example, time series, the activity (activity) of communication between the persons wearing the sensor terminals (TR) and mutual movements. The rhythm of each other, the correlation of the mutual movement, etc. can be analyzed.

  In this embodiment, in the sensor terminal (TR), the data acquired by the triaxial acceleration sensor (AC) is stored in the storage unit (STRG) by the sensing data storage control unit (SDCNT), and at the same time, the vertical detection circuit (UDDET) detects the vertical direction of the name tag. This is because two types of acceleration detected by the three-axis acceleration sensor (AC) are observed: a dynamic acceleration change due to the wearer's movement and a static acceleration due to the gravitational acceleration of the earth. Yes.

  When the terminal (TR) is worn on the chest, the display device (LCDD) displays personal information such as the affiliation and name of the wearer. In other words, it behaves as a name tag.

  Whether the sensor terminal (TR) has faced another sensor terminal (TR) by transmitting / receiving infrared rays to / from the other sensor terminal (TR), that is, the sensor terminal ( It is detected whether or not the person wearing TR) faces a person wearing another sensor terminal (TR). For this reason, it is desirable that the sensor terminal (TR) be mounted on the front part of a person.

  As described above, the sensor terminal (TR) includes a sensor such as a triaxial acceleration sensor (AC). The sensing process in the sensor terminal (TR) corresponds to the sensing (TRSS1) process in FIGS. 5A and 5B.

  The storage unit (STRG) is specifically composed of a nonvolatile storage device such as a hard disk or a flash memory, and includes terminal information (TRMT) that is a unique identification number of the sensor terminal (TR), a sensing interval, and a display. Operation settings (TRMA) that define operations such as output contents are recorded. In addition, the storage unit (STRG) can temporarily record data and is used to record sensed data.

  The clock (TRCK) is a clock that holds time information (GWCSD) and updates the time information (GWCSD) at regular intervals. In order to prevent the time information (GWCSD) from deviating from that of other sensor terminals (TR), the time information is periodically corrected based on the time information (GWCSD) transmitted from the base station (GW).

  The sensing data storage control unit (SDCNT) controls the sensing interval of each sensor according to the operation setting (TRMA) recorded in the storage unit (STRG) and manages the acquired data.

  The communication control unit (TRCC) performs transmission interval control and conversion to a data format compatible with wireless transmission and reception when transmitting and receiving data.

  The transmission / reception unit (TRSR) includes an antenna and transmits and receives radio signals.

<Conference meeting secondary data generation sequence>
FIG. 6 is a sequence diagram showing a procedure for generating conference-facing secondary data representing the activity status of each participant during a conference, which is executed in the embodiment of the present invention. In FIG. 6, processes executed in each of the sensor terminal wearer detector (ISD), the distance sensor (RS), the measurement PC (MP), and the data processing server (DS) are shown in time series.

  In the measurement PC (MP) installed in the conference room, a conference measurement application (not shown) is activated, and an operation meaning a conference start (MPST) is performed, for example, a conference start button is pressed by a mouse (MPIM) operation. Then, it connects with the NPT server (TS) and performs time correction (MPCS). By correcting the time, the time at the time of data measurement can be recorded correctly, and even when the physical movements of multiple participants performed at the same time are acquired by multiple measurement devices, the time information is illuminated. By combining them, it is possible to extract data at the same timing. Note that the conference measurement application includes the clock (MPCK), distance sensor control (MPRS), detector control (MPISD), conference basic information generation (MPDM), and seating chart generation (MPSC) processing shown in FIG. 3B. Software.

  The measurement PC (MP) transmits a measurement (MPRQ) request to the two sensors after correcting the time. The first is a sensor terminal wearer detector (ISD). The sensor terminal wearer detector (ISD) receives infrared rays transmitted by the sensor terminal (TR) worn by a part of the conference participants by sensing (ISDSS), and is specific to the sensor terminal (TR). Get the terminal ID.

  The ID detected by the sensor terminal wearer detector (ISD) is transmitted to the measurement PC (MC) by data transmission (ISDSE) and stored along with the time. By using the directivity of the sensor terminal wearer detector (ISD) and installing a plurality of sensor terminal wearer detectors (ISD) in different directions, which sensor terminal wearer detector (ISD) It is possible to estimate the approximate position of the sensor terminal (TR) depending on which sensor terminal (TR) ID is acquired.

  The second sensor is a distance sensor (RS). The distance sensor (RS) is a device that measures the distance to an obstacle surface such as a person or a wall by sensing (RSSS). The measurement PC (MC) can grasp the three-dimensional shape in the conference room by scanning the conference room in three dimensions with a distance sensor (RS) installed at a known position. Then, the measurement PC (MC) is obtained from the depth image measured from the measurement position (X, Y, Z), the measurement direction (α, β, γ), and the position and direction of the distance sensor (RS). The coordinate value of one point can be calculated.

  Such a collection of coordinate values in space is called a point group, and coordinate values are stored as a point group. When generating point cloud data, measure data in each direction using one or more distance sensors (RS), and integrate the data with a measurement PC (MP) to generate 360 degree omnidirectional point cloud data To do. An example of the data structure is shown in FIG.

  FIG. 23 shows an example of sensing data (RSSD) held in the sensor network server (SS). Sensing data (RSSD) is one entry from a sensing time (SSTM) at which distance data is measured and a point cloud coordinate value (PCCV) that stores the coordinates in the three-dimensional space at the sensing time as point cloud data. Is configured.

  The sensed distance data is transmitted to the measurement PC (MC) by data transmission (RSSE) and stored together with the time.

  In the measurement PC (MP), detection ID data from the sensor terminal wearer detector (ISD) and sensing data sent from the distance sensor (RS), which are transmitted in chronological order, are sequentially stored along with the time. I will do it.

  The sensing data of the distance sensor (RS) is used to acquire the activity data of the conference participants during the conference time, but in order to grasp who was moving in what time and how, It is necessary to grasp the seat arrangement.

  There are desks and chairs in the conference room, but the chairs are not fixed and can be moved, so a seating chart based on the actual layout is required. For this reason, after starting the conference, the measurement PC (MP) first generates a seating chart.

  When a command indicating seating chart generation is received (MPSCQ), for example, a seating chart generation button is pressed by operating the mouse (MPIM) of the measurement PC (MP), etc., sensing currently transmitted from the distance sensor (RS) Based on the data, a seating chart generation (MPSC) that identifies the arrangement of participants is performed. The user of the measurement PC (MP) carries out the work of associating the affiliation and name of the conference participant semi-automatically. Details will be described later with reference to FIGS. 10A and 10B.

  The measurement (MPRQ) request transmitted from the measurement PC (MP) is continued until an operation indicating a conference end (MPMF) is performed, such as pressing a conference end button by operating a mouse (MPIM) or the like. The measurement PC (MP) continues to receive data from the sensor terminal wearer detector (ISD) and the distance sensor (RS). During the seating chart generation (MPSC) work, the data measurement request and the measurement data are continuously received.

  Next, after the conference ends (MPMF), the measurement PC (MP) generates conference basic data (MPDM). FIG. 11 shows an example of conference basic data (MPDM). The basic conference data (MPDM) includes the conference date (MPDM1), conference start time (MPDM2), conference end time (MPDM3), conference location (MPDM4), affiliation of conference participants (MPDM5), It is assumed that the name of the conference participant (MPDM6) is stored.

  The date of the time data after the time correction received from the NPT server is stored in the conference date (MPDM1). The conference start time (MPDM2) stores the time at which an operation meaning the start of the conference occurs, for example, the conference start button is pressed by operating the mouse (MPIM). The conference end time (MPDM3) stores the time when an operation that means the end of the conference occurs, such as when the conference end button is pressed. The meeting place name (MPDM4) stores the name of the meeting room. If the measurement PC (MP) installed in each meeting room is associated with the meeting room name in advance, it depends on the used measurement PC (MP). The meeting room name is uniquely determined. The names of conference participants belonging (MPDM5) and participants (MPDM6) store the names and names of the conference participants input at the time of seating chart generation (MPSC).

  When the generation of the conference basic data (MPDM) is completed, the sensing data acquired by the distance sensor (RS), the seating chart generated by the seating chart generation (MPSC), and the meeting basic data (MPDM) generated by the meeting basic data (MPDM) ) To the data processing server (DS).

  When the data processing server (DS) receives the data transmitted from the measurement PC (MP), it transmits a reception completion response to the measurement PC (MP).

  First, the data processing server (DS) extracts the head movement data of the person who participated in the conference based on the sensor data acquired by the distance sensor (RS) in the conference activity amount calculation (DSAC) and participates in the conference. The amount of activity in a time-series meeting (conference activity amount) is calculated for the person. Details of the calculation of the conference activity amount will be described later with reference to FIG.

  In the meeting face-to-face secondary data generation (DSMM) performed by the data processing server (DS), the activity is calculated from the amount of conference activities of the conference participants in time series. Or a time when the activity is high only for the other party is calculated for each combination of all the conference participants and output as matrix data. Details will be described later with reference to FIG.

<Data storage sequence of sensor terminal (TR)>
FIG. 7 is a sequence diagram showing a procedure for storing sensing data acquired by the sensor terminal (TR) in the sensor network server (SS), which is executed in the embodiment of the present invention. In FIG. 7, processes executed in each of the sensor terminal (TR), the base station (GW), and the sensor network server (SS) are shown in time series.

  When the sensor terminal (TR) becomes ready for communication with one base station (GW) (TRTA1), the sensor terminal (TR) performs time synchronization (TRCS). In time synchronization (TRCS), the sensor terminal (TR) transmits a request for time synchronization to the base station (GW), receives time information from the base station (GW), and receives a clock (TRCK) in the sensor terminal (TR). ) Is set. The base station (GW) periodically connects to the NTP server (TS) and corrects the time.

  Various sensors such as the three-axis acceleration sensor (AC) of the sensor terminal (TR) are activated (TRST) by a timer interrupt at a constant cycle, for example, every 10 seconds, and sense acceleration or the like (TRSS1). The sensor terminal (TR) detects the facing state by transmitting / receiving a sensor terminal ID, which is one of terminal information (TRMT), to / from another sensor terminal (TR) using infrared rays.

  The sensor terminal (TR) attaches time information of the clock (TRCK) and terminal information (TRMT) to the sensed data (TRCT1). When analyzing data, the terminal information (TRMT) identifies the person wearing the sensor terminal (TR).

  In the data format conversion (TRDF1), the sensor terminal (TR) attaches tag information such as sensing conditions to the sensing data, and converts it into a preset wireless transmission format. This format is stored in common with the data format information (GWMF) in the base station (GW) and the data format information (SSMF) in the sensor network server (SS). The converted data is then transmitted to the base station (GW).

  Data transmission (TRSE1) transmits data to the base station (GW) through the transmission / reception unit (TRSR) in accordance with a wireless communication standard.

  When the base station (GW) receives the sensing data from the sensor terminal (TR) (GWRE), the base station (GW) transmits a reception completion response to the sensor terminal (TR). The sensor terminal (TR) that has received the response determines that transmission is complete (TRSO).

  Furthermore, the base station (GW) gives the base station information (GWMG), which is a number unique to the base station, to the sensing data (GWGT), and sends the sensing data to the sensor network server (SS) via the network (NW). (GWSE). The base station information (GWMG) can be used in data analysis as information indicating the approximate position of the sensor terminal (TR) at the transmission time.

  When the sensor network server (SS) receives data from the base station (GW) (SSRE), the sensor network server (SS) classifies the received data for each element such as time, terminal information, acceleration, and infrared rays (SSPB). This classification is performed by referring to a format recorded as data format information (SSMF). The classified data is stored in the appropriate column (row) of the record (row) of the sensing database (SSDB) (SSKI). By storing data corresponding to the same time in the same record, a search based on time and terminal information (TRMT) becomes possible. At this time, if necessary, a table may be generated for each terminal information (TRMT). This data reception (SSRE), data classification (SSPB), and data storage (SSKI) are performed in the sensing data storage (SSCDB) in FIG.

  If the sensor terminal (TR) cannot receive a reception completion response within a predetermined time after transmitting the sensing data to the base station (GW), sensing is performed in the storage unit (STRG) of the sensor terminal (TR). Retain data (TRDM). And it waits until a sensor terminal (TR) becomes communicable with a base station (GW) (TRTA2). During this period, the above-described timer activation (TRST) to terminal information / time attachment (TRCT1) are executed at predetermined intervals, and the sensing data is accumulated in the storage unit (STRG).

  When the sensor terminal (TR) becomes communicable with the base station (GW), the sensing data is converted in the same manner as described above (TRDF2), and then the data is divided (TRBD2). Transmit to the station (GW).

<Basic Content Generation (ASCBC) Sequence>
FIG. 8 shows a sequence of basic content generation (ASCBC) processing executed in the application server (AS) of FIG.

  In the application server (AS), the basic content generation program (ASBP) is activated (ASTK) when the clock (ASCK) reaches a predetermined time. Alternatively, the basic content generation program (ASBP) is activated (ASTK) when a user (US) having administrator authority of the application server (AS) operates at an arbitrary timing.

  As shown by the control unit (ASCO) in FIG. 2B, the basic content generation program may include a plurality of types of programs, and output a plurality of types of basic content files (ASBF) corresponding thereto. Alternatively, the order of starting individual programs may be specified, and the output basic content file (ASBF) may be read to generate another basic content file (ASBF).

  Here, there is one type of basic content, and the basic content is generated based on sensing data. This basic content is especially generated based on both in-person data and conference data between employees in the company, and the basic content is in-person between internal employees and outside visitors and employees. It visualizes the activity state of time.

  The application server (AS) sends a data request to the sensor network server (SS) and the data processing server (DS) by specifying the target period and target user for the necessary data stored in the basic content generation program (ASBP). Transmit (ASCBC1). It is assumed that the secondary data acquired from the sensor network server (SS) includes a face-to-face activity matrix (ASMM) indicating the amount of communication including the activity state within a period between any employee in the company. Further, the face-to-face activity matrix (ASMM) includes a bidirectional face-to-face activity matrix (ASMM1) generated in accordance with both activity states and a bidirectional face-to-face activity matrix (ASMM1), as will be described later. Furthermore, it is assumed that acceleration data representing the degree of activity at the conference time acquired by the sensor terminal (TR) of the user who participated in the conference held during the target period is also included. The acquired acceleration data is used when correcting the activity amount acquired by the sensor terminal (TR) and the conference activity amount calculated from the distance sensor (RS).

  In addition, the conference data acquired from the data processing server (DS) includes basic information in the conference basic information database DSDM in which the date, place, and participants of the conference are stored, and a conference indicating the degree of activity among employees at the conference. A conference activity secondary database DSKM including an activity matrix. It should be noted that the conference activity matrix includes a conference two-way activity matrix (DSKM1) and a conference one-side activity matrix (DSKM2).

  Based on the request received from the application server (AS), the sensor network server (SS) searches the secondary database (SSDT) (SSCTS) and transmits necessary data to the application server (AS). Similarly, the data processing server (DS) performs conference data search (DSCTS) based on the request and transmits the conference information to the application server (AS).

  The application server (AS) receives the secondary data and information retrieved above. The sensor terminal secondary data is read based on the data format using the sensor terminal secondary data reading program (ASPR) (ASCBC3). Similarly, the conference basic data (MPDM) is also read using the conference data reading program (ASGR) based on the data format (ASCBC4).

  Extract information (name, company name, etc.) of external meeting partners who participated in the meeting from the meeting basic data (MPDM), and information on the person (face name, company name, etc.) that has been held in business in advance. ) Is stored and the external meeting list is updated (ASCLU).

  Bi-directional face-to-face activity matrix (ASMM1) shown according to both activity states within a period between arbitrary members in the company, which is one of the sensor terminal secondary data acquired from the sensor network server (SS) Then, the one-way meeting activity matrix (ASMM2) is expanded, and the amount of communication with the external party is stored in the corresponding cell, thereby generating a business meeting matrix (ASCMC). When adding the amount of communication with outside parties, the secondary data for meeting is corrected. A correction value is calculated from the activity amount acquired by the sensor terminal (TR) of the sensor terminal wearer at the conference time and the conference activity amount calculated from the distance sensor (RS), and the correction value for the conference-facing secondary data The value is changed according to (ASCCC).

  A business meeting matrix (ASGM) generated from the secondary data and business information is drawn in a form that is easy for the viewer to understand (ASCBC5). An image file of the drawn content is output (ASCBC6) and stored as a basic content file (ASBF) in the storage unit (ASME). In addition, an access control rule (ASAC) is output together (ASCBC6), and a terminal ID that can view the image file generated by this processing is specified in the form of a logical expression or the like.

<Content display sequence>
FIG. 9A and FIG. 9B are sequence diagrams showing a procedure when displaying contents, mainly images, executed in the embodiment of the present invention. FIG. 9A shows processes executed by the application server (AS), the client (CL), and the sensor terminal (TR) together with operations performed by the user (US).

  The client (CL) usually displays (CLD1) open content (for example, a network diagram or a message board that does not display personal names) that can be viewed by anyone on the display (CLOD). The browser detector (CLVD) is always in a standby state, and performs browser determination (CLCVD). When the client (CL) determines that there is no viewer, the open content is continuously displayed (CLD1).

  When the terminal ID (CLD2) transmitted from the sensor terminal (TR) is received and it is determined that there is a viewer, the client (CL) generates a viewer ID list (CLD3). Then, the client (CL) sends the viewer ID list to the application server (AS), and requests a list of contents that can be browsed by the current viewer member configuration (CLCLR).

  The application server (AS) inquires the content list (ASCL) and the access control rule (ASAC), extracts a list of contents that can be browsed by the member configuration of the viewer, and responds to the client (CL) (ASCLM).

  The application server (AS) also queries the user attribute list (ASUL) and transmits the name of the viewer to the client (CL). Based on the content list, the client (CL) displays a content switching button (OD_C) indicating a link to the browseable content and a viewer selection button (OD_A) indicating the name of the viewer (CLD4). These content switching buttons (OD_C) and viewer selection buttons (OD_A) are shown in FIG.

When the operation of the user (US) is detected, the client (CL) requests the application server (AS) for an image (or other type of data) of the selected content (CLCCR). The application server (AS) selects the corresponding content according to the requested conditions (target date, target user, content type) and transmits it to the client (ASCCS). The client (CL) displays the content received from the application server (AS) (CLD6).
With respect to the content (CLD6) that is highlighted in the content display (CLD6), the user (US) can change the highlighting by performing the content operation (CLD8) (CLD9). . Further, the system automatically determines the viewer (CLCVD), detects when the viewer changes (CLD10), changes the contents of the highlight display, and draws (CLD11). In addition, when displaying the content, the system determines whether the viewer satisfies the conditions for those that require browsing permission (CLD12), and for viewers who do not have browsing permission, Open content is displayed (CLD13).

<Flow chart of seating chart generation>
FIG. 10A and FIG. 10B show flowcharts of seating chart generation (MPSC) performed by the measurement PC (MP). The seating chart generation (MPSC) is a process performed when an event such as a seating chart generation button is pressed (MPSCQ) by a mouse (MPIM) or the like, and is basically performed once after the start of the conference. .

  After the start of processing (MPSTS), the measurement PC (MP) acquires the seating chart generation time (t) (MPST1). By acquiring the seating chart generation time (t), when the data processing server (DS) later generates a conference activity amount for each person and associates a person area with movement with a person (name) In addition, the association process can be performed using data at the same time.

  The seating chart is generated by extracting a person area based on the data acquired by the distance sensor (RS) and generating a sketch, and by using the data acquired by the sensor terminal wearer detector (ISD). The process is roughly divided into three steps: a process for automatically associating the position with the name, and a process for associating the seat position of the person not wearing the sensor terminal by manual input. In this embodiment, a person area is extracted from the data acquired by the distance sensor (RS) to generate a conference room sketch (MPST21 to MPST25), and acquired by a sensor terminal wearer detector (ISD). The example which performs in parallel the process (MPST31-MPST41) which acquires information of a sensor terminal wearer based on data is shown.

  First, the measurement PC (MP) acquires sensing data at time (t) sensed by the distance sensor (RS). The sensing data is described, for example, as sensing data (RSSD) shown in FIG. 23, and only the data (point cloud coordinate value PCCV) at a certain time (t) is extracted from the sensing data at time (t). Is. A person region is extracted from the acquired sensing data (MPST22).

  As an example of the person area extraction method, first, sensing data by a distance sensor (RS) in a state where there is no person in the conference room is measured in advance and stored as measurement data (SD1) before the conference shown in FIG. . And there exists a method of extracting person area extraction data (SD3) by the difference of the measurement data (SD1) before a meeting start, and the sensing data in measurement data (SD2) after a meeting start.

  After the person area is extracted, a circle having a predetermined radius (for example, 20 cm) is applied to the person area, and a floor plan of the seating table when the conference room is viewed from above is generated (MPST23). As one method of fitting a circle, a method of calculating the center of each XY coordinate value in each person area (CPA1) (CPA2) and applying the circle with the calculated center as the person center (CPA3) is shown in FIG. Shown in However, since the distance sensor (RS) can acquire only the front half surface data of a person, there is a possibility that the distance sensor (RS) slightly deviates from the center of the person. In this example, a distance sensor (RS) is installed at the center of the table, and the distance is measured while rotating.

  As another method, as shown in FIG. 13B, an area up to a height obtained by subtracting a predetermined range (for example, 20 cm) from the maximum Z coordinate value (maximum value in the height direction) of each person area is displayed. A method of extracting a partial area point group (CPB1) and applying a circle having a predetermined radius (for example, 20 cm) to the area by collation processing (CPB2) is also conceivable. The head region point group indicated by CPB1 is a diagram obtained by projecting the acquired point group onto the XY plane and extracting only the surface point group located at a short distance from the distance sensor.

  As another method, as shown in FIG. 13C, using the existing motion extraction algorithm, the shape of the person is extracted from the three-dimensional point cloud data (CPC1), the skeleton is fitted (CPC2), the head There is also a method of extracting the coordinate value of the point recognized as a part as the center of the person area (CPC3).

  As shown in FIG. 13D, the measurement PC (MP) represents the calculated person position in a circle, and the figure displayed together with the conference desk is a seat plan sketch.

  The center of the circle representing the person area is output as a person area center coordinate value (MPCV) (MPST24). The measurement PC (MP) assigns person numbers P1 to Pn to each person area (MPST25). For example, the person numbering is performed by assigning numbers from P1 in the order in which the person center coordinate values are detected in the left-to-right scan (X-axis direction) and the top-to-bottom scan (Y-axis direction). Use the method.

  Next, processing based on data acquired by the sensor terminal wearer detector (ISD) will be described. In order to specify the direction in which the wearer of the sensor terminal (TR) is present, a plurality of sensor terminal wearer detectors (ISD) are installed in each direction. For example, FIG. 15A shows an example in which six sensor wearer detectors (ISD_1 to ISD_6) are installed at different angles by 60 degrees. FIG. 15A is a diagram showing the arrangement and viewing angle of the sensor wearer detector ISD. With such an arrangement, the terminal ID of the sensor terminal (TR) can be received by any of the detectors (ISD_1 to ISD_6) regardless of the direction in which the sensor wearer is present.

  FIG. 15B shows basic information of the sensor wearer detector (ISD), in which a detector ID (ISDDID), an installation position (ISDCV), and an installation direction (ISDDR) are stored in association with each other. As will be described later, this basic information is generated by the measurement PC (MP) at each time.

  First, the measurement PC (MP) acquires ID data detected by the sensor wearer detector (ISD) (MPST31). Here, examples of the detection ID data table (ISDDT) are shown in FIGS. 16A and 16B. FIG. 16A shows a table whose detector ID is “ISD_1”, and FIG. 16B shows a table whose detector ID is “ISD_2”. Each table shows an example in which the conference start time is 14:48:00.

  In the detection ID data table (ISDDT), the detector ID (ISDID), the data acquisition time (ISDTM), and the ID (ISDTR) of the sensor terminal detected at the data acquisition time are stored in one entry. Data from the data acquisition start time, that is, from the conference start time to the time when the seating chart generation button is pressed is stored.

  In each detector, the detection ID for a certain period of time (for example, from 5 minutes before the time when the seating chart generation button is pressed to the time when the seating chart generation is pressed) is counted (MPST32), and a detection ID reception frequency table (ISDDC) is generated. .

  With only the data at the time (t) when the seating chart generation button is pressed, the ID is detected because the sensor terminal (TR) does not face the direction of any wearer detector (ISD) during that time zone. In some cases, the terminal ID is detected more reliably by going back in time, obtaining data for a predetermined period, and counting the number of detections.

  The detection ID reception number table (ISDDC) shown in FIG. 17 includes a detector ID (ISDID), a time (ISDTT) at which the detector terminal (TR) ID reception count is counted by each detector, and a detected sensor terminal ( (TR) The number of receptions for each ID (ISDCT1, ISDCT2). Here, an example is given in which only terminal ID: 1001 and ID: 1002 are detected. However, when there are more detection IDs, a column of a detection ID reception frequency table (ISDDC) is sequentially added, and detector ID ( The count number for each (ISDID) is stored. In addition, in the example of FIG. 17, the example which produced | generated the detection ID reception frequency table (ISDDC) at 14:50:00 is shown.

  Next, the measurement PC (MP) estimates at which position of the seating chart generated based on the data acquired by the distance sensor (RS) the sensor wearer.

  First, in order to know the measurement position and direction of the detector ID (ISDID), basic information of the sensor terminal wearer detector (ISD) is read (MPST41). As shown in FIG. 15B, the basic information of the sensor terminal wearer detector (ISD) includes the ID (ISDID) of the sensor terminal wearer detector (ISD), the XY coordinate value (ISDCV) of the installation position, the installation direction ( ISDDR) are stored in association with each other.

  FIG. 18 is a diagram in which the two-dimensional seating chart generated from the data acquired by the distance sensor (RS), the arrangement of the sensor terminal wearer detector (ISD), and the viewing angle are superimposed and displayed. If the coordinate system of the distance sensor (RS) and the sensor terminal wearer detector (ISD) is set to the center of the desk as the origin and the X-axis and Y-axis directions are the same, there is no need for coordinate system conversion processing. Coordinate values can be handled as they are.

  Based on the two-dimensional seating table to which the person number is assigned in MPST 25 in FIG. 10A, the sensor terminal wearer detector basic information read in MPST 41, and the detection ID data count table for each detector generated in MPST 32 The position of the person is estimated (MPST42). Since many terminal (TR) IDs 1001 and 1002 are detected in the sensor terminal wearer detector (ISD) of the detector ID (ISD_2) in the detection ID reception frequency table (ISDDC), it is shown in FIG. The person numbers P2 and P3 within the viewing angle of the detector ID (ISD_2) are estimated to have terminal (TR) IDs of 1001 or 1002. Furthermore, the sensor terminal (TR) ID 1001 is detected in the sensor terminal wearer detector (ISD) with the detector ID (ISD_1), and the sensor terminal wearer detector (ISD) with the detector ID (ISD_3) detects the sensor. Since ID = 1002 of the terminal (TR) is detected, it is estimated that the person number P2 is ID = 1001 of the sensor terminal (TR) and the person number P3 is ID1002 of the sensor terminal (TR).

  In order to obtain the name of the employee wearing the terminal (TR) from the detected ID of the sensor terminal (TR), a user list (MPUL) in which the terminal ID and the user name shown in FIG. 19 are associated with each other. And the name of the sensor terminal wearer is acquired (MPST43).

  The seat layout diagram (MPSC) at time (t), which is displayed with the name of the sensor terminal wearer superimposed on the seat layout map, is displayed on the display of the measurement PC (MP) (MPST51).

  FIG. 20A is an example in which the name of the sensor terminal wearer is displayed superimposed on the two-dimensional seating chart, and FIG. 20B extracts the person area from the data acquired by the distance sensor (RS), and together with the conference desk This is an example in which the name of the sensor terminal wearer is superimposed on the displayed three-dimensional point cloud data.

  In order to associate the person area stored in the seating chart with the name of the person seated there, the person area is designated using a pointing device such as a mouse (MPST52). When the person area is designated, an information input box (IIBX) as shown in FIG. 20C is displayed (MPST 53). Examples of contents to be entered in the information input box (IIBX) include a company name and a name. In addition, there may be items for inputting a department or a title.

  When the conference participant information is input to the information input box (IIBX) (MPST54), the determination button is pressed. FIG. 20D is a seat layout diagram in which information of three conference participants (sensor terminal non-wearers) has been input. Changing the color of the box that displays the affiliation and name of the sensor terminal wearer (employee) and non-sensor terminal wearer (visitor) or changing the line style of the box makes it easier to distinguish between the two .

  Here, although the method (FIG. 20C) which inputs the information of a conference participant using the two-dimensional seating chart 20A is shown, a person area on the three-dimensional seating chart (FIG. 20B) is designated and information is stored in the area. An input box may be displayed.

  The conference participant information is repeatedly input to all the person areas, and all the inputs are completed (MPST55). When the input end button is pressed, the conference participant seating chart (MPLT) is output (MPST6).

  As shown in FIG. 21, the conference participant seat chart (MPLT) includes a person number (MPLT1), an X coordinate value (MPLT2) and a Y coordinate value (MPLT3) of the center of the person area, and a seat chart generation time (MPLT4). The sensor terminal ID (MPLT5) of the sensor wearer, the company name (MPLT6) of the visitor, and the name (MPLT7) are stored.

  As described above, in the measurement PC (MP), it is possible to set the arrangement and names of persons in the meeting using the distance sensor (RS) and the sensor terminal wearer detector ISD. That is, the measurement PC (MP) generates a sketch that indicates the arrangement of the person by specifying the position of the person from the data of the distance sensor (RS). On the other hand, measurement PC (MP) detects the position for every sensor terminal (TR) with a sensor terminal wearer detector (ISD), and specifies the position for every sensor terminal (TR) by this detection result. Then, in the measurement PC (MP), the employee wearing the sensor terminal (TR) and the sensor terminal are attached by combining the sketch showing the arrangement of the person and the position specified for each sensor terminal (TR). It is possible to generate a seating chart that matches visitors who have not visited (MPST6). For a person (employee) wearing the sensor terminal (TR), a user name is acquired from the terminal ID with reference to a preset user list (MPUL). The position of the person who is not wearing the sensor terminal (TR) is specified on the display (MPOD), and the names of all persons who participated in the conference can be specified by prompting the input of the name and company name.

<Flowchart for calculating conference activity>
FIG. 22 shows a flowchart of conference activity amount calculation (DSAC) performed in the data processing server (DS). The amount of movement of each person's head derived from the sensing data measured by the distance sensor (RS) is hereinafter referred to as a conference activity amount.

  The body parts that often move during a meeting are the head and arms. Head movements occur as you speak or crawl. In addition, arm movements occur by speaking or writing with gestures. Head and neck movements are linked. In order to handle the amount of activity of people who hang the sensor terminal (TR) from the neck and visitors outside the sensor terminal (TR) together, the sensor terminal (TR) that is lowered from the neck is linked as much as possible. In order to obtain the value, the amount of conference activity is calculated from the movement of the head, not the arm.

  In FIG. 22, after the start of the process (DSACS), the data processing server (DS) senses the time series from the start to the end of the conference acquired by the distance sensor (RS) sent from the measurement PC (MP). Data (RSSD) is read (DSAC1).

  As shown in FIG. 23, the sensing data (RSSD) includes a sensing time (SSTM) and a three-dimensional coordinate value (PCCV) of a point group measured at the sensing time. A point cloud represents not only a person's area, but also the surface coordinate value of an object measured by a distance sensor (RS) such as a wall, a desk, or other objects existing in a room, with the sensor position as the origin. . In the sensing data (RSSD), a collection of measured points is recorded in one entry (or record) for each measured time.

  The data processing server (DS) first acquires sensing data (RSSD) at the first time (for example, the start time of the conference) (DSAC2). Next, the data processing server (DS) extracts a person area from the sensing data (RSSD) (DSAC31). For this purpose, as shown in FIG. 12, the same method as the person region extraction (MPST22) may be used. Next, the data processing server (DS) extracts the head coordinate value after extracting the person region (DSAC32). The head coordinate value is extracted by, for example, extracting the shape of a person from the three-dimensional point cloud data using the existing motion extraction algorithm shown in FIG. A method of extracting coordinate values as head coordinate values is used.

  In the sensing data (RSSD) during a meeting, since a large movement of a person often does not occur within a short time interval, the closest coordinate among the head coordinate values of each person area in the previous measurement time The person area having a value is estimated to be the same person, and the value is additionally stored in the head coordinate value (HDVV) of the person area (HBAR) (DSAC33). When the calculation of the head coordinate value (HDVV) of the person area in the target time zone is completed, the sensing data (RSSD) in the next time zone is read (DSAC 34), and the heads of the DSACs 31 to 34 are present while the data exists. The head coordinate value (HDPS) data is sequentially updated by repeating the process of recognizing the partial coordinate values.

  The data processing server (DS) outputs the three-dimensional head coordinate value (HDPS) when the calculation of the head coordinate value for each person area is completed in the sensing data of all time zones (DSAC5).

  As shown in FIG. 24, the head coordinate value table (HDPS) includes a person area number (HBAR), a sensing time (HDTM), and a head coordinate value (HDV). FIG. 24 shows an example in which data for a fixed time (for example, one second) is collected and stored in one column. When sensor data is acquired 30 times per second, 30 head coordinate values are stored in the head coordinate value (HDV).

  Next, the data processing server (DS) calculates a head movement table (HDMS) every predetermined time (for example, one minute) (DSAC6). FIG. 25A is a head movement table in which the head movement amount is calculated for every predetermined time (for example, one second) based on the data stored in the head coordinate value table (HDV) in the middle of the head movement amount calculation. (HDMS).

  By calculating the distance between the two points with the head coordinate value before a certain time (for example, one second), the amount of head movement per certain time (for example, one second) is calculated. Then, the head movement amount for every fixed time (for example, one minute) is calculated by integrating all the head movement amounts for every fixed time (for example, one second) in a fixed time (for example, one minute). FIG. 25B is a head movement table (HDMM) every fixed time (for example, one minute).

  The head movement table (HDMM) stores the person area number (HBAR) on the vertical axis and the time (HDTM) on the horizontal axis, and stores the head movement amount per minute for each person area for each hour. .

  Next, the data processing server (DS) assigns the person's name to the head movement table (HDMM). First, the data processing server (DS) reads the conference participant seating chart (MPLT) generated by the measurement PC (MP) (DSAC51).

  The data processing server (DS) obtains the most from the coordinate value of each person Pn in the conference participant seating chart (MPLT) and the head XY coordinate value of each person at the seating chart generation time in the head coordinate value table (HDPS). The persons having similar values are associated with each other as the same person (DSAC 52).

  FIG. 26A is a table in which the head coordinate values of each person stored in the head coordinate value table (HDPS) at the time of seating chart generation time of the conference participant seat chart (MPLT) are extracted. FIG. 26B is a table showing a correspondence between the person area number (HBAR) of the head movement table (HDMM) and the person number (MPLT1) of the conference participant seating chart (MPLT).

  FIG. 26C shows an example in which the person's name is stored in the person area number (HDAR) of the head movement table (HDMM). The data processing server (DS) outputs this table as a conference activity table (MATB) (DSAC6).

  Through the above processing, a conference activity amount table (MATB) in which the activity amount of each person who participated in the conference is gathered at regular time intervals is generated.

<Flow chart of meeting meeting secondary data generation>
FIG. 27 shows a flowchart of meeting-facing secondary data generation (DSMM) performed in the data processing server (DS).

  After the start of processing (DSMMS), the data processing server (DS) reads the conference activity amount table (MATB) of FIG. 26C generated by the conference activity amount calculation (DSAC) (DSMM1). The data processing server (DS) determines whether the active state during the conference is active or inactive based on the preset threshold value from the amount of head movement at each time for each participant of the conference ( DSMM2).

  The data processing server (DS) sets the activity level to “1” when the head movement amount is greater than or equal to the threshold value, and sets the activity level to “0” when the head movement amount is equal to or less than the threshold value, and the conference activity table (MATB2). Generate. FIG. 28A shows a conference activity table (MATB2). The conference activity table (MATB2) stores the name (MANM) specified by the terminal ID list (MPUL) from the terminal ID of the sensing data and the activity for each time (MATM) during the conference period. In this embodiment, the time (MATM) is set at 1 minute intervals.

  Of the time MAMT of the conference activity amount (MATB2) shown in FIG. 28A, the input portion (time) in which “1” is set as the activity level is painted and visualized (tapestri) as shown in FIG. 28B. Is generated by the data processing server (DS).

  From the conference activity table (MATB2) in FIG. 28A and the conference activity amount (MATB2) in FIG. 28B, there are many people who are actively moving in the conference, less time zones, more people who are actively moving, and few people. People can be understood intuitively.

  Next, by combining not only the degree of activity of the person (or the participant of interest) but also the degree of activity of the person who was the other party in the meeting, (1) It is classified into three states: (2) one-active state in which only one is active, and (3) one-active state in which only the partner is active, and the time for each state is counted (DSMM3). In some cases, both yourself and the other party may be inactive, but if both move slowly and are reluctant to the meeting, they will not be counted in the communication time.

  FIG. 29 shows an example in which three states are counted in consideration of the activity level of the face-to-face partner. FIG. 29 is an example of extracting data of Mr. Sato and Mr. Kimura in the time zone of 14: 48-14: 53 of the amount of conference activity (MATB2). The active state is “3” when viewed mainly by Mr. Sato and when viewed mainly by Mr. Kimura. The state where only oneself is active is “2” when viewed mainly by Mr. Sato, and “1” when viewed mainly by Mr. Kimura. Conversely, the active state of only the other party is “1” when viewed mainly by Mr. Sato and “2” when viewed mainly by Mr. Kimura. With this counter, three states are set according to the activity level of the persons facing each other: mutual activity, self activity, and partner activity.

  The data processing server (DS) generates a two-activity matrix diagram and a one-activity matrix diagram (DSMM3) and (DSMM4) based on the result counted as described above.

  FIG. 30A is a two-activity conference two-way activity matrix (DSKM1). Enter the time when the participants in the meeting were active for all the participants. The element (KM1_6) in the figure represents that the time during which both Sato and Suzuki were active was 14 minutes. FIG. 30B is a one-activity conference one-activity matrix (DSKM2). Enter the time when either one of the participants was active, calculated by the combination of all people. The element (KM2_6) in the figure represents that only Mr. Suzuki was active and Mr. Kimura was inactive for 9 minutes. In this way, the state in which only the participant of interest is active is stored in the horizontal row, and the state in which only the other participant is active is stored in the vertical column.

<Business-to-face activity matrix (ASGM) generation process>
In generating the basic contents shown in FIGS. 9A and 9B, the business face-to-face activity matrix (ASGM) that represents the face-to-face state in an N × N matrix is used to generate the contents that visualize the business face-to-face between employees and outside visitors. ) Is generated.

  FIG. 31 shows a flowchart of a business face-to-face matrix (ASGM) generation process executed by the application server (AS). Here is an example of a business-facing matrix where the vertical and horizontal axes are a combination of internal structural members as internal personnel (employees) and external meeting personnel (visitors) as external personnel Show. FIG. 31 shows an example in which the process after reading the conference data (CMC1 to CMC5) and the process of reading the conference activity secondary data (CMC6) are performed in parallel, but the present invention is not limited to this. You may perform sequentially.

  After the start of processing (CMCS), the application server (AS) transmits conditions such as the target period to the data processing server (DS), and the data processing server (DS) searches for information corresponding to the conditions, and conference data Is transmitted to the application server (AS) (CMC1). The conference data includes conference basic information (MPDM) such as the conference date and time, participants, a conference activity table (MATB2) in which the activity status of the conference participants is expressed in time series as “0” or “1”, and at the time of the conference The conference activity secondary database (DSKM) indicating the activity status of the event is included.

  Also, information such as the target period and terminal ID is transmitted from the application server (AS) to the sensor network server (SS), the sensor network server (SS) searches for information corresponding to the condition, and the application as sensor terminal data. The data transmitted to the server (AS) is read (CMC2). The sensor terminal data includes a conference acquisition activity secondary database (DSKM) indicating face-to-face activities between employees, sensing data (acceleration) indicating movement of the sensor terminal (TR), and the like.

  First, the application server (AS) receives the date and time of the relevant participant from the conference date and time and the conference participant wearing the sensor terminal (TR) stored in the conference basic information database (DSDM). Sensing data (acceleration) is extracted, and the activity time of the participant in the corresponding time zone is calculated.

  Further, the application server (AS) calculates the conference activity time by adding the conference activity table (MATB2) and the time when the activity level of the conference participant wearing the sensor terminal (TR) is “1”.

  The application server (AS) calculates a correction value of the conference activity from the activity time from the sensor terminal (TR) and the activity time from the distance sensor (RS) in the same time zone (CMC3).

  As shown in FIG. 32, the sum (23 + 15) of the sensing data (acceleration) of two target users at the target date and time (2012/03/31 14: 48-2012 / 03/31 15:30) The value divided by the sum (19 + 20) of the values in the activity table (MATB2) is taken as the conference activity correction value (0.97).

  Next, the application server (AS) reads the conference activity secondary data (DSKM) (CMC4), and the calculated conference activity correction value is stored in each cell of the conference activity secondary data (DSKM). Is used to correct the conference activity matrix (conference bilateral activity matrix (DSKM1) and conference one-side activity matrix (DSKM2)) (CMC5).

  Next, the application server (AS) reads the face-to-face activity matrix (ASMM) obtained from the sensor network server (SS) and indicating the communication amount within a period between any employee in the company (CMC6).

  The application server (AS) generates a business face-to-face activity matrix (ASGM) based on a face-to-face activity matrix (ASMM) indicating face-to-face activities between employees within the company, and represents a part representing face-to-face visits with outside visitors. Expand.

  First, the application server (AS) expands the size of the face-to-face activity matrix (ASMM) by the number of face-to-face opponents who are outside visitors (CMC7).

  For example, if the size of the face-to-face activity matrix (ASMM) is 30 × 30 (this indicates that the number of employees targeted in the company is 30) and the number of external face-to-face contacts is 15, 45 × 45 matrices are generated.

  The application server (AS) copies the 30 × 30 portion indicating the in-house meeting as it is. Next, the application server (AS) uses the 30 × 15 portion indicating the meeting between the in-house target employee and the outside meeting partner as an extended matrix (EXMT), and a meeting activity matrix (conference meeting activity matrix) corrected by CMC5. (DSKM1) and conference one activity matrix (DSKM2)) are embedded in the corresponding cells of the expansion matrix (EXMT) (CMC8).

  The application server (AS) determines the location in the matrix from the wearer of the in-house sensor terminal (TR) stored in the corrected meeting activity matrix and the visitor who attended the meeting, and the in-house sensor terminal (TR) ) And the communication amount including the activity state between the wearer and the visitor attending the conference are stored in the determined matrix position. On the other hand, when the positions of the matrices for storing the communication amount overlap (when there is data of the same in-house sensor wearer and the meeting attendee), the application server (AS) stores the value stored at the position of the matrix. In addition, the amount of communication is added and updated.

  It is determined whether all the data stored in the conference activity matrix (the conference two-side activity matrix (DSKM1) and the conference one-side activity matrix (DSKM2)) are reflected in the business-facing activity matrix (ASGM) (CMC9). Until the data is reflected, the communication amount is continuously embedded in the matrix. When all the data of the external business meeting table is reflected, the business meeting activity matrix (ASGM) is completed (CMC9).

<Example of secondary database (SSDT): Face-to-face activity matrix>
An example of a face-to-face activity matrix (ASMM) is shown in FIGS. 33A and 33B as an example of a secondary database (SSDT) that stores the results of sensing data processing (SSCDT) in the sensor network server (SS). FIG. 33A shows a two-way face activity matrix (ASMM1) and FIG. 33B shows a one-way face activity matrix (ASMM2).

  The secondary database (SSDT) is a database in which the sensor network server (SS) performs predetermined preprocessing and stores specific user information for a certain period in a common format.

  FIG. 33A and FIG. 33B show an example of a face-to-face activity matrix (ASMM) showing face-to-face time including the degree of mutual activity within a predetermined period between arbitrary employees in the organization. The face-to-face activity matrix is called an adjacency matrix in network analysis terminology.

  The face-to-face activity matrix (ASMM) is based on the face-to-face table (SSDB_IR) of the sensing database (SSDB) shown in FIG. 34A and FIG. 34B (described later). The face-to-face activity matrix (bidirectional) (ASMM1) in FIG. 33A is obtained by calculating the time during which both are active from the acceleration data of each employee of the target combination and arranging them in a matrix format.

  Similarly, from the face-to-face between employees of any combination and the speed data of the target combination at the time of face-to-face, the time when only one is active is calculated and arranged in a matrix format, It is a face-to-face activity matrix (one direction) shown in FIG. 33B (ASMM2).

<Example of sensing database (SSDB): face-to-face table>
34A and 34B show a facing table as an example of a sensing database (SSDB). 34A and 34B are sensing data of sensor terminals (TR) having different terminal IDs.

  The sensing database (SSDB) stores a plurality of types of sensing data corresponding to each of the sensor terminals (TR) of a plurality of employees. Examples are shown in FIGS. 34A and 34B.

  FIG. 34A shows a face-to-face table (SSDB_IR_1002), which is a table in which data acquired by a sensor terminal (TR) whose terminal ID is 1002 is collected. Similarly, FIG. 34B shows a meeting table (SSDB_IR_1003), which is a meeting table of data acquired by the sensor terminal (TR) whose terminal ID is 1003. The detector ID (CLVDID) received from the infrared transmitter / receiver (CLVDIR) of the viewer detector (CLVD) and the infrared transmitter / receiver of the sensor terminal wearer detector (ISD) was also received from the sensor terminal (TR). Similar to the terminal ID, it may be recorded in the infrared transmission side ID (DBR10). In this case, by searching the table using the detector ID as a key, it is possible to check who has held the meeting at which place and who has browsed the display.

  34A and 34B, the time (DBTM) at which the sensor terminal (TR) transmits data, the terminal ID (DBR1) on the infrared transmission side, and the number of receptions from the terminal ID (DBN1) are 10 An example of storing a pair (DBR1 and DBN1, DBR2 and DBN2, ..., DBN10 and DBN10) is shown.

  This face-to-face table indicates how many infrared rays are received from which sensor terminal (TR) within a predetermined time (for example, 10 seconds). When meeting, that is, when there is no infrared reception, the value of the table is “null”. The time interval is not limited to 10 seconds and can be changed according to the purpose.

<Example of sensing database (SSDB): acceleration data table>
FIG. 35 shows an example of an acceleration data table (SSDB_ACC — 1002) as an example of sensing data stored in the sensing database (SSDB) of the sensor network server (SS).

  The acceleration data table basically stores sensing data acquired by the sensor terminal (TR) as it is, and is data in a state in which preprocessing is not performed. The acceleration data table is created for each individual (sensor terminal (TR)), and is associated with time information (DBTM) every predetermined sampling period (for example, 0.02 seconds). ), Y axis (DBAY), and Z axis (DBAZ), the acceleration data in each of the three axis directions orthogonal to each other are stored.

  In addition, the numerical value detected by the acceleration sensor may be stored as it is, or a value obtained by converting the measurement value unit of the sensing data into [G] may be stored. Such an acceleration data table is generated for each member and stored in association with the sensed time information. Note that if a column indicating the terminal ID is added, the table can be integrated without being divided for each individual (a table in which data of all personnel in the organization is recorded).

<Example of business face-to-face activity matrix (ASGM_1)>
FIG. 36 is an example of a business face-to-face activity matrix based on a combination of an arbitrary employee in the company and an outside person (visitor). The business-facing activity matrix (ASGM_1) shown in the figure is a meeting activity matrix (two-way) that shows a two-way activity meeting between any employee in the company that is one of the secondary data acquired from the sensor network server (SS) ( The ASMM 1) and an expansion matrix (EXMT) indicating the face-to-face activity of a company visitor who is present at a meeting with an arbitrary employee in the company are combined by an application server (AS).

  An extended matrix (EXMT) indicated by a broken line in the figure is a matrix in which arbitrary employees in the company and visitors outside the company are added to the respective axes in the application server (AS).

In accordance with the value obtained by correcting the meeting face-to-face activity table (DSKM1) shown in FIG. 30A with the meeting correction value, the application server (AS) sets the communication amount as the time during which both the in-house employee and the outside visitor are active. The data is stored in the corresponding cell in the expansion matrix (EXMT). In the business face-to-face activity matrix shown in FIG. 36, as shown in the element (KM2_8), it is shown that the time that Mr. Yamada in the company and Mr. Yamaguchi of Company X faced each other in an active state was 2 minutes. .
Note that the meeting time between a visitor who is not wearing the sensor terminal and the wearer, or between visitors who are not wearing the sensor terminal is calculated assuming that all the participants sitting at the conference table are facing each other.

<Example of business face-to-face activity matrix (ASGM_2)>
FIG. 37 is an example of a business face-to-face activity matrix (ASGM_2) centered on a combination of an arbitrary employee in the company and a face-to-face person (visitor) outside the company. The business face-to-face activity matrix (ASGM_2) is a face-to-face activity matrix (one-way) that shows a face-to-face active state between any employee in the company, which is one of the secondary data acquired from the sensor network server (SS). ) (ASMM2) and an expansion matrix (EXMT) indicating the face-to-face activity of an in-house employee and an outside visitor who is present at a meeting are combined by an application server (AS).

  An extended matrix (EXMT) indicated by a broken line in the figure is a matrix in which arbitrary employees in the company and visitors outside the company are added to the respective axes in the application server (AS).

In accordance with the value obtained by correcting the meeting face-to-face activity table (DSKM2) shown in FIG. 30B with the meeting correction value, the time during which one of the in-house employee and the outside visitor is active is set as the communication amount, and the application server (AS Are stored in the corresponding cells in the expansion matrix (EXMT). In the business face-to-face activity matrix (ASGM) shown in FIG. 37, as shown in the element (KM2_8), Mr. Yamaguchi of company X was active and Mr. Yamada in the company was inactive for 2 minutes. It shows that. Further, as shown in the element (KM8_2), it is shown that Mr. Yamaguchi of Company X was inactive and Mr. Yamada in the company was active for 21 minutes.
In addition, the time which was the active state of the visitor who is not wearing the sensor terminal and the wearer, or between the non-wearing visitors is calculated as follows. Calculate as
(1) For wearers of sensor terminals, the bidirectionality and unidirectionality of the activity are calculated from the measured values of the acceleration sensor (see FIGS. 33A and 33B).
(2) Regardless of whether the sensor is attached or not, the bidirectionality or unidirectionality of the activity is determined based on the amount of movement of the head by the laser distance sensor (RS) (see FIGS. 33A and 33B).
Of these two calculation methods, the solid line portion (face-to-face activity matrix (ASMM)) described in FIGS. 36 and 37 uses the result of (1) above, and the other extended portion (extended matrix (EXMT)). For ()), by using the result of (2), it is possible to obtain the result without performing complicated processing calculation.

<Network diagram generated from business-facing activity matrix>
In the above, the business face-to-face activity matrix (ASGM) in which communication between people is represented by an N × N matrix according to each active state has been described. In order to express the information of the business meeting activity matrix (ASGM) in a visually easy-to-understand manner, a network diagram that connects the persons who have encountered each other with lines is generated by the application server (AS). By storing the network diagram generated by the application server (AS) as image data, it becomes one of the contents presented to the user by the client (CL).

  The application server (AS) uses the business-facing activity matrix of both the activity (ASGM_1) shown in FIG. 36 and the one activity (ASGM_2) shown in FIG. 37, and constitutes the axis of the business-facing activity matrix. The mutual communication state of (employee and visitor) is represented by a line connecting the nodes.

  FIG. 38A illustrates an example in which the application server (AS) extracts Mr. Yamada and Mr. Tanaka as members.

  The application server (AS) uses the interactive activity matrix (ASGM_1) of the interactive activity shown in FIG. 36 as the ratio (or ratio) of the interactive time of the active state to the total interactive time for the interactive time of Mr. Yamada and Mr. Tanaka. calculate. The total meeting time between Mr. Yamada and Mr. Tanaka can be obtained from the sensing data of the sensor terminal (TR) shown in FIGS. 34A and 34B.

  In addition, the application server (AS) determines the ratio of the meeting time in which only one of the face-to-face times of Mr. Yamada and Mr. Tanaka is active with respect to the total face-to-face time from the one-side active work face-to-face activity matrix (ASGM_2) shown in FIG. calculate. As described above, as shown in FIG. 38A, the ratio of the face-to-face time for both activities is 67%, only Mr. Tanaka is the face-to-face ratio in the active state is 27%, and only Mr. Yamada is the face-to-face time in the active state is 6. The example which becomes% is shown.

  Next, arrows are used to connect Tanaka-san and Yamada-san nodes with a line. Also, the active state and the inactive state of a person in a face-to-face state are distinguished using a solid line and a dotted line. In the illustrated example, the active state is indicated by a solid line, and the inactive state is indicated by a dotted line.

  The time during which Tanaka is active is the time when only Tanaka is active (27%) + the time when both are active (67%), and 94% of the arrow is indicated by a solid line. The remaining 6% is indicated by a dotted line (“Yamada only active” in the figure).

  In addition, the active time of Mr. Yamada is the time when only Mr. Yamada is active (6%) + the time of both activities (67%), 73% of the arrow is indicated by a solid line, and the remaining 27% is indicated by a dotted line . Thereby, it is possible to easily grasp the time of both activity and the time of one activity from the difference between the solid line and the dotted line.

  In the above description, the method of expressing the difference between the active state and the inactive state with the solid line and the dotted line has been described, but it may be expressed with a line with a different color.

  Further, when both the activities of the node A and the node B are 100%, as shown in FIG. 38B, the arrows on both sides are connected to the nodes A and B by a solid line.

  On the other hand, when the activity is 100%, as shown in FIG. 38C or FIG. 38D, an arrow is connected with a solid line from the active person node to the inactive person node.

<Example of internal network diagram generated from face-to-face activity matrix>
39A to 39C show an example of an in-house network diagram generated by the application server (AS) from the face-to-face activity matrix (ASGM).

  The in-house network diagram (ASNF) shown in FIG. 39A is a network generated based on a face-to-face activity matrix indicating face-to-face time between arbitrary employees in the company, which is one of the secondary data acquired from the sensor net server (SS). FIG.

  What is shown here is an example in which the line width is changed according to the meeting time. That is, the line width is increased as the facing time increases.

  FIG. 39B shows an in-house activity network FIG. 1 (ASAN1) in which secondary activity and one-side activity are distinguished from each other by a solid line and a dotted line in accordance with FIGS. 38A to 38D, and secondary data acquired from the sensor network server (SS). In-house generated based on face-to-face activity matrix (ASMM1) and (ASMM2) showing the ratio of face-to-face time corresponding to each other's activity within a given period among any employee in the organization FIG. 1 is a network diagram 1.

  In-house activity network shown in Fig. 39C (ASAN2) is a combination of Fig. 39A and Fig. 39B. Both active and one-sided activities are distinguished by a solid line and a dotted line, and the line width is changed according to the facing time. This is an example. The ratio of facing time corresponding to each other's activity within a predetermined period between arbitrary employees in the organization, which is one of the secondary data acquired from the sensor network server (SS), is distinguished by a solid line and a dotted line, Bilateral activity and unilateral activity were distinguished by arrows.

  Thereby, at the time of meeting, it can grasp | ascertain the relationship of an individual individual whether both sides were active or only one was active. Moreover, FIG. 2 (ASAN2) in-house activity network is an example in which the line width is changed according to the meeting time.

  Further, the application server (AS) can generate at least one of FIGS. 39A to 39C as image data and provide an in-house activity network diagram when a request is received from the client (CL).

<Example of business network diagram generated from business-facing activity matrix>
The business network diagram (ASGN) shown in FIGS. 40A to 40C is obtained by adding information obtained from conference data to the in-house network (ASNF) shown in FIGS. 39A to 39C. It is changed and expressed. Information on visitors from outside the company is added to the internal network diagrams shown in FIGS. 39A to 39C by an application server (AS). By distinguishing and displaying the internal employee node and the non-company visitor node shape, the distinction between internal and external people can be visually understood.

<Flow chart of visitor determination (CSCVD)>
FIG. 41 shows a flowchart of browser determination (CLCVD) performed by the client (CL). The browser determination (CLCVD) process is a process that is always performed while the browser detector (CLVD) is activated.

  After the start of processing (CVDS), the client (CL) takes in the infrared data received from the viewer detector (CLVD) (CVD1) and inquires the terminal ID list for the ID included in the infrared data. If the ID included in the infrared data is not a valid terminal ID stored in the terminal ID list (CLID), the data is determined to be noise and removed (CVD2).

  Then, the number of times the terminal ID is received is counted for a predetermined time, for example, every 1 second or 5 seconds. The client (CL) determines whether or not the number of times the terminal ID has been received is equal to or greater than a predetermined threshold value (CVD3). If the number of times the terminal ID is received is equal to or greater than the threshold, the client (CL) regards the received terminal ID as a viewer (CVD42). On the other hand, if not, the terminal ID is not regarded as a viewer (CVD41). This is a measure to prevent a user (US) who has just passed for a moment from being included in the viewer. In this manner, the client (CL) generates a list (viewer ID list) of terminal IDs of users (US) regarded as viewers within a predetermined time (CVD 5). The client (CL) sends the generated viewer ID list to the application server (AS), and acquires a name corresponding to each terminal ID in the list (CVD 6). That is, the viewer's name is acquired from the application server (AS). The above flow is repeatedly transmitted until the viewer determination (CLCVD) program is terminated manually or by a timer.

<Access control rules (ASAC)>
FIG. 42 shows an example of the data structure in the access control specification (ASAC) file recorded in the storage unit (ASME) of the application server (AS). The access control rule (ASAC) file is output in accordance with basic content generation (ASCBC) in the application server (AS), and stores conditions for accessing the corresponding basic content file (ASBF). is there. For example, an access condition is defined such that a file related to a certain department can be browsed if at least one employee of the department is included in the viewer.

  In the access control rule (ASAC), the file ID (ASAC01), file type (ASAC02), and access condition (ASAC03) of the basic content file are stored in association with each other.

  The file type (ASAC02) indicates the type of content. It is used for heading and classification when displaying a button in the content switching button (OD_C) displayed on the display (CLOD) of the client (CL).

  The access condition (ASAC03) is a logical expression showing the terminal ID of the viewer necessary for displaying the corresponding file.

<Screen example when displaying network diagram>
FIG. 42 shows an example of a screen displayed on the display (CLOD) of the client (CL). As the content information displayed on the display (CLOD) by the client (CL), an example in which a network diagram of an in-house organization is adopted is shown. The network diagram image received from the application server (AS) is displayed in the content display area (OD_B) of the screen (OD) displayed on the display (CLOD) of the client (CL). The viewer selection button (OD_A) displays the name of the user currently detected as a viewer.

  As described above, according to the present invention, the sensing data measured by the sensor terminal (TR) is analyzed by the data processing server (DS) or the application server (AS), and communication between humans wearing the sensor terminal (TR) is performed. Not only can you grasp the amount (face-to-face time) and situation (activity and activity), but also the amount of communication (face-to-face time) and situation (activity and activity) with people outside the sensor terminal (TR). ) Can also be grasped.

  In the first embodiment, whether the active state during the conference is active (activity level = 1) or inactive (activity level = 0) based on the amount of head movement at each time for each participant of the conference. FIG. 27 shows an example in which is determined based on a preset threshold value, but the present invention is not limited to this. For example, a plurality of threshold values may be provided to divide the activity into a plurality of stages.

  Moreover, in the said Example 1, measurement PC (MP) pinpoints the position of the participant of a meeting with a distance sensor (RS), and produces | generates a seating plan. And measurement PC (MP) specifies the name of the participant corresponding to a seat from terminal ID of the sensor terminal (TR) detected with the sensor terminal wearer detector (ISD). Furthermore, in the measurement PC (MP), when the terminal ID does not exist in the seat where the participant exists, it is estimated that there is a visitor not wearing the sensor terminal (TR), and information such as a name is input. Can be encouraged. Thereby, the face-to-face data of the person wearing the sensor terminal (TR) and the person not wearing the sensor terminal (TR) is generated, and the outside person (visitor) not wearing the sensor terminal (TR) Communication amount (meeting time) and situation (activity and activity) can be easily grasped.

  Moreover, in the said Example, the example which comprises a business network face-to-face data generation system mainly by a sensor network server (SS), a data processing server (DS), an application server (AS) measurement PC (MP), and a client (CL). As shown, the sensor network server (SS), the data processing server (DS), the application server (AS), the measurement PC (MP), and the client (CL) may be combined into one computer to be a business-to-face data generation device. it can.

  The configuration of the computer and the like, the processing unit, and the like described in the present invention may be partially or entirely realized by dedicated hardware.

  In addition, the various software exemplified in the present embodiment can be stored in various recording media (for example, non-transitory storage media) such as electromagnetic, electronic, and optical, and through a communication network such as the Internet. It can be downloaded to a computer.

  The present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described.

The present invention is a face-to-face data generation apparatus that includes a processor and a storage unit and generates data related to physical face-to-face contact between persons, and is detected by a first sensor of a sensor terminal attached to each of a plurality of persons. A communication unit that receives sensing data indicating the measured physical quantity and a second sensor that is arranged at a predetermined position and measures the position of the person, and the position of the person based on the received data A first measurement unit that identifies the first measurement unit, a second measurement unit that is disposed at a predetermined position and communicates with the sensor terminal to identify the position of the sensor terminal, and the first measurement unit identifies the position A face data generation unit that combines the position of the person and the position of the sensor terminal specified by the second measurement unit, and generates the face data of the person based on the physical quantity of the sensing data; The second sensor is constituted by a distance sensor for measuring a distance to the person, the first measurement unit, the data acquired from the distance sensor, based on the position and direction of the distance sensor, A seat plan based on the actual arrangement of the person is generated .

Claims (14)

A face-to-face data generation device that includes a processor and a storage unit and generates data related to physical face-to-face between persons,
A communication unit that receives sensing data indicating a physical quantity detected by a first sensor of a sensor terminal attached to each of a plurality of persons;
A first measurement unit that receives data from a second sensor that is arranged at a predetermined position and measures the position of the person, and that specifies the position of the person based on the received data;
A second measuring unit arranged at a predetermined position to communicate with the sensor terminal and identify the position of the sensor terminal;
The position of the person specified by the first measurement unit and the position of the sensor terminal specified by the second measurement unit are combined to generate face-to-face data of the person based on the physical quantity of the sensing data. A face-to-face data generator,
A face-to-face data generation apparatus comprising: The face-to-face data generation device according to claim 1,
The second sensor is
It consists of a distance sensor that measures the distance to the person,
The first measurement unit includes:
A face-to-face data generation apparatus that generates a floor plan based on an actual arrangement of the person based on data acquired from the distance sensor and the position and direction of the distance sensor. The face-to-face data generation device according to claim 1,
The second measuring unit is
It has a sensor terminal detector that communicates with the sensor terminal, and the sensor terminal is mounted based on the terminal ID acquired from the sensor terminal detected by the sensor terminal detector and the position and direction of the sensor terminal detector. A face-to-face data generation apparatus characterized by specifying a position of a person. The face-to-face data generation device according to claim 2,
It further includes an input unit for inputting information,
The input unit is
A face-to-face data generation apparatus, wherein a position of a person on the seat plan is selected and information on the person is input. The face-to-face data generation device according to claim 2,
The first measurement unit includes:
A face-to-face data generation apparatus, wherein a movement amount of the person's head is calculated from data of the distance sensor, and an activity level of the person is calculated from the movement amount. The face-to-face data generation device according to claim 5,
A network diagram generating unit that generates a network diagram showing the relationship between the persons based on the meeting data;
The network diagram generation unit
A face-to-face data generation device, characterized in that an arrow corresponding to the degree of activity is assigned to a node connecting nodes representing the persons. The face-to-face data generation device according to claim 2,
The seat floor plan is
A face-to-face data generation apparatus comprising: an actual arrangement of a person wearing the sensor terminal; and an actual arrangement of a person not wearing the sensor terminal. A face-to-face data generation method for generating data related to physical face-to-face contact between computers using a processor and a storage unit,
A first step in which the calculator receives sensing data indicating a physical quantity detected by a first sensor of a sensor terminal attached to each of a plurality of persons;
A second step in which the calculator receives data from a second sensor arranged at a predetermined position and measures the position of the person, and specifies the position of the person based on the received data;
A third step of identifying a position of the sensor terminal based on a result of the computer communicating with the sensor terminal;
A fourth step in which the computer combines the identified position of the person and the identified position of the sensor terminal, and generates face-to-face data of the person based on a physical quantity of the sensing data;
A method for generating face-to-face data, comprising: The method for generating face-to-face data according to claim 8,
The second sensor is
It consists of a distance sensor that measures the distance to the person,
The second step includes
A method for generating face-to-face data, wherein a seat plan based on an actual arrangement of the person is generated based on data acquired from the distance sensor and a position and direction of the distance sensor. The method for generating face-to-face data according to claim 8,
The third step includes
The computer receives the terminal ID of the sensor terminal detected by the sensor terminal detector that communicates with the sensor terminal, and identifies the position of the person wearing the sensor terminal based on the position and direction of the sensor terminal detector A method for generating face-to-face data. The method for generating face-to-face data according to claim 9,
The calculator further includes an input unit for inputting information,
The method for generating face-to-face data, further comprising a fifth step of selecting a position of a person on the floor plan and inputting information about the person through the input unit. The method for generating face-to-face data according to claim 9,
The second step includes
A method for generating face-to-face data, wherein a moving amount of the head of the person is calculated from data of the distance sensor, and an activity level of the person is calculated from the moving amount. The method for generating face-to-face data according to claim 12,
A sixth step of generating a network diagram showing the relationship between the persons based on the meeting data;
The sixth step includes
A method for generating face-to-face data, characterized in that an arrow corresponding to the degree of activity is given to a line connecting nodes representing the persons. The method for generating face-to-face data according to claim 9,
The seat floor plan is
A method for generating face-to-face data, comprising an actual arrangement of a person wearing the sensor terminal and an actual arrangement of a person not wearing the sensor terminal.

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