Indicating the possibility of detection through multiple indicators

Abstract

One method includes determining (101) a sensing input and, based on the sensing input, determining (103) the probability of the presence of a person or animal. The sensing input reflects changes in radio frequency signals received by one or more devices. The method also includes controlling (105) a lighting device to produce a light effect when the probability is determined to exceed a presence detection threshold, and to continue producing the light effect for a subsequent predetermined period of time, even if the probability changes beyond a predetermined value within a predetermined period of time. The method also includes instructing (107) the probability to a user via an indication selected from a plurality of indications, for example, by presenting the indication on the lighting device. When it is determined that the probability has changed beyond a predetermined value, a different indication from the plurality of indications is selected.

Description

Technical Field

[0001] The present invention relates to a system for determining the likelihood of the presence of a person or animal based on sensing inputs that reflect changes in radio frequency signals received by one or more devices.

[0002] The present invention further relates to a method for determining the likelihood of the presence of a person or animal based on sensing input, said sensing input reflecting changes in radio frequency signals received by one or more devices.

[0003] The present invention also relates to a computer program product that enables a computer system to execute this method. Background Technology

[0004] Presence detection is becoming increasingly important in smart homes and smart offices, for example, for automatically turning lights on and off and automatically controlling heating / air conditioning. Typically, PIR sensors or cameras are used to implement presence detection. These are relatively easy to install and network initialize. For example, US 2010 / 00185969 A1 discloses a light control system with a user interface for interactively changing settings in a lighting system, particularly enabling easy and comfortable interactive changes to the light scene created by the lighting system. In an embodiment, the scene to be illuminated is graphically represented, and some locations are recolored based on motion sensor information.

[0005] Over the past few years, network-based presence sensing technology has matured and entered the market. A prominent example is Ivani's "network presence sensing" technology. This technology has applications ranging from motion detection based on environmental changes to people counting and location. The main idea behind this technology is to measure the behavior of wireless communication (e.g., between IoT devices). A person's location and number, weight, direction of movement, and other parameters will influence this behavior, allowing the detection of a person or group of people based on detected changes (e.g., changes in signal strength or channel state information (CSI)). The system's accuracy and versatility depend on the number of communicating devices and generally perform better with more devices present (the minimum number of devices is two, allowing signals to be generated and received to assess their behavior).

[0006] To set up and initialize network presence sensing, users (with system support) will typically need to define detection areas, assign light and lighting scenes, and find optimal sensitivity settings for each area, among others. Setting sensitivity or understanding why the system operates in a certain way can be challenging for users because, unlike traditional presence sensing devices (e.g., PIR, cameras), this system does not have a well-defined field of view for detection and can be triggered by objects such as walls or doors. This can lead to confusion and affect user acceptance of the system. Additionally, the detection performance of RF sensing may change over time, for example, due to furniture being moved or doors being closed / opened.

[0007] US 2017 / 150578 discloses a method for lighting control using active wireless feedback monitoring of the behavior of moving objects. Moving objects (such as people, pets / animals, vehicles, etc.) within the range of an established wireless network tend to modulate the wireless signal strength between wireless nodes. By monitoring changes in the standard deviation of the wireless signal strength between network nodes, the behavior of moving objects can be used to directly control ambient lighting conditions within the area of ​​interest. Summary of the Invention

[0008] The first objective of this invention is to provide a system that helps users set up a network presence sensing system and perform network access initialization for the network presence sensing system.

[0009] A second objective of this invention is to provide a method that helps users set up a network presence sensing system and perform network access initialization for the network presence sensing system.

[0010] In a first aspect of the invention, a system for determining the likelihood of the presence of a person or animal based on a sensing input reflecting a change in a radio frequency signal received by one or more devices is provided. The system includes at least one input interface, at least one output interface, and at least one processor configured to: determine the sensing input using the at least one input interface; determine the likelihood of the presence of the person or animal based on the sensing input; control a lighting device using the at least one output interface to produce a light effect when the likelihood is determined to exceed a presence detection threshold, and to continue producing the light effect for a subsequent predetermined time period even if the likelihood changes beyond a predetermined value within a predetermined time period; and indicate the likelihood to a user via an indication selected from a plurality of indications using the at least one output interface, selecting a different indication from the plurality of indications when it is determined that the likelihood has changed beyond the predetermined value.

[0011] By allowing a user to move around a room or building and see the extent to which presence sensing covers their current location (including whether it is covered at all), they can easily determine whether the network presence sensing has been adequately set up and initialized. Light sources from lighting devices that are turned on when presence is detected (i.e., the probability begins to exceed the presence detection threshold) will not immediately turn off when the probability drops below the presence detection threshold to avoid flickering lights, etc., and therefore will not turn off even if the probability change exceeds a predetermined value. This is not suitable for checking presence sensing coverage. To check presence sensing coverage, different indications are provided once the probability change has exceeded a predetermined value, for example, once a probability / confidence level corresponding to different indications is determined. The lighting device can be one of the one or more devices mentioned above.

[0012] The at least one processor can be configured to indicate the possibility to the user by displaying the indication on a display, such as that of a mobile device, TV, or projector, using the at least one output interface. This allows more information to be provided compared to using only the lighting equipment itself to provide the indication.

[0013] The at least one processor can be configured to use the at least one output interface in the normal operating mode of the lighting device to control the lighting device to present the light effect when the probability is determined to exceed the presence detection threshold, and to use the at least one output interface in the configuration mode of the lighting device to provide the indication on the lighting device by presenting another light effect among a plurality of light effects, and to select a different light effect among the plurality of light effects when it is determined that the probability has changed beyond the predetermined value.

[0014] While not as informative as displaying possibilities on a monitor, using lighting devices to indicate possibilities is likely the easiest to use and implement because it requires no additional equipment (e.g., mobile devices) and provides feedback directly to the environment. Configuration modes can be activated for all lighting devices in a home or office, or only for a subset of these devices. In the former case, the system itself can switch between a normal operating mode and a configuration mode, thereby switching all associated lighting devices to the same mode. The at least one processor can be configured to receive user input using the at least one input interface and switch between the normal operating mode and the configuration mode based on the user input.

[0015] The at least one processor may be configured to determine the chromaticity of the additional lighting effect based on the probability, such that the chromaticity indicates the probability; determine the luminance and / or light output level of the additional lighting effect based on the probability, such that the luminance and / or light output level indicates the probability; and / or determine the dynamic level of the additional lighting effect based on the probability, such that the dynamic level indicates the probability. For example, the dynamic level may be the flash speed.

[0016] The at least one processor can be configured to determine the additional lighting effect based on the probability and the capabilities of the lighting device. For example, if the lighting device has color capabilities, the chromaticity can be determined for the additional lighting effect based on the probability, and if the lighting device does not have color capabilities, the light output level can be determined for the additional lighting effect based on the probability.

[0017] The at least one processor can be configured to select a first lighting effect from the plurality of lighting effects when the probability is determined to exceed the presence detection threshold, and to select a second lighting effect from the plurality of lighting effects when the probability is determined to be below the presence detection threshold. This makes it easier for the user to see whether he / she is being adequately detected at his / her current location. By presenting a lighting effect even when no user is detected, better feedback is given to the user. If no lighting effect is presented when no user is detected, the user may not be able to determine other reasons why the lighting device is not presenting any lighting effect, such as the power switch being off.

[0018] The at least one processor can be configured to determine the color of the additional light effect in a first color spectrum when the probability exceeds the presence detection threshold, and to determine the color of the additional light effect in a second color spectrum when the probability is determined to be below the presence detection threshold. The at least one processor can be configured to determine the color in the first or second color spectrum based on the first probability, such that the color further indicates the probability. For example, if the probability exceeds the presence detection threshold, a light effect with colors in the green spectrum can be presented, and if the probability remains below the presence detection threshold, a light effect with colors in the red or orange-red spectrum can be presented.

[0019] The at least one processor is configured to determine multiple possibilities of the presence of a person or animal based on multiple sensing inputs, each of which corresponds to a specific spatial location of the person or animal; and to associate each of the multiple possibilities with the corresponding spatial location in memory. This makes it possible to identify and indicate areas where the presence of a person or animal cannot be detected well. For example, the at least one processor can be configured to use the at least one output interface to display a spatial mapping indicating the multiple possibilities at the corresponding spatial location. Not every sensing input needs to be based on information generated by all sensing nodes, and different sensing inputs can be based on information generated by different sets of sensing nodes.

[0020] In a second aspect of the invention, a method for determining the likelihood of the presence of a person or animal based on a sensing input, the sensing input reflecting a change in a radio frequency signal received by one or more devices, the method comprising: determining the sensing input; determining the likelihood of the presence of the person or animal based on the sensing input; controlling a lighting device to produce a light effect when the likelihood is determined to exceed a presence detection threshold, and continuing to produce the light effect for a subsequent predetermined time period even when the likelihood changes by more than a predetermined value within a predetermined time period; and instructing a user of the likelihood via an indication selected from a plurality of indications, selecting a different indication from the plurality of indications when the likelihood is determined to change by more than the predetermined value. The method can be executed by software running on a programmable device. The software can be provided as a computer program product.

[0021] In addition, a computer program for implementing the methods described herein is provided, as well as a non-transitory computer-readable storage medium for storing the computer program. The computer program may be downloaded or uploaded to an existing device, for example, or stored during the manufacture of these systems.

[0022] A non-transitory computer-readable storage medium stores at least one portion of software code that, when executed or processed by a computer, is configured to perform executable operations for determining the likelihood of the presence of a person or animal based on sensed inputs that reflect changes in radio frequency signals received by one or more devices.

[0023] The operable operations include: determining the sensing input; determining the probability of the presence of the person or animal based on the sensing input; controlling the lighting device to present a light effect when the probability is determined to exceed a presence detection threshold, and continuing to present the light effect for a subsequent predetermined time period even when the probability changes beyond a predetermined value within the predetermined time period; and indicating the probability to the user via an indication selected from a plurality of indications, selecting a different indication from the plurality of indications when it is determined that the probability has changed beyond the predetermined value.

[0024] As those skilled in the art will appreciate, aspects of the present invention can be embodied as devices, methods, or computer program products. Therefore, aspects of the present invention can take the form of entirely hardware embodiments, entirely software embodiments (including firmware, resident software, microcode, etc.), or embodiments combining software and hardware aspects, which are generally referred to herein as “circuit,” “module,” or “system.” The functionality described in this disclosure can be implemented as algorithms executed by a computer’s processor / microprocessor. Furthermore, aspects of the present invention can take the form of computer program products embodied in one or more computer-readable media having computer-readable program code embodied thereon (e.g., stored thereon).

[0025] Any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the context of this invention, a computer-readable storage medium can be any tangible medium that can contain or store a program used by or in conjunction with an instruction execution system, apparatus, or device.

[0026] Computer-readable signal media may include propagated data signals having computer-readable program code embodied therein (e.g., in baseband or as part of a carrier wave). Such propagated signals may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and may communicate, propagate, or transmit a program used by or in conjunction with an instruction execution system, apparatus, or device.

[0027] The program code embodied on a computer-readable medium can be transmitted using any suitable medium—including, but not limited to, wireless, wired, fiber optic, cable, RF, or any suitable combination thereof. The computer program code for carrying out the operations of various aspects of the invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​(such as Java™, Smalltalk, or C++) and conventional procedural programming languages ​​(such as the "C" programming language or similar programming languages). The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)) or can be connected to an external computer (e.g., via the Internet provided by an Internet service provider).

[0028] Various aspects of the invention are described below with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, particularly a microprocessor or central processing unit (CPU), to produce a machine such that the instructions, executable via the processor of the computer, other programmable data processing apparatus, or other device, create means for implementing the functions / actions specified in the flowchart illustrations and / or one or more block diagram blocks.

[0029] These computer program instructions may also be stored in a computer-readable medium that can instruct a computer, other programmable data processing apparatus, or other device to operate in a particular manner, such that the instructions stored in the computer-readable medium produce an article of writing, which includes instructions that implement functions / actions specified in flowcharts and / or one or more block diagrams.

[0030] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide for implementing the functions / actions specified in the flowchart and / or one or more block diagram boxes.

[0031] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, comprising one or more executable instructions for implementing a specified logical function(s). It should also be noted that in some alternative implementations, the functions described in the blocks may not appear in the order shown in the figures. For example, two blocks shown consecutively may actually be executed substantially simultaneously, or sometimes the blocks may be executed in reverse order depending on the functions involved. It will also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a system based on dedicated hardware, or a combination of dedicated hardware and computer instructions, that performs the specified function or action. Attached Figure Description

[0032] Referring to the accompanying drawings, these and other aspects of the invention will be clear and further illustrated by way of example, in which:

[0033] Figure 1 This is a block diagram of the first embodiment of the system;

[0034] Figure 2 This is a block diagram of the second embodiment of the system;

[0035] Figure 3 This is a flowchart of the first embodiment of the method;

[0036] Figure 4 This illustrates the possibility of presence indicated by lighting fixtures in a room;

[0037] Figure 5 The presence of indications in the lighting fixtures of both rooms is shown;

[0038] Figure 6 This is a flowchart of the second embodiment of the method;

[0039] Figure 7 A first example of a diagnostic user interface displayed in the first user's position is shown;

[0040] Figure 8 Shown in the second user location Figure 7User interface;

[0041] Figure 9 The image shown is displayed in the third user's location. Figure 7 User interface;

[0042] Figure 10 A second example of a diagnostic user interface displayed in a third user location is shown;

[0043] Figure 11 This is a flowchart of the third embodiment of the method;

[0044] Figure 12 A first example of a displayed spatial map representing the detection coverage is shown;

[0045] Figure 13 A second example of a displayed spatial map representing the detection coverage is shown; and

[0046] Figure 14 This is a block diagram of an exemplary data processing system for performing the methods of the present invention.

[0047] Corresponding elements in the accompanying drawings are represented by the same reference numerals. Detailed Implementation

[0048] Figure 1 A first embodiment of a system for determining the likelihood of the presence of a person or animal based on sensing input is shown. The sensing input reflects changes in radio frequency (RF) signals received by one or more devices. For example, the sensing input may reflect changes in the signal strength and / or channel state information (CSI) of the received RF signals. Alternatively or additionally, for example, when multiple transmit or receive antennas are present, the sensing input may reflect changes in time of arrival and / or phase shift and / or reception differences.

[0049] exist Figure 1 In one example, the presence sensing system includes lighting devices 31-36 and bridge 16. At least one of these devices transmits an RF signal, and the other devices receive the RF signal. For example, lighting devices 31-36 may be Hue lamps, and bridge 16 may be a Hue bridge. In an alternative example, bridge 16 is not part of the presence sensing system.

[0050] In this first embodiment, the system is a mobile device 1. For example, mobile device 1 may run an app that allows users to control lighting devices 31-36. Lighting devices 31-36 communicate with bridge 16, for example, using Zigbee technology. Mobile device 1 is able to control lighting devices 31-36 via wireless LAN access point 17 and bridge 16. Wireless LAN access point 17 is connected to the Internet 11. Internet server 13 is also connected to the Internet 11. Internet server 13 is also able to control lighting devices 31-36, for example, based on input from a voice assistant like Amazon's Alexa.

[0051] The mobile device 1 includes a receiver 3, a transmitter 4, a processor 5, a memory 7, a camera 8, and a display 9. The processor 5 is configured to: use the receiver 3 to determine a sensing input by combining data received from a device receiving RF signals; determine the probability of the presence of a person or animal based on the sensing input; and use the transmitter 4 to control one or more lighting devices 31-36 to produce a light effect when the probability is determined to exceed a presence detection threshold, and continue to produce the light effect for a subsequent predetermined period of time even when the probability changes beyond a predetermined value within a predetermined period of time.

[0052] Processor 5 is also configured to indicate a possibility to the user via an indication selected from multiple indications. When it is determined that the possibility has changed beyond a predetermined value, a different indication is selected from the multiple indications. Figure 1 In one embodiment, the processor 5 is configured to indicate a possibility to the user by displaying an indication on the display 9.

[0053] Therefore, the state of a presence detection system is visualized to the user by indicating the probability of being detected in a specific area. For example, visualization can be achieved via one or more lighting devices or via a floorplan view. The level of detail provided typically depends on the specific visualization method used. Figure 1 In this embodiment, the display 9 of the mobile device 1 is used to provide visualization. As the user moves around, the probability / confidence level of his or her being detected is displayed. Additionally, the identifier or name of the detection area may be shown. In cases where there is a chance that the user will be detected at his or her current location in multiple detection areas, both the confidence level and the name of the detection area may be displayed.

[0054] exist Figure 1In the embodiment of the mobile device 1 shown, the mobile device 1 includes a processor 5. In alternative embodiments, the mobile device 1 includes multiple processors. The processor 5 of the mobile device 1 may be a general-purpose processor (e.g., from ARM or Qualcomm) or a dedicated processor. The processor 5 of the mobile device 1 may run an operating system such as Android or iOS. The display 9 may include, for example, an LCD or OLED display panel. For example, the display 9 may be a touchscreen. For example, the processor 5 may use the touchscreen to provide a user interface. The memory 7 may include one or more memory cells. For example, the memory 7 may include solid-state memory. For example, the camera 8 may include a CMOS or CCD sensor. For example, the camera 8 may be used to provide augmented reality views.

[0055] Receiver 3 and transmitter 4 can communicate with wireless LAN access point 17 using one or more wireless communication technologies—such as Wi-Fi (IEEE 802.11). In alternative embodiments, multiple receivers and / or multiple transmitters are used instead of a single receiver and a single transmitter. Figure 1 In the illustrated embodiment, a separate receiver and a separate transmitter are used. In an alternative embodiment, receiver 3 and transmitter 4 are combined into a transceiver. The mobile device 1 may include other components typically used in mobile devices, such as a battery and power connector. The invention can be implemented using a computer program running on one or more processors.

[0056] exist Figure 1 In one embodiment, lighting devices 31-36 are controlled by mobile device 1 via bridge 16. In an alternative embodiment, one or more of lighting devices 31-36 are controlled by mobile device 1 without a bridge, for example, directly via Bluetooth or WiFi.

[0057] Figure 2 A second embodiment of a system for determining the likelihood of the presence of a person or animal based on sensor input is shown. In this second embodiment, the system is a bridge 41. A mobile device 35 is able to control lighting devices 31-36 via a wireless LAN access point 17 and a bridge 16.

[0058] The bridge 41 includes a receiver 43, a transmitter 44, a processor 45, and a memory 47. The processor 45 is configured to use the receiver 43 to determine a sensing input and, based on the sensing input, to determine the probability of the presence of a person or animal. The processor 45 is also configured, in the normal operating mode of the lighting devices 31-36, to use the transmitter 44 to control one or more of the lighting devices 31-36 to display a light effect when the probability exceeds a presence detection threshold, and to continue displaying the light effect for a subsequent predetermined period of time, even if the probability changes beyond a predetermined value within a predetermined period of time.

[0059] The processor 45 is also configured to use the transmitter 44 to control one or more of the lighting devices 31-36 in the configuration mode of the lighting devices 31-36 to present an additional lighting effect among a variety of lighting effects, in order to provide an indication of possibilities. When it is determined that the possibility has changed beyond a predetermined value, a different lighting effect among the multiple lighting effects is selected.

[0060] As mentioned earlier, the level of detail provided typically depends on the specific visualization method used. Figure 2 In this embodiment, one or more of the lighting devices 31-36 are used to provide visualization. Depending on user preferences and the capabilities of the lighting devices, different mappings from system state to lighting devices may be employed.

[0061] One or more of the following light settings can be used to indicate possibilities:

[0062] Color chroma;

[0063] Color brightness / lightness;

[0064] Light output level / dimming level;

[0065] Dynamic level (e.g., frequency, pattern).

[0066] For example, if the user only has white light bulbs, a full-brightness light can indicate a high confidence level (e.g., >90%) for the person being tested, while a off light can indicate a low confidence level (e.g., <30%), and everything in between can be indicated by a half-brightness light.

[0067] If the user has a colored light bulb, the color can be used to display the confidence level (e.g., as a gradient between green indicating near 100% and red indicating near 0%). Different color spectra can be used for probabilities below and above the presence detection threshold. Therefore, when the probability is determined to be above the presence detection threshold, the color of an additional light effect is determined in the first color spectrum, and when the probability is determined to be below the presence detection threshold, the color of an additional light effect is determined in the second color spectrum. Determining a color based on the first probability within the first or second color spectrum further indicates the probability.

[0068] For example, if a person or animal is detected, a color in the green spectrum is determined; if no person or animal is detected, a color in the orange-red spectrum is determined. If the probability is below the presence detection threshold but relatively close to it, the orange spectrum can be used. If the probability is below the presence detection threshold but relatively far from it, the red spectrum can be used.

[0069] exist Figure 2In the embodiment of bridge 41 shown, bridge 41 includes a processor 45. In alternative embodiments, bridge 41 includes multiple processors. The processor 45 of bridge 41 may be a general-purpose processor (e.g., ARM-based) or a dedicated processor. The processor 45 of bridge 41 may run an operating system such as Unix. Memory 47 may include one or more memory cells. For example, memory 47 may include solid-state memory. For example, memory 47 may be used to store a meter of connected lights.

[0070] For example, receiver 43 and transmitter 44 can use one or more wired or wireless communication technologies, such as Ethernet for communicating with wireless LAN access point 17 and Zigbee for communicating with lighting devices 31-36. In alternative embodiments, multiple receivers and / or multiple transmitters are used instead of a single receiver and a single transmitter. Figure 2 In the illustrated embodiment, a separate receiver and a separate transmitter are used. In an alternative embodiment, receiver 43 and transmitter 44 are combined into a transceiver. Bridge 41 may include other components typically used in network devices, such as power connectors. The invention can be implemented using a computer program running on one or more processors.

[0071] exist Figure 1 and Figure 2 In one embodiment, the system of the present invention includes a mobile device or a bridge. In an alternative embodiment, the system of the present invention is a different device, such as a personal or server computer or a lighting device. Figure 1 and Figure 2 In one embodiment, the system of the present invention includes a single device. In an alternative embodiment, the system of the present invention includes multiple devices.

[0072] Figure 3 The diagram illustrates a first embodiment of determining the probability of the presence of a person or animal based on sensing input. The sensing input reflects changes in radio frequency signals received by one or more devices, such as signal strength or channel state information (CSI). Step 101 includes determining the sensing input. Step 103 includes determining the probability of the presence of a person or animal based on the sensing input. Step 105 includes controlling a lighting device to emit a light effect when the probability exceeds a presence detection threshold, and continuing to emit the light effect for a subsequent predetermined time period even if the probability changes beyond a predetermined value within a predetermined time period.

[0073] Step 107 includes indicating a probability to the user via an indication selected from a plurality of indications. When it is determined that the probability has changed beyond a predetermined value, a different indication from the plurality of indications is selected. This probability can be indicated on a lighting device, such as in a configuration mode of a presence detection system, or on a different device (e.g., a mobile device). The probability can be indicated on multiple lighting devices, such as... Figure 4 Multiple lighting fixtures in a room, as shown, or as Figure 5 Multiple lighting fixtures in multiple rooms shown.

[0074] Figure 6 The diagram illustrates a second embodiment for determining the probability of the presence of a person or animal based on sensor input. Figure 6 In the embodiments, Figure 3 Step 101 is preceded by step 121, and steps 123 and 125 are... Figure 3 After step 103 and Figure 3 Steps 105 and 107 are executed before this. Furthermore, Figure 3 Step 105 includes sub-steps 131-137, and Figure 3 Step 107 includes sub-steps 141-145.

[0075] Step 121 includes receiving user input and switching between a normal operating mode and a configuration mode based on the user input. Step 101 includes determining the sensing input (e.g., based on data received from one or more sensing devices and / or by determining changes in signal strength or CSI in the received RF sensing signal). Step 103 includes determining the probability Lh of the presence of a person or animal based on the sensing input. Step 123 includes determining whether the probability Lh exceeds the presence detection threshold Pt. If so, a value of 1 is assigned to the presence indicator P. k (k represents the current iteration / time). If not, the value 0 is assigned to the existence indicator P. k .

[0076] Step 125 includes determining whether the normal operation mode or the configuration mode is active. If the normal operation mode is active, then proceed to step 131. Step 131 includes determining the P determined in step 123. k Is the value of P 0 or 1? k If the value is 1, meaning the probability Lh exceeds the presence detection threshold Pt, then step 135 is executed next. Step 135 includes ensuring that one or more lighting devices produce a light effect, for example by sending a control command to a lighting device whose light source is turned off.

[0077] If P k If the value is 0, meaning the probability Lh has not exceeded the presence detection threshold Pt, then proceed to step 133. In step 133, determine P...k The previous existence indicates the last x values ​​of P, i.e., P k-x To P k-1 Does it also have a value of 0? If yes, proceed to step 137. If not, repeat step 101. Step 137 involves ensuring that one or more lighting devices do not produce light effects, for example, by sending a control command to a lighting device whose light source is turned on. Repeat step 101 after step 137.

[0078] If the configuration mode is active, then step 141 is performed. Step 141 includes selecting an indicator x corresponding to the probability Lh determined in step 103, for example, by using a function called IND. For example, a probability range of 0%-30% can be associated with value 1, a probability range of 31%-75% can be associated with value 2, and a probability range of 76%-100% can be associated with value 3.

[0079] Step 143 includes determining whether the value determined in step 141 is different from the value determined in a previous iteration of step 141. If these values ​​are not different, no different lighting effect is required, and step 101 is repeated. If the values ​​are different, step 145 is performed. Step 145 includes controlling one or more lighting devices to present a lighting effect corresponding to the value determined in step 141. Light setting LS1 may be associated with a red light effect, light setting LS2 may be associated with a yellow light effect, and light setting LS3 may be associated with a green light effect. Step 101 is repeated after step 145.

[0080] Despite Figure 6 In this example, only step 101 is shown as being repeated after steps 133, 137, 143, or 145 have been executed, but step 121 may also be repeated to allow the user to switch modes. Figure 6 In one embodiment, step 121 is performed before step 101. In an alternative embodiment, step 121 is performed after step 101 or simultaneously with step 101.

[0081] exist Figure 6 In one embodiment, one or more lighting devices are associated with the room, and when their presence is detected, one or more lighting devices turn on (in normal operating mode), and it is indicated that lighting will be provided only through these one or more lighting devices (in configuration mode). An example of this is in... Figure 4 As shown in the image, User 19 is standing in living room 51, where lighting fixtures 31-34 have already been installed. Figure 4 In the example, the presence of user 19 has been detected with the help of the sensors in lighting devices 31-34, and lighting devices 31-34 emit a green light effect to indicate that his presence has been detected.

[0082] exist Figure 4 In the example, lighting fixtures 35-36 in kitchen 52 do not produce any lighting effect. Figure 5 In the example, lighting fixtures 35-36 also produce a light effect that user 19 can see through an open door. Lighting fixtures 35-36 indicate whether their presence has been detected with the help of their sensors. Since this is not the case, lighting fixtures 35-36 emit a red light effect.

[0083] exist Figure 6 In one embodiment, the probability indication is provided via one or more lighting devices. In an alternative embodiment, the probability indication is provided via another device (e.g., a mobile device). Figures 7 to 10 An example of a diagnostic user interface is shown for providing instructions via the display of a mobile device. Figure 7 A first example of a diagnostic user interface is shown. When the user is standing in the first user position, the probability of determining the presence of a person or animal is 95%. This probability is indicated by label 65 on the display 9 of the mobile device 1.

[0084] exist Figures 7-10 In the example, a 0%-30% probability range is associated with value 1, a 31%-75% probability range is associated with value 2, and a 76%-100% probability range is associated with value 3. These ranges can be user-configurable. A happy smiley face 61 is associated with value 3 and is therefore displayed on monitor 9. This user interface allows the user to move around the room / building to see if their presence is detected in all (relevant) user locations and diagnose problems in the current presence settings configuration.

[0085] exist Figure 8 In the example, when the user is standing in the second user position, the probability of the presence of a person or animal is determined to be 20%. This probability is again displayed on display 9 with label 65. A sad smiley face 62 has been associated with the value 1 and is therefore displayed on display 9. Figure 9 In the example, when the user is standing in the third user's position, the probability of the presence of a person or animal is determined to be 58%. This probability is again displayed on display 9 with label 65. The neutral smiley face 63 has been associated with value 2 and is therefore displayed on display 9.

[0086] exist Figures 5 to 8In the above description, a person is described as moving around in order to configure presence sensing. However, the person configuring presence sensing is not necessarily the object to be detected. It could be another person or animal whose presence is being detected. For example, a farmer could configure presence sensing in a barn to detect the presence of his chickens, or a pet owner could configure presence sensing in his home to detect the presence of his (or multiple) pets.

[0087] Figure 10 A second example of a diagnostic user interface is shown when the user is standing in the third user position. When the user is in the third position, the same sad smiley face 63 as in the first user interface is displayed in this second user interface. However, in this second user interface, rooms 71 and 72 are graphically represented on display 9, and the probability of the user being in room 71 and 72 is indicated by labels 66 and 67, respectively.

[0088] The probability of a person or animal being present in living room 71 has been determined to be 58%, and the probability of a person or animal being present in kitchen 72 has been determined to be 30%. Figure 10 In the example, the one with the highest probability of the two is used to determine which indication to provide (in this case, the neutral smiley face 63). In an alternative embodiment, the neutral smiley face 63 is shown in the representation of room 71, and the sad smiley face is shown in the representation of room 72.

[0089] Figure 11 A third embodiment is shown, which determines the probability of the presence of a person or animal based on sensor input. Figure 11 In the embodiments, Figure 6 Steps 1, 2, and 3 have already been included Figure 3 In the embodiment, steps 161-167 are performed after steps 105 and 107. Steps 105 and 107 can be... Figure 6 The method shown can be implemented, or it can be implemented in a different way, such as providing instructions on the display of a mobile device.

[0090] Step 161 includes determining the user's spatial location (SP) at their current location. k For example, using an RF beacon. Step 163 includes storing the probability P determined in step 123 in memory. k With this spatial location (SP) k This is related to the possibility P. k It is determined based on the RF signals transmitted and received when the user is at a defined location. This is done by comparing the signal strength, or CSI, of these RF signals with the signal strength, or CSI, of previously received RF signals.

[0091] In step 165, it is determined whether step 101 should be repeated or whether step 167 should be executed next. For example, the method may begin when the user activates configuration or diagnostic mode, launches an app, or presses the start button in the app, and step 167 may be executed when the user deactivates configuration or diagnostic mode or presses the stop button in the app. Step 167 is typically executed after multiple possibilities of the presence of a person or animal have been determined (based on multiple sensor inputs). Therefore, multiple possibilities have already been associated with corresponding spatial locations in memory.

[0092] Step 167 includes obtaining multiple possibilities and their corresponding spatial locations from memory, generating a spatial map indicating the multiple possibilities at the corresponding spatial locations, and displaying the spatial map, for example, on a display of a mobile device. Therefore, the spatial map represents the detection coverage area. Step 101 is repeated after step 167.

[0093] For example, one of the following techniques can be used to visualize spatial mappings:

[0094] (1) Use a planar graph for visualization. For example, the probability / confidence level of detection can be displayed as a planar graph, where areas are indicated by color (e.g., green: high confidence of being detected, red: high confidence of not being detected);

[0095] (2) Utilizing the augmented reality (AR) capabilities of mobile devices (e.g., smartphones or AR glasses). For example, a user can view an area through a smart device (e.g., a smartphone) to directly see areas with high and low detection probabilities / confidence. Thus, a user can point their smart device at the area to see the detection probability / confidence level overlaid on top of the camera view.

[0096] Figure 12 An example of spatial mapping visualized using a floor plan is shown. Rooms 71 and 72 are graphically represented on display 9 of mobile device 1. Black disks indicate the locations of lighting fixtures, which are also nodes in the presence sensor system and transmit or receive RF signals. Disk 81 and two rings 82 and 83 are superimposed on room 71. Disk 84 and two rings 85 and 86 are superimposed on room 72.

[0097] For example, disks 81 and 84 indicate a high probability of detection and can be colored green. Rings 82 and 85 indicate a medium probability of detection and can be colored orange. Rings 83 and 86 indicate a low probability of detection and can be colored red. The area enclosed by disks 81 and 84 and rings 82 and 85 is the detection area.

[0098] Figure 13A second example of a spatially mapped area representing detection coverage is shown. In this second example, areas where conflicting detection results are expected between two detection zones are shown. Zone 89 shows the overlapping area between rooms 71 and 72 where problems are most likely to occur, meaning that the probability / confidence level of detecting a user is similar for both detection zones in this particular location.

[0099] This visualization can help solve problems in multi-zone scenarios, such as when it's impossible to determine which zone a user is in. Changing the location of (multiple) RF transmitters and / or (multiple) RF receivers, changing (multiple) transmit power, and / or changing detection parameters (such as zone sensitivity) may help resolve these issues. Figure 13 In the example, rings 83 and 86 are shown to make the visualization easier to understand. In an alternative visualization, rings 83 and 86 are omitted and / or one or more disks 81 and 84, as well as rings 82 and 85, are shown.

[0100] Figure 14 The description indicates that the procedure can be performed as per the reference. Figure 3 , Figure 6 and Figure 11 A block diagram of an exemplary data processing system for the described method.

[0101] like Figure 14 As shown, the data processing system 300 may include at least one processor 302 coupled to a memory element 304 via a system bus 306. Thus, the data processing system can store program code within the memory element 304. Furthermore, the processor 302 can execute program code accessed from the memory element 304 via the system bus 306. In one aspect, the data processing system may be implemented as a computer suitable for storing and / or executing program code. However, it should be understood that the data processing system 300 may be implemented in the form of any system including a processor and memory capable of performing the functions described herein.

[0102] Memory element 304 may include one or more physical memory devices, such as, for example, local memory 308 and one or more mass storage devices 310. Local memory may refer to random access memory or (multiple) other non-persistent storage devices generally used during the actual execution of program code. Mass storage devices may be implemented as hard disk drives or other persistent data storage devices. Processing system 300 may also include one or more cache memories (not shown) that provide temporary storage for at least some program code to reduce the number of times program code must be retrieved from mass storage device 310 during execution. For example, if processing system 300 is part of a cloud computing platform, processing system 300 may also be able to use memory elements of another processing system.

[0103] Optionally, the input / output (I / O) devices depicted as input device 312 and output device 314 can be coupled to the data processing system. Examples of input devices may include, but are not limited to, a keyboard, a pointing device such as a mouse, or a microphone (e.g., for voice and / or speech recognition). Examples of output devices may include, but are not limited to, a monitor or display, or a speaker. The input and / or output devices can be coupled to the data processing system directly or through an intermediate I / O controller.

[0104] In embodiments, the input and output devices may be implemented as a combined input / output device (in... Figure 14 (Dashed lines are used to illustrate input device 312 and output device 314). An example of such a combined device is a touch-sensitive display, sometimes also called a "touchscreen display" or simply a "touchscreen". In such embodiments, input to the device can be provided by the movement of a physical object, such as, for example, a user's finger or stylus, on or near the touchscreen display.

[0105] Network adapter 316 can also be coupled to the data processing system to enable it to couple to other systems, computer systems, remote network devices, and / or remote storage devices via an intermediate private or public network. The network adapter may include a data receiver for receiving data transmitted to the data processing system 300 from the systems, devices, and / or networks, and a data transmitter for transmitting data from the data processing system 300 to the systems, devices, and / or networks. Modems, cable modems, and Ethernet cards are examples of different types of network adapters that can be used with the data processing system 300.

[0106] like Figure 14As shown, memory element 304 can store application program 318. In various embodiments, application program 318 can be stored in local memory 308, one or more mass storage devices 310, or separately from local memory and mass storage devices. It should be understood that data processing system 300 can further execute an operating system that facilitates the execution of application program 318. Figure 14 (Not shown in the image). The application program 318, implemented in the form of executable program code, can be executed by the data processing system 300 (e.g., by the processor 302). In response to executing the application program, the data processing system 300 can be configured to perform one or more operational or method steps described herein.

[0107] Figure 14 An input device 312 and an output device 314, separate from the network adapter 316, are shown. However, additionally or alternatively, input may be received via the network adapter 316, and output may be transmitted via the network adapter 316. For example, the data processing system 300 may be a cloud server. In this case, input can be received from a user equipment acting as a terminal, and output can be transmitted to the user equipment acting as a terminal.

[0108] Various embodiments of the present invention can be implemented as a program product for use with a computer system, wherein the program(s) of the program product define the functionality of the embodiments (including the methods described herein). In one embodiment, the program(s) may be contained on a variety of non-transitory computer-readable storage media, wherein, as used herein, the expression “non-transitory computer-readable storage media” includes all computer-readable media, with the sole exception of transient propagation signals. In another embodiment, the program(s) may be contained on a variety of transient computer-readable storage media. Illustrative computer-readable storage media include, but are not limited to: (i) non-writable storage media on which information is permanently stored (e.g., read-only memory devices within a computer, such as CD-ROM discs readable by a CD-ROM drive, ROM chips, or any type of solid-state non-volatile semiconductor memory); and (ii) writable storage media on which changeable information is stored (e.g., flash memory, floppy disks within a floppy disk drive or hard disk drive, or any type of solid-state random access semiconductor memory). The computer program may run on the processor 302 described herein.

[0109] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” (“a” or “an”) and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that, when used in this specification, the terms “comprise” and / or “comprising” specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0110] All the means or steps plus functional elements in the following claims are intended to include any structure, material, action, and equivalent for performing a function in combination with other claimed elements as specifically claimed. Descriptions of embodiments of the invention have been shown for illustrative purposes, but are not intended to be exhaustive or limited to the embodiments in the disclosed forms. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Embodiments have been chosen and described in order to best explain the principles of the invention and some practical applications, and to enable others skilled in the art to understand the invention with respect to various embodiments with various modifications suitable for particular uses.

Claims

1. A system (1, 41) for determining the probability of the presence of a person or animal based on sensing input, said sensing input reflecting changes in radio frequency signals received by one or more devices (16, 31-36), said system (1, 41) comprising: At least one input interface (3, 43); At least one output interface (4, 9, 44). and At least one processor (5, 45) is configured as follows: - The sensing input is determined using the at least one input interface (3, 43). - Determine the probability of the presence of the person or animal based on the sensor input. - In the normal operating mode of the lighting device (31), the lighting device (31) is controlled using at least one output interface (4, 44) to present a light effect when the determined probability exceeds a presence detection threshold, and to continue presenting the light effect for the predetermined time period even if the determined probability changes by more than a predetermined value in a subsequent predetermined time period. - In the configuration mode of the lighting device (31), using the at least one output interface (4, 44), the user is indicated to the determined possibility via the lighting device (31) by presenting an additional light effect among a plurality of light effects, the additional light effect being selected based on the determined possibility. The processor is configured to: determine a value from a plurality of values ​​corresponding to the determined possibility, wherein each of the plurality of values ​​is associated with a corresponding range of possibilities and with a corresponding other lighting effect, wherein the processor is configured to: when determining that a subsequently determined possibility corresponds to a value different from a previously determined value, select a subsequent other lighting effect from the plurality of lighting effects that is different from a previously selected other lighting effect.

2. The system (1, 41) according to claim 1, wherein the at least one processor (45) is configured to use the at least one input interface (43) to receive user input and switch between the normal operation mode and the configuration mode based on the user input.

3. The system (1, 41) according to claim 1 or 2, wherein the at least one processor (45) is configured to determine the chromaticity, luminance and / or light output level of the additional light effect based on the possibility, such that the chromaticity, luminance and / or light output level indicates the possibility.

4. The system (41) according to claim 1 or 2, wherein the at least one processor (45) is configured to determine the additional light effect based on the possibility and the capability of the lighting device.

5. The system (41) according to claim 1 or 2, wherein, In the configuration mode of the lighting device (31), the at least one processor (45) is configured to select a first light effect from the plurality of light effects when it is determined that the probability exceeds the presence detection threshold, and to select a second light effect from the plurality of light effects when it is determined that the probability is below the presence detection threshold.

6. The system (41) according to claim 5, wherein, In the configuration mode of the lighting device (31), the at least one processor (45) is configured to determine the color of the additional light effect in a first color spectrum when the probability is determined to be greater than the presence detection threshold, and to determine the color of the additional light effect in a second color spectrum when the probability is determined to be less than the presence detection threshold.

7. The system (41) according to claim 6, wherein, In the configuration mode of the lighting device (31), the at least one processor (45) is configured to determine the color within the first or second color spectrum based on the probability, such that the color further indicates the probability.

8. The system (41) according to claim 1 or 2, wherein the at least one processor (45) is configured to determine the dynamic level of the additional light effect based on the possibility, such that the dynamic level indicates the possibility.

9. A system (1, 41) for determining the probability of the presence of a person or animal based on sensing input, said sensing input reflecting changes in radio frequency signals received by one or more devices (16, 31-36), said system (1, 41) comprising: At least one input interface (3, 43); At least one output interface (4, 9, 44). and At least one processor (5, 45) is configured as follows: - The sensing input is determined using the at least one input interface (3, 43). - Determine the probability of the presence of the person or animal based on the sensor input. - In the normal operating mode of the lighting device (31), the at least one output interface (4, 44) is used to control the lighting device (31) to present a light effect when it is determined that the determined probability exceeds the presence detection threshold, and to continue presenting the light effect for the predetermined time period even if the probability changes by more than a predetermined value in the subsequent predetermined time period, and - The determined possibility is indicated to the user via an indication selected from a plurality of indications by: sending the indication to a remote display via the at least one output interface (4, 44) to indicate the determined possibility to the user by displaying the indication on the remote display; or, when the system (1, 41) further includes a display (9), indicating the possibility to the user by displaying the indication on the display (9). The at least one processor (5, 45) is configured to: determine an indication among the plurality of indications corresponding to the determined possibility, wherein each of the plurality of indications is associated with a corresponding possibility or range of possibilities, wherein the indication is presented on the remote display or the display (9) in a digital, graphical or a combination of both manner.

10. The system (1, 41) of claim 1, wherein the at least one processor (5, 45) is configured to determine a plurality of possibilities of the presence of a person or animal based on a plurality of sensing inputs, each of the plurality of sensing inputs corresponding to a corresponding spatial location of the person or animal; and to associate each of the plurality of possibilities with the corresponding spatial location in a memory (7, 47).

11. The system (1, 41) according to claim 10, wherein, When the system further includes a display, the at least one processor (5) is configured to use the display to display the spatial mapping indicating the plurality of possibilities at the respective spatial locations.

12. The system (1, 41) according to claim 1, wherein the lighting device (31) is one of the one or more devices (16, 31-36).

13. A method for determining the probability of the presence of a person or animal based on sensing input, said sensing input reflecting changes in radio frequency signals received by one or more devices, the method comprising: - Determine the sensing input (101); - Determine the probability of the presence of the person or animal based on the sensing input (103); - In the normal operating mode of the lighting device (31), the control (105) of the lighting device presents a light effect when it is determined that the determined probability exceeds the presence detection threshold, and continues to present the light effect during the predetermined time period even when the determined probability changes beyond a predetermined value in the subsequent predetermined time period. - In the configuration mode of the lighting device (31), the possibility determined by the lighting device (31) is indicated to the user (107) by presenting another light effect among a plurality of light effects; - Select the additional lighting effect based on the determined possibilities; - Determine a value from a plurality of values ​​corresponding to the determined possibility, wherein each of the plurality of values ​​is associated with a corresponding range of possibilities and with another corresponding lighting effect; as well as - When it is determined that the possibility of a subsequent determination corresponds to a value different from the previously determined value, select another subsequent light effect that is different from the other light effect previously selected from the plurality of light effects.

14. A computer program product storing at least one software code portion, said software code portion being configured, when run on a computer system, to enable the method of claim 13 to be executed.

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