A smart space device data transmission bus arrangement method and device

Abstract

The application discloses a kind of wisdom space equipment data transmission bus arrangement method and equipment, it is related to wisdom space wireless communication technical field, including setting target function calculation equipment position, wisdom space is divided into three-dimensional grid, for each grid allocation index, equipment coordinate is mapped to grid index, calculate grid occupancy probability, generate path occupancy flag;Directly calculate the number of sound window samples and reverberation window samples, divide direct sound energy by reverberation sound energy, calculate linear DRR, calculate the mean square vibration energy of equipment, combine path occupancy probability and average vibration energy, calculate vibration coupling energy, based on received signal strength, convert into linear power and linear signal-to-noise ratio.The application improves the accuracy of effective bandwidth estimation by fast fourier transform combined with power delay spectrum calculation, and improves the rationality of link screening by path occupancy probability combined with DRR utilization factor.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology in smart space, and in particular to a method and device for arranging a data transmission bus for smart space equipment. Background Technology

[0002] With the rapid development of smart spaces, smart buildings, and IoT technologies, efficient and stable data transmission between devices has become an important foundation for realizing intelligent sensing and collaborative control. Ultra-wideband, radio frequency (RF), acoustic signal processing, and multi-source sensor fusion technologies have been widely used in indoor positioning, device interconnection, and environmental sensing. Researchers have proposed a gridded spatial partitioning method, which uses a three-dimensional grid index to map and plan the paths of devices within the smart space, thereby providing a reference for the management of data transmission paths.

[0003] Existing technologies have the following shortcomings in smart space data transmission: most methods fail to combine spatial modeling and path occupancy characteristics to dynamically evaluate link transmission quality, lack accurate characterization of the three-dimensional spatial environment and obstacle distribution, and single-signal dimension indicators (such as radio frequency power or acoustic energy ratio) are difficult to resist multi-source interference in complex environments, resulting in insufficiently refined link selection, which can easily lead to reduced throughput or data packet loss. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method and device for arranging a data transmission bus in a smart space device, which solves the problems of most methods failing to combine spatial modeling and path occupancy characteristics to dynamically evaluate link transmission quality, lacking accurate characterization of the three-dimensional spatial environment and obstacle distribution, and the inability of single signal dimension indicators (such as radio frequency power or acoustic energy ratio) to resist multi-source interference in complex environments, resulting in insufficiently refined link selection and easy to cause reduced throughput or data packet loss.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a method for arranging a data transmission bus for intelligent space devices, comprising,

[0008] Collect and preprocess device data, set an objective function to calculate device location, divide the smart space into a three-dimensional grid, assign an index to each grid, map device coordinates to grid indices, calculate grid occupancy probability, and generate path occupancy flags.

[0009] The number of direct sound window samples and the number of reverberation window samples are calculated separately. The direct sound energy is divided by the reverberation sound energy to calculate the linear DRR. The mean square vibration energy of the device is calculated. The vibration coupling energy is calculated by combining the path occupancy probability and the average vibration energy. Based on the received signal strength, it is converted into linear power and linear signal-to-noise ratio.

[0010] The radio frequency signal is subjected to a fast Fourier transform to calculate the effective bandwidth. Combining the linear signal-to-noise ratio and the effective bandwidth, the theoretical maximum throughput is calculated to generate the comprehensive link quality. Device pairs are then filtered to generate a set of effective links. The number of data packets allocated to each link is calculated, and the data packets are encapsulated to generate formatted data packets for transmission and reception.

[0011] As a preferred embodiment of the intelligent space device data transmission bus layout method of the present invention, the step of mapping device coordinates to grid index, calculating grid occupancy probability, and generating path occupancy flag includes:

[0012] Based on UWB pulse signals, the distance between devices is calculated. The objective function is set through a multidimensional scaling analysis algorithm and solved using gradient descent to obtain the device positions.

[0013] The three-dimensional extent of the smart space is obtained based on the device location and divided into a three-dimensional grid. An index is assigned to each grid cell, the occupied grid matrix is ​​initialized, and all grid cells are marked as "free".

[0014] The device coordinates are mapped to the grid index, and the grid sequence is generated using the Bressenham 3D line algorithm;

[0015] For each cell in the path grid sequence, calculate the center coordinates and obtain the obstacle coordinates from the architectural design drawings. If the center coordinates are within the range of the obstacle coordinates, mark the cell as "occupied".

[0016] Based on point cloud data, the cell occupancy probability is calculated, the cell occupancy probabilities are accumulated, the path occupancy probability is generated, a probability threshold is set using statistical analysis, and cells with probability indices greater than the probability threshold are marked as "occupied" and otherwise marked as "idle", thus generating a path occupancy flag.

[0017] As a preferred embodiment of the data transmission bus arrangement method for intelligent space devices described in this invention, the step of calculating the number of direct sound window samples and the number of reverberation window samples respectively, dividing the direct sound energy by the reverberation sound energy, and calculating the linear DRR includes:

[0018] The time average value of the acoustic signal is calculated as a reference signal, and an acoustic impulse response is generated by cross-correlation between the acoustic signal and the reference signal.

[0019] The direct sound window and the reverberation window are defined using the fixed time window division method, and the number of samples in the direct sound window and the number of samples in the reverberation window are calculated respectively.

[0020] Based on acoustic impulse response, direct sound window, and reverberation window, the energy of direct sound and reverberation sound is calculated respectively.

[0021] Calculate the linear DRR by dividing the direct sound energy by the reverberant sound energy.

[0022] As a preferred embodiment of the data transmission bus arrangement method for intelligent space devices described in this invention, the step of calculating vibration coupling energy by combining path occupancy probability and average vibration energy, and converting it into linear power and linear signal-to-noise ratio based on received signal strength, includes:

[0023] Based on triaxial acceleration data, the mean square vibration energy of the equipment is calculated, and the average vibration energy is generated.

[0024] The vibration coupling energy is calculated by combining the path occupancy probability and the average vibration energy.

[0025] Based on the received power, the received signal strength is calculated and smoothed by mean. Based on the received signal strength, it is converted into linear power and normalized. Based on the received signal strength after mean smoothing, the signal-to-noise ratio is calculated and converted into linear signal-to-noise ratio.

[0026] As a preferred embodiment of the data transmission bus arrangement method for intelligent space devices described in this invention, the step of performing a fast Fourier transform on the radio frequency signal, calculating the effective bandwidth, and combining the linear signal-to-noise ratio and the effective bandwidth to calculate the theoretical maximum throughput includes:

[0027] Perform a Fast Fourier Transform on the radio frequency signal to calculate the channel impulse response. Based on the channel impulse response, calculate the power delay spectrum. Calculate the autocorrelation function of the power delay spectrum. Calculate the coherence bandwidth based on the delay of the first drop of the autocorrelation function. Calculate the effective bandwidth based on the coherence bandwidth.

[0028] Calculate the theoretical maximum throughput by combining the linear signal-to-noise ratio and the effective bandwidth;

[0029] Calculate the DRR utilization factor based on linear DRR.

[0030] As a preferred embodiment of the data transmission bus layout method for intelligent space devices described in this invention, the step of generating a set of valid links, calculating the number of data packets allocated to each link, encapsulating the data packets, generating formatted data packets, and transmitting and receiving them includes:

[0031] The overall link quality is calculated by combining the normalized linear power, vibration coupling energy, path occupancy probability, theoretical maximum throughput, and DRR utilization factor.

[0032] Based on comprehensive link quality, path occupancy flag, and received signal strength, each pair of devices (i,j) is filtered to generate a set of valid links;

[0033] Extract the overall link quality of effective links, calculate the normalized link quality, and convert it into a priority score for effective links;

[0034] Sort the links in descending order of priority score, select the top M links with the highest priority, calculate the number of data packets allocated to each link, add a timestamp to each data packet, encapsulate the data packets, and generate formatted data packets;

[0035] The formatted data packets are transmitted using the IEEE 802.11 transport protocol, and the receiving end receives the transmitted formatted data packets.

[0036] As a preferred embodiment of the intelligent space device data transmission bus layout method of the present invention, the step of collecting device data and performing preprocessing includes:

[0037] Collect device data and perform time synchronization, noise reduction, and normalization processing;

[0038] The device data includes device coordinates, UWB pulse signals, received power, acoustic signals, radio frequency signals, and triaxial acceleration data.

[0039] Secondly, the present invention provides a data transmission bus arrangement device for intelligent space equipment, comprising,

[0040] The data preprocessing module is used to acquire and preprocess data from multiple sources.

[0041] The grid path module is used to divide the smart space into a three-dimensional grid, realize the mapping of device coordinates to the grid, track the path between devices, and generate path occupancy markers by combining building obstacles and point cloud data.

[0042] The energy analysis module is used to calculate the ratio of linear direct sound to reverberation, and combined with triaxial acceleration data and path occupancy probability, to derive the theoretical maximum throughput.

[0043] The quality selection module is used to calculate the overall link quality and filter valid links, allocate the number of data packets according to the link priority, perform encapsulation and transmission.

[0044] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the intelligent space device data transmission bus arrangement method as described in the first aspect of the present invention.

[0045] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the intelligent space device data transmission bus arrangement method as described in the first aspect of the present invention.

[0046] The beneficial effects of this invention are as follows: by combining fast Fourier transform with power delay spectrum calculation, the invention improves the accuracy of effective bandwidth estimation; by combining path occupancy probability with DRR utilization factor, the invention improves the rationality of link selection; and by combining vibration energy with path probability, the invention enhances the consideration of structural characteristics in link modeling. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart of a data transmission bus arrangement method for a smart space device in Example 1.

[0049] Figure 2 This is a schematic diagram of a data transmission bus layout device for a smart space device in Example 1. Detailed Implementation

[0050] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0051] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0053] Example 1, referring to Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for arranging a data transmission bus for a smart space device, including the following steps:

[0054] S1. Collect and preprocess device data, set the objective function to calculate device location, divide the smart space into a three-dimensional grid, assign an index to each grid, map device coordinates to grid indexes, calculate grid occupancy probability, and generate path occupancy flags.

[0055] Specifically, collecting and preprocessing device data includes:

[0056] Collect device data and perform time synchronization, noise reduction, and normalization processing;

[0057] The device data includes device coordinates, UWB pulse signals, received power, acoustic signals, radio frequency signals, and triaxial acceleration data.

[0058] Time synchronization ensures that multi-source data are processed under the same time reference, avoiding calculation errors caused by time delay differences; denoising effectively suppresses the impact of environmental noise and measurement jitter on signal quality, improving data robustness; normalization puts data of different dimensions and scales in a unified calculation range, avoiding objective function deviation caused by numerical imbalance.

[0059] Furthermore, the device coordinates are mapped to the grid index, the grid occupancy probability is calculated, and a path occupancy flag is generated, including:

[0060] The distance between devices is calculated based on UWB pulse signals using the following formula:

[0061] ,

[0062] in Let c be the distance between devices i and j, where i and j are device identifiers, and c is the speed of light. Round trip time, Processing delay time for the equipment;

[0063] The objective function is defined using a multidimensional scaling analysis algorithm, and the formula is as follows:

[0064] ,

[0065] Where J is the value of the MDS objective function. , as well as Let i be the coordinates of device i. , as well as Let j be the coordinates of device j.

[0066] The device location is obtained by using gradient descent.

[0067] The three-dimensional extent of the smart space is obtained based on the device location and divided into a three-dimensional grid. Each grid cell is assigned an index (k, l, m), as follows:

[0068] ,

[0069] ,

[0070] ,

[0071] Where k is the grid index along the x-axis, representing the position of the k-th cell in the x-direction. , where l is the grid index along the y-axis, representing the position of the l-th cell in the y-direction. , where m is the grid index along the z-axis, representing the position of the m-th cell in the z-direction. , , as well as These represent the number of grid cells along the x, y, and z axes, respectively. For grid size, , , , , as well as This represents the spatial boundary.

[0072] Initialize the occupied grid matrix and mark all cells as "free" (0 represents free, 1 represents occupied);

[0073] Mapping device coordinates to the grid index is done using the following formula:

[0074] ,

[0075] ,

[0076] in and These are the grid indices for devices i and j, respectively;

[0077] Using Brexenham's 3D line algorithm, from arrive Track the path and generate a grid sequence;

[0078] For each cell in the path grid sequence, calculate the center coordinates using the following formula:

[0079] ,

[0080] in Let x, y, and z be the coordinates of the center of the grid. This is the lattice center offset factor;

[0081] Obtain obstacle coordinates from architectural design drawings. If the center coordinates are within the obstacle coordinate range, mark the grid as "occupied".

[0082] Based on point cloud data, the probability of cell occupancy is calculated using the following formula:

[0083] ,

[0084] in The probability of a cell being occupied. This represents the number of point clouds within a grid. The maximum point cloud density threshold is set using statistical analysis.

[0085] The formula for summing the cell occupancy probability and generating the path occupancy probability is:

[0086] ,

[0087] in The sum of path occupancy probabilities, Let (i,j) be the sequence of lattice cells traversed by the path pair (i,j).

[0088] Using statistical analysis to set a probability threshold, the grid corresponding to the probability index that is greater than the probability threshold is marked as "occupied", otherwise it is marked as "free", thus generating a path occupancy flag.

[0089] UWB signals possess wide bandwidth and high latency resolution, enabling centimeter-level positioning accuracy in complex indoor environments. The MDS method, even in unknown coordinate systems, reconstructs the global coordinate layout of devices solely based on relative distance information, and gradient descent ensures convergence and stability during computation. This method avoids the cumulative amplification effect of single-point errors on overall positioning. Three-dimensional meshing discretizes continuous space, facilitating computational modeling of complex spaces. Index mapping allows for rapid positioning of any device or path's spatial location, significantly improving data processing efficiency. The Bressenham algorithm is a highly efficient integer arithmetic algorithm capable of quickly... The system rapidly generates the grid sequence traversed by a 3D straight path, avoiding the precision loss caused by floating-point operations. Architectural drawings provide static structural information, while point cloud data reflects dynamic scene characteristics. Combining the two enables high-precision modeling of spatial obstacles. The center coordinate matching method ensures the geometric accuracy of obstacle determination. Unlike binary occupancy, probabilistic modeling reflects uncertainty and environmental dynamism, improving the accuracy of describing space usage. The accumulation of path occupancy probabilities not only reflects the state of individual grid points but also the overall availability of the path. By setting a threshold, the system can quickly distinguish between "available" and "unavailable" paths, ensuring the reliability of data transmission.

[0090] S2. Calculate the number of direct sound window samples and the number of reverberation window samples respectively. Divide the direct sound energy by the reverberation sound energy to calculate the linear DRR. Calculate the mean square vibration energy of the device. Combine the path occupancy probability and the average vibration energy to calculate the vibration coupling energy. Based on the received signal strength, convert it into linear power and linear signal-to-noise ratio.

[0091] Specifically, the number of direct sound window samples and the number of reverberation window samples are calculated separately. The direct sound energy is divided by the reverberation sound energy to calculate the linear DRR, including:

[0092] The time-average value of the acoustic signal is calculated as a reference signal. The acoustic impulse response is generated through the cross-correlation between the acoustic signal and the reference signal, using the following formula:

[0093] ,

[0094] in Acoustic impulse response, For the received acoustic signal, For the reference acoustic signal, n and b are discrete-time indices. The length of the acoustic signal sequence;

[0095] The direct arrival time is calculated based on the distance between devices, using the following formula:

[0096] ,

[0097] in Direct arrival time;

[0098] The direct arrival time is converted into a sampling index using the following formula:

[0099] ,

[0100] in For the sampling index of direct sound arrival, For acoustic sampling rate, This is a rounding function;

[0101] Using a fixed-time-window method, direct sound window and reverberation window are defined separately. The number of samples for the direct sound window and the reverberation window are calculated separately using the following formulas:

[0102] ,

[0103] ,

[0104] in and These represent the number of samples in the direct sound window and the number of samples in the reverberation window, respectively. and These are the direct sound window duration and the reverberation window duration, respectively;

[0105] Based on the acoustic impulse response, direct sound window, and reverberation window, the energy of direct sound and reverberation sound is calculated separately using the following formula:

[0106] ,

[0107] ,

[0108] ,

[0109] in and These are the energies of direct sound and reverberant sound, respectively. This is the starting index of the reverb window. For direct sound arrival time, This is the starting offset time of the reverberation window;

[0110] Calculate the linear DRR by dividing the direct sound energy by the reverberant sound energy.

[0111] Cross-correlation methods can extract the impulse response characteristics of a system from mixed signals in complex acoustic environments, thereby identifying direct sound and reverberant sound components. Through geometric models and sampling rate conversion, precise localization of acoustic signals can be achieved, ensuring the accuracy of direct sound and reverberant sound window division and avoiding window overlap or misalignment. The fixed window method is simple and efficient, ensuring comparability under different environmental conditions. Through energy integration, the distribution characteristics of acoustic energy over time can be intuitively reflected. Linear DRR avoids the nonlinear distortion caused by logarithmic calculations and is more conducive to subsequent coupling calculations with physical quantities such as vibration energy and power. As an acoustic intelligibility index, DRR can reflect the energy comparison relationship between direct sound and reverberant sound, thereby measuring the speech intelligibility and information fidelity of spatial transmission links.

[0112] Furthermore, combining the path occupancy probability and average vibration energy, the vibration coupling energy is calculated and converted into linear power and linear signal-to-noise ratio based on the received signal strength, including:

[0113] Based on triaxial acceleration data, the mean square vibration energy of the equipment is calculated using the following formula:

[0114] ,

[0115] in Let be the mean square vibrational energy of device i. The length of the acceleration sequence, , as well as The triaxial acceleration is the value of the nth sample.

[0116] And it generates average vibrational energy, the formula is:

[0117] ,

[0118] in Let (i,j) be the average vibration energy of the device. Let be the mean square vibrational energy of device j;

[0119] Combining path occupancy probability and average vibration energy, the vibration coupling energy is calculated using the following formula:

[0120] ,

[0121] in Vibrational coupling energy;

[0122] Based on the received power, the received signal strength is calculated and then smoothed by mean. The formula is as follows:

[0123] ,

[0124] in Let be the received signal strength from device i to j in the u-th measurement, where u is the sampling index. Let be the power received for the uth time. For reference power, The decibel conversion factor;

[0125] Based on the received signal strength, it is converted into linear power and then normalized. The formula is as follows:

[0126] ,

[0127] ,

[0128] in Let be the linear power measured in the u-th measurement. Logarithmic base For average linear power, For linear power variance, This is the normalized linear power;

[0129] Based on the received signal strength after mean smoothing, the signal-to-noise ratio (SNR) is calculated and converted to a linear SNR using the following formula:

[0130] ,

[0131] ,

[0132] in Let (i,j) be the signal-to-noise ratio of the device pair. The received signal strength after mean smoothing. For receiver noise, use spectrum analysis settings. Let be the linear signal-to-noise ratio of the device pair (i,j).

[0133] Three-axis acceleration can comprehensively characterize the motion characteristics of equipment in three-dimensional space, while the mean square energy index can smooth out the randomness of instantaneous vibrations and more accurately reflect the overall vibration level of the equipment. Compared with single-axis analysis, multi-dimensional calculation can improve the robustness of modeling, combining space occupancy probability with vibration characteristics, considering both transmission path obstruction and the dynamic stability of the equipment itself. Vibration coupling energy can reveal the decline trend of link quality under vibration environment, providing a quantitative indicator for communication robustness optimization in complex scenarios. Value smoothing can effectively suppress the impact of short-term interference and random noise on received strength, thus more realistically reflecting the long-term trend of communication link. This processing method improves the stability of signal strength estimation, and linearization processing facilitates unified modeling with physical quantities such as acoustic energy and vibration energy, avoiding deviations caused by inconsistencies in dimensions. Signal-to-noise ratio, as an important indicator of communication quality, can intuitively reflect the reliability of the link under noise interference. Using linear signal-to-noise ratio form can facilitate comprehensive modeling with DRR and vibration coupling energy, supporting unified optimization of multi-physical domain data.

[0134] S3. Perform a Fast Fourier Transform on the RF signal to calculate the effective bandwidth. Combining the linear signal-to-noise ratio and the effective bandwidth, calculate the theoretical maximum throughput, generate the overall link quality, filter the device pairs, generate a set of effective links, calculate the number of data packets allocated to each link, encapsulate the data packets, generate formatted data packets, and perform transmission and reception.

[0135] Specifically, the radio frequency signal undergoes a Fast Fourier Transform (FFT) to calculate the effective bandwidth. Combining the linear signal-to-noise ratio (SNR) and effective bandwidth, the theoretical maximum throughput is calculated, including:

[0136] Perform a Fast Fourier Transform on the radio frequency signal to calculate the channel impulse response, using the following formula:

[0137] ,

[0138] in For channel impulse response, The received radio frequency signal sequence, For the reference RF signal sequence, FFT and IFFT are the Fast Fourier Transform and Inverse Fourier Transform, respectively, and q is the discrete-time index;

[0139] Based on the channel impulse response, the power delay spectrum is calculated using the following formula:

[0140] ,

[0141] in Power delay spectrum;

[0142] The autocorrelation function for calculating the power delay spectrum is given by the following formula:

[0143] ,

[0144] in Let be the autocorrelation function of the power delay spectrum. The number of sampling points for the discrete-time series. For lazy indexing;

[0145] The coherence bandwidth is calculated by taking the delay of the first decrease in the autocorrelation function, using the following formula:

[0146] ,

[0147] ,

[0148] in For coherent bandwidth, For coherent time, For the delayed index of the first descent, This refers to the radio frequency sampling rate;

[0149] Based on the coherence bandwidth, the effective bandwidth is calculated using the following formula:

[0150] ,

[0151] in For effective bandwidth, For system bandwidth;

[0152] Combining linear signal-to-noise ratio and effective bandwidth, the theoretical maximum throughput is calculated using the following formula:

[0153] ,

[0154] in This represents the theoretical maximum throughput.

[0155] Based on linear DRR, the DRR utilization factor is calculated using the following formula:

[0156] ,

[0157] in Let (i,j) be the DRR utilization factor of the device. Let (i,j) be the linear DRR of the device pair (i,j).

[0158] Channel impulse response (DIR) reflects the fading characteristics and multipath effects of a wireless channel in the time domain, providing data support for subsequent calculations of the power delay spectrum. By calculating the autocorrelation function of the power delay spectrum, channel correlation characteristics can be obtained, thereby evaluating the frequency-selective fading characteristics of the signal. The size of the coherent bandwidth determines whether a single modulation scheme can be used for efficient transmission within a certain bandwidth. If the bandwidth is greater than the coherent bandwidth, multi-carrier modulation must be introduced to avoid the performance loss caused by frequency-selective fading and to avoid some frequency subbands that are severely interfered with or deeply fading, thereby improving the effective throughput of the system. This invention uses an extended form of the Shannon formula to calculate the theoretical maximum throughput. The theoretical maximum throughput can provide a performance upper limit reference for the system and is an important indicator for link optimization. It can quantitatively compare the transmission capabilities between different devices, providing an accurate decision basis for subsequent data packet allocation and link selection. DRR reflects the difference in data transmission rate capabilities between different devices, while the DRR utilization factor measures the actual degree of performance of this capability under the current channel conditions.

[0159] Furthermore, a set of valid links is generated, the number of data packets allocated to each link is calculated, and the data packets are encapsulated to generate formatted data packets, which are then transmitted and received, including:

[0160] The overall link quality is calculated by combining the normalized linear power, vibration coupling energy, path occupancy probability, theoretical maximum throughput, and DRR utilization factor, using the following formula:

[0161] ,

[0162] in To improve overall link quality;

[0163] Based on comprehensive link quality, path occupancy flag, and received signal strength, each pair of devices (i,j) is filtered using the following formula:

[0164] ,

[0165] in This serves as a flag indicating the validity of the link between device pair (i,j). This is a path occupancy flag for device pair (i,j);

[0166] Generate a set of valid links ;

[0167] in A set of valid links;

[0168] Extract the overall link quality of effective links and calculate the normalized link quality using the following formula:

[0169] ,

[0170] in To normalize link quality, For the overall link quality of an effective link, The maximum link quality among the effective links;

[0171] The priority score is converted to an effective link using the following formula:

[0172] ,

[0173] in The priority score for valid links. The maximum distance in the effective link;

[0174] Sort the links in descending order of priority score, select the top M links with the highest priority, calculate the number of data packets allocated to each link, add a timestamp to each data packet, and encapsulate the data packets to generate formatted data packets. The formula is:

[0175] ,

[0176] ,

[0177] in The total number of data packets. Where W is the fixed size of a single data packet, M is the size of the data to be transmitted, and M is the number of selected links. For the data packets assigned to the u-th link;

[0178] The formatted data packets are transmitted using the IEEE 802.11 transport protocol, and the receiving end receives the transmitted formatted data packets.

[0179] The selection process also incorporates path occupancy flags and received signal strength to avoid path conflicts and resource waste. Priority scores are not only related to link quality but also incorporate a link distance factor, thus balancing link coverage and transmission reliability. The allocation share for each link is calculated using the total number of data packets and the link priority score. Each data packet is timestamped before encapsulation to ensure that packets can be reassembled in order at the receiving end, avoiding out-of-order issues. This provides a basis for subsequent error detection and link delay analysis, enhancing the synchronization and stability of data in multi-link parallel transmission. Combined with the data allocation and link optimization mechanism of this invention, throughput and anti-interference capabilities are significantly improved while ensuring protocol standardization. New parameters such as vibration coupling energy and path occupancy probability are introduced, making link quality assessment more closely aligned with complex application scenarios. Based on traditional throughput calculation, dynamic optimization of resource allocation is achieved by combining DRR utilization factors and link priority scores. Data packet timestamps and formatted encapsulation improve the reliability and controllability of multi-link parallel transmission.

[0180] This embodiment also provides a smart space device data transmission bus deployment device, including:

[0181] The data preprocessing module is used to acquire and preprocess data from multiple sources.

[0182] The grid path module is used to divide the smart space into a three-dimensional grid, realize the mapping of device coordinates to the grid, track the path between devices, and generate path occupancy markers by combining building obstacles and point cloud data.

[0183] The energy analysis module is used to calculate the ratio of linear direct sound to reverberation, and combined with triaxial acceleration data and path occupancy probability, to derive the theoretical maximum throughput.

[0184] The quality selection module is used to calculate the overall link quality and filter valid links, allocate the number of data packets according to the link priority, perform encapsulation and transmission.

[0185] This embodiment also provides a computer device applicable to the data transmission bus arrangement method for smart space devices, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the data transmission bus arrangement method for smart space devices as proposed in the above embodiment.

[0186] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0187] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the data transmission bus arrangement method for intelligent space devices as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0188] In summary, the present invention improves the accuracy of effective bandwidth estimation by combining fast Fourier transform with power delay spectrum calculation, enhances the rationality of link selection by combining path occupancy probability with DRR utilization factor, and strengthens the consideration of structural characteristics in link modeling by combining vibration energy with path probability.

[0189] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for arranging a data transmission bus for intelligent space devices, characterized in that: include, Collect and preprocess device data, set an objective function to calculate device location, divide the smart space into a three-dimensional grid, assign an index to each grid, map device coordinates to grid indices, calculate grid occupancy probability, and generate path occupancy flags. The number of direct sound window samples and the number of reverberation window samples are calculated separately. The direct sound energy is divided by the reverberation sound energy to calculate the linear DRR. The mean square vibration energy of the device is calculated. The vibration coupling energy is calculated by combining the path occupancy probability and the average vibration energy. Based on the received signal strength, it is converted into linear power and linear signal-to-noise ratio. The radio frequency signal is subjected to a fast Fourier transform to calculate the effective bandwidth. Combining the linear signal-to-noise ratio and the effective bandwidth, the theoretical maximum throughput is calculated to generate the comprehensive link quality. The device pairs are then filtered to generate a set of effective links. The number of data packets allocated to each link is calculated, and the data packets are encapsulated to generate formatted data packets for transmission and reception. The calculation of the number of direct sound window samples and the number of reverberation window samples, dividing the direct sound energy by the reverberation sound energy, and calculating the linear DRR includes: The time average value of the acoustic signal is calculated as a reference signal, and an acoustic impulse response is generated by cross-correlation between the acoustic signal and the reference signal. The direct sound window and the reverberation window are defined using the fixed time window division method, and the number of samples in the direct sound window and the number of samples in the reverberation window are calculated respectively. Based on acoustic impulse response, direct sound window, and reverberation window, the energy of direct sound and reverberation sound is calculated respectively. Calculate the linear DRR by dividing the direct sound energy by the reverberant sound energy; The vibration coupling energy is calculated by combining the path occupancy probability and average vibration energy, and then converted into linear power and linear signal-to-noise ratio based on the received signal strength, including: Based on triaxial acceleration data, the mean square vibration energy of the equipment is calculated, and the average vibration energy is generated. The vibration coupling energy is calculated by combining the path occupancy probability and the average vibration energy. Based on the received power, the received signal strength is calculated and smoothed by mean. Based on the received signal strength, it is converted into linear power and normalized. Based on the received signal strength after mean smoothing, the signal-to-noise ratio is calculated and converted into linear signal-to-noise ratio.

2. The method for arranging a data transmission bus for intelligent space devices as described in claim 1, characterized in that: The step of mapping device coordinates to a grid index, calculating the grid occupancy probability, and generating a path occupancy flag includes: Based on UWB pulse signals, the distance between devices is calculated. The objective function is set through a multidimensional scaling analysis algorithm and solved using gradient descent to obtain the device positions. The three-dimensional extent of the smart space is obtained based on the device location and divided into a three-dimensional grid. An index is assigned to each grid cell, the occupied grid matrix is ​​initialized, and all grid cells are marked as "free". The device coordinates are mapped to the grid index, and the grid sequence is generated using the Bressenham 3D line algorithm; For each cell in the path grid sequence, calculate the center coordinates and obtain the obstacle coordinates from the architectural design drawings. If the center coordinates are within the range of the obstacle coordinates, mark the cell as "occupied". Based on point cloud data, the cell occupancy probability is calculated, the cell occupancy probabilities are accumulated, the path occupancy probability is generated, a probability threshold is set using statistical analysis, and cells with probability indices greater than the probability threshold are marked as "occupied" and otherwise marked as "idle", thus generating a path occupancy flag.

3. The method for arranging the data transmission bus of intelligent space equipment as described in claim 2, characterized in that: The process of performing a Fast Fourier Transform on the radio frequency signal, calculating the effective bandwidth, and combining the linear signal-to-noise ratio and the effective bandwidth to calculate the theoretical maximum throughput includes: Perform a Fast Fourier Transform on the radio frequency signal to calculate the channel impulse response. Based on the channel impulse response, calculate the power delay spectrum. Calculate the autocorrelation function of the power delay spectrum. Calculate the coherence bandwidth based on the delay of the first drop of the autocorrelation function. Calculate the effective bandwidth based on the coherence bandwidth. Calculate the theoretical maximum throughput by combining the linear signal-to-noise ratio and the effective bandwidth; Calculate the DRR utilization factor based on linear DRR.

4. The method for arranging a data transmission bus for intelligent space equipment as described in claim 3, characterized in that: The process of generating a set of valid links, calculating the number of data packets allocated to each link, encapsulating the data packets, generating formatted data packets, and transmitting and receiving them includes: The overall link quality is calculated by combining the normalized linear power, vibration coupling energy, path occupancy probability, theoretical maximum throughput, and DRR utilization factor. Based on comprehensive link quality, path occupancy flag, and received signal strength, each pair of devices (i,j) is filtered to generate a set of valid links; Extract the overall link quality of effective links, calculate the normalized link quality, and convert it into a priority score for effective links; Sort the links in descending order of priority score, select the top M links with the highest priority, calculate the number of data packets allocated to each link, add a timestamp to each data packet, encapsulate the data packets, and generate formatted data packets; The formatted data packets are transmitted using the IEEE 802.11 transport protocol, and the receiving end receives the transmitted formatted data packets.

5. The method for arranging a data transmission bus for intelligent space equipment as described in claim 1, characterized in that: The collection and preprocessing of device data includes: Collect device data and perform time synchronization, noise reduction, and normalization processing; The device data includes device coordinates, UWB pulse signals, received power, acoustic signals, radio frequency signals, and triaxial acceleration data.

6. A data transmission bus arrangement device for intelligent space devices, based on the data transmission bus arrangement method for intelligent space devices according to any one of claims 1 to 5, characterized in that: include, The data preprocessing module is used to acquire and preprocess data from multiple sources. The grid path module is used to divide the smart space into a three-dimensional grid, realize the mapping of device coordinates to the grid, track the path between devices, and generate path occupancy markers by combining building obstacles and point cloud data. The energy analysis module is used to calculate the ratio of linear direct sound to reverberation, and combined with triaxial acceleration data and path occupancy probability, to derive the theoretical maximum throughput. The quality selection module is used to calculate the overall link quality and filter valid links, allocate the number of data packets according to the link priority, perform encapsulation and transmission.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the smart space device data transmission bus arrangement method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the data transmission bus arrangement method for intelligent space devices as described in any one of claims 1 to 5.

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