JP2013020338A - Face-to-face detection system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect a face-to-face state by a sensor terminal worn on a user himself/herself even when the other person wears no sensor terminal.SOLUTION: A sensor terminal (TR) is worn on each employee in an organization for detecting a physically face-to-face state between employees in the organization who are the employees belonging to the organization. The sensor terminal (TR) includes: a face-to-face determination unit (TRID) that determines presence/absence of the physically face-to-face state between employees in the organization on the basis of the communication/non-communication with another sensor terminal (TR); a voice detection unit (TRMI) that detects voice and creates voice data; an utterance determination unit (TRSD) that analyzes the voice data and determines the utterance/non-utterance; and a behavior determination unit (TRAD) determining that a certain employee performs either behavior of facing an employee in the organization, facing an employee who does not wear the sensor terminal (TR), and facing no one, on the basis of a determination result of the face-to-face determination unit (TRID) and a determination result of the utterance determination unit (TRSD).

Description

  The present invention relates to a system in which each user wears a sensor terminal and each sensor terminal communicates with each other, thereby detecting the face-to-face between the sensor terminal wearers and quantitatively detecting the actual state of organizational communication. In particular, the present invention relates to a technique capable of detecting a face-to-face partner who is not wearing a sensor terminal in addition to the detection of the face-to-face wearing sensor terminals.

  Improving productivity is an essential issue in every organization, and many trials and errors have been made to improve the work environment and streamline operations. When the assembly or transportation of a factory or the like is limited to an organization that handles business, the process and results can be objectively analyzed by tracking the movement path of parts or products. On the other hand, regarding an organization composed of knowledge workers, there is already known an organization that visualizes business processes by using electronic documents instead of things and usage logs of IT devices.

  In the first place, an organization is formed in order to achieve large-scale work that cannot be done by individuals by combining multiple people. Therefore, in any organization, communication is always performed for decision making and agreement between two or more persons. Examples of communication means include telephone, fax, and e-mail. The most frequently used and most influential means is face-to-face face-to-face communication. In face-to-face communication, you can make the most of the human body, such as gestures, gaze, facial expressions, and tone of voice. For this reason, many of the indispensable communications in the organization, such as the formation of favorable relationships through daily greetings and the compromise in negotiations involving complicated profits, are naturally realized through face-to-face communication. .

  In face-to-face communication, two or more people involved create a conversation rhythm and atmosphere in real time. As a result, emotional resonance and the emergence of ideas can occur from places that cannot be predicted. There is a big part of the results of the creative ideas born in this way in the results of the organization centered on knowledge labor. The number of organizations that have become aware of its importance and have introduced attempts such as free seating for seats and organizing cross-sectional projects have been increasing in recent years. Both of these are expected to create new value by providing opportunities for people with diverse backgrounds to come into contact with each other.

  All of the conventional methods analyze work as the subject, but knowledge labor cannot be grasped without knowledge. This is because it is not possible to obtain the maximum result only by cutting out only the procedure and time for each work and aiming at efficiency improvement. Therefore, in order to obtain good results in knowledge labor, it is necessary to focus on the characteristics of individuals and especially to know the work style. A work style is a pattern of how to proceed with personal work, when, where, and what to do. Work style reflects both the contents of work, which is an external factor, and the personality, which is an internal factor. Knowledge work professionals have established their own work styles. Some people get ideas while discussing, while others think alone. There are also people who go out and walk around, and those who sit at the desk and turn magazines, and the styles are diverse. As knowledge work is particularly spiritual, the method of achieving the most effect depends on the individual qualities and roles they play. However, conventional analysis methods mainly do not take into account the effects of matters that are not directly reflected in the work product, such as reading, walking, chatting, etc. Therefore, it is necessary to capture the work style by observing the actual behavior of each member based on the person. And by grasping and respecting each other's work styles, it is thought that the work style of the entire organization is established, leading to improved productivity.

  For such a purpose, a system is known in which employees wear sensor terminals and the sensor terminals communicate with each other to detect the faces of employees wearing sensor terminals. In this system, it is possible to quantitatively acquire which member the face-to-face communication is made with which member, and can grasp the actual state of communication in the organization.

  In Patent Document 1, each person has a portable electronic device such as a mobile phone provided with a device capable of short-distance communication such as Bluetooth (registered trademark) and a long-distance communication interface. A technique for issuing a notification when an approach is detected is disclosed. When portable electronic devices owned by two people approach each other to a distance at which short-distance communication is possible, a unique ID code is exchanged between the devices via short-range communication, and the result is a long-distance communication interface. Sent to the server. When the server detects that these two people are in a predetermined relationship, a notification is sent to both or one of them to inform them that they are in close proximity.

  Non-Patent Document 1 describes a technique for collecting remote data using RFID and using wireless sensor network technology, thereby performing real-time status monitoring. Many spatially arranged RFIDs and RFIDs worn by users are assigned IDs, and the RFID reader reads the RFID to detect the approach, for example, children in a park Information can be tracked.

US Patent Application Publication No. 2005/0250552 Chao Chen, "Design of a Child Localization System on RFID and Wireless Sensor Networks," Journal of Sensors, Volume 2010, Article ID 450392, 8 pages

  In knowledge creation in an organization, there is communication with various people as described above. Among them, communication between insiders and outsiders occupies an important position, and its detection and identification are extremely important. New knowledge and knowledge are acquired from communication with outsiders, and communication with insiders fulfills functions such as sharing awareness and deepening recognition among members. Therefore, by identifying and comprehensively acquiring communication with insiders and outsiders, it is possible to quantify the “flow of knowledge” process in the organization and contribute to improving the creativity of the organization.

  However, in the system described above and the one disclosed in Patent Document 1, each person needs to have a portable electronic device. Therefore, even if one of them has a portable electronic device, the function cannot be exhibited unless the other has it. For this reason, it cannot be said that this method can sufficiently detect the actual state of communication in an organization.

  The present invention has been made in view of the above, and an object of the present invention is to provide a technology capable of detecting face-to-face communication with a sensor terminal worn by the partner even when the other party does not wear the sensor terminal.

A typical example of the present invention is as follows. That is, a sensor terminal device mounted on each of the in-organization personnel in order to detect physical facing between the in-organization personnel who are members belonging to the organization,
A face-to-face determination unit that determines the presence or absence of physical face-to-face between personnel in the organization based on the success or failure of communication with other sensor terminal devices;
A voice detection unit that detects voice and generates voice data;
An utterance determination unit that analyzes the voice data generated by the voice detection unit and determines the presence or absence of an utterance;
Based on the determination result by the face-to-face determination unit and the determination result by the utterance determination unit, among the actions including face-to-face with the organization personnel, face-to-face with the person not wearing the sensor terminal device, and non-face-to-face And an action determination unit that determines that any action has been performed.

  According to the present invention, between the face-to-face between the personnel within the organization wearing the sensor terminal device, the face-to-face state with the non-organization personnel not wearing the sensor terminal device, and the state of non-face-to-face not facing anyone, It can be determined that any action has been performed.

It is a block diagram explaining the whole structure of the business management support system to which this invention is applied. It is a block diagram which shows only the part which plays an important role in 1st Embodiment in the system shown by FIG. It is a flowchart explaining the example of a procedure of a face-to-face determination process. It is a flowchart explaining the example of a procedure at the time of carrying out the FFT process to audio | voice data, and the process which detects the fundamental frequency originating in a human voice. In 1st Embodiment, it is a figure which shows notionally a mode that the process of speech determination and action determination is performed by the sensor terminal. It is a block diagram which shows only the part which plays an important role in 2nd Embodiment in the system shown by FIG. It is a figure which shows notionally a mode that the process of speech determination and action determination is performed by the sensor terminal in 2nd Embodiment. It is a block diagram which shows only the part which plays an important role in 3rd Embodiment in the system shown by FIG. In 3rd Embodiment, it is a figure which shows notionally a mode that the process of speech determination and action determination is performed in an application server based on the audio | voice data acquired and processed and transmitted with a sensor terminal. It is a block diagram which shows only the part which plays an important role in 4th Embodiment in the system shown by FIG. In 4th Embodiment, it is a figure which shows notionally a mode that the process of speech determination and action determination is performed in an application server based on the audio | voice data acquired by the sensor terminal, processed, and transmitted. It is a block diagram which shows only the part which plays an important role in 5th Embodiment in the system shown by FIG. In 5th Embodiment, it is a figure which shows notionally a mode that the process of speech determination and action determination is performed by the sensor terminal. It is a block diagram which shows only the part which plays an important role in 6th Embodiment in the system shown by FIG. In 6th Embodiment, it is a figure which shows notionally a mode that the process of speech determination and action determination is performed in an application server based on the audio | voice data acquired and processed and transmitted with a sensor terminal. It is a figure explaining the outline of the processing sequence performed in cooperation between the elements which comprise a business management support system, and is a figure explaining the processing sequence performed in 1st, 2nd, and 5th embodiment. . It is a figure explaining the outline of the processing sequence performed in cooperation between the elements which comprise a business management support system, and is a figure explaining the processing sequence performed in 3rd, 4th, and 6th embodiment. .

− Overall system configuration −
FIG. 1 is a diagram illustrating the overall configuration of a business management support system to which the present invention is applied. The business management support system includes an application server (AS), a client (CL), a business information management server (GS), a sensor network server (SS), a base station (GW), and a sensor terminal (TR). Prepare. Among these components, the components other than the sensor terminal (TR) may be realized by an electronic computer and software executed by the electronic computer, or may be realized by dedicated hardware. In addition, a plurality of components may be realized by one electronic computer or the like according to the scale of the organization where the business management support system is installed. Conversely, one component may be realized by a plurality of electronic computers or the like. It is also possible to provide a plurality of base stations (GW) and clients (CL) according to the scale of the organization. FIG. 1 shows an example in which three base stations (GW, GW2, GW3) and two clients (CL, CL2) are provided. Hereinafter, unless individually referred to, they are referred to as a base station (GW) and a client (CL).

  The application server (AS), client (CL), sensor network server (SS), business management server (GS), and base station (GW) are connected via a wired or wireless network (NW).

  The sensor terminal (TR) is worn by each of the personnel belonging to the organization, that is, the personnel within the organization. Therefore, a plurality of sensor terminals (TR) are included in the business management support system, but in FIG. Only one is shown. Hereinafter, the in-organization personnel wearing the sensor terminal (TR) are referred to as users.

− Sensor terminal (TR) −
Since the sensor terminal (TR) has a built-in power supply and can be operated by the power supply, the user wearing the sensor terminal (TR) can freely move in the organization. As a power source, a primary battery, a secondary battery, a capacitor, or the like can be used. Moreover, you may provide the structure which can be received by a solar cell panel or a wireless power feeding system as a power supply.

  The sensor terminal (TR) includes a sensing unit (TRSE), a transmission / reception unit (TRSR), an input / output unit (TRIO), a control unit (TRCO), and a recording unit (TRME).

  The sensing unit (TRSE) senses a physical quantity indicating the state of the sensor terminal (TR). Specifically, the sensing unit (TRSE) includes one or more sensors that sense various physical quantities. For example, an infrared transmitter (TRIS), an infrared receiver (TRIR), an acceleration sensor (TRAC), an illuminance sensor (TRIL), a temperature sensor (TRTE), and a sound sensor (TRMI) are provided.

  The infrared transmitter (TRIS) outputs an infrared light signal at a predetermined timing (time interval). The infrared receiver (TRIR) also detects infrared light at a predetermined timing (time interval). When an infrared light signal emitted from an infrared transmitter (TRIS) of a sensor terminal (TR) worn by a user is detected by an infrared receiver (TRIR) of a sensor terminal (TR) worn by another user, Communication is performed between the sensor terminals (TR), and when communication is successful, a face-to-face contact between users wearing both sensor terminals (TR) is detected. At this time, it is desirable that the sensor terminal (TR) can detect that the two users not only approach but also face each other so as to detect the meeting with high accuracy. That is, it is desirable to be able to discriminate between the case where the user simply sits back-to-back or just sits in the adjacent seat and the case where communication is actually performed while facing each other.

  As one method for enabling discrimination as described above, the sensor terminal (TR) can be configured to be attached to the front of a person. For example, the sensor terminal (TR) can be a name tag type and can be hung from a person's neck by a string. Alternatively, it may be worn on the chest by a clip or the like. In an environment where it is necessary to wear a cap or a protective cap, a sensor terminal (TR) may be fixed or embedded in front of the cap or helmet. When the sensor terminal (TR) is attached to the front part of a person, when the person wearing the sensor terminal (TR) faces, that is, when the front faces each other, the sensor terminal (TR) also has the other sensor. Facing the terminal (TR).

  In FIG. 1, the infrared receiver (TRIR) is shown as comprising four from TRIR1 to TRIR4. These infrared receivers (TRIR1 to TRIR4) do not have a positional relationship in which the users who wear the sensor terminals (TR) completely face each other, but the infrared transmitters ( It is arranged so that infrared light emitted from TRIS can be received by any of the infrared receivers (TRIR1 to TRIR4).

  In addition, infrared transmitters (TRIS) are installed at important points in the tissue, and the infrared receiver (TRIR) can detect infrared rays emitted from the infrared transmitter (TRIS). Each infrared transmitter (TRIS) is uniquely assigned an ID, and the infrared transmitter (TRIS) outputs an infrared light signal including the ID information at a predetermined time interval. When the infrared receiver (TRIR) of the sensor terminal (TR) receives this infrared light signal, the time and position of the sensor terminal (TR) are recorded by recording the reception time and the received ID information. It becomes possible to specify whether or not it was done. That is, the infrared transmitter (TRIS) functions as a beacon.

  In this specification, an example in which a sensor terminal (TR) emits and receives infrared light to detect a face-to-face is described. However, Bluetooth (registered trademark), other short-range wireless communication technologies, or ultrasonic waves are used. A transducer and a sensor may be used. Even in such a case, the mere approach without facing each other and the actual facing, such as narrowing the directivity or using the signal from the sensor that detects the orientation of the sensor terminal (TR) It is desirable to be able to discriminate.

  The acceleration sensor (TRAC) senses acceleration in the X, Y, and Z axis directions. As will be described later, the sensed acceleration information is used to determine the intensity (activity) of the person wearing the sensor terminal (TR) and behavior (for example, walking or standing still).

  The illuminance sensor (TRIL) and the temperature sensor (TRTE) sense illuminance and temperature, respectively. Sensing data obtained by sensing with these illuminance sensors (TRIL) and temperature sensors (TRTE) is used, for example, to determine changes in the environment in which the sensor terminal (TR) is placed. As for the illuminance sensor (TRIL), it is possible to determine whether the sensor terminal (TR) is mounted upside down by providing it on the front side and the back side of the sensor terminal (TR) and comparing the sensing data. it can.

  The sound sensor (TRMI) senses sound. The voice data obtained by sensing can be used, for example, to determine whether a person wearing a sensor terminal (TR) is talking.

  The sensing unit (TRSE) may include any one or more of the sensors described above, or may include a sensor of a type other than those described above. Further, the external input (TROU) shown in FIG. 1 is configured so that an external external sensor (EXTS) can be connected, whereby a new sensor can be added. In addition, various information such as position information, temperature information, humidity information, and the like may be acquired wirelessly or by wire from another device via the external input (TROU).

  The transmission / reception unit (TRSR) transmits and receives data to and from the base station (GW). The connection form between the transmission / reception unit (TRSR) and the base station (GW) may be either wired or wireless, or both. For example, when the user returns to his / her desk and starts desk work or when he / she comes home after finishing his day's work, the user attaches the sensor terminal (TR) to a cradle or the like, and the transmission / reception unit (TRSR) It becomes possible to establish a wired connection with the base station (GW). In this case, the transmission / reception unit (TRSR) responds to, for example, a control command (data transfer request command) transmitted from the base station (GW), and the measurement result obtained by sensing with each sensor described above ( Sensing data) is transmitted to the base station (GW) together with ID information that can identify the sensor terminal (TR).

  When the transmission / reception unit (TRSR) and the base station (GW) are connected wirelessly, the sensing data may be transmitted periodically, or when sensing is performed by each sensor, the sensing data may be transmitted as needed. You may send it. The transmission / reception unit (TRSR) may not only transmit the sensing data but also receive a control command transmitted from the base station (GW). The control information regarding the sensor terminal (TR) is changed according to the received control command.

  The input / output unit (TRIO) functions as an interface between the sensor terminal (TR) and the user. For example, the input / output unit (TRIO) includes an input device such as a button and an output device such as a liquid crystal display, and is configured to be able to acquire information desired by the user and display sensing data. The output device may include an LED indicator, a speaker, a buzzer, a vibration motor, and the like. As the input device, a touch panel provided on a display unit such as a liquid crystal display can be used.

  A control command is received from the base station (GW) via the transmission / reception unit (TRSR), and output to the output device of the input / output unit (TRIO) based on the control command (display, light emission, sound generation, vibration generation, etc.) ) Is executed. In addition, when the user operates the input device of the input / output unit (TRIO), the transmission / reception unit (TRSR) uses the base station (GW) as a control command based on the item selected by the user operating the input device. ).

  The control unit (TRCO) includes a CPU (not shown). When the CPU executes a program stored in the recording unit (TRME), processing such as acquisition of sensor information and output of the acquired sensor information to the base station (GW) is performed. Further, as described later in various embodiments, various determinations based on the acquired sensor information, or analysis of the acquired sensor information, determination based on the analysis result, and the like can be performed. .

  The recording unit (TRME) includes a hard disk, a built-in memory, and the like. The recording unit (TRME) may also be configured so that an external recording device such as an SD (registered trademark) memory card can be attached. The recording unit (TRME) stores a program, sensing data, information described below, and the like.

  In the data format (TRDFI), information specifying the format for transmitting data acquired from each sensor and time information is recorded.

  The remaining battery level (TRBA) records the remaining power level of the sensor terminal (TR). The clock (TRTI) stores the current time measured by a timer built in the sensor terminal (TR). The current time is corrected based on information periodically transmitted from the base station (GW). By periodically correcting the time of the sensor terminal (TR) based on the time information output from the base station (GW), the time among the plurality of sensor terminals (TR) can be synchronized. This makes it possible to align and collate data obtained from different sensor terminals (TR) based on time (time stamp). Since communication is always performed by a plurality of members, it is essential to synchronize the time in order to analyze data from both viewpoints. The time correction is not triggered by the base station (GW), but is triggered by another device, for example, the sensor network server (SS), to the sensor terminal (TR) via the base station (GW). You may send it.

  In the terminal information (TRTR), information unique to the sensor terminal used for uniquely identifying the sensor terminal (TR) is recorded. This information is also referred to as a unique ID and a terminal ID.

− Base station −
A base station (GW) is installed for each area formed by appropriately dividing an organization. FIG. 1 illustrates a base station 2 (GW2) and a base station 3 (GW3) in addition to the base station (GW). Since the description regarding these base stations (GW2, GW3) is the same as that of the base station (GW), it will be omitted hereinafter. Note that the present invention can also be applied when there are an arbitrary number of similar base stations. When any base station uses radio, it establishes connections with 0 to a plurality of sensor terminals (TR) existing within the radio reachable range, and exchanges data. That is, the base station (GW) receives sensing data transmitted from the sensor terminal (TR) that has established the connection wirelessly or by wire. The base station (GW) transmits the received sensing data to the sensor network server (SS) via the network (NW).

  The base station (GW) includes a transmission / reception unit (GWSR), a control unit (GWCO), an input / output unit (GWIO), and a recording unit (GWME). The transmission / reception unit (GWSR) transmits and receives data to and from the sensor terminal (TR). For example, the transmission / reception unit (GWSR) may transmit a control command to the sensor terminal (TR), or may periodically receive sensing data from the sensor terminal (TR). In addition, when the sensor terminal (TR) acquires sensing data, the sensing data may be immediately transmitted from the sensor terminal (TR) to the transmission / reception unit (GWSR). Further, the transmission / reception unit (GWSR) transmits a request to the sensor network server (SS) according to the control command sent from the sensor terminal (TR), and outputs from the sensor network server (SS) in response to the request. The processed data may be transmitted to the sensor terminal (TR). Further, the transmission / reception unit (GWSR) may transmit the item selected by the input device provided in the input / output unit (GWIO) to the sensor terminal (TR) or the sensor network server (SS) as a control command. . Conversely, the transmission / reception unit (GWSR) may receive a control command sent from the sensor network server (SS). The display of the output device is changed according to the received control command.

  The control unit (GWCO) includes a CPU (not shown). When the CPU executes a program stored in the recording unit (GWME), processing such as acquisition of sensor information from the sensor terminal (TR) and transmission of the acquired sensor information to the sensor network server (SS) is performed. .

  The input / output unit (GWIO) includes an input device such as a button or a keyboard and an output device such as a liquid crystal display, and displays information such as a situation in a target area and sensing data. As the input / output unit (GWIO), a touch panel that integrates an input device and an output device may be used.

  The recording unit (GWME) includes a hard disk, a built-in memory, and the like. The recording unit (GWME) may be configured so that an external recording device such as an SD memory card can be attached. The recording unit (GWME) stores programs and sensing data. The sensing data includes data that has received an ID transmitted from an infrared transmitter (TRIS) or another sensor terminal (TR). Furthermore, the recording unit (GWME) includes a data format (GWDFI) and an internal information unit (GWIN).

  The data format (GWDFI) includes information received from the sensor terminal (TR) and information related to the recording format of the time information, and the data is decomposed into each element based on this format.

  The internal information unit (GWIN) stores information related to the base station (GW). The information regarding the base station (GW) includes, for example, a clock (GWTI) (that is, time information) and base station information (GWBA) that is identification information uniquely assigned to each base station (GW).

− Network −
The network (NW) connects a base station (GW), a sensor network server (SS), an application server (AS), and a client (CL) to each other in a wireless or wired form. The network (NW) may be a local area network (LAN), a wide area network (WAN), or any other network.

− Sensor net server −
The sensor network server (SS) receives and stores sensing data sent from the base station (GW), and transmits sensing data based on a request from the application server (AS). The sensor network server (SS) also receives a control command from the base station (GW), and transmits information corresponding to the control command, a response signal, and the like to the base station (GW).

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

  The database unit (SSDB) stores sensing data transmitted from the sensor terminal (TR) via the base station (GW). The sensing data includes data obtained by receiving an ID transmitted from an infrared transmitter (TRIS) or another sensor terminal (TR) with an infrared receiver (TRIR) of the sensor terminal (TR). Further, the database unit (SSDB) stores a response procedure for a control command output from the base station (GW). The database unit (SSDB) may be stored in a hard disk drive (not shown) provided in a recording unit (SSME) described later.

  The control unit (SSCO) includes a CPU (not shown). The CPU executes a program stored in the recording unit (SSME), thereby managing the database unit (SSDB) and processing information transmitted from the application server (AS) and the base station (GW). More specifically, data received from the base station (GW) is stored in the database unit (SSDB).

  The transmission / reception unit (SSSR) transmits and receives data between the base station (GW) and the application server (AS). Specifically, the transmission / reception unit (SSSR) receives the sensing data transmitted from the base station (TR), and the sensing data requested to be transmitted from the application server (AS) to the application server (AS). Send. Moreover, a transmission / reception part (SSSR) transmits the result extracted from the database part (SSDB) to a base station (GW), when a control command is received from a base station (GW).

  The recording unit (SSME) includes a hard disk drive and a built-in memory. The recording unit (SSME) may also be configured so that an external recording device such as an SD memory card can be attached. The recording unit (SSME) stores programs and other information. As described above, a database unit (SSDB) may be provided in the recording unit (SSME). The recording unit (SSME) includes data format (SSDFI) information. The data format (SSDFI) includes information on the format of a file including sensing data and time information transmitted from the base station (GW), and the data is decomposed into each element based on this format, and is stored in the database unit (SSDB). When it is accumulated, it is assigned to the appropriate element.

  In the figure, the sensor network server (SS) is described as being separated from the base station (GW), but may actually be incorporated in the base station (GW).

− Business information management server −
The business information management server (GS) is a server for collecting and processing information (hereinafter referred to as business information) related to business activities of individual personnel in the organization. The business information includes information such as visitor application, conference room use application, and telephone record. The visitor application includes information such as who in the organization receives the visit from the external organization and from what time to what time of the day. When applying for a conference room, the room number of the conference room, what time of day from what time to what time, when the conference room user or outside personnel join the conference, the organization or name to which the person belongs Etc. are included. The telephone record includes information on what day of the week from what time to what time, which telephone in the organization was used and where the telephone call was made. By constructing a database capable of specifying the relationship between the destination telephone number and the organization name or person name, it becomes possible to specify the organization name or person name of the call partner. From the above information, it is possible to extract the face-to-face activity between the personnel in the organization and the personnel who are not wearing the sensor terminal (TR). In the present specification, information capable of extracting the face-to-face activity between a person in the organization and a person not wearing the sensor terminal (TR) is referred to as face-to-face activity information.

− Application server −
The application server (AS) receives business information from the business information management server (GS) and receives sensing data from the sensor network server (SS). The application server (AS) processes and analyzes the received business information and sensing data, and generates content information to be presented to the user (US) through the client (CL). 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 control unit (ASCO), and a recording unit (ASME). Note that the application server (AS) may be integrated with another device such as a client (CL) or a sensor network server (SS).

  The transmission / reception unit (ASSR) transmits / receives information to / from the client (CL), the sensor network server (SS), and the business management server (GS) via the network (NW).

  The recording unit (ASME) includes a hard disk drive, a built-in memory, and the like. The recording unit (ASME) may also be configured so that an external recording device such as an SD memory card can be attached. The recording unit (ASME) includes business information received from the business management server (GS), a program for processing sensing data received from the sensor network server (SS), a program for creating content, created content, Other data related to content creation is stored.

  The control unit (ASCO) includes a CPU (not shown). When the CPU executes a program stored in the recording unit (ASME), processing such as sensing data processing and determination, content generation, and the like are performed. The application server (AS) may be configured integrally with the base station (GW) or the sensor network server (SS).

− Client −
The client (CL) transmits a data processing request to the application server (AS) based on the request from the user, receives the processing result from the application server (AS), and displays the received processing result on the screen. The client (CL) includes a transmission / reception unit (CLSR), a control unit (CLCO), a recording unit (CLME), and an input / output unit (CLIO).

  The input / output unit (CLIO) includes an input device such as a mouse (CLIM) and a keyboard (CLIK), and an output device such as a display (CLWD), and information such as user behavior and face-to-face status belonging to the target area. And sensing data are displayed. As the input / output unit (CLIO), a touch panel that integrates an input device and an output device may be used. An external input / output (CLOU) may be provided to connect other input / output devices.

  The recording unit (CLME) includes a hard disk drive and a built-in memory. The recording unit (CLME) may also be configured so that an external recording device such as an SD memory card can be attached. The recording unit (CLME) records programs, sensing data, and the like. The recording unit (CLME) also stores display contents sent from the application server (AS) and processing results by the control unit (CLCO). The recording unit (CLME) further stores information related to initial condition setting (CLISI). In this initial condition setting (CLISI), conditions such as the screen size are recorded. The contents set by the user are also recorded as the initial condition setting (CLISI).

  The control unit (CLCO) includes a CPU (not shown) that executes a program stored in the recording unit (CLME). The control unit (CLCO) requests information from the application server (AS) based on a request from the user, that is, a user operation of the input / output unit (CLIO). The control unit (CLCO) adjusts the processing result received from the application server (AS), for example, the display size of the display content, and displays it on the output device such as the display (CLWD) of the input / output unit (CLIO) to the user. provide.

  The transmission / reception unit (CLSR) transmits / receives information to / from the application server (AS) via the network (NW).

  In the business management support system described above with reference to FIG. 1, based on the sensing data obtained by sensing with the sensor terminal (TR), Face-to-face with personnel outside the organization, presence / absence of utterances, and the like are determined, and the user's behavior is determined based on the determination results. Hereinafter, a plurality of examples when user behavior determination is performed will be described.

− First embodiment −
In the first embodiment, sensing information from the infrared transmitter (TRIS), infrared receiver (TRIR), and voice sensor (TRMI) in the sensing unit (TRSE) of the sensor terminal (TR) is referred to when determining the user's behavior. Is done. The behavior determination itself is performed in the sensor terminal (TR), and the behavior determination result is transmitted from the sensor terminal (TR) to the sensor network server (SS) via the base station (GW) together with other sensing information. The

  FIG. 2 is a block diagram showing only the part that plays an important role in the first embodiment in the overall system configuration shown in FIG. System components other than those shown in FIG. 2 are the same as those shown in FIG. 2, the same components as those described with reference to FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted.

  In the configuration of the sensor terminal (TR) shown in FIG. 2, the control unit (TRCO) has processing units for face-to-face determination (TRID), FFT processing (TRFT), speech determination (TRSD), and action determination (TRAD). The point is a feature.

  Face-to-face determination (TRID) is based on the result of an attempt to communicate with an infrared transmitter and an infrared receiver provided in another sensor terminal (TR) by an infrared transmitter (TRIS) and an infrared receiver (TRIR). Then, it is determined whether or not the user wearing the sensor terminal (TR) is facing another user in the organization.

  FIG. 3 is a flowchart illustrating a processing example of face-to-face determination (TRID). In S3-1, infrared light is emitted from the infrared transmitter (TRIS). The infrared light is luminance-modulated and carries ID information of the sensor terminal (TR). That is, the infrared ID is transmitted in S3-1. When another sensor terminal (TR) is present nearby, this infrared light is detected by an infrared receiver (TRIR) provided in the other sensor terminal (TR). Below, when distinguishing a self-terminal (TR) and another sensor terminal (TR), another sensor terminal (TR) is called a partner terminal (TR). When the counterpart terminal (TR) receives the infrared ID transmitted in S3-1, the counterpart terminal (TR) outputs a response signal including the ID of the counterpart terminal (TR). An attempt to receive this response signal (infrared ID) is made in S3-2.

  The processes of S3-1 and S3-2 described above are repeatedly performed over a predetermined time, and in S3-4, the same infrared ID (this is the infrared ID output from the counterpart terminal (TR)) is set for a predetermined time. It is determined whether or not the number of times detected in (T seconds) is Λ times or more. If the determination in S3-4 is affirmed, the process proceeds to S3-5, and it is determined that the meeting has been performed for the T seconds, that is, the T seconds are the conversation section. On the other hand, if the determination in S3-4 is negative, the process branches to S3-6, and it is determined that the T second is a non-face-to-face section.

  When the process of S3-5 or S3-6 ends, the face-to-face determination is completed and the process returns. The face-to-face determination process illustrated in FIG. 3 makes it possible to more accurately discriminate between the case of simply passing the counterpart terminal (TR) and the case of actually meeting.

  The FFT process (TRFT) derives a frequency spectrum by performing a fast Fourier transform process on an audio signal obtained by sensing with an audio sensor (TRMI). For example, in a voice sensor (TRMI), sampling is performed at a sampling rate of 8 kHz, and a series of voice signals obtained in this way are separated by a time window of 128 milliseconds, and 1024 obtained (= 8,000 × 0.128). ) Is subjected to FFT processing. As a result, a plurality of spectral peaks are obtained unless the sampled target sound is a pure tone.

  Speech determination (TRSD) attempts to detect spectral components peculiar to human voice based on a set of spectral peaks obtained by processing by FFT processing (TRFT). The detection is repeated, and when a spectral component peculiar to a human voice is detected over a certain time (for example, several seconds) or more, it can be determined that an utterance has occurred.

  FIG. 4 shows an example of processing until the speech data obtained by sensing (sampling) is subjected to FFT processing and attempting to detect spectral components peculiar to human voice.

  In S4-1, audio sampling is performed by the audio sensor (TRMI), and audio data is temporarily recorded in the recording unit (TRME). In S4-2, the audio data is subjected to FFT processing. As a result, a set of spectral peaks is extracted. The process in S4-2 corresponds to the process in the FFT process (TRFT).

  The set of spectral peaks obtained by the process of S4-2 includes various spectral peaks. Among these, by the process of S4-3, a predetermined upper number (X) of spectral peaks are extracted together with their frequency values from those having a large energy value (intensity). Since a human voice is emitted in the vicinity of the sensor terminal (TR), the voice sensor (TRMI) captures the human voice as a relatively loud sound. Therefore, by the process of S4-3, it becomes possible to reduce the influence of the sound generated by rubbing the sensor terminal (TR) with the user's clothes, the air conditioning sound, and the like.

  A process of converting the frequency unit of the extracted spectrum peak into hertz [Hz] is performed in S4-4. Among these spectrum peaks, spectrum peaks less than a predetermined frequency (Y [Hz]) are discarded. By this process, only the spectrum peak in the band assumed as the frequency component of the human voice is extracted, so that it is possible to reduce the processing load required for the subsequent processing and to increase the human voice detection accuracy. At this time, a spectrum peak exceeding a predetermined frequency may be discarded.

  The processing after S4-6 is performed on the spectrum peak left after the above processing, and detection of a spectrum pattern peculiar to human voice is attempted. In S4-6, among the spectrum peaks left as a result of the processing in S4-5, the frequency of the spectrum peak having the lowest frequency (lowest) is multiplied by 2, and the spectrum having the second smallest frequency (low frequency). It is determined whether or not the absolute value of the difference from the peak frequency is smaller than a predetermined determination criterion [ε]. That is, assuming that the spectrum peak of the lowest frequency corresponds to the fundamental frequency of the human voice, it is determined in S4-6 whether or not there is a spectrum peak close to twice the fundamental frequency. If the determination in S4-6 is affirmative, the process proceeds to S4-7, and if negative, the process proceeds to S4-9.

  In S4-7, which is a branch destination when the determination in S4-6 is affirmed, among the spectrum peaks left as a result of the processing in S4-5, the frequency of the spectrum peak having the lowest (lowest) frequency is 3 It is determined whether or not the absolute value of the difference between the value obtained by multiplying by and the frequency of the third smallest (third lowest) spectrum peak is smaller than a predetermined criterion [ε]. That is, assuming that the spectrum peak of the lowest frequency corresponds to the fundamental frequency of human voice, it is determined in S4-7 whether there is a spectrum peak close to three times the fundamental frequency. If the determination in S4-7 is affirmed, the process proceeds to S4-8, and if not, the process proceeds to S4-9.

  In S4-8, which is a branch destination when the determination in S4-7 is affirmed, the frequency of the spectrum peak having the lowest frequency (lowest) among the spectrum peaks left as a result of the processing in S4-5 is basically the same. It is determined that a spectrum pattern that is a frequency, that is, a human voice-specific spectral pattern is included. Since human voice includes the lowest fundamental frequency, twice and three times that frequency, it is possible to detect a spectral pattern peculiar to human voice by the determination process of S4-6 and S4-7. Become. After the process of S4-8, the fundamental frequency detection process is completed and the process returns.

  In S4-9, which is the branch destination when the determinations in S4-6 and S4-7 are denied, the frequency is the second smallest among the spectrum peaks left as a result of the processing in S4-5 (second. Determines whether the absolute value of the difference between the frequency of the (low) spectral peak multiplied by 3 and the frequency of the third smallest (third lowest) spectral peak is smaller than a predetermined criterion [ε] Is done. That is, assuming that the spectrum peak of the second lowest frequency corresponds to the fundamental frequency of the human voice, it is determined in S4-9 whether there is a spectrum peak close to twice the fundamental frequency. If the determination in S4-9 is affirmed, the process proceeds to S4-10, and if not, the process proceeds to S4-12.

  In S4-10, which is the branch destination when the determination in S4-9 is affirmed, among the spectrum peaks left as a result of the processing in S4-5, the spectrum peak having the second lowest frequency (second lowest) It is determined whether or not the absolute value of the difference between the frequency obtained by multiplying 3 by 3 and the frequency of the fourth smallest (fourth lowest) spectrum peak is smaller than a predetermined criterion [ε]. That is, assuming that the spectrum peak of the second lowest frequency corresponds to the fundamental frequency of human voice, it is determined in S4-10 whether or not there is a spectrum peak close to three times the fundamental frequency. If the determination in S4-10 is affirmed, the process proceeds to S4-11. If the determination is negative, the process proceeds to S4-12.

  In S4-11 which is a branch destination when the determination in S4-10 is affirmed, the spectrum peak having the second lowest frequency (second lowest) among the spectrum peaks left as a result of the processing in S4-5. Is a fundamental frequency, that is, it is determined that a spectrum pattern peculiar to human voice is included. After the process of S4-11, the basic frequency detection process is finished and the process returns.

  In S4-12, which is a branch destination when the determinations in S4-9 and S4-10 are denied, there is no fundamental frequency in the spectrum peak left as a result of the processing in S4-5, that is, it is peculiar to human voice. It is determined that the spectrum pattern is not included. After the process of S4-12, the basic frequency detection process is finished and the process returns.

  In the above processing, the determination criteria [ε] in the determination processes of S4-6, S4-7, S4-9, and S4-10 are all set to the same value or different values. Good. Further, although an example has been described in which the fundamental frequency detection process is aborted when the determinations of S4-9 and S4-10 are both denied, it is also possible to repeatedly perform the same determination process as described above.

  By the way, in the determination process of S4-6, among the spectrum peaks left as a result of the process of S4-5, the frequency of the spectrum peak with the lowest frequency multiplied by 2 and the spectrum peak with the second lowest frequency. The example in which it is determined whether or not the absolute value of the difference from the frequency is smaller than the predetermined determination criterion [ε] has been described. If the voice to be analyzed is a human voice, but it happens to have noise in a frequency band close to that of a human voice, the spectrum peak with the second lowest frequency is not from the human voice, but from the noise. May be. In that case, it is conceivable that the determination of S4-6 is denied and a spectrum peak derived from a human voice cannot be detected. Explaining this point, since the user wears the sensor terminal (TR), the voice of the user can be collected relatively loudly. That is, the loudness of a person (user) voice sensed by the voice sensor (TRMI) is larger than that of other sounds (noise). Accordingly, the processing from S4-3 to S4-5 leaves a spectrum peak derived from the human voice and eliminates noise components. Therefore, in the determinations of S4-6, S4-7, S4-9, and S4-10 The possibility of detecting spectral peaks derived from human voice increases.

  If the sound sensor (TRMI) tends to pick up sounds other than human voice due to the directivity and sensitivity of the sound sensor (TRMI), the process of S4-6 may be changed as follows. That is, a process of searching for a spectrum peak having a frequency close to the one obtained by multiplying the frequency of the spectrum peak having the lowest frequency by 2 from the spectrum peaks left as a result of the process of S4-5 may be performed. Specifically, in S4-6, it may be determined [whether there is a spectrum peak whose frequency is less than ε with an absolute value of a difference from 2 × (minimum frequency)]. In this way, even if there is a noise-derived spectrum peak between the spectrum peak at the fundamental frequency and the spectrum peak at twice the fundamental frequency, it can be ignored. The determination process in S4-7, S4-9, and S4-10 is the same.

  As a result of the above processing, it is determined whether or not a spectrum pattern peculiar to a human voice exists in the sound data obtained by detection with the sound sensor (TRMI). This determination is performed on a spectrum peak obtained by performing FFT in a time window of 128 milliseconds in the above-described example. If the process shown in FIG. 4 is repeatedly performed and the fundamental frequency is present in a certain number of times within a predetermined time length, it is possible to determine that the time zone is a time section in which speech is performed. . That is, speech determination (TRSD) is performed.

  The action determination (TRAD) determines the action of the user wearing the sensor terminal (TR) based on the determination result in the face-to-face determination (TRID) and the determination result in the utterance determination (TRSD).

  FIG. 5 is a diagram conceptually showing processing performed inside the sensor terminal (TR) in the first embodiment of the present invention.

  Infrared light reception (IRD) is performed by the infrared receiver (TRIR), and based on the detection result, the face-to-face determination (FJ) described with reference to FIG. 3 is performed, and face-to-face presence (Fe) or no face-to-face A determination result of (Fn) is obtained.

  When the determination of no-face-to-face (Fn) is obtained, the voice data obtained by voice detection (VCD) by the voice sensor (TRMI) is subjected to FFT processing (FFTC), and a spectrum peak value is obtained (FFTP) Is done. The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG. Note that the voice detection (VCD) process may always be performed regardless of the result of the face-to-face determination (FJ).

  Subsequently, fundamental frequency detection (FF) processing is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. An utterance determination (VJ) is performed based on the presence / absence, length, continuity, etc. of the time interval in which it is determined that the utterance has been performed by continuously performing the fundamental frequency detection (FF) process. It is determined that there is no (Vn) or speech is present (Ve).

A combination of the above judgments, that is, (1) no meeting (Fn) and no speech (Vn),
(2) Face-to-face (Fn) and speech present (Ve)
(3) Or facing (Fe)
In the action determination (AJ), the user wearing the sensor terminal (TR) is in a non-face-to-face state (Fnn), faces an outsider (OFe), or faces an insider Whether (IFe) is present is determined. That is, when the meeting is detected by the infrared receiver (TRIR) (Fe), it is determined that the person is facing the insider (IFe) regardless of the result of the speech determination (VJ). On the other hand, when it is determined that there is an utterance (Ve) in a state where no facing by the infrared receiver (TRIR) is detected (Fn), it is determined that it is facing an outsider (OFe). Then, when it is determined that there is no speech (Vn) in a state where no facing by the infrared receiver (TRIR) is detected (Fn), it is determined that there is no facing (Fnn). Note that the processing related to speech determination (JV) and behavior determination (AJ) does not necessarily have to be performed in real time, and can be performed when necessary based on data accumulated in the past. .

  As described above, according to the first embodiment of the present invention, in addition to the faces of users wearing sensor terminals (TR), the result of analyzing the voice data and determining the presence or absence of utterances By referring to it, it is possible to perform a behavior determination including the face-to-face contact between the in-organization personnel and the non-organization personnel in addition to the face-to-face contact between the users wearing the sensor terminals (TR).

− Second Embodiment −
In the second embodiment, an infrared transmitter (TRIS), an infrared receiver (TRIR), a sound sensor (TRMI), and an acceleration sensor (TRAC) are used in the sensing unit (TRSE) of the sensor terminal (TR). The obtained sensing information is referred to when determining the user's behavior. The behavior determination itself is performed in the sensor terminal (TR), and the behavior determination result is transmitted from the sensor terminal (TR) to the sensor network server (SS) via the base station (GW) together with other sensing information. The

  FIG. 6 is a block diagram showing only the part that plays an important role in the second embodiment in the overall system configuration in FIG. System components other than those shown in FIG. 6 are the same as those shown in FIG. In FIG. 6, the same components as those described with reference to FIGS. 1 and 2 are denoted by the same reference numerals, and detailed description thereof is omitted.

  In the configuration of the sensor terminal (TR) shown in FIG. 6, the control unit (TRCO) has face-to-face determination (TRID), FFT processing (TRFT), speech determination (TRSD), motion determination (TRMD), and action determination (TRAD). The feature is that each processing section is provided.

  Face-to-face determination (TRID) is a communication between an infrared transmitter (TRIS) and an infrared receiver (TRIR) provided in another sensor terminal (TR) by an infrared transmitter (TRIS) and an infrared receiver (TRIR). Based on the result of the attempt, whether or not the user wearing the sensor terminal (TR) and the other user (inside person) in the organization face each other is determined. The processing procedure is the same as that described with reference to FIG. 3 in the first embodiment.

  In FFT processing (TRFT) and speech determination (TRSD), processing similar to that described with reference to FIG. 4 in the first embodiment is performed. The motion determination (TRMD) determines the motion of the user wearing the sensor terminal (TR) based on the change in acceleration detected by the acceleration sensor (TRAC). As described above, the acceleration sensor (TRAC) can detect a three-dimensional movement. For example, whether the user is walking or desk work by analyzing the magnitude, change pattern, direction of acceleration change, etc. that occur in the direction along the user's front, back, left, right, up and down It is possible to discriminate whether it is moving actively or the like. In addition, by performing motion determination (TRMD) when the user is in a face-to-face state, it is also possible to determine whether it is a positive face-to-face or a negative face-to-face.

  FIG. 7 is a diagram conceptually showing processing performed inside the sensor terminal (TR) in the second embodiment of the present invention.

  Infrared light reception (IRD) is performed by the infrared receiver (TRIR), and based on the detection result, the face-to-face determination (FJ) described with reference to FIG. 3 is performed, and face-to-face presence (Fe) or no face-to-face A determination result of (Fn) is obtained.

  When the determination of no-face-to-face (Fn) is obtained, the voice data obtained by voice detection (VCD) by the voice sensor (TRMI) is subjected to FFT processing (FFTC), and a spectrum peak value is obtained (FFTP) Is done. The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG. The voice detection (VCD) may be performed regardless of the result of the face-to-face determination (FJ), as described in the first embodiment.

  Subsequently, fundamental frequency detection (FF) processing is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. The basic frequency detection (FF) process is continuously performed, and the speech determination (VJ) is performed based on the presence or absence of the time period in which the speech is performed, and there is no speech (Vn) or speech is present (Ve). Determined.

A combination of the above judgments, that is, (1) no meeting (Fn) and no speech (Vn),
(2) Face-to-face (Fn) and speech present (Ve)
(3) Or facing (Fe)
It is possible to classify the face-to-face (OFn), the face-to-face (OFe), and the face-to-face (IFe). That is, when the meeting is detected by the infrared receiver (TRIR) (Fe), it is determined that the person is facing the insider (IFe) regardless of the result of the speech determination (VJ). On the other hand, when it is determined that there is an utterance (Ve) in a state where no facing by the infrared receiver (TRIR) is detected (Fn), it is determined that it is facing an outsider (OFe). Then, when it is determined that there is no speech (Vn) in a state where no facing by the infrared receiver (TRIR) is detected (Fn), it is determined that there is no facing (Fnn).

  Furthermore, based on the change in acceleration detected by the acceleration sensor (TRAC), a process for determining the movement of the user wearing the sensor terminal (TR), that is, a movement determination process (MJ) is performed. The motion determination (MJ) is performed based on, for example, whether or not an acceleration or a change in acceleration is greater than or equal to a threshold value during a certain time. If this acceleration or change in acceleration is greater than or equal to a threshold, it is determined that there is motion (Me), and if it is less than the threshold, it is determined that there is no motion (Mn). It is determined that the user is moving actively (Me). On the other hand, when the user is quietly listening to the face-to-face partner or is concentrated alone, it is determined that there is no movement (Mn).

The sensor terminal (TR) is based on the combination of the above-mentioned classification of face-to-face (Fnn), face-to-face (OFe), face-to-face (IFe) with the insider, and the judgment result of motion judgment (MJ). The action determination (AJ) of the user who wears is performed. And
(1) When there is a meeting with an insider (IFe) and the motion determination (MJ) result is a movement present (Me), it is determined that the insider is actively facing (IFMe),
(2) When there is a meeting with an outsider (OFe) and the movement determination (MJ) result is a movement present (Me), it is determined that the person is actively facing (OFMe) with the outsider,
(3) When there is a meeting with an insider (IFe) and the motion determination (MJ) result is no movement (Mn), it is determined as a negative facing state (IFMn) with the insider,
(4) When there is a meeting with an outsider (OFe) and the motion determination (MJ) result is no movement (Mn), it is determined as a negative facing state (OFMn) with the outsider,
(5) When there is no meeting (Fnn) and the motion determination (MJ) result is motion present (Me), it is determined as the personal work state (Lme),
(6) When there is no meeting (Fnn) and the result of motion determination (MJ) is no motion (Mn), it is determined to be in a concentrated state (Lmn).

  As described above, according to the second embodiment of the present invention, in addition to the faces of users wearing sensor terminals (TR), the result of analyzing the voice data and determining the presence or absence of utterances By referring to it, it is possible to perform a behavior determination including the face-to-face contact between the in-organization personnel and the non-organization personnel in addition to the face-to-face contact between the users wearing the sensor terminals (TR). In addition, by referring to the detection result of the acceleration sensor (TRAC), it is possible to determine the aggressiveness of the meeting itself or to determine the behavior of the personnel in the organization when there is no meeting.

  In the first and second embodiments described above, the example in which the speech determination (VJ) and the behavior determination (AJ) are performed by the sensor terminal (TR) has been described. However, the speech determination (VJ) and the behavior determination (AJ) are described. ) May be performed in a distributed manner within an information processing device other than the sensor terminal (TR), for example, a sensor network server (SS) or an application server (AS), or a plurality of information processing devices. Good. At that time, the speech determination (VJ) may be performed by the sensor terminal (TR), and the behavior determination (AJ) may be performed by an information processing apparatus other than the sensor terminal (TR). Also, the motion determination (MJ) in the second embodiment may be performed by an information processing apparatus other than the sensor terminal (TR).

− Third embodiment −
In the third embodiment, sensing information obtained by using an infrared transmitter (TRIS), an infrared receiver (TRIR), and a voice sensor (TRMI) in the sensing unit (TRSE) of the sensor terminal (TR) is the user. It is referred to when determining the action. In addition, sensing data may be obtained from an external sensor (EXTS) via an external input (TROU) as necessary. Further, an infrared receiver (TRIR) may receive an infrared signal output from an infrared transmitter (ITR).

  The action determination (ASAD) is performed on the application server (AS) side. At this time, the application server (AS) acquires the face-to-face activity information stored in the business management server (GS), and refers to the face-to-face activity information in the action determination (ASAD) process. The face-to-face activity information is information that can extract the face-to-face activity between the personnel in the organization and the personnel who are not wearing the sensor terminal (TR), as described above.

  The action determination result may be transmitted to the sensor network server (SS) via the network (NW) and stored, or content is generated in the application server (AS) based on a request from the client (CL). In some cases, the behavior determination result may be referred to and then discarded.

  FIG. 8 is a block diagram showing only the part that plays an important role in the third embodiment in the overall system configuration shown in FIG. System components other than those shown in FIG. 8 are the same as those shown in FIG. In FIG. 8, the same components as those described with reference to FIGS. 1 and 2 are denoted by the same reference numerals, and detailed description thereof is omitted.

  The configuration of the sensor terminal (TR) is characterized in that the control unit (TRCO) has processing units for face-to-face determination (TRID) and FFT processing (TRFT). Further, the configuration of the application server (AS) is characterized in that the control unit (ASCO) has processing units for activity information acquisition (ASAR), speech determination (ASSD), and action determination (ASAD).

  First, the characteristic part of the configuration of the sensor terminal (TR) will be described. In-person determination (TRID) is performed by infrared transmission provided in another sensor terminal (TR) by an infrared transmitter (TRIS) and an infrared receiver (TRIR). Based on the result of attempting communication between the machine (TRIS) and the infrared receiver (TRIR), it is determined whether or not the user wearing the sensor terminal (TR) and other users in the organization are facing each other. The processing procedure is the same as that described with reference to FIG. 3 in the first embodiment.

  The FFT process (TRFT) performs the processes of S4-2 and S4-3 during the process described with reference to FIG. 4 in the first embodiment. The processing results in the face-to-face determination (TRID) and FFT processing (TRFT) are transmitted to the sensor network server (SS) via the base station (GW) and stored.

  Next, features of the configuration of the application server (AS) will be described. The activity information acquisition (ASAR) accesses the business management server (GS) and acquires the face-to-face activity information of the personnel in the organization whose behavior is to be analyzed. Specifically, the ID information (may be a name) for identifying the personnel within the organization whose behavior is to be analyzed, the period (year / month / day, time) for which information is required, the type of necessary face-to-face activity information, etc. (AS) to the business management server (GS). The business management server (GS) extracts relevant information and transmits it to the application server (AS).

  The speech determination (ASSD) acquires necessary voice data from the sensor network server (SS), performs the processes from S4-4 to S4-12 during the process described with reference to FIG. Attempts to detect spectral components (fundamental frequency) peculiar to The detection is repeated, and when it is detected that a spectral component peculiar to a human voice exists continuously or intermittently for a certain time (for example, several seconds) or more, it is determined that an utterance has occurred.

  In the action determination (ASAD), necessary face-to-face data is acquired from the sensor network server (SS). Then, the action determination process is performed by referring to the utterance determination result in the utterance determination (ASSD) and the face-to-face activity information acquired by the activity information acquisition (ASAR) from the business information management server (GS) together with the face-to-face data. .

  FIG. 9 is a diagram conceptually showing processing performed in the sensor terminal (TR) and the application server (AS) in the third embodiment of the present invention. In FIG. 9, processing performed on the side of the sensor terminal (TR) from the portion separated by two parallel broken lines drawn in the horizontal direction is performed on the side of the application server (AS). The processing performed on the side is shown.

  First, the processing performed on the sensor terminal (TR) side will be described. Infrared reception (IRD) is performed by the infrared receiver (TRIR), and the meeting described with reference to FIG. 3 based on the detection result. Determination (FJ) is performed, and a determination result of facing (Fe) or not facing (Fn) is obtained. The face-to-face determination result is sent to the sensor network server (SS) as face-to-face data together with information such as the user ID or terminal ID and the face-to-face detection date and time (DTF).

  When the determination of no-face-to-face (Fn) is obtained, the voice data obtained by voice detection (VCD) by the voice sensor (TRMI) is subjected to FFT processing (FFTC), and a spectrum peak value is obtained (FFTP) Is done. The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG. The obtained set of spectrum peak values is transmitted as audio data to the sensor network server (SS) together with information such as the user ID or terminal ID and the audio detection date (DTV).

  Next, processing performed on the application server (AS) side will be described. Based on the content request issued from the client (CL), audio data corresponding to the desired date and time of the desired user is acquired from the sensor network server (SS) (DRV), and the basic frequency detection (FF) is performed on the audio data. ) Is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. An utterance determination (VJ) is performed based on the presence / absence, length, continuity, etc. of the time interval in which it is determined that the utterance has been performed by continuously performing the fundamental frequency detection (FF) process. It is determined that there is no (Vn) or speech is present (Ve).

Further, face-to-face data corresponding to a desired date and time of a desired user is acquired from the sensor network server (SS) (DRF). Then, based on the result (Vn, Ve) of the speech determination (VJ) and the content (Fe, Fn) of the face-to-face data acquired by the face-to-face data reception (DRF), the face-to-face state is classified as follows. Is possible. That is,
(1) No meeting (Fn) and no utterance (Vn)
(2) Face-to-face (Fn) and speech present (Ve)
(3) Or facing (Fe)
It is possible to classify the face-to-face (OFn), the face-to-face (OFe), and the face-to-face (IFe).

  In addition, visit information (OD), conference room usage data (RD), and telephone data (TD) are acquired from the business information management server (GS) as face-to-face activity information (DRAI). Based on (Fnn, OFe, IFe), action determination (AJ) processing is performed. The visit data (OD) includes information such as the name, affiliation, visit time, exit time, name of the visitor who visited the organization (external). The conference room use data (RD) includes information such as a conference room number, a user name, a use date, and a use time zone. The telephone data (TD) includes information such as the start date / time, usage time, and destination of a telephone call made using a certain telephone in the organization. Using these pieces of information as additional information, more detailed action determination (AJ) can be performed.

  In the example shown in FIG. 9, as a result of the action determination (AJ), another action (OA), an insider face-to-face (IFe), an outsider face-to-face (OFe), or a non-face-to-face state (Fnn) Determined. When processing the action determination (AJ), refer to the company data (OD), and if it is found that an outsider's visit was received during a time period when no meeting was detected, there was a meeting with an outsider (OFe) Judgment is possible. When the user forgets to wear the sensor terminal (TR) and attends a meeting in the department, the meeting with the insider cannot be detected. However, by referring to the conference room usage data (RD), it can be determined that there is a meeting with an insider. In addition, referring to the telephone data (TD), if it is found that a call is made with an outsider during a time period determined to be non-face-to-face (Fn), the telephone call is in progress, that is, another action (OA). ) Can be determined.

  As described above, according to the third embodiment of the present invention, in addition to facing each other of users wearing sensor terminals (TR), that is, in-organization personnel, there is a relationship between in-organization personnel and non-organization personnel. It is possible to perform action determination including face-to-face. In addition, it is possible to perform the action determination in more detail by referring to the face-to-face activity information when determining the action.

  Further, by performing the speech determination processing on the application server (AS) side, it is possible to reduce the processing load on the sensor terminal (TR) and extend the battery life. At this time, it is possible to significantly reduce the amount of data communication compared to the case where audio data is transmitted as it is by transmitting the audio data subjected to FFT processing (FFTC) to the sensor network server (SS).

-Fourth embodiment-
In the fourth embodiment, an infrared transmitter (TRIS), an infrared receiver (TRIR), an acceleration sensor (TRAC), and an audio sensor (TRMI) are used in the sensing unit (TRSE) of the sensor terminal (TR). The obtained sensing information is referred to when determining the user's behavior. In addition, sensing data may be obtained from an external sensor (EXTS) via an external input (TROU) as necessary. Further, an infrared receiver (TRIR) may receive an infrared signal output from an infrared transmitter (ITR).

  The behavior determination is performed on the application server (AS) side. At this time, the application server (AS) acquires face-to-face activity information stored in the business management server (GS), and refers to the face-to-face activity information in the action determination process.

  The action determination result may be transmitted to the sensor network server (SS) via the network (NW) and stored, or content is generated in the application server (AS) based on a request from the client (CL). In some cases, the behavior determination result may be referred to and then discarded.

  FIG. 10 is a block diagram showing only a portion that plays an important role in the fourth embodiment in the overall system configuration shown in FIG. System components other than those shown in FIG. 10 are the same as those shown in FIG. 10, the same components as those described with reference to FIGS. 1 and 2 are denoted by the same reference numerals, and detailed description thereof is omitted.

  The configuration of the sensor terminal (TR) is characterized in that the control unit (TRCO) has processing units for face-to-face determination (TRID) and FFT processing (TRFT). In addition, the configuration of the application server (AS) is characterized in that the control unit (ASCO) has processing units for activity information acquisition (ASAR), speech determination (ASSD), motion determination (ASMD), and behavior determination (ASAD). It is.

  First, the characteristic part of the configuration of the sensor terminal (TR) will be described. In-person determination (TRID) is performed by infrared transmission provided in another sensor terminal (TR) by an infrared transmitter (TRIS) and an infrared receiver (TRIR). Based on the result of attempting communication between the machine (TRIS) and the infrared receiver (TRIR), it is determined whether or not the user wearing the sensor terminal (TR) and other users in the organization are facing each other. The processing procedure is the same as that described with reference to FIG. 3 in the first embodiment.

  The FFT process (TRFT) performs the processes of S4-2 and S4-3 during the process described with reference to FIG. 4 in the first embodiment. The processing result in the face-to-face determination (TRID) and FFT processing (TRFT) is transmitted to the sensor network server (SS) via the base station (GW) and stored together with the acceleration detection result detected by the acceleration sensor (TRAC). The

  Next, features of the configuration of the application server (AS) will be described. The activity information acquisition (ASAR) accesses the business management server (GS) and acquires the face-to-face activity information of the personnel in the organization whose behavior is to be analyzed. Specifically, ID information (may be a name) that identifies personnel in the organization whose behavior is to be analyzed, a period (year / month / day, time) for which information is required, and the type of face-to-face activity information required by the application server ( AS) to the business management server (GS). The business management server (GS) transmits the corresponding information to the application server (AS).

  The speech determination (ASSD) acquires necessary voice data from the sensor network server (SS), performs the processes from S4-4 to S4-12 during the process described with reference to FIG. Attempts to detect spectral components (fundamental frequency) peculiar to The detection is repeated, and when it is detected that a spectral component peculiar to a human voice exists continuously or intermittently for a certain time (for example, several seconds) or more, it is determined that an utterance has occurred.

  The motion determination (ASMD) acquires necessary acceleration data from the sensor network server (SS), and determines the motion of the user in the analysis target time zone. For example, the motion determination is performed based on whether or not an acceleration or a change in acceleration is greater than or equal to a threshold value during a certain time. If this acceleration or change in acceleration is greater than or equal to a threshold, it is determined that there is motion, and if it is less than the threshold, it is determined that there is no motion. It is determined that the user is moving when the user is actively moving. On the other hand, when the user is quietly listening to the face-to-face partner or is concentrated alone, it is determined that there is no movement (Mn). It is also possible to make a motion determination on the sensor terminal (TR) side and send the result to the sensor network server (SS). In that case, the motion determination (ASMD) can determine the presence or absence of the user's motion in a given time zone by referring to the log of the motion determination result acquired from the sensor network server.

  In the action determination (ASAD), necessary face-to-face data is acquired from the sensor network server (SS). Then, the speech determination result in the speech determination (ASSD), the motion determination result in the motion determination (ASMD), and the face activity information acquired by the activity information acquisition (ASAR) from the business information management server (GS) The action determination process is performed with reference to the face-to-face data.

  FIG. 11 is a diagram conceptually showing processing performed in the sensor terminal (TR) and the application server (AS) in the fourth embodiment of the present invention. In FIG. 11, processing performed on the side of the sensor terminal (TR) from the portion separated by two parallel broken lines drawn in the horizontal direction is performed on the side of the application server (AS). The processing performed on the side is shown.

  First, the processing performed on the sensor terminal (TR) side will be described. Infrared reception (IRD) is performed by the infrared receiver (TRIR), and the meeting described with reference to FIG. 3 based on the detection result. Determination (FJ) is performed, and a determination result of facing (Fe) or not facing (Fn) is obtained. The face-to-face determination result is sent to the sensor network server (SS) as face-to-face data together with information such as the user ID or terminal ID and the face-to-face detection date and time (DTF).

  When the determination of no-face-to-face (Fn) is obtained, the voice data obtained by voice detection (VCD) by the voice sensor (TRMI) is subjected to FFT processing (FFTC), and a spectrum peak value is obtained (FFTP) Is done. The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG. The obtained set of spectrum peak values is transmitted as audio data to the sensor network server (SS) together with information such as the user ID or terminal ID and the audio detection date (DTV). The voice detection (VCD) may be performed regardless of the result of the face-to-face determination (FJ), as described in the first embodiment.

  In the acceleration sensor (TRAC), acceleration detection (ACD) is performed, and the obtained acceleration data is transmitted to the sensor network server (SS) together with information such as a user ID or a terminal ID and an acceleration detection date (DTA).

  Next, processing performed on the application server (AS) side will be described. Audio data corresponding to a desired date and time of a desired user is acquired from the sensor network server (SS) based on a content request issued from the client (CL) (DRV), and a basic frequency detection ( FF) is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. The basic frequency detection (FF) process is continuously performed, and the speech determination (VJ) is performed based on the presence or absence of the time period in which the speech is performed, and there is no speech (Vn) or speech is present (Ve). Determined.

  Meanwhile, face-to-face data corresponding to a desired date and time of a desired user is acquired from the sensor network server (SS) (DRF). Further, acceleration data corresponding to the user and the date and time is acquired from the sensor network server (SS) (DRA).

First, based on the result (Vn, Ve) of the above speech determination (VJ) and the content (Fe, Fn) of the face-to-face data acquired by face-to-face data reception (DRF), the face-to-face state is classified as follows: Is possible. That is,
(1) No meeting with insider (Fn) and no utterance (Vn)
(2) No face-to-face with insiders (Fn) and utterances (Ve)
(3) Facing with insiders (Fe)
It is possible to classify the face-to-face (OFn), the face-to-face (OFe), and the face-to-face (IFe).

  Subsequently, based on the acceleration data, a motion determination (MJ) with motion (Me) or no motion (Mn) is performed at the date and time of determination.

  In addition, visit information (OD), conference room usage data (RD), and telephone data (TD) are acquired from the business information management server (GS) as face-to-face activity information (DRAI). Action determination (AJ) processing is performed based on the classification (Fnn, OFe, IFe) and the motion determination result (Me, Mn).

  In the example shown in FIG. 11, as a result of the action determination (AJ), other actions (OA), insider positively facing (IFMe), outsider positively facing (OFMe), insider negatively facing ( IFMn), negative face-to-face (OFMn), personal work (Lme), or concentrated state (Lmn). At this time, as described in the third embodiment, by referring to the visit data (OD), the conference room usage data (RD), and the telephone data (TD) in the action determination (AJ) processing, It is possible to make a more detailed action determination with reference to information that cannot be obtained only from the sensor terminal (TR).

  As described above, according to the fourth embodiment of the present invention, in addition to the faces of users wearing sensor terminals (TR), that is, the faces of insiders, the faces of insiders and outsiders are included. It becomes possible to perform action determination. In addition, the behavior determination can be performed in more detail by referring to the acceleration data and the face-to-face activity information when determining the behavior.

  Further, by performing the speech determination process and the motion determination process on the application server (AS) side, it is possible to reduce the processing load of the sensor terminal (TR) and extend the battery life. Further, by transmitting the FFT data (FFTC) as the voice data to the sensor network server (SS), it is possible to significantly reduce the data communication amount as compared with the case of transmitting the voice data as it is. This is the same as the third embodiment.

  As described above, in the fourth and fifth embodiments, the example in which the utterance determination and the behavior determination are performed by the application server (AS) has been described. However, these processes may be performed by another information processing apparatus. Further, a plurality of information processing apparatuses may be used, and utterance determination may be performed by one information processing apparatus and behavior determination may be performed by the other information processing apparatus.

-Fifth embodiment-
In the fifth embodiment, sensing information by the voice sensor (TRMI) is referred to when determining the user's behavior in the sensing unit (TRSE) of the sensor terminal (TR). Further, the behavior determination itself is performed in the sensor terminal (TR), and the behavior determination result is transmitted from the sensor terminal (TR) to the sensor network server (SS) via the base station (GW).

  FIG. 12 is a block diagram showing only a part that plays an important role in the fifth embodiment in the overall system configuration shown in FIG. The system components other than those shown in FIG. 12 are the same as those shown in FIG. In FIG. 12, the same components as those described with reference to FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted.

  The configuration of the sensor terminal (TR) shown in FIG. 12 is characterized in that the control unit (TRCO) has processing units for FFT processing (TRFT), speech determination (TRSD), and behavior determination (TRAD). The sensing unit (TRSE) may include a sensor other than the voice sensor (TRMI). For example, the present embodiment can cope with a situation in which a sensor other than the voice sensor (TRMI) cannot be operated for some reason.

  In FFT processing (TRFT) and speech determination (TRSD), processing similar to that described with reference to FIG. 4 in the first embodiment is performed. In the action determination (TRAD), the action determination of the user wearing the sensor terminal (TR) is performed based on the determination result in the utterance determination (TRSD).

  FIG. 13 is a diagram conceptually showing processing performed inside the sensor terminal (TR) in the fifth embodiment of the present invention.

  Voice detection (VCD) is performed by a voice sensor (TRMI), the obtained voice data is subjected to FFT processing (FFTC), and a spectrum peak value is acquired (FFTP). The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG.

  Subsequently, fundamental frequency detection (FF) processing is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. Based on the presence / absence, length, and continuity of the time interval in which it is determined that the utterance is performed, the fundamental frequency detection (FF) process is continuously performed, and the utterance is not detected. It is determined that (Vn) or speech is present (Ve).

Action determination (AJ) is performed based on the result (Vn, Ve) of the speech determination (VJ).
When it is determined that there is a speech (Ve), it is estimated that the user has performed communication with speech during that time. Therefore, in this case, it is determined that there is facing (Fe). However, the face-to-face detection by the infrared sensor is not performed. Therefore, although there is a meeting, it is unknown whether the meeting partner is an insider or an outsider, or it is determined to meet with an outsider. When it is determined that there is no speech (Vn), it is determined that there is no meeting (Fn).

  As described above, according to the fifth embodiment of the present invention, it is possible to perform presence / absence of face-to-face based on the sound detection result of the sound sensor (TRMI) as the user's action determination. .

-Sixth embodiment-
In the sixth embodiment, sensing information by the voice sensor (TRMI) is referred to when determining the user's behavior in the sensing unit (TRSE) of the sensor terminal (TR). The behavior determination is performed on the application server (AS) side.

  The action determination result may be transmitted to the sensor network server (SS) via the network (NW) and stored, or content is generated in the application server (AS) based on a request from the client (CL). It may be referred to at the time and then discarded.

  FIG. 14 is a block diagram showing only a part that plays an important role in the sixth embodiment in the overall system configuration shown in FIG. The system components other than those shown in FIG. 14 are the same as those shown in FIG. 14, the same components as those described with reference to FIGS. 1 and 2 are denoted by the same reference numerals, and detailed description thereof is omitted.

  The configuration of the sensor terminal (TR) is characterized in that the control unit (TRCO) has an FFT process (TRFT). In addition, the configuration of the application server (AS) is characterized in that the control unit (ASCO) has processing units for speech determination (ASSD) and action determination (ASAD).

  First, the characteristic part of the configuration of the sensor terminal (TR) will be described. The FFT process (TRFT) is the process of S4-2 and S4-3 during the process described with reference to FIG. 4 in the first embodiment. I do. The processing result in the FFT processing (TRFT) is transmitted to the sensor network server (SS) via the base station (GW) and stored.

  Next, features of the configuration of the application server (AS) will be described. The speech determination (ASSD) acquires necessary voice data from the sensor network server (SS), performs the processes from S4-4 to S4-12 during the process described with reference to FIG. Attempts to detect spectral components (fundamental frequency) peculiar to The detection is repeated, and when a spectral component peculiar to a human voice is detected over a certain time (for example, several seconds) or more, it can be determined that an utterance has occurred.

  In the action determination (ASAD), the action determination process is performed with reference to the determination result (Vn, Ve) in the utterance determination (ASSD).

  FIG. 15 is a diagram conceptually showing processing performed in the sensor terminal (TR) and the application server (AS) in the sixth embodiment of the present invention. In FIG. 15, processing performed on the sensor terminal (TR) side from the upper part of the area separated by two parallel broken lines drawn in the horizontal direction, and the lower part of the application server (AS). The processing performed on the side is shown.

  First, the process performed on the sensor terminal (TR) side will be described. The voice data obtained by voice detection (VCD) by the voice sensor (TRMI) is subjected to FFT processing (FFTC), and the spectrum peak value is calculated. Acquired (FFTP). The FFT process (FFTC) corresponds to the process of S4-2 in FIG. 4, and the spectrum peak value acquisition (FFTP) process corresponds to the process of S4-3 in FIG. The obtained set of spectrum peak values is transmitted as audio data to the sensor network server (SS) together with information such as the user ID or terminal ID and the audio detection date (DTV).

  Next, processing performed on the application server (AS) side will be described. Based on the content request issued from the client (CL), audio data corresponding to the desired date and time of the desired user is acquired from the sensor network server (SS) (DRV), and the basic frequency detection (FF) is performed on the audio data. ) Is performed. This processing corresponds to the processing from S4-4 to S4-12 in FIG. An utterance determination (VJ) is performed based on the presence / absence, length, continuity, etc. of the time interval in which it is determined that the utterance has been performed by continuously performing the fundamental frequency detection (FF) process. It is determined that there is no (Vn) or speech is present (Ve).

Action determination (AJ) is performed based on the result (Vn, Ve) of the speech determination (VJ).
When it is determined that there is a speech (Ve), it is estimated that the user has performed communication with speech during that time. Therefore, in this case, it is determined that there is facing (Fe). However, the face-to-face detection by the infrared sensor is not performed. Therefore, although there was a meeting, it is unknown whether the meeting partner is an insider or an outsider, or it is determined to meet with an outsider. When it is determined that there is no speech (Vn), it is determined that there is no meeting (Fn).

  As described above, according to the sixth embodiment of the present invention, it is possible to perform presence / absence of face-to-face based on the sound detection result of the sound sensor (TRMI) as the user's action determination. .

  As described above, in the sixth embodiment, the example in which the speech determination and the behavior determination are performed by the application server (AS) has been described. However, these processes may be performed by another information processing apparatus. Further, a plurality of information processing apparatuses may be used, and utterance determination may be performed by one information processing apparatus and behavior determination may be performed by the other information processing apparatus.

-Processing sequence from voice data acquisition to action determination (part 1)-
As described above, according to the first embodiment to the sixth embodiment, an example in which the speech determination and behavior determination are performed by the sensor terminal (TR) based on the acquired voice data and the application server (AS) are performed. An example is given. FIG. 16 shows an extracted processing sequence for processing the acquired voice data and performing speech determination and action determination, among processing sequences performed in cooperation between elements constituting the business management support system. It is a sequence diagram corresponding to what was described in the first, second, and fifth embodiments.

  The sensor terminal (TR) records voice (S16-1) and performs FFT processing (S16-2). That is, the processing of S4-1 and S4-2 described with reference to FIG. 4 is performed. Subsequently, the sensor terminal (TR) performs processing for obtaining a spectrum peak value (S16-3) and processing for extracting a fundamental frequency (S16-4). This corresponds to the processing from S4-3 to S4-12 described with reference to FIG. In utterance determination (S16-5), utterance determination is performed based on the presence or absence of a time zone in which spectrum peaks derived from human voice are present together. Furthermore, the sensing data obtained by the sensing unit (TRSE) corresponding to each embodiment is appropriately referred to, and action determination (S16-6) is performed, and these determination results are transmitted to the base station (GW). (S16-7).

  The base station (GW) receives the data (S16-8) and transfers it to the sensor network server (SS) (S16-9). The sensor network server (SS) receives the data (S16-10) and accumulates it in the database unit (SSDB) (S16-11).

  On the other hand, the application server (AS) that has started generating content based on a request from the client (CL) sends a query request to the sensor network server (SS) in order to obtain information necessary to generate the content. (S16-12). In other words, the application server (AS) outputs to the sensor network server (SS) information that can specify who (single or plural) and what information is needed from when to when.

  The sensor network server (SS) receives this query (S16-13), extracts the corresponding information from the database unit (SSDB), and transmits it to the application server (AS) (S16-14). The application server (AS) receives this information (S16-15), and generates content based on the request from the client (CL).

  In the example shown in FIG. 16, the processing load on the sensor terminal (TR) increases as the fundamental frequency extraction, speech determination, and action determination are performed on the sensor terminal (TR) side. However, since data exchanged between the components of the system is reduced, it is possible to suppress the occurrence of congestion in data communication performed between the components.

− Processing sequence from voice data acquisition to action determination (Part 2) −
FIG. 17 shows an extracted process of processing the acquired voice data to determine the utterance and the action among the processing sequences performed in cooperation between the elements constituting the business management support system. It is a sequence diagram corresponding to what was demonstrated in 3rd, 4th, and 6th embodiment.

  The sensor terminal (TR) records voice (S17-1) and performs FFT processing (S17-2). That is, the processing of S4-1 and S4-2 described with reference to FIG. 4 is performed. Subsequently, the sensor terminal (TR) performs a spectrum peak value acquisition process (S17-3). The sensor terminal (TR) transmits the spectrum peak thus obtained to the base station (GW) together with the sensing data obtained by the sensing unit (TRSE) corresponding to each embodiment (S17-4).

  The base station (GW) receives this data (S17-5) and transfers it to the sensor network server (SS) (S17-6). The sensor network server (SS) receives this data (S17-7), classifies it based on the terminal ID and time stamp included in each data, and stores it in the database unit (SSDB) (S17-8).

  On the other hand, the application server (AS) that has started generating content based on a request from the client (CL) sends a query request to the sensor network server (SS) in order to obtain information necessary to generate the content. (S17-9). In other words, the application server (AS) outputs to the sensor network server (SS) information that can specify who (single or plural) and what information is needed from when to when.

  The sensor network server (SS) receives this query (S17-10), extracts the corresponding information from the database unit (SSDB), and transmits it to the application server (AS) (S17-11). The application server (AS) receives this information (S17-12), performs basic frequency extraction (S17-13), speech determination (17-14), action determination (S17-15), and client (CL ) To generate content based on the request from.

  In the example shown in FIG. 17, since the processing load on the sensor terminal (TR) side is reduced, the power consumption can be reduced and the battery life can be extended when the sensor terminal (TR) is battery driven. It becomes. In addition, when processing is performed on the side of the application server (AS) or the like, which generally has a higher processing capacity than the processing capacity of the sensor terminal (TR), more advanced and complicated processing is performed, and utterance determination and behavior It is also possible to increase the determination accuracy of the determination. Furthermore, by acquiring and processing face-to-face activity information that is difficult to obtain on the sensor terminal (TR) side from other information processing devices, the accuracy of action determination can be improved, or more detailed action classification can be performed. It is also possible to do.

  Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications can be made and the above-described embodiments can be appropriately combined. Will be understood by those skilled in the art.

TR Sensor terminal GW, GW2, GW3 Base station GS Business information management server SS Sensor network server CL, CL2 Client AS Application server NW Network

Claims (12)

A sensor terminal device attached to each of the in-organization personnel to detect a physical meeting between the in-organization personnel who are members of the organization,
A face-to-face determination unit that determines the presence or absence of physical face-to-face between personnel in the organization based on the success or failure of communication with other sensor terminal devices;
A voice detection unit that detects voice and generates voice data;
An utterance determination unit that analyzes the voice data generated by the voice detection unit and determines the presence or absence of an utterance;
Based on the determination result by the face-to-face determination unit and the determination result by the utterance determination unit, among the actions including face-to-face with the organization personnel, face-to-face with the person not wearing the sensor terminal device, and non-face-to-face A sensor terminal device comprising: an action determination unit that determines that any action has been performed. In claim 1,
The behavior determination unit
It is determined that there is a face-to-face with the organization personnel when the face-to-face determination unit determines that the physical face-to-face is present,
The face determination unit determines that there is no physical meeting, and when the utterance determination unit determines that there is an utterance, it is determined that there is a face with a person who is not wearing the sensor terminal device,
A sensor terminal device, wherein when the face-to-face determination unit determines that there is no physical meeting and when the utterance determination unit determines that there is no utterance, the sensor terminal device is determined to be non-face-to-face. In claim 1 or 2,
An acceleration detection unit for detecting movement of the personnel in the tissue wearing the sensor terminal device;
The behavior determination unit further determines that any one of the behaviors has been performed with reference to the movement detected by the acceleration detection unit. In any one of Claim 1 to 3,
The sensor terminal device is configured to be operable by a power supply provided therein. The sensor information output from the sensor terminal device attached to each of the personnel in the organization is processed in order to detect a physical meeting between the personnel in the organization who are members belonging to the organization, and the facing state of the personnel in the organization A face-to-face detection device for detecting
The sensor information is
Face-to-face determination information corresponding to the result of determining the presence or absence of physical face-to-face between personnel in the organization based on the success or failure of communication with other sensor terminal devices;
Including voice data obtained by detecting voice,
The facing state detection device is:
An utterance determination unit that analyzes the voice data included in the sensor information and determines the presence or absence of an utterance;
Based on the determination result by the utterance determination unit and the face-to-face determination information included in the sensor information, the face-to-face contact with the personnel in the organization, the face-to-face with the person not wearing the sensor terminal device, and the non-face-to-face are included. A face-to-face state detection apparatus comprising: an action determination unit that determines that any of the actions is performed. In claim 5,
The behavior determination unit
When the face-to-face determination information corresponds to a determination result that the physical face-to-face is present, it is determined that there is a face-to-face with the personnel in the organization,
The face-to-face determination information corresponds to a determination result that there is no physical face-to-face, and when the utterance determination unit determines that there is an utterance, there is a face-to-face with a person who is not wearing the sensor terminal device And
The face-to-face state is characterized in that the face-to-face determination information corresponds to a determination result that there is no physical face-to-face, and when the utterance determination unit determines that there is no utterance, it is determined to be non-face-to-face Detection device. In claim 5 or 6,
The sensor information further includes a motion detection result that is a result of detecting a motion of the personnel within the organization wearing the sensor terminal device,
The face-to-face state detection apparatus further determines that any one of the actions has been performed with reference to a result of detecting the movement. In any one of Claims 5-7,
A face-to-face activity information acquisition unit for acquiring face-to-face activity information, which is information that can extract face-to-face activities between the in-organization personnel and personnel not wearing the sensor terminal device,
The face-to-face state detection apparatus further determines that any one of the actions has been performed with reference to the face-to-face activity information. The face-to-face state detection device detects the face-to-face state of the in-organization personnel using a sensor terminal device attached to each of the in-organization personnel in order to detect physical facing between the in-organization personnel who are members of the organization A face-to-face detection method
The meeting detection device provided in the sensor terminal device determines the presence or absence of the physical meeting based on the success or failure of communication with other sensor terminal devices,
A voice detection unit provided in the sensor terminal device detects voice and generates voice data;
The face-to-face detection device analyzes the voice data to determine the presence or absence of speech,
The face-to-face state detection device does not wear the sensor terminal device, face-to-face with the person in the organization, based on a combination of the result of the physical presence / absence determination and the result of the speech presence / absence determination A face-to-face state detection method, comprising: determining which action has been performed among actions including face-to-face and non-face-to-face. In claim 9,
The determination of which action has been performed is further
When it is determined that the physical meeting exists, it is determined that there is a meeting with the personnel in the organization,
When it is determined that there is no physical meeting and it is determined that there is an utterance, it is determined that there is a meeting with a person who is not wearing the sensor terminal device,
When it is determined that there is no physical meeting and it is determined that there is no utterance, it is determined that the person is not facing. In the previous claim 9 or 10,
The acceleration detection unit provided in the sensor terminal device detects the movement of the person in the tissue wearing the sensor terminal device,
In the determination of which action has been performed, the face-to-face detection method is further characterized by referring to the detection result of the movement of the personnel in the organization. In any one of claims 9 to 11,
The face-to-face state detection device acquires face-to-face activity information, which is information that enables extraction of face-to-face activities between personnel in the organization and personnel not wearing the sensor terminal device,
In the determination as to whether any of the actions has been performed, the face-to-face activity detection method further refers to the face-to-face activity information.

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