A wireless communication-based alarm event reporting and remote response linkage method and system

Abstract

This invention provides a method and system for alarm event reporting and remote response linkage based on wireless communication, relating to the field of intelligent security monitoring technology. The method includes: collecting raw sensor data at three-dimensional spatial state sensing anchor points deployed on the top of the equipment casing (acoustic resonant cavity), the bottom inertial reference plane, and the lateral electromagnetic shield); performing trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; converting the processed data into a unified alarm trigger event; performing multi-source feature analysis on the alarm trigger event to obtain event analysis results; extracting the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state sensing anchor points based on the event analysis results, introducing the attenuation characteristics of intermolecular van der Waals forces to map the signal field, and constructing a three-dimensional spatial situation fitting ellipsoid. This invention achieves efficient end-to-end coordination between on-site alarms and remote dispatching.

Description

Technical Field

[0001] This invention relates to the field of intelligent security monitoring technology, and in particular to a method and system for alarm event reporting and remote response linkage based on wireless communication. Background Technology

[0002] This invention relates to the field of fire emergency alarm technology, specifically to integrated remote alarm devices for densely populated places such as schools, factories, shopping malls, and hotels. Although such devices can achieve basic local alarm and remote signal transmission functions, they generally suffer from technical shortcomings such as fixed alarm linkage logic, poor adaptability of voice broadcasts and alarm locations, and disconnection between alarm event reporting and emergency response links.

[0003] For example, when an initial fire broke out in the storage area on the basement floor of a shopping mall, after on-site staff pressed the nearby integrated remote alarm device, the device could only trigger a fixed-parameter audible and visual alarm and a generic fire warning voice. It was difficult to match and send targeted evacuation guidance and fire response voice messages based on the specific location of the alarm point. At the same time, the device did not adaptively compensate for the transmission loss of the 4G wireless communication link during the alarm event reporting process, resulting in delays in receiving alarm information in both the mall's fire control room and the local fire and rescue department's back-end management platform. Furthermore, the device could not automatically dial the preset emergency contact person and fire alarm number after the alarm voice broadcast was completed. The panicked staff on site had to manually dial the numbers to report the fire. Ultimately, due to the untimely initial fire response and personnel evacuation guidance, more than one million yuan worth of goods and building decoration losses were caused. This case clearly exposed that existing wireless communication-based alarm devices lack the ability to link alarm events and location information, the ability to adaptively optimize wireless transmission links, and the ability to achieve full-process automated linkage of alarm triggering, voice broadcasting, and emergency dialing. It is difficult to achieve accurate and rapid reporting of alarm events and efficient linkage of remote emergency response. Summary of the Invention

[0004] This invention provides a method and system for alarm event reporting and remote response linkage based on wireless communication, realizing efficient end-to-end coordination between on-site alarms and remote dispatch.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: Firstly, a method for alarm event reporting and remote response linkage based on wireless communication, the method comprising: Step 1: Collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; convert the processed data into a unified alarm trigger event. Step 2: Perform multi-source feature analysis on the alarm triggering event to obtain the event analysis results; extract the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point based on the event analysis results, introduce the attenuation characteristics of intermolecular van der Waals forces to map the signal field, and construct a three-dimensional spatial situation fitting ellipsoid. Step 3: Perform topological meshing and multi-physics coupled numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; based on the event analysis results and the multi-mode signal transmission link gain correction coefficient, obtain the audible and visual alarm driving command, and simultaneously extract the location and time information in the event, and encapsulate it to obtain the alarm event data packet; Step 4: Based on the location information in the alarm event data packet, and combined with the multimodal signal transmission link gain correction coefficient, perform dynamic weight matching on the pre-stored voice text template to obtain the target TTS voice broadcast content. Step 5: Convert the TTS voice broadcast content into a voice alarm signal and broadcast it through a speaker; Step 6: After the voice broadcast is completed, a call request is automatically generated based on the linkage identifier in the broadcast content, and an alarm voice message is played after the call is connected.

[0006] Furthermore, raw sensor data is collected from the three-dimensional spatial state sensing anchor points deployed on the top of the equipment casing, the bottom inertial reference plane, and the lateral electromagnetic shield. The raw sensor data undergoes trajectory decoupling and phase synchronization processing to obtain processed data. The processed data is then converted into unified alarm trigger events, including: The acoustic pressure fluctuation time sequence output by the acoustic resonant cavity, the three-axis acceleration and angular velocity vector sequence output by the bottom inertial reference plane, and the external electromagnetic field distortion amplitude-frequency sequence induced by the lateral electromagnetic shield are simultaneously acquired. The three types of time signals are spliced ​​together according to the sampling clock and combined to obtain the original sensing data. The raw sensor data is mapped to a preset multi-degree-of-freedom rigid body kinematic state space to construct a six-dimensional state variable matrix containing translational and rotational motion components. Based on the six-dimensional state variable matrix, the kinematic differential equations are substituted, and the translational motion components and rotational motion components are decoupled by the orthogonal projection operator to obtain the decoupled independent motion state vectors. By performing time-domain registration on independent motion state vectors, the phase shift caused by the hardware sampling clock deviation of each three-dimensional spatial state perception anchor point is compensated, and a phase-synchronized data stream is obtained. The phase-synchronized data stream is the processed data. The processed data undergoes sliding window variance evolution calculation and dynamic threshold determination. When the data stream amplitude continuously exceeds the preset safety boundary, a state transition mechanism is triggered, and the transition state identifier is normalized and mapped to a unified alarm trigger event.

[0007] Furthermore, multi-source feature analysis is performed on the alarm triggering events to obtain event analysis results; based on the event analysis results, the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor points are extracted, and the attenuation characteristics of intermolecular van der Waals forces are introduced to map the signal field, constructing a three-dimensional spatial situation fitting ellipsoid, including: For a unified alarm triggering event, joint time-frequency domain feature extraction is performed to separate the frequency domain energy spectrum features and the time domain envelope abrupt change features. Tensor fusion is then used to obtain the event analysis results. Based on the event analysis results, the real-time displacement deviation of each three-dimensional spatial state sensing anchor point is calculated by inverse kinematics solver to obtain spatial vector coordinates. The surface micro-element deformation rate under force at each anchor point is calculated according to the constitutive relation of continuous medium mechanics to construct dynamic stress distribution gradient. The spatial vector coordinates and dynamic stress distribution gradient are substituted into the field mapping function. The field mapping function introduces the distance power-law attenuation characteristics of the intermolecular van der Waals potential energy function to characterize the energy dissipation and phase hysteresis of sound waves and electromagnetic waves in the propagation medium. The equivalent interaction potential weight matrix between each spatial node is calculated to complete the mapping of the signal field. Using spatial vector coordinates as geometric control points and the equivalent interaction potential weight matrix as spatial topological constraints, a three-dimensional spatial situation fitting ellipsoid is obtained by optimizing the boundary envelope of discrete situation data points within the alarm radiation influence domain.

[0008] Furthermore, topological meshing and multiphysics coupling numerical simulations are performed on the 3D spatial situation fitting ellipsoid to obtain the multimodal signal transmission link gain correction coefficients. Based on the event analysis results and the multimodal signal transmission link gain correction coefficients, the audible and visual alarm driving command is obtained. Simultaneously, the location and time information in the event are extracted and encapsulated to obtain an alarm event data packet, including: Using the geometric surface of the ellipsoid fitted to the three-dimensional spatial situation as the computational boundary, the continuous computational domain is discretized into a hybrid topological mesh containing acoustic propagation nodes, electromagnetic radiation nodes, and stress transmission nodes, resulting in a discrete mesh set. Based on a discrete mesh set, the multiphysics coupling solution operator is invoked to jointly iteratively solve the sound pressure attenuation gradient of the acoustic propagation node, the multipath interference intensity of the electromagnetic radiation node, and the vibration energy dissipation of the stress transmission node, so as to obtain the field coupling response matrix. The field coupling response matrix is ​​input into the link compensation calculation unit, and inverse differential operation is performed in combination with the preset wireless communication channel reference attenuation spectrum to extract the quantization parameters for compensating the transmission loss of each mode signal, and obtain the multi-mode signal transmission link gain correction coefficient. The event analysis results are logically mapped to the multimodal signal transmission link gain correction coefficient to obtain the mapping result; the preset sound and light control protocol stack is matched according to the mapping result to obtain the sound and light alarm drive command. The location and time information carried in the event parsing results are extracted synchronously. The audible and visual alarm drive command, location information, time information, and multimodal signal transmission link gain correction coefficient are binary serialized and encapsulated with protocol frames to obtain the alarm event data packet.

[0009] Furthermore, based on the location information in the alarm event data packet, and combined with the multimodal signal transmission link gain correction coefficient, dynamic weight matching is performed on the pre-stored voice text template to obtain the target TTS voice broadcast content, including: The alarm event data packet is parsed to extract location information and multimodal signal transmission link gain correction coefficient, and the location information is converted into a spatial distance attenuation factor. Retrieve the local template repository, retrieve at least two pre-stored speech-text templates associated with the geographic grid to which the location information belongs, and extract acoustic prosodic features and semantic key segments from each template; A dynamic weight allocation vector is constructed by performing a matrix product operation between the spatial distance attenuation factor and the multimodal signal transmission link gain correction coefficient. Based on the dynamic weight allocation vector, the acoustic prosodic features and semantic key segments of at least two pre-stored speech text templates are weighted and fused to obtain the fusion score ranking; the final matching sequence is selected according to the fusion score ranking to obtain the target TTS speech broadcast content.

[0010] Furthermore, the TTS voice broadcast content is converted into a voice alarm signal and broadcast through a speaker, including: Receive the target TTS voice broadcast content, perform a nonlinear mapping operation from phoneme sequence to acoustic parameters, extract the fundamental frequency trajectory, formant frequency and duration envelope parameters, and obtain the initial digital audio stream; The gain correction coefficient of the multimodal signal transmission link is called to perform frequency domain predistortion compensation and dynamic range compression processing on the initial digital audio stream, suppress the masking effect of speaker nonlinear harmonic distortion and environmental background noise, and obtain the channel-adapted digital audio signal. The channel-adapted digital audio signal is input to the digital-to-analog converter unit, and after anti-aliasing low-pass filtering and Class D power amplification, an analog electric drive signal with impedance characteristics strictly matched to the speaker voice coil is obtained. The analog electric drive signal is the voice alarm signal. The voice alarm signal is loaded onto the diaphragm driver of the speaker, and the sound-electric-mechanical-sound energy conversion link is controlled to perform sound pressure radiation, thus completing the physical broadcast of the voice alarm signal in the external space of the device.

[0011] Furthermore, after the voice broadcast is completed, a call request is automatically generated based on the linkage identifier in the broadcast content. Upon connection, an alarm voice message is played, including: Monitor the audio playback buffer status of the speaker. When the buffer data is cleared and the playback duration reaches a preset threshold, the voice playback is determined to be complete. Simultaneously parse the data frame control field of the playback content and extract the embedded linkage identifier. The linkage identifier is input into the session control layer of the wireless communication baseband processor, which matches the preset emergency communication routing policy and the target terminal addressing protocol to construct a telephone dialing request that includes session initiation instructions, identity authentication tokens and media negotiation parameters. The wireless radio frequency front-end sends the call request to the operator's core network side, listens for and parses the link establishment status code in the downlink signaling feedback, and determines that the communication link is connected when the status code indicates that the two-way voice channel handshake is successful. After the communication link is established, the standardized alarm voice coding sequence associated with the alarm triggering event is retrieved, and channel coding, interleaving and orthogonal frequency division multiplexing modulation mapping are performed to obtain the wireless transmission baseband stream, which is then pushed to the remote terminal in real time as alarm voice information. The system listens for the media stream reception confirmation signal returned by the remote terminal. When the confirmation signal indicates that the alarm voice information has been fully delivered and the decoding verification has passed, the media stream transmission is terminated and the communication channel resources occupied by the telephone dialing request are released.

[0012] Secondly, a wireless communication-based alarm event reporting and remote response linkage system includes: The acquisition module is used to collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; to perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; and to convert the processed data into a unified alarm trigger event. The analysis module is used to perform multi-source feature analysis on alarm trigger events to obtain event analysis results; based on the event analysis results, the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point are extracted, and the attenuation characteristics of intermolecular van der Waals forces are introduced to map the signal field and construct a three-dimensional spatial situation fitting ellipsoid. The calculation module is used to perform topological meshing and multi-physics coupled numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; based on the event analysis results and the multi-mode signal transmission link gain correction coefficient, the audible and visual alarm driving command is obtained, and the location information and time information in the event are extracted and encapsulated to obtain the alarm event data packet; The matching module is used to perform dynamic weight matching on the pre-stored voice text template based on the location information in the alarm event data packet and the multimodal signal transmission link gain correction coefficient to obtain the target TTS voice broadcast content. The conversion module is used to convert TTS voice broadcast content into voice alarm signals and broadcast them through a speaker. The processing module is used to automatically generate a call request based on the linkage identifier in the broadcast content after the voice broadcast is completed, and play the alarm voice information after the call is connected.

[0013] Thirdly, a computing device includes: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the method.

[0014] Fourthly, a computer-readable storage medium storing a program that, when executed by a processor, implements the method.

[0015] The above-described solution of the present invention has at least the following beneficial effects: The system collects raw sensing data from three-dimensional spatial state perception anchor points deployed on the top of the equipment casing (acoustic resonant cavity), the bottom inertial reference plane, and the lateral electromagnetic shield. Trajectory decoupling and phase synchronization are performed. The signal field is mapped using intermolecular van der Waals force attenuation characteristics to construct a three-dimensional spatial situation fitting ellipsoid. Topological meshing and multi-physics coupling numerical simulations are then performed on the ellipsoid to obtain multi-modal signal transmission link gain correction coefficients. Based on these coefficients, dynamic weight matching is applied to pre-stored speech text templates. Furthermore, after speech playback, dynamic weights are automatically generated based on the linkage identifiers in the playback content. This technology, which involves making phone calls to request alarms, overcomes the technical problems of existing alarm devices, such as high false trigger rates due to cross-coupling of multi-source sensor signals, inability of static voice templates and constant transmission parameters to adapt to complex spatial field attenuation leading to voice broadcast masking and distortion, delays and packet loss in wireless data reporting, and the disconnect between alarm triggering and remote response links due to rigid alarm linkage logic relying on manual dialing. As a result, it achieves the technical effects of accurate alarm event identification and standardized conversion, adaptive compensation optimization of wireless transmission links and high-fidelity directional voice broadcasting, and seamless and automated collaboration of local on-site warnings and remote emergency communication throughout the entire process. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a wireless communication-based alarm event reporting and remote response linkage method provided by an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of an alarm event reporting and remote response linkage system based on wireless communication, provided by an embodiment of the present invention.

[0018] Figure 3 This is a simulation diagram of the process of constructing a three-dimensional spatial situation fitting ellipsoid.

[0019] Figure 4 It is the time-frequency diagram of the original TTS audio stream.

[0020] Figure 5 This is the time-frequency diagram of the audio stream after channel adaptation. Detailed Implementation

[0021] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art.

[0022] like Figure 1As shown, an embodiment of the present invention proposes a method for alarm event reporting and remote response linkage based on wireless communication, the method comprising the following steps: Step 1: Collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; convert the processed data into a unified alarm trigger event. Step 2: Perform multi-source feature analysis on the alarm triggering event to obtain the event analysis results; extract the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point based on the event analysis results, introduce the attenuation characteristics of intermolecular van der Waals forces to map the signal field, and construct a three-dimensional spatial situation fitting ellipsoid. Step 3: Perform topological meshing and multi-physics coupled numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; based on the event analysis results and the multi-mode signal transmission link gain correction coefficient, obtain the audible and visual alarm driving command, and simultaneously extract the location and time information in the event, and encapsulate it to obtain the alarm event data packet; Step 4: Based on the location information in the alarm event data packet, and combined with the multimodal signal transmission link gain correction coefficient, perform dynamic weight matching on the pre-stored voice text template to obtain the target TTS voice broadcast content. Step 5: Convert the TTS voice broadcast content into a voice alarm signal and broadcast it through a speaker; Step 6: After the voice broadcast is completed, a call request is automatically generated based on the linkage identifier in the broadcast content, and an alarm voice message is played after the call is connected.

[0023] In this embodiment of the invention, multi-source raw sensor data from the acoustic resonant cavity, inertial reference plane, and three-dimensional spatial state sensing anchor points located on the device casing are used. After trajectory decoupling and phase synchronization processing, the raw data is converted into a unified alarm trigger event. Multi-source feature analysis of the alarm trigger event is performed, and the attenuation characteristics of intermolecular van der Waals forces are introduced to complete signal field mapping and construct a three-dimensional spatial situation fitting ellipsoid. Topological meshing and multi-physics coupling numerical simulation are performed on the fitted ellipsoid to obtain multi-modal signal transmission link gain correction coefficients. Combining the location information of the alarm event with the link gain correction coefficients, dynamic weight matching is performed on a pre-stored voice text template to generate target TTS voice broadcast content. After the voice broadcast is completed, a telephone dialing request is automatically generated based on the linkage identifier, and an alarm voice information is pushed after the call is connected—a full-process linkage technology. Therefore, it overcomes the limitations of existing wireless communication-based alarm devices. The core technical problems addressed include: a single alarm triggering method; insufficient accuracy in multi-source sensor data fusion leading to high risks of false alarms and missed alarms; decoupling of alarm events with spatial situation and wireless transmission link characteristics resulting in uncompensated signal transmission loss; delayed alarm information reporting; poor adaptability of TTS voice broadcast to alarm locations and channel environments; and low efficiency of remote emergency response due to the disconnect between alarm triggering, voice broadcasting, and emergency linkage dialing. The solution achieves the following technical effects: accurate fusion of multi-source sensor data and highly reliable alarm event triggering; adaptive gain optimization of multi-modal wireless transmission links in complex scenarios; generation of TTS voice broadcast content accurately matched to alarm location and channel characteristics; and construction of a closed-loop process for alarm event acquisition, situation analysis, link optimization, accurate broadcasting, and emergency linkage dialing. This improves the accuracy and reliability of alarm event reporting and enables efficient linkage between alarm events and remote emergency response.

[0024] In a preferred embodiment of the present invention, step 1 above may include: Step 1.1: Synchronously acquire the sound pressure fluctuation time sequence output by the acoustic resonant cavity, the three-axis acceleration and angular velocity vector sequence output by the bottom inertial reference plane, and the external electromagnetic field distortion amplitude-frequency sequence sensed by the lateral electromagnetic shield. Align and stitch these three types of time signals according to the sampling clock to obtain the original sensing data. Specifically, the acoustic resonant cavity at the top of the equipment casing, the bottom inertial reference plane, and the lateral electromagnetic shield together constitute a three-dimensional spatial state perception anchor point. This anchor point is used to acquire physical signals of the surrounding environment and the equipment's own motion state from all directions. The three types of three-dimensional spatial state perception anchor points maintain synchronous operation, using a unified hardware sampling clock as a reference for signal acquisition. The acoustic resonant cavity continuously outputs the sound pressure fluctuation time sequence, which characterizes the change characteristics of the sound pressure in the surrounding environment of the equipment over time. The bottom inertial reference plane synchronously outputs a three-axis acceleration vector sequence and a three-axis angular velocity vector sequence. These two types of sequences are used to characterize the linear and angular motion states of the device in three-dimensional space. The lateral electromagnetic shield senses changes in the external electromagnetic field in real time and outputs an external electromagnetic field distortion amplitude-frequency sequence. This sequence is used to characterize the disturbance characteristics of the surrounding electromagnetic field. The three types of timing signals are aligned with a unified sampling clock to avoid signal misalignment caused by differences in the hardware startup timing of each three-dimensional spatial state perception anchor point. The three types of timing signals are spliced ​​together according to a fixed timing dimension to form complete original sensing data.

[0025] Step 1.2: Map the raw sensor data to a pre-defined multi-degree-of-freedom rigid body kinematic state space, constructing a six-dimensional state variable matrix containing translational and rotational motion components. Specifically, the multi-degree-of-freedom rigid body kinematic state space describes the complete motion and attitude characteristics of the rigid body in three-dimensional space. This state space can carry the numerical mapping and feature expression of both translational and rotational motion parameters. After the raw sensor data is completely mapped to the multi-degree-of-freedom rigid body kinematic state space, the motion characteristics of the device are extracted from the data and separated into translational and rotational motion components. The translational motion component includes x-axis displacement, y-axis displacement, and z-axis displacement in a three-dimensional Cartesian coordinate system, while the rotational motion component includes rotation angles around the x-axis, y-axis, and z-axis. The six motion parameters are combined into column vectors in the order of translational components first and rotational components last, forming a six-dimensional state variable matrix. This matrix can completely represent the real-time position and attitude information of the device in three-dimensional space.

[0026] Step 1.3: Based on the six-dimensional state variable matrix, substitute the kinematic differential equations and perform trajectory decoupling operations on the translational and rotational motion components using orthogonal projection operators to obtain the decoupled independent motion state vectors. Specifically, the rigid body kinematic differential equations describe the change of the rigid body's motion state over time and are the core mathematical model for numerical modeling of rigid body motion. The six-dimensional state variable matrix is ​​represented by the symbol... In this representation, time is denoted by the symbol K, and the system state matrix is ​​denoted by the symbol... The input matrix is ​​represented by the symbol The external stimulus input is represented by the symbol. This means that substituting the six-dimensional state variable matrix into the rigid body kinematic differential equations completes the motion state modeling, and the corresponding mathematical formula is: ; Orthogonal projection operators are used to separate coupled motion signal components, ensuring the independent calculation accuracy of translation and rotation motion parameters. The orthogonal projection operator for the translation component uses the symbol... The orthogonal projection operator of the rotation component is represented by the symbol The decoupled translational independent motion state vector is represented by the symbol... The rotationally independent motion state vector is represented by the symbol The corresponding mathematical formulas are as follows: ; ; Independent motion state vectors are represented by the symbol This means that the independent motion state vector is obtained by superimposing the translational independent motion state vector and the rotational independent motion state vector, and the corresponding mathematical formula is: .

[0027] Step 1.4 involves performing time-domain registration on the independent motion state vectors to compensate for the phase shift caused by the hardware sampling clock deviation of each 3D spatial state perception anchor point, resulting in a phase-synchronized data stream. This phase-synchronized data stream is the processed data, specifically including: a cross-correlation phase alignment algorithm to correct the phase shift caused by the hardware sampling clock deviation of different signal sources, improving the time-domain synchronization accuracy of multi-source signals. The first set of independent motion state vectors is denoted by the symbol... The second set of independent motion state vectors is represented by the symbol... The time offset is indicated by the symbol. The cross-correlation function is represented by the symbol The mathematical formula for the cross-correlation function of two sets of independent motion state vectors is: ; The optimal time offset is determined by retrieving the peak position of the cross-correlation function. The signal center frequency is denoted by the symbol T, and the phase offset is denoted by the symbol... The mathematical formula for phase offset is: ; Imaginary unit uses a symbol The phase-synchronized data stream is represented by the symbol... This indicates that the phase-synchronized data stream is obtained from the independent motion state vectors after phase compensation, and the corresponding mathematical formula is: ; The phase-synchronized data stream eliminates phase errors caused by hardware clock skew and is used as the final data after trajectory decoupling and phase synchronization processing.

[0028] Step 1.5 involves performing sliding window variance evolution calculation and dynamic threshold determination on the processed data. When the data stream amplitude continuously exceeds the preset safety boundary, a state transition mechanism is triggered, normalizing and mapping the transition state identifier into a unified alarm trigger event. Specifically, the sliding window variance evolution calculation is used to analyze the amplitude fluctuation pattern of the data stream, reflecting the degree of abnormal signal change through the variance value. The sliding window length is set to 120 sampling points. Phase-synchronized data streams are extracted window by window, and the variance of the data within the window is calculated. The safety boundary threshold is set to 0.92. When the variance values ​​of 6 consecutive sliding windows are all greater than the safety boundary threshold, it is determined that the data stream amplitude continuously exceeds the safe range. The state transition mechanism is used to convert the abnormal signal state into an identifiable alarm trigger pre-signal. The transition state identifier is converted into a standardized signal format after normalization mapping. Normalization mapping is used to unify the numerical format of discrete state identifiers, ensuring the consistency of subsequent system identification. After normalization mapping, a unified alarm trigger event is formed, completing the complete conversion from raw sensor data to alarm trigger event.

[0029] In this embodiment of the invention, the acoustic pressure fluctuation time sequence of the acoustic resonant cavity, the three-axis acceleration and angular velocity vector sequence of the bottom inertial reference plane, and the electromagnetic field distortion amplitude-frequency sequence outside the lateral electromagnetic shield are synchronously acquired and spliced ​​according to the sampling clock. These sequences are then mapped to a multi-degree-of-freedom rigid body kinematic state space to construct a six-dimensional state variable matrix. The matrix is ​​substituted into the kinematic differential equations and the translational and rotational motion components are decoupled using orthogonal projection operators. A cross-correlation phase alignment algorithm is employed for time-domain registration to compensate for phase shifts caused by hardware sampling clock deviations at each three-dimensional spatial state sensing anchor point. Finally, the processed data stream is processed... The sliding window variance evolution calculation and dynamic threshold judgment trigger state transition mechanism, and normalized mapping to a unified alarm trigger event, overcome the technical problems of existing alarm devices, such as severe cross-coupling interference of translation and rotation motion in complex working conditions, phase inaccuracy caused by asynchronous hardware clocks of various sensing anchor points, and false alarms and missed alarms caused by traditional fixed threshold judgment. It achieves the technical effects of high-precision spatiotemporal alignment of multi-dimensional original sensor data, complete separation of cross-dimensional motion components, improved data stream fidelity after phase synchronization compensation, and standardized alarm event trigger logic and enhanced anti-interference ability.

[0030] In a preferred embodiment of the present invention, step 2 above may include: Step 2.1 involves performing joint time-frequency domain feature extraction on a unified alarm triggering event, separating the frequency domain energy spectrum features and the time domain envelope abrupt change features. Tensor fusion is then used to obtain the event analysis results. Specifically, joint time-frequency domain feature extraction is used to simultaneously mine the dual feature information of the alarm triggering event in both the time and frequency dimensions, fully preserving the event's time-domain abrupt change characteristics and frequency-domain energy distribution characteristics. Time-domain and frequency-domain analyses are performed simultaneously on the unified alarm triggering event. During time-domain analysis, the change nodes and abrupt change amplitudes of the signal amplitude are tracked to separate the time-domain envelope abrupt change features. During frequency-domain analysis, the energy distribution law of the signal is calculated through spectrum transformation operations to separate the frequency domain energy spectrum features. Tensor fusion is used to integrate independent feature data from different dimensions into a unified feature carrier, preserving the correlation and integrity of all feature information. The frequency domain energy spectrum features are represented by the symbol... The time-domain envelope abrupt change characteristics are represented by the symbol The event resolution results are indicated by symbols. The mathematical formula for tensor fusion is as follows: ; After tensor fusion processing, an event analysis result containing complete time-frequency domain features is generated.

[0031] Step 2.2: Based on the event analysis results, the real-time displacement deviation of each 3D spatial state-sensing anchor point is calculated using the inverse kinematics solver to obtain the spatial vector coordinates. Then, based on the constitutive relations of continuum mechanics, the surface micro-element deformation rate under force at each anchor point is calculated to construct the dynamic stress distribution gradient. Specifically, the inverse kinematics solver is used to deduce the spatial position and displacement change parameters of physical nodes from known motion state characteristic parameters, and is the core tool for calculating the coordinates of 3D spatial state-sensing anchor points. The event analysis results are input into the inverse kinematics solver, which performs inverse calculations on the motion parameters of each 3D spatial state-sensing anchor point to obtain the real-time displacement deviation of each anchor point. The event analysis results are represented by symbols... The real-time displacement deviation is indicated by the symbol. The inverse kinematics solver operator is represented by the symbol. The mathematical formula for the inversion calculation of real-time displacement deviation is as follows: ; Spatial vector coordinates are obtained by accumulating real-time displacement biases along the spatial axis, and are denoted by the symbol S. The constitutive relation of continuum mechanics is used to describe the deformation response of a solid medium under external forces, and can accurately calculate the degree of micro-element deformation on the surface of the three-dimensional spatial state sensing anchor point. Based on the constitutive relation of continuum mechanics, the surface micro-element deformation rate of each three-dimensional spatial state sensing anchor point under the force of an alarm event is calculated, and is denoted by the symbol K. The dynamic stress distribution gradient is constructed by arranging the surface micro-element deformation rates of each three-dimensional spatial state sensing anchor point in spatial order, and is denoted by the symbol K. This parameter indicates that it fully characterizes the stress distribution and change state of each sensing anchor point under the action of an alarm event.

[0032] Step 2.3: Substitute the spatial vector coordinates and dynamic stress distribution gradient into the field mapping function. This field mapping function incorporates the distance power-law attenuation characteristic of the intermolecular van der Waals potential energy function to characterize the energy dissipation and phase hysteresis of sound and electromagnetic waves in the propagation medium. The equivalent interaction potential weight matrix between each spatial node is calculated, completing the mapping of the signal field. Specifically, the field mapping function is used to convert spatial physical parameters into characteristic parameters of the signal propagation field, realizing a numerical mapping from the physical space state to the characteristics of the signal field. The distance power-law attenuation characteristic of the intermolecular van der Waals potential energy function is used to accurately characterize the energy dissipation and phase hysteresis of sound and electromagnetic waves in the propagation medium as the propagation distance increases, and is the core component of the field mapping function. Spatial vector coordinates are represented by the symbol... The dynamic stress distribution gradient is represented by the symbol. The field mapping coefficients are represented by the symbol... The van der Waals force potential energy is represented by the power-law decay exponent, indicated by the symbol. The field mapping function is represented by the symbol The mathematical formula for the field mapping function is: ; The equivalent interaction potential weight matrix between spatial nodes is obtained by matrix normalization of the output value of the field mapping function. The equivalent interaction potential weight matrix is ​​represented by the symbol... This means that the matrix completes the mapping from physical space to the signal field, and intuitively represents the intensity of signal interaction between each spatial node.

[0033] Step 2.4: Using spatial vector coordinates as geometric control points and the equivalent interaction potential weight matrix as spatial topological constraints, a three-dimensional spatial situation fitting ellipsoid is obtained by optimizing the boundary envelope of discrete situation data points within the alarm radiation influence domain. Specifically, this includes: a weighted least-squares surface fitting algorithm for high-precision surface fitting of discrete spatial data points, combined with topological weight constraints to improve the spatial matching degree and morphological accuracy of the fitted surface. Spatial vector coordinates serve as geometric control points, providing a basic spatial geometric positioning basis for surface fitting; the equivalent interaction potential weight matrix serves as a spatial topological constraint, limiting the spatial shape and extension range of the fitted surface. Boundary envelope optimization is used to regularize the external boundary shape of the fitted surface, improving the regularity and recognizability of the three-dimensional situation representation. Discrete situation data points within the alarm radiation influence domain are represented by symbols. The weighted least squares fitting operator is indicated by the symbol... The equivalent interaction potential weight matrix is ​​represented by the symbol... The ellipsoid representing the three-dimensional spatial situation fitting is represented by the symbol The mathematical formula for the weighted least squares surface fitting algorithm is as follows: ; By performing boundary envelope optimization on discrete situation data points using this algorithm, a three-dimensional spatial situation fitting ellipsoid that fully represents the spatial radiation situation and energy distribution of alarm signals is finally obtained.

[0034] In this embodiment of the invention, the event analysis results are obtained by performing joint feature extraction and tensor fusion on a unified alarm trigger event; the spatial vector coordinates are obtained by inverting and calculating the real-time displacement bias through an inverse kinematics solver; and the dynamic stress distribution gradient is constructed based on the constitutive relation of continuous medium mechanics. These two parameters are then substituted into a field mapping function that incorporates the distance power-law attenuation characteristics of the intermolecular van der Waals potential energy function to calculate the equivalent interaction potential weight matrix and complete the signal field mapping. Furthermore, a weighted least-squares surface fitting algorithm is used to optimize the boundary envelope and construct a three-dimensional spatial situation fitting ellipsoid using the spatial vector coordinates as geometric control points and the equivalent interaction potential weight matrix as spatial topological constraints. This overcomes the technical problems of existing alarm systems, such as difficulty in accurately extracting multi-dimensional event features in complex media environments, inability to accurately characterize the energy dissipation and phase hysteresis of sound and electromagnetic waves in the alarm radiation domain, and the lack of dynamic stress constraints in traditional spatial modeling leading to blurred and distorted situation boundaries. Thus, the invention achieves high-fidelity analysis of multi-dimensional features of alarm events, accurate quantitative mapping of signal attenuation and phase hysteresis characteristics in complex propagation media, and high-precision fitting and reconstruction of the three-dimensional situation boundary of the alarm radiation influence domain.

[0035] In a preferred embodiment of the present invention, step 3 above may include: Step 3.1: Using the geometric surface of the 3D spatial situation fitting ellipsoid as the computational boundary, the continuous computational domain is discretized into a hybrid topological mesh containing acoustic propagation nodes, electromagnetic radiation nodes, and stress transmission nodes, resulting in a discrete mesh set. Specifically, the geometric surface of the 3D spatial situation fitting ellipsoid serves as the computational boundary. An adaptive unstructured mesh generation algorithm is used to discretize the continuous 3D computational domain into unstructured mesh units, achieving accurate fitting of complex surface boundaries and mesh refinement in local areas, thus improving the accuracy and efficiency of subsequent multiphysics calculations. Using the geometric surface of the 3D spatial situation fitting ellipsoid as the outer boundary, mesh generation is performed on the internal computational domain. The mesh unit size variation range is set to 0.1 meters to 1.0 meters, and the field gradient change rate threshold is 0.8. When the values ​​of sound pressure attenuation gradient, electromagnetic radiation intensity, and stress change rate are greater than 0.8, the mesh units are automatically refined; when the values ​​are less than or equal to 0.8, coarser mesh units are used, forming a hybrid topological mesh containing acoustic propagation nodes, electromagnetic radiation nodes, and stress transmission nodes. Acoustic propagation nodes are used to characterize field points along the sound wave propagation path, electromagnetic radiation nodes are used to characterize field points within the coverage area of ​​electromagnetic wave radiation, and stress transmission nodes are used to characterize field points along the stress distribution transmission path. The three types of nodes are interconnected and constitute a complete discrete mesh set.

[0036] Step 3.2: Based on the discrete mesh set, the multiphysics coupling solver is invoked to jointly iteratively solve the sound pressure attenuation gradient at the acoustic propagation node, the multipath interference intensity at the electromagnetic radiation node, and the vibration energy dissipation at the stress transmission node, obtaining the field coupling response matrix. Specifically, the multiphysics coupling solver is used to jointly iteratively solve the governing equations of different physical fields, realizing the interaction analysis of the three types of physical fields: acoustic, electromagnetic, and stress, avoiding errors caused by single-field calculations. Based on the discrete mesh set, the multiphysics coupling solver is invoked. This operator uses the three types of nodes in the discrete mesh set as computational units to construct the acoustic propagation control equation, the electromagnetic radiation control equation, and the stress transmission control equation, respectively. By iteratively updating the physical field parameters of each node, the coupling effect analysis between different physical fields is realized. The sound pressure attenuation gradient characterizes the energy attenuation rate of sound waves during propagation, the multipath interference intensity characterizes the signal superposition effect caused by reflection and scattering of electromagnetic waves during propagation, and the vibration energy dissipation characterizes the energy loss caused by the vibration of the medium under stress. The sound pressure attenuation gradient, multipath interference intensity, and vibration energy dissipation are used as input parameters for the coupled solution and input into the multiphysics coupled solution operator. The iterative convergence threshold is set to 1. e-6 After iterative convergence calculation, the field-domain coupled response matrix containing the physical field response data of each node is obtained. The sound pressure attenuation gradient is represented by the symbol... The intensity of multipath interference is indicated by the symbol. The symbol for vibrational energy dissipation is used. Discrete grid sets are represented by the symbol The multiphysics coupling solution operator is represented by the symbol... The field-coupled response matrix is ​​represented by the symbol... The corresponding mathematical formula is: .

[0037] Step 3.3 involves inputting the field coupling response matrix into the link compensation calculation unit, performing inverse differential operations based on a preset wireless communication channel reference attenuation spectrum, extracting quantization parameters for compensating the transmission loss of each mode signal, and obtaining the multimode signal transmission link gain correction coefficients. Specifically, this includes calculating the loss compensation parameters during wireless signal transmission based on the field coupling response matrix and the preset wireless communication channel reference attenuation spectrum, thereby achieving adaptive optimization of the multimode signal transmission link. The field coupling response matrix is ​​represented by the symbol... The reference attenuation spectrum of a wireless communication channel is represented by the symbol [symbol missing]. The inverse difference operator is indicated by the symbol... The multimode signal transmission link gain correction coefficient is indicated by the symbol... This means that the field coupling response matrix is ​​input to the link compensation calculation unit, which has a built-in preset wireless communication channel reference attenuation spectrum. This attenuation spectrum characterizes the loss pattern of wireless signals under ideal transmission conditions. Through inverse differential operation, the actual signal attenuation data of each node in the field coupling response matrix is ​​compared with the ideal data of the reference attenuation spectrum, and the difference between the two is extracted. This difference is the quantized compensation parameter for the transmission loss of each mode signal. After integration and normalization, with the normalization range set to 0 to 1, a unified multimode signal transmission link gain correction coefficient is obtained. This coefficient is used to compensate for energy loss and phase shift during wireless signal transmission, improving the stability and reliability of signal transmission. The corresponding mathematical formula is: .

[0038] Step 3.4: Logically map the event parsing results with the multimodal signal transmission link gain correction coefficient to obtain the mapping result; match the preset sound and light control protocol stack according to the mapping result to obtain the sound and light alarm driving command, specifically including: the logical mapping of the event parsing results with the multimodal signal transmission link gain correction coefficient is used to convert the event characteristics and link status into sound and light alarm control commands to achieve accurate matching between alarm output and event scene. The event analysis results characterize the time-frequency domain features of the alarm event, and the multimodal signal transmission link gain correction coefficient characterizes the transmission status parameters of the wireless communication link. The event analysis results and the multimodal signal transmission link gain correction coefficient are input to the logic mapping module. The logic mapping module has built-in association rules between event features and control commands. Based on the event type, severity and link status characterized by the multimodal signal transmission link gain correction coefficient in the event analysis results, the corresponding audio-visual control protocol stack parameters are matched. The audio-visual control protocol stack contains control parameters such as the frequency, brightness and duration of the audio-visual alarm. Based on the result of the logic mapping, the corresponding parameter configuration is retrieved from the preset audio-visual control protocol stack. The frequency range of the audio-visual alarm is set to 1Hz to 5Hz, the brightness range is 500cd to 1000cd, and the duration is not less than 10 seconds. A standardized audio-visual alarm drive command is generated. This command is used to control the audio-visual output module of the alarm device to perform the corresponding alarm action.

[0039] Step 3.5: Synchronously extract the location and time information carried in the event analysis results. Perform binary serialization encoding and protocol frame encapsulation on the audible and visual alarm drive command, location information, time information, and multimodal signal transmission link gain correction coefficient to obtain the alarm event data packet. Specifically, the location and time information are directly extracted from the event analysis results. The location information represents the specific spatial location of the alarm event, including latitude, longitude, and floor number data. The time information represents the specific time of the alarm event, accurate to the millisecond level. Integrate the audible and visual alarm drive command, location information, time information, and multimodal signal transmission link gain correction coefficient, perform binary serialization encoding to convert various parameters into binary data format, and then encapsulate according to the preset protocol frame format, adding protocol fields such as frame header, frame trailer, and check bit. Set the data packet length to 128 bytes, and use the CRC-16 check algorithm for the check bit to form a complete alarm event data packet. The alarm event data packet contains all the key information of the alarm event and can be directly transmitted to the back-end management platform and emergency terminal equipment through the wireless communication link.

[0040] In this embodiment of the invention, a hybrid topological mesh is constructed by adaptively partitioning an ellipsoid with a three-dimensional spatial state fitting geometric surface as the computational boundary. A multi-physics coupling solver is invoked to jointly iteratively solve the acoustic pressure attenuation gradient at acoustic propagation nodes, the multipath interference intensity at electromagnetic radiation nodes, and the vibration energy dissipation at stress transmission nodes to obtain the field coupling response matrix. This matrix is ​​input into a link compensation calculation unit and, combined with a preset wireless communication channel reference attenuation spectrum, performs inverse differential operations to extract quantization parameters for compensating for the transmission loss of each mode of signal, obtaining the multi-mode signal transmission link gain correction coefficient. Furthermore, this correction coefficient is logically mapped and matched with the event analysis results to a preset acoustic-optical control protocol stack to generate driving instructions. Simultaneously, position and time information are extracted to adjust the driving instructions, spatiotemporal parameters, and gain correction coefficient. The technology employs binary serialization encoding and protocol frame encapsulation to construct alarm event data packets. This overcomes the technical problems of existing alarm systems, such as the difficulty in accurately quantifying the transmission loss caused by the coupling of multiple physical fields (sound, electricity, and force) in complex spaces, the lack of adaptive compensation mechanisms in wireless communication links leading to packet loss and distortion in multipath fading and strong interference channels, and the static solidification of alarm command generation and data encapsulation processes resulting in insufficient integrity of reported information and precision of equipment linkage control. This technology achieves accurate quantification and adaptive dynamic compensation of multimodal signal transmission link losses, intelligent adaptation and issuance of audible and visual alarm drive commands, and high-fidelity standardized encapsulation of alarm event data packets. It improves the anti-interference capability, transmission reliability, and data parsing and linkage response efficiency of wireless alarm data reporting under complex working conditions.

[0041] In a preferred embodiment of the present invention, step 4 above may include: Step 4.1 involves parsing the alarm event data packet, extracting location information and multimodal signal transmission link gain correction coefficients, and converting the location information into a spatial distance attenuation factor. Specifically, the alarm event data packet carries core information related to the alarm event, including location information, time information, audible and visual alarm drive commands, and multimodal signal transmission link gain correction coefficients. This serves as the basic data carrier for voice broadcast content matching. A layer-by-layer parsing operation is performed on the alarm event data packet, disassembling the protocol frame structure within the packet to accurately extract the location information and multimodal signal transmission link gain correction coefficients. The location information characterizes the specific geographical location of the alarm event, including three-dimensional spatial coordinates and the corresponding functional area identifier. The spatial distance attenuation factor characterizes the energy attenuation of the alarm voice signal over propagation distance and is a core dynamic parameter for voice template matching. The alarm event data packet is represented by the symbol W, and the location information is represented by the symbol... The multimodal signal transmission link gain correction coefficient is represented by the symbol Y, and the spatial distance attenuation factor is represented by the symbol The spatial distance conversion factor is indicated by the symbol. This indicates that the spatial distance conversion factor is fixed at 0.05. The mathematical formula for converting location information into a spatial distance attenuation factor is: ; After the parsing and conversion operations are completed, the gain correction coefficient of the multimode signal transmission link is retained synchronously.

[0042] Step 4.2: Retrieve the local template repository and retrieve at least two pre-stored voice-text templates associated with the geographic grid to which the location information belongs. Extract acoustic prosodic features and semantic key fragments from each template. Specifically, the local template repository is used to pre-store fire emergency voice-text templates for different scenarios and locations. The template content covers types such as evacuation guidance, fire handling, and safety reminders, and can be quickly retrieved based on the geographic grid. The geographic grid divides the target location into several fixed-size regional units, each unit corresponding to a unique voice-text template. The fixed side length of the grid unit is 5 meters. Based on the geographic grid to which the location information belongs, perform a precise search in the local template repository to retrieve at least two pre-stored voice-text templates directly associated with that geographic grid. Acoustic prosodic features are used to characterize the acoustic attributes of the voice text, such as the broadcast rhythm, pitch intensity, and pause duration, which are the core guarantee for the fluency of voice broadcasting. Semantic key fragments are used to extract the core emergency instruction information in the voice text, including key content such as location guidance, handling requirements, and evacuation direction. Perform feature extraction operations on each retrieved voice-text template to separate the corresponding acoustic prosodic features and semantic key fragments.

[0043] Step 4.3 involves performing a matrix multiplication operation on the spatial distance attenuation factor and the multimodal signal transmission link gain correction coefficient to construct a dynamic weight allocation vector. Specifically, this includes: the matrix multiplication operation is used to numerically fuse the spatial distance attenuation factor and the multimodal signal transmission link gain correction coefficient to generate dynamic weight parameters adapted to the current scenario, ensuring the accuracy of speech template matching. The spatial distance attenuation factor is represented by the symbol... The multimode signal transmission link gain correction coefficient is indicated by the symbol... The dynamic weight allocation vector is represented by the symbol... The spatial distance attenuation factor and the multimodal signal transmission link gain correction coefficient are multiplied by a matrix, and the corresponding mathematical formula is: ； The dynamic weight allocation vector includes two types of parameters: acoustic prosodic feature weights and semantic key segment weights. The weight values ​​are limited to the range of 0 to 1, and the sum of all weight parameters is 1. This vector can dynamically adjust the proportion of each feature according to the alarm location and link status, thereby improving the scene adaptability of the voice content.

[0044] Step 4.4: Based on the dynamic weight allocation vector, perform weighted fusion calculation on the acoustic prosodic features and semantic key segments of at least two pre-stored speech-text templates to obtain a fusion score ranking; select the final matching sequence based on the fusion score ranking to obtain the target TTS speech broadcast content. Specifically, this includes: weighted fusion calculation is used to combine the dynamic weight allocation vector to optimally integrate the feature data of multiple speech-text templates to generate the speech content most suitable for the current alarm scenario. The dynamic weight allocation vector is represented by the symbol... Acoustic prosodic features are represented by symbols. The semantic key segments are represented by symbols. The fusion score is indicated by symbols. The mathematical formula for weighted fusion calculation is as follows: ; The fusion scores of all speech-text templates are sorted in descending order to obtain the fusion score ranking results. A score filtering threshold of 0.85 is set, and the matching sequence with a fusion score greater than or equal to 0.85 and ranked first is selected. The speech content corresponding to this sequence is then normalized to obtain the final target TTS speech playback content.

[0045] In this embodiment of the invention, the technical means of parsing alarm event data packets to extract location information and multimodal signal transmission link gain correction coefficients and converting them into spatial distance attenuation factors, retrieving and retrieving pre-stored voice text templates associated with the geographic grid to which the location belongs and extracting their acoustic prosodic features and semantic key segments, constructing a dynamic weight allocation vector by performing matrix multiplication of the spatial distance attenuation factor and the link gain correction coefficients, and performing weighted fusion calculation and score sorting based on the acoustic prosodic features and semantic key segments of multiple templates to generate target TTS voice broadcast content, thus overcoming the limitations of existing alarm device voice broadcast methods. The use of static, generic templates, which cannot adaptively match the spatial distance attenuation and wireless channel transmission loss of specific alarm points, leads to poor targeting of broadcast content, insufficient acoustic clarity, and difficulty in effectively conveying accurate evacuation guidance instructions in complex propagation environments. This paper addresses the technical problems of using static, generic templates, which cannot adaptively match the spatial distance attenuation and wireless channel transmission loss of specific alarm points, resulting in poor targeting of broadcast content, insufficient acoustic clarity, and difficulty in effectively conveying accurate evacuation guidance instructions in complex propagation environments. This paper achieves the technical effect of high-fidelity generation and highly adaptable distribution of alarm voice broadcasts under complex working conditions.

[0046] In a preferred embodiment of the present invention, step 5 above may include: Step 5.1: Receive the target TTS voice broadcast content, perform a nonlinear mapping operation from phoneme sequence to acoustic parameters, extract the fundamental frequency trajectory, formant frequencies, and duration envelope parameters to obtain the initial digital audio stream. Specifically, this includes: the target TTS voice broadcast content is a standardized text sequence containing complete emergency broadcast semantic information; after receiving the target TTS voice broadcast content, parse the corresponding phoneme sequence, which is the basic unit of speech synthesis, representing the combination of articulatory units in the broadcast content; perform a nonlinear mapping operation from phoneme sequence to acoustic parameters, which converts discrete phoneme units into continuous speech acoustic parameters; extract three core parameters: fundamental frequency trajectory, formant frequencies, and duration envelope. The fundamental frequency trajectory represents the pitch variation pattern of the speech signal, the formant frequencies represent the timbre characteristics of the speech signal, and the duration envelope represents the rhythm and pause characteristics of the speech signal. Integrate the three types of acoustic parameters to generate the initial digital audio stream. The target TTS voice broadcast content is represented by the symbol U, and the phoneme sequence is represented by the symbol... Nonlinear mapping operators are represented by the symbol The initial digital audio stream uses symbols The corresponding mathematical formula is: ; Phoneme sequence Obtained by parsing the target TTS voice broadcast content U. This is a nonlinear mapping operator that maps a phoneme sequence to acoustic parameters including the fundamental frequency trajectory, formant frequencies, and duration envelope, and generates an initial digital audio stream. .

[0047] Step 5.2 involves applying the multimodal signal transmission link gain correction coefficient to perform frequency domain predistortion compensation and dynamic range compression on the initial digital audio stream. This suppresses the masking effect of speaker nonlinear harmonic distortion and ambient background noise, resulting in a channel-adapted digital audio signal. Specifically, the multimodal signal transmission link gain correction coefficient is a loss compensation parameter for the wireless transmission link, used to correct the transmission attenuation and phase shift of the voice signal. The multimodal signal transmission link gain correction coefficient is applied to sequentially perform frequency domain predistortion compensation and dynamic range compression on the initial digital audio stream. Frequency domain predistortion compensation is used to preemptively cancel the speaker's nonlinear harmonic distortion, while dynamic range compression is used to suppress the masking effect of ambient background noise and improve the intelligibility of the voice signal in complex environments. The cutoff frequency for frequency domain predistortion compensation is set to 3.4kHz, the threshold for dynamic range compression is set to -20dB, and the compression ratio is set to 4:1. The initial digital audio stream is represented by the symbol... The multimode signal transmission link gain correction coefficient is indicated by the symbol... Frequency domain predistortion compensation operator using symbolic representation Dynamic range compression operators use symbols The digital audio signal after channel adaptation is represented by the symbol The corresponding mathematical formula is: ; After frequency domain predistortion compensation and dynamic range compression processing, a channel-adapted digital audio signal is obtained, which can be adapted to the acoustic characteristics of the loudspeaker and the ambient noise conditions.

[0048] Step 5.3: The channel-adapted digital audio signal is input to the digital-to-analog converter (DAC). After anti-aliasing low-pass filtering and Class D power amplification, an analog electric drive signal with impedance characteristics strictly matched to the speaker voice coil is obtained. This analog electric drive signal is the voice alarm signal. Specifically, the channel-adapted digital audio signal is input to the DAC, which converts the discrete digital audio signal into a continuous analog electrical signal. The converted analog electrical signal undergoes anti-aliasing low-pass filtering with a cutoff frequency of 20kHz to filter out high-frequency noise and aliasing components generated during the DAC process. The filtered signal is then input to the Class D power amplification unit. The Class D power amplification unit has high efficiency and low distortion driving characteristics, amplifying the signal to a power level that strictly matches the speaker voice coil impedance. The nominal impedance of the speaker voice coil is 8 ohms. The output impedance of the amplification unit deviates from the voice coil impedance by within ±0.5 ohms, resulting in an impedance-matched analog electric drive signal, which is the voice alarm signal.

[0049] Step 5.4: Load the voice alarm signal onto the diaphragm driver of the speaker, and control the acoustic-electrical-mechanical-acoustic energy conversion link to perform sound pressure radiation. This completes the physical broadcast of the voice alarm signal in the external space of the device. Specifically, this includes: loading the voice alarm signal onto the diaphragm driver of the speaker, driving the speaker to perform the acoustic-electrical-mechanical-acoustic energy conversion link. The electrical signal drives the voice coil to generate an alternating magnetic field. The interaction between the voice coil and the permanent magnet causes the diaphragm to vibrate. The diaphragm vibration pushes the surrounding air to form sound pressure radiation, converting the electrical signal into a propagable sound wave signal. The maximum sound pressure level of the sound pressure radiation is set to 110dB, and the frequency response range is set to 200Hz to 5kHz. This completes the physical broadcast of the voice alarm signal in the external space of the device, realizing on-site broadcasting of emergency voice messages.

[0050] In this embodiment of the invention, the initial digital audio stream is obtained by receiving the target TTS voice broadcast content and performing a nonlinear mapping operation from phoneme sequence to acoustic parameters to extract the fundamental frequency trajectory, formant frequency, and duration envelope parameters. The initial digital audio stream is then subjected to frequency domain pre-distortion compensation and dynamic range compression processing using a multimodal signal transmission link gain correction coefficient to suppress the masking effect of speaker nonlinear harmonic distortion and ambient background noise. An analog electric drive signal with impedance characteristics strictly matched to the speaker voice coil is obtained through anti-aliasing low-pass filtering and Class D power amplification by a digital-to-analog converter. This analog electric drive signal is then applied to the speaker diaphragm drive end to control the acoustic-electric-mechanical-acoustic energy conversion link to perform sound pressure radiation and complete the physical broadcast. This technological approach overcomes the technical problems of existing alarm devices, such as the lack of adaptive compensation for complex acoustic environments and hardware nonlinearity, which leads to a sharp drop in the clarity of the broadcast voice under strong environmental noise, severe harmonic distortion of the speaker itself, and low sound pressure radiation efficiency and limited effective propagation distance due to the lack of impedance matching and signal frequency domain adaptation in traditional audio driving. It achieves high-fidelity conversion of the alarm voice signal across the entire chain, from acoustic feature extraction, frequency domain pre-distortion compensation, impedance matching driving to physical sound pressure radiation. This improves the anti-noise masking capability and sound field penetration of the voice broadcast under complex working conditions, ensuring high-definition, high-fidelity, and long-distance effective coverage of alarm voice information received by on-site personnel.

[0051] In a preferred embodiment of the present invention, step 6 above may include: Step 6.1: Monitor the audio playback buffer status of the speaker. When the buffer data is cleared and the broadcast duration reaches a preset threshold, the voice broadcast is considered complete. Simultaneously, parse the data frame control field of the broadcast content and extract the embedded linkage identifier. Specifically, the speaker's audio playback buffer is used to temporarily store the voice data to be played, and the buffer status directly reflects the real-time progress of the voice broadcast. Monitor the speaker's audio playback buffer status in real time and read the remaining data volume in the buffer. When the remaining data volume in the buffer is 0 and the voice broadcast duration reaches a preset threshold, the voice broadcast is considered complete. The preset threshold for voice broadcast duration is set to 15 seconds, based on the normal duration of emergency voice broadcasts, to ensure the complete delivery of the broadcast content. Simultaneously parse the data frame control field corresponding to the target TTS voice broadcast content. The data frame control field contains control information for the broadcast content, from which the embedded linkage identifier is extracted. The linkage identifier is used to trigger the subsequent emergency call dialing process and is the core correlation parameter between voice broadcast and telephone call linkage.

[0052] Step 6.2: Input the linkage identifier into the session control layer of the wireless communication baseband processor, match the preset emergency communication routing strategy and target terminal addressing protocol, and construct a telephone dialing request containing session initiation command, identity authentication token and media negotiation parameters. Specifically, this includes: inputting the extracted linkage identifier into the session control layer of the wireless communication baseband processor. The session control layer is the core module responsible for establishing emergency communication sessions and negotiating parameters. It has a built-in preset emergency communication routing strategy and target terminal addressing protocol. According to the linkage identifier, the session control layer automatically matches the corresponding emergency communication routing strategy and target terminal addressing protocol. The emergency communication routing strategy prioritizes low-latency and high-reliability communication links to ensure fast and stable transmission of telephone requests. The target terminal addressing protocol is used to accurately locate the preset emergency contact person telephone and fire alarm telephone terminal. Based on the matching results, a complete telephone call request is constructed. This request includes three parts: a session initiation command, an authentication token, and media negotiation parameters. The session initiation command is used to initiate a telephone communication session. The authentication token is used to verify the legitimacy of the device and prevent unauthorized access requests. The media negotiation parameters include voice encoding format, sampling rate, etc., to ensure that the voice transmission between the device and the remote terminal is compatible. Its calculation logic is that the telephone call request is equal to the target terminal addressing protocol after processing.

[0053] Step 6.3: The wireless radio frequency front-end sends the call request to the operator's core network. It listens for and parses the link establishment status code in the downlink signaling feedback. When the status code indicates a successful two-way voice channel handshake, the communication link is considered established. Specifically, the wireless radio frequency front-end converts the constructed call request into a radio frequency signal conforming to the 4G communication standard, enabling wireless transmission of the request signal and sending the call request to the operator's core network. After receiving the request, the operator's core network executes terminal addressing and link establishment processes, and feeds back the link establishment status code to the downlink. The status code uses decimal encoding, where 00 indicates a successful two-way voice channel handshake, 01 indicates link establishment failure, and 02 indicates no terminal response. The link establishment status code in the downlink signaling feedback is monitored and parsed in real time. When a status code of 00 is detected, the emergency communication link is considered established, and voice transmission is possible. If a status code of 01 or 02 is detected, the call request will be re-initiated, with a maximum of 3 retries to ensure a successful communication link establishment and guarantee the stability of emergency communication.

[0054] Step 6.4: After the communication link is established, the standardized alarm voice coding sequence associated with the alarm triggering event is retrieved. Channel coding, interleaving, and orthogonal frequency division multiplexing modulation mapping are performed to obtain the wireless transmission baseband stream, which is then pushed to the remote terminal in real time as alarm voice information. Specifically, after the communication link is established, the standardized alarm voice coding sequence associated with the current alarm triggering event is retrieved from the device's local storage unit. This sequence contains core emergency information such as alarm location, fire type, and emergency response prompts, allowing the remote terminal to quickly grasp the key alarm content. The retrieved standardized alarm voice coding sequence is then processed sequentially with channel coding, interleaving, and orthogonal frequency division multiplexing modulation mapping. Channel coding uses convolutional coding with a code rate of 0.5 to reduce the bit error rate during wireless transmission and ensure accurate voice information transmission. The interleaving depth is set to 128 to break up any sudden errors that may occur during transmission. Orthogonal frequency division multiplexing modulation mapping converts the encoded signal into a baseband signal suitable for 4G wireless transmission, improving transmission efficiency. Its operation logic is that the wireless transmission baseband stream is obtained by processing the orthogonal frequency division multiplexing modulation mapping pair. The generated wireless transmission baseband stream is used as alarm voice information and is pushed to the remote emergency terminal in real time through the established communication link to realize the remote voice transmission of alarm information.

[0055] Step 6.5: Monitor the media stream reception confirmation signal returned by the remote terminal. When the confirmation signal indicates that the alarm voice information has been completely delivered and the decoding verification has passed, terminate the media stream transmission and release the communication channel resources occupied by the phone call request. Specifically, this includes: real-time monitoring of the media stream reception confirmation signal returned by the remote emergency terminal. This signal is used to feedback the reception status and decoding verification result of the alarm voice information, including a reception completion identifier, a decoding verification value, and a preset verification code. When the decoding verification value in the confirmation signal matches the preset verification code, it indicates that the alarm voice information has been completely delivered to the remote terminal and the decoding verification has passed. At this time, immediately terminate the media stream transmission, stop pushing the alarm voice information to the remote terminal, and simultaneously release the 4G wireless communication channel resources occupied by the phone call request to avoid wasting channel resources.

[0056] In this embodiment of the invention, the following technical means are employed: monitoring the speaker audio playback buffer status and broadcast duration to determine the completion of voice broadcasting; simultaneously parsing and extracting the embedded linkage identifier; inputting the linkage identifier into the wireless communication baseband processor session control layer to match the emergency communication routing strategy and target terminal addressing protocol to construct a telephone dialing request; sending the request to the operator's core network side through the wireless radio frequency front end and listening to and parsing the link establishment status code in the downlink signaling feedback to determine the communication link is connected; after the link is connected, retrieving the standardized alarm voice coding sequence, performing channel coding interleaving and orthogonal frequency division multiplexing modulation mapping to generate a wireless transmission baseband stream for real-time push of alarm voice information; and listening to the media stream reception confirmation signal returned by the remote terminal and terminating the transmission and releasing the communication channel resources after complete delivery and verification. Therefore, this overcomes... This invention addresses the technical problems of existing alarm systems, such as the lack of a timing coordination mechanism between local voice broadcasting and remote telephone calls leading to delayed response, the lack of status monitoring and signaling verification during wireless communication link establishment resulting in low call success rates and compromised information transmission integrity, and the lack of an intelligent release mechanism for communication channel resources causing resource waste and subsequent emergency communication blockage. It achieves seamless timing between local voice broadcasting and remote telephone call triggering, traceable verification and high reliability of emergency communication link establishment status, high-fidelity encoded transmission and complete delivery confirmation of alarm voice information, and intelligent scheduling and efficient release of communication channel resources. This improves the timeliness, reliability, and system resource utilization efficiency of the entire automated linkage process from on-site alert to remote dispatch.

[0057] like Figure 2 As shown, embodiments of the present invention also provide an alarm event reporting and remote response linkage system based on wireless communication, comprising: The acquisition module is used to collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; to perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; and to convert the processed data into a unified alarm trigger event. The analysis module is used to perform multi-source feature analysis on alarm trigger events to obtain event analysis results; based on the event analysis results, the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point are extracted, and the attenuation characteristics of intermolecular van der Waals forces are introduced to map the signal field and construct a three-dimensional spatial situation fitting ellipsoid. The calculation module is used to perform topological meshing and multi-physics coupled numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; based on the event analysis results and the multi-mode signal transmission link gain correction coefficient, the audible and visual alarm driving command is obtained, and the location information and time information in the event are extracted and encapsulated to obtain the alarm event data packet; The matching module is used to perform dynamic weight matching on the pre-stored voice text template based on the location information in the alarm event data packet and the multimodal signal transmission link gain correction coefficient to obtain the target TTS voice broadcast content. The conversion module is used to convert TTS voice broadcast content into voice alarm signals and broadcast them through a speaker. The processing module is used to automatically generate a call request based on the linkage identifier in the broadcast content after the voice broadcast is completed, and play the alarm voice information after the call is connected.

[0058] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0059] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0060] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0061] Experimental example: Preset conditions: Voice and text template library: Pre-stores differentiated evacuation voice templates for different sub-areas such as the east passage of Zone H, the middle of the shelves in Zone H, and the vicinity of ventilation ducts.

[0062] Linkage identifier: A linkage identifier code is preset in the TTS voice content to trigger automatic dialing of the warehouse security duty room and the fire brigade.

[0063] Step 1, Multi-source sensor data acquisition and alarm event triggering: In a simulated initial electrical fire scenario in warehouse H area, personnel triggered the equipment's manual alarm button. Simultaneously, the equipment's sensors detected environmental anomalies and collected three data streams: the acoustic resonant cavity captured specific low-frequency noise from the flames; the bottom inertial reference surface detected minute vibrations caused by personnel running or explosions; and the lateral electromagnetic shield sensed spatial electromagnetic field distortion signals caused by short circuits. These three types of time-series signals were aligned and mapped to a six-dimensional state space for trajectory decoupling, separating the motion component dominated by fire characteristics. Phase synchronization was then performed to compensate for minor clock differences between the sensors. A sliding window variance calculation was performed on the processed data stream; if the variance consistently exceeded a safety threshold, a valid alarm was detected, generating a unified alarm trigger event.

[0064] Step 2, Event Analysis and 3D Spatial Situation Construction: By performing joint time-frequency domain feature extraction, the frequency domain energy concentration region of fire noise and the temporal abrupt change envelope of vibration signals are separated from the event. After tensor fusion of the two, an event analysis result is formed, including labels such as fire type-electrical and intensity level-medium. Based on the event analysis result, the spatial vector coordinates of the alarm event's effect on the equipment are calculated by using an inverse kinematics solver and combining the precise coordinates of the equipment itself. The dynamic stress distribution gradient of the equipment shell is calculated based on continuum mechanics to infer the direction of the impact source. The core step is to introduce the attenuation characteristics of intermolecular van der Waals forces to map the physical spatial coordinates and stress gradient into a signal field attenuation model. With spatial vector coordinates as control points and the equivalent interaction potential weight matrix as constraints, a three-dimensional spatial situation fitting ellipsoid is finally constructed.

[0065] Figure 3 The core results of step 2 are visually demonstrated. The scattered points in the figure are discrete situation points calculated based on the inversion of sensor data. By introducing the equivalent interaction potential weight matrix calculated by the van der Waals force attenuation model as a spatial topological constraint, and using the equipment location and the inverted source direction as control points, an optimal ellipsoid boundary is fitted. This ellipsoid accurately wraps the predicted core area affected by the fire.

[0066] Step 3, Multiphysics Coupling Simulation and Alarm Data Packet Generation: Using the surface of a 3D spatial ellipsoid as the computational boundary, an adaptive unstructured mesh is generated within the ellipsoid, containing acoustic, electromagnetic, and stress nodes. A multiphysics coupled solver is then invoked to jointly solve for acoustic attenuation, electromagnetic multipath interference, and structural vibration energy dissipation on the mesh, yielding the field-domain coupled response matrix. This matrix is ​​compared with the ideal 4G channel attenuation spectrum, and through inverse difference operations, the multimode signal transmission link gain correction coefficient required to compensate for the complex environment of the warehouse is calculated.

[0067] Step 4, Intelligent speech generation based on location and link: Parse the alarm event data packet to extract location information: the east side of zone H and the link gain correction coefficient. Convert the location information into a spatial distance attenuation factor. Retrieve two pre-stored templates related to the east side of zone H from the template library. Multiply the spatial distance attenuation factor and the link gain correction coefficient by a matrix to generate a dynamic weight allocation vector. This vector assigns different importance to semantic key segments and acoustic prosodic features. Perform weighted fusion and score ranking on the templates to generate the final target TTS voice broadcast content: Warning! Fire in zone H. Please evacuate to the main exit along the west passage. There is thick smoke on site. Please move low to the ground.

[0068] Step 5, high-fidelity voice broadcasting with channel adaptation: TTS converts the text into an initial digital audio stream containing the fundamental frequency trajectory, formant frequency, and duration envelope. It then calls the calculated link gain correction coefficients to perform frequency domain predistortion compensation and dynamic range compression on the audio stream, and drives the speaker through a Class D amplifier for high-fidelity playback.

[0069] Figure 4 This is the original time-frequency diagram of the TTS audio stream. Figure 5 The comparison shows that the processed signal has more concentrated energy in key frequency components, a more reasonable dynamic range, and suppressed background noise, after frequency domain predistortion compensation and dynamic range compression. This verifies that the gain correction coefficient of the multimodal signal transmission link also plays an important role in the local broadcasting process, ensuring that the alarm voice is clearly identifiable even in noisy warehouse environments.

[0070] Step 6, Automatic emergency call linkage after voice broadcast: Upon detecting that the speaker buffer is cleared and the broadcast has reached the preset duration, the voice broadcast is deemed complete. The system then parses the linkage identifier in the broadcast content data frame, which triggers the session control layer of the wireless communication module. This identifier matches the emergency communication routing strategy, constructing a telephone call request. The request is sent via the 4G network, and upon receiving a successful link establishment status code from the operator, the communication link is deemed established. The system then retrieves the standardized alarm voice code, performs channel coding, interleaving, and modulation, and pushes it as the alarm voice information to the security duty room telephone. When the duty officer answers, the system plays the voice information.

[0071] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A wireless communication-based linkage method for alarm event reporting and remote response, characterized in that, The method includes: Step 1: Collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; convert the processed data into a unified alarm trigger event. Step 2: Perform multi-source feature analysis on the alarm triggering event to obtain the event analysis results; extract the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point based on the event analysis results, introduce the attenuation characteristics of intermolecular van der Waals forces to map the signal field, and construct a three-dimensional spatial situation fitting ellipsoid. Step 3: Perform topological meshing and multi-physics coupled numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; based on the event analysis results and the multi-mode signal transmission link gain correction coefficient, obtain the audible and visual alarm driving command, and simultaneously extract the location and time information in the event, and encapsulate it to obtain the alarm event data packet; Step 4: Based on the location information in the alarm event data packet, and combined with the multimodal signal transmission link gain correction coefficient, perform dynamic weight matching on the pre-stored voice text template to obtain the target TTS voice broadcast content. Step 5: Convert the TTS voice broadcast content into a voice alarm signal and broadcast it through a speaker; Step 6: After the voice broadcast is completed, a call request is automatically generated based on the linkage identifier in the broadcast content, and an alarm voice message is played after the call is connected.

2. The alarm event reporting and remote response linkage method based on wireless communication according to claim 1, characterized in that, Step 1 includes: The acoustic pressure fluctuation time sequence output by the acoustic resonant cavity, the three-axis acceleration and angular velocity vector sequence output by the bottom inertial reference plane, and the external electromagnetic field distortion amplitude-frequency sequence induced by the lateral electromagnetic shield are simultaneously acquired. The three types of time signals are spliced ​​together according to the sampling clock and combined to obtain the original sensing data. The raw sensor data is mapped to a preset multi-degree-of-freedom rigid body kinematic state space to construct a six-dimensional state variable matrix containing translational and rotational motion components. Based on the six-dimensional state variable matrix, the kinematic differential equations are substituted, and the translational motion components and rotational motion components are decoupled by the orthogonal projection operator to obtain the decoupled independent motion state vectors. By performing time-domain registration on independent motion state vectors, the phase shift caused by the hardware sampling clock deviation of each three-dimensional spatial state perception anchor point is compensated, and a phase-synchronized data stream is obtained. The phase-synchronized data stream is the processed data. The processed data undergoes sliding window variance evolution calculation and dynamic threshold determination. When the data stream amplitude continuously exceeds the preset safety boundary, a state transition mechanism is triggered, and the transition state identifier is normalized and mapped to a unified alarm trigger event.

3. The alarm event reporting and remote response linkage method based on wireless communication according to claim 2, characterized in that, Step 2: Perform multi-source feature analysis on the alarm triggering event to obtain the event analysis results; extract the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state sensing anchor point based on the event analysis results, introduce the attenuation characteristics of intermolecular van der Waals forces to map the signal field, and construct a three-dimensional spatial situation fitting ellipsoid, including: For a unified alarm triggering event, joint time-frequency domain feature extraction is performed to separate the frequency domain energy spectrum features and the time domain envelope abrupt change features. Tensor fusion is then used to obtain the event analysis results. Based on the event analysis results, the real-time displacement deviation of each three-dimensional spatial state sensing anchor point is calculated by inverse kinematics solver to obtain spatial vector coordinates. The surface micro-element deformation rate under force at each anchor point is calculated according to the constitutive relation of continuous medium mechanics to construct dynamic stress distribution gradient. The spatial vector coordinates and dynamic stress distribution gradient are substituted into the field mapping function. The field mapping function introduces the distance power-law attenuation characteristics of the intermolecular van der Waals potential energy function to characterize the energy dissipation and phase hysteresis of sound waves and electromagnetic waves in the propagation medium. The equivalent interaction potential weight matrix between each spatial node is calculated to complete the mapping of the signal field. Using spatial vector coordinates as geometric control points and the equivalent interaction potential weight matrix as spatial topological constraints, a three-dimensional spatial situation fitting ellipsoid is obtained by optimizing the boundary envelope of discrete situation data points within the alarm radiation influence domain.

4. The alarm event reporting and remote response linkage method based on wireless communication according to claim 3, characterized in that, Step 3 includes: Using the geometric surface of the ellipsoid fitted to the three-dimensional spatial situation as the computational boundary, the continuous computational domain is discretized into a hybrid topological mesh containing acoustic propagation nodes, electromagnetic radiation nodes, and stress transmission nodes, resulting in a discrete mesh set. Based on a discrete mesh set, the multiphysics coupling solution operator is invoked to jointly iteratively solve the sound pressure attenuation gradient of the acoustic propagation node, the multipath interference intensity of the electromagnetic radiation node, and the vibration energy dissipation of the stress transmission node, so as to obtain the field coupling response matrix. The field coupling response matrix is ​​input into the link compensation calculation unit, and inverse differential operation is performed in combination with the preset wireless communication channel reference attenuation spectrum to extract the quantization parameters for compensating the transmission loss of each mode signal, and obtain the multi-mode signal transmission link gain correction coefficient. The event analysis results are logically mapped to the multimodal signal transmission link gain correction coefficient to obtain the mapping result; the preset sound and light control protocol stack is matched according to the mapping result to obtain the sound and light alarm drive command. The location and time information carried in the event parsing results are extracted synchronously. The audible and visual alarm drive command, location information, time information, and multimodal signal transmission link gain correction coefficient are binary serialized and encapsulated with protocol frames to obtain the alarm event data packet.

5. The alarm event reporting and remote response linkage method based on wireless communication according to claim 4, characterized in that, Step 4: Based on the location information in the alarm event data packet, and combined with the multimodal signal transmission link gain correction coefficient, perform dynamic weight matching on the pre-stored voice text template to obtain the target TTS voice broadcast content, including: The alarm event data packet is parsed to extract location information and multimodal signal transmission link gain correction coefficient, and the location information is converted into a spatial distance attenuation factor. Retrieve the local template repository, retrieve at least two pre-stored speech-text templates associated with the geographic grid to which the location information belongs, and extract acoustic prosodic features and semantic key segments from each template; A dynamic weight allocation vector is constructed by performing a matrix product operation between the spatial distance attenuation factor and the multimodal signal transmission link gain correction coefficient. Based on the dynamic weight allocation vector, the acoustic prosodic features and semantic key segments of at least two pre-stored speech text templates are weighted and fused to obtain the fusion score ranking; the final matching sequence is selected according to the fusion score ranking to obtain the target TTS speech broadcast content.

6. The alarm event reporting and remote response linkage method based on wireless communication according to claim 5, characterized in that, Step 5: Convert the TTS voice broadcast content into a voice alarm signal and broadcast it through a speaker, including: Receive the target TTS voice broadcast content, perform a nonlinear mapping operation from phoneme sequence to acoustic parameters, extract the fundamental frequency trajectory, formant frequency and duration envelope parameters, and obtain the initial digital audio stream; The gain correction coefficient of the multimodal signal transmission link is called to perform frequency domain predistortion compensation and dynamic range compression processing on the initial digital audio stream, suppress the masking effect of speaker nonlinear harmonic distortion and environmental background noise, and obtain the channel-adapted digital audio signal. The channel-adapted digital audio signal is input to the digital-to-analog converter unit, and after anti-aliasing low-pass filtering and Class D power amplification, an analog electric drive signal with impedance characteristics strictly matched to the speaker voice coil is obtained. The analog electric drive signal is the voice alarm signal. The voice alarm signal is loaded onto the diaphragm driver of the speaker, and the sound-electric-mechanical-sound energy conversion link is controlled to perform sound pressure radiation, thus completing the physical broadcast of the voice alarm signal in the external space of the device.

7. The alarm event reporting and remote response linkage method based on wireless communication according to claim 6, characterized in that, Step 6: After the voice broadcast is completed, based on the linkage identifier in the broadcast content, automatically generate a call request, and play alarm voice information after the call is connected, including: Monitor the audio playback buffer status of the speaker. When the buffer data is cleared and the playback duration reaches a preset threshold, the voice playback is determined to be complete. Simultaneously parse the data frame control field of the playback content and extract the embedded linkage identifier. The linkage identifier is input into the session control layer of the wireless communication baseband processor, which matches the preset emergency communication routing policy and the target terminal addressing protocol to construct a telephone dialing request that includes session initiation instructions, identity authentication tokens and media negotiation parameters. The wireless radio frequency front-end sends the call request to the operator's core network side, listens for and parses the link establishment status code in the downlink signaling feedback, and determines that the communication link is connected when the status code indicates that the two-way voice channel handshake is successful. After the communication link is established, the standardized alarm voice coding sequence associated with the alarm triggering event is retrieved, and channel coding, interleaving and orthogonal frequency division multiplexing modulation mapping are performed to obtain the wireless transmission baseband stream, which is then pushed to the remote terminal in real time as alarm voice information. The system listens for the media stream reception confirmation signal returned by the remote terminal. When the confirmation signal indicates that the alarm voice information has been fully delivered and the decoding verification has passed, the media stream transmission is terminated and the communication channel resources occupied by the telephone dialing request are released.

8. A wireless communication-based alarm event reporting and remote response linkage system, wherein the system implements the method as described in any one of claims 1 to 7, characterized in that, include: The acquisition module is used to collect raw sensor data at the three-dimensional spatial state sensing anchor points deployed on the top of the equipment housing, the bottom inertial reference plane, and the side electromagnetic shield; to perform trajectory decoupling and phase synchronization processing on the raw sensor data to obtain processed data; and to convert the processed data into a unified alarm trigger event. The analysis module is used to perform multi-source feature analysis on alarm trigger events to obtain event analysis results; based on the event analysis results, the spatial vector coordinates and dynamic stress distribution gradient of the three-dimensional spatial state perception anchor point are extracted, and the attenuation characteristics of intermolecular van der Waals forces are introduced to map the signal field and construct a three-dimensional spatial situation fitting ellipsoid. The calculation module is used to perform topological meshing and multi-physics coupling numerical simulation on the three-dimensional spatial situation fitting ellipsoid to obtain the multi-mode signal transmission link gain correction coefficient; Based on the event analysis results and the multimodal signal transmission link gain correction coefficient, the audible and visual alarm driving command is obtained. At the same time, the location information and time information in the event are extracted and encapsulated to obtain the alarm event data packet. The matching module is used to perform dynamic weight matching on the pre-stored voice text template based on the location information in the alarm event data packet and the multimodal signal transmission link gain correction coefficient to obtain the target TTS voice broadcast content. The conversion module is used to convert TTS voice broadcast content into voice alarm signals and broadcast them through a speaker. The processing module is used to automatically generate a call request based on the linkage identifier in the broadcast content after the voice broadcast is completed, and play the alarm voice information after the call is connected.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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