Estimation system, estimation method, and program

Abstract

To provide an estimation system, estimation method, and program capable of easily estimating the number of objects existing in a predetermined space even when the predetermined space is under an invisible environment such as dense smoke and darkness.SOLUTION: An estimation system comprises: acquisition means 41 for acquiring information related to a wireless signal based on wireless signals respectively received from one or more terminal devices existing in a predetermined space, in which the information related to the wireless signal includes a plurality of feature amounts of the wireless signal; determination means 42 for performing main component analysis with respect to the acquired information related to the wireless signals so as to determine a plurality of main components corresponding to the feature amounts; and estimation means 43 for estimating the number of terminal devices existing in the predetermined space by clustering the wireless signals into groups of the corresponding terminal devices with the use of the main components.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to an estimation system, an estimation method, and a program. [Background technology]

[0002] Conventionally, there is known a technique for estimating the number of objects (e.g., the number of people) present in a given space in order to perform behavioral analysis such as the degree of congestion and the flow of people in the space (for example, Patent Document 1). The technique described in Patent Document 1 counts (estimates) the number of people present in a given space based on an image captured by a camera. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2015-70359 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, if a specified space is in an invisible environment such as thick smoke or darkness, it becomes difficult to identify objects (people) from the captured image, and as a result, it may become difficult to estimate the number of objects (number of people) present in the specified space.

[0005] The present invention has been made in consideration of the above-mentioned problems, and aims to provide an estimation system, an estimation method, and a program that can easily estimate the number of objects present in a specified space, even if the space is in an invisible environment such as thick smoke or darkness. [Means for solving the problem]

[0006] In order to solve the above problems, firstly, the present invention provides an estimation system (Invention 1) comprising: an acquisition means for acquiring information about a wireless signal based on the wireless signal received from each of one or more terminal devices present within a specified space, the information about the wireless signal including a plurality of features of the wireless signal; a determination means for performing principal component analysis on the information about the acquired plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of features; and an estimation means for estimating the number of terminal devices present within the specified space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components.

[0007] According to this invention (Invention 1), it is possible to estimate the number of terminal devices present in a given space as the number of objects (for example, the number of users who own terminal devices) by using wireless signals received from each of one or more terminal devices present in the given space. As a result, instead of estimating the number of objects from captured video or the like, it is possible to estimate the number of objects using wireless signals received from the terminal devices, so that even if the given space is in an invisible environment such as thick smoke or darkness, the number of objects present in the given space can be easily estimated.

[0008] In the above invention (Invention 1), the acquisition means acquires information regarding the wireless signals based on the wireless signals received from each of the one or more terminal devices within a first predetermined period, and the estimation means may estimate the number of terminal devices present within the specified space within the first predetermined period (Invention 2).

[0009] According to this invention (Invention 2), it becomes possible to estimate the number of terminal devices (i.e., the number of objects) present within a specified space during a first specified period by using radio signals received from each of one or more terminal devices during the first specified period.

[0010] In the above invention (Invention 1), the wireless signal may include identification information of the terminal device (Invention 3).

[0011] According to this invention (Invention 3), it becomes possible to estimate the number of terminal devices (that is, the number of objects) present within a given space by using a wireless signal including identification information of the terminal device.

[0012] In the above invention (Invention 3), when identification information of a terminal device contained in a wireless signal transmitted from a single terminal device changes over time and multiple wireless signals satisfy predetermined conditions, the number of the multiple wireless signals may be included in the multiple features as the number of wireless signals that can be aggregated into a single wireless signal (Invention 4).

[0013] According to this invention (Invention 4), even if, for example, a terminal device whose identification information changes over time is present within a specified space, it becomes possible to accurately estimate the number of terminal devices (i.e., the number of objects) by regarding a single radio signal aggregated from multiple radio signals that satisfy specified conditions as having been transmitted from a single terminal device.

[0014] In the above invention (Invention 4), the predetermined condition may include that the identification information of the terminal device included in each of the plurality of wireless signals is identical (Invention 5).

[0015] According to this invention (Invention 5), it becomes possible to regard a plurality of radio signals including the same identification information as having been transmitted from a single terminal device.

[0016] In the above invention (Invention 4), the predetermined condition may include that the packet lengths of the plurality of wireless signals are the same (Invention 6).

[0017] According to this invention (Invention 6), it becomes possible to regard a plurality of wireless signals including the same packet length as being transmitted from a single terminal device.

[0018] In the above invention (Invention 4), when the received signal strength of the wireless signal is included in the multiple feature quantities, an average value or a maximum value of the received signal strengths of each of the multiple wireless signals that satisfy the specified condition may be included as the received signal strength of the wireless signal (Invention 7).

[0019] According to this invention (Invention 7), it becomes possible to estimate the number of terminal devices (i.e., the number of objects) present within a specified space by using the average or maximum value of the received signal strength of each of multiple wireless signals that satisfy specified conditions.

[0020] In the above invention (Invention 3), the identification information may be a MAC address (Invention 8).

[0021] According to this invention (Invention 8), it becomes possible to estimate the number of terminal devices (that is, the number of objects) present within a given space by using a wireless signal including a MAC address.

[0022] In the above invention (Invention 1), the determination means may determine a first principal component related to characteristic data of the terminal device and a second principal component related to time series data of the wireless signal by executing the principal component analysis (Invention 9).

[0023] According to this invention (Invention 9), it becomes possible to estimate the number of terminal devices (i.e., the number of objects) present in a specified space by clustering a plurality of wireless signals into groups of corresponding terminal devices using a first principal component related to characteristic data of the terminal devices and a second principal component related to time series data of the wireless signals.

[0024] In the above invention (Invention 1), the estimation means may perform clustering using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) (Invention 10).

[0025] According to this invention (Invention 10), a plurality of wireless signals can be clustered into groups of corresponding terminal devices without explicitly specifying the number of clusters.

[0026] In the above invention (Invention 1), the multiple features may include any of the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength of the wireless signal, and the amount of data that the terminal device can transmit within a second predetermined period (Invention 11).

[0027] According to this invention (Invention 11), it becomes possible to estimate the number of terminal devices (i.e., the number of objects) present within a specified space by using any one of the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength of the wireless signal, and the amount of data that the terminal device can transmit within a second specified period.

[0028] In the above invention (Invention 1), the wireless signal may be a probe request signal (Invention 12).

[0029] According to this invention (Invention 12), it becomes possible to estimate the number of terminal devices (that is, the number of objects) present in a given space by using a probe request signal.

[0030] Secondly, the present invention provides an estimation method in which a computer executes the steps of: acquiring information about a wireless signal based on a wireless signal received from each of one or more terminal devices present within a specified space, the information about the wireless signal including a plurality of features of the wireless signal; performing principal component analysis on the acquired information about the plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of features; and estimating the number of terminal devices present within the specified space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components (Invention 13).

[0031] Thirdly, the present invention provides a program for causing a computer to realize the following functions: acquiring information about wireless signals based on wireless signals received from each of one or more terminal devices present within a specified space, the information about the wireless signals including a plurality of features of the wireless signals; performing principal component analysis on the acquired information about the plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of features; and estimating the number of terminal devices present within the specified space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components (Invention 14). Effect of the Invention

[0032] According to the estimation system, estimation method, and program of the present invention, the number of objects present in a specified space can be easily estimated even if the space is in an invisible environment such as thick smoke or darkness. [Brief description of the drawings]

[0033] [Figure 1] 1 is a diagram illustrating a basic configuration of an estimation system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram showing a configuration of a communication device. [Diagram 3] FIG. 2 is a block diagram showing a configuration of an estimation device. [Figure 4] FIG. 2 is a functional block diagram for explaining functions that play a major role in the estimation system. [Diagram 5] FIG. 4 is a diagram illustrating an example of the configuration of acquired data. [Figure 6] FIG. 13 is a diagram illustrating an example of a process of principal component analysis. [Figure 7] FIG. 13 is a diagram illustrating an example of a clustering process. [Figure 8] 4 is a flowchart illustrating an example of main processing of the estimation system according to one embodiment of the present invention. [Figure 9] 5A and 5B are diagrams illustrating an example of division of functions of the estimation system between a communication device and an estimation device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0034] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, this embodiment is merely an example, and the present invention is not limited thereto.

[0035] (1) Basic configuration of the estimation system Fig. 1 is a diagram showing a schematic basic configuration of an estimation system according to an embodiment of the present invention. As shown in Fig. 1, in this estimation system, a communication device 20 receives wireless signals transmitted from each of a plurality of terminal devices 10 (three in the example of Fig. 1) present in a predetermined space S, for example, inside a tunnel, and an estimation device 30 estimates the number of terminal devices 10 present in the space S based on information related to the wireless signals received by the communication device 20. The communication device 20 and the estimation device 30 are connected to a communication network NW (network) such as the Internet or a LAN (Local Area Network).

[0036] Each terminal device 10 is configured to be able to perform wireless communication with the communication device 20 using a wireless LAN (e.g., Wi-Fi (registered trademark)) when present in the space S. Each terminal device 10 is also configured to transmit a wireless signal (e.g., a probe request signal, etc.) including its own identification information (e.g., a MAC address, etc.) at a predetermined interval (e.g., several seconds interval) in order to perform wireless communication with the communication device 20. Each terminal device 10 may be a terminal device operated by an individual user, such as a mobile terminal, a smartphone, a PDA (Personal Digital Assistant), a personal computer, or a television receiver with a two-way communication function (including a so-called multi-function smart TV).

[0037] The communication device 20 is provided in a position in the space S where it can perform wireless communication with each terminal device 10 using a wireless LAN. The communication device 20 may be configured to measure a received signal strength (RSSI: Received Signal Strength Indicator) when receiving a wireless signal transmitted from each terminal device 10. The communication device 20 may be a device that relays wireless communication between each terminal device 10, a device that relays wireless communication between each terminal device 10 and another terminal device (not shown) in the space S, or a device that relays communication between each terminal device 10 and another device connected via a communication network NW. The communication device 20 may also be a packet capture device.

[0038] The estimation device 30 is configured to acquire information on the wireless signal transmitted from the communication device 20 via the communication network NW, and estimate the number of terminal devices 10 present in the space S based on the acquired information on the wireless signal. Here, the information on the wireless signal may include, for example, the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength of the wireless signal, and the amount of data that the terminal device 10 can transmit within a predetermined period (HT Capability). Furthermore, the estimation device 30 may be, for example, a general-purpose personal computer.

[0039] (2) Configuration of communication device The configuration of the communication device 20 will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the internal configuration of the communication device 20. As shown in Fig. 2, the communication device 20 includes a CPU (Central Processing Unit) 21, a ROM (Read Only Memory) 22, a RAM (Random Access Memory) 23, a storage device 24, and a communication interface unit 25, and is provided with a bus 20a for transmitting control signals or data signals between the units.

[0040] When the power supply is turned on to the communication device 20, the CPU 21 loads various programs stored in the ROM 22 or the storage device 24 into the RAM 23 and executes them.

[0041] The storage device 24 may be, for example, a non-volatile storage device such as a flash memory, an SSD (Solid State Drive), a magnetic storage device (e.g., an HDD (Hard Disk Drive), a floppy disk (registered trademark), a magnetic tape, etc.), an optical disk, or a volatile storage device such as a RAM, and stores the programs executed by the CPU 21 and the data referenced by the CPU 21.

[0042] The communication interface unit 25 includes an interface circuit for performing communication using the above-mentioned wireless communication method, and an interface circuit for performing communication via the communication network NW. The interface circuit for performing communication using the wireless communication method may be provided with an RSSI circuit for detecting a received signal strength (RSSI) when a wireless signal transmitted from each terminal device 10 is received.

[0043] Here, every time the CPU 21 receives (acquires) a wireless signal from any of the terminal devices 10 via the communication interface unit 25, the CPU 21 stores in the RAM 23 or the storage device 24 acquisition date and time information (e.g., year, month, date, hour, minute, second, etc.) when the wireless signal was received (acquired) and the value of the received signal strength of the wireless signal detected by the RSSI circuit in a state associated with the data of the wireless signal. Then, every time the CPU 21 receives a wireless signal from the terminal device 10, the CPU 21 may transmit information about the wireless signal, including the acquisition date and time information when the wireless signal was received and the value of the received signal strength of the wireless signal, to the estimation device 30 via the communication interface unit 25. Furthermore, every time a predetermined period (e.g., 15 seconds, etc.) elapses, the CPU 21 may transmit information about all wireless signals received within the predetermined period to the estimation device 30 via the communication interface unit 25.

[0044] (3) Configuration of the estimation device The configuration of the estimation device 30 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the internal configuration of the estimation device 30. As shown in Fig. 3, the estimation device 30 includes a CPU 31, a ROM 32, a RAM 33, a storage device 34, a display processing unit 35, a display unit 36, an input unit 37, and a communication interface unit 38, and is provided with a bus 30a for transmitting control signals or data signals between the respective units.

[0045] When the power is turned on to the estimation device 30, the CPU 31 loads various programs stored in the ROM 32 or the storage device 34 into the RAM 33 and executes them. In this embodiment, the CPU 31 reads out and executes the programs stored in the ROM 32 or the storage device 34, thereby realizing the functions of an acquisition means 41, a determination means 42, and an estimation means 43 (shown in FIG. 4) described below.

[0046] The storage device 34 may be, for example, a non-volatile storage device such as a flash memory, an SSD, a magnetic storage device (e.g., an HDD, a floppy disk (registered trademark), a magnetic tape, etc.), an optical disk, or a volatile storage device such as a RAM, and stores the programs executed by the CPU 31 and the data referenced by the CPU 31. The storage device 34 also stores acquired data (shown in FIG. 5) which will be described later.

[0047] The display processing unit 35 displays the display data provided from the CPU 31 on the display unit 36. The display unit 36 ​​is, for example, an LCD (Liquid Crystal Display) monitor including thin film transistors arranged in a matrix on a pixel basis, and displays the data to be displayed on the display screen by driving the thin film transistors based on the display data.

[0048] When the estimation device 30 is a terminal device of a button input type, the input unit 37 includes a button group including a plurality of instruction input buttons such as a direction indication button and a decision button for accepting user operation input, and a button group including a plurality of instruction input buttons such as a numeric keypad, and includes an interface circuit for recognizing the depression (operation) input of each button and outputting it to the CPU 31.

[0049] When the estimation device 30 is a terminal device that employs a touch panel input method, the input unit 37 mainly receives input by touching the display screen with a fingertip or a pen. The touch panel input method may be a known method such as a capacitance method.

[0050] Furthermore, when the estimation device 30 is a device capable of receiving voice input, the input unit 37 may be configured to include a microphone for voice input, or may be provided with an interface circuit for outputting voice data input via an external microphone to the CPU 31. Furthermore, when the estimation device 30 is a device capable of receiving moving images and / or still images, the input unit 37 may be configured to include a digital camera or digital video camera for image input, or may be provided with an interface circuit for receiving image data captured by an external digital camera or digital video camera and outputting the image data to the CPU 31.

[0051] The communication interface unit 38 includes an interface circuit for performing communication via the communication network NW.

[0052] (4) Overview of each function in the estimation system The functions realized by the estimation system of this embodiment will be described with reference to Fig. 4. Fig. 4 is a functional block diagram for explaining the functions that play a major role in the estimation system of this embodiment. In the functional block diagram of Fig. 4, an acquisition means 41, a decision means 42, and an estimation means 43 correspond to the main components of the present invention.

[0053] In describing each function of the estimation system of this embodiment, it is assumed that each terminal device 10 transmits a wireless signal (e.g., a probe request signal, etc.) including a MAC address as its own identification information at a predetermined interval (e.g., several seconds) within the space S. All terminal devices 10 present within the space S may be configured so that the MAC address included in the wireless signal does not change over time (having a fixed MAC address), or may be configured so that the MAC address changes over time (having a dynamic MAC address). Furthermore, the space S may contain a mixture of terminal devices 10 whose MAC addresses do not change over time and terminal devices 10 whose MAC addresses change over time.

[0054] The acquisition means 41 has a function of acquiring information about a wireless signal based on the wireless signal received from each of one or more terminal devices 10 present in a predetermined space S. Here, the information about the wireless signal includes a plurality of feature amounts of the wireless signal.

[0055] Furthermore, the acquisition means 41 may acquire information about a wireless signal based on the wireless signal received from each of one or more terminal devices 10 within a first predetermined period (e.g., 15 seconds, etc.). This makes it possible to estimate the number of terminal devices 10 (i.e., the number of objects) present within a predetermined space S during the first predetermined period, using the wireless signals received from each of one or more terminal devices 10 during the first predetermined period.

[0056] Furthermore, the wireless signal may include identification information of the terminal device 10. This makes it possible to estimate the number of terminal devices 10 present within a given space S by using the wireless signal including the identification information of the terminal device 10.

[0057] Furthermore, in the case where the identification information of the terminal device 10 included in the wireless signal transmitted from a single terminal device 10 changes over time and the multiple wireless signals satisfy a predetermined condition, the number of the multiple wireless signals may be included in the multiple feature quantities as the number of wireless signals that can be aggregated into a single wireless signal. As a result, even if, for example, a terminal device 10 whose identification information changes over time is present in a predetermined space S, it is possible to accurately estimate the number of terminal devices 10 by regarding a single wireless signal aggregated from multiple wireless signals that satisfy a predetermined condition as being transmitted from a single terminal device 10.

[0058] Here, the predetermined condition may include that the identification information of the terminal device 10 included in each of the multiple wireless signals is the same. This makes it possible to consider multiple wireless signals including the same identification information as having been transmitted from a single terminal device 10.

[0059] The predetermined condition may also include that the packet lengths of the multiple wireless signals are the same, which makes it possible to regard multiple wireless signals including the same packet length as having been transmitted from a single terminal device 10.

[0060] Furthermore, when the received signal strength (RSSI) of a wireless signal is included in the multiple feature quantities, the average or maximum value of the received signal strength of each of the multiple wireless signals that satisfy a predetermined condition may be included as the received signal strength of the wireless signal. This makes it possible to estimate the number of terminal devices 10 present within a predetermined space S using the average or maximum value of the received signal strength of each of the multiple wireless signals that satisfy a predetermined condition.

[0061] Furthermore, the identification information of the terminal device 10 may be a MAC address. This makes it possible to estimate the number of terminal devices 10 present within a given space S by using a wireless signal including the MAC address.

[0062] Furthermore, the multiple feature amounts may include any of the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength of the wireless signal, and the amount of data that the terminal device 10 can transmit within a second predetermined period (for example, one second) (HT Capability). This makes it possible to estimate the number of terminal devices 10 present within a predetermined space S using any of the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength of the wireless signal, and the amount of data that the terminal device 10 can transmit within a second predetermined period (HT Capability).

[0063] Furthermore, the wireless signal may be a probe request signal, which makes it possible to estimate the number of terminal devices 10 present within a given space S using the probe request signal.

[0064] The function of the acquisition means 41 is realized, for example, as follows. Every time the CPU 31 of the estimation device 30 receives (acquires) information on a wireless signal from the communication device 20 via the communication interface unit 38, the CPU 31 stores the received information on the wireless signal in the acquired data shown in FIG. 5. Here, the communication device 20 may transmit information on all wireless signals received within a first predetermined period (for example, 15 seconds) to the estimation device 30 every time the first predetermined period elapses. Also, the acquired data shown in FIG. 5 is data in which, for each wireless signal received by the communication device 20 from each terminal device 10, identification information of the wireless signal (here, a MAC address) and a plurality of feature amounts of the wireless signal (here, the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength indicator (RSSI) value of the wireless signal, the amount of data that the terminal device 10 can transmit within a second predetermined period (HT Capability), and the number of wireless signals that can be aggregated into the same wireless signal) are described in a state of being associated with each other.

[0065] Here, an example is described in which the multiple features of the wireless signal include the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength (RSSI) value of the wireless signal, the amount of data that the terminal device 10 can transmit within a second specified period (HT Capability), and the number of wireless signals that can be aggregated into the same wireless signal. However, the multiple features may be configured to include any of the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength (RSSI) value of the wireless signal, the amount of data that the terminal device 10 can transmit within a second specified period (HT Capability), and the number of wireless signals that can be aggregated into the same wireless signal.

[0066] Among the multiple feature amounts, the “packet length of the wireless signal”, the “sequence number of the wireless signal”, and the “amount of data that the terminal device 10 can transmit within a second predetermined period (HT Capability)” may be included in the wireless signal transmitted from the terminal device 10. Also, among the multiple feature amounts, the “acquisition date and time of the wireless signal” and the “received signal strength indicator (RSSI) value of the wireless signal” may be measured by the communication device 20.

[0067] Furthermore, the CPU 31 of the estimation device 30 may determine, for each of the multiple wireless signals in the acquired data, "the number of wireless signals that can be aggregated into the same wireless signal" from among the multiple feature amounts, in order to aggregate multiple wireless signals transmitted from the same terminal device 10 into a single wireless signal. In this case, when the multiple wireless signals satisfy a predetermined condition, the CPU 31 may determine the number of the multiple wireless signals as "the number of wireless signals that can be aggregated into the same wireless signal".

[0068] Here, when the identification information (MAC address) of the terminal device 10 included in the wireless signal transmitted from a single terminal device 10 changes over time, the timing of changing the MAC address may differ depending on the model of the terminal device 10, the OS, the version of the OS, and the like. For example, depending on the model of the terminal device 10, the same MAC address may be used for several seconds, or the MAC address may be changed every time several wireless signals are transmitted. Therefore, the predetermined condition may include that the identification information of the terminal device 10 included in each of the multiple wireless signals is the same. In this case, the CPU 31 may aggregate, among the data of the wireless signals in the acquired data, the data of multiple wireless signals including the same MAC address, for example, where the difference between the acquisition dates and times of the wireless signals is within a predetermined range (for example, 2 seconds, etc.), into the data of a single wireless signal. Then, the CPU 31 may store the number of the multiple wireless signals to be aggregated in the item of "number of wireless signals that can be aggregated into the same wireless signal" of the data of the aggregated wireless signal. The CPU 31 may also store the average value or maximum value of the received signal strength indicator (RSSI) of the multiple wireless signals to be aggregated in the item of "received signal strength indicator (RSSI) value of wireless signal" of the data of the aggregated wireless signal.

[0069] Furthermore, even if the identification information (MAC address) of the terminal device 10 included in the wireless signal transmitted from a single terminal device 10 changes over time, the packet length of the wireless signal differs depending on, for example, the model, OS, and OS version of the terminal device 10. For example, when the packet lengths of two wireless signals are equal, it can be considered that these two wireless signals are transmitted from the same terminal device 10. Therefore, the predetermined condition may include that the packet lengths of the multiple wireless signals are the same. In this case, the CPU 31 may aggregate, among the data of the wireless signals in the acquired data, data of multiple wireless signals that include the same packet length and for example have a difference in the acquisition date and time of the wireless signals within a predetermined range (for example, 2 seconds), into data of a single wireless signal. Then, the CPU 31 may store the number of the multiple wireless signals to be aggregated in the item "number of wireless signals that can be aggregated into the same wireless signal" of the data of the aggregated wireless signal. Furthermore, the CPU 31 may store the average value or maximum value of the received signal strength indicator (RSSI) of the multiple wireless signals to be aggregated in the item "value of received signal strength indicator (RSSI) of wireless signal" of the data of the aggregated wireless signal.

[0070] Note that, here, an example is described in which multiple wireless signals are aggregated into a single wireless signal when there is a terminal device 10 whose identification information (MAC address) changes over time (has a dynamic MAC address). However, it is also possible to aggregate multiple wireless signals into a single wireless signal even when there is a terminal device 10 whose identification information (MAC address) does not change over time (has a fixed MAC address) or when there is a mixture of terminal devices 10 with dynamic MAC addresses and terminal devices 10 with fixed MAC addresses.

[0071] The determining means 42 has a function of performing a principal component analysis on the information relating to the plurality of acquired wireless signals to determine a plurality of principal components corresponding to a plurality of feature quantities.

[0072] Furthermore, the determination means 42 may determine a first principal component related to the characteristic data of the terminal device 10 and a second principal component related to the time series data of the wireless signals by performing a principal component analysis. This makes it possible to estimate the number of terminal devices 10 present in a predetermined space S by clustering a plurality of wireless signals into groups of corresponding terminal devices 10 using the first principal component related to the characteristic data of the terminal device 10 and the second principal component related to the time series data of the wireless signals.

[0073] The function of the determination means 42 is realized, for example, as follows. The CPU 31 of the estimation device 30 accesses the acquired data and performs principal component analysis on a plurality of feature amounts (here, the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength (RSSI) value of the wireless signal, the amount of data that the terminal device 10 can transmit within a second predetermined period (HT Capability), and the number of wireless signals that can be aggregated into the same wireless signal). As a result, as shown in FIG. 6, a first principal component related to the characteristic data (model-dependent data) of the terminal device 10 and a second principal component related to the time series data (time series-dependent data) of the wireless signal are determined. Note that, here, a case where two principal components are determined is described as an example, but the number of principal components determined may be, for example, three or more. Also, here, a case where dimensional compression is performed using principal component analysis is described as an example, but other dimensional compression using other statistical data analysis methods may be performed.

[0074] Furthermore, the CPU 31 may calculate a first principal component score and a second principal component score from a plurality of feature amounts for each of a plurality of wireless signals. This makes it possible to display a plurality of wireless signals in a two-dimensional graph as shown in FIG.

[0075] The estimation means 43 has a function of estimating the number of terminal devices 10 present within a given space S by clustering a plurality of wireless signals into groups of corresponding terminal devices 10 using a plurality of principal components.

[0076] Furthermore, the estimation means 43 may perform clustering using DBSCAN (Density-Based Spatial Clustering of Applications with Noise), which allows clustering of multiple wireless signals into groups of corresponding terminal devices 10 without explicitly specifying the number of clusters.

[0077] The function of the estimation means 43 is realized, for example, as follows. The CPU 31 of the estimation device 30 may perform clustering of the first principal component score and the second principal component score calculated from the multiple feature quantities using DBSCAN. As a result, as shown in FIG. 7, multiple wireless signals are classified into multiple groups (four groups shown by dashed lines in the example of the figure) of the corresponding terminal devices 10. Then, the CPU 31 may estimate the number of classified groups (the number of clusters) as the number of terminal devices 10 present in the space S. Note that the radius and density, which are parameters of DBSCAN, may be adjusted in advance, for example, so that the matching rate between the number of generated clusters and the actual correct answer labels is maximized. Note that, although the case where clustering is performed using DBSCAN is described here as an example, clustering may be performed using other clustering techniques, such as k-means.

[0078] The CPU 31 may present the estimation result of the number of terminal devices 10 present in the space S. For example, when the CPU 31 estimates the number of terminal devices 10 based on the function of the estimation means 43, the CPU 31 may display information on the estimation result of the number of terminal devices 10, for example, on the display unit 36. Here, the information on the estimation result of the number of terminal devices 10 may be composed of text data or image data, etc. In addition, when the information on the estimation result of the number of terminal devices 10 is composed of audio data, the CPU 31 may output the information on the estimation result of the number of terminal devices 10 from an audio output device such as a speaker. Furthermore, the CPU 31 may transmit the information on the estimation result of the number of terminal devices 10 to another computer (for example, a server, etc.) connected to the estimation device 30 via the communication network NW.

[0079] (5) Flow of main processing of the estimation system of this embodiment Next, an example of the flow of main processes performed by the estimation system of this embodiment will be described with reference to the flowchart of FIG.

[0080] First, each terminal device 10 transmits a wireless signal (e.g., a probe request signal, etc.) including a MAC address as its own identification information at a predetermined interval (e.g., several seconds) within the space S. Also, for example, every time the communication device 20 receives a wireless signal from any of the terminal devices 10 via the communication interface unit 25, the communication device 20 transmits information about the wireless signal, including acquisition date and time information when the wireless signal was received and a value of the received signal strength of the wireless signal, to the estimation device 30 via the communication interface unit 25.

[0081] On the other hand, the CPU 31 of the estimation device 30 acquires information about the wireless signal based on the wireless signal received from each of one or more terminal devices 10 present in the predetermined space S (step S100). Specifically, every time the CPU 31 receives (acquires) information about the wireless signal from the communication device 20 via the communication interface unit 38, the CPU 31 stores the received information about the wireless signal in the acquired data. Note that the information about the wireless signal includes a plurality of features of the wireless signal (for example, the acquisition date and time of the wireless signal, the packet length of the wireless signal, the sequence number of the wireless signal, the received signal strength indicator (RSSI) value of the wireless signal, the amount of data (HT Capability) that the terminal device 10 can transmit within a second predetermined period (for example, one second, etc.), and the number of wireless signals that can be aggregated into the same wireless signal).

[0082] Next, the CPU 31 of the estimation device 30 performs a principal component analysis on the acquired information on the plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of feature quantities (step S102). Here, the CPU 31 may perform the principal component analysis to determine a first principal component related to the characteristic data of the terminal device 10 and a second principal component related to the time-series data of the wireless signals.

[0083] Next, the CPU 31 of the estimation device 30 estimates the number of terminal devices 10 present in a predetermined space S by clustering the multiple wireless signals into groups of corresponding terminal devices 10 using multiple principal components (step S104). Here, the CPU 31 may perform clustering using DBSCAN.

[0084] As described above, according to the estimation system, estimation method, and program of the present embodiment, it is possible to estimate the number of terminal devices 10 present in a predetermined space S as the number of objects (for example, the number of users possessing the terminal devices 10) using wireless signals received from each of one or more terminal devices 10 present in the predetermined space S. As a result, instead of estimating the number of people (number of objects) from, for example, a captured video or the like, it is possible to estimate the number of people (number of objects) using wireless signals received from the terminal devices 10, so that even if the predetermined space S is in an invisible environment such as thick smoke or darkness, the number of people (number of objects) present in the predetermined space S can be easily estimated.

[0085] The program of the present invention may be stored in a computer-readable storage medium. The storage medium on which the program is recorded may be the ROM 22, RAM 23, or storage device 24 of the communication device 20 shown in Fig. 2, or the ROM 32, RAM 33, or storage device 34 of the estimation device 30 shown in Fig. 3. The program may also be a CD-ROM or the like that can be read by being inserted into a program reading device such as a CD-ROM drive. Furthermore, the storage medium may be a magnetic tape, a cassette tape, a flexible disk, an MO / MD / DVD, or a semiconductor memory.

[0086] The above-described embodiments are described for the purpose of facilitating understanding of the present invention, and are not described for the purpose of limiting the present invention. Therefore, each element disclosed in the above embodiment is intended to include all design modifications and equivalents that fall within the technical scope of the present invention.

[0087] For example, in the above embodiment, the object is a person (a user who owns the terminal device 10) as an example, but the present invention is not limited to this case. The object may be anything that can be counted, and may be, for example, an animal equipped with the terminal device 10, or another object such as a moving object equipped with the terminal device 10 (a work machine, a vehicle, an aircraft, etc.).

[0088] In the above embodiment, a case where one communication device 20 communicates with each of one or more terminal devices 10 has been described as an example, but the present invention is not limited to this case. For example, each of the multiple communication devices 20 may communicate with each of one or more terminal devices 10.

[0089] Furthermore, in the above embodiment, a case where wireless communication is performed between each terminal device 10 and the communication device 20 using a wireless LAN has been described as an example, but the present invention is not limited to this case. For example, other wireless communication methods such as Bluetooth (registered trademark), ZigBee (registered trademark), UWB, and optical wireless communication (e.g., infrared) may be used.

[0090] Furthermore, in the above embodiment, a case where a MAC address is used as identification information of each terminal device 10 has been described as an example, but the present invention is not limited to this case. For example, the identification information may be any information that is included in a wireless signal and is configured to be able to identify each terminal device 10.

[0091] In the above embodiment, the case where one estimation device 30 is provided has been described as an example, but the present invention is not limited to this case. For example, a plurality of estimation devices 30 may be provided, and in this case, the operation content and processing result, etc. of any estimation device 30 may be presented in real time on the other estimation devices 30, or the processing result, etc. of any estimation device 30 may be shared among the plurality of estimation devices 30.

[0092] Furthermore, in the above-described embodiment, the estimation device 30 is configured to realize the functions of the acquisition means 41, the determination means 42, and the estimation means 43, but the present invention is not limited to this configuration. For example, all of these means 41 to 43 may be realized by the communication device 20. Furthermore, the functions of these means 41 to 43 may be arbitrarily shared between the communication device 20 and the estimation device 30, as shown in Figs. 10(a) and 10(b).

[0093] Furthermore, the functions of at least one of the above-mentioned means 41 to 43 may be realized by the terminal device 10. [Industrial Applicability]

[0094] The estimation system, estimation method, and program of the present invention as described above can easily estimate the number of objects present in a specified space S even if the specified space S is in an invisible environment such as thick smoke or darkness. Therefore, the estimation system, estimation method, and program can be suitably used for systems and services that perform people flow analysis (people flow analysis of users carrying terminal devices 10) and traffic volume surveys in invisible environments or environments where it is difficult to introduce cameras, and therefore have extremely great industrial applicability. [Explanation of symbols]

[0095] 10...Terminal device 20...Communication equipment 30…Estimation device 41…Acquisition means 42...Decision-making means 43…Estimation means S…Space

Claims

1. an acquisition means for acquiring information about a wireless signal based on the wireless signal received from each of one or more terminal devices present in a predetermined space, the information about the wireless signal including a plurality of feature quantities of the wireless signal; a determination means for performing a principal component analysis on information regarding the acquired plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of feature quantities; and an estimation means for estimating the number of terminal devices present in the predetermined space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components. Estimation system.

2. the acquiring means acquires information about the wireless signal based on the wireless signal received from each of the one or more terminal devices within a first predetermined period; The estimation system according to claim 1 , wherein the estimation means estimates the number of terminal devices present in the predetermined space within the first predetermined period.

3. The estimation system according to claim 1 , wherein the wireless signal includes identification information of the terminal device.

4. 4. The estimation system according to claim 3, wherein when identification information of a terminal device contained in a wireless signal transmitted from a single terminal device changes over time and when the multiple wireless signals satisfy a predetermined condition, the number of the multiple wireless signals is included in the multiple feature quantities as the number of wireless signals that can be aggregated into a single wireless signal.

5. The estimation system according to claim 4 , wherein the predetermined condition includes that the identification information of the terminal device contained in each of the plurality of wireless signals is identical.

6. The estimation system according to claim 4 , wherein the predetermined condition includes that the packet lengths of the plurality of wireless signals are the same.

7. 5. The estimation system according to claim 4, wherein when the received signal strength of the wireless signal is included in the plurality of feature quantities, an average value or a maximum value of the received signal strengths of each of the plurality of wireless signals that satisfy the predetermined condition is included as the received signal strength of the wireless signal.

8. The estimation system according to claim 3 , wherein the identification information is a MAC address.

9. The estimation system according to claim 1 , wherein the determining means determines a first principal component related to characteristic data of the terminal device and a second principal component related to time-series data of the radio signal by performing the principal component analysis.

10. The estimation system according to claim 1 , wherein the estimation means performs clustering using Density-Based Spatial Clustering of Applications with Noise (DBSCAN).

11. 2. The estimation system according to claim 1, wherein the plurality of features include any one of an acquisition date and time of the wireless signal, a packet length of the wireless signal, a sequence number of the wireless signal, a received signal strength of the wireless signal, and an amount of data that the terminal device can transmit within a second predetermined period.

12. The estimation system of claim 1 , wherein the wireless signal is a probe request signal.

13. The computer A step of acquiring information about a wireless signal based on a wireless signal received from each of one or more terminal devices present in a predetermined space, the information about the wireless signal including a plurality of feature quantities of the wireless signal; performing a principal component analysis on information about the acquired plurality of wireless signals to determine a plurality of principal components corresponding to the plurality of feature quantities; estimating the number of terminal devices present in the predetermined space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components; Execute each step of Estimation method.

14. On the computer, a function of acquiring information about a wireless signal based on the wireless signal received from each of one or more terminal devices present in a predetermined space, the information about the wireless signal including a plurality of feature quantities of the wireless signal; a function of performing a principal component analysis on information regarding the plurality of acquired wireless signals to determine a plurality of principal components corresponding to the plurality of feature quantities; A function of estimating the number of terminal devices present in the predetermined space by clustering the plurality of wireless signals into groups of corresponding terminal devices using the plurality of principal components; A program to achieve this.

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