Human body detection processing method and device and terminal equipment

Abstract

The invention relates to a human body detection processing method and device and terminal equipment, and the human body detection processing method is applied to a detection device and at least comprises the steps that detection state data is sent in response to a data obtaining request, so that the terminal equipment obtains the detection state data, fault diagnosis analysis is carried out on the detection state data based on a set diagnosis rule, and active service control is carried out by detecting and responding to an input instruction of a user on a diagnosis analysis result; acquiring a detection parameter sent by the terminal equipment, and executing a reconfiguration operation on the detection response characteristic; wherein the detection parameters are sent based on input after the terminal equipment captures parameter input of at least one parameter adjustment item included in a solution generated and output when a diagnosis analysis result of a user is abnormal based on active service control; the parameter adjustment item and at least one adjustable detection parameter form a direct operation binding relationship; the detection parameters are used for adjusting the detection response characteristics of the detection device.

Description

Technical Field

[0001] This disclosure relates to the field of human body detection technology, and in particular to a human body detection processing method, apparatus and terminal equipment. Background Technology

[0002] With the rapid development of the Internet of Things and intelligent sensing technologies, human body detection systems based on radar, infrared, and other technologies have been widely used in smart homes, security monitoring, health care, and other fields.

[0003] In practical applications, various electromagnetic interferences (such as Wi-Fi signals and radiation from home appliances) and dynamic environmental noises (such as swaying curtains and pet activities) often require the adjustment of various detection parameters during the use of detection devices. Existing parameter adjustment methods require users to manually search for relevant settings in complex parameter menus, and non-professional users find it difficult to accurately match the problem with the corresponding parameters, which seriously affects configuration efficiency and accuracy.

[0004] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0005] One objective of this invention is to provide a human body detection processing method, device, and electronic device, wherein the detection threshold is transformed from static setting to intelligent dynamic adjustment through a three-layer mapping architecture of "adjustment path - sensing characteristics - threshold mechanism".

[0006] Another objective of this invention is to provide a human body detection processing method, apparatus, and electronic device, wherein a precise mapping relationship between adjustment path and sensing characteristics is established, enabling the overall optimization of the threshold system to be automatically completed with a single strategy selection, thereby improving the reliability and scene adaptability of the detection device under the expected sensing characteristics.

[0007] Another objective of this invention is to provide a human body detection processing method, apparatus, and electronic device, wherein a stationary condition screening mechanism is introduced, which significantly improves the accuracy of the detection device 100 in identifying spaces where people are present.

[0008] Another objective of this invention is to provide a human body detection processing method, device, and electronic device, which effectively filters false alarms caused by environmental noise, multipath effects, etc. through a dual screening of "peak value + threshold". The comparison of intensity value signals of adjacent detection subspaces is introduced, which is more consistent with the signal distribution characteristics of real human targets (usually localized). The introduction of a stationary condition screening mechanism optimizes the triggering logic of the detection device and significantly improves the accuracy of the detection device in identifying spaces where people are present.

[0009] Another objective of this invention is to provide a human body detection and processing method, apparatus, and electronic device, in which multiple parameter adjustment items are intelligently organized and displayed according to operating conditions. After the user selects the corresponding operating condition description item, the terminal device automatically generates a composite interface integrating relevant solutions and parameter adjustments. Through this intelligent interface, users can not only quickly view the operating condition description but also directly adjust relevant parameters, thereby quickly troubleshooting or optimizing performance.

[0010] Another objective of this invention is to provide a human body detection processing method, apparatus, and electronic device, in which users can easily trigger fault diagnosis and adjust parameter settings based on feedback results, thereby improving the stability and response speed of the device. Furthermore, by directly binding parameter adjustment items to detection characteristics, a "diagnosis-adjustment" closed loop is formed, facilitating adjustment operations and simplifying the device maintenance and configuration process, significantly improving the efficiency and reliability of the detection device.

[0011] Another objective of this invention is to provide a human body detection processing method, apparatus, and electronic device, wherein the presence determination window can be dynamically adjusted according to changes in environmental parameters and detection status, and the device is more sensitive to rapidly changing environments or irregular detection statuses.

[0012] Another objective of this invention is to provide a human body detection processing method, apparatus, and electronic device, wherein an adaptive human body detection processing method based on multi-parameter collaborative sensing is provided. This method can flexibly adjust the judgment window according to the synergistic effect of environmental changes and detection status, thereby improving the adaptability and accuracy of human presence detection.

[0013] To achieve at least one of the above objectives, according to a first aspect of the present invention, a human body detection processing method is provided, applied to a detection device, the method comprising at least: sending detection status data in response to a data acquisition request, such that: a terminal device acquires the detection status data, performs fault diagnosis analysis on the detection status data based on set diagnostic rules, and detects and responds to a user's input instruction on the diagnostic analysis result, performs active service control; wherein the data acquisition request is sent by the terminal device in response to an active detection request initiated by the user, and the detection status data characterizes the current human body presence state in the detection space; acquiring detection parameters sent by the terminal device, and performing a reconfiguration operation on the detection response characteristics; wherein the detection parameters are sent by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, based on the active service control; the parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter; the detection parameters are used to adjust the detection response characteristics of the detection device.

[0014] To achieve at least one of the above objectives, according to a second aspect of the present invention, a detection device is provided, comprising: a data transmission unit, configured to transmit detection status data in response to a data acquisition request, such that: a terminal device acquires the detection status data, performs fault diagnosis analysis on the detection status data based on a set diagnostic rule, and detects and responds to a user's input instruction on the diagnostic analysis result to perform active service control; wherein the data acquisition request is sent by the terminal device in response to an active detection request initiated by a user, and the detection status data characterizes the current human presence state in the detection space; and a response characteristic configuration unit, configured to acquire detection parameters sent by the terminal device and perform real-time reconfiguration operation on the detection response characteristics; wherein the detection parameters are transmitted by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, captured by the active service control; the parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter; and the detection parameters are used to adjust the detection response characteristics of the detection device.

[0015] To achieve at least one of the above objectives, according to a third aspect of the present invention, a human body detection processing method is provided, comprising: in response to an active detection request initiated by a user, acquiring detection status data of a detection device; performing fault diagnosis analysis on the detection status data based on set diagnostic rules; detecting and responding to an input instruction from a user regarding the diagnostic analysis result, performing active service control; the active service control is used to capture parameter input of at least one parameter adjustment item included in a solution generated and output by the user when the diagnostic analysis result is abnormal, and performing a reconfiguration operation on the detection response characteristics of the detection device based on the input; the parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter; the detection parameter is used to adjust the detection response characteristics of the detection device; or, based on a normal diagnostic analysis result, generating confirmation information that the detection device is operating normally.

[0016] To achieve at least one of the above objectives, according to a fourth aspect of the present invention, a terminal device is provided, comprising: an active detection unit, configured to acquire detection status data of a detection device in response to an active detection request initiated by a user; a diagnostic analysis unit, configured to perform fault diagnostic analysis on the detection status data based on set diagnostic rules; and an active service control unit, configured to detect and respond to an input command from a user regarding the diagnostic analysis result, and perform active service control; the active service control is configured to capture parameter input of at least one parameter adjustment item included in a solution generated and output by the user when the diagnostic analysis result is abnormal, and to perform a reconfiguration operation on the detection response characteristics of the detection device based on the input; the parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter; the detection parameter is used to adjust the detection response characteristics of the detection device; or, based on a normal diagnostic analysis result, to generate confirmation information that the detection device is operating normally.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. The foregoing inventive descriptions can be combined in any way, and these and other objectives of this disclosure will be fully realized through the following detailed description and accompanying drawings.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. These drawings are incorporated in and constitute a part of this specification, illustrating embodiments consistent with this application and serving together with the specification to explain the principles of this application. Obviously, the drawings described below are merely some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0020] Figure 1 This is a schematic diagram of an exemplary network connection environment for a human body detection system according to one embodiment of this disclosure;

[0021] Figure 2 This is a schematic diagram of the hardware implementation circuit of a detection device according to one embodiment of the present disclosure;

[0022] Figure 3 This is a schematic diagram of a specific use scenario in one embodiment of the present disclosure;

[0023] Figure 4 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 1 ;

[0024] Figure 5 This is a schematic diagram of the path selection adjustment interface in one embodiment of the present disclosure;

[0025] Figure 6 This is a schematic diagram of the detection space division in one embodiment of this disclosure;

[0026] Figure 7 This is a schematic diagram of the detection sub-threshold adjustment in one embodiment of this disclosure;

[0027] Figure 8 This is a schematic diagram of manual adjustment of the detection sub-threshold in one embodiment of this disclosure;

[0028] Figure 9a This is a schematic diagram illustrating the effect of setting the maximum detection distance to trigger the adjustment of the working mode in one embodiment of this disclosure;

[0029] Figure 9b This is a schematic diagram illustrating the detection subspace shielding effect in one embodiment of this disclosure;

[0030] Figure 9c This is a schematic diagram of interface changes in close-range spatial settings according to one embodiment of the present disclosure;

[0031] Figure 9d This is a schematic diagram of the alternating arrangement of effective detection subspace and shielded detection subspace in one embodiment of this disclosure;

[0032] Figure 10 Is with Figure 9a and Figure 9b The corresponding interference indicator elements are shown in the diagram.

[0033] Figure 11 This is a schematic block diagram of a terminal device according to an embodiment of the present disclosure. Figure 1 ;

[0034] Figure 12 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 2 ;

[0035] Figure 13 This is a schematic block diagram of a detection device according to an embodiment of the present disclosure. Figure 1 ;

[0036] Figure 14 This is one embodiment of the present disclosure

[0037] Figure 15 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 3 ;

[0038] Figure 16This is a schematic diagram of a stationary subspace based on spatiotemporal distribution characteristics in one embodiment of this disclosure;

[0039] Figure 17 This is a schematic diagram of a stationary subspace detection of the curtain position in a closed window state according to an embodiment of this disclosure;

[0040] Figure 18 Is Figure 17 A schematic diagram of the stationary subspace detection during the process of a human body moving towards the detection device, with the window further opened in the scenario shown.

[0041] Figure 19 This is a schematic diagram showing the human signal feature intensity corresponding to the stationary subspace where a person is triggered in one embodiment of this disclosure;

[0042] Figure 20 This is a schematic block diagram of a detection device according to an embodiment of the present disclosure. Figure 2 ;

[0043] Figure 21 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 4 ;

[0044] Figure 22 This is a schematic diagram of the working condition description selection interface in one embodiment of this disclosure;

[0045] Figure 23 This is a schematic diagram illustrating the adjustment of working mode parameters under a first abnormal working condition in one embodiment of this disclosure;

[0046] Figure 24 This is a schematic diagram of radar sensitivity adjustment under a first abnormal operating condition in one embodiment of this disclosure;

[0047] Figure 25 This is a schematic diagram of infrared sensitivity adjustment under a first abnormal operating condition in one embodiment of this disclosure;

[0048] Figure 26 This is a schematic diagram of the anti-interference level adjustment under the first abnormal operating condition in one embodiment of this disclosure;

[0049] Figure 27 This is a schematic diagram of radar sensitivity adjustment under a second abnormal operating condition in one embodiment of this disclosure;

[0050] Figure 28 This is a schematic diagram of adjusting the parameters of the second abnormal operating condition determination window under the present disclosure;

[0051] Figure 29 This is a schematic diagram of the accidental triggering operation under the second abnormal working condition in one embodiment of this disclosure;

[0052] Figure 30This is a schematic diagram of an installation guide operation according to one embodiment of the present disclosure;

[0053] Figure 31 This is a schematic block diagram of a terminal device according to an embodiment of the present disclosure. Figure 2 ;

[0054] Figure 32 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 5 ;

[0055] Figure 33 This is a schematic block diagram of a detection device according to an embodiment of the present disclosure. Figure 3 ;

[0056] Figure 34 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 6 ;

[0057] Figure 35 This is a flowchart illustrating the process of a normal diagnostic result under a third abnormal operating condition in one embodiment of this disclosure;

[0058] Figure 36 This is a schematic diagram illustrating the abnormal diagnostic results under the third abnormal operating condition in one embodiment of this disclosure;

[0059] Figure 37 This is a flowchart illustrating the process of diagnosing a normal result under the fourth abnormal operating condition in one embodiment of this disclosure;

[0060] Figure 38 This is a schematic diagram illustrating the abnormal diagnostic results under the fourth abnormal operating condition in one embodiment of this disclosure;

[0061] Figure 39 This is a schematic block diagram of a terminal device according to an embodiment of the present disclosure. Figure 3 ;

[0062] Figure 40 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 7 ;

[0063] Figure 41 This is a schematic block diagram of a detection device according to an embodiment of the present disclosure. Figure 4 ;

[0064] Figure 42 This is a flowchart illustrating a human body detection and processing method according to an embodiment of this disclosure. Figure 8 ;

[0065] Figure 43 This is a flowchart illustrating the specific workflow of a mode switching instruction in one embodiment of this disclosure;

[0066] Figure 44This is a schematic block diagram of a detection device according to an embodiment of the present disclosure. Figure 5 . Detailed Implementation

[0067] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0068] With the rapid development of the Internet of Things and intelligent sensing technologies, human body detection systems based on radar, infrared, and other technologies have been widely used in smart homes, security monitoring, health care, and other fields.

[0069] Please refer to Figure 1 This is a schematic diagram of an exemplary network connection environment for a human body detection system provided in this embodiment. It can be seen that the human body detection system includes a detection device 100, a gateway 300, a router 400, a cloud platform 500, a terminal device 600, and a controlled device 700.

[0070] Figure 1 The diagram illustrates a detection device 100 and a controlled device 700. In a real system, there can be multiple detection devices 100 and controlled devices 700. The detection device 100, terminal device 60, controlled device 700, and gateway 300 can transmit data wirelessly, which can be based on protocols such as Bluetooth, Wi-Fi, or ZigBee.

[0071] Furthermore, the detection device 100 can connect to the router 400 via the gateway 300 (e.g., a Bluetooth gateway) to access the internet and communicate with the cloud 500. The terminal device 600 can interact with the cloud 500 via cellular communication or Wi-Fi.

[0072] The terminal device 600 may include, but is not limited to, smart terminal devices such as smartphones and tablets. The controlled device 700 may include, for example, but is not limited to, lamps, air conditioners, curtain motors, etc.

[0073] When the controlled device 700 is a lighting fixture, the system also includes a switching device for controlling the lighting fixture, such as turning the light on, turning it off, and dimming it. The switching device includes, but is not limited to, the following types:

[0074] Wall switch: A wall switch powered by a neutral wire and a live wire can be a traditional wall switch that switches the on / off state of a light fixture by controlling the power supply circuit of the light fixture, or a smart wall switch that controls the light fixture by wireless signal.

[0075] Wireless switch: A wireless switch powered by a battery or a self-generating motor, which controls the lighting fixtures via wireless signals.

[0076] The detection device 100 can be understood as a sensing device that integrates human body sensing function and light detection function.

[0077] Furthermore, the terminal device 600 and / or the detection device 100 are also used to execute the human body detection processing methods provided in the following embodiments. Therefore, the following description of the human body detection processing methods is essentially a detailed exposition of the software and / or hardware working processes, functions, and specific implementation methods in the terminal device 600 and / or the detection device 100.

[0078] like Figure 2 As shown, a possible hardware implementation embodiment of the detection device 100 is given.

[0079] like Figure 2 The diagram shown is a schematic circuit block diagram of the detection device 100. It can be seen that the detection device 100 includes a radar module, an infrared pyroelectric module, a light acquisition module, and a processor. The processor receives data signals acquired by the radar module, the infrared pyroelectric module, and the light acquisition module. The integrated design of the radar module and the infrared pyroelectric module enables the processor to possess multimodal sensing capabilities, including at least one of the following: fusion detection mode, pure radar mode, and pure infrared mode. In the fusion detection mode, both the radar module and the infrared pyroelectric module are used simultaneously to detect the presence of a human in the detection space. The infrared pyroelectric module performs biological confirmation, while the radar module performs motion / micro-motion confirmation. Only when both confirm a person is a person detected is the detection space confirmed to be occupied. The pure radar mode uses only the radar module to detect whether a person is in the space. The pure infrared mode uses only the infrared pyroelectric module to detect whether a person is in the space. In this mode, the radar module can be powered off (e.g., ...). Figure 2 In this system, the processor cuts off power to the radar module via a switching component to save energy. Furthermore, when the radar module malfunctions (e.g., crashes), the processor can also restart it by cutting off power via the switching component.

[0080] In this embodiment, the detection device 100 is powered by high-voltage electricity (e.g., 220V AC power). A power conversion circuit transforms the 220V AC power into a suitable power supply for the downstream circuitry. Specifically, the power output from the power conversion circuit is further supplied to the radar module and the processor via two independent first voltage conversion circuits. In other words, the radar module and the processor have the same power supply level, but use independent power supply circuits.

[0081] Furthermore, the power output from the first voltage conversion circuit that powers the processor is further regulated by the second voltage conversion circuit before supplying power to the light acquisition module and the infrared pyroelectric module. The radar module and the light acquisition module share one circuit board (e.g., the second circuit board 22, which will be described later), while the processor and the infrared pyroelectric module share another circuit board, such as the first circuit board 4, which will be described later. Additionally, the first circuit board 4 also houses other high-voltage and low-voltage circuits.

[0082] As can be seen, in this embodiment, the light acquisition module and the infrared pyroelectric module, which share a power supply circuit (i.e., share a first voltage conversion circuit and a second voltage conversion circuit), are placed on different circuit boards, while the light acquisition module and the radar module, which do not share a power supply circuit (i.e., do not share a first voltage conversion circuit), are placed on the same circuit board. By adopting this heterogeneous power supply method with a separate board design and independent power supply architecture, power supply efficiency and electromagnetic compatibility are cleverly balanced. A two-level power supply architecture of "main conversion - secondary conversion" is constructed on the power link, and a three-dimensional isolation mechanism of "same source, heterogeneous distribution of power supply" is formed in the physical layout, providing a better layout scheme for multi-sensor integration.

[0083] Furthermore, the power conversion circuit employs an AC-DC isolated power supply to convert 220V AC power into 5V DC power output. Specifically, the isolated power supply includes a transformer. The 220V AC power is rectified by a rectifier bridge and then connected to the primary winding of the transformer. The primary and secondary windings of the transformer operate alternately in a time-sharing manner. During the positive half-cycle of the control power supply pulse, the converter stores energy through the primary winding and releases energy through the secondary winding during the negative half-cycle, thus reducing the 220V input voltage to 5V output and achieving electrical isolation.

[0084] The 5V DC power supply is supplied to two first voltage conversion circuits. The first voltage conversion circuit can use a low dropout linear regulator (LDO) to convert 5V to 3.3V output. One 3.3V output supplies power to the radar module through a switching component, while the other 3.3V output supplies power to the processor and is also supplied to the second voltage conversion circuit. The second voltage conversion circuit can use another type of low dropout linear regulator to regulate the 3.3V to 2.5V and then supply power to the light acquisition module and the infrared pyroelectric module.

[0085] In a specific example, the radar module can employ millimeter-wave radar, such as the MRS262 millimeter-wave radar sensor. As a 24GHz 1T1RAoB millimeter-wave radar sensor, it integrates a 24GHz millimeter-wave radar antenna, RF front-end, baseband, and application processor. The MRS262 millimeter-wave radar sensor possesses high-precision ranging capabilities, while simultaneously enabling accurate perception of human movement, subtle movements, and presence.

[0086] The switching component can be a PMOS transistor. The processor controls the power supply of the MRS262 through the PMOS. When the MRS262 malfunctions, the processor can power off and restart the MRS262 by controlling the gate of the PMOS. When in some special modes (such as pure infrared mode, low power mode, etc.), the processor can also turn off the power supply of the MRS262.

[0087] The infrared pyroelectric module can use the L142F7 light sensor, and the second voltage conversion circuit that powers it can use the LDO chip LDO-WL9005S5-25. The typical output current of the LDO-WL9005S5-25 is 500mA, and the typical PSRR is 70dB.

[0088] The light acquisition module can use a phototransistor XYC-PT0805BC-L4-D. The greater the ambient light, the greater the photocurrent and the greater the output analog voltage ALS value. The processor calculates the corresponding illuminance by recognizing the change in the ALS voltage value.

[0089] The processor can be an electronic component with data processing capabilities, such as a microcontroller (MCU), microprocessor (MPU), digital signal processor (DSP), programmable logic controller (PLC), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or system-on-a-chip (SoC). It can also be an integrated circuit system composed of the above components through a bus architecture, on-chip network (NoC), or other interconnection methods. Depending on the specific application scenario, the processor can integrate heterogeneous computing cores such as a central processing unit (CPU) and a graphics processing unit (GPU), and can achieve performance expansion through multi-core architecture, cluster architecture, or distributed architecture.

[0090] In addition, the detection device 100 also includes a communication unit, which provides the processor with external data interaction capabilities and supports wired or wireless communication. The communication unit and the processor can be designed separately (such as an external communication module connected via interfaces such as UART, SPI, or USB) or integrated (such as a SoC chip integrating Wi-Fi / Bluetooth). The antenna of the communication unit (e.g., antenna 46) is also disposed on the first circuit board 4.

[0091] In addition, the detection device 100 may also include a light-emitting unit electrically connected to a processor for providing an indication signal, such as a blue indicator light. The blue indicator light flashes when someone is detected. It may also include an electronic switch electrically connected to the processor for detecting external operations. For example, when a user presses the electronic switch to a predetermined condition (e.g., press and hold for more than 5 seconds), the processor enters a network reset mode. In network reset mode, network reset messages are continuously broadcast. These messages carry network reset information representing the detection device 100, enabling external devices such as the terminal device 600 and gateway 300 to receive the messages and, based on the network reset information, guide the detection device 100 to join the designated network according to predetermined steps, thereby completing the network reset of the detection device 100. After completing the network reset, the detection device 100 can connect to the cloud 500 through the gateway 300 and router 400, and then report its own status data to the cloud.

[0092] When the terminal device 600 is a mobile phone, it can run a corresponding application to configure and view the parameters of the detection device 100. In addition, the detection device 100 will report its own detection status data to the gateway 300 and / or the cloud 500. The gateway 300 can directly trigger the controlled device 700 to switch its working status (e.g., turning on the light when someone is there, turning off the light when no one is there), or indirectly trigger the controlled device 700 through the cloud 500. When triggered through the cloud, the cloud will match the received detection status data with the pre-configured control rules. When the detection status data matches the control conditions defined by the control rules, the controlled device 700 will be triggered to perform the corresponding action (e.g., turning on the light, turning off the light, etc.) according to the control result defined by the control rules.

[0093] like Figure 3 The diagram illustrates a practical application scenario of the detection device 100. Specifically, the switching device is a wall switch 900, and the light fixture 800 is arranged in the control channel of the wall switch 900, thereby controlling the on / off state of the light fixture 800 by turning the wall switch 900 on / off. Simultaneously, the wall switch 900 can also interact with the light fixture 800 via wireless signals to perform corresponding dimming actions. The detection device 100 is embedded in the ceiling panel 200 to detect whether someone has entered the room. When someone enters, it directly or indirectly triggers the light fixture 800 to turn on; when no one is detected in the room, it triggers the light fixture 800 to turn off.

[0094] In practical applications, various electromagnetic interferences (such as Wi-Fi signals and radiation from home appliances) and dynamic environmental noise (such as swaying curtains and pet activities) often require the sensitivity of detection devices to be adjusted during use. Traditional solutions use fixed thresholds or single adjustment methods, which severely restricts the reliability of the devices and the user experience in diverse scenarios.

[0095] Specifically, existing sensitivity adjustment methods for detection devices are fixed and singular, making it impossible to simultaneously address the diverse needs for false trigger suppression and detection sensitivity in different scenarios. Especially when environmental interference exists (such as electrical radiation or moving objects), users often need to find trade-offs between various sensing characteristics (e.g., "reducing false alarms" and "improving detection rate") based on the actual usage scenario. However, existing technologies lack a systematic strategy selection mechanism, resulting in a cumbersome adjustment process and limited effectiveness.

[0096] Based on this, one embodiment of this disclosure provides a human body detection processing method, which offers a three-layer mapping architecture of "adjustment path - perception characteristics - threshold adjustment mechanism". This architecture transforms complex signal processing parameters into intuitive user strategy options, establishes a precise mapping relationship between the adjustment path and perception characteristics, and enables automatic optimization of the overall threshold system with a single strategy selection. This human body detection processing method can be applied to applications such as... Figure 1 The human body detection system shown can be applied to terminal device 600.

[0097] like Figure 4 The diagram shows a flowchart of a human body detection processing method 40 provided in an embodiment of this disclosure; it can be seen that the method 40 includes at least steps S401 to S403.

[0098] In step S401, the terminal device responds to the adjustment trigger request and outputs at least two adjustment paths with different sensing characteristics.

[0099] The adjustment trigger request can be understood as an instruction signal initiated by the user or system to start the sensitivity configuration process of the detection device. The generation and response of the adjustment trigger request constitute the entry logic of the sensitivity adjustment of the detection device.

[0100] Sensing characteristics can be understood as one or more performance characteristics of a detection device, such as, but not limited to, indicators like accidental touch prevention, detection sensitivity, and detection latency. Correspondingly, adjustment paths can be understood as a set of predefined or user-defined sensitivity adjustment strategies, with each path corresponding to one or more specific sensing characteristics.

[0101] Each adjustment path is mapped to an independent detection threshold adjustment mechanism. This adjustment mechanism can be understood as a dynamic adjustment algorithm designed to achieve target perception characteristics. The detection threshold is used to determine the trigger threshold for the presence of a human in the detection space, i.e., the critical intensity level for judging the presence of a human in the detection space. Different adjustment paths correspond to different dynamic adjustment algorithms, allowing the detection thresholds adjusted through different paths to reflect different overall performance characteristics of the detection device.

[0102] Specifically, the detection device has:

[0103] Trigger detection state, used to check whether someone has entered the detection space after confirming that no one is in the detection space. And,

[0104] Maintaining the detection status is used to detect whether the detection space is empty after it has been determined that someone is in the detection space (i.e., whether the person in the detection space has left).

[0105] During normal operation of the detection device, the triggered detection state and the maintained detection state alternate to detect the presence of a human body in the detection space. The detection threshold includes a first trigger threshold and / or a second trigger threshold. The first trigger threshold is used to determine the trigger threshold for the triggered detection state; that is, in the triggered detection state, when the detection device detects a human characteristic signal strength value greater than or equal to the first trigger threshold, it determines that someone has entered the detection space. The second trigger threshold is used to determine the trigger threshold for the maintained detection state; that is, in the maintained detection state, when the detection device detects a human characteristic signal strength value less than the second trigger threshold, it determines that a person has left the detection space.

[0106] The first trigger threshold value can be adjusted within a first threshold range. The second trigger threshold value can be adjusted within a second threshold range. The first threshold range and the second threshold range can be independent of each other or partially overlap.

[0107] In step S402, the terminal device dynamically corrects the detection threshold according to the adjustment mechanism mapped by the selected adjustment path, so that it conforms to the sensing characteristics defined by the selected path.

[0108] Specifically, after responding to a user-triggered adjustment request (e.g., clicking the sensitivity setting button), the terminal device presents adjustment path options with differentiated perception characteristics. Each adjustment path maps to a pre-set independent detection threshold adjustment mechanism, which is used to adjust the first trigger threshold value and / or the second trigger threshold value to achieve the perception characteristics under the corresponding adjustment path.

[0109] When the detection threshold includes both the first trigger threshold value for triggering the detection state and the second trigger threshold value for maintaining the detection state, the dynamic correction of the detection threshold includes correcting the first trigger threshold value and correcting the second trigger threshold value, wherein the adjustment mechanism used to correct these two trigger threshold values ​​is the same. In the following description, unless otherwise specified, the detection threshold can be understood as the first trigger threshold value, and the specific implementation method where the detection threshold is the second trigger threshold value can be understood by referring to this description.

[0110] Furthermore, the terminal device, based on the dynamic adjustment algorithm determined by the adjustment mechanism, transforms the abstract adjustment strategy into a specific threshold parameter adjustment scheme. While ensuring the core perception characteristics of the selected path, it achieves real-time matching of the detection threshold with the environmental state and usage scenario.

[0111] In step S403, the terminal device adaptively configures the sensitivity of the detection device based on the corrected detection threshold to optimize its response accuracy under the sensing characteristics corresponding to the selected adjustment path.

[0112] Specifically, the terminal device adaptively configures the sensitivity of the detection device based on a dynamically corrected detection threshold by sending the detection threshold. For example, the dynamically corrected detection threshold can be transmitted to the detection device in real time via Bluetooth direct connection.

[0113] The sensitivity of the detection device refers to its ability to respond to the amplitude of human body movements. The corrected detection threshold is a dynamically adjusted trigger threshold (either a first trigger threshold or a second trigger threshold). Its numerical characteristics directly determine the sensitivity of the detection device. Specifically, the lower the detection threshold, the higher the sensitivity, and the weaker the human body presence signal can be detected, but the risk of false alarms will also increase. The higher the detection threshold, the lower the sensitivity, and the stronger the anti-interference ability, but some small-amplitude human body presence signals may be missed.

[0114] The technical solution proposed in this disclosure achieves the transformation of detection threshold from static setting to intelligent dynamic adjustment through a three-layer mapping architecture of "adjustment path - sensing characteristics - threshold mechanism". This architecture establishes a precise mapping relationship between the adjustment path and sensing characteristics, enabling the overall optimization of the threshold system to be completed automatically with a single strategy selection, thereby improving the reliability and scene adaptability of the detection device under the expected sensing characteristics.

[0115] In some embodiments, the dynamic adjustment algorithm corresponding to the adjustment mechanism for adjusting the detection threshold includes an adjustment magnitude parameter. The adjustment magnitude parameter is a control variable in the dynamic correction process of the detection threshold, used to quantitatively characterize the degree of change of the detection threshold by different adjustment mechanisms. The difference in adjustment magnitude parameters between different adjustment mechanisms reflects the path-oriented optimization logic.

[0116] In one specific implementation, each adjustment mechanism corresponds to an independent adjustment magnitude parameter. The adjustment magnitude parameters differ between different adjustment mechanisms.

[0117] In practice, different adjustment mechanisms can apply the same adjustment strategy to the adjustment threshold through their own independent adjustment magnitude parameters, so that the dynamically corrected detection threshold reflects the perception characteristics expected by different adjustment paths.

[0118] The same adjustment strategy can be, for example, a positive offset calculation based on the intensity value of human feature signals. Specifically, in step S402, the detection threshold is dynamically corrected according to the adjustment mechanism mapped by the selected adjustment path, specifically including steps S4021 and S4022.

[0119] In step S4021, the terminal device acquires the intensity value of the human feature signal. This intensity value is obtained by the detection device through spatial detection and then transmitted, serving as a quantitative indicator characterizing the probability of a human presence within the detection space.

[0120] In step S4022, the terminal device positively offsets the intensity value based on the adjustment amplitude parameter corresponding to the selected adjustment path, and dynamically corrects the detection threshold so that the corrected detection threshold conforms to the sensing characteristics defined by the selected adjustment path.

[0121] Specifically, the dynamic correction detection threshold process is implemented as follows: The terminal device first obtains the intensity value of human feature signals in the current environment through the detection device. This intensity value is a dynamic quantitative indicator generated by the detection device through spatial detection (e.g., based on millimeter-wave radar, through periodic scanning (typical sampling period is 100ms-1s)) and signal processing (including but not limited to Doppler frequency shift analysis, micro-motion feature extraction, thermal radiation detection, etc.), which can objectively reflect the quantitative indicator of the presence of human bodies in each detection space.

[0122] After obtaining the intensity value, the terminal device will call the corresponding adjustment mechanism according to the adjustment path selected by the user. Specifically, the corresponding adjustment amplitude parameter will be applied to the obtained human feature signal intensity value, and a corrected detection threshold will be generated through positive offset mathematical operations (such as positive offset (i.e., adding the adjustment amplitude parameter to the human feature signal intensity value)).

[0123] The terminal device acquires the human feature signal intensity value in real time, which makes the dynamic correction mechanism provided in this embodiment of the present disclosure dually adaptive—it reflects changes in environmental background interference through real-time updates of the acquired human feature signal intensity value, and maintains the user-set perception characteristics through strategic configuration of the amplitude parameter adjustment, ultimately achieving a balance and optimization of the detection threshold in terms of environmental robustness and strategy consistency.

[0124] Of course, in other implementations, different adjustment mechanisms can apply different adjustment strategies to the adjustment threshold through their own independent adjustment magnitude parameters, so that the dynamically corrected detection threshold reflects the perceptual characteristics expected by different adjustment paths.

[0125] Specifically, in step S402, the detection threshold is dynamically corrected based on the adjustment mechanism mapped by the selected adjustment path. This includes the terminal device acquiring the intensity value of the human feature signal and, based on the sensing characteristics corresponding to the selected adjustment path, applying a positive or negative offset to the intensity value according to the corresponding adjustment amplitude parameter, dynamically correcting the detection threshold so that the corrected detection threshold conforms to the sensing characteristics defined by the selected adjustment path. For example, when the selected adjustment path indicates a sensitivity-priority response characteristic, an adjustment amplitude parameter is subtracted from the intensity value, and a negative offset is applied to dynamically correct the detection threshold and improve the response sensitivity of the detection device. When the selected adjustment path indicates a response characteristic prioritizing anti-accidental touch, another adjustment amplitude parameter is added to the intensity value, and a positive offset is applied to dynamically correct the detection threshold and reduce the false touch rate of the detection device.

[0126] In another specific implementation, all adjustment mechanisms share a common adjustment amplitude parameter; that is, the adjustment amplitude parameter is the same across different adjustment mechanisms. Furthermore, different adjustment mechanisms apply different adjustment strategies to the adjustment threshold based on the adjustment amplitude parameter, so that the dynamically corrected detection threshold reflects the sensing characteristics expected by different adjustment paths. For example, for the same adjustment amplitude parameter, when the selected adjustment path indicates a sensitivity-prioritized response characteristic, the adjustment amplitude parameter is subtracted from the intensity value, applying a negative offset to dynamically correct the detection threshold and improve the response sensitivity of the detection device. When the selected adjustment path indicates a response characteristic prioritizing accidental touch prevention, the adjustment amplitude parameter is added to the intensity value, applying a positive offset to dynamically correct the detection threshold and reduce the accidental touch rate of the detection device.

[0127] In some embodiments, the adjustment range parameter includes:

[0128] A preset offset. Then, based on the adjustment amplitude parameter corresponding to the selected adjustment path, a positive or negative offset is made from the intensity value. Specifically, this includes: determining the corresponding offset based on the selected adjustment path, and adding or subtracting the corresponding offset from the human feature signal intensity value to obtain the adjusted detection threshold; or,

[0129] The adjustment is based on a percentage of the intensity value of the human feature signal. Furthermore, based on the adjustment amplitude parameter corresponding to the selected adjustment path, the intensity value is positively or negatively offset. Specifically, this includes: determining the corresponding percentage adjustment based on the selected adjustment path, and adjusting the intensity value of the human feature signal positively or negatively according to the percentage adjustment to obtain the adjusted detection threshold.

[0130] Furthermore, the adjustment amplitude parameters corresponding to each adjustment mechanism are arranged according to a predetermined relationship, and the arrangement of the predetermined relationship makes the sensing characteristics of different adjustment paths in the detection space form a differentiated distribution.

[0131] In a specific example, the adjustment range parameter includes a preset offset, and the predetermined relationship can be an increasing relationship, such that the adjustment range of the detection threshold monotonically increases as the false trigger prevention level of the adjustment path increases. Alternatively, the predetermined relationship can be a decreasing relationship, such that the adjustment range of the detection threshold monotonically decreases as the detection sensitivity level of the adjustment path increases.

[0132] In further examples, such as Figure 5 As shown, there are three adjustment paths: the first path 501, the second path 502, and the third path 503. The offsets of the first path 501, the second path 502, and the third path 503 are distributed in descending order, and the offset difference between adjacent paths is 2 to 5. This allows these three adjustment paths to adapt to the differentiated distribution requirements of sensing characteristics that prioritize accidental touch prevention, compromise, and sensitivity and range.

[0133] To give a further example, such as Figure 5 As shown, the terminal device also displays prompt information 504 in the adjustment path selection interface. These prompts can guide users to do some preparatory work before adjusting the sensitivity, such as "Please ask people to leave the room" and "If there are interference sources that you want to block, such as air conditioners or fans, keep them on." Based on these preparatory work, the accuracy of sensitivity settings can be improved.

[0134] Based on this, if the offsets for positively adjusting the detection threshold corresponding to the first path 501, the second path 502, and the third path 503 are 10, 7, and 4 respectively, then the first path 501 can be selected when preventing accidental touches is prioritized. Under this path, the sensitivity near the interference source will be reduced as much as possible to avoid accidental touches. The second path 502 can be selected when there is a trade-off between sensitivity and preventing accidental touches. The third path 503 can be selected when sensitivity is prioritized. Under this path, the sensitivity will be guaranteed as much as possible.

[0135] In some embodiments, in step S4021, the terminal device acquires the human feature signal intensity value, specifically including: the terminal device acquires the human feature signal intensity value of each detection subspace in real time; wherein, the human feature signal intensity value of each detection subspace is sent by the detection device after periodically detecting the human feature signal intensity value of each detection subspace, and is used as a quantitative indicator to characterize the possibility of the presence of a human body in the detection subspace; each detection subspace is obtained by dividing the detection space of the detection device.

[0136] Specifically, the detection space can be understood as the complete and effective detection range of the detection device, representing the range composed of all unshielded detection subspaces. This range lies within the theoretically maximum signal coverage area of ​​the detection device, which is determined by the hardware performance of the device (such as transmission power, field of view, and detection distance). The detection subspace can be understood as a discretized analysis unit obtained by logically dividing the detection space. This division can be based on, but is not limited to, distance layering (e.g., near / far range), angular partitioning (e.g., 30° sector), or three-dimensional mesh partitioning (based on spatial coordinates). The detection subspace is a manageable subset of the detection space. Through this partitioning, the detection device and terminal equipment can achieve refined environmental perception processing, supporting regionally differentiated sensitivity configuration and interference management.

[0137] The human feature signal intensity value in the detection subspace is a localized, independent parameter, calculated by performing feature extraction (e.g., micro-motion energy integration, Doppler frequency shift analysis) and interference suppression (e.g., static clutter filtering) on ​​the human feature signal intensity values ​​within the detection subspace. The human feature signal intensity value in the detection subspace is used to locate human activity in specific layered segments, supporting dynamic adjustment of local detection thresholds. Figure 6 As shown in the example, the detection device can cover a maximum detection distance of 8 meters in general, and based on distance layering, the 8-meter detection space is divided into 32 detection subspaces with each layer segment being 0.25m.

[0138] exist Figure 6 Based on the example of detection space division shown, if all 32 detection subspaces are valid spaces (i.e., not shielded by the user), the detection device will independently analyze each detection subspace during the signal acquisition phase, simultaneously acquiring 32 independent human feature signal intensity values. The human feature signal intensity values ​​for these 32 detection subspaces will be acquired separately. Due to the dynamic changes in actual environmental interference (such as furniture reflections) in different detection subspaces, the final 32 human feature signal intensity values ​​are independent of each other. For example, they may exhibit a continuous gradient distribution (e.g., near-field values ​​are generally higher than far-field values), or they may show local abrupt changes (e.g., the 15th subspace is significantly higher than adjacent subspaces due to curtain movement).

[0139] In step S4022, based on the adjustment amplitude parameter corresponding to the selected adjustment path, the detection threshold is dynamically corrected by shifting positively on the intensity value, specifically including S40221 and S40222.

[0140] In step S40221, the terminal device 600 performs an independent positive offset operation on the human feature signal intensity value of each detection subspace based on the real-time acquired human feature signal intensity value of each detection subspace and the adjustment amplitude parameter corresponding to the selected adjustment path, thereby generating the detection sub-threshold of each detection subspace.

[0141] At step S40222, the terminal device 600 sends threshold configuration data including the detection sub-thresholds of each detection subspace to the detection device 100, so that the detection device 100 resets the detection sub-thresholds of each detection subspace to adjust the detection sensitivity.

[0142] Specifically, when the terminal device performs dynamic correction of the detection threshold, it performs dynamic correction of the detection sub-thresholds of each detection subspace.

[0143] The detection sub-threshold is a personalized trigger threshold dynamically calculated for each independent detection subspace. Specifically, it is a quantitative judgment standard formed by the detection device based on the human feature signal intensity value of the corresponding detection subspace, superimposed with the predefined adjustment amplitude parameter of the selected adjustment path. Each detection sub-threshold has spatial specificity.

[0144] In a specific application example, such as Figure 7 As shown, if the user selects "First Path 501", the detection sub-threshold corresponding to each detection subspace is obtained by increasing the current human feature signal intensity value by 10 units. The maximum value of the human feature signal intensity is 255 units, representing the maximum signal intensity of the corresponding space and serving as a quantification indicator.

[0145] It's worth noting that the numbers "255" and "10" are unit values ​​used to represent signal strength; they themselves do not have explicit physical units. Here, 255, as the maximum value of the human body characteristic signal strength, is a quantized representation, indicating a maximum quantization level of signal strength, serving only as a relative reference point. The 10 units indicate that in "First Path 501" mode, to improve accidental touch protection, the original human body characteristic signal strength value is increased by 10 quantization units. Although these quantization units do not have explicit physical units, they can still be understood as increments in signal strength.

[0146] Of course, in some embodiments, the adjustment amplitude parameters of different detection subspaces can be configured differently according to their spatial location characteristics, so as to ensure that detection subspaces at different distances can obtain differentiated threshold configurations according to their signal attenuation characteristics.

[0147] Furthermore, it is worth mentioning that for each detection subspace, the following features are also provided:

[0148] The first sub-trigger threshold value corresponding to its trigger detection state is used to determine the trigger threshold value of the trigger detection state of the detection subspace. In the trigger detection state, when the detection device identifies that the intensity value of the human feature signal in the corresponding detection subspace is greater than or equal to its first sub-trigger threshold value, it determines that someone has entered the detection subspace; and,

[0149] The second sub-trigger threshold value corresponding to its maintaining detection state is used to determine the trigger threshold value for maintaining the detection state of the detection subspace. When the detection device identifies that the human feature signal intensity value of the corresponding detection subspace is less than its second sub-trigger threshold value in the maintaining detection state, it determines that the detection subspace has entered an unmanned state.

[0150] The first sub-trigger threshold value can be adjusted within the range of the first sub-threshold. The second sub-trigger threshold value can be adjusted within the range of the second sub-threshold. The ranges of the first and second sub-thresholds can be independent of each other or partially overlap.

[0151] When the detection sub-threshold simultaneously includes both the first sub-trigger threshold value for triggering the detection state and the second sub-trigger threshold value for maintaining the detection state, calculating the corresponding detection sub-threshold includes calculating the first sub-trigger threshold value based on the human feature signal intensity value, and also calculating the second sub-trigger threshold value based on the human feature signal intensity value. The adjustment mechanism used to correct these two trigger threshold values ​​is the same. In the following description, unless otherwise specified, the detection sub-threshold can be understood as the first sub-trigger threshold value, and the specific implementation method where the detection sub-threshold is the second sub-trigger threshold value can be understood by referring to this description.

[0152] In some embodiments, the method 40 further includes:

[0153] An independent reference sub-detection threshold is configured for each detection subspace. When performing an independent positive offset operation on the environmental energy value of each detection subspace, if the calculated detection sub-threshold is less than the reference sub-detection threshold, then the reference sub-detection threshold is used as the detection sub-threshold.

[0154] Specifically, each detection subspace is assigned a baseline sub-detection threshold (which can be a pre-set fixed baseline) during the initialization phase. This baseline sub-detection threshold is a pre-set safety threshold based on the physical characteristics of the detection subspace (such as distance and typical interference levels). When performing dynamic threshold adjustment, a temporary threshold of "current human feature signal strength value + strategy offset" is first calculated. If this value is lower than the corresponding baseline sub-detection threshold, the baseline sub-detection threshold is automatically switched to as the final detection sub-threshold; otherwise, the temporary threshold is used as the final detection sub-threshold. This dual-threshold mechanism ensures both strategy flexibility and maintains the reliability of sensitivity settings.

[0155] In some embodiments, the method 40 further includes:

[0156] Establish a reference threshold sequence associated with predefined sensitivity levels for each detection subspace;

[0157] The detection sub-threshold of each detection subspace is compared with the reference threshold in the corresponding reference threshold sequence;

[0158] The interference level of each detection subspace is determined based on the comparison results.

[0159] Specifically, the predefined sensitivity levels are several sensitivity levels preset by the detection device (such as high, medium, and low sensitivity). Each sensitivity level sets an independent reference threshold for each detection subspace. Different sensitivity levels have different thresholds to accommodate the detection needs of different sensitivity levels (e.g., a lower reference threshold is set for high sensitivity levels to improve response speed, while a higher detection threshold is set for low sensitivity levels to reduce false alarms). The sensitivity level determines which set of reference thresholds is currently used. For example, if the "high sensitivity" level is selected, all detection subspaces will use the reference threshold corresponding to that high sensitivity level. The reference threshold includes both the reference threshold for triggering the detection state and the reference threshold for maintaining the detection state. These two thresholds can be different; that is, the reference threshold can be used for the first sub-trigger threshold, the second sub-trigger threshold, or both.

[0160] In addition, some solutions include a custom sensitivity setting in the predefined sensitivity settings. When switching to the custom setting, the detection device will automatically restore the previously saved user-defined detection threshold, that is, automatically restore the previously saved detection sub-thresholds.

[0161] Furthermore, this disclosure provides a possible implementation method for users to set detection thresholds. Specifically, in response to a user-defined threshold adjustment trigger command, the terminal device enters the corresponding custom threshold setting interface and displays the human feature signal intensity value and the current detection sub-threshold for each detection subspace, allowing the user to more clearly observe the specific situation of each detection subspace. In response to the user's selection and adjustment of the current detection sub-threshold for a certain detection subspace, the terminal device adjusts the corresponding detection sub-threshold and updates the adjusted detection sub-threshold to the detection device in real time.

[0162] For specific examples, such as Figure 8As shown, the custom threshold setting interface displays the real-time human feature signal intensity value for each detection subspace, as well as the current detection sub-threshold for each subspace. For example, the current intensity value for the 0.25m to 0.5m detection subspace is 45, and the detection sub-threshold is 60. After the user selects the slider control for the 0.25m to 0.5m detection subspace, they can drag the slider control up and down to adjust the detection sub-threshold for that subspace. For example, if the user slides the slider control upwards to adjust the detection sub-threshold to 70 and then stops, the terminal device will send the adjusted detection sub-threshold of 70 to the detection device, which will then adjust the threshold corresponding to the 0.25m to 0.5m detection subspace from 60 to 70 accordingly. If this detection sub-threshold is the threshold for triggering the detection state, then in subsequent use, during the process of triggering person detection, if the intensity value of the 0.25m to 0.5m detection subspace exceeds 70, it is considered that there is someone in this detection subspace; otherwise, it is considered that there is no one. Similarly, it can also be adjusted individually based on the threshold row for maintaining the detection state.

[0163] Furthermore, the reference threshold sequence is composed of a high sensitivity level reference threshold, a medium sensitivity level reference threshold, and a low sensitivity level reference threshold arranged in sequence, wherein each reference threshold is inversely proportional to the detection sensitivity of the corresponding sensitivity level.

[0164] Specifically, the reference threshold sequence can be understood as a list of all reference thresholds for a detection subspace at different sensitivity levels, arranged in order of sensitivity level. For example, in the reference threshold sequences established for each detection subspace and associated with a predefined sensitivity level, each reference threshold is inversely proportional to the detection sensitivity of the corresponding sensitivity level (the reference threshold for low sensitivity level is greater than that for medium sensitivity level, and the reference threshold for medium sensitivity level is greater than that for high sensitivity level). For example, the reference threshold sequence for the detection subspace from 0 to 0.25m can be: [high sensitivity: 10, medium sensitivity: 20, low sensitivity: 30]; the reference threshold sequence for the detection subspace from 0.25 to 0.5m can be: [high sensitivity: 15, medium sensitivity: 25, low sensitivity: 35].

[0165] Furthermore, the interference level of the detection subspace is determined based on the comparison results, specifically including: determining the interference level of the detection subspace according to the distribution position of the detection sub-threshold in the reference threshold sequence associated with the sensitivity level.

[0166] Specifically, when comparing the detection sub-threshold of each detection subspace with each reference threshold in the corresponding reference threshold sequence, the dynamically corrected detection sub-threshold is compared with multiple reference thresholds corresponding to the reference threshold sequence of the corresponding detection subspace. Based on the distribution position of the detection sub-threshold in the reference threshold sequence associated with the sensitivity level, the interference level of the detection subspace is determined.

[0167] The distribution position refers to the comparison between the detection sub-threshold and the corresponding reference threshold in the reference threshold sequence.

[0168] In a specific example, if the detection sub-threshold reaches or exceeds the low sensitivity level reference threshold, it is determined to be strong interference. If the detection sub-threshold reaches or exceeds the medium sensitivity level reference threshold but does not reach the low sensitivity level reference threshold, it is determined to be moderate interference. If the detection sub-threshold does not reach the medium sensitivity level reference threshold, it is determined to be no interference.

[0169] In some embodiments, after acquiring the human feature signal intensity values ​​of each detection subspace in real time, the method further includes: generating interference identification elements that correspond one-to-one with each detection subspace in real time; and dynamically configuring the color attributes of the interference identification elements of each detection subspace based on a preset interference level-color mapping relationship.

[0170] Specifically, interference identification elements can be understood as graphical components used to visually present the interference status of each detection subspace. Each interference identification element is bound to a specific subspace and reflects the interference level of that detection subspace in real time through visual display attributes (such as color, shape, and dynamic effects), so as to transform abstract interference data into intuitive interface feedback and help users quickly identify interference situations.

[0171] In this embodiment of the disclosure, there is a preset interference level-color mapping relationship. This relationship can be understood as a preset rule for the correspondence between interference level and color. The terminal device periodically reads the human feature signal intensity value of each detection subspace through the detection device, calculates the corresponding detection sub-threshold, compares it with the corresponding reference threshold sequence, divides the interference level (strong / moderate / none), and assigns the corresponding color attribute to the corresponding interference identification element according to the "interference level-color" mapping relationship.

[0172] In a specific example, the interference level-color mapping relationship satisfies the following: the color saturation of the interference marker element is positively correlated with the interference level of the corresponding detection subspace. For example, strong interference corresponds to red, moderate interference corresponds to yellow, and no interference corresponds to green. The terminal device updates the interference marker elements of the corresponding detection subspace in real time to ensure that the visual feedback is synchronized with the physical spatial interference distribution.

[0173] In some embodiments, the method 40 further includes: receiving a detection subspace masking instruction input by a user; the masking instruction is used to perform a masking operation on one or more detection subspaces; and determining a set of masked detection subspaces.

[0174] The display attributes of interference identifier elements in each detection subspace are dynamically configured, including: stopping the updating of interference level information of the blocked detection subspace; and / or setting the display attributes of the interference identifier elements corresponding to the blocked detection subspace to an inactive state.

[0175] Specifically, users trigger a blocking command by selecting or deselecting one or more detection subspaces to manually block specific detection subspaces, thereby achieving interference source blocking or setting an effective detection space. When a detection subspace is selected, it is included in the detection space; when it is deselected, it is blocked and temporarily excluded from the effective detection range of the detection space. Blocked detection subspaces are marked as temporarily disabled, preventing them from participating in interference statistics and human presence determination. When determining the interference level of a detection space, data from the blocked detection subspaces are excluded from the statistics. The interference level information corresponding to the blocked detection subspace stops updating, and the display attributes of its corresponding interference representation elements are set to an inactive state (e.g., grayed out). Figure 9b As shown, the detection subspace within the range of 4m to 8m in the current detection space is shielded.

[0176] Furthermore, the shielding command can also be generated based on the user's setting of the maximum detection distance, meaning the user can arbitrarily adjust the maximum detection distance within the coverage area of ​​the detection device (e.g., 0–8 m). Consequently, the detection subspace corresponding to the area outside the maximum detection distance can be understood as a set of shielded detection subspaces.

[0177] Furthermore, users can selectively block one or more detection subspaces within the detection space determined by the maximum detection distance, thus selectively blocking one or more detection subspaces within the detection space, creating an alternating pattern of effective and blocked detection subspaces. For example, ... Figure 9d As shown, the user set the maximum detection distance to 6m and masked three detection subspaces: 2m-2.5m and 3.25m-3.5m. The result is as follows: Figure 9d The pattern shown.

[0178] Furthermore, it is worth mentioning that if the blocking instruction is generated based on the user's setting of the maximum detection distance, then after obtaining the blocking instruction, method 40 further includes:

[0179] Determine whether the maximum detection distance indicated by the shielding command matches the current working mode;

[0180] If the current working mode is fusion detection mode, the matching result is determined based on whether the maximum detection distance exceeds the constraint range; if it exceeds, it is considered a mismatch; otherwise, it is considered a match. The constraint range is determined based on the theoretical detection range of the infrared pyroelectric module, which in turn is determined based on the performance and model of the specific hardware used in the infrared pyroelectric module.

[0181] Furthermore, if a mismatch is deemed to occur, a prompt message will be displayed to guide the user to switch operating modes. For example, if the detection range of the infrared pyroelectric module is 3m, and the user sets the maximum detection distance to 3.5m, the following message will be displayed: Figure 9a The pop-up notification shown.

[0182] Furthermore, in some embodiments, the change in operating mode only affects the trigger detection state of the detection device. That is, the operating mode of the detection device during the trigger detection phase can be changed according to user settings. If the operating mode is a fusion detection mode, then in the trigger detection state, the detection results from both the infrared pyroelectric module and the radar module jointly determine whether someone has entered the detection space. If the operating mode is a pure radar mode, then in the trigger detection state, only the radar module's detection results determine whether someone has entered the detection space. Regardless of the operating mode setting for the trigger detection state, the detection device uses a pure radar mode during the maintenance detection state, meaning that during the maintenance detection phase, only the radar module's detection results determine whether a person has left the detection space.

[0183] Furthermore, the method also includes: determining whether to switch the operating mode based on the user's response to the prompt information; wherein, if the user chooses to remain in the fusion detection mode, the operating mode of the detection device is not switched, but the detection space of the detection device in the triggered detection phase is still limited by the theoretical range of the infrared pyroelectric module. If the user chooses to switch to pure radar mode, an operating mode switching command is issued to the detection device to instruct the detection device to switch to pure radar mode, and then the detection device will determine the range of the detection space based on the maximum detection distance set by the user in the triggered detection state.

[0184] For specific examples, such as Figure 10 As shown, when the detection subspace of 4m to 8m is blocked, the corresponding interference marker elements will be grayed out and enter an inactive state.

[0185] In some embodiments, after determining the interference level of each detection subspace, the method further includes:

[0186] The terminal device calculates statistical characteristics of interference status based on the interference level distribution of each detection subspace. Specifically, it counts the number of detection subspaces at a predetermined interference level (e.g., moderate and strong interference) and calculates their proportion of all detection subspaces. When determining the overall interference level of the detection space, data from the shielded detection subspaces are excluded from the statistics.

[0187] The terminal device determines the overall interference level of the detection space based on the matching relationship between the statistical features and the preset level classification rules. Specifically: when the proportion of strongly interfering subspaces exceeds a first preset proportion, or when the combined proportion of moderate and strongly interfering subspaces exceeds a second preset proportion, the overall interference is determined to be strong; when the combined proportion of moderate and strongly interfering subspaces is lower than a third preset proportion, the overall interference is determined to be minor; when all detection subspaces (unshielded detection subspaces) are in an interference-free state, the overall interference is determined to be non-interfering; all other cases are determined to have relatively strong overall interference.

[0188] Subsequently, the terminal device generates a visual prompt message corresponding to the overall interference level, wherein different interference levels are associated with different visual presentation schemes.

[0189] In some embodiments, the method 40 further includes:

[0190] In response to a user instruction, a first graphic corresponding to the coverage area of ​​the detection device is presented; this coverage area is the theoretical maximum signal coverage area of ​​the detection device.

[0191] Receive a proximity range adjustment command applied by the user; the proximity range adjustment command is used to determine a spatial range extending outward from the detection device, defined as the proximity spatial range;

[0192] Based on this range adjustment command, the area where the near-space range is located changes dynamically in real time within the first graphic range.

[0193] Furthermore, the method 40 also includes:

[0194] In the first graphic, the range of the set of shielded detection subspaces is set as an inactive range. When the area of ​​the near space range indicated by the range adjustment command enters the inactive range, the dynamic change is stopped, so that the graphic range covered by the detection space can only be adjusted within the range of the detection space.

[0195] In specific examples, such as Figure 3 In the actual application scenario shown, the detection device is installed in a top-mounted manner, thus its downward coverage area presents a cone-shaped region. For example... Figure 9cAs shown, in response to a user command, the first graphic corresponding to the coverage area of ​​the detection device can be, for example, a sector (this sector is a planar simulation of the actual coverage area, intended to allow the user to intuitively observe the range changes in the near space). The user can set the maximum detection distance of the detection device, and the space outside the maximum detection distance can be understood as a set of shielded detection subspaces. Figure 9c As shown, the detection device can theoretically cover a maximum distance of 8m. If the user sets the maximum detection distance to 4m, then the range from 0m to 4m is the effective range (i.e., the detection space), and the range from 4m to 8m is the shielded range (i.e., the inactive range). Figure 9c The diagram shows the interface changes as the user sets the near-field space (near-field interval) to 1.5m, 2.5m, and 5.25m respectively. As the range of the near-field space gradually increases, the corresponding sector also gradually increases within the detection space determined by the maximum detection distance, until it covers the entire detection space (0-4m). At this point, the near-field space and the detection space coincide. If the range of the near-field space is further increased, for example to 5.25m, the sector will not continue to increase, but a pop-up window will prompt the user, such as "The near-field interval is not allowed to exceed the farthest effective distance," to prevent the user from continuing to adjust.

[0196] Furthermore, method 40 further includes: based on the user-applied proximity range adjustment command, sending the determined proximity space range to the detection device in real time via a proximity space configuration command, so that the detection device can set the proximity space range and report a proximity space occupancy event when someone is triggered within the proximity space range. This proximity space occupancy event triggers the cloud to query a pre-set control rule library based on the received proximity space occupancy event and control the execution of the control result defined by the matching control rule. The control rule library pre-stores at least one control rule, which defines a mapping relationship between a proximity space occupancy event and at least one executable function of at least one controlled device connected to the cloud.

[0197] Furthermore, if there are one or more shielded detection subspaces within the detection space determined by the maximum detection distance, then these shielded detection subspaces will also be shielded in the near-field space, meaning that a near-field space "person" event will not be triggered within these shielded detection subspaces.

[0198] Based on the above method 40, an embodiment of this disclosure also provides a terminal device, which can be applied to, for example... Figure 1 The human body detection system shown, or the terminal device used in it.

[0199] like Figure 11 As shown, the terminal device includes a response receiving unit, a dynamic correction unit, and a data sending unit.

[0200] The response receiving unit is configured to output at least two adjustment paths with different sensing characteristics in response to an adjustment trigger request; wherein each adjustment path is mapped to an independent detection threshold adjustment mechanism.

[0201] The dynamic correction unit is used to dynamically correct the detection threshold according to the adjustment mechanism mapped by the selected adjustment path, so that it conforms to the perception characteristics defined by the selected path; the detection threshold is used to determine the trigger threshold value of the human presence state in the detection space.

[0202] The data processing unit is used to adaptively configure the sensitivity of the detection device based on the corrected detection threshold, so as to optimize its response accuracy under the sensing characteristics corresponding to the selected adjustment path.

[0203] In some embodiments, each adjustment mechanism corresponds to an independent adjustment magnitude parameter; the adjustment magnitude parameters differ between different adjustment mechanisms.

[0204] The dynamic correction unit specifically includes:

[0205] An intensity value acquisition unit is used to acquire the intensity value of human characteristic signals; the intensity value is obtained by the detection device through spatial detection and then sent, and is used as a quantitative indicator to characterize the possibility of the presence of a human body in the detection space.

[0206] The correction unit is used to positively offset the intensity value based on the adjustment amplitude parameter corresponding to the selected adjustment path, and dynamically correct the detection threshold so that the corrected detection threshold conforms to the sensing characteristics defined by the selected adjustment path.

[0207] In some embodiments, the adjustment amplitude parameter includes a preset fixed offset or a percentage adjustment based on the intensity value of human feature signals.

[0208] In some embodiments, the adjustment amplitude parameters corresponding to each adjustment mechanism are arranged according to a predetermined relationship, and the arrangement of the predetermined relationship makes the sensing characteristics of different adjustment paths in the detection space form a differentiated distribution.

[0209] In some embodiments, the intensity value acquisition unit acquires the intensity value of the human feature signal, specifically for:

[0210] The human feature signal intensity values ​​of each detection subspace are acquired in real time. The human feature signal intensity values ​​of each detection subspace are periodically detected by the detection device and then sent. They are used as a quantitative indicator to characterize the probability of the presence of a human body in the detection subspace. Each detection subspace is obtained by dividing the detection space of the detection device.

[0211] The correction unit, based on the adjustment amplitude parameter corresponding to the selected adjustment path, positively offsets the intensity value to dynamically correct the detection threshold, specifically for:

[0212] Based on the real-time acquired human feature signal intensity values ​​of each detection subspace, and combined with the adjustment amplitude parameters corresponding to the selected adjustment path, an independent positive offset operation is performed on the human feature signal intensity values ​​of each detection subspace to generate the detection sub-threshold of each detection subspace.

[0213] Threshold configuration data, including the detection sub-thresholds of each detection subspace, is sent to the detection device, so that the detection device resets the detection sub-thresholds of each detection subspace to adjust the detection sensitivity.

[0214] In some embodiments, the data processing unit is further configured to establish a reference threshold sequence associated with a predefined sensitivity level for each detection subspace;

[0215] The detection sub-threshold of each detection subspace is compared with the reference threshold in the corresponding reference threshold sequence;

[0216] The interference level of each detection subspace is determined based on the comparison results.

[0217] In some embodiments, the data processing unit determines the interference level of the detection subspace based on the comparison results, specifically for:

[0218] The interference level of the detection subspace is determined based on the distribution position of the detection subthreshold in the reference threshold sequence associated with the sensitivity level.

[0219] In some embodiments, the reference threshold sequence is composed of a high sensitivity level reference threshold, a medium sensitivity level reference threshold, and a low sensitivity level reference threshold arranged in sequence, wherein each reference threshold is inversely proportional to the detection sensitivity of the corresponding sensitivity level.

[0220] The data processing unit determines the interference level of the detection subspace based on the distribution position of the detection sub-threshold in the reference threshold sequence associated with the sensitivity level, specifically for:

[0221] If the detection sub-threshold reaches or exceeds the low sensitivity level reference threshold, it is judged as strong interference;

[0222] If the detection sub-threshold reaches or exceeds the reference threshold for the medium sensitivity level but does not reach the reference threshold for the low sensitivity level, it is judged as moderate interference;

[0223] If the detection sub-threshold does not reach the reference threshold for the medium sensitivity level, it is determined to be without interference.

[0224] In some embodiments, after the correction unit acquires the human feature signal intensity values ​​of each detection subspace in real time, it is further used for:

[0225] In real time, interference identification elements are generated that correspond one-to-one with each of the detection subspaces;

[0226] Based on the preset interference level-color mapping relationship, the color attributes of the interference identification elements in each detection subspace are dynamically configured.

[0227] In some embodiments, the interference level-color mapping relationship satisfies the following: the color saturation of the interference identifier element is positively correlated with the interference level of the corresponding detection subspace.

[0228] In some embodiments, the data processing unit is further configured to:

[0229] Receive a user-inputted detection subspace masking command; the masking command is used to mask one or more detection subspaces.

[0230] Determine the set of masked detection subspaces;

[0231] Dynamically configure the display attributes of interference flag elements in each detection subspace, including:

[0232] Stop updating the interference level information for the blocked detection subspace; and / or,

[0233] Set the display attribute of the interference identifier element corresponding to the blocked detection subspace to an inactive state.

[0234] Based on the above method 40, an embodiment of this disclosure also provides a human body detection processing method, applied to a detection device. For example... Figure 12 As shown, method 120 includes steps S1200 to S1201.

[0235] In step S1200, the detection device receives a corrected detection threshold from the terminal device. The detection threshold is used to determine the trigger threshold value for the presence of a human body in the detection space. The corrected detection threshold is obtained by the terminal device dynamically correcting the current detection threshold according to the adjustment mechanism mapped by the selected adjustment path. The adjustment path is at least two adjustment paths with different sensing characteristics output by the terminal device in response to the adjustment trigger request. Each adjustment path is mapped to an independent detection threshold adjustment mechanism.

[0236] In step S1201, the detection device adaptively configures the sensitivity based on the corrected detection threshold to optimize the response accuracy under the sensing characteristics corresponding to the selected adjustment path.

[0237] In some embodiments, each adjustment mechanism corresponds to an independent adjustment magnitude parameter; the adjustment magnitude parameters differ between different adjustment mechanisms.

[0238] The terminal device dynamically corrects the current detection threshold based on the adjustment mechanism mapped by the selected adjustment path, including:

[0239] The terminal device acquires the intensity value of human feature signals; the intensity value is obtained by the detection device through spatial detection and then sent, and is used as a quantitative indicator to characterize the possibility of the presence of a human body in the detection space;

[0240] Based on the adjustment amplitude parameter corresponding to the selected adjustment path, the terminal device shifts positively from the intensity value and dynamically corrects the detection threshold so that the corrected detection threshold conforms to the sensing characteristics defined by the selected adjustment path.

[0241] In some embodiments, the adjustment amplitude parameter includes a preset fixed offset or a percentage adjustment based on the intensity value of human feature signals.

[0242] In some embodiments, the adjustment amplitude parameters corresponding to each adjustment mechanism are arranged according to a predetermined relationship, and the arrangement of the predetermined relationship makes the sensing characteristics of different adjustment paths in the detection space form a differentiated distribution.

[0243] In some embodiments, the terminal device acquires human feature signal intensity values, including:

[0244] The human feature signal intensity values ​​of each detection subspace are acquired in real time. The human feature signal intensity values ​​of each detection subspace are periodically detected by the detection device and then sent. They are used as a quantitative indicator to characterize the probability of the presence of a human body in the detection subspace. Each detection subspace is obtained by dividing the detection space of the detection device.

[0245] Based on the adjustment amplitude parameter corresponding to the selected adjustment path, the detection threshold is dynamically corrected by positively shifting from the intensity value, including:

[0246] Based on the real-time acquired human feature signal intensity values ​​of each detection subspace, and combined with the adjustment amplitude parameters corresponding to the selected adjustment path, an independent positive offset operation is performed on the human feature signal intensity values ​​of each detection subspace to generate the detection sub-threshold of each detection subspace.

[0247] Threshold configuration data, including the detection sub-thresholds of each detection subspace, is sent to the detection device, so that the detection device resets the detection sub-thresholds of each detection subspace to adjust the detection sensitivity.

[0248] In some embodiments, the method further includes:

[0249] Obtain a space selection instruction; the space selection instruction is generated and sent by the terminal device after receiving the detection subspace blocking instruction input by the user and determining the set of detection subspaces to be blocked; the blocking instruction is used to block one or more detection subspaces; the space selection instruction carries the set of detection subspaces to be blocked;

[0250] According to the instructions of the space selection command, the corresponding detection subspace is masked.

[0251] The unmasked detection subspace is listed as the valid space, and in the subsequent detection process, only the detection subspaces listed as valid spaces are detected.

[0252] Based on the above method 120, one embodiment of this disclosure provides a detection device, such as... Figure 13 As shown, the detection device includes a data receiving unit and a sensitivity adjustment unit.

[0253] The data receiving unit is used to receive the corrected detection threshold sent by the terminal device. The detection threshold is used to determine the trigger threshold value for the presence of a human body in the detection space. The corrected detection threshold is obtained by the terminal device dynamically correcting the current detection threshold according to the adjustment mechanism mapped by the selected adjustment path. The adjustment path is at least two adjustment paths with different sensing characteristics output by the terminal device in response to the adjustment trigger request. Each adjustment path is mapped to an independent detection threshold adjustment mechanism.

[0254] The sensitivity adjustment unit is used to adaptively configure the sensitivity based on the corrected detection threshold in order to optimize the response accuracy under the sensing characteristics corresponding to the selected adjustment path.

[0255] In some embodiments, such as Figure 14 As shown, the detection device also includes an instruction acquisition unit and a shielding unit.

[0256] The instruction acquisition unit is used to acquire a space selection instruction; the space selection instruction is generated and sent by the terminal device after receiving the detection subspace blocking instruction input by the user and determining the set of detection subspaces to be blocked; the blocking instruction is used to block one or more detection subspaces; the space selection instruction carries the set of detection subspaces to be blocked.

[0257] The shielding part is used to perform a shielding operation on the corresponding detection subspace according to the instruction of the space selection command.

[0258] The unmasked detection subspace is listed as the valid space, and in the subsequent detection process, only the detection subspaces listed as valid spaces are detected.

[0259] Furthermore, in practical application scenarios, various electromagnetic interferences (such as Wi-Fi signals and radiation from household appliances) and dynamic environmental noises (such as swaying curtains and pet activities) cause the signals collected by the detection device to often contain a large amount of noise and interference, leading to serious false alarms and severely affecting reliability and practicality.

[0260] Especially in scenarios involving multiple spatial divisions, existing technologies typically employ a simple threshold-based judgment logic: if the signal strength value of human characteristics (such as radar reflection energy) in a certain space exceeds the corresponding threshold, it is determined that there is someone in that space. However, due to the inherent characteristics of radar detection (such as signal scattering and multipath effects), when there is actually someone in a space, the signal strength value of its adjacent spaces may also increase abnormally due to interference, leading to false triggering. This "signal leakage" problem seriously reduces the reliability of the detection device.

[0261] Based on this, one embodiment of the present disclosure provides a human body detection processing method applied to a detection device 100. This method introduces a stationary condition screening mechanism, which significantly improves the accuracy of the detection device 100 in identifying spaces where people are present.

[0262] like Figure 15 The diagram shown is a flowchart illustrating the method provided in an embodiment of this disclosure. It can be seen that the method 150 includes at least steps S150 to S152.

[0263] In step S150, the detection device periodically detects the intensity value of human feature signals in each detection subspace. The intensity value is obtained through spatial detection and is used as a quantitative indicator to characterize the possibility of the presence of a human body in the detection subspace. Each detection subspace is obtained by dividing the detection space of the detection device.

[0264] Specifically, the detection device sequentially scans the regions corresponding to each divided detection subspace according to a preset time interval (this time interval is set to 20ms to 1s, for example, 50ms), and calculates the human feature signal intensity value corresponding to each detection subspace. A detailed explanation of the human feature signal intensity value can be found in the description of the above embodiments, and will not be repeated here.

[0265] In a specific example, the quantitative indicators include physical quantities that reflect the presence of a human body within the detection subspace, obtained through active detection methods; the active detection methods include beam transmission and reception methods (e.g., radar detection waves).

[0266] In step S151, the detection device marks the detection subspaces that meet the stationary point condition and whose intensity values ​​exceed the corresponding detection sub-threshold as stationary point subspaces; the stationary point condition refers to the fact that the intensity value of a certain detection subspace satisfies a preset peak relationship condition relative to the intensity values ​​of adjacent subspaces.

[0267] Specifically, the stationary condition can be understood as the human feature signal intensity value of a certain detection subspace must meet certain peak relationship conditions, that is, the signal intensity of the detection subspace exhibits a "convex" feature in the spatial dimension. Furthermore, if the human feature signal intensity value of a certain detection subspace meets certain peak relationship conditions, but the detection subspace is a shielded detection subspace, then it will not be necessary to perform subsequent stationary conditions and whether there is a person.

[0268] In some embodiments, the peak relationship condition includes that the intensity value of a certain detection subspace is strictly greater than the intensity value of the previous detection subspace and not less than the intensity value of the next detection subspace.

[0269] The peak relationship conditions, expressed by a formula, specifically include:

[0270] If the i-th detection subspace a(i) satisfies the formula: T a(i-1) <T a(i) ≤T a(i+1) If , then the detection subspace a(i) satisfies the peak relation condition. Where i∈[1,S], S represents the total number of detection subspaces in the detection space; T a(i) T represents the intensity value of the human feature signal in the i-th detection subspace. a(i-1) T represents the human feature signal intensity value of the (i-1)th detection subspace a(i-1). a(i+1) This represents the intensity value of the human feature signal in the (i+1)th detection subspace a(i+1).

[0271] Specifically, the peak relationship condition is valid if it meets at least one of the following formula conditions:

[0272] T a(i-1) <T a(i) <T a(i+1) For example, if the intensity values ​​of the 2nd, 3rd, and 4th detection subspaces are 40, 60, and 50 respectively, then the 3rd detection subspace meets the stationary point condition.

[0273] T a(i-1) <T a(i) =T a(i+1) For example, if the intensity values ​​of the 2nd, 3rd, and 4th detection subspaces are 50, 60, and 60 respectively, then the 3rd detection subspace meets the stationary point condition.

[0274] T a(i-1) <T a(i) For example, if the intensity values ​​of the 2nd, 3rd, and 4th detection subspaces are 30, 40, and 50 respectively, then the 4th detection subspace meets the stationary point condition.

[0275] T a(i) =T a(i+1)For example, if the intensity values ​​of the 2nd, 3rd, and 4th detection subspaces are 40, 40, and 40 respectively, then the 2nd detection subspace meets the stationary point condition.

[0276] Furthermore, if T a(i) ≥σ (i) Then the detection subspace T is determined. a(i) Let σ be the stationary subspace; where σ (i) For T a(i) The corresponding detection sub-threshold. The process of obtaining the detection sub-threshold can be understood by referring to the description in the above embodiments, and will not be repeated here.

[0277] In this embodiment of the disclosure, a detection subspace is marked as a stationary subspace when it simultaneously meets the following two conditions:

[0278] The signal strength exceeds the detection sub-threshold of this detection subspace;

[0279] The conditions for stationing are met.

[0280] The stationary subspace serves as a candidate target space, entering the subsequent trigger detection space to determine whether there are people, in order to avoid false alarms caused by relying solely on threshold detection (such as false intensity signals caused by environmental noise or interference from adjacent spaces).

[0281] In step S152, the detection device determines whether to trigger the determination that someone is in the detection space based on the stationary point subspace.

[0282] Furthermore, the solution provided in this disclosure effectively filters false alarms caused by environmental noise, multipath effects, etc. through dual screening of "peak value + threshold". It introduces the comparison of intensity value signals of adjacent detection subspaces, which is more in line with the signal distribution characteristics of real human targets (usually localized). It introduces a stationary condition screening mechanism, optimizes the triggering logic of the detection device, and significantly improves the accuracy of the detection device in identifying spaces where people are present.

[0283] In some embodiments, in step S152, the detection device 100 determines whether a person detection is triggered based on the stationary subspace, specifically including:

[0284] The detection device 100 determines whether a manned detection is triggered based on the spatiotemporal distribution characteristics of the stationary point subspace during continuous detection, combined with the set anti-interference level judgment conditions; wherein:

[0285] Analyze the frequency of stationary point subspace occurrences in continuous detection over time; and / or,

[0286] In terms of spatial dimension, the positional movement of stationary point subspaces during adjacent detection cycles is analyzed.

[0287] Specifically, the frequency of stationary point subspace occurrences during continuous detection can be analyzed solely in terms of time dimension, and combined with the set anti-interference level judgment conditions, it can be determined whether a human detection is triggered.

[0288] It can also analyze the positional movement of stationary points in adjacent detection subspaces in terms of spatial dimension alone, and combine this with the set anti-interference level judgment conditions to determine whether a human detection is triggered.

[0289] It can also analyze the frequency of the occurrence of stationary subspaces in continuous detection in the time dimension, and the positional movement of stationary subspaces in adjacent detections in the spatial dimension, and combine these factors with the set anti-interference level judgment conditions to determine whether a human detection is triggered.

[0290] In this embodiment of the disclosure, such as Figure 16 As shown, the horizontal axis represents the time dimension. Analyzing the frequency of stationary point subspace occurrences in continuous detection along the time dimension can be, for example, several consecutive periods ( Figure 16 In the detection (where each unit on the horizontal axis represents one cycle), stationary subspaces appeared in all cases; the vertical axis represents the spatial dimension, and the positional movement of stationary subspaces in adjacent detections is analyzed along this spatial dimension. Figure 16 In this diagram, each unit on the vertical axis represents a detection subspace. For example, it represents the positional shift of a stationary point subspace between adjacent detection cycles. This positional shift refers to the change in the index of the stationary point subspace within the divided detection subspace grid between adjacent detection cycles, used to quantify the displacement of the target (e.g., a human body). For instance, within an 8-meter detection range, if it is uniformly divided into 32 detection subspaces (numbered 0-31) at 0.25-meter intervals, as shown... Figure 16 As shown, when the stationary point subspace is located at 0–0.25 meters (index 0) in the first cycle, and moves to 0.25–0.5 meters (index 1) in the second cycle, the position movement is 1 unit; when it moves further to 0.75–1.0 meters (index 3) in the third cycle, the position movement between the second and third cycles is 2 units (index difference |3-1|=2). This calculation method based on grid indexing transforms the physical displacement of the human body into standardized units, facilitating a unified analysis of the target's movement trend and velocity, while also adapting to detection spaces of different sizes.

[0291] Specific examples:

[0292] like Figure 17 As shown, a schematic diagram of a stationary subspace detection for the position of a curtain when the window is closed is given; the curtain is positioned 3m to 3.5m directly opposite the detection device. It can be seen that... Figure 16Of the 61 detection cycles shown, no stagnation subspace was detected in 19 cycles, while stagnation subspace was detected in the remaining cycles. This indicates that in daily life, curtains can cause high-frequency disturbances to the detection device, but the amplitude of the disturbances is limited.

[0293] like Figure 18 As shown, the following is given: Figure 17 The diagram illustrates the detection of a stationary subspace during the movement of a human body toward the detection device 100, with the window further opened in the shown scenario. Figure 18 In the scenario shown, due to the significantly increased disturbance caused by the curtains from the window, the human body reaches the location of the detection device around the 40th cycle. If each cycle is 50ms, then it takes approximately 2 seconds for the person to move from the location of the curtains to the location of the detection device. The curtains are positioned 3m to 3.5m directly opposite the detection device, meaning the person is moving at a speed of approximately 1.5 to 1.75m per second, which is consistent with the normal walking speed of a person (less than 2m / s).

[0294] In some embodiments, the anti-interference level determination criteria include:

[0295] A combination of different stringency judgment thresholds is used to compare with the frequency and / or the movement amplitude to determine whether a person judgment is triggered.

[0296] Specifically, the threshold combination is a set of dynamic triggering conditions used to compare the frequency of occurrence and movement amplitude of the stationary subspace. For example, it may include a frequency threshold and an amplitude threshold. Therefore, when only the time dimension is considered, a presence detection is triggered as long as the frequency of occurrence of the stationary subspace in continuous detection reaches the frequency threshold. When only the spatial dimension is considered, a stationary subspace is required in each continuous detection, and the movement amplitude of the stationary subspace must exceed the amplitude threshold for a presence detection to be triggered. When both the time and space dimensions are considered simultaneously, both frequency and amplitude must meet their respective thresholds for a detection to be triggered.

[0297] Furthermore, in continuous detection, a sliding window mechanism is used to dynamically analyze the results of the most recent N detections to obtain the spatiotemporal distribution characteristics of the stationary point subspace; N is an integer greater than or equal to 2. In a specific example, N is set to be less than or equal to n. max , where n max The value of is [7, 15].

[0298] Specifically, during continuous detection, the detection device employs a sliding window mechanism to dynamically analyze the results of the most recent N (N≥2) detections. It extracts spatiotemporal distribution characteristics by analyzing the frequency of occurrence and positional movement of stationary points within the window subspace. The window size N can be configured within the range [2, nmax] according to actual needs. For example, when nmax = 7, N = 3 can be selected for short-term rapid response (low latency), or N = 7 for long-term stability judgment (high interference immunity). This dynamic window design ensures both real-time detection and balances sensitivity and interference immunity by adjusting the window length.

[0299] When the detection cycle reaches N times, after each new detection is completed, the oldest detection result is automatically discarded and the latest result is incorporated, thus always maintaining the analysis of the most recent N detections.

[0300] Furthermore, the frequency of stationary subspace occurrences in continuous detection is analyzed in the time dimension, specifically including: analyzing the most recent N detection results using a sliding window mechanism to obtain the number of consecutive occurrences of stationary subspaces. In the spatial dimension, the positional movement amplitude of stationary subspaces in adjacent detection cycles is analyzed, specifically including: the sum of positional movement amplitudes of adjacent stationary subspaces in the most recent N detection results.

[0301] For example, when N=5, the window always contains the current time and the data from the previous 4 detections. Two types of key metrics are calculated within the window:

[0302] Time dimension: Count the total number of consecutive occurrences of the stationary subspace (e.g., 3 consecutive occurrences out of 5) to obtain the number of consecutive occurrences of the stationary subspace;

[0303] Spatial dimension: Calculate the cumulative displacement amplitude between adjacent detection cycles (e.g., a cumulative movement of 4 units in 5 detections), which is used as the sum of the positional movement amplitudes of adjacent stationary point subspaces in a continuously occurring stationary point subspace.

[0304] Furthermore, based on the set anti-interference level judgment conditions, it is determined whether a human judgment is triggered. Specifically, this includes determining the matching target judgment threshold combination according to the set anti-interference level, including the number threshold and the amplitude threshold.

[0305] The spatiotemporal distribution features are compared with the target determination threshold, including: when the number of consecutive occurrences of a stationary subspace reaches a corresponding number threshold, and / or when the total positional movement amplitude of adjacent candidate subspaces reaches a corresponding amplitude threshold, it is determined that someone has been triggered.

[0306] For example, with a window size N=7, if the set anti-interference level determines the target judgment threshold combination as a frequency threshold of 3 and an amplitude threshold of 4, then the detection device extracts the spatiotemporal characteristics of the stationary subspace by dynamically analyzing the results of the most recent 7 detections: It requires that "a stationary subspace appears consecutively in 7 detections" and that the cumulative displacement amplitude of adjacent stationary subspaces in these 3 consecutive stationary subspaces is greater than or equal to 4 to trigger a person detection. This requires determining whether there are 3 consecutive periods within the detection window that are all marked as stationary subspaces. For example, if stationary subspaces appear in periods 1, 2, and 4 but are interrupted in period 3, then the strict continuity condition is not met (the detected stationary subspaces can correspond to different detection subspaces in different periods). If the requirement is "a cumulative movement of 4 units in 3 consecutive detections," then the sum of the index differences between adjacent stationary subspaces is calculated to be greater than or equal to 4. For example, if period 1→2 moves 1 unit, period 2→3 moves 2 units, and period 3→4 moves 1 unit, the cumulative displacement of 4 units satisfies the condition.

[0307] Furthermore, the mechanism provided in this embodiment of the present disclosure achieves accurate identification and interference filtering of real human targets by quantifying the distribution pattern of the stationary subspace in the time and space dimensions (e.g., 0.25 meters / physical displacement of the detection subspace corresponds to 1 index unit) and combining it with a configurable judgment threshold (frequency / displacement).

[0308] Furthermore, the method 150 also includes:

[0309] The detection device acquires a setting command; the setting command is generated and sent after one of at least two anti-interference level identifiers displayed in the terminal device is selected.

[0310] The detection device sets the anti-interference level according to the set instructions.

[0311] Specifically, the method 150 provided in this embodiment of the present disclosure also includes an anti-interference level setting function: after the user selects the anti-interference level (including at least three levels: weak, medium and strong) through the terminal device, the detection device configures the corresponding judgment threshold combination according to the selected level.

[0312] In practice:

[0313] When the anti-interference level is turned off, it is required that the stationary subspace is detected for W consecutive detection cycles, where W≤3; for example, if W=3, then even without the anti-interference level turned on, the stationary subspace needs to be detected for 3 consecutive detection cycles (the 3 stationary subspaces can be the same detection subspace or different detection subspaces) before it is determined that there is someone in the detection space.

[0314] The weak anti-interference level requires that the presence of stationary subspace be detected in 3 consecutive detection cycles (threshold = 3) and the cumulative displacement of adjacent displacements be ≥1 (amplitude threshold ≥1).

[0315] The medium anti-interference level requires that the presence of stationary subspaces be detected in 4 consecutive detection cycles (threshold = 4) and the cumulative displacement of adjacent displacements be ≥3 (amplitude threshold ≥3).

[0316] The strong anti-interference level requires that the presence of stationary subspaces be detected in 5 consecutive detection cycles (threshold = 5) and the cumulative displacement of adjacent displacements be ≥ 5 (amplitude threshold ≥ 5).

[0317] The detection device 100 uses a sliding window mechanism (window size is 7 detections) for dynamic analysis: taking the strong anti-interference level as an example, the detection device 100 will start from the 5th cycle to judge the spatiotemporal distribution characteristics of the stationary subspace in the most recent 5 detection results. When there are 5 consecutive stationary subspaces in the window and the cumulative displacement of adjacent stationary subspaces is ≥5, a man detection is triggered; if the condition is not met, the window slides one position to continue detection. When it reaches the 7th time, each new detection result will automatically discard the oldest detection result, and the most recent 7 detection results will always be checked until the condition is met.

[0318] Furthermore, in this embodiment of the disclosure, each anti-interference level achieves differentiated anti-interference capabilities through the requirements of the number of times threshold and the amplitude threshold, with higher levels having stricter triggering conditions.

[0319] For specific examples:

[0320] The threshold for weak anti-interference level is 3 times and the threshold for amplitude is 1.

[0321] The threshold for the number of interferences in the medium-level anti-interference system is 4, and the threshold for the amplitude is 3.

[0322] The threshold for the strong anti-interference level is 5, and the amplitude threshold is 5.

[0323] Based on this, in such Figure 17 In the application scenarios shown, the application descriptions for each anti-interference level regarding curtain disturbance when the windows are closed are as follows:

[0324] If a weak anti-interference level is adopted, since the stationary subspace appears consecutively in the three cycles from 39 to 41, and between the two detection cycles from 40 to 41, the stationary subspace moves from the detection subspace of 3-3.25m to the detection subspace of 3.25-3.5m, while between the two detection cycles from 39 to 40, the stationary subspace does not move. Therefore, the total positional movement of the stationary subspace between the three cycles from 39 to 41 reaches 1. In the 41st detection cycle, a person will be triggered, that is, the curtain disturbance will be mistakenly detected as a human body, causing a false trigger.

[0325] If the medium anti-interference level is used, it will not be triggered. It should be noted that the medium anti-interference level requires a threshold of 4 times. It can be seen that there are 6 instances of stationary subspace in the 39th to 44th detection cycles, which meets the threshold requirement. However, the total positional movement amplitude of the stationary subspace in these 6 instances is 2 (cycles 40→41 and 43→44), which is less than 3. Therefore, the amplitude threshold is not met, so no one will be triggered.

[0326] The strong anti-interference level has stricter standards, so if the strong anti-interference level is used, it will naturally not be accidentally triggered.

[0327] It is evident that, in response to Figure 17 In the application scenario shown, using the medium anti-interference level can filter out interference caused by curtain movements with a high probability. In this case, the speed of response to the human body can also be taken into account (if each cycle is 50ms, then the delay time for human body response due to the medium anti-interference level is 4×).

[0328] 50ms = 200ms).

[0329] In some embodiments, the method 150 further includes:

[0330] The detection device sends the acquired human signal feature intensity values ​​of each detection subspace to the terminal device, so that the terminal device can visualize the human signal feature intensity values ​​of each detection subspace. Specifically, for the stationary point subspace, the first type of visualization scheme is applied, and for the other detection subspaces, the second type of visualization scheme is applied. The first type of visualization scheme and the second type of visualization scheme have perceptible display differences to intuitively show the location of the stationary point subspace, making it convenient for users to view.

[0331] In specific examples, the first type of visualization scheme includes a bar chart display of a first visual feature; the second type of visualization scheme includes a bar chart display of a second visual feature; wherein the first visual feature and the second visual feature have distinguishable display differences in color, brightness, pattern and / or dynamic effects.

[0332] In further examples, such as Figure 19 As shown, the first visual feature and the second visual feature have a distinguishable display difference in color depth. Figure 19 As can be seen, the human signal intensity values ​​corresponding to the stationary subspaces that trigger the presence of a person are displayed in dark color, indicating that a person has been detected in the corresponding detection subspace (the 0.75m to 1m detection subspace). The human signal intensity values ​​corresponding to the other detection subspaces are displayed in light color, indicating that no person has been detected in the corresponding detection subspace.

[0333] Based on the above method 150, an embodiment of this disclosure also provides a detection device, which can be applied to, for example... Figure 1 The human body detection system shown, or the detection device used in it.

[0334] like Figure 20 As shown, the detection device includes a detection unit, a stationary marker unit, and a determination unit.

[0335] The detection unit is used to periodically detect the intensity value of human feature signals in each detection subspace. The intensity value is obtained through spatial detection and is used as a quantitative indicator to characterize the possibility of the presence of a human body in the detection subspace. Each detection subspace is obtained by dividing the detection space of the detection device.

[0336] The stationary point marking unit is used to mark a detection subspace that meets the stationary point condition and whose intensity value exceeds the corresponding detection sub-threshold as a stationary point subspace; the stationary point condition refers to the intensity value of a detection subspace satisfying a preset peak relationship condition relative to the intensity value of an adjacent subspace.

[0337] The determination unit is used to determine whether to trigger the determination of whether there are people in the detection space based on the stationary subspace.

[0338] In some embodiments, the quantitative indicators include physical quantities that reflect the presence of a human body within the detection subspace, obtained through active detection; the active detection method includes beam transmission and reception.

[0339] In some embodiments, the peak relationship condition specifically includes: if the i-th detection subspace a(i) satisfies the formula: T a(i-1) <T a(i) ≤T a(i+1) Then, the detection subspace a(i) is determined to satisfy the peak relation condition; where i∈[1,S], and S represents the total number of detection subspaces in the detection space; T a(i) T represents the intensity value of the human feature signal in the i-th detection subspace. a(i-1) T represents the human feature signal intensity value of the (i-1)th detection subspace a(i-1). a(i+1) This represents the intensity value of the human feature signal in the (i+1)th detection subspace a(i+1).

[0340] In some embodiments, the determination unit determines whether a person detection is triggered based on the stationary subspace, specifically by: determining whether a person detection is triggered based on the spatiotemporal distribution characteristics of the stationary subspace in continuous detection, combined with the set anti-interference level determination conditions; wherein: the frequency of occurrence of the stationary subspace in continuous detection is analyzed in the time dimension; and / or, the positional movement amplitude of the stationary subspace in adjacent detections is analyzed in the spatial dimension.

[0341] The anti-interference level determination criteria include: a combination of determination thresholds with different levels of strictness, used to compare with the frequency and / or the movement amplitude to determine whether a human presence determination is triggered.

[0342] In some embodiments, during continuous detection, a sliding window mechanism is used to dynamically analyze the results of the most recent N detections to obtain the spatiotemporal distribution characteristics of the stationary point subspace; N is an integer greater than or equal to 2.

[0343] In some embodiments, the frequency of the stationary subspace in continuous detection is analyzed in the time dimension. Specifically, this is done by using a sliding window mechanism to analyze the results of the most recent N detections to obtain the number of consecutive occurrences of the stationary subspace.

[0344] In terms of spatial dimension, the analysis of the positional movement amplitude of the stationary point subspace in adjacent detections is specifically used for: the sum of the positional movement amplitudes of adjacent stationary point subspaces in the N most recent detection results, which are consecutively appearing stationary point subspaces.

[0345] The judgment threshold combination includes a frequency threshold and an amplitude threshold; combined with the set anti-interference level judgment conditions, it determines whether a human judgment is triggered. Specifically, it is used to determine the matching target judgment threshold combination based on the set anti-interference level, including the frequency threshold and the amplitude threshold.

[0346] The spatiotemporal distribution features are compared with the target determination threshold, including: when the number of consecutive occurrences of a stationary subspace reaches a corresponding number threshold, and / or when the total positional movement amplitude of adjacent candidate subspaces reaches a corresponding amplitude threshold, it is determined that someone has been triggered.

[0347] In some embodiments, the determination unit of the detection device is further configured to: acquire a setting instruction; the setting instruction is generated and sent after one of at least two anti-interference level identifiers displayed in the terminal device is selected; and set the anti-interference level according to the setting instruction.

[0348] In some embodiments, N is set to be less than or equal to n. max , where n max The value of is [7, 15].

[0349] In some embodiments, such as Figure 20As shown, the detection device further includes a transmitting unit for sending the acquired human signal feature intensity values ​​of each detection subspace to the terminal device, so that: the terminal device visualizes the human signal feature intensity values ​​of each detection subspace; wherein, for the stationary point subspace, a first type of visualization scheme is applied, and for the remaining detection subspaces, a second type of visualization scheme is applied; the first type of visualization scheme and the second type of visualization scheme have perceptible display differences; wherein, the first type of visualization scheme includes a bar chart display of a first visual feature; the second type of visualization scheme includes a bar chart display of a second visual feature; wherein, the first visual feature and the second visual feature have distinguishable display differences in color, brightness, pattern and / or dynamic effects.

[0350] Furthermore, in practical application scenarios, various electromagnetic interferences (such as Wi-Fi signals and radiation from home appliances) and dynamic environmental noises (such as swaying curtains and pet activities) often require the detection device to adjust various detection parameters during use. These detection parameters are not limited to the sensitivity mentioned in the above embodiments, but also include other parameters that can affect the sensing characteristics of the detection device, such as anti-interference level, unattended detection time, and manned detection time.

[0351] In existing parameter adjustment methods, users need to manually search for relevant settings in complex parameter menus. Furthermore, non-professional users find it difficult to accurately match the problem with the corresponding parameter, which seriously affects configuration efficiency and accuracy.

[0352] Based on this, one embodiment of this disclosure also provides a human body detection and processing method, which is applied to a terminal device.

[0353] like Figure 21 The diagram shown is a schematic flowchart of a human body detection and processing method according to an embodiment of this disclosure. It can be seen that the human body detection and processing method 210 includes at least steps S210 to S212.

[0354] In step S210, the terminal device responds to the user's first operation by displaying at least one operating condition description item; each operating condition description item describes at least one detection anomaly scenario; each operating condition description item establishes a mapping relationship with at least one adjustable detection parameter, the detection parameter being used to adjust the detection response characteristics of the detection device.

[0355] Specifically, a working condition description item can be understood as a predefined technical description unit used to characterize a specific abnormal working state of the detection device. Each working condition description item describes different possible abnormal scenarios, serving as a reference for users to diagnose and configure the detection device. An abnormal detection scenario can be understood as an unexpected working state exhibited by the detection device under specific environmental conditions. For example, some working condition description items may correspond to false triggering in an unmanned state, that is, the detection device erroneously triggers the operation of the controlled equipment even when no human is present.

[0356] Furthermore, before responding to the user's first action and displaying the operating condition description items, the method further includes: acquiring a scalable operating condition description database, which stores multiple preset operating condition description items. The operating condition description items can be stored as structured data, for example, through database tables or cloud storage, to ensure that these operating condition description items can be flexibly accessed and updated according to different environments and needs.

[0357] Furthermore, in some embodiments, the operating condition description database can be flexibly expanded, supporting the addition of specific operating condition description items, and the latest operating condition description database can be obtained through software upgrades. These new items are particularly suitable for detection applications under different detection anomaly scenarios, such as differences between indoor and outdoor environments, different equipment configurations, or adaptation after equipment upgrades. This flexibility allows the detection device to be continuously optimized and adjusted according to actual conditions, ensuring its effectiveness in diverse environments.

[0358] The adjustable detection parameters mapped to each operating condition description accurately reflect the technical correlation between abnormal detection scenarios and key detection parameters (such as detection thresholds, presence judgment time windows, sensitivity levels, etc.). This mapping relationship allows users to adjust the response characteristics of the detection device in a targeted manner based on recommended adjustments, thereby optimizing the device's performance under different environments and operating conditions.

[0359] In step S211, the terminal device responds to the user's trigger command for the target operating condition description item and displays at least one parameter adjustment item, which forms a direct operational binding relationship with the mapped detection parameter.

[0360] Parameter adjustment items refer to interactive controls (such as sliders, buttons, and option boxes) displayed by the terminal device through the user interface (UI). Through these controls, users can adjust specific parameters of the detection device. These adjustment items are directly bound to the mapped detection parameters. User operations on the interactive controls (such as dragging sliders or selecting options) directly trigger updates to the corresponding detection parameters, ensuring that user input can be reflected in the working status of the detection device in a timely and accurate manner.

[0361] In step S212, the terminal device captures the user's parameter input through the parameter adjustment item and performs a reconfiguration operation on the detection response characteristics of the detection device based on the input.

[0362] Furthermore, the terminal device performs real-time reconfiguration based on the detection response characteristics of the detection device. That is, after the user operates the interactive controls, the detection device will immediately adjust the detection parameters to adapt to new usage requirements or environmental changes.

[0363] As can be seen, the method provided in this disclosure intelligently organizes and displays multiple parameter adjustment items according to operating conditions. After the user selects the corresponding operating condition description item, the terminal device automatically generates a composite interface integrating relevant solutions and parameter adjustments. Through this intelligent interface, users can not only quickly view the operating condition description but also directly adjust relevant parameters, thereby quickly troubleshooting or optimizing performance. This method effectively simplifies the user operation process and improves the usability and adaptability of the detection device.

[0364] In some embodiments, after responding to a user's trigger command for a target operating condition description item, method 210 further includes: displaying semantically rendered content, including at least one of the following:

[0365] The typical detection scenarios corresponding to the target working condition description items are presented in graphical form. This graphical representation uses methods such as images, animations, and waveforms to intuitively present the abnormal detection scenarios of the detection device under specific working conditions, helping users to quickly understand the root cause of the problem.

[0366] This document explains the impact of adjusting each parameter on the detection response characteristics of the detection device. It serves to guide users on how adjusting the detection parameters affects the performance of the detection device, enabling them to intuitively understand the technical effects of parameter adjustments on the device's performance.

[0367] Based on the analysis of the current detection status of the detection device, a predetermined solution is output; this solution provides optimization suggestions or troubleshooting measures for the current detection status, helping users to quickly take effective remedial actions.

[0368] Furthermore, after responding to the user's trigger command for the target working condition description item, the method 210 further includes: arranging the semantic presentation content and the parameter adjustment item on the same interactive interface, so that the user can complete the entire process from problem diagnosis to parameter adjustment without switching pages, thereby improving operational efficiency and enhancing user experience.

[0369] Furthermore, generating and displaying a graphical representation of the typical detection scenario corresponding to the target working condition description item, specifically including: generating and displaying a dynamic schematic diagram of the working condition described by the target working condition description item; and / or, calculating and predicting the simulation effect of the change in detection response characteristics under the adjustment of the mapped adjustable parameters, and generating and displaying a simulation diagram of the parameter adjustment effect.

[0370] The dynamic schematic diagram vividly demonstrates the operating status and abnormal scenarios of the detection device under target conditions through graphics, animations, or interactive elements. The dynamic schematic diagram may include real-time changes in the usage environment of the detection device or changes in environmental factors occurring under specific abnormal detection scenarios, helping users intuitively understand the abnormal performance of the detection device under those conditions.

[0371] The parameter adjustment effect simulation diagram can calculate and predict changes in detection response characteristics based on the current status and operating condition description of the detection device. The simulation effect includes changes in detection sensitivity, response speed, and detection accuracy, thereby generating a corresponding parameter adjustment effect simulation diagram. The simulation diagram visually displays the response under different parameter settings, allowing users to preview the potential changes after adjustment, ensuring the rationality and effectiveness of parameter adjustments.

[0372] In this way, the entire solution not only achieves a graphical presentation of abnormal operating conditions, but also closely links the effect of parameter adjustment with its corresponding detection response characteristics, enabling users to intuitively understand the root cause of the problem and the effect after adjustment within a single interface, further improving the accuracy and efficiency of operation.

[0373] Furthermore, the title of the parameter adjustment item also serves as an operable control. Specifically, the parameter adjustment item not only acts as descriptive text, but also possesses interactive functionality. Users can directly access the settings interface related to the response detection parameters by clicking or manipulating the title to adjust the parameters. Through this design, the title text and interactive control are integrated into a dual-function interface element, which not only simplifies the user's operation steps but also allows users to make configuration adjustments more intuitive and convenient.

[0374] The display of at least one parameter adjustment item specifically includes: displaying the configuration guidance information in the title of the parameter adjustment item; the configuration guidance information refers to the suggested content generated based on the detection anomaly scenario corresponding to the target working condition description item, which is used to guide users to optimize parameter settings.

[0375] The configuration guidance information is generated based on the detected anomaly scenarios corresponding to the target operating condition description items, and serves as suggestions to guide users in optimizing parameter settings. This guidance information can be concise and clear text descriptions, recommended settings, or solutions to common problems, helping users quickly understand how to adjust parameters to cope with anomalies under specific operating conditions. Through intuitive suggestions, users can make reasonable adjustments in the shortest possible time, avoiding misoperation or improper settings.

[0376] The method of capturing user parameter input through the parameter adjustment item specifically includes: in response to the title being operated, directly jumping to the parameter adjustment interface of the detection parameters that form a direct operation binding relationship.

[0377] Specifically, when a user interacts with a parameter adjustment item title (such as clicking, swiping, or selecting), the terminal device instantly captures the user's input and transmits it to the device's detection parameter adjustment interface. In this interface, the user can see detailed adjustable parameters bound to the current title and adjust them using intuitive controls. A direct operational binding relationship is established between each parameter adjustment item and the detection parameter; that is, the user's adjustment input will affect the corresponding detection parameter in real time, thereby directly changing the response characteristics of the detection device.

[0378] When a user adjusts a parameter heading, the terminal device will automatically redirect to the relevant parameter adjustment interface based on the detection parameters associated with that heading. This interface will display detailed adjustable parameters and corresponding adjustment controls (such as sliders, input boxes, and selection buttons) to allow the user to precisely adjust the detection parameters. This design centralizes the processing of related configuration settings, improves user efficiency, and reduces the complexity of switching between multiple interfaces and operations.

[0379] Furthermore, the method provided in this disclosure allows users to quickly and accurately adjust various detection parameters of the device within the same interface, making the overall operation simpler and more efficient, while avoiding complex menu hierarchies and multi-step operation processes.

[0380] For specific examples, such as Figure 22 As shown, the operating condition description item includes a first abnormal operating condition 2201, which describes a detection failure scenario where the detection device continuously triggers the switching of the controlled device's operating state in an unmanned state. Specifically, when the detection device fails to correctly identify the unmanned state, causing the device to still trigger the switching of the controlled device's operating state even when no human is present, a false triggering or false response occurs. For example, in an unmanned state, the controlled lighting fixtures are frequently triggered to switch between on and off.

[0381] When the target operating condition description item is the first abnormal operating condition 2201, method 210 includes providing at least one of the following: adjustment item for operating mode parameter, adjustment item for radar sensitivity parameter, adjustment item for infrared sensitivity parameter, and adjustment item for anti-interference level parameter.

[0382] For specific examples, such as Figure 23 As shown, for example, the first abnormal condition 2201 describes the abnormal detection scenario of "frequent switching of lights on / off by unattended personnel".

[0383] like Figure 23 As shown, the adjustment item 22011 of the working mode parameter is used to switch between fusion detection mode and pure radar mode. Wherein:

[0384] Fusion Detection Mode: Combining infrared and radar technologies, this mode offers higher detection accuracy. It comprehensively analyzes radar and infrared signals, improving adaptability to complex environments and reducing false alarms. Specifically, a person detection is triggered only when both the infrared pyroelectric module and the radar module detect a person.

[0385] Pure radar mode: Relies solely on the radar module to detect the presence of human signals. Suitable for scenarios with minimal environmental interference or applications requiring optimized radar sensitivity. Users can select the appropriate operating mode based on their actual needs to optimize device response.

[0386] It is worth mentioning that in the aforementioned fusion detection mode and pure radar mode, the radar module makes a corresponding human presence determination based on the corresponding anti-interference level during the process of determining the presence of a human in the detection space. Specifically, the detection device periodically detects the human feature signal intensity value of each detection subspace through the radar module; and marks the detection subspace that meets the stationary point condition and whose intensity value exceeds the corresponding detection sub-threshold as a stationary point subspace, and then determines whether to trigger the determination that there is a person in the detection space based on the stationary point subspace. The specific determination process can be understood by referring to the description in the above embodiments, and will not be repeated here.

[0387] Furthermore, before, after, or simultaneously with the user clicking or selecting the title of the working mode parameter adjustment item 22011, configuration suggestions related to switching to the fusion detection mode are displayed through the title, guiding the user on how to achieve the best detection effect by adjusting relevant settings (such as radar sensitivity, infrared sensitivity, etc.). Figure 23 As shown, the title of the adjustment item 22011 of the working mode parameter displays configuration guidance information for "changing the working mode to the fusion mode".

[0388] The adjustment item 22013 of the radar sensitivity parameter is used to adjust the radar sensitivity. For example... Figure 24 As shown, the radar sensitivity adjustment methods include preset levels.

[0389] The preset sensitivity settings offer several different sensitivity levels for users to select (e.g., high, medium, low) to suit the radar sensitivity requirements of different scenarios. Users simply select the appropriate setting, and the detection device automatically adjusts the sensitivity. Custom sensitivity settings are also provided (e.g., ...). Figure 24 The "Custom" setting (as described in the text) allows the detection device to automatically restore the previously saved user-defined detection thresholds when switched to the custom setting; that is, it automatically restores the previously saved sub-thresholds for each detection threshold. The implementation method for user-defined detection thresholds can be found in [reference needed]. Figure 8 The embodiments shown are for illustrative purposes only and will not be repeated here.

[0390] Furthermore, the radar sensitivity adjustment method provided by the radar sensitivity parameter adjustment item 22013 also includes an automatic adjustment method. This automatic adjustment method is used to trigger the automatic adjustment of the detection threshold. Specifically, the user can trigger the adjustment trigger request through this automatic adjustment method. Then, the terminal device responds to the adjustment trigger request and outputs at least two adjustment paths with different sensing characteristics. Based on the adjustment mechanism mapped by the selected adjustment path, the detection threshold is dynamically corrected to conform to the sensing characteristics defined by the selected path. Based on the corrected detection threshold, the terminal device performs corresponding adaptive configuration of the sensitivity of the detection device to optimize the response accuracy of the detection device under the sensing characteristics corresponding to the selected adjustment path.

[0391] For specific examples, such as Figure 24 As shown, the user enters the sensitivity adjustment interface by clicking the title of the radar sensitivity parameter adjustment item 22013. This interface provides a "Scan for interference sources, automatically adjust sensitivity" option at the bottom. Triggering this option will trigger the adjustment request, subsequently leading to... Figure 5 The adjustment path selection interface is described above. For specific adjustment methods, please refer to the following: Figures 4 to 10 The embodiments shown are for illustrative purposes only and will not be elaborated upon here.

[0392] Furthermore, before, after, or simultaneously with the user clicking or selecting the title of the radar sensitivity parameter adjustment item, configuration suggestions on how to reduce radar sensitivity are displayed, especially in scenarios with lower detection accuracy requirements or less environmental interference. These suggestions help users adjust radar sensitivity to reduce unnecessary false triggers and ensure efficient device operation. Figure 24 As shown, the configuration guidance information for "reducing radar sensitivity" is displayed under the title of the radar sensitivity parameter adjustment item 22013.

[0393] The adjustment item 22014 of the infrared sensitivity parameter is used to determine the infrared sensitivity based on user selection when the working mode is the fusion detection mode. Figure 25As shown, the infrared sensitivity offers three preset levels: high, medium, and low. When the user selects the fusion detection mode, the detection device adjusts the infrared sensor's sensitivity in real time based on the user-input infrared sensitivity parameters, ensuring that the infrared and radar signals can complement each other. By properly adjusting the infrared sensitivity, users can reduce false triggering caused by external environmental factors such as changes in lighting conditions.

[0394] Furthermore, before, after, or simultaneously with selecting the infrared sensitivity parameter adjustment option, users will be shown relevant guidance information on reducing infrared sensitivity. This helps users reduce the risk of infrared misidentification based on actual environmental conditions (such as strong light or high temperature), thereby optimizing stability. Figure 25 As shown, the title of the infrared sensitivity parameter adjustment item displays configuration guidance information for "reducing infrared sensitivity".

[0395] The anti-interference level parameter adjustment item 22015 is provided for adjusting the anti-interference level. For example... Figure 26 As shown, the anti-interference levels include weak anti-interference level, medium anti-interference level, strong anti-interference level, and custom delay trigger. The specific implementation methods of the weak anti-interference level, the medium anti-interference level, and the strong anti-interference level can be understood by referring to the description in the above embodiments, and will not be repeated here.

[0396] Furthermore, before, after, or simultaneously with selecting the adjustment option for the anti-interference level parameter, users will be displayed relevant guidance information on enhancing the anti-interference level. For example... Figure 25 As shown, the title of the anti-interference level parameter adjustment item 22015 displays configuration guidance information for "turning on or strengthening the anti-interference level".

[0397] It's worth noting that the custom delay trigger option provides an adjustment option for the presence detection window parameter, used to adjust the presence detection window. The presence detection window represents the continuous state detection time required to switch from an unoccupied state to an occupied state. That is, the presence detection window controls the continuous state detection time (i.e., the time period during which human signals are continuously detected) required when switching from an "unoccupied state" to a "occupied state." By setting an appropriate presence detection window duration, brief interference, such as briefly passing through a darkened scene, can be filtered out. Figure 26 As shown, if the custom delay trigger time is set to 3 seconds, then the window for determining if someone is present is 3 seconds. When switching from "no one" to "present", the required continuous state detection time is 3 seconds. That is, the period of continuous detection of human signals will last for more than 3 seconds before "present" will be triggered.

[0398] In some embodiments, when the target operating condition description item is a second abnormal operating condition, method 210 includes providing at least one of an adjustment item for radar sensitivity parameters and an adjustment item for no-man's-land determination window parameters.

[0399] The second abnormal operating condition describes a detection failure scenario where the detection device fails to maintain the controlled equipment in the on state when personnel are present. For example... Figure 27 As shown, the second abnormal condition 2202 describes the abnormal detection scenario of "someone is there but the lights are off".

[0400] For specific examples, such as Figure 27 As shown, the radar sensitivity parameter adjustment item 22021 is used to adjust the radar sensitivity. The method of adjusting radar sensitivity through the radar sensitivity parameter adjustment item 22021 in this embodiment can be referred to as follows: Figure 24 The description of the illustrated embodiment is for understanding purposes only, and identical parts will not be repeated. The difference is that in this embodiment, before, after, or simultaneously with the user clicking or selecting the title of the radar sensitivity parameter adjustment item, the displayed configuration suggestions on how to reduce radar sensitivity are different from those shown in the example. Figure 24 The illustrated embodiments differ. For example... Figure 27 As shown in this embodiment, the configuration guidance information for "Increase Radar Sensitivity" is displayed under the title of the radar sensitivity parameter adjustment item 22013. It is evident that even for the same parameter adjustment item, the displayed configuration guidance information differs depending on the detection anomaly scenario.

[0401] like Figure 28 As shown, the adjustment item 22022 of the no-man presence determination window parameter is used to adjust the no-man presence determination window; the no-man presence determination window represents the length of continuous state detection time required to determine the transition from a manned state to a manless state.

[0402] The adjustment item 22022 of the "No-Occupancy Determination Window" parameter is used to adjust the "No-Occupancy Determination Window"; the "No-Occupancy Determination Window" represents the continuous state detection time required to determine the transition from a occupied state to an unoccupied state. By setting an appropriate "No-Occupancy Determination Window" duration, brief interferences, such as a user's brief period of stillness, can be filtered out. Figure 28 As shown, the unmanned judgment time is set to 30 seconds, so the unmanned existence judgment window is 30 seconds. When switching from "manned state" to "unmanned state", the required continuous state detection time is 30 seconds. That is, the unmanned state will only be triggered if the period of no human signal is detected for more than 30 seconds.

[0403] In some embodiments, such as Figures 23-26 As shown, when the target operating condition description item is the first abnormal operating condition 2201, at least one parameter adjustment item is displayed, and it also includes:

[0404] Provides option 22012 for accidental trigger exclusion, which automatically adjusts the detection threshold based on historical trigger records.

[0405] Specifically, in response to the user's selection of an accidental touch exclusion item, the terminal device presents an accidental touch exclusion interface, displaying an identifier corresponding to at least one first data record. This first data record is generated when the detection device detects a switch from an unoccupied state to an occupied state (i.e., triggering a detection state), and includes the specific location of the detected subspace that triggered the presence of someone. In response to the user's selection of at least one first data record, the terminal device automatically increases the human feature signal intensity value corresponding to the detected subspace that triggered the presence of someone within that first data record by a certain value, and uses this as a detection sub-threshold, sending it to the detection device to update the detection sub-threshold of the corresponding detection subspace. When multiple first data records are selected, if multiple data records contain duplicate detected subspaces that were triggered by someone, the highest human feature signal intensity value is used as a benchmark for increasing the value by a certain value to obtain the corresponding detection sub-threshold.

[0406] For specific examples, such as Figure 29 As shown, in the accidental touch elimination interface, the user selects the first data record corresponding to the first identifier. In the first data record corresponding to the identifier, the segment corresponding to the detection subspace of 0.75~1m is filled with shade, which means that the human feature signal intensity value of the detection subspace exceeds the corresponding detection sub-threshold (specifically the first trigger threshold value). The user further clicks the "Eliminate Interference" control to trigger the automatic adjustment of the threshold. The terminal device will automatically increase the human feature signal intensity value (80) corresponding to the detection subspace of 0.75~1m by 25 to obtain the updated detection sub-threshold (100). Furthermore, it will pop up example diagrams of the historical detection sub-thresholds and the current detection sub-threshold (updated) for each detection subspace for the user to view. After the user clicks the "Confirm" option, the updated detection sub-threshold is loaded into the calibration command and sent to the detection device. After receiving the calibration command, the detection device adjusts the detection sub-threshold of the detection subspace of 0.75~1m to 100.

[0407] In some embodiments, such as Figure 22 As shown, the operating condition description item includes a third abnormal operating condition 2203 and / or a fourth abnormal operating condition 2204.

[0408] The third abnormal operating condition, 2203, describes a detection failure scenario where the detection device fails to trigger a state switch in the controlled equipment after a human body leaves the detection space. This situation typically occurs when the user expects the controlled equipment to automatically shut down or switch states after a human body leaves a certain area, but the detection device fails to detect the human body's departure in time, resulting in the equipment not undergoing the expected state change. Specifically, the detection device may not have detected the human body's departure in time, or its sensitivity may not have met the trigger conditions, leading to a failure to respond correctly. This situation may occur when there is significant environmental interference or when the device parameters are improperly set.

[0409] The fourth abnormal operating condition 2204 describes a detection failure scenario where the detection device fails to trigger a state switch of the controlled equipment after a human body enters the detection space. This situation typically occurs when the user expects the controlled equipment to automatically start or switch states when a human body enters a specific area, but the detection device fails to detect the human body entering the area in a timely manner, causing the equipment not to start or work as expected. For example, the detection device may fail to effectively sense the entry of a human body, or its sensitivity may be insufficient to trigger a response from the detection device.

[0410] Furthermore, when the target operating condition description item is the third abnormal operating condition 2203, based on the analysis of the current detection status of the detection device and the output of a predetermined solution, it further includes responding to the user's trigger command for the third abnormal operating condition 2203 and performing fault diagnosis analysis, wherein:

[0411] If the detection status data indicates that someone is in the detection space, an abnormal diagnostic result containing a status conflict flag is generated. This flag indicates that the current detection status of a human body conflicts with the user's expected status. For example, the user expects the detection device to shut down the controlled equipment when a person leaves, but the detection status still indicates that someone is in the detection space. This means that the detection device failed to detect the departure of the person in a timely or accurate manner.

[0412] If the detection status data indicates that the detection space is empty, but the historical human presence status indicates that someone is present, a diagnostic result containing a data transmission anomaly flag is generated. This flag indicates that the current detected human presence status is inconsistent with the cloud storage, suggesting a possible data transmission delay, transmission error, or other issue causing untimely synchronization between the detection device and the cloud. In this case, although the detection device considers the detection space empty, the cloud storage status indicates that someone is present, suggesting a possible transmission error (e.g., packet loss).

[0413] If both the detection status data and historical human presence status indicate that the detection space is empty, a confirmation message indicating that the detection device is operating normally is generated. In this case, both the local detection device and the cloud consistently indicate that the detection space is empty, the detection device is operating normally, and data transmission is normal. That is, the detection device correctly senses the absence of a human in the detection space. If the controlled device's response is not as expected, it may be due to other reasons unrelated to the human presence status or data transmission status of the detection device.

[0414] Based on this, when generating anomaly diagnostic results that include state conflict identifiers, at least one of the following parameter adjustment items is provided:

[0415] This provides adjustment options for radar sensitivity parameters, used to adjust radar sensitivity; these include preset level selection and custom adjustment. For a detailed understanding and implementation of preset level selection and custom adjustment, please refer to the description in the above embodiments, which will not be repeated here. The configuration guidance information carried by the radar sensitivity parameter adjustment options displays parameter adjustment suggestions to reduce radar sensitivity.

[0416] An adjustment option for the "no one present" determination window parameter is provided to adjust the "no one present" determination window. The "no one present" determination window represents the continuous state detection time required to determine whether a state is occupied or unoccupied; that is, the shortest duration for which the detection device does not detect any human feature signals. Only after this time will the detection device determine that the detection space is unoccupied and switch to an unoccupied state. This adjustment option captures user parameter input and adjusts the "no one present" determination window accordingly. For example, in some application scenarios, users may want the detection device to quickly switch to an unoccupied state (e.g., automatically turning off lights), in which case the "no one present" determination window can be shortened; while in other scenarios, users may want the device to be more lenient in determining the "no one present" state, thus avoiding false judgments due to short periods of undetected presence, in which case the "no one present" determination window can be appropriately extended.

[0417] For specific examples, such as Figure 35As shown, if the third abnormal condition 2203 describes the detection abnormal scenario of "leaving the room without turning off the lights", the system responds to the user's selection of the title "leaving the room without turning off the lights" and enters the corresponding condition confirmation interface 3500. This interface 3500 displays the working status of the human body sensor in a specific environment through a scene diagram (as shown in the image and text) and provides a control for entering the detection process (as shown in the "Fault Cause Detection" control). The terminal device responds to the user's trigger command to the "Fault Cause Detection" control and enters the detection preparation interface 3501. The terminal device responds to the user's trigger command to the "Start Detection" control and triggers the active detection request. At this time, the terminal device enters the detection process, based on the previous preparation steps, and begins the actual acquisition and analysis of detection status data, ultimately obtaining the detection result. If the detection result is normal (the detection status data of the detection device indicates no one is present), confirmation information that the detection device is operating normally is obtained (as shown in interface 3502). If the detection status data indicates that someone is in the detection space, an abnormal diagnostic result containing a status conflict identifier is generated, such as... Figure 36 As shown, adjustment items 35041 for radar sensitivity parameters and 35042 for unmanned presence determination window parameters are provided. The configuration guidance information for adjustment item 35041 for radar sensitivity parameters suggests "reducing radar sensitivity", while the configuration guidance information for adjustment item 35042 for unmanned presence determination window parameters suggests "reducing unmanned determination time".

[0418] In some embodiments, when the target operating condition description item is the fourth abnormal operating condition 2204, the analysis and output of a predetermined solution based on the current detection status of the detection device further includes, in response to the user's trigger command for the fourth abnormal operating condition 2204, performing fault diagnosis analysis, wherein:

[0419] If the detection status data indicates that the detection space is empty, an abnormal diagnostic result containing a status conflict flag is generated. This flag indicates that the current detection status of a human body detected by the detection device conflicts with the user's expected status. For example, the user expects the detection device to activate the controlled equipment when a human body enters the detection space, but the detection device's detection status still indicates that the detection space is empty. This means that the detection device failed to detect the entry of a human body in a timely or accurate manner.

[0420] When generating an anomaly diagnostic result containing a status conflict identifier, an adjustment option for the radar sensitivity parameter is provided for adjusting the radar sensitivity; this includes preset level selection and custom adjustment. Furthermore, the configuration guidance information carried by the radar sensitivity parameter adjustment option at this time displays parameter adjustment suggestions for modifying the radar sensitivity (e.g., suggesting increasing sensitivity).

[0421] If the detected status data indicates that someone is in the detected space, but the historical human presence status indicates that no one is present, a diagnostic result containing a data transmission anomaly flag is generated. This flag indicates that the current detected human presence status is inconsistent with the cloud storage, suggesting a possible data transmission delay, transmission error, or other issue causing untimely synchronization between the detection device and the cloud. In this case, although the detection device believes someone is in the detected space, the cloud storage status indicates that the detected space is empty, suggesting a possible transmission error (e.g., packet loss).

[0422] If both the detected status data and historical human presence data indicate that someone is in the detection space, a confirmation message indicating that the detection device is operating normally is generated. In this case, both the local detection device and the cloud consistently indicate that someone is in the detection space, and that the detection device and data transmission are normal. That is, the detection device correctly senses a human body in the detection space. If the controlled device's response is not as expected, it may be due to other reasons and is unrelated to the human presence status or data transmission status of the detection device.

[0423] For specific examples, such as Figure 37 As shown, if the fourth abnormal condition 2204 describes the abnormal detection scenario of "entering a room but not turning on the lights," the system responds to the user's selection of the title "entering a room but not turning on the lights" and enters the corresponding condition confirmation interface 3700. This interface 3700 displays the working status of the human body sensor in a specific environment through a scene diagram (as shown in the image) and provides a control for entering the detection process (as shown in the "Fault Cause Detection" control). The terminal device responds to the user's trigger command to the "Fault Cause Detection" control and enters the detection preparation interface 3701. The terminal device responds to the user's trigger command to the "Start Detection" control and triggers the active detection request. At this time, the terminal device enters the detection process, based on the previous preparation steps, and begins the actual acquisition and analysis of detection status data, ultimately obtaining the detection result. If the detection result is normal (the detection status data of the detection device indicates that someone is present), confirmation information that the detection device is operating normally is obtained (as shown in interface 3702). If the detection status data indicates that the detection space is empty, an abnormal diagnostic result containing a status conflict identifier is generated, such as... Figure 38 As shown, adjustment item 37041 for radar sensitivity parameters is provided, and the configuration guidance information in the title suggests "view and modify sensor sensitivity".

[0424] In some embodiments, the method 210 further includes:

[0425] Retrieve a pre-stored set of frequently asked questions; wherein each question item in the set of frequently asked questions is associated with a pre-defined solution document; the solution document includes:

[0426] Technical problem description text: Briefly describe the technical problem encountered by the user, helping the user quickly understand the background and cause of the problem;

[0427] Principle Explanation: Provides a detailed explanation of the technical principles underlying the problem, helping users gain a deeper understanding of its technical details; and / or,

[0428] Operation guide: Provides specific solutions or operating procedures to guide users in troubleshooting or adjusting equipment;

[0429] In response to the user's selection of specific common questions, the corresponding solution content is displayed.

[0430] When a user selects a specific frequently asked question, the terminal device displays a complete solution document corresponding to that question, including a description of the technical problem, an explanation of the underlying principles, and / or operating instructions. In this way, users can quickly obtain relevant solutions to resolve problems or adjust device settings.

[0431] In some embodiments, the method 210 further includes:

[0432] In response to the user's selection of the installation guide, a multi-level interface gradually guides the user to configure the detection device according to a predetermined logic. For example, this can be achieved through... Figure 30 The installation guide steps shown gradually guide the user through the setup and calibration of the testing device. Specific installation instructions can be found in the accompanying diagrams; further details are omitted here.

[0433] Based on the above method 210, an embodiment of this disclosure also provides a terminal device, which can be applied to, for example... Figure 1 The human body detection system shown, or the terminal device used in it.

[0434] like Figure 31 As shown, the terminal device includes a working condition description unit, a parameter adjustment unit, and a data transmission unit.

[0435] The operating condition description unit is used to display at least one operating condition description item in response to a first user operation; each operating condition description item describes at least one detection anomaly scenario; each operating condition description item is mapped to at least one adjustable detection parameter, the detection parameter being used to adjust the detection response characteristics of the detection device.

[0436] The parameter adjustment unit is used to respond to the user's trigger command for the target working condition description item and display at least one parameter adjustment item, which forms a direct operational binding relationship with the mapped detection parameters.

[0437] The data distribution unit is used to capture the user's parameter input through the parameter adjustment item, and perform a reconfiguration operation on the detection response characteristics of the detection device based on the input.

[0438] In some embodiments, after responding to a user's trigger command for a target operating condition description item, the parameter adjustment unit is further configured to:

[0439] Display semantically rendered content, including at least one of the following:

[0440] The typical detection scenarios corresponding to the target working condition description items are displayed graphically.

[0441] This section explains the impact of adjusting each parameter on the detection response characteristics of the detection device.

[0442] Based on the current detection status analysis of the detection device, a predetermined solution is output.

[0443] In some embodiments, after responding to a user's trigger command for a target operating condition description item, the parameter adjustment unit is further configured to:

[0444] The semantic presentation content and the parameter adjustment items are arranged on the same interactive interface.

[0445] In some embodiments, generating and displaying a graphical representation of a typical detection scenario corresponding to the target working condition description item is specifically used for:

[0446] Generate and display a dynamic schematic diagram of the working condition described by the target working condition description item; and / or,

[0447] Calculate and predict the simulation effect of changes in detection response characteristics under the adjustment of the map's adjustable parameters, and generate and display the simulation graph of the parameter adjustment effect.

[0448] In some embodiments, the title of the parameter adjustment item also serves as an operable control;

[0449] The aforementioned display of at least one parameter adjustment item is specifically used for:

[0450] The configuration guidance information is displayed in the title of the parameter adjustment item; the configuration guidance information refers to the suggested content generated based on the detection anomaly scenario corresponding to the target working condition description item, which is used to guide users to optimize parameter settings;

[0451] The method of capturing user parameter input through the parameter adjustment item specifically includes:

[0452] In response to the title being manipulated, the user is directly redirected to the parameter adjustment interface of the detection parameters that form a direct operation binding relationship.

[0453] In some embodiments, when the target operating condition description item is a first abnormal operating condition, the parameter adjustment unit is specifically used for:

[0454] It provides adjustment options for operating mode parameters, which can be used to switch between fusion detection mode and pure radar mode;

[0455] Provides adjustment options for radar sensitivity parameters, used to adjust radar sensitivity;

[0456] Provides an adjustment option for the infrared sensitivity parameter, used to determine the infrared sensitivity based on user selection when the operating mode is a fusion detection mode; and / or,

[0457] Provides adjustment options for the anti-interference level parameter, used to adjust the anti-interference level;

[0458] The first abnormal operating condition describes a detection failure scenario in which the detection device continuously triggers the switching of the working state of the controlled equipment when the device is unattended.

[0459] In some embodiments, when the target operating condition description item is a second abnormal operating condition, the parameter adjustment unit is specifically used for:

[0460] Provides adjustment options for radar sensitivity parameters, including preset level selection and custom adjustment; and / or,

[0461] An adjustment option is provided for the parameter of the no-man's-land determination window; the no-man's-land determination window represents the length of continuous state detection time required to determine the transition from a manned state to a manless state;

[0462] The second abnormal operating condition describes a detection failure scenario in which the detection device fails to maintain the controlled equipment in the open state when a person is present.

[0463] Based on the above method 210, an embodiment of this disclosure also provides a human body detection processing method, applied to a detection device. For example... Figure 32 As shown, the method 320 includes at least S320 and S321.

[0464] In step S320, the detection device 100 acquires detection parameters.

[0465] The detection parameters are sent by the terminal device after capturing the user's parameter input through parameter adjustment items; the parameter adjustment items are at least one parameter adjustment items displayed by the terminal device in response to the user's trigger command for the target operating condition description item; the target operating condition description item is the operating condition description item selected by the user from at least one operating condition description item displayed by the terminal device in response to the user's first operation; wherein, each operating condition description item describes at least one detection abnormal scenario; each operating condition description item establishes a mapping relationship with at least one adjustable detection parameter, and the detection parameter is used to adjust the detection response characteristics of the detection device.

[0466] In step S321, the detection device 100 performs a reconfiguration operation on the detection response characteristics using the detection parameters.

[0467] In some embodiments, obtaining detection parameters includes at least one of the following:

[0468] Obtain working mode parameters; the working mode parameters are sent by the terminal device after capturing the user's selection of a predetermined working mode through the adjustment items of the working mode parameters;

[0469] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters.

[0470] Acquire infrared sensitivity parameters; these infrared sensitivity parameters are obtained by the terminal device after capturing the user's adjustment of the infrared sensitivity through the adjustment items of the infrared sensitivity parameters.

[0471] Obtain anti-interference level parameters; the anti-interference level parameters are obtained by the terminal device after capturing the user's adjustment of the anti-interference level by providing adjustment items for the anti-interference level parameters.

[0472] The adjustment items for the working mode parameter, the radar sensitivity parameter, the infrared sensitivity parameter, and / or the anti-interference level parameter are provided by the terminal device in response to the user's selection of the first abnormal working condition. The first abnormal working condition is used to describe the detection failure scenario in which the detection device continuously triggers the switching of the working state of the controlled device in an unmanned state.

[0473] In some embodiments, obtaining detection parameters includes at least one of the following:

[0474] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters.

[0475] Obtain the no-man's-existence determination window parameters; the no-man's-existence determination window parameters are captured by the terminal device after capturing the user's adjustment of the no-man's-existence determination window through the adjustment items of the no-man's-existence determination window parameters and sent; the no-man's-existence determination window represents the length of continuous state detection time required to determine the switch from manned state to no-man's-existence state;

[0476] The adjustment terms of the radar sensitivity parameter and / or the adjustment terms of the unmanned presence determination window parameter are provided by the terminal device in response to the user's selection of the second abnormal working condition. The second abnormal working condition is used to describe the detection failure scenario in which the detection device fails to maintain the controlled equipment in the state of being occupied.

[0477] Based on the above method 320, an embodiment of this disclosure also provides a detection device, such as... Figure 33 As shown, the detection device includes a detection parameter acquisition unit and a response characteristic configuration unit.

[0478] The detection parameter acquisition unit is used to acquire detection parameters.

[0479] The detection parameters are sent by the terminal device after capturing the user's parameter input through parameter adjustment items; the parameter adjustment items are at least one parameter adjustment items displayed by the terminal device in response to the user's trigger command for the target operating condition description item; the target operating condition description item is the operating condition description item selected by the user from at least one operating condition description item displayed by the terminal device in response to the user's first operation; wherein, each operating condition description item describes at least one detection abnormal scenario; each operating condition description item establishes a mapping relationship with at least one adjustable detection parameter, and the detection parameter is used to adjust the detection response characteristics of the detection device.

[0480] The response characteristic configuration unit is used to perform a reconfiguration operation on the detection response characteristics using the detection parameters.

[0481] In some embodiments, the detection parameter acquisition unit acquires detection parameters, specifically for acquiring at least one of the following parameters:

[0482] Obtain working mode parameters; the working mode parameters are sent by the terminal device after capturing the user's selection of a predetermined working mode through the adjustment items of the working mode parameters;

[0483] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters.

[0484] Acquire infrared sensitivity parameters; these infrared sensitivity parameters are obtained by the terminal device after capturing the user's adjustment of the infrared sensitivity through the adjustment items of the infrared sensitivity parameters.

[0485] Obtain anti-interference level parameters; the anti-interference level parameters are obtained by the terminal device after capturing the user's adjustment of the anti-interference level by providing adjustment items for the anti-interference level parameters.

[0486] The adjustment items for the working mode parameter, the radar sensitivity parameter, the infrared sensitivity parameter, and / or the anti-interference level parameter are provided by the terminal device in response to the user's selection of the first abnormal working condition. The first abnormal working condition is used to describe the detection failure scenario in which the detection device continuously triggers the switching of the working state of the controlled device in an unmanned state.

[0487] In some embodiments, the detection parameter acquisition unit acquires detection parameters, specifically for acquiring at least one of the following parameters:

[0488] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters.

[0489] Obtain the no-man's-existence determination window parameters; the no-man's-existence determination window parameters are captured by the terminal device after capturing the user's adjustment of the no-man's-existence determination window through the adjustment items of the no-man's-existence determination window parameters and sent; the no-man's-existence determination window represents the length of continuous state detection time required to determine the switch from manned state to no-man's-existence state;

[0490] The adjustment terms of the radar sensitivity parameter and / or the adjustment terms of the unmanned presence determination window parameter are provided by the terminal device in response to the user's selection of the second abnormal working condition. The second abnormal working condition is used to describe the detection failure scenario in which the detection device fails to maintain the controlled equipment in the state of being occupied.

[0491] This disclosure also provides a human body detection processing method in one embodiment, aiming to solve the problems of low configuration efficiency and accuracy of detection devices in the prior art. Specifically, the human body detection processing method provided by this invention has self-diagnostic capabilities for its working state, and, in conjunction with user-input commands, adjusts the detection response characteristics of the detection device in real time, enabling dynamic adjustment of the detection device's performance according to the actual operating state. Figure 34 The diagram shown is a schematic flowchart illustrating a human body detection and processing method provided in this embodiment. It can be seen that the human body detection and processing method 340 includes at least steps S340 to S343.

[0492] In step S340, the terminal device responds to the user's active detection request and obtains the detection status data of the detection device.

[0493] Specifically, before acquiring the detection status data from the detection device, a data transmission channel with the detection device must be established in advance. This channel needs to have efficient and stable data transmission capabilities, capable of transmitting large amounts of data in real time to ensure the timeliness and accuracy of the detection results.

[0494] Furthermore, the detection device can be a continuously powered device based on high-voltage power supply, which remains in a continuously connectable state after power-on, facilitating the establishment of a data transmission channel between the terminal device and the detection device at any time. Specifically, the data transmission channel can be a point-to-point direct connection channel, such as Bluetooth Direct. The detection device can adopt a continuously powered high-voltage power supply to ensure that it is always in a connectable state after power-on. When the terminal device responds to an active detection request initiated by the user, it can directly establish a point-to-point direct data transmission channel with the detection device and obtain the detection status data of the detection device in real time based on this channel.

[0495] A user-initiated proactive detection request can be understood as a user requesting the detection device to perform status detection through the user interface of the terminal device. For example, the user can trigger the detection device to start working and obtain detection status data by pressing the "Detect" button on the terminal device or selecting the corresponding function in the mobile application.

[0496] Detection status data typically includes various information related to the target object, such as the presence of a human body, used to characterize whether a human body is present in the detection space. Other possible detection status data may include data related to environmental conditions, such as temperature, humidity, and light intensity.

[0497] In step S341, the terminal device performs fault diagnosis analysis on the detection status data based on the set diagnostic rules.

[0498] Specifically, the established diagnostic rules can be understood as a predefined set of rules that includes analytical logic for different detection states. For example, these rules may include assessments of the consistency between the detection state data and the expected data, or assessments of the fluctuation range of the detection state data.

[0499] Based on the established diagnostic rules, after analyzing the detection status data, the diagnostic analysis result may be one of several preset outcomes. Specifically, these outcomes include, but are not limited to:

[0500] Abnormal diagnostic analysis results: This indicates that there are abnormalities in the detection status data, such as the detection device failing to correctly identify the presence of a human body.

[0501] Normal diagnostic analysis results: This indicates that the test status data meets the expected standards and the testing device is in normal working condition.

[0502] Based on the diagnostic analysis results, the terminal device will selectively proceed to step S342 or S343.

[0503] In step S342, the terminal device detects and responds to the user's input command on the diagnostic analysis result, and performs active service control; the active service control is used to capture the parameter input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, and to perform a reconfiguration operation on the detection response characteristics of the detection device based on the input; the parameter adjustment item forms a direct operation binding relationship with at least one adjustable detection parameter; the detection parameter is used to adjust the detection response characteristics of the detection device.

[0504] Specifically, users can input specific parameter values ​​to adjust the working status of the detection device in response to diagnostic analysis results.

[0505] The parameter adjustment item is directly operationally bound to at least one adjustable detection parameter. Specifically, the detection response characteristics include response characteristics associated with abnormal detection scenarios. For example, when the detection device falsely reports or fails to detect the presence of a human body, the detection response characteristics may include parameters such as sensitivity and false trigger suppression. These parameters can be adjusted according to user input instructions to optimize the performance of the detection device in that specific environment.

[0506] In this step, users do not need professional technical knowledge to complete the precise configuration of the detection device, thereby realizing closed-loop control of "diagnosis-adjustment".

[0507] In step S343, the terminal device generates confirmation information that the detection device is operating normally based on the normal diagnostic analysis results. Furthermore, after diagnosing any faults in the detection device and confirming its normal status, the terminal device generates feedback information and presents it to the user. This confirmation information can be displayed through a graphical interface, informing the user that the device is functioning well, avoiding manual intervention and improving the user experience.

[0508] Furthermore, the human body detection processing method provided in this embodiment of the present disclosure, by realizing active detection and adaptive adjustment, can effectively improve the diagnostic capabilities and fault response speed of the equipment. Combined with user-input commands, the detection device can adjust its detection response characteristics in real time based on diagnostic analysis results, thereby ensuring its good performance under different operating environments.

[0509] This method allows users to easily trigger fault diagnosis and adjust parameter settings based on feedback, thereby improving the stability and response speed of the device. Furthermore, by directly linking parameter adjustment items to detection characteristics, a "diagnosis-adjustment" closed loop is formed, facilitating adjustment operations and simplifying device maintenance and configuration, significantly improving the efficiency and reliability of the detection device.

[0510] In summary, the technical solutions provided by the embodiments of this disclosure can improve the working efficiency of the detection device, enhance its stability and adaptability, and reduce maintenance costs and fault response time, providing users with an efficient, convenient and intelligent configuration solution.

[0511] In some embodiments, step S340, in response to a user-initiated active detection request, includes steps S3401 and S3402.

[0512] In step S3401, as follows Figure 22 As shown, in response to the user's first operation, the terminal device displays at least one operating condition description item; each of the operating condition description items describes at least one detection anomaly scenario.

[0513] Specifically, a working condition description item can be understood as a predefined technical description unit used to characterize a specific abnormal working state of the detection device. Each working condition description item describes different possible abnormal scenarios, serving as a reference for users to diagnose and configure the detection device. An abnormal detection scenario can be understood as an unexpected working state exhibited by the detection device under specific environmental conditions. For example, some working condition description items may correspond to false triggering in an unmanned state, that is, the detection device erroneously triggers the operation of the controlled equipment even when no human is present.

[0514] Furthermore, before responding to the user's first action and displaying the operating condition description items, the method further includes: acquiring a scalable operating condition description database, which stores multiple preset operating condition description items. The operating condition description items can be stored as structured data, for example, through database tables or cloud storage, to ensure that these operating condition description items can be flexibly accessed and updated according to different environments and needs.

[0515] Furthermore, in some embodiments, the operating condition description database can be flexibly expanded to support the addition of specific operating condition description items. These new items are particularly suitable for detection applications under different detection anomaly scenarios, such as differences between indoor and outdoor environments, different equipment configurations, or adaptation after equipment upgrades. This flexibility allows the detection device to be continuously optimized and adjusted according to actual conditions, ensuring its effectiveness in diverse environments.

[0516] In step S3402, the terminal device responds to the user's trigger command for the target operating condition description item and enters the guidance interface to trigger the active detection request.

[0517] Specifically, the target operating condition description item refers to the operating condition description item selected by the user from multiple operating condition description items. This guidance page can be understood as a guide page, used to help the user select and / or confirm the required operating condition description item. This guidance page can be a single-level page or a multi-level progressive page, ultimately helping the user trigger the aforementioned active detection request. In this way, users can easily select the expected abnormal detection scenario and complete the detection request through a clear operation process.

[0518] Furthermore, in this embodiment, the user first selects the desired operating condition description item, and then triggers the corresponding active detection request. This two-layer filtering mechanism not only more accurately identifies the user's abnormal scenarios but also effectively addresses the user's specific needs, thereby improving the accuracy of detection device configuration and fault diagnosis.

[0519] Further, in step S3402, in response to the user's trigger command for the target working condition description item, the guide interface is entered to trigger the active detection request; including steps S34021 to S34023.

[0520] Step S34021: Enter the operating condition confirmation interface.

[0521] In step S34021, the terminal device responds to the user's trigger command for the target operating condition description item and enters the operating condition confirmation interface. The operating condition confirmation interface includes semantically presented content and a detection process entry control. The semantically presented content describes the detection anomaly scenario to be detected.

[0522] Specifically, semantic presentation content may include graphical representations (e.g., a scene diagram showing the operation of a human sensor in a specific environment) and / or textual descriptions (e.g., “The detection device failed to trigger the controlled device to shut down when no one is present”).

[0523] The detection process entry control is used to enter the detection process. This control is the interaction link between the user and the detection process. Clicking the control will start the subsequent detection process and guide the user to the next stage of operation.

[0524] For example, in some embodiments, the operational status confirmation interface may display a schematic diagram of a human body sensor, showing the sensor's behavior in "manned" and "unmanned" states. Combined with textual descriptions, users can clearly understand the abnormal situation indicated by the currently selected operational status description. Through this interface, users can further confirm whether to perform a detection operation.

[0525] Step S34022: Enter the detection preparation interface.

[0526] In step S34022, the terminal device responds to the user's trigger command to enter the detection process control and enters the detection preparation interface, which includes detection condition requirements and a detection start control.

[0527] The detection conditions are listed as conditions that must be met to perform the detection, including a description of the communication connection status of the detection device and a description of whether the target space is occupied or unoccupied.

[0528] The communication connection status description for the detection device requires the terminal device to establish a direct communication connection that meets quality requirements. Specifically, the communication connection must be stable and the data transmission must be accurate to ensure that subsequent data transmission is without delay or loss. Successful triggering of the active detection request requires the detection device to establish the correct communication connection according to the aforementioned communication connection status description.

[0529] The description of the presence / absence status of the target space is used to guide the user in confirming the status of the detection space and ensuring that environmental conditions are suitable for detection. For example, the detection device may need to confirm whether a human body is present in the detection space, or whether the environment meets the standard conditions for normal detection.

[0530] In this step, accurate descriptions and clear prompts regarding the detection conditions are crucial for the user. For example, the communication connection status description of the detection device could require the user to ensure that their phone and sensor are successfully paired via Bluetooth and that the signal strength is stable before triggering subsequent detection operations. If the communication connection does not meet the requirements, the user will receive a prompt guiding them to make the necessary adjustments.

[0531] Step S34023: Trigger an active detection request.

[0532] In step S34023, the terminal device responds to the user's trigger command to the detection start control, triggering the active detection request. At this time, the terminal device enters the detection process, and based on the previous preparation steps, begins the actual acquisition and analysis of detection status data.

[0533] Based on this, acquiring the detection status data of the detection device includes: acquiring real-time detection status data locally on the detection device via the direct communication connection. For example, the detection device provides real-time feedback on the presence status information of human beings in the current detection space (such as a person / no one indicator).

[0534] The reconfiguration operation of the detection response characteristics of the detection device based on the input includes: reconfiguring the detection response characteristics of the detection device in real time via a direct communication connection based on the input. For example, if a user inputs a command to enhance sensor sensitivity, the terminal device will adjust the sensitivity settings of the detection device in real time via a direct connection to ensure that the device adapts to changes in the current environment.

[0535] Furthermore, through the method provided in this disclosure, users can accurately identify abnormal scenarios and execute detection requests via a multi-layered interactive and guided interface. Each stage (such as operating condition confirmation and detection preparation) provides clear steps and feedback, ensuring the efficiency and accuracy of the detection process. Through real-time configuration and sensitivity adjustment, the detection device can adapt to different environmental conditions, achieving efficient fault detection and adjustment.

[0536] In some embodiments, each of the operating condition description items is associated with an objective actual state, which represents the actual presence of a human body in the detection space under the detection anomaly scenario corresponding to that operating condition description item, i.e., the actual state in the detection anomaly scenario corresponding to that operating condition description item. For example, if the detection anomaly scenario described by a certain operating condition description item is "the light cannot be turned on when someone is present," then the corresponding objective actual state is "someone is present," rather than the state actually perceived by the device (e.g., whether the device senses whether someone is present). In this case, although the actual state of the device may be "no one is present," in this scenario, the user expects the device to sense "someone is present," so fault diagnosis analysis is needed to compare whether the actual state of the device is consistent with the target objective actual state.

[0537] The fault diagnosis analysis in step S341 specifically includes S3411 and S3412.

[0538] In step S3411, the terminal device compares the human body presence status indicated by the detected status data with the objective actual status corresponding to the target working condition description item.

[0539] Specifically, the detection device acquires the current detection status data (such as whether there are people in the detection space) and then compares it with the preset objective actual status in the target working condition description. For example, if the target working condition description indicates that "the lights cannot be turned on when someone is present," but the actual detection status of the detection device is "no one is present," then a conflict of inconsistent status is considered to have occurred.

[0540] This comparison can determine whether the detection device has failed to accurately identify the presence of a human body, and thus make a decision on whether to adjust the detection parameters.

[0541] S3412. When the two are inconsistent (the physical state indicated by the detection state data is inconsistent with the objective actual state corresponding to the target working condition description item), generate an abnormal diagnosis result containing a state conflict identifier.

[0542] Specifically, a state conflict flag can be understood as a marker indicating a discrepancy between the operating state of the detection device and the user's expected target state. For example, if a user expects the detection device to trigger an action in a "personned" state, but the device actually detects an "unoccupied" state, this flag will be generated to alert the user that the device's current state does not match the actual situation. This flag helps to quickly pinpoint the problem, such as insufficient sensitivity preventing the detection of a "personned" state.

[0543] Based on this, when generating anomaly diagnostic results that include state conflict indicators, the output solution includes at least one parameter adjustment item. That is, the generated anomaly diagnostic results will be accompanied by one or more solutions, which may include parameter adjustment items, such as suggestions for adjusting sensitivity or detection thresholds, to help users resolve the problem of the detection device failing to detect the presence of a human body as expected.

[0544] Furthermore, when the human body status indicated by the detection status data is consistent with the objective actual status, it is further compared with the data in the target storage node outside the detection device, and a fault diagnosis analysis is performed based on the comparison results to confirm whether the two are updated synchronously; the data in the target storage node is synchronized to the target storage node in real time after the detection device acquires the detection status data.

[0545] Specifically, after acquiring the detection status data, the detection device not only stores it locally but also backs it up in real time to a target storage node to facilitate subsequent fault diagnosis and analysis. The target storage node includes, but is not limited to, local servers, cloud servers, edge computing devices, or other distributed storage systems, used to receive and persist the detection status data synchronized by the detection device.

[0546] Further comparison with data in the target storage node outside the detection device, and based on the comparison results, fault diagnosis analysis can be performed, which may include, for example:

[0547] When the human body presence status indicated by the detected status data matches the human body presence status indicated by the data in the target storage node, a confirmation message indicating that the detection device is operating normally is generated; otherwise, a diagnostic result containing a data transmission anomaly identifier is generated.

[0548] Taking a cloud server as an example, the data in the target storage node includes historical human presence status stored in the cloud. This historical human presence status is pre-reported by the detection device based on certain reporting conditions. The detection device uploads the detected human presence status to the cloud server for storage and subsequent analysis. These reporting conditions may specifically include timed conditions and / or triggering conditions to ensure timely data updates and accurate synchronization. Wherein:

[0549] Timing conditions: This refers to the detection device periodically uploading human presence data to the cloud at preset time intervals. For example, the detection device automatically uploads the current human presence status in the detection space every minute to ensure that the data in the cloud reflects the current working status of the device.

[0550] Triggering condition: This refers to the condition where the detection device immediately uploads the changed data to the cloud when the presence of a human changes (e.g., from "no one" to "someone," or vice versa). This condition ensures the real-time nature of the detection status, especially when important events are detected (such as a human entering or leaving the detection space), enabling timely data synchronization.

[0551] Under normal circumstances, the detection device continuously synchronizes data with the cloud to ensure that the human presence status stored in the cloud is consistent with the real-time human presence status of the detection device. If the detection device is operating normally and there is no network latency or interruption, the data stored in the cloud should always remain synchronized with the data in the detection device.

[0552] The detection device connects to the cloud via wireless communication methods such as Bluetooth, Wi-Fi, and Zigbee, or wired communication methods such as power line communication (PLC). Terminal devices connect to the cloud via cellular data, Wi-Fi, or other means. Through the terminal device's application, users can access and retrieve historical human presence data stored in the cloud in real time. This allows users to view the device's operational history and analyze and compare changes in human presence over different time periods.

[0553] If the detected status data matches the objective reality of the target, the terminal device will proceed to step S3413 to perform a cloud verification operation to further confirm whether the detection device is operating normally. Furthermore, the method also includes S3413: when the human body's presence indicated by the detected status data matches the objective reality, cloud verification steps S34131 and S34132 are executed.

[0554] Step S34131: Retrieve cloud data. In step S34131, the terminal device retrieves the historical human presence status stored in the cloud.

[0555] In step S34132, the terminal device compares the consistency between the human body presence status indicated by the detection status data and the historical human body presence status; when the status is inconsistent, a diagnostic result containing a data transmission anomaly identifier is generated; when the status is consistent, confirmation information that the detection device is operating normally is generated.

[0556] Specifically, the terminal device compares the human presence status indicated by the detected status data with the historical human presence status stored in the cloud. If they match, it indicates that the data reporting is normal, and a confirmation message indicating that the detection device is operating normally is generated. If they do not match, it indicates a data transmission problem, and a diagnostic result containing a data transmission anomaly identifier is generated.

[0557] A data transmission anomaly flag indicates a communication problem between the detection device and the cloud, preventing the current detection status from being synchronized with the cloud in a timely manner. Possible causes include network problems, data loss, or communication interruption.

[0558] Furthermore, when generating diagnostic results that include data transmission anomaly indicators, the output solution does not include parameter adjustment items. In this case, the solution may focus on network diagnostics, such as advising the user to check the device's network connectivity to ensure stable data transmission.

[0559] Furthermore, the solution provided in this disclosure, by comparing the detection status of the detection device with the actual objective state of the target, can quickly identify situations where the detection device fails to recognize the presence of a human body as expected, and provide appropriate solutions. Simultaneously, the cloud verification step further enhances accuracy. When data transmission problems occur, solutions can be quickly identified and provided, reducing device malfunctions caused by data loss or transmission delays.

[0560] It is worth mentioning that when the target storage node is a cloud server, the detection status data sent by the detection device is also used to trigger the cloud server to query a pre-set control rule library based on the human body presence status indicated by the received detection status data. This allows the cloud server to generate corresponding device control instructions based on the query results, and then send the device control instructions to at least one controlled device connected to the cloud, so that the controlled device performs the corresponding function. The control rule library pre-stores the correspondence between human body presence status and device control instructions (indicating at least one executable function of at least one controlled device) (i.e., control rules), and the device control instructions are used to control specific functions of the controlled device.

[0561] Furthermore, the control rule base stores the correspondence between human body status and device control commands, which is freely defined by the user in advance through the terminal device.

[0562] Furthermore, the title of the parameter adjustment item also serves as an operable control.

[0563] Specifically, the parameter adjustment item not only serves as descriptive text, but also possesses interactive functionality. Users can directly access the settings interface related to the response detection parameters by clicking or manipulating the title, and then adjust the parameters accordingly. Through this design, the title text and interactive controls are integrated into a dual-function interface element, which not only simplifies the user's operation steps but also allows users to make configuration adjustments more intuitive and convenient.

[0564] The output solution includes at least one parameter adjustment item, specifically including:

[0565] Configuration guidance information is displayed in the title of the parameter adjustment item; the configuration guidance information refers to the suggestions generated based on the diagnostic results to guide users in optimizing parameter settings.

[0566] Specifically, the configuration guidance information will be customized based on the specific fault diagnosis results to guide users in making targeted parameter adjustments. The configuration guidance information may include concise text descriptions, recommended settings, or solutions for specific common problems, helping users quickly understand how to adjust parameters to deal with abnormal situations under specific operating conditions.

[0567] Among these, the configuration guidance information differs for the same parameter adjustment item triggered by different operating condition descriptions. For example, for the scenario of "frequent on / off switching of lights by unmanned personnel," the parameter adjustment item provided for this scenario is sensitivity parameter adjustment item 22013, and the corresponding configuration guidance information is a suggestion to "reduce radar sensitivity" (e.g., ...). Figure 23 (As shown); For the scenario of "someone is here but the lights are off", the provided parameter adjustment item may still be the sensitivity parameter adjustment item 22021, but the corresponding configuration guidance information suggests "increasing radar sensitivity" (e.g. Figure 27 As shown in the diagram, different operating condition descriptions may offer the same parameter adjustment options, but the corresponding configuration guidance information may differ. The terminal device will generate corresponding configuration guidance information based on the diagnostic results. Therefore, for each specific operating condition description, the user will receive relevant customized suggestions (which are reflected in the configuration guidance information) to ensure that the parameter settings are adjusted to meet actual needs.

[0568] The configuration guidance information is generated based on diagnostic results and serves as a suggestion to help users optimize parameter settings. This information can provide concise and clear text descriptions, recommended parameter settings, or guidance including common problems and solutions, depending on the specific testing device and operating condition characteristics. This intuitive and concise guidance allows users to understand how to adjust parameters in the shortest possible time, avoiding misoperation or improper settings, while simultaneously increasing user trust in the equipment and operational satisfaction.

[0569] The method of capturing user parameter input through the parameter adjustment item specifically includes:

[0570] In response to the title being manipulated, the user is directly redirected to the parameter adjustment interface of the adjustable detection parameters that form a direct operation binding relationship.

[0571] Specifically, when a user interacts with a parameter adjustment item title (such as clicking, swiping, or selecting), the terminal device instantly captures the user's input and transmits it to the device's detection parameter adjustment interface. In this interface, the user can see detailed adjustable parameters bound to the current title and adjust them using intuitive controls. A direct operational binding relationship is established between each parameter adjustment item and the detection parameter; that is, the user's adjustment input will affect the corresponding detection parameter in real time, thereby directly changing the response characteristics of the detection device.

[0572] When a user adjusts a parameter heading, the terminal device will automatically redirect to the relevant parameter adjustment interface based on the detection parameters associated with that heading. This interface will display detailed adjustable parameters and corresponding adjustment controls (such as sliders, input boxes, and selection buttons) to allow the user to precisely adjust the detection parameters. This design centralizes the processing of related configuration settings, improves user efficiency, and reduces the complexity of switching between multiple interfaces and operations.

[0573] Furthermore, the method provided in this disclosure allows users to quickly and accurately adjust various detection parameters of the device within the same interface, making the overall operation simpler and more efficient, while avoiding complex menu hierarchies and multi-step operation processes.

[0574] In some embodiments, such as Figure 22 As shown, the operating condition description item includes a third abnormal operating condition 2203 and / or a fourth abnormal operating condition 2204.

[0575] The third abnormal operating condition, 2203, describes a detection failure scenario where the detection device fails to trigger a state switch in the controlled equipment after a human body leaves the detection space. This situation typically occurs when the user expects the controlled equipment to automatically shut down or switch states after a human body leaves a certain area, but the detection device fails to detect the human body's departure in time, resulting in the equipment not undergoing the expected state change. Specifically, the detection device may not have detected the human body's departure in time, or its sensitivity may not have met the trigger conditions, leading to a failure to respond correctly. This situation may occur when there is significant environmental interference or when the device parameters are improperly set.

[0576] The fourth abnormal operating condition 2204 describes a detection failure scenario where the detection device fails to trigger a state switch of the controlled equipment after a human body enters the detection space. This situation typically occurs when the user expects the controlled equipment to automatically start or switch states when a human body enters a specific area, but the detection device fails to detect the human body entering the area in a timely manner, causing the equipment not to start or work as expected. For example, the detection device may fail to effectively sense the entry of a human body, or its sensitivity may be insufficient to trigger a response from the detection device.

[0577] Furthermore, when the target operating condition description item is the third abnormal operating condition 2203, the method 340 further includes responding to the user's trigger command for the third abnormal operating condition 2203 and performing fault diagnosis analysis, wherein:

[0578] If the detection status data indicates that someone is in the detection space, an abnormal diagnostic result containing a status conflict flag is generated. This flag indicates that the current detection status of a human body conflicts with the user's expected status. For example, the user expects the detection device to shut down the controlled equipment when a person leaves, but the detection status still indicates that someone is in the detection space. This means that the detection device failed to detect the departure of the person in a timely or accurate manner.

[0579] If the detection status data indicates that the detection space is empty, but the historical human presence status indicates that someone is present, a diagnostic result containing a data transmission anomaly flag is generated. This flag indicates that the current detected human presence status is inconsistent with the cloud storage, suggesting a possible data transmission delay, transmission error, or other issue causing untimely synchronization between the detection device and the cloud. In this case, although the detection device considers the detection space empty, the cloud storage status indicates that someone is present, suggesting a possible transmission error (e.g., packet loss).

[0580] If both the detection status data and historical human presence status indicate that the detection space is empty, a confirmation message indicating that the detection device is operating normally is generated. In this case, both the local detection device and the cloud consistently indicate that the detection space is empty, the detection device is operating normally, and data transmission is normal. That is, the detection device correctly senses the absence of a human in the detection space. If the controlled device's response is not as expected, it may be due to other reasons unrelated to the human presence status or data transmission status of the detection device.

[0581] Based on this, when generating anomaly diagnostic results that include state conflict identifiers, at least one of the following parameter adjustment items is provided:

[0582] This provides adjustment options for radar sensitivity parameters, used to adjust radar sensitivity; these include preset level selection and custom adjustment. For a detailed understanding and implementation of preset level selection and custom adjustment, please refer to the description in the above embodiments, which will not be repeated here. The configuration guidance information carried by the radar sensitivity parameter adjustment options displays parameter adjustment suggestions to reduce radar sensitivity.

[0583] An adjustment option for the "no one present" determination window parameter is provided to adjust the "no one present" determination window. The "no one present" determination window represents the continuous state detection time required to determine whether a state is occupied or unoccupied; that is, the shortest duration for which the detection device does not detect any human feature signals. Only after this time will the detection device determine that the detection space is unoccupied and switch to an unoccupied state. This adjustment option captures user parameter input and adjusts the "no one present" determination window accordingly. For example, in some application scenarios, users may want the detection device to quickly switch to an unoccupied state (e.g., automatically turning off lights), in which case the "no one present" determination window can be shortened; while in other scenarios, users may want the device to be more lenient in determining the "no one present" state, thus avoiding false judgments due to short periods of undetected presence, in which case the "no one present" determination window can be appropriately extended.

[0584] For specific examples, such as Figure 35 As shown, if the third abnormal condition 2203 describes the abnormal detection scenario of "leaving the room without turning off the lights", the user selects the title "leaving the room without turning off the lights" and enters the corresponding condition confirmation interface 3500. This interface 3500 displays the working status of the human body sensor in a specific environment through a scene diagram (as shown in the figure) and provides a detection process entry control (as shown in the figure's "fault cause detection" control). The terminal device responds to the user's trigger command to the "fault cause detection" control and enters the detection preparation interface 3501. The terminal device responds to the user's trigger command to the "start detection" control and triggers the active detection request. At this time, the terminal device will enter the detection process, based on the previous preparation steps, and begin to acquire and analyze the actual detection status data, and finally obtain the detection result. If the detection result is normal (the detection status data of the detection device indicates that no one is there), the user obtains confirmation information that the detection device is operating normally (as shown in interface 3502). Furthermore, the user can view the specific detection status data (as shown in interface 3504). If the detection status data indicates that someone is in the detection space, an abnormal diagnosis result containing a status conflict identifier is generated, such as... Figure 36 As shown, adjustment items 35041 for radar sensitivity parameters and 35042 for unmanned presence determination window parameters are provided. The configuration guidance information for adjustment item 35041 for radar sensitivity parameters suggests "reducing radar sensitivity", while the configuration guidance information for adjustment item 35042 for unmanned presence determination window parameters suggests "reducing unmanned determination time".

[0585] In some embodiments, when the target operating condition description item is the fourth abnormal operating condition 2204, the method further includes performing fault diagnosis analysis in response to a user's trigger command for the fourth abnormal operating condition 2204, wherein:

[0586] If the detection status data indicates that the detection space is empty, an abnormal diagnostic result containing a status conflict flag is generated. This flag indicates that the current detection status of a human body detected by the detection device conflicts with the user's expected status. For example, the user expects the detection device to activate the controlled equipment when a human body enters the detection space, but the detection device's detection status still indicates that the detection space is empty. This means that the detection device failed to detect the entry of a human body in a timely or accurate manner.

[0587] When generating an anomaly diagnostic result containing a status conflict identifier, an adjustment option for the radar sensitivity parameter is provided for adjusting the radar sensitivity; this includes preset level selection and custom adjustment. Furthermore, the configuration guidance information carried by the radar sensitivity parameter adjustment option at this time displays parameter adjustment suggestions for modifying the radar sensitivity (e.g., suggesting increasing sensitivity).

[0588] If the detected status data indicates that someone is in the detected space, but the historical human presence status indicates that no one is present, a diagnostic result containing a data transmission anomaly flag is generated. This flag indicates that the current detected human presence status is inconsistent with the cloud storage, suggesting a possible data transmission delay, transmission error, or other issue causing untimely synchronization between the detection device and the cloud. In this case, although the detection device believes someone is in the detected space, the cloud storage status indicates that the detected space is empty, suggesting a possible transmission error (e.g., packet loss).

[0589] If both the detected status data and historical human presence data indicate that someone is in the detection space, a confirmation message indicating that the detection device is operating normally is generated. In this case, both the local detection device and the cloud consistently indicate that someone is in the detection space, and that the detection device and data transmission are normal. That is, the detection device correctly senses a human body in the detection space. If the controlled device's response is not as expected, it may be due to other reasons and is unrelated to the human presence status or data transmission status of the detection device.

[0590] For specific examples, such as Figure 37As shown, if the fourth abnormal condition 2204 describes the abnormal detection scenario of "entering a room but not turning on the lights," the user selects the title "entering a room but not turning on the lights" and enters the corresponding condition confirmation interface 3700. This interface 3700 displays the working status of the human body sensor in a specific environment through a scene diagram (as shown in the image) and provides a control for entering the detection process (as shown in the "Fault Cause Detection" control). The terminal device responds to the user's trigger command to the "Fault Cause Detection" control and enters the detection preparation interface 3701. The terminal device responds to the user's trigger command to the "Start Detection" control and triggers the active detection request. At this time, the terminal device enters the detection process, based on the previous preparation steps, and begins the actual acquisition and analysis of detection status data, ultimately obtaining the detection result. If the detection result is normal (the detection status data on the local detection device indicates that someone is present), confirmation information that the detection device is operating normally is obtained (as shown in interface 3702). Furthermore, the user can view the specific detection status data (as shown in interface 3703). If the detection status data indicates that the detection space is empty, an abnormal diagnostic result containing a status conflict identifier is generated, such as... Figure 38 As shown, adjustment item 37041 for radar sensitivity parameters is provided, and the configuration guidance information in the title suggests "view and modify sensor sensitivity".

[0591] Based on the above method 340, an embodiment of this disclosure also provides a terminal device, which can be applied to, for example... Figure 1 The human body detection system shown, or the terminal device 600 used in it.

[0592] like Figure 39 As shown, the terminal device includes an active detection unit, a diagnostic analysis unit, and an active service control unit.

[0593] The active detection unit is used to respond to an active detection request initiated by the user and obtain the detection status data of the detection device;

[0594] The diagnostic analysis unit is used to perform fault diagnosis analysis on the detection status data based on the set diagnostic rules.

[0595] The active service control unit is used to detect and respond to user input commands regarding diagnostic analysis results, and to perform active service control. The active service control is used to capture parameter inputs from at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis results are abnormal, and to perform a reconfiguration operation on the detection response characteristics of the detection device based on the input. The parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter. The detection parameter is used to adjust the detection response characteristics of the detection device; or...

[0596] Based on the normal diagnostic analysis results, a confirmation message indicating that the detection device is operating normally is generated.

[0597] In some embodiments, the active detection unit responds to an active detection request initiated by a user, specifically for:

[0598] In response to the user's first action, at least one working condition description item is displayed; each of the working condition description items describes at least one detection anomaly scenario.

[0599] In response to the user's trigger command for the target operating condition description item, the system enters the guidance interface to trigger the active detection request.

[0600] In some embodiments, each of the working condition description items is associated with an objective actual state, and the objective actual state characterizes the actual human presence state in the detection space under the detection anomaly scenario corresponding to the working condition description item.

[0601] The diagnostic analysis unit performs fault diagnosis analysis, specifically for:

[0602] The consistency of the human body presence status indicated by the detection status data is compared with the objective actual status corresponding to the target working condition description item.

[0603] When the two are inconsistent, an anomaly diagnostic result containing a state conflict identifier is generated.

[0604] Furthermore, the diagnostic analysis unit is also used to, when the human body state indicated by the detection status data is consistent with the objective actual state, further compare it with the data in the target storage node outside the detection device, and judge and perform fault diagnosis analysis based on the comparison result; wherein the data in the target storage node is synchronized to the target storage node in real time after the detection device acquires the detection status data.

[0605] In a specific example, the diagnostic analysis unit performs fault diagnosis analysis, which is further used for:

[0606] When the detected state data indicates the presence of the human body in accordance with the objective reality, the cloud verification step is executed:

[0607] Retrieve the historical state of a human body stored in the cloud;

[0608] Compare the consistency between the human body presence status indicated by the detection status data and the historical human body presence status; when the status is inconsistent, generate a diagnostic result containing a data transmission anomaly identifier;

[0609] When the status is consistent, a confirmation message indicating that the detection device is operating normally is generated.

[0610] In some embodiments, when generating an abnormal diagnostic result containing a state conflict identifier, the solution output by the active service control unit includes at least one parameter adjustment item; and / or, when generating a diagnostic result containing a data transmission anomaly identifier, the solution output by the active service control unit does not include a parameter adjustment item.

[0611] In some embodiments, the title of the parameter adjustment item also serves as an operable control;

[0612] The solution output by the active service control unit includes at least one parameter adjustment item, specifically used for:

[0613] Configuration guidance information is displayed in the title of the parameter adjustment item; the configuration guidance information refers to the suggestions generated based on the diagnostic results to guide users in optimizing parameter settings;

[0614] Among them, the configuration guidance information for the same parameter adjustment item triggered by different operating condition description items is different.

[0615] In some embodiments, when the target operating condition description item is a third abnormal operating condition, the diagnostic analysis unit is specifically used to respond to the user's trigger command for the third abnormal operating condition and perform fault diagnosis analysis, wherein:

[0616] If the detection status data indicates that there are people in the detection space, an abnormal diagnosis result containing a status conflict identifier is generated;

[0617] If the detection status data indicates that the detection space is empty, but the historical human presence status indicates that there is a person, a diagnostic result containing a data transmission anomaly identifier will be generated.

[0618] If both the detection status data and the historical human presence status indicate that the detection space is empty, a confirmation message indicating that the detection device is operating normally will be generated.

[0619] Among them, the third abnormal working condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled equipment after the human body leaves the target space.

[0620] In some embodiments, when the target operating condition description item is a fourth abnormal operating condition, the diagnostic analysis unit is specifically used to respond to the user's trigger command for the fourth abnormal operating condition and perform fault diagnosis analysis, wherein:

[0621] If the detection status data indicates that there is no one in the detection space, an abnormal diagnosis result containing a status conflict identifier is generated;

[0622] If the detection status data indicates that there is someone in the detection space, but the historical human presence status indicates that there is no one, a diagnostic result containing a data transmission anomaly identifier is generated.

[0623] If both the detection status data and the historical human presence status indicate that there are people in the detection space, a confirmation message that the detection device is operating normally will be generated.

[0624] The fourth abnormal working condition description detection device fails to trigger the state switching of the controlled equipment after a human enters the target space.

[0625] Based on the above method 340, an embodiment of this disclosure also provides a human body detection and processing method, applied to, for example... Figure 1 The human body detection system shown, or the detection device 100 used therein.

[0626] like Figure 40 As shown, the method 400 includes steps S4000 and S4001.

[0627] In step S4000, the detection device sends detection status data in response to a data acquisition request, so that: the terminal device acquires the detection status data, performs fault diagnosis analysis on the detection status data based on the set diagnostic rules, and detects and responds to the user's input command on the diagnostic analysis results to perform active service control; wherein, the data acquisition request is sent by the terminal device in response to an active detection request initiated by the user, and the detection status data represents the current human presence status in the detection space.

[0628] In step S4001, the detection device acquires the detection parameters sent by the terminal device and performs a real-time reconfiguration operation on the detection response characteristics; wherein, the detection parameters are sent by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, based on the active service control capture; the parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter; the detection parameters are used to adjust the detection response characteristics of the detection device.

[0629] In some embodiments, the method 400 further includes: sending acquired detection status data so that a target storage node acquires and stores the detection status data, and then sends it to a terminal device based on a request from the terminal device, so that the terminal device can further compare the detection status data of the detection device with the detection status data stored in the target storage node, and perform fault diagnosis analysis based on the comparison result. The request from the terminal device is sent after the terminal device acquires the detection status data and performs fault diagnosis analysis on the detection status data based on set diagnostic rules, and confirms that the human body presence state indicated by the detection status data is consistent with the objective reality. If the detection device confirms that the human body presence state indicated by the detection status data is inconsistent with the objective reality, it generates an abnormal diagnosis result containing a state conflict identifier.

[0630] The objective actual state is the objective actual state associated with the working condition description item determined by the user's trigger command for the target working condition description item after the terminal device responds to the user's first operation and displays at least one working condition description item; each working condition description item describes at least one detection anomaly scenario; the objective actual state associated with each working condition description item represents the actual human body presence state in the detection space under the detection anomaly scenario corresponding to that working condition description item.

[0631] Furthermore, the active detection request is triggered by the terminal device after entering the guidance interface in response to the user's trigger command for the target operating condition description item.

[0632] The target storage node includes a cloud server, and the method 400 further includes: sending acquired detection status data so that the cloud can acquire the detection status data and store it as a historical human presence status; the historical human presence status is used to send to the terminal device according to the request of the terminal device so that the terminal device can perform cloud verification steps according to the historical human presence status, wherein: when the human presence status indicated by the detection status data is inconsistent with the historical human presence status, a diagnostic result containing a data transmission anomaly identifier is generated; when the status is consistent, confirmation information that the detection device is operating normally is generated; wherein, when an abnormal diagnostic result containing a status conflict identifier is generated, the output solution includes at least one parameter adjustment item; and / or, when a diagnostic result containing a data transmission anomaly identifier is generated, the output solution does not include a parameter adjustment item.

[0633] In some embodiments, obtaining the detection parameters sent by the terminal device specifically includes:

[0634] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters; and / or,

[0635] Obtain the no-man's-existence determination window parameters; the no-man's-existence determination window parameters are captured by the terminal device after capturing the user's adjustment of the no-man's-existence determination window through the adjustment items of the no-man's-existence determination window parameters and sent; the no-man's-existence determination window represents the length of continuous state detection time required to determine the switch from manned state to no-man's-existence state;

[0636] The adjustment terms of the radar sensitivity parameter and / or the adjustment terms of the no-person presence determination window parameter are provided by the terminal device after responding to the user's selection of the third abnormal condition, when the detection status data indicates that there is a person in the detection space; the third abnormal condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled device after the human body leaves the target space.

[0637] In some embodiments, acquiring detection parameters sent by the terminal device specifically includes acquiring radar sensitivity parameters; the radar sensitivity parameters are sent by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment item of the radar sensitivity parameters; wherein, the adjustment item of the radar sensitivity parameters is provided by the terminal device in response to the user's selection of the fourth abnormal working condition, when the detection status data indicates that there is no one in the detection space; the fourth abnormal working condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled device after a human body enters the target space.

[0638] Based on the above method 400, an embodiment of this disclosure also provides a detection device, such as... Figure 41 As shown, the detection device includes a data transmission unit and a response characteristic configuration unit.

[0639] The data sending unit is used to send detection status data in response to a data acquisition request, so that: the terminal device acquires the detection status data, performs fault diagnosis analysis on the detection status data based on the set diagnostic rules, and detects and responds to the user's input command on the diagnostic analysis results to perform active service control; wherein, the data acquisition request is sent by the terminal device in response to an active detection request initiated by the user, and the detection status data represents the current human presence status in the detection space.

[0640] The response characteristic configuration unit is used to acquire the detection parameters sent by the terminal device and perform real-time reconfiguration operations on the detection response characteristics; wherein, the detection parameters are sent by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, based on the active service control capture; the parameter adjustment item forms a direct operation binding relationship with at least one adjustable detection parameter; the detection parameters are used to adjust the detection response characteristics of the detection device.

[0641] In some embodiments, the data sending unit is further configured to: send the acquired detection status data so that the target storage node acquires and stores the detection status data, and then sends it to the terminal device based on a request from the terminal device, so that the terminal device can further compare the detection status data of the detection device with the detection status data stored in the target storage node, and perform fault diagnosis analysis based on the comparison result; wherein, the request from the terminal device is sent after the terminal device acquires the detection status data and performs fault diagnosis analysis on the detection status data based on the set diagnostic rules, and confirms that the human body existence state indicated by the detection status data is consistent with the objective actual state; wherein, if the detection device confirms that the human body existence state indicated by the detection status data is inconsistent with the objective actual state, an abnormal diagnosis result containing a state conflict identifier is generated.

[0642] The objective actual state is the objective actual state associated with the working condition description item determined by the user's trigger command for the target working condition description item after the terminal device responds to the user's first operation and displays at least one working condition description item; each working condition description item describes at least one detection anomaly scenario; the objective actual state associated with each working condition description item represents the actual human body presence state in the detection space under the detection anomaly scenario corresponding to that working condition description item.

[0643] In some embodiments, the active detection request is triggered by the terminal device after entering the guide interface in response to the user's trigger instruction for the target operating condition description item.

[0644] In some embodiments, the data sending unit is further configured to: send the acquired detection status data so that the cloud can acquire the detection status data and store it as a historical human presence status; the historical human presence status is used to send to the terminal device according to a request from the terminal device so that the terminal device can perform a cloud verification step based on the historical human presence status, wherein: when the human presence status indicated by the detection status data is inconsistent with the historical human presence status, a diagnostic result containing a data transmission anomaly identifier is generated; when the status is consistent, confirmation information that the detection device is operating normally is generated; wherein when an abnormal diagnostic result containing a status conflict identifier is generated, the output solution includes at least one parameter adjustment item; and / or, when a diagnostic result containing a data transmission anomaly identifier is generated, the output solution does not include a parameter adjustment item.

[0645] In some embodiments, obtaining the detection parameters sent by the terminal device specifically includes:

[0646] Obtain radar sensitivity parameters; these radar sensitivity parameters are transmitted by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment items of the radar sensitivity parameters; and / or,

[0647] Obtain the no-man's-existence determination window parameters; the no-man's-existence determination window parameters are captured by the terminal device after capturing the user's adjustment of the no-man's-existence determination window through the adjustment items of the no-man's-existence determination window parameters and sent; the no-man's-existence determination window represents the length of continuous state detection time required to determine the switch from manned state to no-man's-existence state;

[0648] The adjustment terms of the radar sensitivity parameter and / or the adjustment terms of the no-person presence determination window parameter are provided by the terminal device after responding to the user's selection of the third abnormal condition, when the detection status data indicates that there is a person in the detection space; the third abnormal condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled device after the human body leaves the target space.

[0649] In some embodiments, acquiring detection parameters sent by the terminal device specifically includes acquiring radar sensitivity parameters; the radar sensitivity parameters are sent by the terminal device after capturing the user's adjustment of the radar sensitivity through the adjustment item of the radar sensitivity parameters; wherein, the adjustment item of the radar sensitivity parameters is provided by the terminal device in response to the user's selection of the fourth abnormal working condition, when the detection status data indicates that there is no one in the detection space; the fourth abnormal working condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled device after a human body enters the target space.

[0650] In addition, existing detection parameter adjustment methods typically use a fixed detection time threshold, and this static judgment mechanism is clearly no longer able to meet the increasingly complex and ever-changing application scenarios.

[0651] In particular, existing methods for determining the presence window in detection parameters are usually fixed or adjusted according to simple rules, which makes it difficult to adapt to complex environments and changing usage scenarios, and is prone to misjudgment and missed judgment, affecting detection accuracy.

[0652] Based on this, one embodiment of this disclosure provides a human body detection processing method that can effectively and dynamically adjust the presence determination window according to changes in environmental parameters and detection status, and is more sensitive to rapidly changing environments or irregular detection states. For example... Figure 42 As shown in the figure, a flowchart illustrating a human body detection and processing method provided in this embodiment of the present disclosure is specifically illustrated. It can be seen that the method 420 includes at least steps S420 to S422.

[0653] In step S420, the detection device acquires sensing data in real time; the sensing data includes detection status data and associated environmental parameters.

[0654] Specifically, the detection status data characterizes the current presence of a human body within the detection space, indicating whether or not a person is present in the detection space. In some schemes, the detection status data may also characterize other types of detection status, such as a person's movement or positional changes.

[0655] The associated environmental parameters can directly reflect the environmental characteristics of the detection space, or other environmental factors related to the detection space. Specifically, the associated environmental parameters may include, for example, ambient light intensity, ambient temperature, and / or ambient humidity. Among them, ambient light intensity reflects the light intensity in the current detection space.

[0656] In step S421, when the sensing data acquired by the detection device meets the first change characteristic, the first dynamic adjustment of the existence determination window is performed; the existence determination window represents the length of continuous state detection time required to determine whether a human body exists.

[0657] That is, if the detection device detects a change in the presence of a human in the detection space, it will not immediately switch the presence / absence status of the detection space. Instead, it will continue to determine whether the change has actually occurred within the presence determination window. If it is determined that the presence of a human has changed during the detection in the presence determination window, the presence / absence status of the detection space will be switched after the presence determination window has expired. For example, it can switch from the triggered detection state to the maintained detection state, or from the maintained detection state to the triggered detection state.

[0658] Specifically, the existence determination window includes the following two sub-windows:

[0659] No-Visibility Detection Window: This window determines the length of continuous detection time required to switch from a occupied state to an unoccupied state. Typically, when a person leaves the target area, the detection device needs a certain amount of time to confirm whether they have completely left. Specifically, while maintaining detection, if the detection device detects that the detection space is unoccupied, it does not immediately conclude that the detection space is unoccupied. Instead, it continues to assess within the No-Visibility Detection Window. If the detection space is still detected as occupied within the No-Visibility Detection Window, then the detection space is determined to be occupied, and the detection remains in the maintained detection state; otherwise, the detection space is determined to be unoccupied, and the device switches to the triggered detection state.

[0660] The presence determination window determines the length of continuous detection time required to switch from an unoccupied state to an occupied state. Specifically, when a human body is detected entering the detection space, a certain amount of time is needed to confirm that this state is continuous. In the triggered detection state, if the detection device identifies someone in the detection space, it does not immediately conclude that someone is in the detection space. Instead, it continues to determine presence within the presence determination window. If the detection space is still identified as unoccupied within the presence determination window, then the detection space is determined to be unoccupied and the triggered detection state is maintained; otherwise, the detection space is determined to be occupied and the detection is switched to a sustained detection state.

[0661] In step S422, the detection device determines the presence of a human body in the detection space based on the adjusted presence determination window, and performs a second-direction dynamic adjustment of the presence determination window when the acquired perception data satisfies the second change feature.

[0662] The first change feature is different from the second change feature, and at least one of them is based on the coordinated change of detection state data and associated environmental parameters; the first direction and the second direction have an inverse correlation.

[0663] The first and second change features represent the changes in perceived data under different conditions. These change features, together with the detection state within the detection space (such as the presence of a human body) and associated environmental parameters (such as illuminance and temperature), determine the dynamic adjustment of the presence determination window. For example, the first change feature might be a sudden drop in illuminance, while the second change feature might be a rebound in illuminance. The adjustments in the first and second directions are inversely related, meaning that the first and second dynamic adjustments have opposite effects. For example, a decrease in illuminance may shorten the presence determination window, while a return to normal illuminance may lengthen it to provide a more accurate determination. Specifically, if the first dynamic adjustment can accelerate the response speed by reducing detection time, suitable for scenarios with rapid environmental changes, then the second dynamic adjustment can improve accuracy by increasing detection time, suitable for scenarios with slower environmental changes and higher accuracy requirements. Conversely, if the first dynamic adjustment can accelerate the response speed by increasing detection time, suitable for scenarios with slower environmental changes and higher accuracy requirements, then the second dynamic adjustment can improve accuracy by reducing detection time, suitable for scenarios with rapid environmental changes.

[0664] This embodiment of the disclosure acquires and analyzes the changing characteristics of sensing data in real time, and dynamically adjusts the presence determination window according to environmental changes and the switching of human body states, so that the human body detection characteristics can be flexibly adjusted according to different environmental conditions, reducing the occurrence of false judgments and false negatives.

[0665] Furthermore, this disclosure provides an adaptive human detection processing method based on multi-parameter collaborative perception. This method can flexibly adjust the judgment window according to the synergistic effect of environmental changes and detection status, thereby improving the adaptability and accuracy of human presence detection.

[0666] In some embodiments, there is an inverse relationship between the first change feature and the second change feature in terms of parameter change characteristics. Specifically, the inverse relationship manifests in at least one of the following forms:

[0667] The changes in the state of a human body are logically inverse; this inverse relationship refers to the logically reverse process of changes in the state of a human body. That is, when a human body is detected to change from a state of "existence (someone is present)" to "non-existence (no one is present)," or from a state of "non-existence" to "existence," the judgment window can be dynamically adjusted according to specific conditions. Specifically, if the first change characteristic is that the human body changes from being present to being absent, then the second change characteristic is that the human body changes from being absent to being present.

[0668] The changes in the associated environmental parameters are inversely related; this inverse relationship involves the direction of change of the associated environmental parameters. For example, the first change characteristic is a sudden drop in ambient illuminance (i.e., a sudden decrease in light intensity), while the second change characteristic is a sudden increase in ambient illuminance (i.e., a sudden increase in light intensity).

[0669] The relationship between the state of the human body and changes in environmental parameters is inverse. In this inverse relationship, changes in both the state of the human body and environmental parameters occur simultaneously. The complexity of this relationship lies in the interaction between the human body's state and the environmental state, involving dynamic adjustments to their coordinated changes.

[0670] Based on this, the first change feature includes detecting the presence of a human body and the associated environmental parameters meeting a preset negative change. The second change feature includes any of the following:

[0671] Based on the current determination window, it is determined that the human body does not exist;

[0672] The presence of a human body was detected and the associated environmental parameters met the preset positive changes.

[0673] For example: when the first change feature is that someone is detected and the associated environmental parameters meet the preset negative change (e.g., a sharp drop in ambient light), the second change feature is that no one is detected, or that a human body is detected and the environmental parameters meet the preset positive change.

[0674] The associated environmental parameters satisfy a preset positive change, including: the rate of change of the associated environmental parameter reaches a preset positive threshold, for example, the rate of change of illuminance increases from -10% to +15%, that is, the direction and magnitude of the rate of change reach the preset threshold. And / or, the numerical change of the associated environmental parameter reaches a second predetermined value, for example, the ambient illuminance increases from 10 lux to 50 lux, satisfying the preset numerical change threshold.

[0675] The associated environmental parameters meet the preset negative change, including: the rate of change of the associated environmental parameter reaches the preset negative threshold; and / or, the change of the associated environmental parameter reaches a first predetermined value, for example, the illuminance drops from 400 lux to 50 lux, reaching the preset change range.

[0676] Furthermore, the specific conditions for the preset negative changes can be set by the user, allowing them to customize the trigger conditions according to their actual needs.

[0677] Furthermore, the absolute value of the preset positive threshold is greater than the absolute value of the preset negative threshold, which means that the response sensitivity to positive changes is stronger than that to negative changes, or that the response is more conservative to negative changes. This design is intended to avoid over-adjustment during negative changes and to recover more quickly during positive changes.

[0678] The second predetermined value is greater than or equal to the first predetermined value, meaning that when judging changes in environmental parameters, the magnitude of positive changes is greater than the magnitude of negative changes. In other words, a larger numerical change is needed to trigger a reverse adjustment for restoring environmental parameters such as illuminance. When the second predetermined value is equal to the first predetermined value, it means that the adjustment magnitudes for positive and negative changes are consistent. This can be applied to certain environments to ensure the same accuracy and response time under both positive and negative changes. For example, in environments with very stable illuminance, adjustments are made to illuminance changes by the same magnitude to maintain high-precision detection under stable environmental conditions.

[0679] In a specific example, when a negative change includes the rate of change of the associated environmental parameter reaching a preset negative threshold and the change of the associated environmental parameter reaching a first predetermined value, the first change characteristic may include, for example, detecting the presence of a human body and the ambient illuminance decreasing by more than 50% within 2 seconds with a change amount ≥ 50 lux (determined as a sudden drop in illuminance). When a positive change includes the rate of change of the associated environmental parameter reaching a preset positive threshold and the change of the associated environmental parameter reaching a second predetermined value, the second change characteristic may include, for example, detecting the presence of a human body and the illuminance increasing by more than 100% within 2 seconds with a change amount ≥ 50 lux (determined as a sudden increase in illuminance).

[0680] In some embodiments, the human body detection processing method further includes:

[0681] The detection device acquires setting instructions; these instructions are generated directly or indirectly by the terminal device based on user settings of one or more of the existence determination windows before, after, and in the second dynamically adjusted states. The setting instructions can be input by the user through a user interface (such as the terminal device). Specifically, the user can directly control the settings of the existence determination windows before and after the first dynamic adjustment via a graphical interface or buttons, or adjust the values ​​of each dynamically adjusted window using sliders, input boxes, etc.

[0682] The detection device configures the presence determination window before the first dynamic adjustment, the presence determination window after the first dynamic adjustment, and / or the presence determination window after the second dynamic adjustment according to the setting command.

[0683] In some embodiments, the presence determination window after the first dynamic adjustment is smaller than the presence determination window before the first dynamic adjustment. That is, performing the first dynamic adjustment of the presence determination window includes: reducing the presence determination window (the reduction amount can be set to be greater than 3 seconds). The presence determination window includes the no-existence determination window.

[0684] Furthermore, when the dynamically adjusted window for determining the absence of people in the first direction is smaller than the window for determining the absence of people before the dynamic adjustment, the dynamically adjusted window for determining the absence of people in the first direction does not support configuration according to the set instructions and is fixed to 1 to 5 seconds, so as to ensure that the response speed is not too slow during the dynamic adjustment process, especially in rapidly changing environments, and to reduce misjudgments or delays caused by an excessively long window for determining the absence of people.

[0685] Furthermore, the presence determination window is reduced, including reducing the absence determination window from its original value (the absence determination window before the first dynamic adjustment, which can be freely defined by the user) to a fixed value (1 to 5 seconds, for example, 1 second).

[0686] In one example, the first dynamic adjustment and the second dynamic adjustment are opposite in direction and the same in magnitude, such that the existence determination window before the first dynamic adjustment is equal to the existence determination window after the second dynamic adjustment. Then, performing the second dynamic adjustment of the existence determination window includes: increasing the no-existence determination window, that is, increasing the no-existence determination window from the adjusted fixed value (the no-existence determination window after the first dynamic adjustment) to the original value.

[0687] Assuming the window for determining the absence of people before the first dynamic adjustment is 11 seconds, and if the first and second dynamic adjustments have the same directional magnitude and are both 10 seconds, then the adjustment process is as follows:

[0688] When someone is detected and the lighting suddenly drops, the first dynamic adjustment of the absence determination window is performed. During this adjustment, the absence determination window decreases by 10 seconds from 11 seconds to 1 second. Subsequently, the presence detection in the detection space is performed according to this 1-second absence determination window, improving the efficiency of absence determination. If no one is detected, or if there is someone but the lighting suddenly increases, a second dynamic adjustment of the absence determination window is performed. This second adjustment restores the absence determination window from 1 second to the original 11 seconds or a window set according to user instructions.

[0689] Example application scenario: Linked control of room lighting fixtures:

[0690] Assume the detection device is installed in a room and linked to the room's lights to control their on / off state. The configuration is as follows: when someone is in the room, the lights automatically turn on; when no one is in the room, the lights automatically turn off.

[0691] In this scenario, the strategy of dynamically adjusting the absence determination window provided in this disclosure enables the detection device to adapt to rapidly changing environments, so as to avoid the inability to trigger the light switch in time when the user quickly returns to the room after leaving the room due to the absence determination window being too long.

[0692] Specifically:

[0693] Initial state: Inside the room, the user turns on the lights and enters the room. The detection device detects the presence of a human body using sensors. The lights then turn on and maintain their brightness.

[0694] User leaving the room: When a user leaves the room, the detection device detects a sudden drop in ambient light (e.g., the user turns off the lights). At this point, the detection device determines that "the user has left the room and manually turned off the lights," thus entering the "lights-off and leaving mode." The detection device shortens the absence detection window from 11 seconds to 1 second.

[0695] Returning to the room: Assuming the user returns to the room approximately 5 seconds after leaving, the detection device detects the human body entering the room and switches the human presence status from unoccupied to occupied, thereby triggering the lights to turn on.

[0696] Restore the original judgment window: When the detection device determines that the human body's state has changed, it automatically exits the "lights off and leave mode" and restores the original 11-second no-person judgment window, and continues to monitor the detection space accordingly.

[0697] In summary, when a user leaves the room, if the detection device detects someone in the room and the ambient light level drops sharply (for example, the user manually turns off the lights and leaves the room), the detection device will shorten the absence detection window from the original 11 seconds to 1 second. At this time, the detection device will determine whether the space is empty more quickly based on the shorter time window, thus avoiding false alarms caused by an excessively long window. This mechanism ensures that the user can promptly trigger the light switch when quickly returning to the room.

[0698] This application scenario demonstrates how by flexibly adjusting the absence detection window, the on / off status of room lights can be accurately controlled during the rapid transition from user departure to return. By combining the dynamic adjustment of the absence detection window with environmental changes (such as changes in illuminance), the detection device can improve accuracy, response speed, and the overall user experience in complex usage environments.

[0699] In some embodiments, the presence determination window after the first dynamic adjustment is larger than the presence determination window before the first dynamic adjustment. That is, performing the first dynamic adjustment of the presence determination window includes: increasing the presence determination window (the increase can be set to be greater than 5 seconds). The presence determination window includes a no-existence determination window.

[0700] Furthermore, when the dynamically adjusted no-man's-place determination window is larger than the original no-man's-place determination window, the dynamically adjusted no-man's-place determination window can be customized according to the setting instructions. For example, users can set a longer no-man's-place determination window according to different usage scenarios (such as corridors, bedrooms, etc.) to reduce the impact of environmental noise or interference on the response.

[0701] Furthermore, the presence determination window is increased, including: reducing the absence determination window from its original value (the absence determination window before the first dynamic adjustment, which can be freely defined by the user) to the absence determination window after the first dynamic adjustment (which can be freely defined by the user).

[0702] In one example, the first dynamic adjustment and the second dynamic adjustment are opposite in direction and the same in magnitude, such that the existence determination window before the first dynamic adjustment is equal to the existence determination window after the second dynamic adjustment. Then, performing the second dynamic adjustment of the existence determination window includes: reducing the existence determination window from the no-existence determination window after the first dynamic adjustment to its original value.

[0703] Assuming the window for determining the absence of people before the first dynamic adjustment is 20 seconds, and if the first and second dynamic adjustments have the same directional magnitude and are both 10 seconds, then:

[0704] The first dynamic adjustment changes the window for determining if no one is present from 20 seconds to 30 seconds.

[0705] The second dynamic adjustment will restore the window to 20 seconds (unless further settings are specified).

[0706] Example application scenario: Linked control of room lighting fixtures:

[0707] Assume the detection device is installed in the room and used to control the on / off status of the room's lights. It is set to a "lights on when someone is there, lights off when no one is there" linkage control mode.

[0708] In this scenario, the strategy of dynamically adjusting the absence determination window provided in this disclosure enables the detection device to adapt to rapidly changing environments, so as to avoid the user remaining still in the room (such as sleeping), which may lead to a misjudgment of an unoccupied state, resulting in frequent switching of the light fixtures on and off (for example, when the user is sleeping in the room, it may be mistakenly judged as an unoccupied state, and the room lights may be turned off. When the user turns over or moves slightly, it may be mistakenly assumed that someone has returned and the lights will be turned back on).

[0709] Specifically:

[0710] Initial state: When a user enters the room, the lights automatically turn on. The detection device detects the presence of a human body through sensors, and the lights remain on.

[0711] User Sleep or Stillness: When a user enters sleep mode after turning off the lights, and remains still (or moves only slightly) in the room, a sudden drop in light intensity is detected. The detection device infers this change as "the user manually turned off the lights and remained in the room," thus entering "lights-off sleep mode." To avoid false alarms, since the user is still and moves minimally, the absence detection window is increased from 20 seconds to 30 seconds. This way, even if the user remains completely still for a period of time during sleep, it will not trigger a false alarm due to minimal movement.

[0712] When a user wakes up or opens the curtains: If a sudden increase in light intensity is detected (e.g., the user turns on the lights or opens the curtains after waking up), it is assumed that the change in light intensity is caused by "the user manually turning on the lights" or "a change in the external environment (such as opening the curtains)," and the system automatically exits the "lights-off sleep mode." At this time, the original absence detection window will be restored, reducing it from 30 seconds to the original 20 seconds, thus maintaining accurate detection of human status and avoiding unnecessary false triggers.

[0713] In summary, the solution provided in this disclosure can prevent accidental operation triggered by slight movements when the user is stationary in the room (such as sleeping) by dynamically adjusting the absence detection window, and ensures more intelligent and precise linkage control of the lighting fixtures. By combining the judgment of changes in ambient light intensity and the presence of the human body, it can better adapt to the actual usage needs of users, avoid unnecessary accidental triggers or delays, and improve the overall user experience.

[0714] In some embodiments, the first change feature includes detecting the presence of a human body and the associated environmental parameters meeting a preset negative change. For example, a sudden drop in illuminance indicates that the user has turned off the lights.

[0715] The second change feature includes continuously detecting the presence of a human body up to a third predetermined value; the third predetermined value is greater than the first dynamically adjusted presence determination window to adapt to specific usage scenarios, such as the situation where the user remains in the room after manually turning off the lights.

[0716] Furthermore, the presence determination window includes an absence determination window. Based on this, the solution provided by the present disclosure is intended to adapt to scenarios where someone turns off the lights but does not leave when "Away Mode" is enabled, such as manually turning off the lights in a "movie viewing scenario".

[0717] Furthermore, the third predetermined value is equal to the existence determination window before the first dynamic adjustment.

[0718] In one application scenario, if the detection device is installed in a room and used to control the lighting in the room, and if a linkage control is set for someone turning on the lights and no one turning them off, when the detection device detects someone and the illuminance drops suddenly, it will assume that "the user manually turned off the lights and left the room," and reduce the no-man's-room determination window from 11 seconds to 1 second. If the user remains in the room and does not leave, for example, while watching a movie, the detection device will continue to detect someone. If the duration of the detected person exceeds the original no-man's-room determination window of 11 seconds, it will assume that "the user manually turned off the lights and continued watching the movie," and the no-man's-room determination window will be restored to 11 seconds.

[0719] In some embodiments, such as Figure 43 As shown, before acquiring the sensing data in real time in step S420, the method further includes:

[0720] The receiving mode switching instruction is generated and sent by the terminal device after one of at least two working modes displayed on the user interface is selected; wherein these working modes correspond to the working modes of the detection device.

[0721] The system switches to the operating mode indicated by the switching command. After switching to the indicated operating mode, the detection device determines how to adjust the presence determination window based on the selected mode. This switching process determines the size relationship between the presence determination window after the first dynamic adjustment and the presence determination window before the first dynamic adjustment. That is, it determines whether the first dynamic adjustment of the presence determination window is to decrease or increase the presence determination window.

[0722] Specifically, when the existence determination window includes the absence determination window, if the working mode includes a first mode (such as the "lights off and leave mode" described in the above embodiment) and a second mode (such as the "lights off and sleep mode" described in the above embodiment), then when switching to the first mode, the first dynamic adjustment will reduce the absence determination window, that is, the existence determination window after the first dynamic adjustment is smaller than the existence determination window before the first dynamic adjustment.

[0723] For example, suppose a user selects the "lights off and leave mode." When someone is detected and the light level drops sharply, the window for determining if someone is not present will be shortened from its original value (e.g., 11 seconds) to 1 second, quickly determining whether the user has left the room. If no human presence is detected within 1 second, it will be assumed that the user has left the room.

[0724] When switching to the second mode, the first dynamic adjustment will increase the absence determination window, that is, the presence determination window after the first dynamic adjustment is larger than the presence determination window before the first dynamic adjustment.

[0725] For example, when a user selects "lights off sleep mode", the detection device increases the window for determining the absence of people from 20 seconds to 30 seconds. This helps to identify that even if the user is stationary in the room (such as sleeping), it will not trigger a false judgment due to minor movements, thereby preventing the lights from being turned off or on incorrectly.

[0726] Furthermore, this embodiment can provide more flexible and intelligent control in different scenarios by adjusting the size of the no-man's-area determination window according to the user's selected working mode.

[0727] In some embodiments, a detection device is also provided for implementing the method 420.

[0728] like Figure 44 As shown in the illustration, a detection device provided in this embodiment is specifically illustrated. It can be seen that the detection device includes a detection unit and a judgment unit.

[0729] The detection unit is used to acquire sensing data in real time; the sensing data includes detection status data and associated environmental parameters.

[0730] The judgment unit is used to perform a first-direction dynamic adjustment of the existence judgment window when the acquired perception data meets the first change feature; the existence judgment window represents the length of continuous state detection time required to determine whether a human body exists.

[0731] The detection unit determines the presence of a human body in the detection space based on the adjusted presence determination window, and triggers the judgment unit to perform a second-direction dynamic adjustment of the presence determination window when the acquired perception data meets the second change feature.

[0732] The first change feature is different from the second change feature, and at least one of them is based on the coordinated change of detection state data and associated environmental parameters; the first direction and the second direction have an inverse correlation.

[0733] In some embodiments, the detection state data characterizes the presence of a human body and is used to characterize whether there is a person in the detection space; there is an inverse relationship between the first change feature and the second change feature, and the inverse relationship is expressed in at least one of the following forms:

[0734] The changes in the state of the human body are logically contradictory.

[0735] The changes in the associated environmental parameters are inverse;

[0736] The relationship between the state of the human body and changes in environmental parameters is inverse.

[0737] In some embodiments, the first change feature includes detecting the presence of a human body and the associated environmental parameters satisfying a preset negative change;

[0738] The second variation feature includes any of the following:

[0739] Based on the current determination window, it is determined that the human body does not exist;

[0740] The presence of a human body was detected and the associated environmental parameters met the preset positive changes.

[0741] In some embodiments,

[0742] The associated environmental parameters meet the preset negative change, including: the rate of change of the associated environmental parameter reaches the preset negative threshold; or, the change of the associated environmental parameter reaches the first predetermined value.

[0743] The associated environmental parameters meet the preset positive change, including: the rate of change of the associated environmental parameter reaches the preset positive threshold; or, the change of the associated environmental parameter reaches the second predetermined value.

[0744] In some embodiments, the absolute value of the preset positive threshold is greater than the absolute value of the preset negative threshold; the second predetermined value is greater than or equal to the first predetermined value.

[0745] In some embodiments, the first change feature includes detecting the presence of a human body and the associated environmental parameters satisfying a preset negative change, and the second change feature includes continuously detecting the presence of a human body up to a third predetermined value; the third predetermined value is greater than the first dynamically adjusted presence determination window.

[0746] In some embodiments, the third predetermined value is equal to the existence determination window before the first dynamic adjustment.

[0747] In some embodiments, the associated environmental parameters include ambient light intensity.

[0748] In some embodiments, the detection device further includes a data receiving unit for acquiring setting instructions; the setting instructions are generated directly or indirectly by the terminal device based on one or more settings made by the user to the existence determination window before the first dynamic adjustment, the existence determination window after the first dynamic adjustment, and the existence determination window after the second dynamic adjustment.

[0749] The processing unit is configured to configure the existence determination window before the first dynamic adjustment, the existence determination window after the first dynamic adjustment, and / or the existence determination window after the second dynamic adjustment according to the setting instruction.

[0750] In some embodiments, the existence determination window after the first dynamic adjustment is smaller or larger than the existence determination window before the first dynamic adjustment.

[0751] In some embodiments, the presence determination window includes an unoccupied presence determination window, which is used to determine the length of continuous state detection time required to switch from an occupied state to an unoccupied state;

[0752] When the dynamically adjusted window for determining the absence of people in the first direction is smaller than the window for determining the absence of people before the dynamic adjustment, the dynamically adjusted window for determining the absence of people in the first direction does not support configuration according to the set instructions and is fixed to 1 to 5 seconds.

[0753] When the dynamically adjusted window for determining the absence of people in the first direction is larger than the window for determining the absence of people before the dynamic adjustment, the dynamically adjusted window for determining the absence of people in the first direction can be customized according to the setting instructions.

[0754] In some embodiments, the first dynamic adjustment and the second dynamic adjustment are opposite in direction and have the same magnitude, such that the existence determination window before the first dynamic adjustment is equal to the existence determination window after the second dynamic adjustment.

[0755] In the description of this specification, the references to terms such as "some embodiments," "a specific implementation," "a specific implementation process," and "an example" indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms corresponding to the ...

Claims

1. A human body detection processing method, applied to a detection device, characterized in that, The method includes at least: In response to a data acquisition request, detection status data is sent, enabling: the terminal device to acquire the detection status data, perform fault diagnosis analysis on the detection status data based on set diagnostic rules, and detect and respond to the user's input command on the diagnostic analysis results to perform proactive service control; wherein, the data acquisition request is sent by the terminal device in response to a proactive detection request initiated by the user, and the detection status data represents the current human presence status in the detection space; The detection parameters sent by the terminal device are acquired, and a reconfiguration operation is performed on the detection response characteristics. The detection parameters are sent by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, based on the active service control. The parameter adjustment item forms a direct operation binding relationship with at least one adjustable detection parameter. The detection parameters are used to adjust the detection response characteristics of the detection device.

2. The processing method according to claim 1, characterized in that, The method further includes: sending the acquired detection status data so that the target storage node can acquire and store the detection status data, and then sending it to the terminal device based on the request of the terminal device, so that the terminal device can further compare the detection status data of the detection device with the detection status data stored in the target storage node, and perform fault diagnosis analysis based on the comparison result; wherein, the request of the terminal device is sent after the terminal device acquires the detection status data and performs fault diagnosis analysis on the detection status data based on the set diagnostic rules, and confirms that the human body existence state indicated by the detection status data is consistent with the objective actual state; wherein, if the detection device confirms that the human body existence state indicated by the detection status data is inconsistent with the objective actual state, an abnormal diagnosis result containing a state conflict identifier is generated; The objective actual state is the objective actual state associated with the working condition description item determined by the user's trigger command for the target working condition description item after the terminal device responds to the user's first operation and displays at least one working condition description item; each working condition description item describes at least one detection anomaly scenario; the objective actual state associated with each working condition description item represents the actual human body presence state in the detection space under the detection anomaly scenario corresponding to that working condition description item.

3. The processing method according to claim 2, characterized in that, The active detection request is triggered by the terminal device in response to the user's trigger command for the target operating condition description item and after entering the guidance interface.

4. The processing method according to claim 2, characterized in that, The method further includes: sending acquired detection status data so that the cloud can acquire the detection status data and store it as a historical human presence status; the historical human presence status is used to send to the terminal device according to the request of the terminal device so that the terminal device can perform cloud verification steps according to the historical human presence status, wherein: when the human presence status indicated by the detection status data is inconsistent with the historical human presence status, a diagnostic result containing a data transmission anomaly identifier is generated; when the status is consistent, confirmation information that the detection device is operating normally is generated; wherein when an abnormal diagnostic result containing a status conflict identifier is generated, the output solution includes at least one parameter adjustment item; and / or, when a diagnostic result containing a data transmission anomaly identifier is generated, the output solution does not include a parameter adjustment item.

5. A detection device, characterized in that, include: The data transmission unit is used to send detection status data in response to a data acquisition request, so that: the terminal device acquires the detection status data, performs fault diagnosis analysis on the detection status data based on the set diagnostic rules, and detects and responds to the user's input command on the diagnostic analysis results to perform active service control; wherein, the data acquisition request is sent by the terminal device in response to an active detection request initiated by the user, and the detection status data represents the current human presence status in the detection space; The response characteristic configuration unit is used to acquire detection parameters sent by the terminal device and perform real-time reconfiguration operations on the detection response characteristics; wherein, the detection parameters are sent by the terminal device based on the input of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis result is abnormal, based on the active service control capture; the parameter adjustment item forms a direct operation binding relationship with at least one adjustable detection parameter; the detection parameters are used to adjust the detection response characteristics of the detection device.

6. A method for human body detection and processing, characterized in that, include: In response to a user-initiated active detection request, obtain the detection status data of the detection device; The detection status data is analyzed for fault diagnosis based on the established diagnostic rules. The system detects and responds to user input commands regarding diagnostic analysis results, and performs proactive service control. This proactive service control captures parameter inputs from at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis results are abnormal, and performs a reconfiguration operation on the detection response characteristics of the detection device based on these inputs. The parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter. The detection parameters are used to adjust the detection response characteristics of the detection device; or, Based on the normal diagnostic analysis results, a confirmation message indicating that the detection device is operating normally is generated.

7. The processing method according to claim 1, characterized in that: In response to a user-initiated proactive detection request, including: In response to the user's first action, at least one working condition description item is displayed; each of the working condition description items describes at least one detection anomaly scenario. In response to the user's trigger command for the target operating condition description item, the system enters the guidance interface to trigger the active detection request.

8. The processing method according to claim 7, characterized in that, Each of the above working condition description items is associated with an objective actual state, which represents the actual human body presence state in the detection space under the detection anomaly scenario corresponding to the working condition description item. The fault diagnosis analysis includes: The consistency of the human body presence status indicated by the detection status data is compared with the objective actual status corresponding to the target working condition description item. When the two are inconsistent, an anomaly diagnostic result containing a state conflict identifier is generated.

9. The processing method according to claim 8, characterized in that, When the human body status indicated by the detection status data is consistent with the objective actual status, it is further compared with the data in the target storage node outside the detection device, and the fault diagnosis analysis is performed based on the comparison results. The data in the target storage node is synchronized to the target storage node in real time after the detection device acquires the detection status data.

10. The processing method according to claim 9, characterized in that, The target storage node includes a cloud server, and the method further includes: When the detected state data indicates the presence of the human body in accordance with the objective reality, the cloud verification step is executed: Retrieve the historical state of a human body stored in the cloud; Compare the consistency between the human body presence status indicated by the detection status data and the historical human body presence status; when the status is inconsistent, generate a diagnostic result containing a data transmission anomaly identifier; When the status is consistent, a confirmation message indicating that the detection device is operating normally is generated; Specifically, when generating an anomaly diagnostic result containing a state conflict identifier, the output solution includes at least one parameter adjustment item; and / or, when generating a diagnostic result containing a data transmission anomaly identifier, the output solution does not include a parameter adjustment item.

11. The processing method according to claim 10, characterized in that, The title of the parameter adjustment item also serves as an operable control; The output solution includes at least one parameter adjustment item, specifically including: Configuration guidance information is displayed in the title of the parameter adjustment item; the configuration guidance information refers to the suggestions generated based on the diagnostic results to guide users in optimizing parameter settings; Among them, the configuration guidance information for the same parameter adjustment item triggered by different operating condition description items is different.

12. The processing method according to claim 11, characterized in that: When the target operating condition description item is the third abnormal operating condition, the method further includes, in response to the user's trigger command for the third abnormal operating condition, performing fault diagnosis analysis, wherein: If the detection status data indicates that there are people in the detection space, an abnormal diagnosis result containing a status conflict identifier is generated; If the detection status data indicates that the detection space is empty, but the historical human presence status indicates that there is a person, a diagnostic result containing a data transmission anomaly identifier will be generated. If both the detection status data and the historical human presence status indicate that the detection space is empty, a confirmation message indicating that the detection device is operating normally will be generated. Among them, the third abnormal working condition describes a detection failure scenario in which the detection device fails to trigger the state switching of the controlled equipment after the human body leaves the target space.

13. The processing method according to claim 10, characterized in that: When the target operating condition description item is the fourth abnormal operating condition; the method further includes, in response to the user's trigger command for the fourth abnormal operating condition, performing fault diagnosis analysis, wherein: If the detection status data indicates that there is no one in the detection space, an abnormal diagnosis result containing a status conflict identifier is generated; If the detection status data indicates that there is someone in the detection space, but the historical human presence status indicates that there is no one, a diagnostic result containing a data transmission anomaly identifier is generated. If both the detection status data and the historical human presence status indicate that there are people in the detection space, a confirmation message that the detection device is operating normally will be generated. The fourth abnormal working condition description detection device fails to trigger the state switching of the controlled equipment after a human enters the target space.

14. A terminal device, characterized in that, include: The active detection unit is used to respond to active detection requests initiated by users and obtain detection status data of the detection device; The diagnostic analysis unit is used to perform fault diagnosis analysis on the detection status data based on the set diagnostic rules. An active service control unit is used to detect and respond to user input commands for diagnostic analysis results, and to perform active service control. The active service control is used to capture parameter inputs of at least one parameter adjustment item included in the solution generated and output by the user when the diagnostic analysis results are abnormal, and to perform a reconfiguration operation on the detection response characteristics of the detection device based on the input. The parameter adjustment item forms a direct operational binding relationship with at least one adjustable detection parameter. The detection parameters are used to adjust the detection response characteristics of the detection device; or, Based on the normal diagnostic analysis results, a confirmation message indicating that the detection device is operating normally is generated.

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