Detection system, detection method, program, and information processing system

Abstract

A detection system according to the present disclosure is a detection system which detects presence or absence of an object in a space and comprises: a pair of transceivers that transmit and receive, in the space, a plurality of radio waves having different frequency bands; and a detection unit that detects the presence of the object in the space on the basis of the radio wave intensities of the plurality of radio waves transmitted and received by the pair of transceivers.

Description

Detection system, detection method, program, and information processing system

[0001] [Related Application] This application claims priority to Japanese Patent Application No. 2024-157074, filed on 11 September 2024, entitled “Detection System, Detection Method, Program, and Information Processing System,” the disclosure thereof is incorporated herein by reference in its entirety. The technology relates to a detection system, a detection method, a program, and an information processing system.

[0002] As background technology for this field, there is Japanese Patent Publication No. 6-241544 (Patent Document 1). This publication discloses an air conditioning management system used for managing air conditioning using a large number of air conditioners installed in a building, which can be operated, controlled, and monitored from multiple locations in the building.

[0003] Japanese Patent Application Publication No. 6-241544

[0004] The aforementioned Patent Document 1 does not detect whether or not there are people in each room when controlling an air conditioner, and does not perform air conditioning management that takes into account the presence of people in the room where the air conditioner is installed. Furthermore, it is time-consuming for administrators to check whether or not there are people in each room. Therefore, this technology provides a mechanism that can be used, for example, in an air conditioning management system for a building, and that can detect the presence of people.

[0005] To solve the above problems, for example, the configuration described in the claims is adopted.

[0006] This technology provides a mechanism for detecting the presence of a person. Other issues, configurations, and effects will be clarified by the following description of the embodiments.

[0007] Figure 1 is an example of an overall configuration diagram of the building-wide control system according to this embodiment. Figure 2 is an example of a schematic diagram showing the communication state of the building-wide control system shown in Figure 1. Figure 3 is an example of the hardware configuration of the pair of transceivers shown in Figure 2. Figure 4 is an example of the functional configuration of the microcontroller of the sensor unit shown in Figure 3. Figure 5 is an example of the functional configuration of the information processing device shown in Figure 1. Figure 6 is an example of unit information shown in Figure 5. Figure 7 is an example of sensing information shown in Figure 5. Figure 8 is an example of communication radio wave strength information shown in Figure 5. Figure 9 is an example of power supply radio wave strength information shown in Figure 5. Figure 10 is an example of detection information shown in Figure 5. Figure 11 is an example of a schematic diagram showing the implementation state of system 100. Figure 12 is an example of a conceptual diagram of the position calculation process of the sensor unit. Figure 13 is an example of a diagram showing an overview of the object detection process based on the strength of the communication radio waves. Figure 14 is an example of a diagram showing an overview of the object detection process based on the strength of the power supply radio waves. Figure 15 is an example of a diagram showing an example of the temporal change in power reception strength. Figure 16 is an example of a flowchart for the transmission and reception of multiple radio waves. Figure 17 is an example of a flowchart for object detection. Figure 18 is an example of a flowchart for the first example of object presence detection. Figure 19 is an example of a flowchart for the second example of object presence detection. Figure 20 is an example of a flowchart for the third example of object presence detection. Figure 21 is an example of a flowchart for the fourth example of object presence detection. Figure 22 is an example of a diagram showing the measurement results by a sensor. Figure 23 is an example of a diagram showing the object detection results. Figure 24 is an example of a diagram illustrating the process of detecting an object using communication quality in the second embodiment. Figure 25 is an example of a diagram illustrating monostatic sensing using power-fed radio waves. Figure 26 is an example of a diagram illustrating bistatic sensing using power-fed radio waves. Figure 27 is an example of a diagram illustrating multistatic sensing using power-fed radio waves. Figure 28 is an example of a diagram illustrating monostatic sensing using communication radio waves and power-fed radio waves. Figure 29 is an example diagram illustrating bistatic sensing using communication radio waves and power supply radio waves. Figure 30 is an example diagram illustrating multistatic sensing using communication radio waves and power supply radio waves.Figure 31 is an example of a diagram illustrating an application example that uses both communication radio waves and power supply radio waves, and combines the reception results from multiple transceivers to detect an object. Figure 32A is an example of a diagram showing an example of setting spatial attribute values. Figure 32B is a diagram showing an example of a quantity estimation rule that shows the correspondence between radio wave intensity features and the number of people in a room. Figure 32C is an example of a diagram showing a state transition model that expresses the temporal change in the occupancy state. Figure 33A is a diagram showing a state transition matrix when a small conference room is used as the target space. Figure 33B shows an example of time-series data of radio wave intensity features measured in the small conference room shown in Figure 33A. Figure 34A is a diagram showing a state transition matrix when a six-person meeting space is used as the target space. Figure 34B shows an example of time-series data of radio wave intensity features measured in the meeting space shown in Figure 34A. Figure 35 is an example of a diagram illustrating threshold judgment criteria for determining the presence or absence of an object. Figure 36 is an example of a screen for reviewing spatial attributes using the whole-building control system of this technology.

[0008] The embodiments will be described below with reference to the drawings.

[0009] (1. Overall System Configuration) Figure 1 shows the overall configuration of the whole-building control system 100 (hereinafter simply referred to as System 100) according to this embodiment. System 100 is used, for example, in office buildings, various commercial facilities, or factories, and is a system that controls the air conditioning equipment and other systems of the entire building in one place. System 100 also functions as a detection system that detects the presence or absence of people in a space. Note that the scope of use of System 100 is not limited to facilities where specific persons stay, but may also be used in facilities where specific and unspecified persons stay, such as transportation facilities and public institutions.

[0010] For example, in a building space, it's sometimes necessary to have not only information about the number of people present ("who is there and how many"), but also information about areas where no one is present ("absence"). Furthermore, air conditioning accounts for approximately half of a building's energy consumption. Therefore, in order to achieve more sustainable building management and reduce air conditioning energy consumption throughout the building, it is necessary to understand which areas are occupied and which are unoccupied, and to link this information with the building's air conditioning system.

[0011] System 100 enables the detection of people's presence or absence within a building space with high temporal resolution, without using sensitive information that infringes on people's privacy, such as cameras, and simultaneously grasps the degree of congestion within the space. Furthermore, by combining it with other sensor information described later, it enables efficient and effective building management in a wide variety of building spaces.

[0012] As shown in Figure 1, the system 100 comprises a central control unit 200, lighting equipment 210, air conditioning equipment 220, a pair of transceivers 300, and an information processing device 500. Note that the quantities of each device and piece of equipment shown in Figure 1 are illustrative and can be changed as needed. The components of the system 100 are interconnected via a network. The network can be wired or wireless, and each terminal can send and receive information via the network.

[0013] The central management device 200 includes a processor that runs the operating system, applications, and programs; main memory such as RAM (Random Access Memory); auxiliary storage such as IC cards, hard disk drives, SSDs (Solid State Drives), and flash memory; a communication control unit such as a network card, wireless communication module, and mobile communication module; input devices such as a touch panel, keyboard, mouse, voice input, and motion detection input via camera imaging; and output devices such as monitors and displays. The output devices may also be devices or terminals that transmit information for output to external monitors, displays, printers, or other equipment.

[0014] The main memory stores various programs and applications (modules), and the processor executes these programs and applications to realize each functional element of the overall system. These modules may be implemented in hardware, such as through integration. Furthermore, each module may be an independent program or application, or it may be implemented as a subprogram or function within a single integrated program or application.

[0015] The central control device 200 automatically controls the lighting equipment 210 and the air conditioning equipment 220 based on information input from the information processing device 500, which will be described later. The functions that the central control device 200 realizes through automatic control include the following: - Control function for the target temperature of the air conditioning equipment 220 - Function for determining the comfortable temperature of the air conditioning equipment 220 - Function to prevent forgetting to turn off the air conditioning equipment 220 and the lighting equipment 210. Each of these functions will be described in detail.

[0016] In the target temperature control function of the air conditioning equipment 220, the central control device 200 transmits control values ​​corresponding to a preset target to the air conditioning equipment 220 installed in each air conditioning zone via the network, based on the sensor temperature of the space where people are present, determined by processing by the information processing device 500 (described later), and the temperature recognized by the air conditioning equipment 220.

[0017] Furthermore, in the function for determining the comfortable temperature of the air conditioning system 220, the central control device 200 determines the temperature that people find comfortable based on the discomfort index expressed in terms of humidity and temperature, and determines the control value of the air conditioning system 220 based on the discomfort index. The determined control value is transmitted via the network to the air conditioning systems 220 installed in each air conditioning zone.

[0018] In the function to prevent forgetting to turn off the air conditioning equipment 220 and lighting equipment 210, the central control device 200 automatically turns off the power to the air conditioning equipment 220 and lighting equipment 210 in areas where no people are found to be present, as determined by the human body detection function of the information processing device 500 described later.

[0019] The information processing device 500 is a server device (management server) that monitors the operation of the sensor unit 310 and the power supply unit 320 that constitute the system 100. For example, the information processing device 500 determines whether the power supply unit 320 or the sensor unit 310 is in a preset state based on information about the status of the sensor unit 310 and the power supply unit 320 transmitted from the power supply unit 320. If it determines that the unit is not in a preset state, it outputs an error message to that effect.

[0020] Furthermore, the information processing device 500 stores information about the sensor unit 310 and the power supply unit 320 housed in the system 100. For example, the information processing device 500 stores information about the status of the sensor unit 310 and the power supply unit 320, transmitted from the power supply unit 320, in its auxiliary storage device 502 (see Figure 5). The specific contents of the information stored in the auxiliary storage device 502 will be described later.

[0021] Furthermore, the information processing device 500 controls the operation of the power supply unit 320 housed in the system 100. For example, the information processing device 500 transmits predetermined instructions or information to the power supply unit 320.

[0022] Furthermore, the information processing device 500 analyzes the stored information regarding the status of the sensor unit 310 and the power supply unit 320, and outputs the analysis results to the administrator. This includes: information regarding the placement of the sensor unit 310, information regarding the placement of the power supply unit 320, information regarding power consumption, information regarding radio wave intensity, and information regarding sensing values.

[0023] A pair of transceivers 300 transmit and receive multiple radio waves with different frequency bands within a space. The pair of transceivers 300 includes a sensor unit 310 and a power supply unit 320. The pair of transceivers 300 transmit and receive multiple radio waves in different frequency bands from each other. Alternatively, one of the transceivers 300 may only transmit multiple radio waves in different frequency bands, while the other only receives multiple radio waves in different frequency bands.

[0024] In system 100, the sensor unit 310 acquires temperature information used by the central control device 200 for control. The sensor unit 310 operates on power supplied wirelessly from the power supply unit 320 and transmits the acquired sensing values ​​to the central control device 200 via wireless communication through the information processing device 500. The communication state of this system 100 will be explained with reference to Figure 2.

[0025] (2. System Communication Status) Figure 2 shows the communication status of system 100. As shown in Figure 2, the power supply unit 320 transmits power supply radio waves to the sensor unit 310 and supplies power wirelessly. The sensor unit 310 and the power supply unit 320 communicate information with each other wirelessly via communication radio waves.

[0026] The power supply radio waves of the power supply unit 320 may be radio waves that can be considered as substantially continuous waves. The power supply signal transmitted from the power supply unit 320 is a radio frequency signal having a predetermined power, and it is preferable to make this radio frequency signal a radio frequency signal that can be considered as substantially continuous waves by providing a pause period of any period (e.g., 50 milliseconds) that is short compared to the period other than the pause period (e.g., 4 seconds).

[0027] Specifically, the power supply signal (power supply radio wave) transmitted from the power supply unit 320 may, for example, be a continuous wave (CW) with a predetermined power. The frequency band of the power supply signal is, for example, a 920 MHz band, taking into account the distance between the sensor unit 310 and the power supply unit 320. If the frequency band is higher than the example frequency band, it may not be possible to supply the predetermined power necessary for the sensor unit 310 to operate unless the distance between the sensor unit 310 and the power supply unit 320 is shortened. Therefore, an appropriate frequency band can be determined by considering a practical range (for example, a distance of a few meters between the sensor unit 310 and the power supply unit 320).

[0028] The power supply radio wave of the power supply unit 320 is preferably an unmodulated, modulation signal-free, information-free radio wave. Specifically, there is a radio wave type that represents the characteristics of radio waves generally used in communication systems. The radio wave type is represented by a three-character string combining an alphabet or numerical value indicating the modulation type of the main carrier wave, the nature of the signal modulating the main carrier wave, and the type of transmitted information.

[0029] The modulation type of the main carrier wave consists of any one of the following: unmodulated: N, amplitude modulation (double sideband): A, amplitude modulation (single sideband / full carrier wave): H, amplitude modulation (single sideband / reduced carrier wave): R, amplitude modulation (single sideband / suppressed carrier wave): J, amplitude modulation (independent sideband): B, amplitude modulation (independent sideband): C, angle modulation (frequency modulation): F, angle modulation (phase modulation): G, amplitude modulation and angle modulation simultaneously or in a fixed order: D.

[0030] The nature of the signal modulating the main carrier wave consists of any one of the following: no modulation signal: 0, single channel of digital signal without using a subcarrier: 1, single channel of digital signal using a subcarrier: 2, single channel of analog signal: 3, two or more channels of digital signal: 7, two or more channels of analog signal: 8, composite method of one or more channels of analog signal and one or more channels of digital signal: 9.

[0031] The type of transmitted information consists of any one of the following: no information: N, telecommunication (aural reception): A, telecommunication (automatic reception): B, facsimile: C, data transmission / remote measurement / remote command: D, telephone (acoustic): E, television (video): F, combination from N to F: W.

[0032] In the present disclosure, the radio wave type of the power supply radio wave of the power supply unit 320 is N0N, where unmodulated: N, single channel of digital signal without using a subcarrier: 0, no information: N. In this case, it indicates that the main carrier wave is not modulated (unmodulated), there is no digital signal (single channel of digital signal without using a subcarrier), and there is no transmitted information (no information).

[0033] As a result, the absence of modulation reduces interference with other surrounding communication systems, enabling stable energy transmission. Furthermore, because there is no modulation, the transmitted energy is concentrated in the carrier wave. This allows for efficient energy transmission between the sensor unit 310 and the power supply unit 320. Since no information is transmitted, the system configuration is simple, and the design and implementation of the power supply unit 320 (transmitter) and the sensor unit 310 (receiver) can be simplified.

[0034] In this specification, with respect to power supply radio waves, the power supply unit 320 is a transmitter in the sense that it transmits power wirelessly, and the sensor unit 310 is a receiver in the sense that it receives power wirelessly. On the other hand, as will be described later, the sensor unit 310 may transmit information about the state of the sensor unit 310 or information about the measurement results from the sensor 311 as a data signal (communication radio wave) to the power supply unit 320, and the power supply unit 320 may receive such data signals. For this reason, in this specification, the sensor unit 310 and the power supply unit 320 are considered as a pair of transceivers 300, with the sensor unit 310 being an example of a first transceiver and the power supply unit 320 being an example of a second transceiver.

[0035] The power supply unit 320 transmits, for example, a power supply signal or a data signal to the sensor unit 310. The power supply unit 320 transmits the power supply signal to the sensor unit 310 using, for example, radio waves in the 920 MHz band. The power supply unit 320 also transmits a data signal to the sensor unit 310 using, for example, radio waves in the 2.4 GHz band. In this way, in system 100, a pair of transceivers 300 transmit and receive a 2.4 GHz communication radio wave (first radio wave) and a 920 MHz power supply radio wave (second radio wave) which has a lower frequency than the communication radio wave. The power supply unit 320 may also transmit the data signal to the sensor unit 310 using radio waves in the 920 MHz band or the 5 GHz band.

[0036] In this embodiment, power supply radio waves are transmitted from a plurality of power supply units 320 to a plurality of sensor units 310. That is, one sensor unit 310 receives a plurality of power supply radio waves transmitted from a plurality of power supply units 320. Note that power supply radio waves may be transmitted from one power supply unit 320 to one or a plurality of sensor units 310.

[0037] The power supply unit 320 may, for example, transmit a data signal to one sensor unit 310 or may transmit a data signal to a plurality of sensor units 310. The power supply unit 320 may, for example, transmit the same data signal as another power supply unit 320 or may transmit a data signal different from that of another power supply unit 320. The power supply unit 320 may, for example, transmit a predetermined command signal as a data signal to the sensor unit 310 or may transmit a preset signal as a data signal to the sensor unit 310.

[0038] The power supply unit 320 receives, for example, a data signal transmitted from the sensor unit 310. The power supply unit 320 may, for example, receive a data signal transmitted from one sensor unit 310 or may receive data signals transmitted from a plurality of sensor units 310. The power supply unit 320 transmits the data signal transmitted from the sensor unit 3 10 to the information processing device 500. The power supply unit 320 transmits information regarding the state of the power supply unit 320 to the information processing device 500.

[0039] The sensor unit 310 receives, for example, a power supply signal or a data signal transmitted from the power supply unit 320). When the sensor unit 310 has, for example, a power storage unit, the sensor unit 310 converts the power supply signal transmitted from the power supply unit 320 into electric power and stores the converted electric power in the power storage unit. When the sensor unit 310 has, for example, a predetermined sensor 311, the sensor unit 310 converts the power supply signal transmitted from the power supply unit 320 into electric power and drives the sensor 311 with the converted electric power.

[0040] The sensor unit 310 transmits, for example, information regarding the state of the sensor unit 310 or information regarding the measurement results from the sensor 311 as a data signal to the power supply unit 320. The information regarding the state of the sensor unit 310 includes information regarding the voltage supplied to the sensor unit 310 by wireless power supply (receiving voltage).

[0041] (3. Hardware configuration of the pair of transceivers 300) Figure 3 is a block diagram showing the hardware configuration of the pair of transceivers 300. As shown in Figure 3, the sensor unit 310 and the power supply unit 320 are separated from each other by a predetermined distance, for example. For example, the sensor unit 310 and the power supply unit 320 are installed separated by a distance of several meters.

[0042] Specifically, for example, the power supply unit 320 is fixedly installed at a predetermined high position indoors, for example, on the ceiling or wall. The sensor unit 310 is installed in various locations in the room, for example. The sensor unit 310 may also be carried by the user. The power supply unit 320 transmits a power supply signal to the sensor unit 310 using radio waves at a predetermined frequency, for example, in the 920 MHz band. The sensor unit 310 converts the power supply signal transmitted from the power supply unit 320 into power, and either charges itself with the converted power or supplies the converted power to a predetermined device (sensor 311).

[0043] As shown in Figure 3, the power supply unit 320 includes an oscillator 321, a transmitting antenna 322, a microcontroller (controller) 323, a data transceiver 324, a data transmitting / receiving antenna 325, a PLL 326, a power amplifier 327, and a power supply 328. The oscillator 321, microcontroller 323, data transceiver 324, data transmitting / receiving antenna 325, PLL 326, power amplifier 327, power supply 328, or at least a combination of these, may be mounted on a PCB (printed circuit board), for example.

[0044] The oscillator 321 generates a signal in a predetermined frequency band, for example, the 920 MHz band. The generated signal may be amplified as needed to remove unwanted frequency components.

[0045] The transmitting antenna 322 is configured to efficiently transmit, for example, radio waves in the 920 MHz band. The transmitting antenna 322 radiates the signal oscillated by the oscillator 321 as a feed wave.

[0046] The microcontroller 323 controls the operation of the power supply unit 320. The microcontroller 323 is implemented, for example, by a semiconductor element equipped with an ARM processor. The microcontroller 323 can be implemented using any integrated circuit such as GPIO, SPI, I2C, FPGA, DSP, SoC, etc. The microcontroller 323 controls, for example, the transmission of radio waves by the transmitting antenna 322.

[0047] The data transceiver 324 performs processing such as converting digital data to analog and modulating analog data. The data transceiver 324 also performs processing such as demodulating the data signal received by the data transmission antenna 325 and digitizing the demodulated data. For example, the data transceiver 324 extracts a predetermined signal from the data signal received by the data transmission antenna 325, converts it to digital data, and transmits it to the microcontroller 323.

[0048] The data transmission antenna 325 is configured to efficiently transmit and receive radio waves in the 2.4 GHz band, for example. The data transmission antenna 325 radiates data signals supplied from the data transceiver 324. The data transmission antenna 325 also receives data signals transmitted from the sensor unit 310.

[0049] The PLL 326 is an electronic circuit for controlling frequency and phase, called a Phase-Locked Loop. A capacitor is connected to the PLL 326, and the frequency of the radio waves transmitted by the transmitting antenna 322 changes according to the capacitance of the capacitor. In this disclosure, the capacitor is provided between the oscillator 321 and the PLL 326.

[0050] The capacitor is further placed between the PLL 326, the power supply 328, and GND (ground, 0V), and serves as a bypass capacitor for generating a high-quality signal. Alternatively, the capacitor may be connected to the PLL 326 and serve as a low-pass filter for generating a high-quality signal and removing unwanted high-frequency components. A low-pass filter includes a resistor and a capacitor, and functions to allow high-frequency components to flow through the capacitor while allowing low-frequency components to pass through. By installing a low-pass filter between the oscillator 321 and the PLL 326, unwanted high-frequency components can be removed, improving the quality of the output signal.

[0051] The power amplifier 327 is an electronic circuit that amplifies the signal output from the PLL 326 based on the power from the microcontroller 323 and outputs it to the transmitting antenna 322. The power supply 328 is a power supply device that supplies power to the oscillator 321 and the microcontroller 323.

[0052] In this way, in the power supply unit 320, the oscillator 321, transmitting antenna 322, PLL 326, and power amplifier 327 are controlled by the microcontroller 323 to function as a power transmitter PTx. Also in the power supply unit 320, the data transceiver 324 and data transceiver antenna 316 are controlled by the microcontroller 323 to function as a data receiver DRx.

[0053] For example, in a system 100 used in a factory, it is desirable for the power supply unit 320 to supply power above a predetermined value. Therefore, the microcontroller 323 controls the transmission of radio waves by the transmitting antenna 322 based on a feedback signal transmitted from the power supply unit 320. The feedback signal is, for example, information on the strength of the power supply radio waves, and as an example, information relating to the voltage value of a predetermined part in the sensor unit 310 is used. Based on the feedback signal, the electric field strength due to the power supply radio waves from the power supply unit 320 can be estimated.

[0054] If the transmitting antenna 322 has, for example, multiple antenna elements, the microcontroller 323 controls the transmitting antenna 322 so that it transmits the feed radio waves from the optimal antenna element. For example, the microcontroller 323 adjusts the polarization direction of the feed radio waves by switching the antenna element being driven. The microcontroller 323 also adjusts the direction of the feed signal by adjusting the driving timing of the antenna elements.

[0055] Furthermore, in the system 100 used indoors in buildings, the microcontroller 323 controls the transmission of radio waves by the transmitting antenna 322 based on the feedback signal transmitted from the power supply unit 320. If the transmitting antenna 322 is, for example, a single antenna element, the microcontroller 323 optimizes the power output from the transmitting antenna 102, for example.

[0056] The sensor unit 310 shown in Figure 3 includes, for example, a receiving antenna 312, a rectifier circuit 313, a power management unit 314, a battery 315, a data transmission / reception antenna 316, a data transceiver 317, and a microcontroller 400. The receiving antenna 312, the rectifier circuit 313, the power management unit 314, the battery 315, the data transmission / reception antenna 316, the data transceiver 317, the microcontroller 400, or at least a combination of these, may be mounted on, for example, a PCB or FPC (flexible printed circuit board).

[0057] The receiving antenna 312 is configured to efficiently receive, for example, radio waves in the 920 MHz band. The receiving antenna 312 receives the feed signal radiated from the transmitting antenna 322.

[0058] The rectifier circuit 313 rectifies the radio waves received as a power supply signal and converts them into a DC voltage.

[0059] The power management unit 314 manages the DC voltage. For example, the power management unit 314 controls the charging voltage based on the DC voltage. By controlling the charging voltage, the power management unit 314 charges the battery 315. Also, for example, when the battery 315 has stored more than a predetermined capacity of power, the power management unit 314 supplies the DC voltage to the connected components.

[0060] Furthermore, the power management unit 314 releases the power stored in the battery 315 in response to control from the microcontroller 400.

[0061] The battery 315 stores power in response to instructions from the power management unit 314. The battery 315 is implemented, for example, by a capacitor. The battery 315 also releases the stored power in response to instructions from the power management unit 314.

[0062] The microcontroller 400 controls the operation of the sensor unit 310. The microcontroller 400 is powered by a DC voltage supplied from the power management unit 314 or by power stored in the battery 315. The microcontroller 400 controls the power management unit 314 to release the power stored in the battery 315. Details of the microcontroller 400 will be described later.

[0063] Various sensors 311 are connected to the sensor unit 310. For example, the sensor unit 310 is an environmental measuring instrument. Specifically, heat sensors, temperature sensors, light sensors, humidity sensors, vibration sensors, etc., are connected to the sensor unit 310. In this embodiment, a temperature sensor and a humidity sensor are connected to the sensor unit 310 as sensors 311.

[0064] The sensor 311 connected to the sensor unit 310 is driven, for example, by a DC voltage supplied from the power management unit 314 or by power discharged from the battery 315. The microcontroller 400 continuously or intermittently monitors the voltage value at a predetermined part of the sensor unit 310, the status of the sensor 311 connected to the sensor unit 310, and information detected by the sensor 311.

[0065] The microcontroller 400 transmits the voltage value at a predetermined location on the sensor unit 310, the status of the sensor 311 connected to the sensor unit 310, and the information detected by the sensor 311 as digital data to the data transceiver 317. The sensor 311 may be built into the sensor unit 310.

[0066] The data transmission antenna 316 is configured to efficiently transmit and receive radio waves in the 2.4 GHz band, for example. The data transmission antenna 316 radiates data signals supplied from the data transceiver 317. The data transmission antenna 316 also receives data signals transmitted from the power supply unit 320. For example, the data transmission antenna 316 is driven by, for example, a DC voltage supplied from the power management unit 314 or power emitted from the battery 315.

[0067] The data transceiver 317 performs processing such as converting digital data supplied from the microcontroller 400 to analog and modulating the analog data. The data transceiver 317 also performs processing such as demodulating the data signal received by the data transceiver antenna 316 and digitizing the demodulated data. The data transceiver 317 is driven, for example, by a DC voltage supplied from the power management unit 314 or power discharged from the battery 315.

[0068] In the sensor unit 310, the receiving antenna 312 and the rectifier circuit 313 function as a power transmitter PTx that receives power supply radio waves and converts them into DC current. In addition, the sensor unit 310 also functions as a data transmitter DTx that transmits and receives communication radio waves under control from the microcontroller 400, with the data transmitting and receiving antenna 316 and the data transceiver 317.

[0069] The transmission format of the data signals transmitted and received by the data transmitter DTx is arbitrary. In particular, since the data signals transmitted and received by the data transmitter DTx are radio waves in the 2.4 GHz band, they may be signals compliant with Bluetooth® or IEEE 802.11x (i.e., so-called wireless LAN) formats. In this case, it is preferable that the data receiver DRx of the power supply unit 320 also has the function to analyze a data signal in a format that matches the format of the data signal transmitted from the data transmitter DTx. Alternatively, the information processing device 500 may also have such a function.

[0070] (4. Functional Configuration of Microcontroller 400) Figure 4 shows an example of the functional configuration of the microcontroller 400 in 2310. As shown in Figure 4, the microcontroller 400 includes a processor 403 that executes an operating system, applications, programs, etc., a main memory 401 such as RAM (Random Access Memory), an auxiliary memory 402 such as an IC card, a hard disk drive, an SSD (Solid State Drive), or flash memory, an A / D conversion unit 404, a voltage acquisition unit 405, and a communication control unit 406.

[0071] The main memory 401 stores various programs and applications (modules), and the processor 403 executes these programs and applications to realize each functional element of the overall system. These modules may be implemented in hardware by integration or other means. Furthermore, each module may be an independent program or application, or it may be implemented as a subprogram or function within a single integrated program or application.

[0072] In this specification, each module is described as the entity (subject) that performs the processing, but in reality, the processor 403, which processes various programs and applications (modules), executes the processing. The auxiliary storage device 402 stores various databases (DBs). A "database" is a functional element (storage unit) that stores a data set so that it can handle any data operations (e.g., extraction, addition, deletion, overwriting, etc.) from the processor 403 or an external computer. The implementation method of the database is not limited; for example, it may be a database management system, spreadsheet software, or text files such as XML or JSON.

[0073] The auxiliary storage device 402 stores, for example, sensing information 700 and power supply strength information 900. A specific example of sensing information 700 is detailed in Figure 7. A specific example of power supply strength information 900 is detailed in Figure 9.

[0074] The A / D conversion unit 404 performs the process of converting the analog signal input to the microcontroller 400 into a digital signal. The A / D conversion unit 404 may also include an A / D converter as a circuit. In this embodiment, the A / D conversion unit 404 converts the rectified voltage and power supply voltage, which are analog signals, into digital values.

[0075] The voltage acquisition unit 405 acquires values ​​obtained by converting the power supply voltage and rectified voltage from the A / D conversion unit 404 into digital signals. The voltage acquisition unit 405 includes a timer, a DMA controller, and a ring buffer.

[0076] The timer, for example, is composed of an oscillator circuit and is used to determine the timing for acquiring the digital values ​​of the power supply voltage and rectified voltage. Specifically, the timer generates a signal at predetermined intervals, making it possible to measure time. The timing and interval for acquiring the power supply voltage and rectified voltage by the voltage acquisition unit 405 are arbitrary; they may be acquired periodically, or they may be acquired in conjunction with the timing at which the transmission control module 412 transmits the physical quantity measured by the sensor 311 as a data signal to the power supply unit 320, etc. The term "in conjunction" here includes the meaning of timing the acquisition so that a signal representing the determination result can be transmitted to the power supply unit 320, etc., approximately simultaneously with the data signal, taking into account the time required for the detection process by the voltage detection module 413, which will be described later.

[0077] The A / D conversion unit 404 is, for example, linked to the timer of the voltage acquisition unit 405 by a MUX (Multiplexer) (not shown), and converts the analog signal acquired from the analog power supply terminal (AVDD) (not shown) into a digital signal at the timing determined by the timer. In actual design, an RFSoC (Radio Frequency System on a chip) with a functional block that enables the linking of the timer and the A / D conversion unit 404 may be used.

[0078] Furthermore, when the A / D conversion unit 404 acquires an analog signal from the analog power supply terminal, it may acquire either the rectified voltage or the power supply voltage, one at a time (so-called single acquisition), or it may acquire both (so-called scan acquisition). In addition, the A / D conversion unit 404 may also accept a reference voltage (for example, a 5V bandgap) as offset information from the analog power supply terminal.

[0079] The DMA controller controls DMA (Direct Memory Access) transfers within the microcontroller 400 without activating the processor 403 located within the microcontroller 400. The DMA controller transfers the digital signals converted by the A / D conversion unit 404 to the ring buffer. The ring buffer is an example of a buffer memory, and it temporarily stores the digital values ​​of the digital signals converted by the A / D conversion unit 404. Because the beginning and end of the storage area of ​​the ring buffer are logically connected, the storage area can be used cyclically.

[0080] The processor 403 shown in Figure 4 is realized by reading an application program stored in the main memory 401 and executing instructions contained in the application program. By operating according to the application program, the processor 403 performs functions as a receive control module 411, a transmit control module 412, a voltage detection module 413, and a sensing module 414.

[0081] The receive control module 411 controls the process by which the microcontroller 400 receives signals from external devices such as the power supply unit 320 according to a communication protocol. The transmit control module 412 controls the process by which the microcontroller 400 transmits signals to external devices such as the power supply unit 320 according to a communication protocol.

[0082] The voltage detection module 413 controls the voltage acquisition unit 405 to detect the rectified voltage output from the rectifier circuit 313 of the sensor unit 310 and the power supply voltage output from the battery 315.

[0083] The sensing module 414 continuously acquires the sensing values ​​from the sensor 311 at a predetermined frequency.

[0084] (5. Functional Configuration of Information Processing Device 500) Figure 5 shows the functional configuration of the information processing device 500. The information processing device 500 comprises a main memory 501, an auxiliary memory 502, a processor 503, an input device 504, an output device 505, and a communication control unit 506.

[0085] The main memory 501 is RAM (Random Access Memory) or the like, and stores various programs and applications (modules). The processor 503 executes these programs and applications to realize each functional element of the overall system. These modules may be implemented in hardware by integration or other means. In addition, each module may be an independent program or application, but it may also be implemented in the form of a subprogram or function within a single integrated program or application.

[0086] In this specification, each module is described as the entity (subject) that performs the processing; however, in reality, the processor 503 that processes various programs and applications (modules) executes the processing.

[0087] The auxiliary storage device 502 is a storage means such as an IC card, a hard disk drive, an SSD (Solid State Drive), or flash memory. The data stored in the auxiliary storage device 502 will be described later.

[0088] The input device 504 is an input device used for touch panels, keyboards, mice, voice input, and motion detection input via imaging by the camera unit. The output device 505 is an output device such as a monitor or display. The output device 505 may also be a device or terminal that transmits information for output to an external monitor, display, printer, or other device. The communication control unit 506 is a communication device such as a network card, wireless communication module, or mobile communication module.

[0089] The main memory 501 stores programs and applications such as the receive control module 511, the transmit control module 512, the storage module 513, the acquisition module 514, the calculation module 515, and the detection module 516. The processor 503 executes these programs and applications to realize each functional element of the information processing device 500.

[0090] The reception control module 511 controls the process by which the communication control unit 506 receives signals from an external device according to a communication protocol. The transmission control module 512 controls the process by which the communication control unit 506 transmits signals to an external device according to a communication protocol.

[0091] The memory module 513 stores information acquired from the sensor unit 310 and the power supply unit 320 in the auxiliary storage device 502. Specifically, for example, information regarding the sensing results of the sensor 311 is transmitted at a predetermined interval via the data transmitter DTx and the data receiver DRx. The memory module 513 stores the acquired information as sensing information 700 in the auxiliary storage device 502.

[0092] The acquisition module 514 acquires information contained in the communication radio waves transmitted from the sensor unit 310 or the power supply unit 320. The acquisition module 514 also acquires information regarding the signal strength of the communication radio waves transmitted from the sensor unit 310 or the power supply unit 320.

[0093] The calculation module 515 calculates the position information of the sensor unit 310. Specifically, the calculation module 515 calculates the position information of the sensor unit 310 based on known position information of the power supply unit 320 corresponding to one of the pair of transceivers 300, and the signal strength of the communication radio waves received by the power supply unit 320. The calculation module 515 is an example of a calculation unit. Details of the calculation process for the position information of the sensor unit 310 by the calculation module 515 will be described later in Figure 12.

[0094] The detection module 516 detects the presence of an object in space based on the radio wave intensity of multiple radio waves transmitted and received by a sensor unit 310 and a power supply unit 320, which form a pair of transceivers 300. That is, the computer of system 100 has a CPU, and the CPU performs the following: It detects the presence of the object in space based on the radio wave intensity of multiple radio waves transmitted and received by a pair of transceivers 30 that transmit and receive multiple radio waves with different frequency bands in space. As a result, system 100 can easily detect the presence of an object without having to directly confirm its presence. The detection module 516 is an example of a detection unit. Details of the object detection process by the detection module 516 will be described later in Figure 13.

[0095] The auxiliary storage device 502 is a storage means such as an IC card, a hard disk drive, an SSD (Solid State Drive), or flash memory. Various databases (DBs) are stored in the auxiliary storage device 502. A "database" is a functional element (storage unit) that stores a data set so that it can handle any data operations (e.g., extraction, addition, deletion, overwriting, etc.) from the processor 503 or an external computer. The implementation method of the database is not limited; for example, it may be a database management system, spreadsheet software, or text files such as XML or JSON.

[0096] The auxiliary storage device 502 stores unit information 600, sensing information 700, communication strength information 800, power supply strength information 900, and detection information 1000. The auxiliary storage device 502 includes a database necessary for storing these various types of information. The database may be implemented as a relational database or as a NoSQL database.

[0097] (6. Structure of Each Database) Next, we will describe an example of the structure of each database stored in the information processing device 500.

[0098] (6-1. Unit Information 600) Figure 6 shows an example of unit information 600. Unit information 600 is information about the sensor unit 310 and the power supply unit 320. As shown in Figure 6, unit information 600 includes unit ID 611, unit type 612, and unit position 613. Note that the configuration in Figure 6 is merely an example, and unit information 600 may include other columns.

[0099] Unit ID 611 is unique identification information for each unit that can identify the sensor unit 310 or the power supply unit 320.

[0100] The unit type 612 stores information indicating whether the unit corresponding to unit ID 611 is a sensor unit 310 or a power supply unit 320.

[0101] The unit location 613 stores information that allows for the identification of the location where the unit corresponding to unit ID 611 is installed. This location-identifying information may include, for example, the partition number when a room is divided into certain areas, or coordinate information.

[0102] (6-2. Sensing Information 700) Figure 7 shows an example of sensing information 700. Sensing information 700 is information about the sensing results acquired by the sensor 311. As shown in Figure 7, sensing information 700 includes sensing ID 711, sensor ID 712, unit ID 713, sensing date and time 714, sensor type 715, and sensing value 716. Note that the configuration in Figure 7 is merely an example, and sensing information 700 may include other columns.

[0103] Sensing ID 711 is unique identification information for each sensing result that can identify the sensing result.

[0104] Sensor ID 712 stores identification information for the sensor 311 that measured the sensing result corresponding to Sensing ID 711.

[0105] Unit ID 713 stores identification information for the sensor unit 310 to which the sensor 311 that measured the sensing result corresponding to sensing ID 711 is connected.

[0106] The sensing date and time 714 stores the date and time information of when the sensor 311 measured the sensing result corresponding to the sensing ID 711.

[0107] The sensor type 715 stores the type information of the sensor 311 that measured the sensing result corresponding to the sensing ID 711. In the illustrated example, since the sensing result is temperature information, the corresponding sensor 311 is a temperature sensor.

[0108] The sensing value 716 stores the sensing result value corresponding to the sensing ID 711. In the illustrated example, it can be confirmed that the corresponding sensor 311 measured 27.6°C.

[0109] (6-3. Communication Strength Information 800) Figure 8 shows an example of communication strength information 800. Communication strength information 800 is information regarding the strength of communication radio waves transmitted and received by the sensor unit 310 and the power supply unit 320. Communication strength information 800 is mainly communication radio wave strength information transmitted from the sensor unit 310 and received by the power supply unit 320. Note that communication strength information 800 may also include communication radio wave strength information transmitted from the power supply unit 320 and received by the sensor unit 310.

[0110] The communication strength information 800 includes a measurement ID 811, a measurement date and time 812, a receiving unit ID 813, a transmitting unit ID 814, and a radio wave strength 815. Note that the configuration in Figure 8 is merely an example, and the communication strength information 800 may include other columns.

[0111] Measurement ID 811 is unique identification information for each record that can identify the strength of the communication radio waves.

[0112] The measurement date and time 812 stores the date and time information of the measurement of the communication radio wave intensity record corresponding to measurement ID 811.

[0113] The receiving unit ID 813 stores the unit ID 611 of the power supply unit 320 that received the communication radio waves measured in the record of the communication radio wave intensity corresponding to the measurement ID 811.

[0114] The transmission unit ID 814 stores the unit ID 611 of the sensor unit 310 that transmitted the communication radio waves measured in the record of the communication radio wave intensity corresponding to measurement ID 811.

[0115] The radio wave strength value 815 stores the strength value of the communication radio wave corresponding to measurement ID 811. In other words, it stores the RSSI value corresponding to the received strength of the 2.4 GHz radio wave, which is the communication radio wave.

[0116] (6-4. Power Supply Strength Information 900) Figure 9 shows an example of power supply strength information 900. Power supply strength information 900 is information regarding the strength of the power supply radio waves transmitted from the power supply unit 320 and received by the sensor unit 310. In this embodiment, the electric field strength due to the power supply radio waves from the power supply unit 320 is estimated based on the values ​​of the power supply voltage and rectified voltage acquired by the voltage acquisition unit 405 within the sensor unit 310.

[0117] The power supply strength information 900 includes a measurement ID 911, a measurement date and time 912, a power receiving unit ID 913, and a power receiving voltage 914. Note that the configuration in Figure 9 is merely an example, and the power supply strength information 900 may include other columns.

[0118] Measurement ID 911 is unique identification information for each record that can identify the strength of the power supply radio waves.

[0119] The measurement date and time 912 stores the date and time information of the measurement of the record of the strength of the power supply radio wave corresponding to the measurement ID 911.

[0120] The power receiving unit ID 913 stores the unit ID 611 of the sensor unit 310 that received the power supply radio waves measured in the record of the power supply radio wave intensity corresponding to measurement ID 911.

[0121] The received voltage 914 stores the received voltage of the sensor unit 310, which corresponds to the strength of the power supply radio wave corresponding to the measurement ID 911. The received voltage corresponds to the values ​​of the power supply voltage and rectified voltage acquired by the voltage acquisition unit 405 within the sensor unit 310. In the case where power supply radio waves are multi-input to a single sensor unit 310 from multiple power supply units 320, the received voltage 914 may represent the voltage of the composite wave of power supply radio waves from the multiple power supply units 320.

[0122] The power supply strength information 900 may also include a power transmission unit ID. The power transmission unit ID is the identification information of the power supply unit 320 that transmitted the power supply radio waves. In this embodiment, power supply radio waves transmitted from multiple power supply units 320 are input to a single sensor unit 310 as a composite wave as a multi-input. Therefore, without identifying the power supply unit 320 that output the power supply radio waves, only the information of the sensor unit 310 that received the power supply radio waves is recorded as the power receiving unit ID 913. However, if the identification information of the transmitting power supply unit 320 is to be included in the power supply radio waves, the identification information of the transmitting power supply unit 320 may be managed as the power transmission unit ID as the strength of the power supply radio waves received by the sensor unit 310.

[0123] (6-5. Detection Information 1000) Figure 10 shows an example of detection information 1000. Detection information 1000 is information regarding the detection result of object displacement in the target space, obtained by the object detection process described later by System 1. Detection information 1000 includes detection ID 1011, detection date and time 1012, target measurement ID 1013, estimated attribute of the detected object 1014, estimated position of the detected object 1015, and estimated quantity of the detected object 1016. Note that the configuration in Figure 10 is merely an example, and detection information 1000 may include other columns.

[0124] Detection ID 1011 is unique identification information for each detection result that allows for the identification of the detection result of the target object.

[0125] The detection date and time 1012 stores the date and time information of the detection result of the object corresponding to detection ID 1011.

[0126] The target measurement ID 1013 stores the measurement ID of the radio wave strength information that was detected in the detection result of the object corresponding to detection ID 1011. The radio wave strength measurement ID includes the measurement ID 811 of the communication strength information 800 and the measurement ID 911 of the power supply strength information 900. The object detection process based on the radio wave strength information will be described later in Figures 13 and 14.

[0127] The estimated attribute 1014 of the detected object stores the estimated value of the attribute of the object detected in the detection result of the object corresponding to detection ID 1011. The process of estimating the attribute of the detected object will be described later in Figures 13 and 14, together with the object detection process based on radio wave intensity information.

[0128] The estimated position 1015 of the detected object stores the estimated position of the object detected in the detection result of the object corresponding to detection ID 1011. The process of estimating the position of the detected object will be described later in Figures 13 and 14, along with the object detection process based on radio wave intensity information.

[0129] The estimated quantity of detected objects 1016 stores the estimated quantity of objects detected in the detection result of the object corresponding to detection ID 1011. The process for estimating the position of the detected objects will be described later in Figures 13 and 14, along with the object detection process based on radio wave intensity information.

[0130] (7. Outline of the Embodiment) Next, an outline of this embodiment will be described.

[0131] (7-1. Overview of System 100 Implementation) Figure 11 is a schematic diagram showing the system 100 in an implemented state. System 100 is applied, for example, to an office building with a whole-building air conditioning system. Figure 11 is a floor plan of an office space to which system 100 is applied.

[0132] As shown in Figure 11, multiple air conditioning units are installed on the ceiling of the office space. Lighting units 210 are also installed on the ceiling of the office space. The lighting units 210 and air conditioning units 220 are controlled by a central control unit 200 (see Figure 2). The office space is divided into multiple zones for management. In the illustrated example, management spaces from Zone 1 to Zone 6 are set up. For example, the central control unit 200 individually controls the lighting units 210 or air conditioning units 220 included within each zone. Each zone is assigned an area point.

[0133] Power supply units 320 are arranged on the ceiling and walls of the office space at predetermined intervals. The power supply units 320 are generally located in the upper part of the office space. In the illustrated example, 16 power supply units 320 are arranged.

[0134] Furthermore, numerous sensor units 310 are arranged in the office space. The sensor units 310 are installed in various locations within the office space, such as on desks, furniture, or office equipment. In the illustrated example, 36 sensor units 310 are arranged at random locations. The sensor units 310 may also be installed alongside lighting equipment 210 and air conditioning equipment 220. In this way, each zone in the space is arranged with multiple pairs of power supply units 320 and sensor units 310, each pairing a transceiver with an area point assigned to that zone.

[0135] The sensor unit 310 is powered by power supplied wirelessly from the power supply unit 320. Specifically, the sensor 311 connected to the sensor unit 310 is powered by power supplied wirelessly and acquires sensing values ​​at a predetermined sampling period. The acquired sensing values ​​are transmitted to the information processing device 500 via the data transmitter DTx and data receiver DRx. In this embodiment, since the sensor unit 310 is connected to a temperature sensor and a humidity sensor, temperature and humidity can be measured at a considerable number of measurement locations in the office space, and uniform temperature and humidity control can be achieved in the control of the air conditioning equipment 220 by the central control device 200, regardless of location.

[0136] (7-2. Overview of the Sensor Unit Position Calculation Process) Next, an overview of the process for calculating the position of sensor units 310 randomly placed in the room will be described. Figure 12 is a conceptual diagram of the sensor unit 310 position calculation process. As a premise for this process, the positions of the multiple power supply units 320 are known and stored in the unit information 600 beforehand, and the position of the sensor unit 310 is unknown, so the value of the unit position 613 in the unit information 600 is blank. In addition, the data transceiver 317 of the sensor unit 310 uses radio waves in three frequency bands as advertising channels used to inform the surroundings of its position.

[0137] As shown in Figure 12, the sensor unit 310 transmits communication radio waves to a plurality of power supply units 320A to 320C. The power supply units 320A to 320C acquire RSSI values ​​indicating the strength of the received communication radio waves and transmit them to the information processing device 500. The calculation module 515 of the information processing device 500 calculates the position information of the sensor unit 310 based on the known position information of the power supply unit 320 and the radio wave strength of the communication radio waves received by the power supply unit 320.

[0138] Specifically, if the RSSI values ​​(S1 to S3) of the communication radio waves received by each of the power supply units 320A to 320C are the same, the calculation module 515 estimates that the position of the sensor unit 310 is the centroid (center) of the three power supply units 320A to 320C in terms of plane geometry. This is because the RSSI value, which is the strength of the communication radio waves, generally changes depending on the distance between the source sensor unit 310 and the destination power supply units 320A to 320C.

[0139] On the other hand, if the RSSI values ​​(S1 to S3) of the communication radio waves received by each of the power supply units 320A to 320C are different, the calculation module 515 weights the RSSI values ​​and takes a weighted average to calculate the centroid of the three power supply units 320A to 320C in plane geometry, and then calculates the position of the sensor unit 310. This is because the RSSI value changes depending on the distance between the sensor unit 310 and each of the power supply units 320A to 320C.

[0140] Note that while Figure 12 shows a configuration with three power supply units 320A to 320C, this is not the only configuration. In practice, for all power supply units 320 that receive communication radio waves transmitted from the sensor unit 310 whose position is to be calculated, the position of the target sensor unit 310 is calculated based on the position information of each unit and the RSSI value of the communication radio waves received by each unit. The calculation module 515 associates the calculated position information of the sensor unit 310 with the unit ID 611 of the sensor unit 310 and stores it in the unit position 613 of the unit information 600. By performing this process for all sensor units 310, the positions of a large number of randomly placed sensor units 310 are recorded in the unit information 600.

[0141] (7-3. Overview of object detection process based on communication radio wave intensity) Next, an overview of the object detection process based on communication radio wave intensity will be explained. Figure 13 is a diagram showing an overview of the object detection process based on communication radio wave intensity. As a prerequisite for this process, it is assumed that the positions of all sensor units 310 are known by the process described in Figure 12.

[0142] As shown in Figure 13, when a person is present between the sensor unit 310 and the power supply unit 320C, the communication radio waves transmitted from the sensor unit 310 are blocked by the person. This causes the RSSI value in the power supply unit 320C to decrease. In other words, the detection module 516 of the information processing device 500 can detect that some object (target) is present between the sensor unit 310 and the power supply unit 320C by detecting that the RSSI value of the communication radio waves acquired from the power supply unit 320 has changed from the initial S3 to S3'.

[0143] Incidentally, the RSSI value does not always show a constant value even if there are no obstacles present. This is because the RSSI value fluctuates due to other factors such as airflow in the space, changes in temperature and humidity, and interference with other radio waves. For this reason, in order to detect the presence of a person based on fluctuations in the RSSI value, system 100 can use histogram features that show the distribution of communication strength.

[0144] Specifically, system 100 acquires RSSI values ​​that change over time for each unit of time (time window), and for each time window, it creates a histogram showing the distribution of communication strength with the horizontal axis being the RSSI value and the vertical axis being the frequency of RSSI value acquisition. In this case, instead of creating a histogram showing the distribution of communication strength for the entire period, it is also possible to create a histogram showing the distribution of communication strength only for periods where the missing rate, obtained by dividing the frequency of RSSI value acquisition by the unit of time, exceeds a predetermined standard. This can reduce the burden of analysis.

[0145] The histogram showing the distribution of communication strength displays the RSSI values ​​for each advertising channel. Features are extracted from the waveform of this distribution. For example, a histogram showing the distribution of communication strength when no people are present in the space is created, and its features (first features) are extracted. A histogram showing the distribution of communication strength when people are present in the space is also created, and its features (second features) are extracted. System 100 can then determine the presence of a person in the space by evaluating whether the RSSI value targeted for person detection is similar to the first or second features.

[0146] Furthermore, system 100 may use a fluctuation factor estimation model that has learned the features of a histogram showing the distribution of communication strength for each factor that causes the RSSI value to fluctuate. The fluctuation factor estimation model takes the waveform of a histogram showing the distribution of communication strength to be evaluated as input, compares its features with previously learned features, and evaluates the similarity to output the fluctuation factor with the highest likelihood. For example, the fluctuation factor estimation model outputs whether the cause of the RSSI value fluctuation is the presence of a person or some other factor. This makes it possible to determine the attributes of the detected object.

[0147] Furthermore, the detection module 516 considers the route connecting the source sensor unit 310 and the destination power supply unit 320 as the propagation route of the communication radio waves whose RSSI values ​​have fluctuated, and detects when an object is present within the propagation route. The detection module 516 can estimate the object's movement route over time by detecting the object's position using RSSI values ​​obtained from all power supply units 320 for the communication radio waves transmitted from a considerable number of sensor units 310 as shown in Figure 11. In addition, the number of people that can be approximated as the size of an obstacle can be estimated based on the degree of fluctuation in the RSSI values.

[0148] Thus, in system 100, the detection module 516 uses the position information of the power supply unit and 320, which are stored in the memory unit beforehand, to detect the location of the object in space. Therefore, it is possible not only to detect the presence of the object but also to detect its location.

[0149] In other words, the computer in system 100 has a CPU, which performs the following: acquires the position information of the transceiver, analyzes the relationship between the position information and radio wave intensity based on the presence of the object, and estimates the position of the object. As a result, system 100 can not only determine the presence or absence of an object, but also understand the distribution and movement of the object within space.

[0150] (7-4. Overview of object detection process based on the strength of the power supply radio waves) Next, an overview of the object detection process based on the strength of the power supply radio waves will be explained. Figure 14 is a diagram showing an overview of the object detection process based on the strength of the power supply radio waves. Figure 15 is a diagram showing an example of the change in the received voltage over time in the sensor unit 310. As a prerequisite for this process, it is assumed that the positions of all sensor units 310 are known by the process described in Figure 12.

[0151] As shown in Figure 14, when a person is present between the sensor unit 310 and the power supply unit 320C, the power supply radio waves transmitted from the power supply unit 320C are shielded by the person. As a result, the radio wave intensity of the power supply radio waves at the sensor unit 310 (in this embodiment, the received voltage within the sensor unit 310) decreases, as shown in Figure 15, for example. In the example shown in Figure 15, the received voltage of the sensor unit 310 changes over time with a sampling period of 1 minute. Note that the sampling period for voltage intensity can be changed arbitrarily.

[0152] The detection module 516 of the information processing device 500 detects that some object (target) has intervened between the sensor unit 310 and the power supply unit 320C when the voltage intensity value acquired from the power supply unit 320 changes from the initial P to P'. Specifically, the detection module 516 calculates a moving average of the received voltage and compares it with a threshold indicating a steady state. This removes fluctuation noise in the received voltage and improves the accuracy of the determination. Furthermore, the detection module 516 defines a steady state as a state where there are no people in the space, and it is known that there is a positive correlation between the amount of fluctuation (decrease) in the received voltage in the steady state and the amount of obstacles (people) present in the space at that time. Therefore, the number of people present in the space can be estimated based on the amount of fluctuation in the received voltage.

[0153] In this embodiment, since the power supply radio waves are multi-input to the sensor unit 310 without distinguishing between each power supply unit 320, it is not possible to determine which of the multiple power supply units 320 and the sensor unit 310 the obstacle is located between them based solely on fluctuations in the strength of the power supply radio waves received by the sensor unit 310. For this reason, the detection module 516 can use the information on the estimated position of the object detected by fluctuations in RSSI values, as explained in Figure 13, to estimate the position of the obstacle that caused the fluctuations in the strength of the power supply radio waves.

[0154] Here, we will explain the propagation characteristics of communication radio waves and power supply radio waves. The wavelength of a communication radio wave with a frequency of 2.4 GHz is approximately 12 cm. The wavelength of a power supply radio wave with a frequency of 920 MHz is approximately 32 cm. Therefore, because the wavelength of the communication radio wave is shorter than that of the power supply radio wave, it has higher directivity, and the RSSI value will change with even slight movements of obstacles or environmental changes. In other words, by performing detection processing based on fluctuations in the RSSI value, the detection module 516 can be expected to detect a small number of small movements without fail. On the other hand, if detection processing is based on fluctuations in the RSSI value, it is expected that it will be difficult to detect large numbers of people or large movements.

[0155] In contrast, the wavelength of the feed radio wave, which has a frequency of 920 MHz, is approximately 32 cm. Therefore, the feed radio wave has higher diffraction properties than the communication radio wave, and is expected to detect large numbers of people or large movements with good sensitivity. In addition, the feed radio wave is multi-input, and superimposed radio waves are input to the sensor unit 310, so the range of the detection target can be widened. On the other hand, detection based on fluctuations in the feed radio wave may result in low sensitivity to a small number of small movements. Therefore, system 100 realizes a detection process that complements the characteristics of the two radio waves by detecting the presence of an object based on fluctuations in the radio wave intensity of two radio waves with different frequency bands. The details of this system 100 process are described below.

[0156] (8. Processing of System 100) Next, we will explain the processing of System 100.

[0157] (8-1. Radio wave transmission and reception processing) Figure 16 is a flowchart of the multiple radio wave transmission and reception processing 1600. As shown in Figure 16, in the multiple radio wave transmission and reception processing 1600, first, the power supply unit 320 transmits the power supply radio waves (step 1610). Specifically, the microcontroller 323 of the power supply unit 320 controls the power transmitter PTx to transmit the power supply radio waves from the transmitting antenna 322. At this time, the transmission is performed uniformly from the multiple power supply units 320 included in the system 100.

[0158] Next, the power receiver PRx of the sensor unit 310 receives the power supply radio waves (step 1620). Specifically, the receiving antenna 312 of the sensor unit 310 receives the power supply radio waves transmitted from the power supply unit 329. At this time, one sensor unit 310 simultaneously receives multiple power supply radio waves uniformly output from multiple power supply units 320. The rectifier circuit 313 of the sensor unit 310 rectifies the power supply radio waves and converts them into a DC voltage. The DC voltage converted by the rectifier circuit 313 is stored in the battery 315 by the power management unit 314 and supplied to components such as the sensor 311.

[0159] Next, the microcontroller 400 of the sensor unit 310 acquires the strength of the power supply radio waves (step 1630). Specifically, the voltage detection module 413 of the microcontroller 400 controls the voltage acquisition unit 405 to detect the rectified voltage output from the rectifier circuit 313 and the power supply voltage output from the battery 315 as the powered voltage. In other words, in this embodiment, the value of the powered voltage of the sensor unit 310 is acquired as an indicator of the strength of the power supply radio waves. The voltage detection module 413 continuously detects the powered voltage of the sensor unit 310, for example with a sampling period of 1 minute. The voltage detection module 413 records the detected powered voltage value as power supply strength information 900 in the auxiliary storage device 420.

[0160] Next, the microcontroller 410 of the sensor unit 310 acquires the sensing value (step 1640). Specifically, the sensing module 414 of the microcontroller 410 continuously acquires the sensing value of the sensor 311. The sensing module 414 records the acquired sensing value as sensing information 700 in the auxiliary storage device 402.

[0161] Next, the sensor unit 310 transmits a communication radio wave (step 1650). Specifically, the microcontroller 400 of the sensor unit 310 controls the data transmitter DTx to transmit a communication radio wave from the data transmission antenna 316. The communication radio wave contains the following information: - Sensing value of sensor 311 - Powered voltage of the sensor unit (information regarding the strength of the power supply radio wave)

[0162] In this case, the data transmission antenna 316 uniformly emits communication radio waves. That is, communication radio waves transmitted from one sensor unit 310 are transmitted to multiple power supply units 320.

[0163] Next, the power supply unit 320 receives the communication radio waves (step 1660). Specifically, the microcontroller 323 of the power supply unit 320 controls the data receiver DRx to receive the communication radio waves with the data transmission / reception antenna 325. With this, the transmission and reception process 1600 of multiple radio waves is completed.

[0164] (8-2. Object Detection Process) Figure 17 is a flowchart showing the object detection process 1700. As shown in Figure 17, in the object detection process 1700, first, the power supply unit 320 transmits the received data to the information processing device 500 (step 1710). Specifically, the power supply unit 320 transmits the information contained in the received communication radio waves from the data transmission antenna 325 to the information processing device 500, with the microcontroller 323 controlling the data transceiver 324. The following information is transmitted to the information processing device 500: - Sensing value of sensor 311 - Power receiving voltage of sensor unit 310 (information regarding the strength of the power supply radio waves)

[0165] Next, the information processing device 500 acquires the data transmitted from the power supply unit 320 (step 1720). Specifically, the acquisition module 514 of the information processing device 500 acquires the information contained in the communication radio waves received by the receiving control module 511. The acquisition module 514 also acquires the RSSI value, which indicates the strength of the communication radio waves received by the receiving control module 511.

[0166] The memory module 513 records the sensing value as sensing information 700 in the auxiliary storage device 502. The memory module 513 records the value of the power receiving voltage of the sensor unit 310 as power supply strength information 900 in the auxiliary storage device 502. The memory module 513 records the RSSI value as communication strength information 800 in the auxiliary storage device 502.

[0167] Next, the information processing device 500 detects the presence of the object (steps 1800 to 2100). The process for detecting the presence of the object will be described in detail in Figures 18 to 21.

[0168] Next, the information processing device 500 estimates the noise factors (step S1730). Specifically, the acquisition module 514 of the information processing device 500 acquires information about artifacts that cause fluctuations in radio wave intensity in space. Here, an artifact refers to an error or noise that is unintentionally included in the detection of an object. Artifacts include, for example, the following actions: - Driving a cleaning robot that periodically cleans the office - Operating electronic devices such as multifunction printers in the office

[0169] Here, it is known that the RSSI value of communication radio waves propagating in the space and the received voltage of power supply radio waves can fluctuate when, for example, a cleaning robot is driven or a multifunction printer is in operation. Such cleaning robots may have pre-set operating times. Furthermore, system 100 can be linked with electronic devices such as multifunction printers through settings. For this reason, the acquisition module 514 can refer to the time period when the cleaning robot was driven or acquire logs related to the operation of electronic devices linked with system 100.

[0170] In other words, if the operation of various devices corresponding to artifacts is scheduled in advance, the acquisition module 514 acquires information about the scheduled action in advance. Specifically, it reads the robot's schedule information from information in the communication packet or from the information system of the system partner, and stores the pre-specified artifacts associated with the area. On the other hand, if the action corresponding to the artifact occurs each time, the acquisition module 514 acquires information about the artifact at the time it occurs.

[0171] The detection module 516 of the information processing device 500 then determines whether the acquired artifact is causing noise in the detection result of the presence of the object. Specifically, if any artifact is present during the time period in which the presence of the object was detected, the detection module 516 estimates that the artifact is a noise factor affecting the detection result of the object. On the other hand, if no artifact is present during the time period in which the presence of the object was detected, the detection module 516 estimates that there were no noise factors affecting the detection result.

[0172] Next, the information processing device 500 outputs the detection result of the object (step 1740). Specifically, the transmission control module 512 of the information processing device 500 outputs information about the object detected by the detection module 516 to the output device 505. At this time, if an artifact that causes noise was estimated in step S1730, the transmission control module 512 simultaneously notifies the estimated noise factor. For example, if the presence of a person is detected on a holiday morning, and a cleaning robot is scheduled to operate during that time, the following information is output: ・(Detection result) *Month *Day morning: Presence detected in Zone 1 ・(Noise factor) A cleaning robot was scheduled to operate at the same time on the same day.

[0173] Thus, system 100 has a function to mark up artifacts that are estimated to be noise factors as annotations to the detection results, based on artifact information linked to spatial information such as building areas and floors. Therefore, it can not only provide the detection results of the target object, but also estimate and simultaneously notify artifacts that are noise factors in relation to the detection results. As a result, if the detection results contain noise, users such as building security guards can easily grasp the estimated factors and effectively utilize the detection results.

[0174] Further specific examples of the processing results output from system 100 will be described in detail in Figures 22 and 23. This completes the object detection process by system 100. Next, the details of the object presence detection process will be explained with several examples using Figures 18 to 21.

[0175] (8-3. First Example of Object Presence Detection) Figure 18 is a flowchart showing the details of the first example of object detection processing. As shown in Figure 18, the first example of object presence detection is characterized by detecting the presence of an object based on a combination of radio wave intensity.

[0176] In this process, first, the information processing device 500 detects the presence of an object based on a combination of the RSSI value (first radio wave intensity) and the value of the powered voltage of the sensor unit 310 (second radio wave intensity) (step 1810). Specifically, the detection module 516 determines whether or not an object (person) exists in the target space based on the combination of the two values. The following are examples of the determinations made by the detection module 516: Method 1) A method that compares the two radio wave intensity values ​​with their respective thresholds. Method 2) A method that compares the ratio of the two radio wave intensity values ​​with a threshold. Each of these methods is described in detail below.

[0177] <About Method 1> In Method 1, a threshold (first threshold) is set for determining whether a person is present in the target space based on the features of a histogram showing the distribution of communication strength obtained from RSSI values, which are two values ​​related to radio wave strength. In addition, in this method, a threshold (second threshold) is set for determining whether a person is present in the target space based on the moving average value of the received voltage of the sensor unit 310.

[0178] The first and second thresholds are set based on the RSSI value and the powered voltage of the sensor unit 310 in the steady state, where no person is present in the target space. The detection module 516 determines that a person is present in the target space when the histogram feature quantity showing the distribution of communication strength obtained from the RSSI value fluctuates beyond the first threshold, and the moving average value of the powered voltage of the sensor unit 310 fluctuates beyond the second threshold.

[0179] In other words, in this method, the detection module 516 determines that a person is present in the space if the determination based on the first radio wave intensity is "True: A person is present" and the determination based on the second radio wave intensity is "True: A person is present". By using both determinations as AND conditions to make the final determination, the detection module 516 can accurately detect two radio wave intensities with different propagation characteristics.

[0180] Specifically, determining the presence of a person based on fluctuations in RSSI values ​​has a high detection sensitivity and therefore a high negative predictive value, but conversely, it also has a high rate of false positives. In contrast, determining the presence of a person based on fluctuations in the power reception voltage of the sensor unit 310 has a high positive predictive value and high specificity. Therefore, the detection module 516 can improve the overall detection accuracy by complementaryly using the results of the two radio wave intensity-based determinations.

[0181] Furthermore, the detection module 516 may use multiple judgment results based on radio wave intensity as an OR condition. That is, the detection module 516 may determine that a person is present in the space if the judgment result based on any one of the radio wave intensity values ​​is "True: A person is present". In this case, the comprehensiveness of the detection can be increased.

[0182] <About Method 2> In Method 2, a threshold (third threshold) is set for determining whether a person is present in the space based on the ratio of two radio wave intensity values ​​in a steady state. The third threshold is set based on the ratio of the RSSI value and the powered voltage value of the sensor unit 310 in a steady state, where the state in which no person is present in the target space is considered the steady state. The detection module 516 then determines that a person is present in the target space if the ratio of the RSSI value and the powered voltage value fluctuates beyond the third threshold.

[0183] Then, if it is determined that the object does not exist (No. in step 1820), that is, if there is no change in the RSSI value that indicates the presence of the object, the detection module 516 determines that the object does not exist. In this case, the detection module 516 repeats the process of step 1810 at predetermined intervals set in advance.

[0184] On the other hand, if it is determined that an object exists (Yes in step 1820), that is, if there is a fluctuation in the RSSI value that indicates the presence of an object, the information processing device 500 detects the number of objects and their respective locations. Specifically, the detection module 516 of the information processing device 500 estimates the number of objects from the degree of change in the RSSI value and the received voltage. That is, a state where there are no people in the space is considered a steady state, and it is known that there is a positive correlation between the amount of fluctuation (decrease) in the RSSI value in the steady state and the amount of obstacles (people) present in the space at that time. Therefore, the number of people present in the space can be estimated based on the amount of fluctuation in the RSSI value. Furthermore, the detection module 516 detects the location where a person has been present from the propagation path of radio waves whose intensity has changed. This concludes the first example of object presence detection.

[0185] In this way, the detection module 516 detects the presence of an object in space based on a combination of the radio wave strengths of multiple radio waves transmitted and received by the sensor unit 310 and the power supply unit 320. Therefore, it can improve detection accuracy compared to other systems that detect the presence of a person based on the radio wave strength of a single radio wave.

[0186] (8-4. Second Example of Object Presence Detection) Figure 19 is a flowchart showing a second example of the details of the object detection process. As shown in Figure 19, the second example of object presence detection is characterized by detecting the presence of an object based on the strength of the communication radio waves and detecting the quantity of the object based on the strength of the power supply radio waves.

[0187] In this process, first, the information processing device 500 detects the presence of an object based on the strength of the communication radio waves (step 1910). Specifically, the detection module 516 of the information processing device 500 determines whether the feature quantity of the histogram showing the distribution of communication strength obtained from the RSSI value exceeds a threshold indicating the presence of a person.

[0188] If the detection module 516 determines that the object does not exist (No. in step 1920), that is, if there is no change in the RSSI value that indicates the presence of the object, the detection module 516 determines that the object does not exist. In this case, the detection module 516 repeats the process in step 1910 at predetermined intervals.

[0189] On the other hand, if it is determined that an object exists (Yes in step 1820), that is, if it is determined that there is a fluctuation in the RSSI value that indicates the presence of an object, the information processing device 500 detects the quantity of objects based on the intensity of the power supply radio waves (step S1930). Specifically, the detection module 516 of the information processing device 500 detects the degree of the quantity of objects based on the moving average value of the power receiving voltage of the sensor unit 310.

[0190] In other words, the computer in system 100 has a CPU, which performs the following: it detects the presence of an object based on the first radio wave intensity, and if it determines that an object exists, it estimates the quantity based on the second radio wave intensity. This allows system 100 to detect a small number of people in stages, from a small number to a large number, improving the accuracy of the person estimation.

[0191] Here, the degree of quantity includes not only the numerical value of the quantity but also information indicating the scale of the quantity of the object. Information indicating the scale of the quantity may be expressed as stages assigned based on a predetermined range of quantities, such as "small, medium, large." Alternatively, information indicating the scale of the quantity may be expressed by specific numerical ranges, such as "less than 10 people, 10 people or more but less than 20 people, 20 people or more."

[0192] Next, the information processing device 500 detects the position of each object (step 1940). Specifically, the detection module 516 of the information processing device 500 detects the position of a person based on the fluctuation of the RSSI value around the sensor unit 310 where the power supply voltage has fluctuated. This completes the second example of object presence detection.

[0193] Thus, in system 100, the detection module 516 detects the presence of an object in space based on the signal strength of the communication radio waves transmitted and received by the transceiver, and then detects the number of the object present in the space based on the signal strength of the power supply radio waves, which have a lower frequency than the communication radio waves. In other words, the detection module 516 performs a screening that is a primary determination of whether or not an object exists based on the signal strength of the first radio wave, and performs a state determination that is a secondary determination of whether or not an object exists based on the signal strength of the second radio wave. For this reason, by taking advantage of the characteristics of the power supply radio waves, which have a lower frequency and longer wavelength than the communication radio waves, it is expected that the system can detect large numbers of people or large movements of people with high sensitivity.

[0194] In other words, the computer in system 100 has a CPU, which performs the following: it makes a primary determination of the presence of an object based on the high-frequency radio wave intensity, and a secondary determination of the presence of an object based on the low-frequency radio wave intensity, and then makes a determination by combining both. As a result, system 100 can evaluate from minute changes to large shielding in a multi-layered manner, reducing false detections and missed detections, and improving detection accuracy.

[0195] (8-5. Third Example of Object Presence Detection) Figure 20 is a flowchart showing a third example of the details of the object detection process. As shown in Figure 20, the third example of object presence detection is characterized by detecting the presence of objects based on the strength of communication radio waves, and then detecting the quantity of objects based on the strength of power supply radio waves when the number of detected objects exceeds a threshold.

[0196] In this process, first, the information processing device 500 detects the presence of an object based on the strength of the communication radio waves (step 2010). The detection module 516 of the information processing device 500 determines whether the feature quantity of the histogram showing the distribution of communication strength obtained from the RSSI value exceeds a threshold indicating the presence of a person, and detects an estimated quantity.

[0197] Next, the information processing device 500 compares the quantity of detected objects with a preset threshold (step 2020). Specifically, at this time, the detection module 516 compares the quantity of detected objects with a preset threshold.

[0198] If the detected quantity does not exceed the threshold (No. in step 2030), the information processing device 500 detects the position of each object based on the strength of the communication radio waves (step 2050). Specifically, the detection module 516 of the information processing device 500 detects the position of a person based on the fluctuation of the RSSI value.

[0199] On the other hand, in step S2030, if the detected quantity exceeds a threshold (Yes in step 2030), the information processing device 500 detects the quantity of objects based on the strength of the power supply radio waves. Specifically, the detection module 516 of the information processing device 500 estimates the quantity of objects based on fluctuations in the power supply voltage.

[0200] Subsequently, the information processing device 500 detects the position of each object (step 2050). Specifically, the detection module 516 of the information processing device 500 detects the position of a person based on the change in RSSI value in the sensor unit 310 where the power supply voltage has changed. This completes the third example of object presence detection.

[0201] Thus, in system 100, the detection module 516 detects the number of objects present in space based on the signal strength of the power supply radio waves when the number of objects detected by the signal strength of the communication radio waves transmitted and received by the transceiver 300 exceeds a predetermined threshold. Therefore, by taking advantage of the characteristics of power supply radio waves, which have a lower frequency and longer wavelength than communication radio waves, it is expected that detection will be highly sensitive even when there are large numbers of people or when there is a lot of movement.

[0202] (8-6. Fourth Example of Object Presence Detection) Figure 21 is a flowchart showing the fourth example of the details of the object detection process. As shown in Figure 21, the fourth example of object presence detection is characterized by detecting the number of objects based on the intensity of the communication radio waves and the power supply radio waves, and adopting the larger value among the estimated number of detected objects as the detected value.

[0203] In this process, first, the information processing device 500 detects the presence of an object based on the first radio wave intensity (step S2110). Specifically, the detection module 516 of the information processing device 500 determines whether the feature quantity of the histogram showing the distribution of communication intensity obtained from the SSI value exceeds a threshold indicating the presence of a person.

[0204] Next, the information processing device 500 obtains a first estimate of the quantity of detected objects (step S2120). Specifically, the detection module 516 of the information processing device 500 estimates the quantity of objects from the histogram features and obtains a first estimate.

[0205] Next, the information processing device 500 detects the presence of an object based on the second radio wave intensity (step S2130). Specifically, the detection module 516 of the information processing device 500 detects the presence of an object based on fluctuations in the moving average of the received voltage.

[0206] Next, the information processing device 500 obtains a second estimate of the quantity of detected objects (step S2140). Specifically, the detection module 516 of the information processing device 500 estimates the quantity of objects based on the degree of fluctuation of the moving average of the received voltage and obtains a second estimate.

[0207] Next, the information processing device 500 compares the first estimated value with the second estimated value (step S2150). Specifically, the detection module 516 of the information processing device 500 compares the magnitudes of the first estimated value and the second estimated value.

[0208] Next, the information processing device 500 selects the larger value as the detected value of the object (step S2160). Specifically, the detection module 516 of the information processing device 500 adopts the larger of the first and second estimated values ​​as the detected value of the object. This completes the fourth example of object presence detection.

[0209] Thus, in system 100, the detection module 516 uses the larger of the first estimated value detected from the signal strength of the communication radio waves and the second estimated value detected from the signal strength of the power supply radio waves as the detected value for the quantity of objects present in space. This improves the accuracy of detecting the quantity of objects.

[0210] In other words, the computer in system 100 has a CPU, which performs the following: calculates a first estimated value of the quantity based on the first radio wave intensity, calculates a second estimated value of the quantity based on the second radio wave intensity, and adopts the larger of the first and second estimated values ​​as the final detected value. As a result, system 100 is suitable for both small-scale and large-scale detection, preventing underestimation and enabling highly reliable quantity estimation.

[0211] (9. Processing Results) Next, the processing results by system 100 will be explained.

[0212] (9-1. Measurement Results 2200 from Sensor 311) Figure 22 shows the measurement results 2200 from sensor 311. Note that in this figure, the lighting equipment 210 and power supply unit 320 are omitted from the illustration for explanatory purposes. As shown in Figure 22, the measurement results 2200 from sensor 311 display the temperature information sensed by each sensor unit 310. In the illustrated example, zones 1 and 2 show 26°C, zones 3 and 4 show 27°C, and zones 5 and 6 show 28°C. The central control device 200 determines the control values ​​of the air conditioning equipment corresponding to each zone based on the acquired temperature information. Humidity is also acquired in the same way for each sensor unit 310.

[0213] Furthermore, although the illustrated example shows multiple sensor units 310 within a single zone indicating the same temperature, this is not always the case. If there are temperature variations within a single zone, they will be displayed as different temperatures, allowing for the detection of subtle temperature variations within a zone. Additionally, it is possible to check the difference in sensing values ​​between temperature sensors installed within the air conditioning system and temperature sensors placed in the living space, enabling highly accurate air conditioning control.

[0214] (9-2. Regarding the detection results 2300 of objects) Figure 23 shows the detection results 2300 of objects. Note that in this figure, the lighting equipment 210 and air conditioning equipment 220 are omitted from the illustration for explanatory purposes. As shown in Figure 22, the detection results 2300 detect the presence of people, and the number of people and the path they moved are displayed. In the example shown, two people moved from zone 2 to zone 1, one person moved from zone 4 to zone 5, and one person moved from zone 5 to zone 6. Note that the travel time can also be displayed on this screen. In this way, the detection module 516 can detect the presence of objects within each zone and the area point corresponding to each zone.

[0215] In this way, the system 100 can detect the presence of a person in a room, and for example, by automatically turning off the lighting equipment 210 and the air conditioning equipment 220 when no one is present, it can contribute to energy saving.

[0216] As explained above, system 100 detects the presence of an object in space using the radio wave strengths of multiple radio waves in different frequency bands. By using multiple radio waves in different frequency bands in this way, it is possible to adjust and switch the detection sensitivity, and the influence of environment-dependent radio wave strength can be reduced in the final determination.

[0217] Furthermore, by using multiple radio waves in different frequency bands, system 100 can perform a determination with relatively simple calculations, compared to other systems that detect the presence of an object using only the communication strength of a single frequency band, for example, by using two indicators with different detection sensitivity spectra.

[0218] Furthermore, in system 100, the object detection system is configured with a sensor unit 310 that measures predetermined physical quantities as an environmental measuring instrument, a power supply unit 320 that wirelessly supplies power to the sensor unit 310, and an information processing device 500 that monitors their operation. In other words, the object detection function is implemented as a secondary function of the wireless power supply type sensing system, including the sensor unit 310, without using a dedicated human presence sensor device to detect the presence of objects. Therefore, the system configuration can be simplified compared to a configuration that uses a dedicated human presence sensor device.

[0219] Furthermore, in system 100, since multiple sensor units 310 and power supply units 320 that constitute the transceiver 300 are arranged, the influence of environmental factors occurring in a part of the space can be limited to area-level determination, thereby reducing the impact on the final determination of the entire space.

[0220] Furthermore, since system 100 uses the value of the receiving voltage of the sensor unit 310 as the strength of the power supply radio wave, robustness as a system for detecting the presence of a person can be ensured. In other words, if the presence of a person is detected based on the radio wave strength of multiple communication radio waves, the radio wave strength of the communication radio waves does not depend on the space in which they propagate, so the same determination process can be performed by intercepting the communication radio waves near the target space. That is, if there is someone attempting to enter the target space, there is a risk that information such as the fact that the room is unoccupied may be extracted. On the other hand, the receiving voltage of the sensor unit 310, which is used as an indicator of the radio wave strength of the power supply radio wave, depends on the space in which the power supply radio wave propagates, so even if a single value is obtained, the same determination cannot be made outside the area, and information on presence or absence cannot be immediately extracted.

[0221] Furthermore, since system 100 detects the presence of a person using the RSSI value of the advertised packet, it is possible to suppress the influence of variations in signal strength due to the contents of the signal packet on the detection result.

[0222] Furthermore, system 100 uses the signal strength of the communication radio waves transmitted from the advertised sensor unit 310 and the received voltage received by the sensor unit 310 by the power supply radio waves. In other words, since the information that was originally intended to be exchanged as a wireless power supply system is used for detecting the presence of a person, there is no need to send or receive additional data for detecting the presence of a person. Moreover, since one of the transceivers 300 is a wireless power supply compatible sensor unit 310, there is no need to improve energy efficiency compared to existing wireless power supply compatible sensor units 310 when performing human presence detection.

[0223] Furthermore, since system 100 detects the presence of an object in space using the radio wave intensity of multiple radio waves in different frequency bands, the detectable range can be expanded by using radio waves with a wide range of wavelengths. In addition, by using long-wavelength power-feeding radio waves, it is possible to use a different sensitive spectrum than that of short-wavelength, highly directional communication radio waves in situations with high levels of disturbance, such as indoor congestion, and stable environmental measurements can be expected even in highly disturbed environments.

[0224] Furthermore, system 100 allows for the classification of spatial statuses with simple processing by setting the frequency band of the radio waves used for determination and the determination index associated with the status, based on the characteristics of multiple radio waves in different frequency bands, according to pre-defined statuses. This can also be easily implemented by updating the firmware of existing multi-band communication standards such as Wi-Fi® routers and wireless power supply devices.

[0225] Furthermore, in system 100, the detection module 516 of the information processing device 500 detects the presence of an object within a zone for each area point linked to a pair of transceivers arranged as multiple pairs. By integrating the determination results based on fluctuations in radio wave intensity obtained from multiple power supply units 320 and sensor units 310 installed in the space, the system as a whole can exponentially increase its sensitivity to detecting the presence or absence of people throughout the entire space.

[0226] For example, if there are four power supply units 320 and one sensor unit 310, there will be four pairs of transceivers, and four possible combinations of RSSI values ​​and the power received by the sensor unit 310. On the other hand, if this is changed to four power supply units 320 and four sensor units 310, the number of possible combinations of RSSI values ​​and the power received by the sensor unit 310 will be 4 to the power of 4, or 256. As a result, the number of evaluation samples of RSSI values ​​and power received strength to be judged will increase exponentially, and it is expected that the detection level can be dramatically improved.

[0227] Furthermore, in system 100, the detection module 516 of the information processing device 500 may calculate the likelihood of an object being present in each zone for each area point. Specifically, in the example shown in Figure 23, the following information may be output: - Likelihood of a person being present in zone 1: L1 - Likelihood of a person being present in zone 2: L2 - Likelihood of a person being present in zone 3: L3 - Likelihood of a person being present in zone 4: L4 - Likelihood of a person being present in zone 5: L5 - Likelihood of a person being present in zone 6: L6 In this way, the detection module 516 can determine the presence or absence of a person in each zone by outputting the likelihood of a person being present for each area point.

[0228] Furthermore, the detection module 516 may detect the presence of an object within a zone based on the feature quantities of the likelihood combination calculated for each area point. Specifically, if the feature quantities of the likelihood L1 for the presence of a person in zone 1 and the respective likelihoods L2 to L4 for the presence of people in the surrounding zones 2 to 4 match the typical occupancy pattern when a person is doing desk work in zone 1, the detection module 516 determines that a person is doing desk work in zone 1. In this way, by comparing the feature quantities of the likelihood combination including the surrounding area with known feature quantities, the detection module 516 can estimate not only the presence of an object within a zone but also its behavioral patterns.

[0229] In other words, the computer in system 100 has a CPU, which performs the following: calculates the likelihood of an object's existence for each area point, extracts features by combining the likelihoods of multiple area points, and detects the presence of the object based on these features. As a result, system 100 can reflect complex occupancy patterns and behavioral states, enabling highly accurate presence detection even under complex usage conditions.

[0230] (10. Modified Versions) Next, a modified version of system 100 will be described.

[0231] In the above embodiment, the presence of an object is detected based on the signal strength of the power supply radio wave and the communication radio wave, but this is not limited to this. System 1 may detect the presence of an object based on the signal strength of two communication radio waves. For example, a wireless LAN standard using radio waves in two frequency bands, 2.4 GHz and 5 GHz, may be adopted as the communication standard between the sensor unit 310 and the power supply unit 320. In this case, the presence of an object in space may be detected based on the signal strength of the 2.4 GHz radio wave and the 5 GHz radio wave, both of which are used as communication radio waves.

[0232] Furthermore, the communication band used for power supply is not limited to the 920 MHz band; any UHF band may be used, for example, the 868 MHz band in Europe and the 915 MHz band in the United States. Other frequency bands belonging to the UHF band are also acceptable.

[0233] Furthermore, the communication bandwidth for data communication is not limited to the 2.4 GHz band; a frequency band within a range of ±10% of 2.4 GHz may also be used. For example, a 2.45 GHz band can be used. Alternatively, a communication bandwidth near 5.7 GHz may also be used. While high frequency bandwidths are required for high-speed data communication, lower frequency bandwidths can be used for power supply compared to data communication.

[0234] Furthermore, while the above embodiment detects the presence of an object based on the strengths of two radio waves, this is not limited to this. In other words, the system 100 may detect an object based on the strengths of three or more radio waves.

[0235] Furthermore, in the above embodiment, the presence of an object is detected using the features of a histogram showing the distribution of communication signal strength. However, this is not limited to this. For example, the presence of an object may be detected based on the trend of changes in communication signal strength over time.

[0236] Furthermore, in the above embodiment, the power supply unit 320 transmits information on the powered voltage of the sensor unit 310 to the information processing device 500 as information included in the communication radio waves received by the power supply unit 320, but this is not limited to this configuration. In other words, the sensor unit 310 may transmit information on the powered voltage to the information processing device 500.

[0237] Furthermore, although the above embodiment shows a configuration in which power supply radio waves transmitted from multiple power supply units 320 are multi-input as a composite wave to a single sensor unit 310, this is not limited to this configuration. That is, instead of a composite wave, the sensor unit 310 may receive a single power supply radio wave transmitted from a single power supply unit 320.

[0238] (11. Other Embodiments) Next, other configurations of the present technology will be described. In the following description, the same reference numerals will be used for components identical to those in the embodiments described above, and repeated explanations will be omitted.

[0239] (11-1. Second Embodiment) Figure 24 is a diagram illustrating the process of detecting an object using information on communication quality in the second embodiment. As shown in Figure 24, in this embodiment, under normal circumstances, the data transmitter DTx of the sensor unit 310 performs normal packet transmission (step S2110). As a result, the data receiver DRx of the power supply unit 320 receives the packet normally (step S2120). The communication data obtained here includes the sensing value of the sensor 311 and the power receiving voltage of the sensor unit 310 (information on the strength of the power supply radio waves).

[0240] Next, the data receiver DRx of the power supply unit 320 notifies the detection module 516 of the information processing device 500 of the received communication data (step S2130). Based on the information regarding radio wave strength contained in the notified communication data (information regarding the strength of the power supply radio wave and information regarding the strength of the communication radio wave), the detection module 516 detects the presence of an object in the target space (step S2140). This detection process is the same as in the embodiment described above.

[0241] On the other hand, in this embodiment, when packet transmission from the data transmitter DTx of the sensor unit 310 is performed, the communication quality deteriorates due to the presence of an object or disturbance (step S2150), exhibiting different behavior. Specifically, first, the data receiver DRx of the power supply unit 320 detects a low packet rate state based on the occurrence of lost or retransmitted received packets (step S2160).

[0242] At this point, the data receiver DRx notifies the detection module 516 of communication data indicating a low packet rate ratio, i.e., a decrease in communication quality (step S2170). Here, the packet rate ratio is the actual packet reception frequency divided by the theoretically expected packet reception frequency, and this corresponds to the communication quality, which changes moment by moment. In addition to information indicating that the communication quality is a low packet rate, this communication data includes the sensing value of the sensor 311 and the powered voltage of the sensor unit 310 (information regarding the strength of the power supply radio waves).

[0243] The detection module 516 estimates the presence of an object based on information received at a low packet rate (step S2180). Specifically, the detection module 516 first compares the packet rate with a preset threshold. If the packet rate is equal to or greater than the threshold, it performs the usual object detection process based on radio wave strength. On the other hand, if the packet rate is less than the threshold, the detection module 516 performs the object detection process based on the packet rate instead of the object detection process based on radio wave strength (step S2180). Specifically, for example, it detects the presence of a person when the packet rate ratio falls below the threshold for determining the presence or absence of an object. The threshold for determining presence or absence and the threshold for determining whether or not to perform detection based on the packet rate ratio may be the same. Also, the threshold for determining presence or absence may be smaller or larger than the threshold for determining whether or not to perform detection based on the packet rate ratio.

[0244] In this embodiment, the packet rate threshold for switching the object detection method can be set by multiple methods. For example, past communication logs may be analyzed, and the packet rate distribution obtained when an object is present and when it is not may be compared, and a value that can identify the presence of an object may be set as the threshold. Alternatively, a rule-based method can be applied, which uses attribute information such as the structure and use of the space to set the threshold. For example, in an environment with many obstructions, even if there is no object (person) in the target space, the packet rate ratio is expected to change compared to an environment with few obstructions. Therefore, the threshold for determining whether or not to perform detection based on the packet rate ratio may be changed based on the input of attribute information such as the layout of the target space. Furthermore, the stability and adaptability of detection may be improved by combining this with a method that dynamically corrects the threshold based on measured values ​​obtained during operation.

[0245] System 100 determines the presence of an object based on communication quality, i.e., the packet rate. Specifically, for example, if an object is present in the target space, the success rate of reception may decrease due to shielding or multiple reflections of radio waves by people or other objects, resulting in the packet rate falling below a standard value. On the other hand, if no object is present, there are fewer obstructions in the communication path, and the packet rate tends to remain high. Therefore, the detection module 516 can determine the presence or absence of an object in the target space by monitoring this fluctuation in the packet rate. In this way, the detection module 516 can appropriately switch between detection based on radio wave strength and detection based on packet rate, enabling flexible object detection that takes into account fluctuations in communication quality.

[0246] In other words, this embodiment is characterized by its use of communication quality, such as fluctuations in the packet rate ratio, as an indicator for object detection. Conventionally, packet loss and retransmissions were treated as "quality degradation" or "fault factors" in the communication channel, but in this embodiment, these phenomena are instead used as signals for object detection. This complements conventional detection methods based on radio wave intensity, enabling stable detection under a wider range of conditions.

[0247] Furthermore, when setting the threshold for determining whether or not to perform detection based on the packet rate ratio, for example, the target space may be made unoccupied before the system operation begins, and the packet rate distribution measured there may be saved as a reference value. Subsequently, in the actual operating environment, the correlation between the packet rate distribution when people are present and when they are absent is analyzed, and the threshold is determined based on the difference between the two. In this way, presence / absence determination based on packet rate may be operated using statistically supported reference values.

[0248] Furthermore, system 100 can combine packet rate-based detection processing with conventional signal strength-based detection processing. For example, hybrid control is possible in which presence or absence is normally determined by received signal strength, and only when communication quality deteriorates does it switch to detection using packet rate. This allows for stable and flexible object detection while absorbing fluctuations in the radio wave environment.

[0249] In other words, the computer in system 100 has a CPU, which performs the following: calculates the communication quality of the first radio wave, and if the communication quality falls below a predetermined threshold, detects the presence of an object based on the communication quality. This allows system 100 to utilize indicators other than radio wave strength, and improves the stability of detection even in noisy environments.

[0250] (11-2. Third Embodiment) Figures 25 to 27 illustrate a third embodiment, which describes a method for detecting an object using a single-frequency radio wave.

[0251] Figure 25 illustrates monostatic sensing using a power-supplying radio wave (second radio wave). Here, monostatic sensing refers to a method of detecting the presence of an object based on the received signal, where one of a pair of transceivers transmits a radio wave and the transceiver itself receives the signal. In other words, a configuration in which both transmission and reception are performed by the same transceiver is called monostatic sensing.

[0252] As shown in Figure 25, in this embodiment, the power supply unit 320 includes a power receiver PRx in addition to the power transmitter PTx and data receiver DRx. In monostatic sensing using a single-frequency radio wave by system 100, the power supply radio wave Rw transmitted from the power transmitter PTx of the power supply unit 320... ｐ However, it is reflected by the object (person), and the reflected power supply radio wave ref_Rw ｐ It then reaches the power receiver PRx of the same power supply unit 320.

[0253] At this time, the power receiver PRx receives the reflected wave ref_Rw of the power supply radio waves from the object. ｐ The system 100B detects the presence of an object in the target space by receiving the signal and acquiring its intensity via the detection module 516. This type of monostatic sensing enables object detection without the need for additional signal sources. In the illustrated example, a monostatic sensing method using a single-frequency radio wave is described using a power supply radio wave (second radio wave), but this is not limited to this. In other words, the system 100 may also use a communication radio wave (first radio wave) as a monostatic sensing method using a single-frequency radio wave. In this case, the sensor unit 310 includes a power receiver PRx and a data transmitter DTx, as well as an additional data receiver DRx.

[0254] Figure 26 illustrates bistatic sensing using a power-supplying radio wave (second radio wave). Here, bistatic sensing is a method in which one of a pair of transceivers transmits a radio wave, and the other transceiver 300 receives it, thereby detecting the presence of an object based on the received signal. In other words, a configuration in which transmission and reception are handled by different transceivers 300 is called bistatic sensing.

[0255] As shown in Figure 26, in this embodiment, the power supply unit 320 includes a power transmitter PTx, a data receiver DRx, and a power receiver PRx, similar to the example in Figure 22. In bistatic sensing using a single-frequency radio wave by the system 100, the power supply radio wave Rw is transmitted from the power transmitter PTx of one of the power supply units 320 in the other pair of transceivers 300. ｐ The reflected radio wave ref_Rw is reflected by the object and supplied to the power receiver PRx of the power supply unit 320 in the other pair of transceivers 300. ｐ It arrives as such.

[0256] At this time, the reflected wave ref_Rw ｐ The power receiver PRx, upon receiving the signal, notifies the detection module 516 of its intensity, and the detection module 516 determines the presence of the object based on this information. In other words, in this embodiment, by dividing the transmission and reception between different power supply units 320, a variety of radio wave propagation paths in space can be captured. This makes it possible to detect a variety of objects that cannot be obtained with a monostatic sensing configuration by using bistatic sensing with a single-frequency power supply radio wave. In the illustrated example, bistatic sensing using a power supply radio wave (second radio wave) has been described, but this is not limited to this. In other words, in system 100, a communication radio wave (first radio wave) may be used as bistatic sensing using a single-frequency radio wave. In this case, the sensor unit 310 includes a power receiver PRx, a data transmitter DTx, and a data receiver DRx, similar to monostatic sensing.

[0257] Figure 27 illustrates multistatic sensing using a power supply radio wave (second radio wave). Here, multistatic sensing refers to a method of detecting the presence of an object based on multiple received signals obtained when a radio wave transmitted by one of a pair of transceivers 300 is received by multiple transceivers 300 in the other pair of transceivers 300. In other words, a configuration that combines a transmission source and multiple receiving points is called multistatic sensing.

[0258] As shown in FIG. 27, in the present embodiment, the power supply unit 320 includes a power transmitter PTx, a data receiver DRx, and a power receiver PRx, similar to the example of FIG. 22. In the multi-static sensing using a single-frequency radio wave by the system 100, the power supply radio wave Rw transmitted from the power transmitter PTx of the power supply unit 320 in a pair of transceivers ｐ is reflected by the object and reaches the power receiver PRx of the power supply unit 320 in a plurality of other pairs of transceivers as the reflected wave ref_Rw of the power supply radio wave ｐ .

[0259] At this time, each power receiver PRx transmits the reflected wave ref_Rw of the power supply radio wave received by each to the information processing device 500, and the detection module 516 analyzes its intensity and time-series characteristics, so that the presence of the object in the target space can be detected. That is, in multi-static sensing, by providing a plurality of reception points while sharing the transmission source, observation from multiple viewpoints with respect to the object becomes possible, and the reliability of detection can be improved. In the illustrated example, multi-static sensing using a power supply radio wave (second radio wave) has been described, but this is not the limit. That is, in the system 100, communication radio waves (first radio waves) may be used as multi-static sensing using a single-frequency radio wave. In this case, the sensor unit 310 includes a power receiver PRx, a data transmitter DT x, and a data receiver DRx, similar to monostatic sensing ｐ .

[0260] (11-3. Fourth Embodiment) FIGS. 28 to 31 will describe a method for detecting an object using radio waves of multiple frequencies as the fourth embodiment

[0261] Figure 28 illustrates monostatic sensing using communication radio waves (first radio waves) and power supply radio waves (second radio waves). As shown in Figure 28, in this embodiment, the power supply unit 320 includes a power transmitter PTx and a data receiver DRx, as well as an additional power receiver PRx. In this embodiment, the sensor unit 310 includes a power receiver PRx and a data transmitter DTx, as well as an additional data receiver DRx.

[0262] Furthermore, in monostatic sensing using multiple frequency radio waves by system 100, the power supply radio wave Rw transmitted from the power transmitter PTx of the power supply unit 320... ｐ And the communication radio wave Rw transmitted from the data transmitter DTx of the sensor unit 310 ｃ These are reflected by the target object. And the reflected wave of the power supply radio wave ref_Rw ｐ The power receiver PRx of the power supply unit 320 receives the following: the reflected signal of the communication radio wave ref_Rw ｃ This information is received by the data receiver DRx of the sensor unit 310.

[0263] At this time, the power receiver PRx of the power supply unit 320 and the data receiver DRx of the sensor unit 310 provide the intensity and quality of the reflected waves they have received to the detection module 516 via wired or wireless communication. The detection module 516 can detect the presence of an object with higher reliability by comprehensively analyzing these signals from multiple frequency bands. In other words, by using radio waves of different frequencies, namely communication radio waves and power supply radio waves, in the system 100B, stable object detection can be achieved even in disturbed or noisy environments compared to the case of a single frequency.

[0264] Figure 29 illustrates bistatic sensing using communication radio waves (first radio waves) and power supply radio waves (second radio waves). As shown in Figure 29, in this embodiment, the power supply unit 320 includes a power transmitter PTx, a data receiver DRx, and a power receiver PRx, similar to the configuration shown in Figure 28. The sensor unit 310 also includes a power receiver PRx, a data transmitter DTx, and a data receiver DRx.

[0265] Furthermore, in bistatic sensing using multiple frequency radio waves by system 100, the power supply radio wave Rw transmitted from the power transmitter PTx of one of the power supply units 320 ｐ And the communication radio wave Rw transmitted from the data transmitter DTx of the sensor unit 310 ｃ These are reflected by the target object. And the reflected wave of the power supply radio wave ref_Rw ｐ The power receiver PRx of the power supply unit 320 in the other pair of transceivers receives the reflected signal ref_Rw of the communication radio waves. ｃ This information is received by the data receiver DRx of the sensor unit 310 in the other pair of transceivers.

[0266] At this time, the power receiver PRx of the power supply unit 320 and the data receiver DRx of the sensor unit 310 provide the intensity and quality of the reflected waves they have received to the detection module 516 via wired or wireless communication. The detection module 516 can detect the presence of an object with high reliability by comprehensively analyzing these signals from multiple frequency bands. In other words, by using radio waves of different frequencies, namely communication radio waves and power supply radio waves, in the system 100, and by separating the transmission source and the receiving point, stable object detection can be achieved even in disturbed or noisy environments, compared to the case of a single frequency or single path.

[0267] Figure 30 illustrates multistatic sensing using communication radio waves (first radio waves) and power supply radio waves (second radio waves). As shown in Figure 30, in this embodiment, the power supply unit 320 includes a power transmitter PTx, a data receiver DRx, and a power receiver PRx, similar to the configuration shown in Figures 28 and 29. The sensor unit 310 also includes a power receiver PRx, a data transmitter DTx, and a data receiver DRx.

[0268] Furthermore, in multi-static sensing using multiple frequency radio waves by system 100, the power supply radio wave Rw transmitted from the power transmitter PTx of the power supply unit 320 ｐ And the communication radio wave Rw transmitted from the data transmitter DTx of the sensor unit 310 ｃ These are reflected by the target object. And the reflected wave of the power supply radio wave ref_Rw ｐ Regarding this, the power receiver PRx of the multiple power supply units 320 in the other pair of transceivers receives it. Also, the reflected signal of the communication radio wave ref_Rw ｃ This information is received by the data receivers DRx of the multiple sensor units 310 in the other pair of transceivers.

[0269] At this time, the power receivers PRx of the multiple power supply units 320 and the data receivers DRx of the multiple sensor units 310 provide the intensity and quality of the reflected waves they have received to the detection module 516 of the information processing device 500 via wired or wireless communication. The detection module 516 can detect the presence of an object with even higher reliability by comprehensively analyzing the signals of multiple frequency bands obtained from these numerous receiving points. In other words, the system 100 uses radio waves of different frequencies, namely communication radio waves and power supply radio waves, and performs observation from multiple viewpoints using a multi-static configuration, thereby achieving more stable object detection even in disturbed or noisy environments compared to detection using a single frequency or single viewpoint.

[0270] Figure 31 illustrates an application example that uses both communication radio waves (first radio waves) and power supply radio waves (second radio waves) and combines the reception results from multiple transceivers to detect an object. As shown in Figure 31, in this embodiment, the power supply unit 320 includes a power transmitter PTx, a data receiver DRx, and a power receiver PRx. The sensor unit 310 also includes a power receiver PRx, a data transmitter DTx, and a data receiver DRx.

[0271] In this application example, the communication strength and power reception strength transmitted and received between the power transmitter PTx of the power supply unit 320 and the power receiver PRx of the sensor unit 310, or between the data transmitter DTx of the sensor unit 310 and the data receiver DRx of the power supply unit 320, are acquired. Furthermore, another transceiver 300, separate from this pair of transceivers 300, receives the transmitted communication radio waves or power supply radio waves and measures their strength. In the illustrated example, the power receiver PRx of the other power supply unit 320 measures the reflected wave ref_Rw of the power supply radio waves. ｐ Receiving.

[0272] At this time, the detection module 516 analyzes the strength information of the two radio waves obtained between the pair of transceivers 300 and the strength information of the feed radio wave (reflected wave) received by the other transceiver 300. As a result, the presence of the object does not depend on a single path, but is determined by integrating information from multiple reception paths. In other words, the system 100 can detect the presence or absence of the object with higher reliability by comprehensively utilizing the communication strength, the received strength, and the received strength received by the other transceiver. In the illustrated example, the power receiver PRx of the other power supply unit 320 receives the reflected wave ref_Rw of the feed radio wave. ｐ The configuration shown is that it is receiving data, but the data receiver DRx of another sensor unit 310 is reflecting the communication radio waves ref_Rw ｃ The data may be received, and the object may be detected through a similar analysis.

[0273] In other words, the computer in system 100 has a CPU, which performs the following: it acquires the strength of the first and second radio waves transmitted and received by a pair of transceivers, and also acquires the strength of the radio waves received by another receiver, and combines them to detect the presence of an object. As a result, system 100 can avoid single-path dependent false detections through multi-point observation, and stable detection is possible even in disturbed environments.

[0274] (11-4. Fifth Embodiment) Figures 32 to 34 illustrate a fifth embodiment, which describes a method for setting a threshold for determining the presence or absence of an object.

[0275] In system 100, when determining the presence or absence of an object, the detection module 516 of the information processing device 500 performs a determination process by comparing the acquired radio wave strength with a preset threshold. The radio wave strength includes the radio wave strength of the power supply radio wave and the radio wave strength of the communication radio wave. The information processing device 500 may further include a setting module (setting unit) for setting the threshold. The setting module sets the threshold used for the determination based on spatial attributes such as the structure, use, and layout of the target space. As a result, even with the same radio wave strength, an appropriate threshold is given according to differences in spatial attributes, such as small conference rooms and large halls, improving the accuracy of detection.

[0276] Figure 32A shows an example of setting spatial attribute values. In the example shown, a small meeting room usable by a maximum of two people is defined as the target space (zone), and spatial attributes such as zone name, zone ID, purpose (teleconferencing, 1on1 meeting), capacity, dimensions (length, width, height), and layout information are registered. These spatial attribute values ​​are used for the initial setup of the quantity estimation rules and state transition models described later.

[0277] Figure 32B shows an example of a quantity estimation rule that shows the correspondence between radio wave intensity features and the number of people present. The configuration module sets initial values ​​for the quantity estimation rule to estimate quantities such as 0 people present, 1 person present, and 2 people present, based on the attribute values ​​of the target space and features such as radio wave intensity and packet rate. The configuration module also adjusts the correspondence range between radio wave intensity features and quantities based on the spatial attributes of the target space. By combining this quantity estimation rule with a state transition model obtained in advance based on the spatial attributes, the configuration module can set thresholds.

[0278] Figure 32C shows a state transition model that represents the temporal changes in the occupancy state (number of people) of a target space. The state transition model is a function that shows the probability of existence of a state of an object (e.g., people) obtained in advance based on spatial attributes. In this embodiment, the probability of existence of a state of an object is given as the state transition matrix P = [p_ij]. In the illustrated example, states such as absent (0 people), 1 person present, and 2 people present are used as nodes, and the transition probabilities between them are defined. This model allows us to obtain a realistic transition model, for example, that "the probability of a small meeting room that had 0 people just before suddenly having 2 people in the next moment is low."

[0279] The configuration module can set thresholds based on a quantity estimation rule that estimates the number of objects present in a target space based on radio wave intensity, and a state transition model. In this case, the quantity estimation rule estimates quantities such as 0 people, 1 person, and 2 people from the features, and the state transition function applies a realistic transition correction, such as "the probability that a space that was 0 people just before will have 2 people at the next time step is low." As a result, the quantity estimation rule is updated based on a realistic transition model. Alternatively, the probability transition matrix may be updated based on the number of people estimated from the quantity estimation rule.

[0280] Furthermore, the configuration module can also set thresholds based on the correlation between actual values ​​related to fluctuations in radio wave intensity and the presence / absence determination results in the target space. In other words, the configuration module may optimize the thresholds by referring to past usage history and learning data that shows the relationship between actual fluctuations in radio wave intensity and presence / absence determination. This performance-based method makes it possible to set thresholds that are suitable for each space, regardless of environmental noise or variations in installation location.

[0281] Thus, by combining the setting of spatial attribute values ​​shown in Figure 32A, the definition of quantity estimation rules shown in Figure 32B, the construction of a state transition model shown in Figure 32C, and threshold correction based on past performance, the setting module can accurately set thresholds for determining the presence or absence of an object.

[0282] In other words, the computer in system 100 has a CPU, which performs the following: acquires spatial attributes such as the structure, purpose, and layout of the target space, compares the radio wave intensity with a threshold to determine the presence of an object, and sets a threshold based on the spatial attributes. As a result, system 100 is given an optimal reference value for each usage environment, enabling highly accurate determination even under different conditions such as conference rooms and halls.

[0283] Next, we will explain an example of setting actual thresholds. Figure 33A shows the state transition matrix P1 given based on spatial attribute values ​​when a small meeting room is the target space. Matrix P1 has nodes for the states of absent (0 people), present (1 person), and present (2 people), and represents the transition probability between each state. For example, the probability of transitioning from 0 people to 1 person in the next time step, and the probability of transitioning from 1 person to 2 people are quantified. In the example shown, because the area is small and enclosed by walls, the setting is such that the number of people does not change easily once it is determined.

[0284] Figure 33B shows the time-series data of the radio wave intensity feature quantities measured in the small conference room. In this figure, the vertical axis represents the feature quantities (e.g., statistical values ​​of received radio wave intensity), and the horizontal axis represents the time series. The number of people in the room is estimated according to the changes in the feature quantities. At this time, it is assumed that the quantity estimation rule shown in Figure 32B is associated with the feature quantities, such as 0 people, 1 person, 2 people, etc. Note that for simplicity of explanation, statistical values ​​of received radio wave intensity are used as an example, but statistical values ​​of communication radio wave intensity may be used, or statistical values ​​of both may be used.

[0285] In the illustrated example, it is assumed that a quantity estimation rule has already been given based on the attribute values ​​of the small meeting room. In this case, the configuration module performs processing that combines the estimated number of people obtained from the features using the known quantity estimation rule with the known state transition matrix P shown in Figure 33A. Specifically, the configuration module corrects the final threshold based on the transition probabilities shown in the state transition matrix P or past feature fluctuation information, while using the threshold candidate given by the quantity estimation rule as a reference.

[0286] In this way, the configuration module can determine thresholds for the difference between 0 and 1 person, and between 1 and 2 people, based on the measured feature distribution. In other words, this method provides thresholds that take into account the realism of the number of people changing, in line with the attributes of the target space, such as its use. This makes it less susceptible to temporary noise and sudden fluctuations, significantly improving the stability and reliability of presence / absence detection.

[0287] Next, we will explain an example of setting thresholds in a meeting space without walls. Figure 34A shows a state transition matrix P2 given based on spatial attribute values, with a meeting space for six people as the target space. Matrix P2 has seven states as nodes, from absent (0 people) to present (6 people), and quantifies the transition probability between each state. In this example, since the area is not surrounded by walls, a transition probability with relatively high fluctuations in the number of people is set to correspond to the spatial attribute that the number of people can easily come and go and fluctuate greatly. On the other hand, a low probability is given for extreme transitions (e.g., from 0 people to 6 people), modeling a realistic usage situation.

[0288] Figure 34B shows the time-series data of characteristic quantities of radio wave intensity measured in the meeting space. The vertical axis represents characteristic quantities (e.g., indices calculated from received radio wave intensity and packet rate), and the horizontal axis represents the date, recording fluctuations according to usage. Here, it is assumed that the characteristic quantities of this meeting space are associated with the estimated number of people present, ranging from 0 to 6, as the initial values ​​for the quantity estimation rule.

[0289] In this case, the configuration module processes the estimated number of people obtained from the features using the quantity estimation rule, combined with the state transition matrix P shown in Figure 34A. Specifically, the correspondence between the number of people and the features based on the quantity estimation rule is used as the initial value, and the threshold is corrected while eliminating unnatural fluctuations in the number of people due to the probabilistic constraints given by the state transition matrix P. As a result, multiple thresholds such as 0 people and 1 person, 1 person and 2 people, ... 5 people and 6 people are set according to the measured data. The configuration module also sets the threshold by inputting the fluctuation value of the radio wave intensity in the target space, based on the correlation between the actual value of the fluctuation of radio wave intensity and the judgment result indicating whether or not an object exists in the target space.

[0290] Using this method, stable person-to-person estimation can be performed even in meeting spaces without walls and where people can freely enter and exit, without being affected by sudden fluctuations in radio wave strength or temporary noise. Furthermore, by adjusting the state transition matrix according to spatial attributes, it becomes possible to set thresholds that are suitable for different spatial conditions such as conference rooms, large halls, and open spaces, which is expected to significantly improve the reliability of presence / absence detection.

[0291] Furthermore, the computer in system 100 has a CPU, which performs the following: It applies a quantity estimation rule that estimates quantities based on radio wave intensity, analyzes it in combination with a state transition function obtained based on spatial attributes, and sets a threshold in the target space. As a result, system 100 can eliminate unnatural changes in the number of people and set a threshold that reflects realistic changes in the number of people.

[0292] (11-5. Sixth Embodiment) Next, with reference to Figure 35, a method for setting threshold criteria will be described as the sixth embodiment. Here, the threshold criteria are not the threshold value itself, but rather define the judgment policy for whether to allow false detections or avoid overlooking objects when detecting objects using the threshold. System 100 can set judgment criteria using the optimal threshold according to the purpose of object detection.

[0293] Figure 35 illustrates the threshold criteria for determining the presence or absence of an object. The horizontal axis represents signal intensity, and the vertical axis represents probability density. The distribution on the left of the figure shows the probability density function for the case of "no object," and the distribution on the right shows the probability density function for the case of "object present." The characteristics of the detection result change depending on where the threshold is set in the intersection region of the two distributions.

[0294] As shown in Figure 35, setting a low threshold on the left side makes it easier to determine that an object is present, but it also increases the probability of incorrectly determining that an object "is present." This type of setting is called "positive-positive dominance." On the other hand, setting a high threshold makes it easier to determine that an object is not present, but it also increases the probability of missing an object that is actually present. This type of setting is called "positive-negative dominance."

[0295] Furthermore, it is preferable to select whether to adopt a positive-dominant or positive-negative dominant threshold criterion depending on the purpose of object detection. For example, if the priority is to "detect the presence of suspicious persons or intruders," such as for crime prevention purposes, it is necessary to avoid overlooking anything, even if it means tolerating some false alarms, so setting a positive-dominant threshold is appropriate.

[0296] In contrast, for example, in cases where the emphasis is on "accurately detecting the absence of an object," such as in energy-saving control or automated equipment management, setting a threshold that favors positive and negative detections is suitable to suppress unnecessary operations due to false detections. Furthermore, in system 100, the threshold judgment criteria can be flexibly switched according to the purpose of object detection. This makes it possible to achieve optimal presence / absence determination that is suitable for the detection purpose.

[0297] In the system 100 relating to this technology, the detection objective can be set by the user or administrator and can be changed as needed. The setting module sets threshold criteria according to the purpose of detecting objects in the input target space. In this case, a judgment criterion table (judgment criterion information) in which suitable judgment criteria for the input detection objective are pre-set may be referenced. Alternatively, the user or administrator may directly input the threshold criteria (i.e., either positive-positive dominant or positive-negative dominant). Through this process, for example, even if the detection objective switches from a security scenario to an energy-saving scenario, the system 100 can immediately change the threshold criteria in response to the input operation and perform detection operations that are appropriate for the operating environment.

[0298] Other criteria for judgment include negative positive dominance and negative negative dominance. Negative positive dominance means a policy that allows for the incorrect judgment of "present" when the object does not exist. On the other hand, negative negative dominance means a policy that allows for the incorrect judgment of "non-existent" when the object does exist. In this technology, threshold judgment criteria that include negative positive dominance and negative negative dominance, in addition to positive positive dominance and positive negative dominance, may also be set.

[0299] In other words, the computer in system 100 has a CPU, which performs the following: acquires the purpose of detection in the target space, sets threshold criteria according to the purpose, and detects the presence of an object based on those criteria. This allows system 100 to flexibly control the detection accuracy according to applications such as security and energy saving.

[0300] (12. Other) In this system, in addition to a configuration that uses communication radio waves and power supply radio waves in stages for object detection, additional control may be introduced to further improve the accuracy of the number of people estimation. For example, the detection module 516 first estimates the number of people in the space based on the strength of the communication radio waves, and only performs a secondary estimation process based on the strength of the power supply radio waves if the estimated number of people exceeds a predetermined threshold. Specifically, if the presence of three or more people is detected in the first estimation, the number of people can be re-evaluated using power supply radio waves, which have a longer wavelength and better diffraction properties than communication radio waves, thereby ensuring detection accuracy in environments with a large number of people.

[0301] Furthermore, the detection module 516 compares an estimated number of people based on the strength of the communication radio waves (first estimate) with an estimated number of people based on the strength of the power supply radio waves (second estimate), and uses the larger of the two as the final detected value. This utilizes the difference in characteristics between the two: communication radio waves tend to overestimate minute fluctuations in a narrow bandwidth, while power supply radio waves more accurately capture fluctuations over a wide area and for large numbers of people. By detecting the presence of an object using multiple radio wave intensity features with different propagation characteristics in this way, it becomes possible to achieve both detection sensitivity for small numbers of people and detection stability for large numbers of people.

[0302] Furthermore, the threshold for estimating the number of people is not fixed, but is adjusted based on the state transition model and usage history of the target space. In other words, the "probability of a large change in the number of people at once" is learned and set by the state transition matrix, and the threshold condition changes according to that probability distribution. For example, if it is learned that it is rare for many people to enter a space at the same time, the threshold number will be set lower, and the judgment will be made with an emphasis on changes in small numbers. This kind of dynamic threshold setting enables flexible detection according to the environment and usage scenario.

[0303] Furthermore, in this system, by combining the likelihoods calculated at multiple area points, it is possible to estimate behavioral patterns such as movement history within the target space, going beyond simple presence / absence detection. Specifically, the detection module 516 simultaneously analyzes the likelihoods (L1, L2, L3…) of multiple adjacent zones and extracts features from their combination. This enables stable detection while suppressing false positives, even when the target object spans multiple zones or exhibits a specific behavioral pattern.

[0304] Furthermore, this system can dynamically grasp behavioral patterns derived from combinations of likelihoods, depending on the attributes of the target space. For example, in a small meeting room, it estimates that a meeting is taking place when multiple people are present at the same time. On the other hand, in an open space, situations where multiple people are dispersed are more likely to correspond to "desk work" or "movement," so such estimations are prioritized. In this way, by performing estimations based on input values ​​of spatial attributes, it becomes possible to make estimations that are more realistic, even with the same likelihood distribution.

[0305] In estimation based on spatial attributes, past usage data for the target space is used. Specifically, by learning a combination of typical usage patterns in a given space (e.g., multiple people enter and exit a conference room every hour, or people stay in an open space at a dispersed rate during working hours) and attribute information of that space (structure, purpose, layout), the correspondence between features and behavioral patterns is refined. As a result, estimation of complex occupancy situations, which was difficult with simple threshold comparisons, is achieved, further improving the reliability and accuracy of detection.

[0306] Furthermore, this system can suggest a review of the spatial attributes if there is a discrepancy between the input spatial attributes and the estimated use. Specifically, if the input use of the target space is a meeting space, and that space subsequently changes to an office space, the detection module 516 detects that people are constantly present in the meeting space, where there should normally be no people, as shown in Figure 36, and estimates that the usage has changed from a meeting space to an office space. The detection module 516 can then suggest a review of the spatial attributes. Figure 36 is an example of a user terminal screen during the spatial attribute review process by system 100.

[0307] As shown in Figure 36, on this screen, the information processing device 500 of the system 100 functions as a display unit that shows the user terminal that there is a mismatch between the pre-set spatial attributes (room type) and the usage status of the target space estimated by the detection module 516. In addition to the fact of the mismatch, the display unit also displays the pre-set attribute information (conference room in the illustrated example) and the intended use estimated from the actual radio wave intensity characteristics (office space in the illustrated example, in other words, a spatial attribute value that is a candidate for change) to the user terminal. The display unit may also display the reason why the actual use was estimated to be an office space (the presence of a continuous user in the illustrated example).

[0308] In other words, the computer in system 100 has a CPU, which performs the following: acquires artifact information that causes fluctuations in radio wave intensity within the target space, estimates noise factors that affect the detection results, and reports those factors. As a result, system 100 can identify disturbance factors and reduce detection errors, enabling stable object detection.

[0309] In this technology, "based on radio wave intensity" may refer to the radio wave intensity value itself, a feature of the radio wave intensity, or a feature of the true value estimated from the waveform of the radio wave intensity. Furthermore, the feature of the radio wave intensity may refer to the fluctuations obtained by statistical methods for the time-series changes in radio wave intensity, or to features obtained by machine learning.

[0310] Specifically, statistical quantities such as the mean and variance of radio wave intensity can be used as features. The mean serves as a reference value representing the reception state in space, while the variance reflects fluctuations caused by the movement of objects or changes in the number of people. By using these statistical quantities, it becomes possible to determine presence or absence more stably than with simple signal intensity values.

[0311] Furthermore, frequency analysis such as Fourier transform and wavelet transform can be performed on the time-series waveform of radio wave intensity to extract the presence and intensity of specific frequency components as features. This method is expected to quantify the influence of periodic human movements such as walking and talking on the signal, and contribute not only to the presence or absence of occupants but also to the estimation of their behavioral state.

[0312] Furthermore, it is possible to input patterns of change obtained from time-series data of radio wave intensity into a machine learning model and utilize high-dimensional features extracted through supervised or unsupervised learning. This makes it possible to capture nonlinear fluctuations and behavior in complex multi-person environments that are difficult to grasp with statistical methods, thereby achieving more accurate object detection.

[0313] Furthermore, this technology is not limited to the embodiments described above, and includes various modifications. For example, the embodiments described above are detailed explanations provided to make the technology easier to understand, and are not necessarily limited to those having all the configurations described. Also, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0314] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. Alternatively, each of the above configurations and functions may be implemented in software by having the processor interpret and execute programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0315] Furthermore, the control lines and information lines shown are those deemed necessary for explanatory purposes and do not necessarily represent all control lines and information lines in the actual product. In practice, it can be assumed that almost all components are interconnected. The above-described embodiment discloses at least the configuration described in the claims.

[0316] Furthermore, the present invention includes at least the following embodiments (1) to (22). The present invention further includes configurations that combine the following embodiments (1) to (22).

[0317] (1) A detection system for detecting the presence or absence of an object in a space, comprising: a pair of transceivers that transmit and receive a plurality of radio waves with different frequency bands in the space; and a detection unit that detects the presence of the object in the space based on the radio wave intensity of the plurality of radio waves transmitted and received by the pair of transceivers.

[0318] (2) The detection system according to (1), wherein the detection unit detects the presence of the object in the space based on a combination of the radio wave intensities of the plurality of radio waves transmitted and received by the pair of transceivers.

[0319] (3) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit makes a primary determination of whether or not the object exists based on the radio wave intensity of the first radio wave, and makes a secondary determination of whether or not the object exists based on the radio wave intensity of the second radio wave.

[0320] (4) The detection system according to (1) or (2), wherein a plurality of pairs of transceivers are arranged in the space in a plurality of pairs, each associated with an area point assigned to each region of the space, and the detection unit detects the presence of the object within the region for each area point.

[0321] (5) The detection system according to (4), wherein the detection unit calculates the likelihood of the object being present in the region for each area point.

[0322] (6) The detection system according to (5), wherein the detection unit detects the presence of the object within the region based on the characteristic quantity of the combination of likelihoods calculated for each area point.

[0323] (7) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit, when the presence of the object in the space is detected based on the radio wave intensity of the first radio wave transmitted and received by the transceivers, detects the degree of the quantity of the object present in the space based on the radio wave intensity of the second radio wave transmitted and received by the transceivers.

[0324] (8) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit detects the number of objects in the space based on the radio wave intensity of the second radio wave transmitted and received by the transceiver when the number of objects present in the space, detected based on the radio wave intensity of the first radio wave transmitted and received by the transceiver, exceeds a predetermined threshold.

[0325] (9) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, the detection unit detects the number of objects present in the space as a first estimated value based on the radio wave intensity of the first radio wave transmitted and received by the transceivers, the detection unit detects the number of objects present in the space as a second estimated value based on the radio wave intensity of the second radio wave transmitted and received by the transceivers, and the larger of the first estimated value and the second estimated value is used as the detected value of the number of objects present in the space.

[0326] (10) The detection system according to (3) or (7), wherein the pair of transceivers comprises a first transceiver that transmits the first radio wave and receives the second radio wave, and a second transceiver that transmits the second radio wave and receives the first radio wave.

[0327] (11) The detection system according to (10), further comprising an acquisition unit that acquires information relating to the signal strength of the second radio wave received by the first transceiver and information relating to the signal strength of the first radio wave received by the second transceiver, wherein the detection unit detects the presence of the object based on the signal strength of the first radio wave and the signal strength of the second radio wave.

[0328] (12) The detection system according to (11), wherein the second transceiver acquires information relating to the signal strength of the second radio wave from the first transceiver, and the acquisition unit acquires information relating to the signal strength of the first radio wave and information relating to the signal strength of the second radio wave transmitted from the second transceiver.

[0329] (13) The detection system according to (12), wherein the first radio wave is a communication radio wave used for information communication, and the second radio wave is a power supply radio wave used for power supply.

[0330] (14) The detection system according to (1) or (2), wherein the detection unit detects the position of the object in the space using the position information of the transceiver.

[0331] (15) The detection system according to (14), further comprising: a storage unit that stores in advance the location information of one of the pair of transceivers that transmit and receive radio waves from each other; and a calculation unit that calculates the location information of the other transceiver that is paired with the one transceiver, based on the location information of the one transceiver and the radio wave intensity of the radio waves received by the transceiver.

[0332] (16) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication, and the detection unit detects the presence of the object in the space based on the communication quality when the communication quality of the first radio wave falls below a predetermined threshold.

[0333] (17) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and the detection unit detects the presence of the object in the space based on the radio wave intensity of the first radio wave which is transmitted by one of the pair of transceivers in the space and received by the transceiver.

[0334] (18) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and the detection unit detects the presence of the object in the space based on the radio wave intensity of the first radio wave which is transmitted by one of the pair of transceivers in the space and received by one of the other pair of transceivers.

[0335] (19) The detection system according to (1) or (2), wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and the system further comprises another receiver that receives radio waves transmitted by one of the pair of transceivers, and the detection unit detects the presence of the object based on the radio wave intensity of the first radio wave and the second radio wave transmitted and received by the pair of transceivers and the radio wave intensity of the first radio wave or the second radio wave received by the other receiver.

[0336] (20) The detection system according to (1) or (2), wherein the detection unit compares the radio wave intensity of the radio waves with a preset threshold to determine whether or not the object exists in the target space, and further comprises a setting unit that sets the threshold based on spatial attributes including at least one of the structure, use, and layout of equipment in the target space.

[0337] (21) The detection system according to (20), wherein the setting unit sets the threshold based on a quantity estimation rule for estimating the quantity of objects present in the target space based on the radio wave intensity, and a state transition function that shows the transition of the probability of existence of the state of the objects in the target space, which has been obtained in advance based on the spatial attributes.

[0338] (22) The detection system according to (1) or (2), wherein the setting unit sets the threshold by inputting the value of the fluctuation in radio wave intensity in the target space based on the correlation between the actual value of the fluctuation in radio wave intensity and the determination result indicating whether or not the target object exists in the target space.

[0339] (23) The detection system according to (1) or (2), wherein the setting unit sets a threshold determination criterion for determining the presence of an object in the space, based on the purpose of detecting the presence of the object in the space.

[0340] (24) A detection method for detecting the presence or absence of an object in a space, the detection method comprising: a detection system performing a transmission step in which a pair of transceivers transmit and receive a plurality of radio waves with different frequency bands in the space; and a detection step in which the presence of the object in the space is detected based on the radio wave intensity of the plurality of radio waves transmitted and received in the transmission step.

[0341] (25) A program that causes the management server to perform each step of the detection method described in (24).

[0342] (26) An information processing system comprising an acquisition unit that acquires information on the radio wave strength of a plurality of radio waves that are transmitted wirelessly between a pair of transceivers in a space and have different frequency bands, and which detects the presence of an object in the space based on the radio wave strength information acquired by the acquisition unit.

[0343] (27) The information processing system according to (26), wherein a plurality of pairs of transceivers are arranged in the space in a plurality of pairs, each associated with an area point assigned to each region of the space, and based on the information on the radio wave intensity acquired by the acquisition unit, the presence of the object in the region is detected for each area point.

[0344] (28) The information processing system according to (26), wherein the acquisition unit acquires information about artifacts that cause the radio wave intensity to fluctuate in the space, estimates noise factors among the artifacts that affect the detection result of the presence of an object in the space based on the acquired information about the artifacts, and notifies the estimated noise factors.

[0345] 100...Whole building control system, 200...Central control unit, 210...Lighting equipment, 220...Air conditioning equipment, 310...Sensor unit (first transceiver), 320...Power supply unit (second transceiver), 511...Receive control module, 512...Transmit control module, 513...Storage module, 514...Acquisition module, 515...Calculation module, 516...Detection module, 600...Unit information, 700...Sensing information, 800...Communication strength information, 900...Power supply information, 1000...Detection information

Claims

1. A detection system for detecting the presence or absence of an object in a space, comprising: a pair of transceivers that transmit and receive a plurality of radio waves with different frequency bands in the space; and a detection unit that detects the presence of the object in the space based on the radio wave intensity of the plurality of radio waves transmitted and received by the pair of transceivers.

2. The detection system according to claim 1, wherein the detection unit detects the presence of the object in the space based on a combination of the radio wave intensities of the plurality of radio waves transmitted and received by the pair of transceivers.

3. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit makes a primary determination of whether or not the object exists based on the radio wave intensity of the first radio wave, and makes a secondary determination of whether or not the object exists based on the radio wave intensity of the second radio wave.

4. The detection system according to claim 1 or 2, wherein a plurality of pairs of transceivers are arranged in the space in association with area points assigned to each region of the space, and the detection unit detects the presence of the object within the region for each area point.

5. The detection system according to claim 4, wherein the detection unit calculates the likelihood of the object being present within the area for each area point.

6. The detection system according to claim 5, wherein the detection unit detects the presence of the object within the region based on the characteristic quantity of the combination of likelihoods calculated for each area point.

7. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit, when the presence of the object in the space is detected based on the radio wave intensity of the first radio wave transmitted and received by the transceivers, detects the degree of the quantity of the object present in the space based on the radio wave intensity of the second radio wave transmitted and received by the transceivers.

8. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, and the detection unit detects the number of objects in the space based on the radio wave intensity of the second radio wave transmitted and received by the transceiver when the number of objects present in the space, detected based on the radio wave intensity of the first radio wave transmitted and received by the transceiver, exceeds a predetermined threshold.

9. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave and a second radio wave having a lower frequency than the first radio wave, the detection unit detects the number of objects present in the space as a first estimated value based on the radio wave intensity of the first radio wave transmitted and received by the transceivers, the detection unit detects the number of objects present in the space as a second estimated value based on the radio wave intensity of the second radio wave transmitted and received by the transceivers, and the larger of the first estimated value and the second estimated value is used as the detected value of the number of objects present in the space.

10. The detection system according to claim 3, wherein the pair of transceivers comprises a first transceiver that transmits the first radio wave and receives the second radio wave, and a second transceiver that transmits the second radio wave and receives the first radio wave.

11. The detection system according to claim 10, further comprising an acquisition unit that acquires information relating to the signal strength of the second radio wave received by the first transceiver and information relating to the signal strength of the first radio wave received by the second transceiver, wherein the detection unit detects the presence of the object based on the signal strength of the first radio wave and the signal strength of the second radio wave.

12. The detection system according to claim 11, wherein the second transceiver acquires information relating to the signal strength of the second radio wave from the first transceiver, and the acquisition unit acquires information relating to the signal strength of the first radio wave and information relating to the signal strength of the second radio wave transmitted from the second transceiver.

13. The detection system according to claim 12, wherein the first radio wave is a communication radio wave used for information communication, and the second radio wave is a power supply radio wave used for power supply.

14. The detection system according to claim 1 or 2, wherein the detection unit detects the position of the object in the space using the position information of the transceiver.

15. The detection system according to claim 14, further comprising: a storage unit that stores in advance the location information of one of the pair of transceivers that transmit and receive radio waves from each other; and a calculation unit that calculates the location information of the other transceiver that is paired with the one transceiver, based on the location information of the one transceiver and the radio wave intensity of the radio waves received by the transceiver.

16. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication, and the detection unit detects the presence of the object in the space based on the communication quality when the communication quality of the first radio wave falls below a predetermined threshold.

17. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and the detection unit detects the presence of the object in the space based on the radio wave intensity of the first radio wave transmitted by one of the pair of transceivers in the space and received by the transceiver.

18. The detection system according to claim 1 or 2, wherein the pair of transceivers transmit and receive a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and the detection unit detects the presence of the object in the space based on the radio wave intensity of the first radio wave which is transmitted by one of the pair of transceivers in the space and received by one of the other pair of transceivers.

19. The detection system according to claim 1 or 2, wherein the pair of transceivers transmits and receives a first radio wave which is a communication radio wave used for information communication and a second radio wave which is a power supply radio wave used for power supply, and further comprises another receiver that receives radio waves transmitted by one of the pair of transceivers, and the detection unit detects the presence of the object based on the radio wave intensity of the first radio wave and the second radio wave transmitted and received by the pair of transceivers and the radio wave intensity of the first radio wave or the second radio wave received by the other receiver.

20. The detection system according to claim 1 or 2, wherein the detection unit compares the radio wave intensity with a preset threshold to determine whether or not the object exists in the target space, and further comprises a setting unit that sets the threshold based on spatial attributes including at least one of the structure, use, and layout of equipment in the target space.

21. The detection system according to claim 20, wherein the setting unit sets the threshold based on a quantity estimation rule for estimating the quantity of objects present in the target space based on the radio wave intensity, and a state transition function that shows the transition of the probability of existence of the state of the objects in the target space, which has been obtained in advance based on the spatial attributes.

22. The detection system according to claim 20, wherein the setting unit sets the threshold by inputting the value of the fluctuation of the radio wave intensity in the target space based on the correlation between the actual value of the fluctuation of the radio wave intensity and the determination result indicating whether or not the target object exists in the target space.

23. The detection system according to claim 20, wherein the setting unit sets a threshold determination criterion for determining the presence of an object in the target space, based on the purpose of detecting the presence of the object in the target space.

24. A detection method for detecting the presence or absence of an object in a space, wherein the detection method comprises: a transmission step in which a pair of transceivers transmit and receive a plurality of radio waves with different frequency bands in the space; and a detection step in which the presence of the object in the space is detected based on the radio wave intensity of the plurality of radio waves transmitted and received in the transmission step.

25. A program that causes a management server to perform each step of the detection method described in claim 24.

26. An information processing system comprising an acquisition unit that acquires information on the radio wave intensity of multiple radio waves with different frequency bands that are transmitted wirelessly between a pair of transceivers in a space, and which detects the presence of an object in the space based on the radio wave intensity information acquired by the acquisition unit.

27. The information processing system according to claim 26, wherein a plurality of pairs of transceivers are arranged in the space in a plurality of pairs, each associated with an area point assigned to each region of the space, and based on the information regarding the radio wave intensity acquired by the acquisition unit, the presence of the object in the region is detected for each area point.

28. The information processing system according to claim 26, wherein the acquisition unit acquires information about artifacts that cause the radio wave intensity to fluctuate in the space, estimates noise factors among the artifacts that affect the detection result of the presence of an object in the space based on the acquired information about the artifacts, and notifies the estimated noise factors.

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